Publications (Google Scholar Profile)


Guest Editorials

  1. P.-E. Gaillardon, Ch. Papavassiliou, Th. Prodromakis, G. Ch. Sirakoulis, and Q Xia, “Special Section/Issue on the 1st International Conference on Memristive Materials, Devices & Systems,” IEEE Transactions on Nanotechnology, accepted for publication, under preparation.
  2. W. Spataro, G. A. Trunfio and G. Ch. Sirakoulis, “Parallel Computing in Modelling and Simulation,” Journal of Parallel and Distributed Computing, accepted for publication, under preparation.
  3. A. Adamaztky, G. Ch. Sirakoulis, and I. Vourkas, “Memristor Networks,” International Journal of Parallel, Emergent and Distributed Systems, accepted for publication, under preparation.
  4. W. Spataro, G. A. Trunfio and G. Ch. Sirakoulis, “High Performance Computing in Modelling and Simulation,” Concurrency and Computation: Practice and Experience, accepted for publication, under preparation.
  5. G. Ch. Sirakoulis, J. Wąs and G. Wainer, “Discrete Modelling and Simulation,” IEEE Computing in Science and Engineering, vol. 18, no. 4, pp. 8-10, August 2016.
  6. G. Ch. Sirakoulis and S. Hamdioui, “Editorial Note on Memristor Models, Circuits and Architectures,” International Journal of Unconventional Computing, vol. 12, no. 4, pp. 247-250, 2016.
  7. J. Wąs and G. Ch. Sirakoulis, “Special Issue on Simulation with Cellular Automata,” Simulation, vol. 92, no. 2, pp. 99-100, 2016.
  8. S. Bandini, G. Ch. Sirakoulis, and G. Vizzari, “Guests Editors’ Editorial Note on Special Issue of Advances in Cellular Automata Modeling,” ACM TOMACS, vol. 26, no. 3, article no. 17, Feb. 2016.
  9. J. Wąs and G. Ch. Sirakoulis, “Cellular Automata Applications for Research and Industry Journal of Computational Science, vol. 11, pp. 223-225, November 2015.
  10. G. Ch. Sirakoulis and J. Wąs and “Editorial Note on Cellular Automata in Theoretical Computer Science,” Journal of Cellular Automata, vol. 12, no. 1-2, pp. 1-5, 2017.
  11. W. Spataro, G. A. Trunfio and G. Ch. Sirakoulis, “Special Issue in High Performance Computing in Modelling and Simulations,” International Journal of High Performance and Applications, 2015, in press.
  12. G. Ch. Sirakoulis, and E. Lehtonen, “Special Issue on Computational Structures and Methods with Memristive Devices and Systems,” Microelectronics Journal, vol. 45, no. 11, 2014.
  13. G. Ch. Sirakoulis, and S. Bandini, “Special Issue of Cellular Automata Applications,Journal of Cellular Automata, vol. 9, no. 2-3, 2014.
  14. I. Georgoudas, S. Manzoni, K. Nishinari, A. Schadschneider, and G. Ch. Sirakoulis, “Special Issue of C&CA and TCA workshops of the ACRI 2012 Conference,” Journal of Cellular Automata, vol. 8, no. 5-6, 2013.

Referred Journal Papers

  1. A. Adamatzky, J. Vallverdu, and G. Ch. Sirakoulis, “Chemical excitable medium in Barcelona street t network as a method for panicked crowds behaviour analysis,” accepted for publication in Complex Systems.
  2. V. Ntinas, A. Ascoli, R. Tetzlaff, and G. Ch. Sirakoulis, “A complete analytical solution for the on and off dynamic equations of a TaO memristor, accepted for publication in IEEE Transactions on Circuits and Systems II.
  3. I. Gerakakis, P. Gavriilidis, N.I. Dourvas, I.G. Georgoudas, G.A. Trunfio, and G. Ch. Sirakoulis, “Accelerating Fuzzy Cellular Automata for Modeling Crowd Dynamics,” accepted for publication in Journal of Computational Science.
  4. M. Mitsopoulou, N. Dourvas, and G. Ch. Sirakoulis, K. Nishinari, “Spatial games and memory effects on crowd evacuation behavior with Cellular Automata,” accepted for publication in Journal of Computational Science.
  5. A. Adamatzky, N. Phillips, R. Weerasekera, M.A. Tsompanas, and G. Ch. Sirakoulis, “Street map analysis with excitable chemical medium,” in Physical Review E vol. 98, no.1, pp. 012306, 2018.
  6. V. Ntinas, I. Vourkas, A. Abusleme, G. Ch. Sirakoulis, A. Rubio, “Experimental Study of Artificial Neural Networks Using a Digital Memristor Simulator,” accepted for publication in IEEE Transactions on Neural Networks and Learning Systems.
  7. M.-A. Tsompanas, A. Adamatzky, I. Ieropoulos, N. Phillips, G. Ch. Sirakoulis, and J. Greenman, “Modelling Microbial Fuel Cells using lattice Boltzmann methods,” accepted for publication in IEEE/ACM Transactions on Computational Biology and Bioinformatics.
  8. A. Dimitriadis, M. Kutrib, and G. Ch. Sirakoulis, “Revisiting the cutting of the firing squad synchronization,” Natural Computing, vol. 17, no. 3, pp. 455-465, September 2018.
  9. I. Vourkas, D. Stathis, and G. Ch. Sirakoulis, “Massively Parallel Analog Computing: Ariadne’s Thread Was Made of Memristors,” IEEE Transactions on Emerging Topics in Computing, vol. 6, no. 1, pp. 145-155, Jan-March 2018.
  10. N. Dourvas and G. Ch. Sirakoulis, “A Inhibitor Sensitive, Collision Based Switching Like Transistor Element Using Periodic Traveling Waves and Cellular Automata,” International Journal of Unconventional Computing, vol. 13, no. 4-5, pp. 377-397, 2018.
  11. A. Adamatzky, S. Akl, M. Burgin, C. S. Calude, J. F. Costa, M. M. Dehshibi, Y.-P. Gunji, Z. Konkoli, B. MacLennan, B. Marchal, M. Margenstern, G. J. Martinez, R. Mayne, K. Moritan, A. Schumann, Y. D. Sergeyev, G. Ch. Sirakoulis, S. Stepney, K. Svozil, H. Zenil, “East-West Paths to Unconventional Computing,” Progress in Biophysics & Molecular Biology, vol. 131, pp. 469-493, December 2017.
  12. A. Tsiftsis, G. Ch. Sirakoulis, and J. Lygouras, “FPGA Processor with GPS for Modelling Railway Traffic Flow,” Journal of Cellular Automata., vol. 12, no. 5, pp. 381-400, 2017.
  13. V. Evangelidis, J. Jones, N. Dourvas, M.-A. Tsompanas, G. Ch. Sirakoulis and A. Adamatzky, “Physarum machines imitating a Roman road network: the 3D approach,” Scientific Reports, vol. 7, Article Number 7010, August 2017, (OPEN ACCESS https://doi:10.1038/s41598-017-06961-y).
  14. A. Ascoli, V. Ntinas, R. Tetzlaff and G. Ch. Sirakoulis, “Closed-form analytical solution for on-switching dynamics in a TaO memristor,” IET Electronic Letters, vol. 53, no. 16, pp. 1125-126, August 2017.
  15. M.-A. I. Tsompanas, A. Adamatzky, G. Ch. Sirakoulis, J. Greenman, and I. Ieropoulos, “Towards implementation of cellular automata in Microbial Fuel Cells,” accepted for publication in Plos One.( https://doi.org/10.1371/journal.pone.0177528, May 2017).
  16. N. Dourvas, G. Ch. Sirakoulis, and A. Adamatzky, “Cellular Automaton Belousov-Zhabotinsky Model for Binary Full Adder,” International Journal of Bifurcation and Chaos, vol. 27, no. 6, pp. 1750089, 2017.
  17. M.-A. I. Tsompanas, A. Adamatzky, I. Ieropoulos, N. Phillips, G. Ch. Sirakoulis, and J. Greenman, “Cellular non-nonlinear network model of microbial fuel cell,” Biosystems, vol. 156-157, pp. 53-62, June-July 2017.
  18. L.V. Gambuzza, M. Frasca, L. Fortuna, V. Ntinas, I. Vourkas, and G. Ch. Sirakoulis, “Memristor Crossbar for Adaptive Synchronization,” IEEE Transactions on Circuits and Systems I: Regular Papers., vol. 64, no. 8, pp. 2124-2133, Aug. 2017.
  19. A. Adamatzky, G. Ch. Sirakoulis, G. J. Martínez, F. Balŭska, and S. Mancuso, “On plant roots logical gatesBiosystems, vol. 156-157, pp. 40-45, June-July 2017.
  20. G. Papandroulidakis, I. Vourkas, A. Abusleme, G. Ch. Sirakoulis, and A. Rubio, “Crossbar-Based Memristive Logic-In-Memory Architecture,” IEEE Transactions on Nanotechnology, vol. 16, no. 3, pp. 491-501, April 2017.
  21. A. Amanatiadis, L. Bampis, E. G. Karakasis, A. Gasteratos and G. Ch. Sirakoulis, “Real-time surveillance detection system for medium-altitude long-endurance unmanned aerial vehicles,” accepted for publication in Concurrency and Computation: Practice and Experience.
  22. V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, and A. Adamatzky, “Physarum Space Exploration Using Memristors,” in Journal of Physics D: Applied Physics, vol. 50, no. 17, March 2017 (Invited Paper).
  23. V. S. Kalogeiton, D. Papadopoulos, O. Liolis, V. Mardiris, G. Ch. Sirakoulis, and I. Karafyllidis, “Programmable crossbar quantum-dot cellular automata circuits,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems., vol. 36, no. 8, pp. 1367-1380, Aug. 2017.
  24. V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, and A. Adamatzky, “Oscillation-Based Slime Mould Electronic Circuit Model for Maze-Solving Computations,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 64, no. 6, pp. 1552-1563, June 2017.
  25. D. Tourtounis, N. Mitianoudis, and G. Ch. Sirakoulis, “Salt-n-pepper noise filtering using Cellular Automata,” accepted for publication in Journal of Cellular Automata.
  26. M. Kechaidou, and G. Ch. Sirakoulis, “Game of Life variations for image scrambling,” Journal of Computational Science, vol. 21, pp. 432-447, 2017.
  27. V. Ntinas, B. Moutafis, G. A. Trunfio, and G. Ch. Sirakoulis, “Parallel fuzzy cellular automata for data-driven simulation of wildfire simulations,” Journal of Computational Science, vol. 21, pp. 469-485, 2017.
  28. T. Bontzorlos, and G. Ch. Sirakoulis, “Bioinspired algorithm for area surveillance using autonomous robots,” International Journal of Parallel, Emergent and Distributed Systems, vol 32, no. 4, pp. 368-385, 2017.
  29. N. Dourvas, G. Ch. Sirakoulis, and Ph. Tsalides, “A GPGPU Physarum Cellular Automaton Model,” Applied Mathematics & Information Sciences, vol. 10, no. 6, pp. 2055-2069, July 2017.
  30. Th. Giitsidis, and G. Ch. Sirakoulis, “Modeling passengers boarding in aircraft using Cellular Automata,” IEEE/CAA Journal of Automatica Sinica, vol. 3, no. 4, pp. 365-384, Oct. 2016.
  31. S. Diamantopoulos, Ch. Kachris, G. Ch. Sirakoulis, and D. Soudris, “An FPGA-based Integrated MapReduce Accelerator platform,” Journal of VLSI Signal Processing Systems, vol. 87, no. 3, pp. 357–369, 2017.
  32. I. Vourkas, G. Papandroulidakis, G. Ch. Sirakoulis, and A. Abusleme, “2T1M-Based Double Memristive Crossbar Architecture for In-Memory Computing,” International Journal of Unconventional Computing, vol. 12, no. 4, pp. 265-280, 2016.
  33. I. Vourkas, and G. Ch. Sirakoulis, “Emerging Memristor-based Logic Circuit Design Approaches: A Review,” IEEE Circuits and Systems Magazine, vol. 16, no. 3, pp. 15-30, August 2016.
  34. P. Chatziagorakis, Ch. Ziogou, C. Elmasides, G. Ch. Sirakoulis, I. Karafyllidis, I. Andreadis, N., Georgoulas, D. Giaouris, A. Papadopoulos, D. Ipsakis, P. Seferlis, S. Papadopoulou, F. Stergiopoulos and P. Voutetakis, “Enhancement of Hybrid Renewable Energy Systems Control with Neural Networks applied to Weather Forecasting: The case of Olvio,” Neural Computing and Applications, vol. 27, no. 5, pp. 1093-1118, July 2016.
  35. A. Tsiftsis, I. G. Georgoudas, and G. Ch. Sirakoulis, “Real Data Evaluation of a Crowd Supervising System for Stadium Evacuation and its Hardware Implementation,” IEΕE Systems, vol. 10, no. 2, pp. 649-660, June 2016.
  36. L. Spartalis, I. G. Georgoudas, and G. Ch. Sirakoulis, “A CA-based Model with Virtual Field for Guided Evacuation of People with Motion Difficulties,” Journal of Cellular Automata, vol. 11, no. 4, pp. 311-326, 2016.
  37. G. Pouiklis, and G. Ch. Sirakoulis, “Clock gating methodologies and tools: A Survey,” accepted for publication in International Journal of Circuit Theory and Applications, vol. 44, no. 4, pp. 798-816, April 2016.
  38. G. Ch. Sirakoulis, “Parallel Application of Hybrid DNA Cellular Automata for Pseudorandom Number Generation,” Journal of Cellular Automata, vol. 11, no. 1, pp. 63-89, 2016.
  39. M.-A. I. Tsompanas, Ch. Kachris, and G. Ch. Sirakoulis, “Modeling Cache Memory Utilization on Multicore Using Common Pool Resource Game on Cellular Automata,” ACM Transactions on Modeling and Computer Simulation (TOMACS), vol. 26, no. 3, article no. 21, Feb. 2016.
  40. I. Vourkas, D. Stathis, G. Ch. Sirakoulis, and S. Hamdioui, “Alternative Architectures towards Reliable Memristive Crossbar Memories,” IEEE Transactions on VLSI Systems, vol. 24, no. 1, pp. 206-217, Jan. 2016.
  41. G. Ch. Sirakoulis, “The Computational Paradigm of Cellular Automata in Crowd Evacuation,” International Journal of Foundations of Computer Science, vol. 26, no. 7, pp. 851, Nov. 2015.
  42. Ch. Kachris, G. Ch. Sirakoulis, D. Soudris, “A MapReduce scratchpad memory for multi-core cloud computing applications,” Microprocessors and Microsystems, vol. 39, no. 8, pp. 599–608, November 2015.
  43. P. Chatziagorakis, and G. Ch. Sirakoulis, “Cellular automata simulation of saltwater intrusion in coastal aquifer,” International Journal of Parallel, Emergent and Distributed Systems, first published September 2015, DOI:10.1080/17445760.2015.1077523, vol. 31, no. 6, pp. 517-528, 2016.
  44. M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Evolving Transport Networks with Cellular Automata Models Inspired by Slime Mould,” IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1887-1899, September 2015.
  45. V. Mardiris, G. Ch. Sirakoulis, and I. Karafyllidis, “Automated Design Architecture for 1-D Cellular Automata using Quantum Cellular Automata,” IEEE Transactions on Computers, vol. 64, no. 9, pp. 2476-2489, September 2015.
  46. A. Adamatzky, and G. Ch. Sirakoulis, “Building exploration with leeches Hirudo verbana,” Biosystems, vol. 134, pp. 48-55, August 2015.
  47. X. Zhang, A. Adamatzky, F. T.S. Chan, Y. Deng, H. Yang, X.-S. Yang, M.-A. I. Tsompanas, G. Ch. Sirakoulis and S. Mahadevan, “A Biologically Inspired Network Design Model,” Scientific Reports, 5, Article number: 10794, June 2015.
  48. V. Evangelidis, M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Slime Mould Imitates Development of Roman Roads in Balkans,” Journal of Archaeological Science: Reports, vol. 2, pp. 264–281, June 2015.
  49. Th. Giitsidis, N. Dourvas, and G. Ch. Sirakoulis, “Parallel implementation of aircraft disembarking and emergency evacuation based on Cellular Automata,” International Journal of High Performance and Applications, first published June 2015, vol. 31, no. 2, pp. 134-151, 2017.
  50. N. Bitsakidis, S. Chatzichristofis, and G. Ch. Sirakoulis, “Hybrid Cellular Ants for Clustering Problems,” International Journal of Unconventional Computing, vol. 11, pp. 103–130, 2015.
  51. I. Vourkas, A. Mpatsos, and G. Ch. Sirakoulis, “SPICE Modeling of Nonlinear Memristive Behavior,” International Journal of Circuit Theory and Applications, vol. 43, no. 5, pp. 553–565, May 2015.
  52. E. Boukas, I. Kostavelis, A. Gasteratos, and G. Ch. Sirakoulis, “Robot Guided Crowd Evacuation,” IEEE Transactions on Automation Science and Engineering, vol. 12, no. 2, pp. 739–751, April 2015.
  53. M.-A. I. Tsompanas, R. Mayne, G. Ch. Sirakoulis, and A. I. Adamatzky, “A Cellular Automata Bio-Inspired Algorithm Designing Data Trees in Wireless Sensor Networks,” International Journal of Distributed Sensor Networks, vol. 2015, 471045 [10 pages], March 2015.
  54. R. Mayne, M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Towards a slime mould-FPGA interface,” Biomedical Engineering Letters, vol. 5, no. 1, pp. 51–57, March 2015.
  55. V. S. Kalogeiton, D. P. Papadopoulos, I. P. Georgilas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Cellular Automaton model of Crowd Evacuation Inspired by Slime Mould,” International Journal of General Systems, vol. 43, no. 4, pp. 354-391, 2015.
  56. N. Dourvas, M.-A. I. Tsompanas, G. Ch. Sirakoulis, and Ph. Tsalides, “Hardware Acceleration of Cellular Automata Physarum Polycephalum Model,” Parallel Processing Letters, vol. 25, 1540006 [25 pages], 2015.
  57. I. Vourkas, and G. Ch. Sirakoulis, “Employing Threshold-based Behavior and Network Dynamics for the Creation of Memristive Logic Circuits and Architectures,” Physica Status Solidi C, vol. 12, no. 1-2, pp. 168-174, January 2015.
  58. A. Adamatzky, R. Armstrong, B. De Lacy Costelllo, V. Deng, J. Jones, R. Mayne, T. Schubert, G. Ch. Sirakoulis, and X. Zhang, “Slime mould analogue models of space exploration and planet colonization,” Journal of The British Interplanetary Society, Space Architecture 67, pp. 290-304, 2015.
  59. G. Papandroulidakis, I. Vourkas, N. Vasileiadis, and G. Ch. Sirakoulis, “Boolean Logic Operations and Computing Circuits Based on Memristors,” IEEE Trans. Circuits Syst. II, vol. 61, no. 12, pp. 972-976, 2014.
  60. I. Vourkas, D. Stathis, and G. Ch. Sirakoulis, “Memristor-based parallel sorting approach using one-dimensional cellular automata,” IET Electron. Letters, vol. 50, no. 24, pp. 1819-1821, 2014.
  61. M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. Adamatzky “Physarum in Silicon: The Greek Motorways Study,” Natural Computing, pp. 1-17, Doi: 10.1007/s11047-014-9459-0, 2014.
  62. I. Vourkas, and G. Ch. Sirakoulis, “On the Generalization of Composite Memristive Network Structures for Computational Analog/Digital Circuits and Systems,” Microelectronics Journal, vol. 45, no. 11, pp. 1380-1391, 2014.
  63. P. Saravakos, and G. Ch. Sirakoulis, “Modeling employees behavior in workplace dynamics,” Journal of Computational Science, vol. 5, no. 5, pp. 821-833, 2014.
  64. I. Vourkas, and G. Ch. Sirakoulis, “Nano-Crossbar Memories Comprising Parallel/Serial Complementary Memristive Switches,” BioNanoScience, vol. 4, no. 2, pp. 166-179, 2014.
  65. D. Chrysostomou, G. Ch. Sirakoulis, and A. Gasteratos, “A bio-inspired multi-camera system for dynamic crowd analysis,” Pattern Recognition Letters, vol. 44, pp. 141-151, July 2014.
  66. I. Vourkas, and G. Ch. Sirakoulis, “Study of Memristive Elements Networks,” Journal of Nano Research, vol. 27, pp. 5-14, Mar 2014.
  67. V. S. Kalogeiton, D. P. Papadopoulos, and G. Ch. Sirakoulis, “Hey Physarum! Can you perform SLAM?,” International Journal of Unconventional Computing, vol. 10, no. 4, pp. 271-293, 2014.
  68. I. Vourkas, and G. Ch. Sirakoulis, “Memristor-based Combinational Circuits: A Design Methodology for Encoders/Decoders,” Microelectronics Journal., vol. 45, no. 1, pp. 59-70, Jan 2014.
  69. Ch. Vihas, I. Georgoudas and G. Ch. Sirakoulis, “Cellular Automata incorporating Follow–the–Leader Principles to Model Crowd Dynamics,” Journal of Cellular Automata, vol. 8, no. 5-6, pp. 333-346, 2013.
  70. I. Vourkas, and G. Ch. Sirakoulis, “Recent Progress and Patents on Computational Structures and Methods with Memristive Devices,” Recent Patents on Electrical & Electronic Engineering, vol. 6, no. 2, pp. 101-116, Aug. 2013.
  71. P. Progias and G. Ch. Sirakoulis, “An FPGA Processor for Modelling Wildfire Spread,” Mathematical and Computer Modeling, vol. 57, no. 5-6, pp. 1436-1452, 2013.
  72. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “Cellular Automata-based Architecture for Cooperative Miniature Robots,” Journal of Cellular Automata, vol. 8, no. 1-2, pp. 91-111, 2013.
  73. G. Kalogeropoulos, G. Ch. Sirakoulis, and I. Karafyllidis, “Cellular automata on FPGA for real-time urban traffic signals control,” Journal of Supercomputing, pp. 1-18, 2013.
  74. I. Vourkas, and G. Ch. Sirakoulis,  “A Novel Design and Modeling Paradigm for Memristor-based Crossbar Circuits,” IEEE Transactions on Nanotechnology, vol. 11, no. 6, pp. 1151-1159, 2012.
  75. M. Kechaidou, G. Ch. Sirakoulis, and E. Skordilis, “Modelling real earthquake activity with reverse engineering based on evolutionary computation methods,” Georisk, vol. 7, no. 4, pp. 275-288, 2013.
  76. D. Chrysostomou, L. Nalpantidis, A. Gasteratos, and G. Ch. Sirakoulis, “Multi-view 3D scene reconstruction using ant colony optimization techniques,” Measurement Science and Technology, vol. 23, 114002 (11 pp.), 2012.
  77. L. Pavlou, I.G. Georgoudas, G.Ch. Sirakoulis, E.M. Scordilis, I. Andreadis, “An event-driven model simulating fundamental seismic characteristics with the use of cellular automata,” Physics and Chemistry of the Earth, vol. 49, pp. 64-78, 2012.
  78. V. Tsoutsouras, G. Ch. Sirakoulis, G Pavlos, and A. Iliopoulos, “Simulation of healthy and epileptiform brain activity using cellular automata,” International Journal of Bifurcation and Chaos, vol. 22, 1250229 (23 pp.), 2012.
  79. M.-A. I. Tsompanas, and G. Ch. Sirakoulis, “Modeling and hardware implementation of an amoeba-like cellular automaton,” Bioinspiration & Biomimetics, vol. 7, 036013 (19 pp.), 2012.
  80. G. Ch. Sirakoulis, and I. Karafyllidis, “Cooperation in a Power-Aware Embedded System Changing Environment: Public Goods Games with Variable Multiplication Factors,” IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans, vol. 42, no. 3, pp. 596-603, 2012.
  81. G. Ch. Sirakoulis, and I. Karafyllidis, “Cellular Automata and Power Consumption,” Journal of Cellular Automata, vol. 7, no. 1, pp. 67-80, 2012.
  82. P. Chatziagorakis, G.Ch. Sirakoulis, J. Lygouras, “Design Automation of Cellular Neural Networks for Data Fusion Applications,” Microprocessors and Microsystems, vol. 36, no. 1, pp. 33-44, 2012.
  83. K. Konstantinidis, I. Andreadis, and G. Ch. Sirakoulis, “Application of Artificial Intelligence Methods to Content-Based Image Retrieval,” Advances in Imaging and Electron Physics, vol. 169, Ch. 3, pp. 99-145, 2011 (Invited Contribution).
  84. L. Nalpantidis, G. Ch. Sirakoulis, and A. Gasteratos, “Non-probabilistic cellular automata-enhanced stereo vision simultaneous localisation and mapping (SLAM),” Measurement Science and Technology, vol. 22, no. 11, pp. 114027, 2011.
  85. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “A path planning method based on Cellular Automata for Cooperative Robots,” Applied Artificial Intelligence, vol. 25, no. 8, pp. 721-745, 2011. 
  86. I. G. Georgoudas, G. Ch. Sirakoulis, E.M. Skordilis and I. Andreadis, “Parametric optimisation in a 2-D cellular automata model of fundamental seismic attributes with the use of genetic algorithms,” Advances in Engineering Software, vol. 42, no. 9, pp. 623-633, 2011.
  87. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “Cellular Ants: A Method to Create Collision Free Trajectories for a Cooperative Robot Team,Robotics and Autonomous Systems, vol. 59, no. 2, pp. 113-237, 2011.
  88. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “An Anticipative Crowd Management System Preventing Clogging in Exits during Pedestrian Evacuation Processes,” IEΕE Systems, vol. 5, no. 1, pp. 129-141, 2011.
  89. L. Nalpantidis, A. Amanatiadis, G. Ch. Sirakoulis, and A. Gasteratos, “An Efficient Hierarchical Matching Algorithm for Processing Uncalibrated Stereo Vision Images and its Hardware Architecture,” IET Image Processing, vol. 5, no. 5, pp. 481–492, 2011.
  90. S. A. Chatzichristofis, D. A. Mitzias, G. Ch. Sirakoulis, and Y. S. Boutalis, “A Novel Cellular Automata Based Technique for visual multimedia content encryption,” Optics Communications, vol. 283, no. 21, pp. 4250-4260 , 2010.
  91. I. G. Georgoudas, P. Kyriakos, G. Ch. Sirakoulis, and I. Andreadis, “An FPGA Implemented Cellular Automaton Crowd Evacuation Model Inspired by the Electrostatic-Induced Potential Fields,” Microprocessors and Microsystems, vol. 34, no. 7-8, pp. 285-300, 2010.
  92. J. N. Lygouras, V. Kodogiannis, T. P. Pachidis, and G. Ch. Sirakoulis, “A new method for digital encoder adaptive velocity/acceleration evaluation using a TDC with picosecond accuracy,Microprocessors and Microsystems, vol. 33, no. 7-8, pp. 453-460, 2009.
  93. K. Konstantinidis, G. Ch. Sirakoulis, and I. Andreadis, “Design and Implementation of a Fuzzy Modified Ant Colony Hardware Structure for Image Retrieval,” IEEE Transactions on Systems, Man and Cybernetics – Part C, vol. 50, no. 3, pp. 519-537, 2009.
  94. L. Nalpantidis, G. Ch. Sirakoulis, and A. Gasteratos, “Review of Stereo Vision Algorithms: from Software to Hardware,” International Journal of Optomechatronics, vol. 2, no. 4, pp. 435-462, 2009.
  95. I. G. Georgoudas, G. Ch. Sirakoulis, E. M. Skordilis, and I. Andreadis, “On Chip Earthquake Simulation Model Using Potentials,” Natural Hazards, vol. 50, no. 3, pp. 519-537, 2009.
  96. C. Georgoulas, L. Kotoulas, G. Ch. Sirakoulis, I. Andreadis, and A. Gasteratos, “Real-Time Disparity Map Computation Module,” Microprocessors and Microsystems, vol. 32, no. 3, pp. 159-170, 2008.
  97. Ch. Mizas, G. Ch. Sirakoulis, V. Mardiris, I. Karafyllidis, N. Glykos and R. Sandaltzopoulos, “Reconstruction of DNA sequences using Genetic Algorithms and Cellular Automata: towards mutation prediction?,” Biosystems, vol. 92, no. 1, pp. 61-68, 2008.
  98. V. Mardiris, G. Ch. Sirakoulis, Ch. Mizas, I. Karafyllidis, and A. Thanailakis, “A CAD system for modeling and Simulation of Computer Networks using Cellular Automata,” IEEE Transactions on Systems, Man and Cybernetics – Part C , vol. 38, no. 2, pp. 253-264, 2008.
  99. I. G. Georgoudas, G. Ch. Sirakoulis, E. M. Skordilis, and I. Andreadis, “A Cellular Automaton simulation tool for modelling seismicity in the region of Xanthi,” Environmental Modelling & Software, vol. 22, no. 10, pp. 1455-1464, 2007.
  100. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “Modelling Earthquake Activity Features using Cellular Automata,” Mathematical and Computer Modelling, vol. 46, no. 1-2, pp. 124-137, 2007.
  101. G. Ch. Sirakoulis, and I. Karafyllidis, “A self-regulation mechanism of the resist development process in integrated circuit fabrication,” Journal of Computer-Aided Material Design, vol. 12, no. 1, pp. 35-56, 2005.
  102. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “A Cellular Automaton for the propagation of circular fronts and its applications,” Engineering Applications of Artificial Intelligence, vol. 18, no. 6, pp. 731-744, 2005.
  103. G. Ch. Sirakoulis, V. Raptis, I. Karafyllidis, Ph. Tsalides, and A. Thanailakis, “A fault-tolerant message passing algorithm and its hardware implementation,” Advances in Engineering Software, vol. 36, no. 3, pp. 159-171, 2005.
  104. G. Ch. Sirakoulis, I. Karafyllidis, R. Sandaltzopoulos, Ph. Tsalides, and A. Thanailakis, “An algorithm for the study of DNA sequence evolution based on the genetic code,” Biosystems, vol. 77, no. 1-3, pp. 11-23, 2004.
  105. G. Ch. Sirakoulis, “A TCAD system for VLSI implementation of the CVD process using VHDL,” Integration, the VLSI Journal, vol. 37, no. 1, pp. 63-81, 2004.
  106. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “A CAD system for the construction and VLSI implementation of Cellular Automata algorithms using VHDL,” Microprocessors and Microsystems, vol. 27, no. 8, pp. 381-396, 2003.
  107. G. Ch. Sirakoulis, I. Karafyllidis, Ch. Mizas, V. Mardiris, A. Thanailakis, and Ph. Tsalides, “A cellular automaton model for the study of DNA sequence evolution,” Computers in Biology and Medicine, vol. 33, no. 5, pp. 439-453, 2003.
  108. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “A Cellular Automaton Methodology for the Simulation of Integrated Circuit Fabrication Processes,” Future Generation Computer Systems, vol. 18, no. 5, pp. 639-657, 2002.
  109. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “A TCAD tool for the simulation of the CVD process based on Cellular Automata,” Journal de Physique IV, vol. 11, Pr 3, pp. 205-212, 2001.
  110. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “Study of the effect of non-planarity and defects on the geometrical accuracy of semiconductor surface structures using a CA_TCAD system,” Materials Science and Engineering B, vol. 80, no. 1-3, pp. 68-72, 2001.
  111. G. Ch. Sirakoulis, I. Karafyllidis, A. Thanailakis, and V. Mardiris, “A methodology for VLSI implementation of Cellular Automata algorithms using VHDL,” Advances in Engineering Software, vol. 32, no. 3, pp. 189-202, 2001.
  112. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “A cellular automaton model for the effect of population movement on epidemic propagation,” Ecological Modelling, vol. 133, no. 3, pp. 209-223, 2000.
  113. G. Ch. Sirakoulis, I. Karafyllidis, V. Mardiris, and A. Thanailakis, “Study of the effects of photoresist surface roughness and defects on developed profiles,” Semiconductor Science and Technology, vol. 15, no. 2, pp. 98-107, 2000.
  114. G. Ch. Sirakoulis, I. Karafyllidis, V. Mardiris, and A. Thanailakis, “Study of lithography profiles developed on non-planar Si surfaces,” Nanotechnology, vol. 10, no. 4, pp. 421-427, 1999.
  115. G. Ch. Sirakoulis, I. Karafyllidis, D. Soudris, N. Georgoulas, and A. Thanailakis, “A new simulator for the oxidation process in integrated circuit fabrication based on cellular automata,” Modelling and Simulation in Materials Science and Engineering, vol. 7, no. 4, pp. 631-640, 1999.

Books

  1. L. O. Chua, G. Ch. Sirakoulis, and A. Adamatzky, “Handbook of Memristor Networks,” published by Springer, 2019.
  2. A. Adamatzky, Selim G. Akl, and G. Ch. Sirakoulis, “From Parallel to Emergent Computing,” published by CRC Press/Taylor & Francis, 2019.
  3. I. Vourkas and G. Ch. Sirakoulis, “Memristor-Based Nanoelectronic Computing Circuits and Architectures,” accepted to be publication by Springer, 2015.
  4. G. Ch. Sirakoulis, and A. Adamatzky, “Robots and Lattice Automata,” published by Springer, 2015, (ISBN 978-3-319-10924-4).
  5. J. Was, G. Ch. Sirakoulis, and S. Bandini, “Cellular Automata, Proceedings of 11th International Conference on Cellular Automata for Research and Industry, ACRI 2014”, published by Springer, LNCS 8751, 2014, (ISBN: 978-3-319-11519-1).
  6. G. Ch. Sirakoulis, and S. Bandini, “Cellular Automata, Proceedings of 10th International Conference on Cellular Automata for Research and Industry, ACRI 2012”, published by Springer, 2012 (ISBN: 978-3-642-33349-1).
  7. I. Boutalis, and G. Ch. Sirakoulis, “Computational Intelligence and Applications” (in Greek) Xanthi, Greece, 2009.

Book chapters

  1. A. Adamatzky, K. Szaciłowski, Z. Konkoli, L. C. Werner, D. Przyczyna, and G. Ch. Sirakoulis, “On buildings that compute. A proposal,” to be published by Springer, 2019.
  2. T. Bontzorlos, G. Ch. Sirakoulis, and F. Seredynski “Swarm Intelligence for Area Surveillance Using Autonomous Robots,” to be published as a chapter in the book “From Parallel to Emergent Computing,” by CRC Press/Taylor & Francis, 2019.
  3. A. Adamatzky, J. Tuszynski, J. Pieper, D. V. Nicolau, R. Rinalndi, G. Ch. Sirakoulis, V. Erokhin, J. Schnauss, and D. M. Smith, “Towards Cytoskeleton Computers. A proposal,” to be published as a chapter in the book “From Parallel to Emergent Computing,” by CRC Press/Taylor & Francis, 2019.
  4. V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, and A. Adamatzky, “Mimicking Physarum Space Exploration with Networks of Memristive Oscillators,” to be published as a chapter in the book Handbook of Memristor Networks by Springer, 2019.
  5. A. Adamatzky, S. Harding, V. Erokhin, R. Mayne, N. Gizzie, F. Baluška, S. Mancuso, and G. Ch. Sirakoulis, “Computers from Plants We Never Made: Speculations,” in Inspired by Nature, pp. 357-387, published by Springer, 2018.
  6. G. Ch. Sirakoulis, “Cellular Automata Hardware Implementation,” in Cellular Automata of Encyclopedia of Complexity and Systems Science Series, pp. 555-582, published by Springer, 2018.
  7. K. Ioannidis and G. Ch. Sirakoulis, “Cellular Automata Ants,” in Unconventional Computing of Encyclopedia of Complexity and Systems Science Series, pp. 565-576, published by Springer, 2018.
  8. M.-A. I. Tsompanas, N. I. Dourvas, K. Ioannidis, G. Ch. Sirakoulis, R. Hoffmann, and A. Adamatzky, “Cellular Automata Applications in Shortest Path Problem,” in Shortest Path Solvers. From Software to Wetware, pp 199-237, published by Springer, 2018.
  9. G. Ch. Sirakoulis, and I. Karafyllidis, “Power Consumption in Cellular Automata,” in Reversibility and Universality, pp. 183-198, published by Springer, 2017.
  10. E. Gale, O. Matthews, J. Jones, R. Mayne, G. Ch. Sirakoulis, and A. Adamatzky, “Physarum Inspired Audio: From Oscillatory Sonification to Memristor Music,” in Guide to Unconventional Computing and Music, pp. 181-198, published by Springer, 2017.
  11. N. Bitsakidis, N. I. Dourvas, S. Chatzichristofis, and G. Ch. Sirakoulis, “Cellular Automata Ants,” in Advances in Slime Mould Computing: Sensing and Computing with Slime Mould to be published by Springer, 2016.
  12. I. Georgoudas, G. Ch. Sirakoulis, E. M. Scordilis, and I. Andreadis, “Seismic Cellular Automata,” in “Designing Beauty: The Art of Cellular Automata,” pp. 125-126, published by Springer, 2016.
  13. M. Mizas, G. Ch. Sirakoulis, V. Mardiris, I. Karafyllidis, N. Glykos and R. Sandaltzopoulos, “DNA Cellular Automata,” in “Designing Beauty: The Art of Cellular Automata,” pp. 127-128, published by Springer, 2016.
  14. R. Mayne, M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Towards a slime mould-FPGA interface,” in “Advances in Slime Mould Computing: Sensing and Computing with Slime Mould,” pp. 299–310, published by Springer, 2016.
  15. V. Evangelidis, M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Application of Slime Mould Computing on Archaeological Research,” in “Advances in Slime Mould Computing: Sensing and Computing with Slime Mould,” pp. 349-372, published by Springer, 2016.
  16. N. I. Dourvas, M.-A. I. Tsompanas, and G. Ch. Sirakoulis, “Parallel Accelaration of Slime Mould Discrete Models,” in “Advances in Slime Mould Computing: Sensing and Computing with Slime Mould,” pp. 595-618, published by Springer, 2016.
  17. M.-A. I. Tsompanas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Cellular Automata Models Simulating Slime Mould Computing,” in “Advances in Slime Mould Computing: Sensing and Computing with Slime Mould,” pp. 563-594, published by Springer, 2016.
  18. V. S. Kalogeiton, D. P. Papadopoulos, I. P. Georgilas, G. Ch. Sirakoulis, and A. I. Adamatzky, “Biomimicry of Crowd Evacuation with a Slime Mould Cellular Automaton Model,” in “Computational Intelligence, Medicine and Biology,” Chapter 7, pp. 123-151, published by Springer, 2015.
  19. A. Ch. Kapoutsis, S. A. Chatzichristofis, G. Ch. Sirakoulis, L. Doitsidis, and E. B. Kosmatopoulos, “Employing Cellular Automata for Shaping Accurate Morphology Maps Using Scattered Data from Robotics’ Missions,” in “Robots and Lattice Automata,” Chapter 10, pp. 229-246, published by Springer UK, 2015.
  20. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “Cellular Robotic Ants Synergy Coordination for Path Planning,” in “Robots and Lattice Automata,” Chapter 9, pp. 197-228, published by Springer UK, 2015.
  21. D. Portokalidis, I. G. Georgoudas, A. Gasteratos, and G. Ch. Sirakoulis, “A Full-scale Hardware Solution for Crowd Evacuation via Multiple Cameras,” in “Human Behaviour Understanding in Networked Sensing – Theory and Applications of Networks of Sensors,” Chapter 6, pp 127-154, published by Springer, 2014.
  22. I. Vourkas, and G. Ch. Sirakoulis, “Modeling memristor–based circuit networks on crossbar architectures,” in: A. Adamatzky, L. Chua (Eds.) “Memristor Networks,” Chapter 23, pp. 505-535, published by Springer International Publishing, Switzerland, 2014.
  23. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “Cellular Automata for Image Resizing,” in “Cellular automata for Image Processing, Computer Graphics and Computational Geometry,” accepted to be published by Springer, in 2014.
  24. K. Konstantinidis, G. Ch. Sirakoulis, and I. Andreadis, “Ant Colony Optimization for Use in Content Based Image Retrieval,” in “Artificial Immune Systems and Natural Computing: Applying Complex Adaptive Technologies,” Chapter XIIV, pp. 384-404, 2009, published by IGI Publishing Group.
  25. C. Georgoulas, G. Ch. Sirakoulis, and I. Andreadis, “Real Time Stereo Vision Applications,” in “Robot Vision,” Chapter 15, pp. 275-291, 2010, published by IN-TECH.

Conference Proceedings

  1. I.-A. Fyrigos, V. Ntinas, G. Ch. Sirakoulis, A. Adamatzky, V. Erokhin, and A. Rubio, “Wave Computing with Passive memristive Networks,” accepted for presentation in International Symposium on Circuits and Systems 2019 (ISCAS 2019), Sapporo, Japan, May 26-29, 2019.
  2. V. Ntinas, A. Rubio, G. Ch. Sirakoulis, and S. Cotofana, “A Pragmatic Gaze on Stochastic Resonance Based Variability Tolerant Memristance Enhancement,” accepted for presentation in International Symposium on Circuits and Systems 2019 (ISCAS 2019), Sapporo, Japan, May 26-29, 2019.
  3. P. Karakolis, P. Normand, P. Dimitrakis, V. Ntinas, I.-A. Fyrigos, I. Karafyllidis, and G. Ch. Sirakoulis, “Future and Emergent Materials and Devices for Resistive Switching,” in IEEE 13th Nanotechnology Materials and Devices Conference (IEEE NMDC 2018), pp. 1-5, Portland, Oregon, USA, 14-17 October, 2018. (Invited Talk).
  4. N. Kartalidis, I. G. Georgoudas, and G. Ch. Sirakoulis, “Cellular Automata Based Evacuation Process Triggered by Indoors Wi-Fi and GPS Established Detection,” in 13th International Conference on Cellular Automata for Research and Industry (ACRI 2018), pp. 492-502, Como, Italy, 17-21 September 2018.
  5. I. Karafyllidis, and G. Ch. Sirakoulis, “Quantum Walks on Quantum Cellular Automata Lattices: Towards a New Model for Quantum Computation,” in 13th International Conference on Cellular Automata for Research and Industry (ACRI 2018), pp. 319-327, Como, Italy, 17-21 September 2018.
  6. M. Madikas, M.-A. Tsompanas, N. Dourvas, G. Ch. Sirakoulis, J. Jones, and A. Adamatzky, “Hardware Implementation of a Biomimicking Hybrid CA,” in 13th International Conference on Cellular Automata for Research and Industry (ACRI 2018), pp. 80-92, Como, Italy, 17-21 September 2018.
  7. I.-A. Fyrigos, V. Ntinas, I. Karafyllidis, G. Ch. Sirakoulis, P. Karakolis, and P. Dimitrakis, “Early approach of Qubit state representation with Memristors,” in Advances in Neural Networks and Applications 2018 (ANNA 2018), pp. 1-5, St. St. Konstantin and Elena Resort, Bulgaria, 15-17 September 2018.
  8. A. Ascoli, R. Tetzlaff, V. Ntinas, and G. Ch. Sirakoulis, “Analytical DC model of a TaO memristor,” in Advances in Neural Networks and Applications 2018 (ANNA 2018), pp. 1-5, St. St. Konstantin and Elena Resort, Bulgaria, 15-17 September 2018.
  9. R.-E. Karamani, I.-A. Fyrigos, V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, “Game of Life in Memristor Cellular Automata Grid,” in 16th International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA 2018), pp. 1-4, Budapest, Hungary, 2018.
  10. I. Karafyllidis, G. Ch. Sirakoulis, and P. Dimitrakis, “Representation of Qubit States using 3D Memristance Spaces: A first step towards a Memristive Quantum Simulator,” in 14th IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH 2018), pp. 163-168, Athens, Greece, 2018.
  11. V. A. Mardiris, O. Liolis, G. Ch. Sirakoulis, and I. G. Karafyllidis, “Signal Synchronization in Large Scale Quantum-dot Cellular Automata Circuits,” in 14th IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH 2018), pp. 153-156, Athens, Greece, 2018.
  12. O. Liolis, V. A. Mardiris, G. Ch. Sirakoulis, and I. G. Karafyllidis, “Quantum-dot Cellular Automata RAM design using Crossbar Architecture,” in 14th IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH 2018), pp. 86-90, Athens, Greece, 2018.
  13. K. Rallis, G. Ch. Sirakoulis, I. Karafyllidis, and A. Rubio, “Multi-valued logic circuits on graphene quantum point contact devices,” in 14th IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH 2018), pp. 44-48, Athens, Greece, 2018.
  14. R.-E. Karamani, I.-A. Fyrigos, V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, and A. Rubio, “Memristive Cellular Automata for Modeling of Epileptic Brain Activity,” in International Symposium on Circuits and Systems 2018 (ISCAS 2018), pp. 1-5, Florence, Italy, May 27-30, 2018.
  15. V. Ntinas, I. Vourkas, G. Ch. Sirakoulis, A. Adamatzky and A. Rubio, “Coupled Physarum-Inspired Memristor Oscillators for Neuron-like Operations,” in International Symposium on Circuits and Systems 2018 (ISCAS 2018), Florence, Italy, May 27-30, 2018.
  16. J. Gomez, I. Vourkas, A. Abusleme and G. Ch. Sirakoulis, “Experimental measurements on resistive switching devices: Gaining hands-on experience,” in 2018 International Conference on Modern Circuits and Systems Technologies (MOCAST 2018), pp. 1-4, Thessaloniki, Greece, May 7-9, 2018 (Nomination for Best Paper Award).
  17. P. Kontou, I. G. Georgoulas, G. A. Trunfio, and G. Ch. Sirakoulis, “Cellular Automata Modelling of the Movement of People with Disabilities during Building Evacuation,” in 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP 2018), pp. 550-557, Cambridge, UK, 21-23 March 2018.
  18. V. G. Ntinas, I. Vourkas, G. Ch. Sirakoulis, A. Adamatzky, and A. Rubio, “Memristor-based electronic computing circuits and systems inspired by Physarum Polycephalum’s space exploration,” in workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2017 Conference, Manchester, UK, 22-24 January 2018..
  19. A. Ascoli, R. Tetzlaff, V. Ntinas, and G. Ch. Sirakoulis, “Towards an analytical description of a TaO memristor,” in Electronics and Telecommunications (PACET 2017), Panhellenic Conference on Electronics and Telecommunications (PACET 2017), pp. 1-4, Xanthi, Greece, November 17-18, 2017.
  20. M.-A. Tsompanas and G. Ch. Sirakoulis, “The MapReduce application of matrix multiplication implemented on field programmable gate arrays,” in Panhellenic Conference on Electronics and Telecommunications (PACET 2017), pp. 1-6, Xanthi, Greece, November 17-18, 2017.
  21. R.-E. Karamani, V. Ntinas, I. Vourkas and G. Ch. Sirakoulis, “1-D memristor-based cellular automaton for pseudo-random number generation,” in 27th Symposium on Power and Timing Modelling, Optimization and Simulation (PATMOS 2017), pp. 1-6, Thessaloniki, Greece, September 25-27, 2017.
  22. P. Gavriilidis, I. Gerakakis, I. Georgoudas, G. Trunfio and and G. Ch. Sirakoulis, “A Fuzzy Logic Inspired Cellular Automata Based Model for Simulating Crowd Evacuation Processes,” in “Workshop on Complex Collective Systems (CCS)” within the “11th International Conference on Parallel Processing and Applied Mathematics (PPAM 2017)”, pp. 436-445, Lublin, Poland, September 10-13, 2017.
  23. V. Ntinas, A. Ascoli, R. Tetzlaff, and G. Ch. Sirakoulis, “Transformation techniques applied to a TaO memristor model,” in European Conference on Circuit Theory and Design (ECCTD 2017), pp. 1-4, Catania, Italy, September 4-6, 2017.
  24. J. Gomez, I. Vourkas, A. Abusleme, R. Rodriguez, J.M. Martinez, M. Nafria, G. Ch. Sirakoulis, and A. Rubio, “Universal Performance Parameters for Resistive Switching Devices,” in 2017 IEEE Int’l Symposium on Circuits & Systems (ISCAS 2017), Baltimore, MD, USA, May 28-31, 2017.
  25. N. Vasileiadis, I. Vourkas, G. Ch. Sirakoulis, and N. Papamarkos, “Towards Memristive Crossbar-Based Neuromorphic HW Accelerators for Signal Processing,” in 6th International Conference on Circuits and Systems Technologies (MOCAST 2017), Thessaloniki, Greece, 4-6 May 2017.
  26. Ch. Sichonidis, V. Ntinas, I. Vourkas, and G. Ch. Sirakoulis, “Memristors in Excitable Cellular Automata-based Computing Arrays,” in International Conference on Memristive Materials, Devices & Systems (MEMRISYS 2017), Athens, Greece, 3-6 April 2017.
  27. J. Martin-Martinez, I. Vourkas, J. Gomez, A. Abusleme, G. Ch. Sirakoulis, E. Salvador, A. Crespo, R. Rodriguez, M. Nafria, and A. Rubio, “The Voltage Divider Effect Revisited for Multi-Level Memristor Tuning,” in International Conference on Memristive Materials, Devices & Systems (MEMRISYS 2017), Athens, Greece, 3-6 April 2017.
  28. I. Vourkas, J. Gomez, N. Vasileiadis, A. Abusleme, G. Ch. Sirakoulis, and A. Rubio “Exploring the Voltage Divider Approach for Accurate Memristor State Tuning,” accepted for presentation in 8th IEEE Latin American Symposium (LASCAS 2017), Bariloche, Argentina, 20-23 February 2017.
  29. I. Koumis, I. G. Georgoudas, G. A. Trunfio, J. Wąs, and G. Ch. Sirakoulis, “A GPU Implemented 3F Cellular Automata-based Model for a 2D Evacuation Simulation Pattern,” in 25th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2017), pp. 497-504, St. Petersburgh, Russia, 6-8 March 2017.
  30. I. Vourkas, G. Papandroulidakis, M. Escudero, G. Ch. Sirakoulis, and A. Rubio “Variability Challenges in Emerging Memristor-based Logic Circuits,” in workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2017 Conference, Stockholm, Sweden, 23-25 January 2017.
  31. S. Zuin, M. Escudero López, F. Moll, A. Rubio, I. Vourkas and G. Ch. Sirakoulis, “Experience on Material Implication Computing With an Electromechanical Memristor Emulator,” accepted for presentation in 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016), Athens, Greece, 6-9 December 2016.
  32. Ch. Semertzidou, N. I. Dourvas, M.-A. I. Tsompanas, A. Adamatzky, and G. Ch. Sirakoulis, “Introducing Chemotaxis to a Mobile Robot,” Artificial Intelligence Applications and Innovations (AIAI 2016) vol. 475, IFIP Advances in Information and Communication Technology, pp. 396-404, Thessaloniki, Greece, 16-18 September 2016.
  33. D. Tsorvas, I. G. Georgoudas, F. Seredynski, and G. Ch. Sirakoulis, “Enhanced Multi-parameterized Cellular Automaton Model for Crowd Evacuation: The Case of a University Building,” 12th International Conference on Cellular Automata for Research and Industry (ACRI 2016), Vol. 9863 Lecture Notes in Computer Science, pp. 376-386, Fez, Morocco, 5-8 September 2016.
  34. A. Dimitriadis, M. Kutrib, and G. Ch. Sirakoulis, “Cutting the Firing Squad Synchronization,” 12th International Conference on Cellular Automata for Research and Industry (ACRI 2016), Vol. 9863 Lecture Notes in Computer Science, pp. 123-133, Fez, Morocco, 5-8 September 2016.
  35. I. Vourkas, A. Abusleme, G. Ch. Sirakoulis, and Antonio Rubio “1-D Memristor Networks as Ternary Storage Cells,” 15th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2016), Dresden, Germany, 23-25 August 2016.
  36. L. V. Gambuzza, M. Frasca, L. Fortuna, V.Ntinas, I. Vourkas , and G. Ch. Sirakoulis, “A new approach based on memristor crossbar for synchronization,” 15th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2016), Dresden, Germany, 23-25 August 2016.
  37. I. Vourkas, A. Abusleme, V. Ntinas, G. Ch. Sirakoulis, and Antonio Rubio, “A Digital Memristor Emulator for FPGA-Based Artificial Neural Networks,” in Proceedings of 1st IEEE International Verification and Security Workshop (IVSW 2016), pp. 1-4, Sant Feliu de Guixols, Catalunya, Spain, 4-6 July 2016.
  38. I. Vourkas, and G. Ch. Sirakoulis, “Memristive Electronic Computing Circuits and Systems,” 5th International Conference from Nanoparticles and Nanomaterials to Nanodevices and Nanosystems (IC4N), Porto Heli Peloponnese, Greece, 26-30 June 2016. (Invited Talk)
  39. P. Progias, A. A. Amanatiadis, W. Spataro, G. A. Trunfio, and G. Ch. Sirakoulis, “A Cellular Automata Based FPGA Realization of a New Metaheuristic Bat-Inspired Algorithm,” Second International Conference on Numerical Computations: Theory and Algorithms (NUMTA 2016), Calabria, Italy, 19-25 June 2016.
  40. Ch. Sichonidis, I. Vourkas, N. Mitianoudis and G. Ch. Sirakoulis, “A memristive circular buffer for real-time signal processing,” The International Conference on Modern Circuits and Systems Technologies (MOCAST 2016), DOI: 10.1109/MOCAST.2016.7495153, Thessaloniki, Greece, 12-14 May 2016.
  41. G. A. Trunfio, and G. Ch. Sirakoulis, “Computing Multiple Accumulated Cost Surfaces with Graphics Processing Units,” 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2016), pp. 694-701, Heraklion Crete, Greece, 17-19 February 2016.
  42. K. Konstantara, N. Dourvas, I. G. Georgoudas, and G. Ch. Sirakoulis, “Parallel Implementation of a Cellular Automata-based Model for Assisted Evacuation of Elderly People,” 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015), pp. 702-709, Heraklion Crete, Greece, 17-19 February 2016.
  43. G. Papandroulidakis, I. Vourkas, and G. Ch. Sirakoulis, “Composite memristive nano-architectures with memory and in memory computing capabilities,” in workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2016 Conference, Amsterdam, Netherlands, 18-20 January 2016.
  44. G. Papandroulidakis, I. Vourkas, G. Ch. Sirakoulis, and A. Rubio, “Heterogeneous Memristive Crossbar for In-Memory Computing,” International Conference on Memristive Systems (Memrisys 2015), pp. 1-2, Paphos, Cyprus, 8-10 November 2015.
  45. D. Strongylis, A. Makarantzis, I. G. Georgoudas, and G. Ch. Sirakoulis, “Hardware implementation principles of a probabilistic CA-based crowd evacuation model,” 19th Panhellenic Conference on Informatics (PCI 2015), pp. 424-425, Athens, Greece, 2-4 October 2015.
  46. V. G. Ntinas, B. E. Moutafis, G. A. Trunfio and G. Ch. Sirakoulis, “GPU and FPGA Parallelization of Fuzzy Cellular Automata for the Simulation of Wildfire Spreading,” accepted for presentation in “Workshop on Complex Collective Systems (CCS)” within the “10th International Conference on Parallel Processing and Applied Mathematics (PPAM 2015)“, pp. 560-569, Krakow, Poland, September 8-11, 2015.
  47. G. Papandroulidakis, I. Vourkas, and G. Ch. Sirakoulis, S. Stavrinides, and S. Nikolaidis, “Multi-state Memristive Nanocrossbar for High-Radix Computer Arithmetic Systems,” 15th IEEE International Conference on Nanotechnology (IEEE NANO 2015), pp. 625-628, Rome, Italy, 27-30 July 2015.
  48. M.-A. I. Tsompanas, and G. Ch. Sirakoulis, “Mimicking the Exploration of 3D Terrains by Physarum with Cellular Automata Models,” in European Conference on Artificial Life (ECAL 2015), pp. 33-40, York, UK, 20-24 July 2015.
  49. M.-A. I. Tsompanas, and G. Ch. Sirakoulis, “Mimicking Physarum Polycephalum with Discrete Models: The Cellular Automata Approach,” in Physarum Machines: Embedded Computation with Slime Mould Workshop organized within European Conference on Artificial Life (ECAL 2015), York, UK, 20-24 July 2015.
  50. I. Vourkas, D. Stathis, and G. Ch. Sirakoulis, “Live Demonstration: XbarSim: An Educational Simulation Tool for Memristive Crossbar-Based Circuits,” in IEEE Int. Symp. Circ. Syst. (ISCAS 2015), pp. 1909, Lisbon, Portugal, 24-27 May 2015.
  51. I. Vourkas, D. Stathis, and G. Ch. Sirakoulis, “XbarSim: An Educational Simulation Tool for Memristive Crossbar-Based Circuits,” in IEEE Int. Symp. Circ. Syst. (ISCAS 2015), pp. 1798-1801, Lisbon, Portugal, 24-27 May 2015.
  52. V. Ntinas, I. Vourkas, and G. Ch. Sirakoulis, “LC Filters with Enhanced Memristive Damping,” in IEEE Int. Symp. Circ. Syst. (ISCAS 2015), pp. 2664-2667, Lisbon, Portugal, 24-27 May 2015.
  53. T. Giitsidis, E. G. Karakasis, A. Gasteratos, and G. Ch. Sirakoulis, “Human and fire detection from high altitude UAV images,” 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015), pp. 372-379, Turku, Finland, 4-6 March, 2015.
  54. G. Papandroulidakis, I. Vourkas, and G. Ch. Sirakoulis, “Memristor-based High-radix Computer Arithmetic System,” in workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2015 Conference, Amsterdam, Netherlands, 19-21 January 2015.
  55. I. Vourkas, and G. Ch. Sirakoulis, “Boolean Logic Operations and Computing Circuits Based on Memristors,” HiPEAC 2014 Computing Systems Week (HIPEAC 2014 CSW) special session on Memristive Computing Architectures: Emergent and Future Challenges, Athens, Greece, 08-10 October 2014.
  56. Ch. Kachris, G. Ch. Sirakoulis, and D. Soudris, “A Reconfigurable MapReduce Accelerator for multi-core all-programmable SoCs,” in International Symposium on System-on-Chip 2014 (SoC 2014), pp. 1-6, Tampere, Finland, 28-29 October 2014.
  57. A. Amanatiadis, E. G. Karakasis, L. Bampis, T. Giitsidis, P. Panagiotou, G. Ch. Sirakoulis, A. Gasteratos, P. Tsalides, A. Goulas, and K. Yakinthos, “The HCUAV project: Electronics and software development for medium altitude remote sensing,” in 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2014), pp. 1-5, Toya, Japan, 27-30 October 2014.
  58. K. Konstantinidis, A. Amanatiadis, S. Chatzichristofis, R. Sandaltzopoulos, and G. Ch. Sirakoulis, “Identification and Retrieval of DNA Genomes Using Binary Image Representations Produced by Cellular Automata,” accepted for presentation in 2014 IEEE International Conference on Imaging Systems & Techniques (IST 2014), Santorini, Greece, 14-17 October 2014.
  59. D. Stathis, I. Vourkas, and G. Ch. Sirakoulis, “Solving AI problems with memristors: A case study for optimal “bin packing”,” in 18th Panhellenic Conference on Informatics (PCI 2014), pp. 30:1-30:6, Athens, Greece, 2-4 October 2014.
  60. N. Dourvas, G. Ch. Sirakoulis, and Ph. Tsalides, “GPU Implementation of Physarum Cellular Automata Model,” accepted for presentation in “1st International Symposium on Artificial, Biological and Bio-Inspired Intelligence (ABBII)” organized within the 12th International Conference on Numerical Analysis and Applied Mathematics (ICNAAM 2014), Rhodes, Greece, 22-28 September 2014.
  61. P. Chatziagorakis, C. Elmasides, G. Ch. Sirakoulis, I. Karafyllidis, I. Andreadis, N., Georgoulas, D. Giaouris, A. Papadopoulos, Ch. Ziogou, D. Ipsakis, P. Seferlis, S. Papadopoulou, F. Stergiopoulos and P. Voutetakis, “Cellular Automata model with Game Theory for Power Management of Hybrid Renewable Energy Smart Grids,” in 11th International Conference on Cellular Automata for Research and Industry (ACRI2014), pp. 248-257, Krakow, Poland, 22-25 September 2014.
  62. D. Stathis, I. Vourkas, and G. Ch. Sirakoulis, “Shortest Path Computing Using Memristor-Based Circuits and Cellular Automata,” in 11th International Conference on Cellular Automata for Research and Industry (ACRI2014), pp. 398-407, Krakow, Poland, 22-25 September 2014.
  63. L. Spartalis, I. G. Georgoudas, and G. Ch. Sirakoulis, “CA Crowd Modeling for a Retirement House Evacuation with Guidance,” in “Fifth International Workshop on Crowds and Cellular Automata (C&CA-2014) organized within the 11th International Conference on Cellular Automata for Research and Industry (ACRI2014), pp. 481-491, Krakow, Poland, 22-25 September 2014.
  64. P. Chatziagorakis, C. Elmasides, G. Ch. Sirakoulis, I. Karafyllidis, I. Andreadis, N., Georgoulas, D. Giaouris, A. Papadopoulos, Ch. Ziogou, D. Ipsakis, P. Seferlis, S. Papadopoulou, F. Stergiopoulos and P. Voutetakis, “’Application of Neural Networks Solar Radiation Prediction for Hybrid Renewable Energy Systems,” in 15th Engineering Applications of Neural Networks (EEAN 2014), pp. 133-144, Sofia, Bulgaria, 5-7 September 2014.
  65. G. Ch. Sirakoulis, “Cellular Automata in Crowd Dynamics,” 19th International Conference Implementation and Application of Automata (CIAA 2014), pp. 58-69, Giessen, Germany, July 30 – August 2, 2014 (Keynote Talk).
  66. I. Vourkas, and G. Ch. Sirakoulis, “Employing Threshold-based Behavior and Network Dynamics for the Creation of Memristive Logic Circuits and Architectures,” in Symposium on Memristor materials, mechanisms and devices for unconventional computing affiliated with E-MRS 2014 Spring Meeting, Lille, France, May 26-28, 2014.
  67. E. Boukas, L. Crociani, S. Manzoni, G. Vizzari, A. Gasteratos, and G. Ch. Sirakoulis, “An Intelligent Tool for the Automated Evaluation of Pedestrian Simulation,” 8th Hellenic Conference on Artificial Intelligence (SETN 2014), pp. 136-149, Ioannina, Greece, 15-17 May 2014.
  68. S. Hamdioui, H. Aziza, and G. Ch. Sirakoulis, “Memristor based memories: Technology, design and test,” 9th IEEE International Conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS 2014), pp. 1-7, Santorini Island, Greece, 6-8 May 2014.
  69. Ch. Kachris, G. Ch. Sirakoulis, D. Soudris: “A configurable mapreduce accelerator for multi-core FPGA” 22nd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2014), pp. 241, Monterey, California February 26-28, 2014.
  70. T. Giitsidis, and G. Ch. Sirakoulis, “Simulation of aircraft disembarking and emergency evacuation,” 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2014), pp. 372-379, Turin, Italy, 12-14 February, 2014.
  71. I. Vourkas, and G. Ch. Sirakoulis, “Incorporating Memristors in Currently Established Logic Circuit Architectures: Design Considerations and Challenges,” in Workshop on Memristor Technology, Design, Automation and Computing (MemTDAC) affiliated with the HiPEAC 2014 Conference, Vienna, Austria, January 20-22, 2014.
  72. I. Vourkas, and G. Ch. Sirakoulis, “On the Analog Computational Characteristics of Memristive Networks” 2013 IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2013), pp. 309-312, Abu Dhabi, UAE, 8-11 December, 2013.
  73. O. Liolis, V. Kalogeiton, D. Papadopoulos, G. Ch. Sirakoulis, V. Mardiris, and A. Gasteratos, “Morphological Edge Detector Implemented in Quantum Cellular Automata,” 2013 IEEE International Conference on Imaging Systems and Techniques (IST 2013), pp. 406-409, Beijing, China, 22-23 Oct. 2013.
  74. I. Vourkas, D. Stathis and G. Ch. Sirakoulis, “Improved Read Voltage Margins with Alternative Topologies for Memristor-based Crossbar Memories,” 21st IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), pp. 364-267, Istanbul, Turkey, 7-9 October, 2013.
  75. I. Vourkas, and G. Ch. Sirakoulis, “Design and Development of Nano-Electronic Circuits and Architectures With Memristive Devices,” 21st IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), pp. 300-301, Istanbul, Turkey, 7-9 October, 2013.
  76. P. Saravakos, and G. Ch. Sirakoulis, “Modelling behavioral traits of employees in a workplace with Cellular Automata,” accepted for presentation in “Workshop on Complex Collective Systems (CCS)” within the “10th International Conference on Parallel Processing and Applied Mathematics (PPAM 2013)“, pp. 569-574, Warsaw, Poland, September 8-11, 2013.
  77. M.A. Tsompanas, Ch. Kachris, and G. Ch. Sirakoulis, “Evaluating conflicts impact over shared Last Level Cache using Public Goods Game on Cellular Automata,” 2013 International Conference on High Performance Computing and Simulation (HPCS 2013), pp. 326-332, Helsinki, Finland, July 1-5, 2013.
  78. Ι. Vourkas, and G. Ch. Sirakoulis, “A Threshold-based Approach for Modeling Memristive Devices and Systems,” accepted for presentation in 4th International Conference from Nanoparticles and Nanomaterials to Nanodevices and Nanosystems (IC4N), Korfu, Greece, June 16-20, 2013.
  79. M.A. Tsompanas, Ch. Kachris, and G. Ch. Sirakoulis, “Optimization of shared-memory multicore systems using Game Theory and Genetic Algorithms on Cellular Automata lattices,” NIDISC 2013 Workshop of «The 27th IEEE/ACM International Parallel and Distributed Processing (IPDPS 2013)», pp. 482-490, Boston, USA, 20-24 May 2013.
  80. V. Kalogeiton, D. Papadopoulos, and G. Ch. Sirakoulis, “Implementation of a Novel Physarum-Inspired and CA-based Single-Camera SLAM Method,” accepted for presentation in the Workshop of Unconventional Approaches to Robotics, Automation and Control inspired by Nature (UARACIN 2013) of the «2013 IEEE International Conference on Robotics and Automation (ICRA 2013)», Karlsruhe, Germany, 6-10 May 2013.
  81. G. Ch. Sirakoulis, “Cellular Automata for the advancement of Robotics” accepted for presentation in the Workshop of Unconventional Approaches to Robotics, Automation and Control inspired by Nature (UARACIN 2013) of the «2013 IEEE International Conference on Robotics and Automation (ICRA 2013)», Karlsruhe, Germany, 6-10 May 2013. (Keynote Talk)
  82. Ι. Vourkas, and G. Ch. Sirakoulis, “Modeling earthquake activity using a memristor-based cellular grid,” in Proceedings of General Assembly of European Geosciences Union 2013, Natural Hazards, Session NH9.12, (EGU2013-NH9.12), Vol. 15, EGU2013-12925, Vienna, Austria, April 7-12, 2013.
  83. Ι. Vourkas, and G. Ch. Sirakoulis, “FPGA based Cellular Automata for Environmental Modeling,” in Proceedings of the 2012 IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2012), pp. 308-313, Seville, Spain, 9-12 December 2012.
  84. D. Chrysostomou, G. Ch. Sirakoulis, and A. Gasteratos, “A bio-inspired multi-camera topology for crowd analysis,” in Proceedings of the 2nd International Workshop on Pattern Recognition and Crowd Analysis (PRCA ’12) held in conjunction with 21st IARP International Conference on Pattern Recognition (ICPR ’12), Tsukuba, Japan, 11-16 November, 2012.
  85. I. Katis, and G. Ch. Sirakoulis, “Cellular Automata on FPGAs for Image Processing,” in Proceedings of the 16th Panhellenic Conference on Informatics (PCI 2012), pp. 308-313, Athens, Greece, 5-7 October 2012.
  86. Ch. Kachris, G. Ch. Sirakoulis, and D. Soudris, “Performance Evaluation of Embedded Processor in MapReduce Cloud Computing Applications,” in Proceedings of the 3rd International Conference on Cloud Computing (CloudComp 2013), pp. 1-9, Wien, Austria, 24-26 September 2012.
  87. Ch. Vihas, I. Georgoudas, and G. Ch. Sirakoulis,”Follow-the-Leader Cellular Automata based Model Directing Crowd Movement,” in Lecture Notes in Computer Science (LNCS), Vol. 7495, 10th International Conference on Cellular Automata for Research and Industry (ACRI2012), G. Ch. Sirakoulis and S. Bandini (Eds.), pp. 752-762, Santorini, Greece, 24-27 September 2012.
  88. K. Ioannidis, I. Andreadis, and G. Ch. Sirakoulis, “An edge preserving image resizing method based on Cellular Automata,” in Lecture Notes in Computer Science (LNCS), Vol. 7495, 10th International Conference on Cellular Automata for Research and Industry (ACRI2012), G. Ch. Sirakoulis and S. Bandini (Eds.), pp. 375-384, Santorini, Greece, 24-27 September 2012.
  89. I. Vourkas, D. Michail, and G. Ch. Sirakoulis,”Spreading Patterns of Mobile Phone Viruses using Cellular Automata,” in Lecture Notes in Computer Science (LNCS), Vol. 7495, 10th International Conference on Cellular Automata for Research and Industry (ACRI2012), G. Ch. Sirakoulis and S. Bandini (Eds.), pp. 263-272, Santorini, Greece, 24-27 September 2012.
  90. G. Ch. Sirakoulis, “Hybrid DNA Cellular Automata for pseudorandom number generation,” in Proceedings of the 2012 International Conference on High Performance Computing and Simulation (HPCS 2012), pp. 238-244, Madrid, Spain, July 4-8, 2012.
  91. M. Kechaidou, G. Ch. Sirakoulis, and E. M. Scordilis, “Monitoring of seismic time-series with advanced parallel computational tools and complex networks,” General Assembly of European Geosciences Union 2012, Natural Hazards, Session NH9.11, (EGU2012-NH9.11), EGU2012-11003, Vienna, Austria, April 22-27, 2012.
  92. I. Vourkas, and G. Ch. Sirakoulis,”FPGA Implementation of a Cellular Automata-based Algorithm for the Prediction of Oil Slick Spreading,” in Proceedings of Second Pan-Hellenic Conference in Electronics and Communications (PACET 2012), Thessaloniki, Greece, March 2012.
  93. P. Chatziagorakis, and G. Ch. Sirakoulis, “Cellular Automata Simulation of Saltwater Intrusion in Coastal Aquifer,” in Proceeding of Interdisciplinary Symposium on Complex Systems, organized within the 9th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2011), AIP Conf. Proc. 1389, pp. 987-990, Chalkidiki, Greece, September 19-22, 2011 (Invited Presentation).
  94. G. Kalogeropoulos, G. Ch. Sirakoulis, and I. Karafyllidis, “FPGA Implementation of a Bioinspired Model for Real-Time Traffic Signals Control,” accepted for presentation in “2011 International Conference on Scientific Computing (CSC’11)”, Las Vegas, USA, July 13-19, 2011.
  95. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “Depicting Pathways for Cooperative Miniature Robots Using Cellular Automata,” in Proceedings of 2011 International Conference on High Performance Computing and Simulation (HPCS 2011), pp. 794-800, Constantinople, Turkey, July 4 – 8, 2011.
  96. M. Kechaidou, G. Ch. Sirakoulis, E. M. Scordilis, and I. Karafyllidis, “Modelling real earthquake activity with reverse engineering based on evolutionary computation methods,” in Proceedings of General Assembly of European Geosciences Union 2011, Natural Hazards, Session NH11.12, (EGU2009-NH11.12), vol. 13, EGU2011-10776, Vienna, Austria, April 19-24, 2011.
  97. A. Tsiftsis, G. Ch. Sirakoulis, and I. Lygouras, “FPGA Design of a Cellular Automaton Model for Railway Traffic Flow with GPS Module,” in Proceedings of 9th International Conference on Cellular Automata for Research and Industry (ACRI2010), Ascoli-Pizeno, Italy, 21-24 September 2010.
  98. I. G. Georgoudas, G. Koltsidas, G. Ch. Sirakoulis, and I. Andreadis, “A Cellular Automaton Model for Crowd Evacuation and its Auto-Defined Obstacle Avoidance Attribute,” accepted for presentation at Third International Workshop on Crowds and Cellular Automata (C&CA-2010) organized within the 9th International Conference on Cellular Automata for Research and Industry (ACRI2010), Ascoli-Pizeno, Italy, 21-24 September 2010.
  99. L. Nalpantidis, G. Ch. Sirakoulis, A. Carbone and A. Gasteratos, “Computationally Effective Stereovision SLAM,” in Proceedings of IEEE International Workshop on Imaging Systems and Techniques (IST 2010)“, pp. 458-463, Thessaloniki, Greece, 1-2 July, 2010.
  100. G. Ch. Sirakoulis, and I. Karafyllidis, “Power estimation of 1-d Cellular Automata circuits,” in Proceedings of2010 International Conference on High Performance Computing and Simulation (HPCS 2010)“, pp. 691-697, Caen, France, June 28 – July 2, 2010.
  101. M.-A. I. Tsompanas, G. Ch. Sirakoulis, and I. Karafyllidis, “Modeling memory resources distribution on multicore processors using games on cellular automata lattices,” in Proceedings of The 13th International Workshop on Nature Inspired Distributed Computing (NIDISC’10)” within the “The 24th IEEE/ACM International Parallel and Distributed Processing (IPDPS2010)“, pp. Atlanta, Georgia, USA, April 19-23, 2010.
  102. G. Ch. Sirakoulis, E. M. Scordilis, and I. Karafyllidis, “An automatic hybrid three-dimensional spatiotemporal model for earthquake activity by the dissociation of seismic data,” accepted for presentation in General Assembly of European Geosciences Union 2010, Natural Hazards, Session NH10.2, (EGU2010-NH10.2), Vienna, Austria, May 2-7, 2010.
  103. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “A Cooperative Robot Path Planner based on Cellular Automata and Artificial Ant Colonies,” in Proceedings of IASTED International Conference on Advances in Computer Science and Engineering (ACSE 2010)“, Sharm El Sheikh, Egypt, March 15-17, 2010.
  104. P. Progias, E. Vardaki, and G. Ch. Sirakoulis, “FPGA Realization of a Cellular Automata Based Epidemic Processor,” in Lecture Notes in Computer Science (LNCS) (PART 2), vol. 6068 of “Workshop on Complex Collective Systems” within the “8th International Conference on Parallel Processing and Applied Mathematics (PPAM 2009)“, pp. 569-574, Wroclaw, Poland, September 13-16, 2009.
  105. P. Chatziagorakis, G. Ch. Sirakoulis, and J. Lygouras, “Automatic generation of Cellular Neural Networks for distributed sensor data processing,” in Proceedings of  “13th Panhellenic Conference on Informatics (PCI 2009)“, pp. 35-39, Corfu, Greece, September 10-12, 2009.
  106. G. Ch. Sirakoulis, I. Karafyllidis, and W. Spataro, “A computational intelligent oxidation process model and its VLSI implementation,” in Proceedings of “2009 International Conference on Scientific Computing (CSC’09)”, pp.329-335, Las Vegas, USA, July 13-19, 2009.
  107. I. G. Georgoudas, P. Kyriakos, G. Ch. Sirakoulis, and I. Andreadis, “A Cellular Automaton Evacuation Model Based on Electric and Potential Fields Technique,” accepted for presentation in First International Conference on Evacuation Modeling (RISE 2008), Delft, The Netherlands, 23-25 September, 2009.
  108. L. Nalpantidis, A. Amanatiadis, G. Ch. Sirakoulis, N. Kyriakoulis and A. Gasteratos, “Dense Disparity Estimation Using a Hierarchical Matching Technique from Uncalibrated Stereo Vision,” in Proceedings of IEEE International Workshop on Imaging Systems and Techniques (IST 2009)”, pp. 427-431, Shenzhen, China, 11-12 May, 2009.
  109. G. Ch. Sirakoulis, “Evolving a three-dimensional cellular automata dynamic system constituted of cells-charges for modelling real earthquake activity,” accepted for presentation in General Assembly of European Geosciences Union 2009, Natural Hazards, Session NH11.12, (EGU2009-NH11.12), Vienna, Austria, April 19-24, 2009.
  110. G. De Cubber, D. Doroftei, L. Nalpantidis, G. Ch. Sirakoulis, and A. Gasteratos, “Stereo-based terrain traversability analysis for robot navigation,” in Proceedings of “International workshop on Robotics for risky interventions and Environmental Surveillance (RISE 2009), Brussels, Belgium, January 12-14, 2009.
  111. A. Amanatiadis, G. Ch. Sirakoulis, and I. Andreadis, “Hardware Implementations of Membership Function Generators for Fuzzy Systems,” accepted for presentation in “16th International Conference on Very Large Scale Integration (IFIP/IEEE VLSI-SoC 2008), Rhodes Island, Greece, 13-15 October 2008.
  112. L. Nalpantidis, G. Ch. Sirakoulis, and A. Gasteratos, ” Dense Stereo Correspondence Algorithm for Hardware Implementation with Enhanced Disparity Selection,” in Lecture Notes in Artificial Intelligence (LNAI), Vol. 5138, 5th Hellenic Conference on Artificial Intelligence 2008 (SETN’08), J. Darzentas et al. (Eds.), pp. 365 – 370, Syros Island, Greece, October 2008.
  113. K. Ioannidis, G. Ch. Sirakoulis, and I. Andreadis, “A Cellular Automaton Collision-Free Path Planner suitable for Cooperative Robotics,” in Proceedings of the 12th Panhellenic Conference on Informatics (PCI 2008), IEEE Computer Society Press, pp. 256-260, Samos Island, Greece, August 2008.
  114. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “Potential Field Approach of a Cellular Automaton Evacuation Model and its FPGA implementation,” in Lecture Notes in Computer Science (LNCS), Vol. 5191, “Second International Workshop on Crowds and Cellular Automata (C&CA-2008)” organized within the 8th International Conference on Cellular Automata for Research and Industry (ACRI2008), H. Umeo, K. Nishinari, T. Komatsuzaki and S. Bandini (Eds.), pp. 546-549, Yokohama, Japan, September 2008.
  115. G. Ch. Sirakoulis, “Automatic Design of FPGA Processor for the Backtracking of DNA Sequences Evolution using Cellular Automata and Genetic Algorithms,” in Lecture Notes in Computer Science (LNCS), Vol. 5191, 8th International Conference on Cellular Automata for Research and Industry (ACRI2008), H. Umeo, K. Nishinari, T. Komatsuzaki and S. Bandini (Eds.), pp. 522-530, Yokohama, Japan, September 2008.
  116. I. G. Georgoudas, G. Ch. Sirakoulis, E. M. Scordilis and I. Andreadis, “Long-range interaction in a 2D cellular automata model of fundamental seismic attributes and parametric optimisation with the use of genetic algorithms,” accepted for presentation in General Assembly of European Geosciences Union 2008, Natural Hazards, Session NH10.03, (EGU2008-NH10.03), Vienna, Austria, April 14-18, 2008.
  117. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “Hardware implementation of a Crowd Evacuation Model based on Cellular Automata,” in Proceedings of the 4th International Conference on Pedestrian and Evacuation Dynamics (PED 2008), pp. 451-463, Wuppertal, Germany, February 27-29, 2008.
  118. G. De Cubber, L. Nalpantidis, G. Ch. Sirakoulis, and A. Gasteratos, “Intelligent Robots need Intelligent Vision: Visual 3D Perception,” in Proceedings of International workshop on Robotics for risky interventions and Environmental Surveillance (RISE 2008), Benicàssim, Spain, January 8-9, 2008.
  119. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “An Intelligent Cellular Automaton Model for Crowd Evacuation in Fire Spreading Conditions,” in Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), IEEE Computer Society Press, Vol. I, pp. 36-43, Patra, Greece, October 2007.
  120. N. Zompakis, L. Papadopoulos, G. Ch. Sirakoulis, and D. Soudris, “Implementing Cellular Automata Modelled Applications into Network-on-Chip Platform,” in Proceedings of International Conference on Very Large Scale Integration 2007 (IFIP VLSI-SoC 2007), pp. 288-291, Atlanta, GA USA, October 2007.
  121. L. Nalpantidis, G. Ch. Sirakoulis, and A. Gasteratos, “Review of stereo matching algorithms for 3D vision,” in Proceedings of the 16th International Symposium on Measurement and Control in Robotics (ISMCR 2007), pp. 116-124, Warsaw, Poland, June 2007.
  122. K. Konstantinidis, G. Ch. Sirakoulis, and I. Andreadis, “An Intelligent Image Retrieval System Based on the Synergy of Color and Artificial Ant Colonies,” in Lecture Notes in Computer Science (LNCS), Vol. 4522, 15th Scandinavian Conference on Image Analysis (SCIA 2007), B.K. Ersbøll and K.S. Pedersen (Eds.), pp. 868-877, Aalborg, Denmark, June 2007.
  123. G. Ch. Sirakoulis, D. Soudris, I. Karafyllidis, and I. Andreadis, “GNS: A Tool for the Analysis of Gene Regulatory Networks,” in Proceedings of the 11th Panhellenic Conference on Informatics (PCI 2007), vol. B, pp. 59-68, Patra, Greece, May 2007.
  124. I. G. Georgoudas, G. Ch. Sirakoulis, E.M. Skordilis, and I. Andreadis, “VLSI implementation perspectives of a two-dimensional cellular automata model for earthquake simulation,” in Proceedings of General Assembly of European Geosciences Union 2007, Natural Hazards, Session NH11.04, (EGU2007-NH11.04), Vienna, Austria, EGU2007-A-08189, April 2007.
  125. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “A Cellular Automaton Crowd Tracking System for Modelling Evacuation Processes,” in Lecture Notes in Computer Science (LNCS), Vol. 4173, “First International Workshop on Crowds and Cellular Automata (C&CA-2006)” organized within the 7th International Conference on Cellular Automata for Research and Industry (ACRI2006), S. El Yacoubi, B. Chopard, and S. Bandini (Eds.), pp. 699-702, Perpignan, France, September 2006.
  126. G. Ch. Sirakoulis, “A Cellular Automata Simulation Tool for Modelling and Automatic VLSI Implementation of the Oxidation Process in Integrated Circuit Fabrication,” in Lecture Notes in Computer Science (LNCS), Vol. 4173, 7th International Conference on Cellular Automata for Research and Industry (ACRI2006), S. El Yacoubi, B. Chopard, and S. Bandini (Eds.), pp. 417-426, Perpignan, France, September 2006.
  127. G. Ch. Sirakoulis, D. Soudris, I. Karafyllidis, and I. Andreadis, “Modelling Gene Regulatory Networks using Cellular Automata,” in Proceedings of 5th European Symposium on Biomedical Engineering (ESBME 2006), P.55, pp. 1-4, Patra, Greece, July 2006.
  128. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “A Simulation Tool for Modelling Pedestrian Dynamics during Evacuation of Large Areas,” in IFIP International Federation for Information Processing, Vol. 204, Artificial Intelligence Applications and Innovations (AIAI 2006), eds. Maglogiannis, I., Karpouzis, K., Bramer, M., (Boston: Springer), pp. 618-626, Athens, Greece, June 2006.
  129. L. Kotoulas, D. Tsarouchis, G. Ch. Sirakoulis, and I. Andreadis, “1-d Cellular Automaton for PseudoRandom Number Generation and its Reconfigurable Hardware Implementation,” in Proceedings of 2006 IEEE International Symposium on Circuits and Systems (ISCAS’2006), pp. 4627-4630, Island of Kos, Greece, May 2006.
  130. I. G. Georgoudas, G. Ch. Sirakoulis, E.M. Skordilis, and I. Andreadis, “Evaluating the role of seismic energy on the behaviour of a Cellular Automata model for real earthquake processes,” in Proceedings of General Assembly of European Geosciences Union 2006, Natural Hazards, Session NH11.01, (EGU2006-NH11.01), Vienna, Austria, EGU-A-7542, April 2006.
  131. M. Mamakou, G. Ch. Sirakoulis, I. Andreadis, and I. Karafyllidis, “Adaptive Reverse Engineering of Gene Regulatory Networks using Genetic Algorithms,” in Proceedings of IEEE International Conference on “Computer as a tool” (EUROCON’2005), pp. 401-404, Belgrade, Serbia & Montenegro, November 2005.
  132. V. Mardiris, G. Ch. Sirakoulis, Ch. Mizas, I. Karafyllidis, and A. Thanailakis, “Net_CA: A Tool for Simulation and Modeling of Wired/Wireless Computer Networks based on Cellular Automata,” in Proceedings of 10th Panhellenic Conference on Informatics (PCI’2005), Volos, Greece, pp. 407-417, November 2005.
  133. Ch. Mizas, G. Ch. Sirakoulis, V. Mardiris, I. Karafyllidis, and A. Thanailakis, “Cellular Automata Evolution for Backtracking the DNA Sequence Evolution,” in Proceedings of 10th Panhellenic Conference on Informatics (PCI’2005), Volos, Greece, pp. 217-224, November 2005.
  134. K. Konstantinidis, G. Ch. Sirakoulis, and I. Andreadis, “Content-Based Image Retrieval using Cellular Automata,” in Proceedings of 5th International Conference on Technology and Automation (ICTA’05), Thessaloniki, Greece, pp. 371-375, October 2005.
  135. L. Kotoulas, A. Gasteratos, G. Ch. Sirakoulis, Ch. Georgoulas, and I. Andreadis, “Enhancement of fast acquired disparity maps using a 1-D Cellular Automaton filter,” in Proceedings of IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP 2005), Benidorm, Spain, pp. 355-359, September 2005.
  136. L. Kotoulas, Ch. Georgoulas, A. Gasteratos, G. Ch. Sirakoulis, and I. Andreadis, “A novel three stage technique for accurate disparity maps” in Proceedings of EOS Conference on Industrial Imaging and Machine Vision at the World of Photonics Congress 2005, Munich, Germany, pp. 13-14, June 2005.
  137. I. G. Georgoudas, G. Ch. Sirakoulis, E.M. Skordilis, and I. Andreadis, “Modelling Xanthi Region’s earthquake activity using a two-dimensional cellular automaton,” in Proceedings of General Assembly of European Geosciences Union 2005, Natural Hazards, Session NH11.01, (EGU2005-NH11.01), Vienna, Austria, EGU-A-7603, pp. 456, April 2005.
  138. I. G. Georgoudas, G. Ch. Sirakoulis, and I. Andreadis, “A Potential – Based Cellular Automaton Model for Earthquake Simulation,” in Proceedings of International Conference of Computational Methods in Science and Engineering 2004 (ICCMSE 2004), Athens, Greece, pp. 185-189, November 2004.
  139. G. Ch. Sirakoulis, I. Karafyllidis, A. Thanailakis, and Ph. Tsalides, “Design of dedicated parallel processors for the simulation of physical processes using cellular automata and genetic algorithms,” in 3rd WSEAS Int. Conf. on Systems Theory and Scientific Computation (ISTASC’03), Rhodes, Greece, November 2003.
  140. G. Ch. Sirakoulis, I. Karafyllidis, A. Thanailakis, and Ph. Tsalides, “A Methodology for Modeling Ecological Systems based on Cellular Automata,” in 3rd WSEAS Int. Conf. on Systems Theory and Scientific Computation (ISTASC’03), Rhodes, Greece, November 2003.
  141. G. Ch. Sirakoulis, “An algorithm for the direct conversion of Boolean expressions into VHDL code,” in 7th WSEAS International Multiconference on Circuits, Systems, Communications and Computers (CSCC 2003), Corfu, Greece, July 2003. Also published in «Computational Methods in Circuits and Systems Applications» (Electrical and Computer Engineering Series, A Series of Reference Books and Textbooks), WSEAS Press, eds.: N. E. Mastorakis, I. A. Stathopulos, C. Manikopoulos, G. E. Antoniou, V. M. Mladenov, I. F. Gonos, pp. 29-33, 2003.
  142. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “A TCAD tool for the simulation of the CVD process based on Cellular Automata,” in Thirteenth European Conference on Chemical Vapor Deposition (EUROCVD13), Athens, Greece, September 2001.
  143. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “Study of the effect of non-planarity and defects on the geometrical accuracy of semiconductor surface structures,” in 5th International Workshop on Expert Evaluation & Control of Compound Semiconductor Materials & Technologies (EXMATEC 2000), Heraklion, Crete, Greece, May 2000.
  144. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “Genetic Partitioning and Placement for VLSI Circuits,” in Proceedings of The Sixth IEEE International Conference on Electronics, Circuits and Systems (ICECS’99), Pafos, Cyprus, vol. III, pp. 1647-50, September 1999.
  145. G. Ch. Sirakoulis, I. Karafyllidis, D. Soudris, N. Georgoulas, and A. Thanailakis, “An oxidation process simulator for TCAD,” in Proceedings of the 20th International Spring Seminar on Semiconductor and Hybrid Technologies Annual School Lectures, Sofia, Bulgaria, vol. ΙΙ, pp. 103-108, September 1998.
  146. G. Ch. Sirakoulis, I. Karafyllidis, and A. Thanailakis, “Genetic Algorithms applications in VLSI physical design,” in Proceedings of the Third Conference and Eight Summer School in Complexity and Chaotic Dynamics of non Linear Systems, Xanthi, July 1995 (in greek).
Aircraft are profitable to their owners as long as they are in the air transporting passengers to their destinations; therefore it is vital to minimize as much as possible their preparation time on the ground. In this paper we simulate different boarding strategies with the help of a model based on cellular automata parallel computational tool, attempting to find the most efficient way to deliver each passenger to her/his assigned seat. Two seat arrangements are used, a small one based on Airbus A320/ Boeing 737 and a larger one based on Airbus A380/ Boeing 777-300. A wide variety of parameters, including time delay for luggage storing, the frequency by which the passengers enter the plane, different walking speeds of passengers depending on sex, age and height, and the possibility of walking past their seat, are simulated in order to achieve realistic results, as well as monitor their effects on boarding time. The simulation results indicate that the boarding time can be significantly reduced by the simple grouping and prioritizing of passengers. In accordance with previous papers and the examined strategies, the outside-in and reverse pyramid boarding methods outperform all the others for both the small and large airplane seat layout. In the latter, the examined strategies are introduced for first time in an analogous way to the initial small seat arrangement of Airbus A320/ Boeing 737 aircraft family. Moreover, since in real world scenarios, the compliance of all the passengers to the suggested group division and boarding strategy cannot be guaranteed, further simulations were conducted. It is clear that as the number of passengers disregarding the priority of the boarding groups increases, the time needed for the boarding to complete tends towards that of the random boarding strategy, thus minimizing the possible advantages gained by the proposed boarding strategies.
MapReduce is a programming framework for distributed systems that is used to automatically parallelize and schedule the tasks to distributed resources. MapReduce is widely used in data centers to process enterprise databases and Big Data. This paper presents a novel MapReduce accelerator platform based on FPGAs that can be used to speedup the processing of the MapReduce data. The proposed platform consists of specialized hardware accelerators for the Map tasks and a shared configurable accelerator for the Reduce tasks. The hardware accelerators for the Map tasks are developed using a modified source-tosource High-level Synthesis (HLS) tool while the Reduce accelerator is based on a novel hashing scheme. The proposed scheme is implemented, mapped and evaluated to a Virtex 7 FGPA. The performance evaluation is based on a benchmark suite that represent typical MapReduce applications and it shows that the proposed scheme can achieve up to 2 orders of magnitude energy reduction compared to General Purpose Processors (GPPs).
The recent discovery of the memristor has renewed the interest for fast arithmetic operations via high-radix numeric systems. In this direction, a conceptual solution for high-radix memristive arithmetic logic units (ALUs) was recently published. The latter combines CMOS circuitry for data processing and a reconfigurable “segmented” crossbar memory block. In this paper we build upon such a conceptual design and propose a 3D extension of the classic crossbar topology via 2T1M cross-points which still permits the parallel creation of partial products for faster multiplication with lower circuit complexity. Furthermore, we present a binary to high-radix data conversion circuit to complement the stateprogramming module of the previous work. A simulation-based validation of read/write multi-level memory operations from/to the 2T1M 3D memristive crossbar was performed using SPICE and a thresholdtype switching model of a bipolar voltage-controlled memristor. Such realization of in-memory computations could lead to faster arithmetic algorithms in future memristive ALUs.
This article is a comprehensive review of the state-of-the art of memristor-based logic circuit design concepts of the recent literature. Amongst all the identified circuit design approaches, those discussed here are all based on collective memristive dynamics and share a number of common characteristics which facilitate their comparison. The focus is on the evolution of the memristor-based logic circuit design strategies from the early proposed sequential stateful logic up to most recently published design schemes which support parallel processing of the applied input signals. The main operational properties of all the selected computational concepts are presented in an accessible manner, aiming to serve as an informative cornerstone for students and scientists who wish to get involved in emerging memristive logic circuit research and development.
In this paper, an intelligent forecasting model, a recurrent neural network (RNN) with nonlinear autoregressive architecture, for daily and hourly solar radiation and wind speed prediction is proposed for the enhancement of the power management strategies (PMSs) of hybrid renewable energy systems (HYRES). The presented model (RNN) is applicable to an autonomous HYRES, where its estimations can be used by a central control unit in order to create in real time the proper PMSs for the efficient subsystems’ utilization and overall process optimization. For this purpose, a flexible network-based design of the HYRES is used and, moreover, applied to a specific system located on Olvio, near Xanthi, Greece, as part of Systems Sunlight S.A. facilities. The simulation results indicated that RNN is capable of assimilating the given information and delivering some satisfactory future estimation achieving regression coefficient from 0.93 up to 0.99 that can be used to safely calculate the available green energy. Moreover, it has some sufficient for the specific problem computational power, as it can deliver the final results in just a few seconds. As a result, the RNN framework, trained with local meteorological data, successfully manages to enhance and optimize the PMS based on the provided solar radiation and wind speed prediction and make the specific HYRES suitable for use as a stand-alone remote energy plant.
The aim of this paper is to develop an integrated electronic system that allows the dynamical management of congestion and provides the fast evaluation of dynamical circumstances. Thus, a cellular-automata-based model is proposed that estimates the movement of individuals. The presented system incorporates a process that allows the efficient camera-based initialization of the model, without any special prerequirements. The efficiency of the model has been thoroughly validated. Specifically, simulation-derived diagrams that depict the relationship of flow and speed of people as a function of crowd density have been compared with corresponding diagrams from the literature. Furthermore, the system has been evaluated with the use of real data. In particular, simulation results have been compared with real video recordings that depict the crowd evacuation process from a football stadium. Results prove that the proposed management system can estimate fast possible routes of people for the very near future, evaluating all possible exit alternatives. Finally, the proposed model has been implemented in hardware with a field-programmable gate array, enabling its incorporation into an integrated electronic system that estimates crowd movement and prevents congestion in exits almost in real time. The proposed electronic system is advantageous in terms of easy incorporation and portability as well as performance when compared with its analogous graphical-processing-unit implementation.
This paper presents a Cellular Automata (CA) based model that simulates movement of pedestrians with motion difficulties, such as elderly people and further focuses on how such groups can be guided within specific areas, as for example a nursing home. The model is originated by a virtual potential field. The aim of the model is to provide valuable information regarding the dynamics of their motion and to propose advanced layout settings of the corresponding places, in order to optimize the safety levels. Various scenarios are studied that include different layouts, presence of obstacles, group categorisation, crowd guiding and fire spreading. Simulation results confirm that the model can be proven a helpful tool, in order spatial parameters that affect evacuation time to be defined as well as personnel to be trained in guiding weak people.
Clock gating (CG) is a widely used design method for reducing the dynamic power consumption in digital circuits. Although it is a mature technique, theoretical work and tools for its application are still evolving and considered a matter of ongoing research, due to its significant effect in the overall power of the designs under study. This paper introduces a detailed review of the spectrum of CG approaches, theoretical and practical, from an architectural and register transfer level to synthesis, place and route, and testing issues. Furthermore, tools availability, limitations, and requirements concerning CG are examined for each design flow step. Conclusively, an evaluation of the presented techniques and literature is provided, estimating their usefulness and identifying areas for future research, exploration, and automation.
With the advent of massively parallel scientific computation, the parallel generation of pseudorandom numbers has become essential. During the last decades several researchers have successfully implemented Cellular Automata (CA) as Pseudorandom Number Generators (PRNGs). On the other hand, recently Autonomous DNA Turing Machines and DNA Cellular Automata were proposed as cellular computing devices that can serve as reusable, compact computing devices to perform (universal) computation. In this paper, we introduce a methodology for the design of one-dimensional (1-d) Hybrid Autonomous DNA Cellular Automata (HADCA), able to run in parallel, different CA rules with certain modifications on their molecular implementation and information flow compared to their origins. In this aspect, an easy to use HADCA simulator was developed to encourage the possible use of the biological inspired computation tool. As a result, the proposed 1-d HADCAs are used to generate high-quality random numbers which can pass the statistical tests of DIEHARD, one of the most well known general test suites for randomness, proving their suitability as PRNGs.
Recent computing architectures are implemented by shared memory technologies to alleviate the high latency experienced by off-chip memory transfers, but the high architectural complexity of modern multicore processors has presented many questions. To tackle the design of efficient algorithms scheduling workloads over available cores, this article presents a parallel bioinspired model that simulates the utilization of shared memory on multicore systems. The proposed model is based on cellular automata (CA) and coupled with game theory principles. CA are selected due to their inherent parallelism and especially their ability to incorporate inhomogeneities. Furthermore, the novelty of the model is realized on the fact that multilevel CA are used to simulate the different levels of cache memory usually found in multicore processors. These characteristics make the model able to cope with the increasing diversity of cache memory hierarchies on modern and future processors. Nonetheless, by acquiring data from hardware performance counters and processing them with the proposed model online, the performance of the system can be calculated and a better scheduling strategy can be adopted in real time. The CA-based model was verified on the behavior of a real multicore system running amultithreaded application, and it successfully simulated the acceleration achieved by an increased number of cores available for the execution of the workload. More specifically, the example of common pool resource from game theory was used with two variations: a static and a variable initial endowment. The static variation of the model approximates slightly better the acceleration of a workload when the number of available processor cores increases, whereas the dynamic variation simulates better the moderate differences due to operation system’s scheduler alternations on the same amount of cores.
Resistive random access memory (ReRAM), referred to as memristor, is an emerging memory technology to potentially replace conventional memories, which will soon be facing serious design challenges related to continued scaling. Memristor-based crossbar architecture has been shown to be the best implementation for ReRAM. However, it faces a major challenge related to the sneak current (current sneak paths) flowing through unselected memory cells, which significantly reduces the voltage read margins. In this paper, five alternative architectures (topologies) are applied to minimize the impact of sneak current; the architectures are based on the introduction of insulating junctions within the crossbar. Simulations that were performed while considering different memory accessing aspects, such as bit reading versus word reading, stored data background distribution, crossbar dimensions, etc., showed that read margins can be increased significantly (up to 4×) as compared with standard crossbar architectures. In addition, the proposed architectures eliminate the requirement for extra select devices at each cross point and have no operational complexity overhead.
During last decades, Cellular Automata (CAs) as bio-inspired parallel computational tools have been proven rather efficient and robust on modeling and simulating many different physical processes and systems and solving scientific problems, in which global behavior arises from the collective effect of simple components that interact locally. Among others of most renowned and well established CA applications, crowd evacuation and pedestrian dynamics are considered ones of the most timely and lively topics. Numerous models and computational paradigms of CAs either as standalone models or coupled with other theoretical and practical modeling approaches have been introduced in literature. All these crowd models are taking advantage of the fact that CA show evidence of a macroscopic nature with microscopic extensions, i.e. they provide adequate details in the description of human behavior and interaction, whilst they retain the computational cost at low levels. In this aspect, several CA models for crowd evacuation focusing on different modeling principles, like potential fields techniques, obstacle avoidance, follow the leader principles, grouping and queuing theory, long memory effects, etc. are presented in this paper. Moreover, having in mind the inherent parallelism of CA and their straightforward implementation in hardware, some anticipative crowd management systems based on CAs are also shown when operating on medium density crowd evacuation for indoor and outdoor environments. Real world cases and different environments were examined proving the efficiency of the proposed CA based anticipative systems. The proposed hardware implementation of the CAs-based crowd simulation models is advantageous in terms of low-cost, high-speed, compactness and portability features. Finally, robot guided evacuation with the help of CAs is also presented. The proposed framework relies on the well established CAs simulation models, while it employs a real-world evacuation implementation assisted by a mobile robotic guide, which in turn guides people towards a less congestive exit at a time.
Phoenix MapReduce is a multi-core programming framework that is used to automatically parallelize and schedule programs. This paper presents a novel scratchpad memory architecture that is used accelerate MapReduce applications by indexing and processing the key/value pairs. The proposed scratchpad memory scheme can be mapped onto programmable logic or multi-core processors chips as a coprocessor to accelerate MapReduce applications. The proposed architecture has been implemented in a Zynq FPGA with two embedded ARM cores. The performance evaluation shows that the proposed scheme can reduce up to 2.3× the execution time and up to 1.7× the energy consumption.
The wasteful consumption of freshwater in heavily populated coastal areas usually consist the basic reason for the intrusion of saltwater into the coastal aquifers. In order to avoid such catastrophic scenarios, their prediction is of utter significance. Underground water systems are highly complex and the water flow is extremely dynamic, thus making the prediction of this phenomenon a difficult task. For this reason, a two dimensional Cellular Automaton (CA) was designed enabling both the qualitative and quantitative simulation and illustration of the saltwater intrusion into an unconfined coastal aquifer. The presented results ensure the robustness of the proposed CA model taking full advantage of its inherent parallelism and local connectivity.
Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of a cellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould.
Cellular automata (CAs) have been widely used to model and simulate physical systems and processes. CAs have also been successfully used as a VLSI architecture that proved to be very efficient at least in terms of silicon-area utilization and clock-speed maximization. Quantum cellular automata (QCAs) as one of the promising emerging technologies for nanoscale and quantum computing circuit implementation, provides very high scale integration, very high switching frequency and extremely low power characteristics. In this paper we present a new automated design architecture and a tool, namely DATICAQ (Design Automation Tool of 1-D CAs using QCAs), that builds a bridge between 1-D CAs as models of physical systems and processes and 1-D QCAs as nanoelectronic architecture. The QCA implementation of CAs not only drives the already developed CAs circuits to the nanoelectronics era but improves their performance significantly. The inputs of the proposed architecture are CA dimensionality, size, local rule, and initial and boundary conditions imposed by the particular problem. DATICAQ produces as output the layout of the QCA implementation of the particular 1-D CA model. Simulations of CA models for zero and periodic boundary conditions and the corresponding QCA circuits showed that the CA models have been successfully implemented.
Safe evacuation of people from building and outdoor environments, and search and rescue operations, always will remain actual in course of all socio-technological developments. Modern facilities offer a range of automated systems to guide residents towards emergency exists. The systems are assumed to be infallible. But what if they fail? How occupants not familiar with a building layout will be looking for exits in case of very limited visibility where tactile sensing is the only way to assess the environment? Analogous models of human behaviour, and socio-dynamics in general, are provided to be fruitful ways to explore alternative, or would-be scenarios. Crowd, or a single person, dynamics could be imitated using particle systems, reaction–diffusion chemical medium, electro-magnetic fields, or social insects. Each type of analogous model offer unique insights on behavioural patterns of natural systems in constrained geometries. In this particular paper we have chosen leeches to analyse patterns of exploration. Reasons are two-fold. First, when deprived from other stimuli leeches change their behavioural modes in an automated regime in response to mechanical stimulation. Therefore leeches can give us invaluable information on how human beings might behave under stress and limited visibility. Second, leeches are ideal blueprints of future soft-bodied rescue robots. Leeches have modular nervous circuitry with a rich behavioral spectrum. Leeches are multi-functional, fault-tolerant with autonomous inter-segment coordination and adaptive decision-making. We aim to answer the question: how efficiently a real building can be explored and whether there any dependencies on the pathways of exploration and geometrical complexity of the building. In our case studies we use templates made on the floor plan of real building.
A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach.
Due to its unexpected computing abilities, Physarum polycephalum, a vegetative stage of acellular slime, has been repeatedly used during the last decade in order to reproduce transport networks. After conducting a series of biological experiments and with the help of a Cellular Automata (CA) model we try to explore the ability of the slime in order to imitate the Roman road network in the Balkans, an area which was of great strategic importance for the stability of the Roman Empire in the East. The application of Physarum machines hopes to offer a first step towards a new interdisciplinary, almost unconventional, approach to archaeology.
In this paper we present a model based on the parallel computational tool of cellular automata (CA) capable of simulating the process of disembarking in a small airplane seat layout, corresponding to Airbus A320/ Boeing 737 layout, in search of ways to make it faster and safer under normal evacuation conditions, as well as emergency scenarios. The proposed model is highly customizable, with the number of exits, the walking speed of passengers, depending on their sex, age and height, and the effects of retrieving and carrying luggage. Additionally, the presence of obstacles in the aisles as well as the emergence of panic being parameters whose values can be varied in order to enlighten the disembarking and emergency evacuation processes are considered in detail. The simulation results were compared to existing aircraft disembarking and evacuation times and indicate the efficacy of the proposed model in investigating and revealing passenger attributes during these processes in all the examined cases. Moreover, we parallelized our code in order to run on a graphics processing unit (GPU) using the CUDA programming language, speeding up the simulation process. Finally, in order to present a fully dynamical anticipative real-time system helpful for decision-making we implemented the proposed CA model in a field programmable gate array (FPGA) device, and recreated the results given by the software simulations in a fraction of the time. We then compared and exported the performance results among a sequential software implementation, the implementation running on a GPU, and a hardware implementation, proving the consequent acceleration that results from the parallel CA implementation in specific hardware.
In the last decade the amount of the stored data related to almost all areas of life has rapidly increased. However, the overall process of discovering knowledge from data demands more powerful clustering techniques to ensure that this knowledge is useful. In this paper, two nature inspired computation techniques, Cellular Automata (CA) and Ant Colonies are combined by taking advantage of their common prominent features, such as simplicity, locality and self organization. Inspired by the cellular ants algorithm of Vande Moere and Clayden which has designed for clustering purposes, a corresponding cellular ants model was developed in order to overcome some of the previous model limitations and to provide new insights in cellular ants based clustering. The presented simulation results prove the clustering efficiency of the proposed model in both qualitative and quantitative terms.
The recent discovery of the ‘modern’ memristor has drawn great attention of both academia and industry. Given their favorable performance merits, memristors are expected to play a fundamental role in electronic industry. Modeling of memristive devices is essential for circuit design, and a number of Simulation Program with Integrated Circuit Emphasis (SPICE) models have already been introduced. The common problem in most models is that there is no threshold consideration; hence, only a few address the nonlinear nature of the device. This paper aims to present a SPICE implementation of a threshold-type switching model of a voltage-controlled memristive device that attributes the switching effect to a tunneling distance modulation. Threshold-type switching is closer to the actual behavior of most experimentally realizable memristive systems, and our modeling approach addresses the issue of programming thresholds. Both the netlist and the simple schematic are provided, thus making it easy to comprehend and ready to be used. Compared with other modeling solutions, it involves significantly low-complexity operation under an unlimited set of frequencies, and its simulation results are in good qualitative and quantitative agreement with the theoretical formulation. The proposed model is used to simulate an antiserial memristive switch, proving that it can be efficiently introduced in complex memristive circuits.
The congregation of crowd undoubtedly constitutes an important risk factor, which may endanger the safety of the gathered people. The solution reported against this significant threat to citizens safety is to consider careful planning and measures. Thereupon, in this paper, we address the crowd evacuation problem by suggesting an innovative technological solution, namely, the use of mobile robot agents. The contribution of the proposed evacuation system is twofold: (i) it proposes an accurate Cellular Automaton simulation model capable of assessing the human behavior during emergency situations and (ii) it takes advantage of the simulation output to provide sufficient information to the mobile robotic guide, which in turn approaches and redirects a group of people towards a less congestive exit at a time. A custom-made mobile robotic platform was accordingly designed and developed. Last, the performance of the proposed robot guided evacuation model has been examined in real-world scenarios exhibiting significant performance improvement during the crucial first response time window.
Several studies present methods to economize energy in wireless sensor networks (WSNs) which is one of the most confining resources in these systems. This paper presents a bioinspired, cellular automata (CA) based model for constructing data trees that connect all nodes with a sink node. Nonetheless, the proposed model takes into consideration not only the proximity between two nodes but also their remaining available energy. Consequently, by avoiding nodes with nearly depleted energy sources, the life time of the network can be prolonged. The plasmodium of Physarum polycephalum is the inspiration for the proposed model, as it has proved its robustness in graphically expressed problems. Moreover, CAs are able to encapsulate the parallel dynamics of the model and, thus, achieve a very fast execution.
Purpose: The plasmodium of slime mould Physarum polycephalum is a multinucleate single celled organism which behaves as a living amorphous unconventional computing substrate. As an excitable, memristive cell that typically assumes a branching or stellate morphology, slime mould is a unique model organism that shares many key properties of mammalian neurons. There are numerous studies that reveal the computing abilities of the plasmodium realized by the formation of tubular networks connecting points of interest. Recent research demonstrating typical responses in electrical behaviour of the plasmodium to certain chemical and physical stimuli has generated interest in creating an interface betweenP. polycephalum and digital logic, with the aim to perform computational tasks with the resulting device. Methods: Through a range of laboratory experiments, wemeasure plasmodial membrane potential via a non-invasive method and use this signal to interface the organism with a digital system. Results: This digital system was demonstrated to perform predefined basic arithmetic operations and is implemented in a field-programmable gate array (FPGA). These basic arithmetic operations, i.e. counting, addition, multiplying, use data that were derived by digital recognition of membrane potential oscillation and are used here to make basic hybrid biologicalartificial sensing devices. Conclusions: We present here a low-cost, energy efficient and highly adaptable platform for developing next-generation machine-organism interfaces. These results are therefore applicable to a wide range of biological/medical and computing/electronics fields.
In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic the Physarum’s behaviour. In particular, the proposed CA model takes into account while mimicking the Physarum foraging process, the food diffusion, the organism’s growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model’s efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity–density and flow–density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several real Physarum experiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently the Physarum’s recorded behaviour derived from observation of the aforementioned biological laboratory experiments.
During the past decades, computer science experts were inspired from the study of biological organisms. Moreover, bio-inspired algorithms were produced that many times can give excellent solutions with low computational cost in complex engineering problems. In our case, the plasmodium of Physarum polycephalum is capable of finding the shortest path solution between two points in a labyrinth. In this study, we implement a Cellular Automata (CA) model in hardware, which attempts to describe and, moreover, mimic the behavior of the plasmodium in a maze. Beyond the successful implementation of the CA-based Physarum model in software, in order to take full advantage of the inherent parallelism of CA, we focus on a Field Programmable Gate Array (FPGA) implementation of the proposed model. Namely, two different implementations were considered here. Their difference is on the desired precision produced by the numerical representation of CA model parameters. Based on the corresponding results of the shortest path in the labyrinth,the modeling efficiency of both approaches was compared depending on the resulting error propagation. The presented FPGA implementations succeed to take advantage of the CA’s inherit parallelism and improve the performance of the CA algorithm when compared with software in terms of computational speed and power consumption. As a result, the implementations presented here, can also be considered as a preliminary CA-based Physarum polycephalum IP core which produces a biological inspired solution to the shortest-path problem.
This work focuses on the creation of logic circuits by employing the collective dynamics of assembles of reciprocal memristors. A novel circuit design methodology is described where the computing systems comprise passive memristors interfaced with active CMOS circuitry, working under already known circuit design principles from the CMOS technology. The accuracy and completeness of this straightforward methodology is demonstrated through SPICE simulations which are based on a threshold-type device model for memristors. Overall, this work contributes to the creation of proper methodologies which will enable the development of efficient design flows for circuits and architectures comprising memristors.
Slime mould Physarum polycephalum is a single cell visible by unaided eye. When spanning sources of nutrients the slime mould builds a network of protoplasmic tubes which is sometimes considered to be optimal in terms minimization of metabolite transportation time and distance away from repellents. Previously we have shown that the slime mould is efficient in imitating formation of man-made road networks in major countries, where major urban areas are sources of nutrients. We used a similar approach to grow slime mould on a three-dimensional template of Moon to speculate on potential colonization scenarios. The slime mould imitated propagation of colonisation in an exploratory mode, i.e. without any definite targets. Additional transportation hubs/targets were added after the initial network was formed, to imitate the development of colonies in parallel to slime mould growth. We provide analyses of proximity graphs representing colonisation networks and support the findings with Physarum-inspired algorithms to inform supply chain design. Based on laboratory experiments with Physarum interacting with chemical components we speculate on how living Physarum, or its incorporation into a polymer hybrid material, can be used as a wearable smart wetware.
This brief contributes to the design of computational and reconfigurable structures that exploit unique threshold-dependent switching response of single memristors and their compositions. A new logic circuit design paradigm, which assumes parallel processing of input signals, is proposed, along with a methodology for the construction of robust programmable composite memristive switches of variable precision. This methodology is applied to the design of memristive computing circuits. A SPICE simulation-based validation of the proposed circuits and systems is provided.
A novel memristor-based circuit-level cellular automata (CA)-inspired approach to the solution of the classic sorting problem of n Keys in a linear array is presented. The presented system utilises the structural simplicity of CA combined with the threshold-type switching behaviour of memristors and composite memristive components; the latter is used for both information encoding and computation. The focus is on a threshold-type model for memristors for the implementation of the fundamental CA cell and the overall CA operation is verified via simulations.
Physarum polycephalum has repeatedly, during the last decade, demonstrated that has unexpected computing abilities. While the plasmodium of P. polycephalum can effectively solve several geographical described problems, like evaluating human–made transport networks, a disadvantage of a biological computer, like the aforementioned is directly apparent; the great amount of time needed to provide results. Thus, the main focus of this paper is the enhancement of the time efficiency of the biological computer by using conventional computers or even digital circuitry. Cellular automata (CA) as a powerful computational tool has been selected to tackle with these difficulties and a software (Matlab) CA model is used to produce results in shorter time periods. While the duration of a laboratory experiment is occasionally from 3 to 5 days, the CA model, for a specific configuration, needs around 40 s. In order to achieve a further acceleration of the computation, a hardware implementation of the corresponding CA software based model is proposed here, taking full advantage of the CA inherent parallelism, uniformity and the locality of interconnections. Consequently, the digital circuit designed can be used as a massively parallel nature inspired computer for real–time applications. The hardware implementation of the model needs six orders of magnitude less time than the software representation. In this paper, in order to develop a proof of concept and depict the applicability of the proposed hardware oriented CA approach, the topology of Greece is used as an input of the biological computer. The network formed by the in vitro experiments, along with the one designed by the CA model and implemented in hardware are compared with the real motorways and the proximity graphs of the topology.
The unique adaptive properties of memory resistors (memristors) are ideal for use in computational architectures. Multiple interconnected memristors demonstrate complicated overall behavior which significantly improves the efficiency of logic operations via massive parallelism. Nowadays, within an ever-growing variety of memristive systems, most of the research has so far focused on the properties of the individual devices; little is known about the extraordinary features of complex memristive networks and their application prospects. The composite characteristics of regular and irregular memristive networks are explored in this work. A generalized concept for the construction of composite memristive systems, efficiently built out of individual memristive devices, is presented. A new type of threshold-dependent programmable memristive switches, presenting different electrical characteristics from their structural elements, is proposed. As an example of the introduced approach, a SPICE simulation-based evaluation of several programmable analog circuits is presented. The proposed circuit design approach constitutes a step forward towards novel memristor-based nanoelectronic computational systems and architectures.
During the past years, Cellular Automata (CAs) have been extensively used for modeling of many complex systems and processes with great success. In this paper, we study a Cellular Automaton (CA) model for the influence of employees’ behavior in a parameterized workplace environment taking into account different behavioral characteristics. In specific, we model employees’ interactions based on their influence radius, the degree of their willingness on adaption of organizational norms and the employee’s attitude in general in the under study workplace. The proposed CA model is taking into account employee loyalty, a combined statistic of the employee behavior and her/his insistence and company policies applied to the employees so as to restrain unwanted or impose desirable behavioral patterns in correspondence to the organization norms. Conclusively, the CA model facilitates the presentation and simulation of a workplace with a variety of employee behavioral characteristics and under adaptable company policies. Different workplaces were used to illustrate the simulation of employee behavior with CA model. As a result, the proposed model was practically used on two levels, firstly to estimate the workplace robustness and secondly to illustrate workspace dynamics. Finally, the CA model has been utilized to simulate behavioral patterns at a small enterprise in Greece. In specific, based on the employees answers to detailed surveys the CA model was initialized and then applied to describe the behavioral traits of the under study company employees. Finally, the proposed model, in all the examined cases can be utilized in conjunction with applied employee management techniques to facilitate managerial decisions and forecast the impact of employee behavioral changes and company decisions.
This work explores anti-serial (anti-parallel) memristive switches – ASMs (APMs) – as potential cross-point elements in nano-crossbar resistive random access memory arrays. The memory operation principles for both device combinations are shown in detail. The effectiveness of these memristive structures to the solution of the parasitic conducting (current sneak-paths) problem is presented via an analytical approach which is based on the basic setup of resistive crossbar memories. Simulation results of crossbars of up to 4096 elements, arranged in quadratic configurations, are conducted. The provided results supplement this comprehensive analysis of APMs and ASMs, outlining their overall performance characteristics and commenting on their applicability to the practical realization of large crossbar memory systems. Finally, a special array topology is applied to an ASM-based crossbar memory. Its performance is compared to the performance of the pure ASM-based memory. The conducted simulations reveal significantly improved read-out voltage margins which further contribute to addressing the parasitic current paths which prevent the reliable operation of memristive crossbar circuit topologies.
Analysis of crowd density has emerged nowadays as a hot topic issue related to the crowd safety and comfort and directly depended on the design and the operation of the crowded places under study. Usually multiple camera networks are employed to cover, monitor and improve the safety of people in large multifunctional crowded buildings. On the other hand, the art gallery problem is a computational geometry approach to a classical real-world visibility challenge. In a nutshell, it concerns the minimization of the free moving guards required to observe the entire gallery. In this paper we attempt to approach this problem from a novel perspective. To begin with, the number of guards are replaced by multiple cameras whose number should be minimized. At the same time, the observability of the camera network in the available space should be dynamically maximized, so as to observe the evolving density of the crowded areas adequately. In order to achieve this objective a twofold bio-inspired method is described and implemented, based on the emergent computation of swarms to come up with solutions in complex mathematical problems. More specifically, the observations on bumblebee colonies lead us firstly to the definition of artificial bumblebee agents used to determine the number of cameras needed to maximize the observability of a space given the safety specifications emerged from the crowd analysis. Secondly, the way the spiders wave their webs was used as a source of inspiration to determine the exact positions of the cameras in the given space by artificial spider agents. The feedback of the algorithm is then used to cover the areas with significant crowd density in a dynamic fashion. Experimental results show that the algorithm is capable of producing promising results where the areas with the maximum crowd density are continuously detected and covered in a dynamic way.
The existence of the fourth fundamental circuit element, the memristor, was first postulated over 30 years ago by Leon Chua. The implementation of the first “modern” memristor prototype by Hewlett Packard Laboratories in 2008 initiated a great scientific interest for these unique nano-electronic devices and currently, there is a growing variety of systems that exhibit memristive behavior. However, most of the research has focused on the properties of the single devices, therefore very little is known about their response when these devices are organized into networks. In this work, the composite characteristics of memristive elements connected in network configurations are studied and the relationships among the single devices are investigated. We finally show how the threshold-dependent nonlinear memristive behavior could be elaborated to make possible the development of novel and sophisticated digital/analog memristive nano-systems.
In this paper, an innovative bio-inspired unconventional approach to tackle with the Simultaneous Localization and Mapping (SLAM) task is presented. The proposed method draws inspiration from the slime mold Physarum polycephalum by utilizing the computational tool of Cellular Automata (CA). In particular, a fully autonomous robot, equipped only with an omni-directional camera, explores and maps successfully an indoor unknown terrain by adopting the behaviour of the microorganism Physarum polycephalum, namely its olfaction, its propagation and foraging process. The Physarum’s sense of olfaction corresponds to the robots unique sensor, namely an omni-directional camera and the foraging as well as the movement procedure of the organism in terms of robots SLAM is matched with the detection and mapping of an unknown space and the movement strategy, respectively. Moreover, the diffusion field of the plasmodium corresponds to the robots field of view. In order to evaluate the proposed approach several experiments are drawn, that indicate the ability of the presented model to effectively and efficiently achieve its goals. The obtained results were compared to the corresponding ones produced by the random movement algorithm as well as by an exhaustive search algorithm. In all the examined cases, the presented simulation results reveal the strength and the superiority of the proposed method.
The crossbar architecture is viewed as the most likely path towards novel nanotechnologies which are expected to continue the technological revolution. Memristor-based crossbars for integrating memory units have received considerable attention, though little work has been done concerning the implementation of logic. In this work we focus on memristor-based complex combinational circuits. Particularly, we present a design methodology for encoder and decoder circuits. Digital encoders are found in a variety of electronics multi-input combinational circuits (e.g. keyboards) nowadays, converting the logic level ‘1’ data at their inputs into an equivalent binary code at the output. Their counterparts, digital decoders, constitute critical components for nanoelectronics, mainly in peripheral/interface circuitry of nanoelectronic circuits and memory structures. The proposed methodology follows a CMOS-like design scheme which can be used for the efficient design and mapping of any 2n×n (n×2n) encoder (decoder) onto the memristor-based crossbar geometry. For their implementation, a hybrid nano/CMOS crossbar type with memristive cross-point structures and available transistors is elaborated, which is a promising solution to the interference between neighboring cross-point devices during access operation. Circuit functionality of the presented encoder/decoder circuits is exhibited with simulations conducted using a simulator environment which incorporates a versatile memristor device model. The proposed design and implementation paradigm constitutes a step towards novel computational architectures exploiting memristor-based logic circuits, and facilitating the design and integration of memristor-based encoder/decoder circuits with nanoelectronics applications of the near future.
Following the leader is a bio–inspired technique that is intuitively adopted by living organisms when moving together. Trying to emulate physical processes, the proposed here Cellular Automaton (CA) model aims at crowd movement simulation by embedding the follow–the–leader technique as its fundamental driving mechanism. Prominent characteristics of the collective motion of biological organisms are apparent to the simulation process. Macroscopically, the study focuses on the emergence of qualitative attributes of crowd behaviour, such as collective effects, random to coherent motion due to a common purpose and transition to incoordination (arching) due to clogging. Microscopically, all configurations of the CA model are triggered by simple rules applied locally to each of the group members. These CA rules are enhanced with memory capacity to gain back model’s reversibility and prevent group members from self–entrapment. The inherent attributes of CA allowed the development of a micro–operating model that presents macro–features. Different simulation scenarios validate the response of the presented model.
The recent discovery of the first modern prototype of the 4th fundamental circuit element by HP Laboratories turned the attention of both academia and industry to today’s broad classification of resistance switching devices, known as memristive devices and systems. The variety of applications which have been proposed recently, ranging from memory and reconfigurable architectures to neuromorphic learning and computing, is characteristic of the intense developing interest of these novel electronic devices which show excellent scalability, fast switching speed, long retention time and endurance. The primary purpose of this short review is to summarize and discuss a set of recent patents describing the progress towards the implementation of novel computational architectures, comprising memristive elements, and their applications, where the favorable characteristics of memristors and their nonvolatility are exploited.
In this paper, a model based on Cellular Automata (CAs) for predicting wildfire spreading is presented. The proposed model is inspired by existing fire spread models, but also includes a number of changes and additions, compared to them. Primary goal of the paper is to design and implement a software-based model as well as a corresponding hardware-based one that will sufficiently describe real fires, but will also have less stringent requirements on computational resources and computational power for execution. Therefore, an effort has been made to minimize the complexity of the model and the resulting computational burden aiming at an implementation that will have a practical significance in predicting the evolution of a fire. The proposed model is implemented on an Altera®Stratix IV®FPGA (Field-Programmable Gate Array), designed to execute in a parallel way in order to produce valuable information in real time that can be used to optimize response to a fire crisis. The FPGA design results from the automatically produced synthesizable VHDL code of the CA model and is advantageous in terms of low-cost, high speed and portability. The resulting implementation sufficiently depicts the natural phenomenon of wildfire spreading and provides short calculation times. Finally, the presented FPGA implementation of the proposed CA model offers the possibility a portable system to be designed, connected with GPS as well as GIS and/or wind monitoring systems able to provide real-time information concerning the wildfire propagation on the under test area.
The creation of collision-free paths for mobile robots, also known as the path planning problem, is a vibrant research field of robotics. Most related approaches for robotic teams display an increment of their total complexity due to the cooperative tasks that must be simultaneously achieved such as forming specific patterns. In addition, these methods extensively bind resources of the system in order to be fully functional and thus, no further tasks could be performed. In this paper, a path planning approach based on Cellular Automata (CA) is introduced. The proposed method assumes that a predefined distance must be covered by a team of robots while preserving their initial formation through cooperations. Due to its simplicity, the resulted computational burden permits the implementation of different methods in the same system in order to accomplish further tasks including image processing techniques. The usage of multiple digital cameras is one of the most interesting aspects of the image processing research area; nevertheless, in mobile robotics, miniature robots are equipped with low resolution cameras constraining the range of image processing applications. In order to preserve the total computational burden and produce higher resolution images, a CA-based image resizing method is inserted in the same cooperative robot system. Higher resolution images could be further processed to attain area measurements, panoramic images etc. Exploiting the inherit parallelism of the CA, both approaches could be executed concurrently. Results indicate that the total CA architecture outcomes low computational cost leading to an appropriate scheme for miniature robots functionality while both paths are properly created and the resolution of the captured images is sufficiently increased.
Among different traffic features, the urban traffic has received a lot of attention due to the ongoing traffic congestion as a result of increased car usage, population growth, and changes in population density. In urban networks, the vehicles flow differs when compared with highways flow because of the freeway’s low speed limit but mostly because of the traffic lights control. In this paper, a real-time hardware implemented bio-inspired model for traffic lights control is presented. The proposed model arrives from Cellular Automata (CAs), which have been proven very flexible and powerful computational traffic models, in that they are able to capture all previously mentioned basic phenomena that occur in traffic flows. The resulting CA model was hardware implemented on FPGA to take full advantage of the inherent parallelism of the CAs and to support the function of an advanced electronic system able to provide real-time adaptive control of traffic lights designed to consider traffic conditions for the whole intersections. The analytical results, obtained by application of the aforementioned FPGA CA processor are found in excellent agreement with the numerical simulations.
Over 30 years ago L. Chua proposed the existence of a new class of passive circuit elements, which he called memristors and memristive devices. The unique electrical characteristics associated with them, along with the advantages of crossbar structures, have the potential to revolutionize computing architectures. A well-defined and effective memristor model for circuit design combined with a design paradigm based on well-understood underlying logic design principles would certainly accelerate research on nanoscale circuits and systems. Toward this goal, we propose a memristor crossbar circuit design paradigm in which memristors are modeled using the quantum mechanical phenomenon of tunneling. We use this circuit model to design and simulate various logic circuit designs capable of universal computation. Finally, we develop and present a new design paradigm for memristor-based crossbar circuits.
Hazard assessment of dangerous natural phenomena is critical because of their evident results concerning loss of human life and property, especially in dense populated areas. Earthquakes are probably the most devastating phenomenon since their immediate and long-term consequences are severe. This study is focused on the earthquake data analysis in different regions of Greece, characterized by different seismicity levels. In specific, a novel model is proposed based on evolutionary computation methods, such as symbolic regression by genetic programming and genetic algorithms in order to elucidate preliminary hidden mathematical relations and patterns found in the under study seismological signals. Furthermore, the model is calibrated using reverse engineering and closes the loop from the data collection to initial hypothesis and thus the model formation. The presented simulation results qualitatively and quantitatively reveal some of the fundamental characteristics of each studied geographical region located in Greece that stem from its geodynamic properties.
This paper presents a new method performing high-quality 3D object reconstruction of complex shapes derived from multiple, calibrated photographs of the same scene. The novelty of this research is found in two basic elements, namely: (i) a novel voxel dissimilarity measure, which accommodates the elimination of the lighting variations of the models and (ii) the use of an ant colony approach for further refinement of the final 3D models. The proposed reconstruction procedure employs a volumetric method based on a novel projection test for the production of a visual hull. While the presented algorithm shares certain aspects with the space carving algorithm, it is, nevertheless, first enhanced with the lightness compensating image comparison method, and then refined using ant colony optimization. The algorithm is fast, computationally simple and results in accurate representations of the input scenes. In addition, compared to previous publications, the particular nature of the proposed algorithm allows accurate 3D volumetric measurements under demanding lighting environmental conditions, due to the fact that it can cope with uneven light scenes, resulting from the characteristics of the voxel dissimilarity measure applied. Besides, the intelligent behavior of the ant colony framework provides the opportunity to formulate the process as a combinatorial optimization problem, which can then be solved by means of a colony of cooperating artificial ants, resulting in very promising results. The method is validated with several real datasets, along with qualitative comparisons with other state-of-the-art 3D reconstruction techniques, following the Middlebury benchmark.
This paper presents an extensive simulation tool based on a Cellular Automata (CA) system that models fundamental seismic characteristics of a region. The CA-based dynamic model consists of cells-charges and it is used for the simulation of the earthquake process. The simulation tool has remarkably accelerated the response of the model by incorporating principles of the High Performance Computing (HPC). Extensive programming features of parallel computing have been applied, thus improving its processing effectiveness. The tool implements an enhanced (or hyper-) 2-dimensional version of the proposed CA model. Regional characteristics that depend on the seismic background of the area under study are assigned to the model with the application of a user-friendly software environment. The model is evaluated with real data that correspond to a circular region around Skyros Island, Greece, for different time periods, as for example one of 45 years (1901–1945). The enhanced 2-dimensional version of the model incorporates all principal characteristics of the 2-dimensional one, also including groups of CA cells that interact with others, located to a considerable distance in an attempt to simulate long-range interaction. The advanced simulation tool has been thoroughly evaluated. Several measurements have been made for different critical states, as well as for various cascade (earthquake) sizes, cell activities and different neighbourhood sizes. Simulation results qualitatively approach the Gutenberg–Richter (GR) scaling law and reveal fundamental characteristics of the system.
In this study, we first present a modeling mechanism for the loss of neurons in limbic brain regions (epileptogenic focus) that could cause epileptic seizures by spreading the pathological dynamics from the focal to healthy brain regions. Prior work has shown that Cellular Automata (CAs) are very effective in simulating physical systems and solving scientific problems by capturing essential global features of the systems resulting from the collective effect of simple system components that interact locally. Nontrivial CAs are obtained whenever the dependence on the values at each CA site is nonlinear. Consequently, in this study, we show that brain activity in a healthy and epileptic state can be simulated by CA long-range interactions. Results from analysis of CA simulation data, as well as real electroencephalographic (EEG) data clearly show the efficiency of the proposed CA algorithm for simulation of the transition to an epileptic state. The results are in agreement with ones from previous studies about the existence of high-dimensional stochastic behavior during the healthy state and low-dimensional chaotic behavior during the epileptic state. The correspondence of the CA simulation results with the ones from real EEG data analysis implies that the spatiotemporal chaotic dynamics of the epileptic brain are similar to observed nonequilibrium phase transition processes in spatially distributed complex systems.
Over the last few years, an increasing number of publications has shown that living organisms are very effective in finding solutions to complex mathematical problems which usually demand large computation resources. The plasmodium of the slime mould Physarum polycephalum is a successful example that has been used to solve path-finding problems on graphs and combinatorial problems. Cellular automata (CAs) computational model can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally (emergent computation). We developed a CA that models exactly the Physarum’s behavior and applied it in finding the minimum-length path between two points in a labyrinth, as well as in solving a path-planning problem by guiding the development of adaptive networks, as in the case of the actual rail network of Tokyo. The CA results are in very good agreement with the computation results produced by the living organism experiments in both cases. Moreover, our CA hardware implementation results in faster and more effective computation performance, because of its inherent parallel nature. Consequently, our CA, implemented both in software and hardware, can serve as a powerful and low-cost virtual laboratory that models the slime mould Physarum’s computation behavior.
Power is becoming a critical constraint for designing embedded applications because the amount of power available to these portable systems is limited due to battery life. On the other hand, many of the emerging real-time applications designed for battery-operated systems, such as wireless communication, and audio and video processing, tend to compete in order to gain a larger fraction of the energy provided by the common (public) source. It is known that both cooperation and competition are very important for every vivid system operation and evolution because cooperation leads to the formation of more complex systems and competition is crucial for the efficient operation, especially when common sources are used. In this paper, we study the cooperation between individuals, i.e., power-aware jobs, of a group, i.e., an embedded system, in a power-aware changing environment, using a variation of the public goods game, in which the changing environment is modeled by a variable multiplication factor. Based on this PGG, we aim to find out what are themost essential conditions under which the cooperation between the power-aware jobs in periodically and abruptly power-aware changing environments of the embedded system is emerging and sustained. The most interesting result is that even in harsh situations, the jobs maintain a degree of cooperation to exploit favorable future energy changes in the power-aware environment.
Cellular Automata (CAs) are a computational tool for modeling complex phenomena. CAs can be simulated exactly by computers and algorithms based on CAs are ideally suited for hardware implementation, due to their discreteness and their simple, regular and modular structure with local interconnections. On the other hand, power dissipation is recognized as a critical parameter in modern VLSI design field. As a result, the study of the undergoing relationship between CA algorithms and the corresponding power consumption could be considered as a matter of importance for their VLSI design analysis with many promising aspects. In this paper, different point of views on power consumption and CAs will be presented. First of all, a power estimation model for combinational logic circuits using CA and focused on glitching estimation is presented in order to elucidate the application of CA model to VLSI power dissipation measurements. The presented simulation results prove the robustness of the aforementioned model. On the other hand, the power consumption of CA based logic circuits and namely of 1-d CAs rules logic circuits is investigated in details. More specifically, CMOS power consumption estimation measurements for the entireness of 1-d CAs rules as well as entropy variation measurements were conducted for various study cases and different initial conditions.
In this study, a novel methodology for the design automation of cellular neural networks (CNNs) for different applications is proposed. In particular, an evolvable algorithm has been developed providing the ability to generate the netlist of the requested CNN in any desired dimension through a very simple procedure, which greatly simplifies the network design process, without the requirement of any relative design knowledge. Furthermore, the user is also granted with control over the selection of the overall function of the network, in order to make it suitable for a variety of data fusion applications. Moreover, the generated netlist can be imported in the SPICE Cad System, resulting in the automated generation of the network schematic, which can be used for the circuit hardware implementation. More specifically, a tutorial 10 × 10 CNN model is generated via the proposed methodology for use in a data fusion and control application. The produced model is tested by its application to a real distributed temperature sensor network for an application involving the attainment and the conservation of the thermal stability of a system. The data transmission is implied through the use of a set of wireless transmitters–receivers. Finally, a series of experimental results on real world conditions are presented, proving the effectiveness and the robustness of the generated CNN and respectively of the proposed methodology.
Every single day, millions of people worldwide create a vast amount of digital images and the need to index and retrieve these images has become more than obvious. The majority of retrieval systems are based on descriptors created by aggregating certain amounts of a specific feature from the image itself, thus creating a representation of its content. Over the years, many conventional probabilistic methods have been proposed that attempt to solve the problem of image retrieval. In this chapter, a variety of such methods are presented to pave the path that eventually will lead to an answer of whether or not artificial intelligence (AI) methods such as fuzzy logic are the correct way to proceed to enhance the image retrieval process. Moreover, since an abundance of swarm intelligence techniques have been used to find a solution for many non-deterministic polynomial time–complete problems, a discussion is being made concerning the possibility of the successful application of these methods to content-based image retrieval. This chapter provides an introduction to the advances in image retrieval as they occurred over the years, beginning with conventional methods. Readers are familiarized with AI techniques and a fully functional fuzzy ant colony image retrieval system is presented so that readers might grasp the “how,” “where,” and “why” AI techniques are applied to image retrieval.
In this paper, a visual non-probabilistic simultaneous localization and mapping (SLAM) algorithm suitable for area measurement applications is proposed. The algorithm uses stereo vision images as its only input and processes them calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a stereo correspondence algorithm that is tolerant to illumination differentiations, the robust scale- and rotation-invariant feature detection and matching speeded-up robust features method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated cellular automata-based enhancement stage. A moving robot equipped with a stereo camera has been used to gather image sequences and the system has autonomously mapped and measured two different indoor areas.
A Cellular Automaton-based technique suitable for solving the path planning problem in a distributed robot team is outlined. Real-time path planning is a challenging task that has many applications in the fields of artificial intelligence, moving robots, virtual reality, and agent behavior simulation. The problem refers to finding a collision-free path for autonomous robots between two specified positions in a configuration area. The complexity of the problem increases in systems of multiple robots. More specifically, some distance should be covered by each robot in an unknown environment, avoiding obstacles found on its route to the destination. On the other hand, all robots must adjust their actions in order to keep their initial team formation immutable. Two different formations were tested in order to study the efficiency and the flexibility of the proposed method. Using different formations, the proposed technique could find applications to image processing tasks, swarm intelligence, etc. Furthermore, the presented Cellular Automaton (CA) method was implemented and tested in a real system using three autonomous mobile minirobots called E-pucks. Experimental results indicate that accurate collision-free paths could be created with low computational cost. Additionally, cooperation tasks could be achieved using minimal hardware resources, even in systems with low-cost robots.
A two-dimensional (2-D) cellular automata (CA) dynamic system constituted of cells-charges has been proposed for the simulation of the earthquake process. In this paper, the study is focused on the optimal parameterisation of the model introducing the use of genetic algorithm (GA). The optimisation of the CA model parameterisation, by applying a standard GA, extends its ability to study various hypotheses concerning the seismicity of the region under consideration. The GA evolves an initially random population of candidate solutions of model parameters, such that in time appropriate solutions to emerge. The quality criterion is realised by taking into account the extent that the simulation results match the Gutenberg–Richter (GR) law derived from recorded data of the area under test. The simulation results presented here regard regions of Greece with different seismic and geophysical characteristics. The results found are in good quantitative and qualitative agreement with the GR scaling relations.
Creating collision-free trajectories for mobile robots, known as the path planning problem, is considered to be one of the basic problems in robotics. In case of multiple robotic systems, the complexity of such systems increases proportionally with the number of robots, due to the fact that all robots must act as one unit to complete one composite task, such as retaining a specific formation. The proposed path planner employs a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every robot of a team while their formation is kept immutable. The method reacts with obstacles distribution changes and therefore can be used in dynamical or unknown environments, without the need of a priori knowledge of the space. The team is divided into subgroups and all the desired pathways are created with the combined use of a CA path planner and an ACO algorithm. In case of lack of pheromone, paths are created using the CA path planner. Compared to other methods, the proposed method can create accurate collision-free paths at real time with low complexity while the implemented system is completely autonomous. A simulation environment was created to test the effectiveness of the applied CA rules and ACO principles. Moreover, the proposed method was implemented in a system using a real world simulation environment, called Webots. The CA and ACO combined algorithm was applied to a team of multiple simulated robots without the interference of a central control. Simulation and experimental results indicate that accurate collision free paths could be created with low complexity, confirming the robustness of the method.
This paper presents an anticipative system which operates during pedestrian evacuation processes and prevents escape points from congestion. The processing framework of the system includes four discrete stages; a) the detection and tracking of pedestrians, b) the estimation of possible route for the very near future, indicating possible congestion in exits, c) the proposal of free and nearby escape alternatives and d) the activation of guiding signals, sound and optical. Detection and tracking of pedestrians is based on an enhanced implementation of a system proposed by Viola, Jones and Snow that incorporates both appearance and motion information in near real-time. At any moment, detected pedestrians can instantly be defined as the initial condition of the second stage of the system, i.e. the route estimation model. Route estimation is enabled by a dynamic model inspired by electrostatic-induced potential fields. The model combines electrostatic-induced potential fields to incorporate flexibility in the movement of pedestrians. It is based on Cellular Automata (CA), thus taking advantage of their inherent ability to represent effectively phenomena of arbitrary complexity. Presumable congestion during crowd egress, leads to the prompt activation of sound and optical signals that guide pedestrians towards alternative escaping points. Anticipative crowd management has not been thoroughly employed and this system aims at constituting an effective proposal.
In motion estimation, the sub-pixel matching technique involves the search of sub-sample positions as well as integer-sample positions between the image pairs, choosing the one that gives the best match. Based on this idea, this work proposes an estimation algorithm, which performs a 2-D correspondence search using a hierarchical search pattern. The intermediate results are refined by 3-D Cellular Automata (CA). The disparity value is then defined using the distance of the matching position. Therefore, the proposed algorithm can process uncalibrated and non-rectified stereo image pairs, maintaining the computational load within reasonable levels. Additionally, a hardware architecture of the algorithm is deployed. Its performance has been evaluated on both synthetic and real self-captured image sets. Its attributes, make the proposed method suitable for autonomous outdoor robotic applications.
This paper proposes a new method for visual multimedia content encryption using Cellular Automata (CA). The encryption scheme is based on the application of an attribute of the CLF XOR filter, according to which the original content of a cellular neighborhood can be reconstructed following a predetermined number of repeated applications of the filter. The encryption is achieved using a key image of the same dimensions as the image being encrypted. This technique is accompanied by the one-time pad (OTP) encryption method, rendering the proposed method reasonably powerful, given the very large number of resultant potential security keys. The method presented here makes encryption possible in cases where there is more than one image with the use of just one key image. A further significant characteristic of the proposed method is that it demonstrates how techniques from the field of image retrieval can be used in the field of image encryption. The proposed method is further strengthened by the fact that the resulting encrypted image for a given key image is different each time. The encryption result depends on the structure of an artificial image produced by the superposition of four 1-D CA time–space diagrams as well as from a CA random number generator. A semi-blind source separation algorithm is used to decrypt the encrypted image. The result of the decryption is a lossless representation of the encrypted image. Simulation results demonstrate the effectiveness of the proposed encryption method. The proposed method is implemented in C# and is available online through the img(Rummager) application.
This paper studies the on-chip realisation of a dynamic model proposed to simulate crowd behaviour, originated from electrostatic-induced potential fields. It is based on Cellular Automata (CA), thus taking advantage of their inherent ability to represent sufficiently phenomena of arbitrary complexity and, additionally, to be simulated precisely by digital computers. The model combines electrostatic-induced potential fields to incorporate flexibility in the movement of pedestrians. It primarily calculates distances in an obstacle filled space based on the Euclidean metric. Furthermore, it adopts a computationally fast and efficient method to overcome trouble-inducing obstacles by shifting the moving mechanism to a potential field method based on Manhattan distance. The hardware implementation of the model is based on FPGA logic. Initialisation of the dedicated processor takes place in collaboration with a detecting and tracking algorithm supported by cameras. The instant response of the processor provides the location of pedestrians around exits. Hardware implementation exploits the prominent feature of parallelism that CA structures inherently possess in contrast to the serial computers, thus accelerating the response of the model. Furthermore, FPGA implementation of the model is advantageous in terms of low-cost, high-speed, compactness and portability features. Finally, the processor could be used as a part of an embedded, real-time, decision support system, aiming at the efficient guidance of crowd in cases of mass egress.
In this paper, a new methodology for deriving the velocity and the acceleration information of a digital encoder through processing its pulse train, is presented. The proposed method is based on accurate time measurement (with picosecond accuracy) as well as encoder pulse counting in adaptively changing time intervals, providing thus a wide-range velocity evaluation with very good accuracy. The method offers better response times at low speeds and very high accuracy at the full range of measured velocities. By using the proposed method, the velocity measurement accuracy is improved compared to currently known methods, since high-resolution time-to-digital converters (TDC) are included in the design. The increased accuracy in velocity measurement allows the application of the simple arithmetic differentiation method on the velocity information in order to derive the acceleration, which in other cases would not be suggested due to accumulated quantization noise. A digital signal processor (DSP) also allows the implementation of numerous other methods to calculate acceleration. The proposed configuration has been implemented in specific hardware (FPGA), reserving thus the computational power of the system controlling DSP for high-level control tasks.
In this paper, a hardware implementation of a fuzzy modified ant colony processor suitable for image retrieval is presented for the first time. The proposed method utilizes three different descriptors in a two stage fuzzy ant algorithm where the query image represents the nest and the database images represent the food. From the hardware point of view, only a small number of algorithms for hardware implementation have been reported in the image retrieval literature, since research focuses mainly on possible software solutions and the acceleration of existing algorithms. The proposed digital hardware structure is based on a sequence of pipeline stages, while parallel processing is also used in order to minimize computational times. It is capable of performing the extraction and comparison of features from 64×64-pixel size color images, although through a simple transformation it can be easily expanded to accommodate images of larger sizes. The architecture of the processor is generic; the units that perform the fuzzy inference can be used with different descriptors than the ones proposed here and can be utilized for other fuzzy applications. It was designed, compiled, and simulated using the Quartus Programmable Logic Development System by the Altera Corporation. The fuzzy processor exhibits a level of inference performance of 800 KFLIPS with 24 rules, and can be used for real-time applications where the need for short processing times is of the utmost importance.
Stereo vision, resulting in the knowledge of deep information in a scene, is of great importance in the field of machine vision, robotics and image analysis. In this paper, an explicit analysis of the existing stereo matching methods, up to date, is presented. The presented algorithms are discussed in terms of speed, accuracy, coverage, time consumption and disparity range. Towards the direction of real-time operation, the development of stereo matching algorithms, suitable for efficient hardware implementation is highly desirable. Implementations of stereo matching algorithms in hardware for real-time applications are also discussed in details.
A two dimensional (2-D) Cellular Automata (CA) dynamic system constituted of cells-charges has been proposed for the simulation of the earthquake process. The CA model has been calibrated with the use of real data. The calibration incorporates major seismic characteristics of the area under test. The simulation results are found in good quantitative and qualitative agreement with the recorded Gutenberg–Richter (GR) scaling relations. The model is enriched with a powerful multi-parameter interface that enables the user to load real data from different regions. This paper examines the on-chip realization of the model and its instrumentation. The CA model hardware implementation is based on Field Programmable Gate Array (FPGA) logic. It utilizes an array of 32×32 cells. Parameters that construct the local CA rule constitute the input data. The initial seed, which in some extend corresponds to the seismic features of the area under test, is loaded in a semi-parallel way and the process is completed in a certain number of time steps. The automatic response of the processor provides the corresponding GR scaling law of the area under study. The hardware implementation of the CA based earthquake simulation model is advantageous in terms of low-cost, high-speed, compactness and portability features. It can operate as a preliminary data-acquisition filter that accelerates the evaluation of recorded data as far as its origin time, spatial and magnitude completeness and quality are concerned. Software that performs reliable automatic phase picking, as well as data elaboration, can be assembled next to the earthquake recording instruments (the whole network) output to assure a quick and reliable iteration of the focal parameters of a recorded earthquake (epicentre coordinates, focal depth and magnitude). The dedicated processor can be accommodated right after this stage (before any manual elaboration) focusing on the near real-time development of a reliable qualitative dynamical seismic record and a mapping of the seismic characteristics of the area.
Stereo vision deals with images acquired by a stereo camera setup, where the disparity between the stereo images allows depth estimation within a scene. 3-D information, hence, is retrieved which is essential in many machine vision applications. Disparity map extraction of an image is a computationally demanding task. Previous work on disparity map computation is mainly limited to software based techniques on general-purpose architectures. In this paper a new hardware-efficient real-time disparity map computation module is developed. This enables a hardware based cellular automata (CA) parallel-pipelined design, for the overall module, realized on a single FPGA device, the typical operating frequency of which is 256 MHz. Accurate disparity maps are computed at a rate of nearly 275 per second, for a stereo image pair with a disparity range of 80 pixels and 640×480 pixels spatial resolution. The presented hardware-based algorithm provides very good processing speed at the expense of accuracy, with very good scalability in terms of disparity levels. The proposed method allows the fastest disparity map computational module to be built, to the best of the authors’ knowledge so far, enabling a suitable module for real-time stereo vision applications.
Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not been possible to decipher the rules that govern DNA sequence evolution due to the extreme complexity of the entire process. In our attempt to approach this issue we focus solely on the mechanisms of mutagenesis and deliberately disregard the role of natural selection. Hence, in this analysis, evolution refers to the accumulation of genetic alterations that originate from mutations and are transmitted through generations without being subjected to natural selection. We have developed a software tool that allows modeling of a DNA sequence as a one-dimensional Cellular Automaton (CA) with four states per cell which correspond to the four DNA bases, i.e. A, C, T and G. The four states are represented by numbers of the quaternary number system. Moreover, we have developed Genetic Algorithms (GAs) in order to determine the rules of CA evolution that simulate the DNA evolution process. Linear evolution rules were considered and square matrices were used to represent them. If DNA sequences of different evolution steps are available, our approach allows the determination of the underlying evolution rule(s). Conversely, once the evolution rules are deciphered, our tool may reconstruct the DNA sequence in any previous evolution step for which the exact sequence information was unknown. The developed tool may be used to test various parameters that could influence evolution. We describe a paradigm relying on the assumption that mutagenesis is governed by a near-neighbor dependent mechanism. Based on the satisfactory performance of our system in the deliberately simplified example, we propose that our approach could offer a starting point for future attempts to understand the mechanisms that govern evolution. The developed software is open-source and has a user-friendly graphical input interface.
The increasing complexity of computer networks calls for the development of new models for their simulation. Cellular Automata (CAs) are a well known and successful model for complex systems. This paper presents a system for modeling and simulation of computer networks based on CAs. More specifically, a two-dimensional NaSch CA computer network model has been developed and several networks were simulated. Algorithms for connectivity evaluation, system reliability evaluation and shortest path computation in a computer network have also been implemented. Our system, called Net_CA system, was designed and developed as an interactive tool that offers automated modeling with the assistance of a dynamic and user friendly graphical environment. The proposed system also produces automatically synthesizable VHDL code leading to the parallel hardware implementation of the above CA algorithms. In terms of circuit design and layout, ease of mask generation, silicon-area utilization and maximization of achievable clock speed CAs are perhaps the computational structures best suited for a fully parallel VLSI realization. The simulation algorithms developed in the present work offer high flexibility. Furthermore, connection reliability and other important parameters are inputs to the algorithms rendering Net_CA a very reliable and fast simulator for wireless networks, ad hoc networks and, generally, for low connection reliability networks.
Seismicity is an extended geophysical characteristic of the Greek dominion. There are certain areas of high seismic activity, as well as, regions of low seismicity where strong earthquakes are rather rare events. Consequently, it is of great interest to present a methodology concerning the earthquake process in Greece even for areas considered to be of low seismicity. In this paper, it is presented the study of the earthquake activity of an area in Northeastern Greece, centred at Xanthi, Thrace, extended over a region of radius R = 80 km, during a certain time period. A two-dimensional cellular automaton (CA) dynamic system consisting of cells-charges is used for the simulation of the earthquake process. The model has been tested as well as calibrated using the recorded events of the above-mentioned region as initial conditions. The simulation results are found in good quantitative and qualitative agreement with the Gutenberg–Richter (GR) scaling relations. Finally, the CA model has a user-friendly interface and enables the user to change several of its parameters, in order to study various hypotheses concerning the seismicity of the region under consideration.
Cellular Automata (CAs) are a powerful technique for modelling otherwise intractably complex systems. On the other hand, earthquake can be defined as a spatially extended dissipative dynamical system that naturally evolves into a critical state with no characteristic time or length scales. In this paper, a two-dimensional CA model capable of reproducing some prominent features of earthquake data is presented. The proposed model with continuous states and discrete time, constituted of cells-charges aims at simulate earthquake activity with the usage of potentials. Several measurements have been carried out different critical states, leading to different paths to criticality, for various cascade (earthquake) sizes, various cell activities and different neighbourhood sizes. Most notably, the produced simulation results emulate the Gutenberg–Richter (GR) scaling law, in both quantitative and qualitative way. Furthermore, the CA model has been implemented with a user-friendly interface and the user can change several of its parameters, in order to study various hypotheses concerning the aforementioned earthquake activity features.
Lithography is the most important process in integrated circuit fabrication. Lithographic profile defect simulator based on cellular automata revealed a self-regulation mechanism of the resist development process, which is expressed as a tendency of the etch-front to retain its parabolic shape. The phase-space picture of this mechanism is an attractor and it is certified that the resist-etchant system spends much time near the unperturbed state.
Artificial Intelligence techniques are widely used to solve complicated manufacturing and fabrication process problems in today’s industrial world. Cellular automata (CAs) have been applied numerous times as an evolvable technique to the solution of some of the aforementioned complicated problems with great success due to their inherent parallelism, structural locality, regularity and modularity. One of the most difficult problems that CAs dealt with in several cases (i.e. integrated circuit fabrication, pattern recognition and classification, computer aided design, machine vision, etc.) is the identification and the reproduction of circular fronts and shapes. In this paper a Cellular Automaton (CA) is used to propagate circular fronts. This CA has an extended Moore neighborhood and a relatively simple local rule based on Boolean operators. Simulation results of an Integrated Circuit fabrication process, namely Chemical Vapor Deposition (CVD) based on the proposed CA are also presented. These results were found to be in very good qualitative agreement with the experimental results published in the literature. Moreover, because of the CA’s binary states and its local rule simplicity, the VLSI implementation of the proposed CA is straightforward.
A message passing algorithm for processor arrays that can tolerate any number of faulty blocks, which form any shape, is presented. Each message is delivered to its destination, provided that the destination processor is not surrounded by faults. In this case the message is returned to its source processor. Only local knowledge of faults is demanded. The hardware implementation of this algorithm leads to a message passing coprocessor which is allocated at each processor of the array. No need for high silicon overhead is required for the implementation of the message passing coprocessor. This coprocessor executes only the fault tolerant message passing algorithm presented here. The usage of the proposed coprocessor improves the general processing efficiency, as well as, the performance reliability under faulty conditions.
Recent studies of the quantum mechanical processes in the DNA molecule have seriously challenged the principle that mutations occur randomly. The proton tunneling mechanism causes tautomeric transitions in base pairs resulting in mutations during DNA replication. The meticulous study of the quantum mechanical phenomena in DNA may reveal that the process of mutagenesis is not completely random. We are still far away from a complete quantum mechanical model of DNA sequence mutagenesis because of the complexity of the processes and the complex three-dimensional structure of the molecule. In this paper we have developed a quantum mechanical description of DNA evolution and, following its outline, we have constructed a classical model for DNA evolution assuming that some aspects of the quantum mechanical processes have influenced the determination of the genetic code. Conversely, our model assumes that the genetic code provides information about the quantum mechanical mechanisms of mutagenesis, as the current code is the product of an evolutionary process that tries to minimize the spurious consequences of mutagenesis. Based on this model we develop an algorithm that can be used to study the accumulation of mutations in a DNA sequence. The algorithm has a user-friendly interface and the user can change key parameters in order to study relevant hypotheses.
Technology computer-aided design (TCAD) is essential for the design of modern integrated circuit fabrication processes. TCAD tools must not only model real processes accurately, to allow predictive simulation during technology research and development, but must work together as an integrated system to allow efficient exploration of new technology options and to perform numerical experiments. Cellular Automata (CAs) have been applied successfully to the simulation of several physical systems and processes, and have been extensively used as VLSI architecture. This paper describes a TCAD system for the simulation of the two-dimensional Chemical Vapor Deposition (CVD) process. The TCAD system is fully automated and is also able to support, the hardware implementation of the corresponding CA algorithm, leading to its execution by dedicated parallel processor. The obtained simulation profiles of the CVD process are in very good qualitative agreement with experimental and simulation results found in the literature. The proposed system produces as output the corresponding VHDL code, which leads to the VLSI implementation of the CA algorithm. Furthermore, a user-friendly interface that enables easy and effective interaction between the user and the TCAD system has been developed. No prior knowledge of VHDL is required by the user. The produced VHDL code is synthesizable and can be used for the automated design of the corresponding VLSI system, using a commercial VLSI CAD system.
Cellular Automata (CAs) are models of physical systems where space and time are discrete and interactions are only local. CAs are very effective in simulating physical systems and solving scientific problems, because they can capture the essential features of systems in which global behaviour arises from the collective effect of simple components which interact locally. CAs have been applied successfully to the simulation of several physical systems and processes, and have been extensively used as a VLSI architecture. We present a CAD system that builds a bridge between CAs as models of physical systems and processes, and CAs as a VLSI architecture. The inputs to our CAD system are the CA dimensionality, lattice size, local rule, and the initial and boundary conditions imposed by the particular problem. Our system produces as output the corresponding VHDL code, which leads to VLSI implementation of the CA algorithm. No prior knowledge of VHDL is required by the user. We have tested our CAD system using well-known one and two dimensional CAs, namely the game of life and the rule 90 CAs. The VHDL code produced in all these cases has been used for the automated design of the corresponding VLSI system, using a commercial VLSI CAD system. Simulations of the operation of these VLSI systems showed that the corresponding CA has been successfully implemented into hardware.
Cellular automata are introduced as a model for DNA structure, function and evolution. DNA is modeled as a one-dimensional cellular automaton with four states per cell. These states are the four DNA bases A, C, T and G. The four states are represented by numbers of the quaternary number system. Linear evolution rules, represented by square matrices, are considered. Based on this model a simulator of DNA evolution is developed and simulation results are presented. This simulator has a user-friendly input interface and can be used for the study of DNA evolution.
This paper presents a methodology for the simulation of physical processes with local interactions using cellular automata. Such processes are common in integrated circuit fabrication, and their simulation presents one of the most difficult problems in developing Technology Computer Aided Design (TCAD) systems. The simulated integrated circuit fabrication processes considered are lithography, oxidation, and deposition processes. The proposed methodology establishes the ability to capture the essential features of these integrated circuit fabrication processes and to translate them into a suitable form, in order to obtain an effective cellular automaton model, for each process. Several numerical experiments were carried out, in this work, using the cellular automaton algorithms obtained, and their results were found to be in very good agreement with published experimental results. Furthermore, cellular automaton algorithms exploit the inherent parallelism of the cellular automaton model and run fast on serial computers.
The development of next-generation VLSI circuits with deep submicron technologies demands fundamental understanding of the wafer surface reaction kinetics. Technology computer-aided design (TCAD) is essential for modeling real fabrication processes accurately, and allowing predictive simulation during technology research and development. This paper describes a two-dimensional Chemical Vapor Deposition (CVD) process TCAD system based on cellular automata (CAs). The proposed TCAD system can handle the complicated boundary and initial conditions imposed by defects and provide SEM-like cross sectional views. The simulated profiles obtained are in very good agreement with experimental and simulation results found in the literature. Furthermore, a user-friendly interface that enables easy and effective interaction between the user and the TCAD system has been developed.
As the ICs are pushed deeper into the submicrometer region, the presence of non-planarity and defects are becoming major yield detractors. In this work, we have studied these effects using a two-dimensional technology computer-aided design (TCAD) system based on cellular automata (CAs), which we have named CA_TCAD. CA_TCAD comprises a photolithography etching and a deposition simulator. The photolithography etching simulator has been tested, verified, and calibrated, with a series of experiments with periodic and isolated lines on negative resist coated Si wafers, using a stepper and a Deep UV source at 248nm. The deposition simulator can provide SEM-like cross sectional views and the simulated profiles obtained are in very good agreement with experimental results found in the literature.
A methodology for the VLSI implementation of Cellular Automata (CA) algorithms using the VHSIC Hardware Description Language (VHDL) is proposed for the first time. This methodology builds a bridge between the CAs as models of physical systems and processes and the CAs as a VLSI architecture. A translation algorithm is developed which has as input the CA algorithms that simulate physical systems and processes, and as output the corresponding VHDL code. The parameters of this translation algorithm are defined by the user and can be automatically mapped into synthesizable VHDL. An example, where this methodology is applied to the hardware implementation of a CA algorithm for automated visual inspection, is presented.
A cellular automaton model for the effects of population movement and vaccination on epidemic propagation is presented. Each cellular automaton cell represents a part of the total population, which may be found in one of the following three states: infected, immunized and susceptible. As parts of the population move randomly in the cellular automaton lattice, the disease spreads. We study the effect of two population movement parameters on the epidemic propagation: the distance of movement and the percentage of the population that moves. Furthermore, the model is extended to include the effect of the vaccination of some parts of the population on epidemic propagation. The model establishes the acceleration of the epidemic propagation, because of the increment, of the percentage of the moving population, or of the maximum distance of population movement. On the contrary, the effect of population vaccination reduces the epidemic propagation. The proposed model can serve as a basis for the development of algorithms to simulate real epidemics based on real data.
A tested, verified, and calibrated lithography simulator was used to study phenomena, the effects of which are becoming more pronounced as the ICs are pushed deeper into the submicron region. Numerical experiments were carried out to elucidate the effect of defects located into the resist bulk, as well as the effect of the resist surface roughness, on the developed profiles.
A tested, verified, and calibrated lithography simulator, based on cellular automata, is used to study phenomena, the effects of which are becoming more pronounced as the ICs are pushed deeper into the nanometer region. Lithography profiles developed on non-planar Si surfaces, where a step or a sloped line is present, were studied. Numerical experiments that elucidate effects such as the resist surface roughness on the developed profiles, as well as the effect of defects located into the resist bulk, in the presence of non-planar Si surfaces, are also presented. These effects are expected to be more pronounced as the integrated circuits are pushed deeper into the nanometer region.
A new two dimensional oxidation simulator based on cellular automata is presented in this paper. The advancement of the Si-SiO2 and SiO2-air fronts during oxidation has been successfully simulated. The simulator reproduced satisfactorily the oxidation profiles in the case of a Gaussian temperature distribution over the Si surface, as well as in the case of the presence of contamination on the Si surface. Oxidation of non-planar Si surfaces, as well as oxidation through a mask, and oxidation through a mask of non-planar Si surfaces have also been successfully simulated. The simulation results are in good qualitative agreement with experimental data.
Cellular automata (CA) are computational models of physical systems, where space and time are discrete and interactions are local. Specific CA attributes make them ideal for designing complex electronic circuits for the automated image processing. In terms of circuit design and layout, ease of mask generation, silicon-area utilization, and maximization of clock speed, CAs are perhaps one of the most suitable computational structures for hardware realization. In this paper, we present a computational tool designed to create specialized FPGAs that achieve automated image processing such as noise filtering, edge thinning and convex hull detection. The user of the tool specifies the initial parameters and the automation design tool returns the VHDL code needed for the dedicated electronic circuit. Testing the tool using various initial conditions showed that the corresponding CA algorithms have been successfully implemented into hardware. 
Current data centers consume huge amount of power to face the increasing network traffic. Therefore energy efficient processors are required that can process the cloud applications efficiently without consuming excessive power. This paper presents a performance evaluation of the processors that are mainly used in high performance embedded systems in the domain of cloud computing. Several representative applications based on the widely used MapReduce framework are mapped in the embedded processor and are evaluated in terms of performance and energy efficiency.  The results shows that high performance embedded processors can achieve up to 7.8x better energy efficiency than the current general purpose processors in typical MapReduce applications.
This paper describes a model that simulates crowd movement incorporating an efficient follow-the-leader technique based on cellular automata (CA). The scope of the method is to derive principal characteristics of collective motion of biological organisms, such as flocks, swarms or herds and to apply them to the simulation of crowd movement. Thus, the study focuses on the massive form of the movement of individuals, which is lastingly detected macroscopically, during urgent circumstances with the help of some form of guidance. Nevertheless, on a lower level, this formation derives from the application of simple local rules that are applied individually to every single member of the group. Hence, the adoption of CA-based formation has allowed the development of a micro-operating model with macro-features. Furthermore, the model takes advantage of the inherent ability of CA to represent sufficiently phenomena of arbitrary complexity. The response of the model has been evaluated through different simulation scenes that have been developed both in two and three dimensions.
This paper introduces a novel image resizing method for both color and grayscale images. The method could be beneficial in applications where time and quality of the processed images are crucial. The basic idea of the proposed method relies on preserving the edges by partitioning the digital images into homogenous and edge areas during the enlargement process. In addition, the basic fundamentals of Cellular Automata were adopted in order to achieve better performance both in terms of processing time as well as in image quality. By creating appropriate transition rules, the direction of the edges is considered so that every unknown pixel is processed based on its neighbors in order to preserve the quality of the edges. Results demonstrate that the proposed method improves the subjective quality of the enlarged images over conventional resizing methods while keeping the required processing time in low levels.
During the last decades, certain research emphasis has been placed on building synthetic molecular machinery from DNA. In specific, biological systems in which individual molecules act, singly and in concert, as specialized machines result are called DNA machines. Recently, Autonomous DNA Turing Machines and DNA Cellular Automata were proposed as cellular computing devices that can serve as reusable, compact computing devices to perform (universal) computation. In this paper, we introduce 1-d Hybrid Autonomous DNA Cellular Automata (HADCA), able to run in parallel different CA rules with certain modifications on their molecular implementation and information flow compared to their origins. Moreover, a HADCA simulator was developed to encourage the possible use of the biological inspired computation tool. Finally, it is shown that a proposed 1-d HADCA can generate high-quality random numbers which can pass the statistical tests of DIEHARD, one of the most well known general test suites for randomness. Consequently, such a HADCA can be efficiently implemented for pseudorandom number generation (PRNG) reasons.
Earthquakes have been in the focus of human and research interest for several centuries due to their catastrophic effect to the everyday life as they occur almost all over the world demonstrating a hard to be modelled unpredictable behaviour. On the other hand, their monitoring with more or less technological updated instruments has been almost continuous and thanks to this fact several mathematical models have been presented and proposed so far to describe possible connections and patterns found in the resulting seismological time-series. Especially, in Greece, one of the most seismically active territories on earth, detailed instrumental seismological data are available from the beginning of the past century providing the researchers with valuable and differential knowledge about the seismicity levels all over the country. Considering available powerful parallel computational tools, such as Cellular Automata, these data can be further successfully analysed and, most important, modelled to provide possible connections between different parameters of the under study seismic time-series. More specifically, Cellular Automata have been proven very effective to compose and model nonlinear complex systems resulting in the advancement of several corresponding models as possible analogues of earthquake fault dynamics. In this work preliminary results of modelling of the seismic time-series with the help of Cellular Automata so as to compose and develop the corresponding complex networks are presented. The proposed methodology will be able to reveal under condition hidden relations as found in the examined time-series and to distinguish the intrinsic time-series characteristics in an effort to transform the examined time-series to complex networks and graphically represent their evolvement in the time-space. Consequently, based on the presented results, the proposed model will eventually serve as a possible efficient flexible computational tool to provide a generic understanding of the possible triggering mechanisms as arrived from the adequately monitoring and modelling of the regional earthquake phenomena.
Oil spills in sea waters are considered as a major threat for ecosystems with numerous accidents recorded each year. Consequently, models for oil slick behavior are important in environmental engineering, and Cellular Automata (CA) have been successfully used in modeling physical systems and processes in the past. Models based on CA can be implemented in hardware (HW) in a straightforward manner, and also lead to fast execution of algorithms especially when implemented on FPGA platforms. In this paper, we demonstrate the dedicated FPGA implementation of a CA-based algorithm for the prediction of oil slick movement and spreading. The presented dedicated processor is able to process various scenarios of weather conditions, and it provides the possible form and location of the oil slick front in future times. Combined with the necessary electronic  communication equipment, it could efficiently support a real-time decision support system to facilitate appropriate response in case of oil slick environmental emergency.
The wasteful consumption of freshwater in heavily populated coastal areas usually consist the basic reason for the intrusion of saltwater into the coastal aquifers. In order to avoid such catastrophic scenarios, their prediction is of utter significance. Underground water systems are highly complex and the water flow is extremely dynamic, thus making the prediction of this phenomenon a difficult task. For this reason, a two dimensional Cellular Automaton (CA) was designed enabling both the qualitative and quantitative simulation and illustration of the saltwater intrusion into an unconfined coastal aquifer.
During the last decades, traffic congestion in urban networks is getting worse affecting many aspects of the residents lives to an increasing extent. Traffic lights play a decisive role in the aforementioned traffic networks of modern metropolises, and the existing conditions of the corresponding vehicular traffic flows. In order to develop an efficient system dedicated to the real-time traffic signals control for which the hardware implementation will be straightforward, Cellular Automata (CAs) were chosen as the simulation and implementation method. Despite its ease of implementation and simplicity, CAs is a powerful tool that can generate realistic traffic models. In this paper, a Cellular Automaton (CA) model was implemented on a FPGA to take full advantage of the inherent parallelism of CAs and provide real-time traffic signals control in accordance with vehicular traffic flow. The proposed hardware was optimized and the resulting single FPGA processor can be finally considered as basic component of an advanced electronic system able to provide real time information concerning the traffic conditions in the under study intersections and thus to efficiently handle-control the traffic signals in real conditions.
One of the major tasks in the field of robotics is the path planning problem. In systems consisted of numerous robots, the creation of collision free trajectories becomes even more complex. Such robotic teams must avoid all detected obstacles while further tasks must be achieved such as forming specific patterns. In this paper, a Cellular Automaton (CA) based path planner and its implementation in a real cooperative robot team are presented. All robots must cover the same distance avoiding all detected obstacles while their formation is kept immutable. Due to its simplicity, the method has low computational load and therefore further applications could be applied. On the other hand, miniature robots can cooperate in order to perform area measurements, simultaneous localization and mapping (SLAM), panoramic images and so on. One of the most interesting cooperation aspects is the usage of multiple digital cameras, usually found with low resolutions. In order to process accurately all the acquired images taken from every robot, image interpolation algorithms could be applied as a preprocessing stage. Consequently, the inherent parallelism and the fundamental features of CA were also used to achieve the desired resolution enhancement. Final results indicate that both the CA based path planner and the image resolution enhancement could be executed concurrently using the resources of each mini robot, confirming their low requirements of computational resources.
Hazard assessment of dangerous natural phenomena is very important because these phenomena result in loss of human life and property, especially in dense populated areas. Earthquakes are probably the most devastating phenomena since their immediate and long-term consequences are severe. Earthquake activity modelling, especially in areas known to experience frequent large earthquakes, could lead to improvements in building regulations and infrastructure development that will prevent as much as possible loss of lives, injuries and property damage. Greece is considered to be one of the top active lands in the world as well as the most active seismically region of Europe. Earthquakes in Greece are monitored continuously and instrumental earthquake data are available since the beginning of the 20th century, when seismological networks were firstly deployed. In this study we concentrate on the earthquake data analysis in different regions of Greece, characterized by different seismicity level. More specifically, a novel model is proposed based on evolutionary computation methods, such as symbolic regression by genetic programming and genetic algorithms in order to elucidate hidden mathematical relations and patterns found in the under study seismological data signals. Automated techniques for collecting and storing earthquake data have become increasingly precise and powerful leading to a very large amount of gathered data increasing with time and difficult to handle. To distil such amounts of gathered data into knowledge and into practical regulations, the data should be organized and the relationships between the measured parameters must be described using analytical mathematical models which will lead to automated processes of data handling. In many scientific research fields, the increasing measurement infrastructure supported by increasing networking and increasing computer power has led to collections of staggering amounts of data, but automated processes for distilling these data into knowledge in the form of analytical mathematical relationships have not kept pace. The proposed model can reveal hidden relations between parameters measured on an earthquake occurrence, such as displacements, velocities and accelerations. Furthermore, it is calibrated with the usage of reverse engineering in an attempt to close the loop from data collection to initial hypothesis model formation and revision. The presented simulation results qualitatively and quantitatively reveal some of the fundamental characteristics for each studied geographical region located in Greece that stem from its geodynamic properties. Consequently, the proposed model could serve as a computer-assisted basis for hazard evaluation and mapping of regional earthquake phenomena.
In this paper, an electronic system able to reproduce the complex dynamic behaviors of the train movement is presented. In particular, a Cellular Automaton (CA) model inspired by Li et al. corresponding model was developed in order to provide efficient control of the railway traffic flow. The proposed model was implemented on a (Field Programmable Gate Array) FPGA to take full advantage of the inherent parallelism of CAs. The FPGA design which results from the automatically produced synthesizable VHDL code of the CA model is considered as basic component of a portable, low total cost electronic system. The later also includes a high performance Global Positioning System (GPS) wireless communication module for the monitoring of train activity in the under study railway. The aforementioned module in conjunction with the proposed fully automatically programmable FPGA device minimizes the design burden offering the chance of real-time train control operation based on the presented CA model.
In this paper, a crowd evacuation model based on Cellular Automata (CA) is described. The model takes advantage of the inherent ability of CA to represent sufficiently phenomena of arbitrary complexity and to be simulated precisely by digital computers as well. Pedestrian movement depends on their distance from the closest exit, which is defined dynamically. The adoption of Manhattan distance as the reference metric provides calculation simplicity, computational speed and improves significantly computational performance. Moreover, the model applies an efficient method to overcome obstacles. The latter is based on the generation of a virtual field along obstacles. A pedestrian moves along the axis of the obstacle towards the direction that the field increases its values, leading her/him to avoid the obstacle effectively. Distinct features of crowd dynamics and measurements on different distributions of pedestrians have been used to evaluate the response of the model.
In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale- and rotation-invariant feature detection and matching Speeded Up Robust Features (SURF) method, a computationally effective v-disparity image calculation scheme as well as a sophisticated Cellular Automata (CA) -based map merging module. The proposed algorithm is suitable for autonomously mapping and measuring indoor areas using robots. The algorithm is presented and experimental results for self-captured image data are provided and analyzed.
During the last decades Cellular Automata (CAs) have been extensively used as powerful computational tool able to represent phenomena of arbitrary complexity and at the same time can be simulated exactly by digital computers, because of their intrinsic discreteness. Furthermore, due to their simple, regular, modular and cascadable structure with local interconnections CAs algorithms are ideally suited for hardware implementation. On the other hand, power dissipation is recognized as a critical parameter in modern VLSI design field. In this paper a power estimation model based on CAs is proposed. With the help of this model the power consumption of 1-d CAs rules logic circuits is investigated in details. More specifically, CMOS power consumption estimation measurements for the entireness of 1-d CAs rules as well as entropy variation measurements were conducted based on the proposed model. The presented simulation results prove the robustness of the aforementioned model and discuss the Wolfram 1-d CAs classes categorization based on the produced power estimation results and depending on the corresponding initial conditions.
Nowadays, there is an increasingly recognized need for more computing power, which has led to multicore processors. However, this evolution is still restrained by the poor efficiency of memory chips. As a possible solution to the problem, this paper examines a model of re-distributing the memory resources assigned to the processor, especially the on-chip memory, in order to achieve higher performance. The proposed model uses the basic concepts of game theory applied to cellular automata lattices and the iterated spatial prisoner’s dilemma game. A simulation was established in order to evaluate the performance of this model under different circumstances. Moreover, a corresponding FPGA logic circuit was designed as a part of an embedded, real-time co-circuit, aiming at memory resources fair distribution. The proposed FPGA implementation proved advantageous in terms of low-cost, high-speed, compactness and portability features. Finally, a significant improvement on the performance of the memory resources was ascertained from simulation results.
Physical processes in the earth’s lithosphere compose a nonlinear complex system. Earthquake generation is part of this process. Till now, several computational geophysical models have been proposed in order to tackle complex problems associated with proper interpretation of the available seismicity information and the understanding of triggering mechanisms. In this study, an automatic, hybrid, 3-d cellular automaton model evolved both in space and time is proposed for the modelling of earthquake activity. The proposed model is further calibrated with the usage of reverse engineering in its attempt to close the loop from data collection to initial hypothesis model formation and revision. More specifically, the CA rules and the rest of the CA parameters are derived by the dissociation of real seismic data of the region under consideration as it was spatiotemporally evolved. As a result, our model not only successfully copes with the volume of provided data but could also realize the first stage of a perspective, real-time, efficient system for hazard evaluation and mapping of regional, dangerous phenomena. Moreover, the corresponding simulation results are found in good quantitative and qualitative agreement with the Gutenberg–Richter (GR) scaling relations emerged by the use of the recorded data over the under study geographical regions mainly located in Greece territory.
The path planning problem is one of the major tasks in the field of robotics. In systems of multiple robots, the creation of collision free paths becomes even more complex due to the fact that all robots must complete one specific task as a team. Forming a specific pattern while the robotic team covers a predefined distance, is a common task in cooperative robotics. The complexity of the problem increases with the number of members of the team. This paper proposes a novel path planning algorithm using a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) to create collision free paths for each robot of the team. The team is divided into subgroups and optimal paths are created using an ACO algorithm. If the algorithm is not applicable, for example, due to lack of pheromone, then paths are created using a CA path planner. The simplicity of the method relies on the fact that it uses fixed discrete values and a probabilistic method to reduce the complexity of the whole system. Simulation results indicate that the proposed method can produce accurate collision free paths even in systems comprising of large number of robots.
More and more attention is paid to epidemics of infectious diseases that spread through populations across large regions and under condition may result on increased mortality in the infected population. In this paper, a FPGA processor based on Cellular Automata (CA) able to produce successive epidemic fronts, as it is expected by theory, is presented. The proposed CA SIR (Susceptible, Infectious and Recovered) model successfully includes the effect of movement of individuals, on the epidemic propagation as well as the effect of population vaccination which reduces the epidemic spreading. The FPGA design results from the automatically produced synthesizable VHDL code of the CA model and is advantageous in terms of low-cost, high speed and portability. Finally, the resulted hardware implementation of the CA model is considered as basic component of a wearable electronic system able to provide real time in-formation concerning the epidemic propagation on the under test part of the examined population.
In this paper, the main interest is the fusion and the control of data that is obtained from a set of sensors. This task requires the use of a both effective and versatile computational model. The chosen architecture is the already known for its suitability Cellular Neural Network (CNN). This specific model, adopts some significant features, such as: continuous-time dynamics, local interconnection, reliability, simple implementation, low power consumption and as far as its behavior is concerned, great flexibility. Furthermore, it is taken into consideration, that depending on the application, the corresponding network dimension may vary. In order to confront this problem, a methodology is proposed for the automatic generation of CNNs of variable dimensions. The above task is achieved by developing an algorithm, which enables the combination of the basic CNN circuit counterparts, so as to produce the desired network dimensions.
With each new generation of integrated circuit (IC) manufacturing technology, the complexities of IC fabrication processes such as oxidation and selective oxidation are increasing significantly. On the other hand, predictive process modelling has proven to be a demanding goal, because the controlling physics is complicated and difficult to investigate experimentally. Technology computer-aided design (TCAD) that accurately predicts the outcome of IC fabrication processes is indispensable for future fabrication technology. Furthermore, hardware implementation of the TCAD algorithms that model the process in question would be a valuable tool in the hands of the process engineer giving him the opportunity to manipulate a powerful “virtual lab” dedicated to the modelling of the specific process. In order to develop an efficient TCAD system dedicated to the modelling of the oxidation fabrication process for which the hardware implementation will be straightforward Cellular Automata (CAs) were chosen as the simulation and implementation method. The simulation results of the proposed TCAD system based on the presented CA oxidation algorithm were found to be in very good qualitative agreement with the experimental results published in the literature. Moreover, because of the produced CA’s binary states and its local rule simplicity, the VLSI implementation of the proposed model is straightforward with the help of Genetic Algorithms (GAs). Finally, the dedicated processor that executes the final CA oxidation algorithm was designed to the level of a silicon compiler output.
A Cellular Automata (CA) based model for the simulation of pedestrian dynamics has been developed, capturing characteristic features of crowd dynamics, such as herding behaviour or clogging in front of exits. Using the Coulomb force as motion-driving mechanism the model calculates the Euclidean distance between the destination (source) and the pedestrian (test charge), allowing smoother change of direction. Introducing an electric field approach, charges of different magnitude represent main or internal exits as well as obstacles and walls. That charge rank in exit points ensures pedestrian guiding towards main exits, dominating upon possible different interior routes. Finally, the case of idiomorphic obstacles that trap pedestrians in recurrent motion is algorithmically encountered by introducing a limit in the number of aimless movement iterations to prevent pedestrians’ motion from deadlocks, by using a potential field technique.
In motion estimation, the sub-pixel matching technique involves the search of sub-sample positions as well as integer-sample positions between the image pairs, choosing the one that gives the best match. Based on this idea, the proposed disparity estimation algorithm performs a 2-D correspondence search using a hierarchical search pattern. The disparity value is then defined using the distance of the matching position. Therefore, the proposed algorithm can process non-rectified stereo image pairs, maintaining the computational load within reasonable levels.
Greece is referred as the most active seismically region of Europe and one of the top active lands in the world. However, the complexity of the available seismicity information calls for the development of ever more powerful and more reliable computational tools to tackle complex problems associated with proper interpretation of the obtained geophysical information. Cellular Automata (CAs) were showed to be a promising model for earthquake modelling, because certain aspects of the earthquake dynamics, function and evolution can be simulated using several mathematical tools introduced through the use of CAs. In this study, a three-dimensional (3-d) CA dynamic system constituted of cell-charges and taking into account the recorded focal depth, able to simulate real earthquake activity is presented. The whole simulation process of the earthquake activity is evolved with an LC analogue CA model in correspondence to well known earthquake models. The parameterisation of the CA model in terms of potential threshold and geophysical area characteristics is succeeded by applying a standard genetic algorithm (GA) which would extend the model ability to study various hypotheses concerning the seismicity of the region under consideration. As a result, the proposed model optimizes the simulation results, which are compared with the Gutenberg – Richter (GR) scaling relations derived by the use of real data, as well as it expands its validity in broader and different regions of increased hazard. Finally, the hardware implementation of the proposed model is also examined. The FPGA realisation of the proposed 3-d CA based earthquake simulation model will exhibit distinct features that facilitate its utilisation, meaning low-cost, high-speed, compactness and portability. The development and manufacture of the dedicated processor aims at its effective incorporation into an efficient seismographic system. As a result, the dedicated processor could realize the first stage of a perspective, real-time, efficient system for hazard evaluation and mapping of regional, dangerous phenomena.
Outdoor mobile robots which have to navigate autonomously in a totally unstructured environment need to auto-determine the suitability of the terrain around them for traversal. Traversability estimation is a challenging problem, as the traversability is a complex function of both the terrain characteristics (slopes, vegetation, rocks, …) and the robot mobility characteristics (locomotion method, wheel properties, …). In this paper, we present an approach where a classification of the terrain in the classes “traversable” and “obstacle” is performed using only stereo vision as input data. In a first step, high-quality stereo disparity maps are calculated by a fast and robust algorithm. Subsequently, the terrain classification is performed, based upon the analysis of the “v-disparity” image which provides a representation of the geometric content of the scene. Using this method, it is possible to detect non-traversable terrain items (obstacles) even in the case of partial occlusion and without any explicit extraction of coherent structures or any a priori knowledge of the environment. The sole algorithm parameter is a single factor which takes into account the robot mobility characteristics. The stereo disparity mapping and terrain traversability estimation processes are integrated in an autonomous robot control architecture, proving that the algorithms allow real-time robot control. Experiments with this robot on rough outdoor terrain show the benefits of the approach.
The rapid utilization of fuzzy inference systems in soft computing has led to their extensive analog and digital hardware implementations. One of the most critical elements in a fuzzy inference system is the used membership function generator. The demands in robustness, efficiency and modularity make the digital implementations a complicated task especially for non-linear function approximators. In this paper an analytical discussion of different reported digital membership functions generators is presented. Furthermore, an innovative dynamically programmable circuit capable of accurately approximating Gaussian membership function is presented. The proposed hardware structure is implemented in a field programmable gate array (FPGA) chip and is based on a sequence of pipeline stages and parallel processing, in order to minimize computational times. Its main features are the ability of accurate approximation of the Gaussian membership functions with very few memory requirements and its high frequency performance of 390 MHz, making it appropriate for real-time applications.
n this paper an effective, hardware oriented stereo correspondence algorithm, able to produce dense disparity maps of improved fidelity is presented. The proposed algorithm combines rapid execution, simple and straightforward structure as well as comparably high quality of results. These features render it as an ideal candidate for hardware implementation and for real-time applications. The proposed algorithm utilizes the Absolute Differences (AD) as matching cost and aggregates the results inside support windows, assigning Gaussian distributed weights to the support pixels, based on their Euclidean distance. The resulting Disparity Space Image (DSI) is furthered refined by Cellular Automata (CA) acting in all of the three dimensions of the DSI. The algorithm is applied to typical as well as to self-recorded real-life image sets. The disparity maps obtained are presented and quantitatively examined.
The settlement of the collision-free path planning problem is considered as a complicated objective and is of vital importance in systems constituted by one or multiple robots. In multi-robots systems, the path planning problem is based on cooperation. In such systems, the robots dynamically exchange roles in order to complete complicated tasks, such as moving in different formations. In this paper, a Cellular Automaton algorithm for solving the path planning problem in a multi-agent system is presented. Moreover, robots must cooperate to keep their initial formation if an unexpected event in the environment takes place. The proposed method was implemented in a real time system of three autonomous mobile robots. Simulation results and the results taken from the real system establish the method’s effectiveness and its robustness.
Crowd evacuation from buildings can be modelled with the use of Cellular Automata. The crowd consists of individuals and its behaviour is modelled by the response of each individual to a simple updating rule that directs him/her to the nearest exit as well as facilitates any object avoidance. Individual interactions are defined locally while the crowd motion emerges. In this paper, this motion approach is based on the concept of virtual potential fields that are defined by the location of exits, other pedestrians or objects. Electric charges located at exit and obstacle positions generate such fields. Characteristic features of crowd dynamics, such as incoherent-to-coherent pedestrian motion, blockings in front of exits and mass behaviour are successfully simulated. Finally, the paper presents the main architectural concepts of the corresponding dedicated FPGA processor, as the major structural part of an integrated, reactive, decision-support system.
In several cases, the DNA sequences of an organism are available in different stages of its evolution and it is desirable to reconstruct the DNA sequence in a previous evolution stage for which the exact sequence is not known. A CAD tool for backtracking the DNA sequence evolution based on Cellular Automata (CA) and Genetic Algorithms (GAs) was developed. Furthermore, the proposed system is able of automatic production of synthesizable VHDL code corresponding to the CA model. More specifically, DNA is modeled as a one-dimensional CA with four states per cell, i.e. the four DNA bases A, C, T and G. Linear evolution rules, represented by square matrices, are considered. The evolution rule can be determined using the global state of the DNA sequence in various evolution steps. This determination is accomplished using GAs. Moreover, because of the final produced CA’s binary states and its local rule simplicity, the hardware implementation of the proposed model is straightforward. Finally, the FPGA processor that executes the CA model was fully designed, placed and routed.
A 2D Cellular Automata (CA) dynamic system constituted of cells-charges has been proposed for the simulation of the earthquake process. The CA model has been calibrated with the use of real data and the simulation results are found in good quantitative and qualitative agreement with the recorded Gutenberg–Richter (GR) scaling relations. In this paper, the study is focused on two points; (a) the application of an extended neighbourhood regarding the activation range of the rule applied to each CA cell and (b) the optimal parameterisation of the model introducing the use of genetic algorithms. The former regards the incorporation in the CA activation rule of the deformation of the seismic waves as they propagate away from the source. The terms of near-field and far-field deformation, which are inverse proportional to the square of the distance and inverse proportional to the distance from the source correspondingly, have been included in the rule extending as well the active neighbourhood of each cell. The second point upgrades the parameterisation of the model by applying a standard genetic algorithm (GA). The GA evolves an initially random population of candidate solutions of model’s parameters, i.e. the potential threshold Vo and the size of the CA grid N, through genetic operators, e.g. mutation and crossover, such that in time appropriate (fitter) solutions to emerge. At every evolutionary step (generation), the candidate solutions are decoded and evaluated according to a predefined quality criterion, which is realised here by comparing in what extent the simulation results match the GR law derived from recorded data of the area under test.
Cellular Automata (CA) can sufficiently represent phenomena of arbitrary complexity and at the same time they can be precisely simulated by digital computers, because of their intrinsic discreteness. A two-dimensional (2-D) CA dynamic system has been proposed to efficiently model crowd behaviour inside bounded areas to contribute to the upgrade of public facilities. This paper examines the on-chip realisation of the proposed model. The hardware implementation of the CA model is based on FPGA logic. CA cells obtain discrete values, thus indicating their status; either free or occupied. Significant parameters of the local CA rule, such as the number and the allocation of the exits or the obstacles are inputs of the dedicated processor. Initial data is loaded to the dedicated processor in a semi-parallel way, i.e. all rows of the CA grid are loaded simultaneously while data propagates in a serial way from one cell of column j to the other cell of its successive column, j+1. The automatic response of the processor provides the signals that guide the crowd in correspondence to its density around exits. In collaboration with smart cameras, the proposed FPGA processor could be incorporated in an efficient, real-time, decision-support system that would be able to guide the crowd in cases of emergency, using sound and optical signals.
Contemporary autonomous robots are generally equipped with an abundance of sensors like for example GPS, Laser, ultrasound sensors, etc to be able to navigate in an environment. However, this stands in contrast to the ultimate biological example for these robots: us humans. Indeed, humans seem perfectly capable to navigate in a complex, dynamic environment using primarily vision as a sensing modality. After all, the world we live in, indoors or outdoors, was intentionally shaped, so as to serve its stereo vision-equipped inhabitants. This observation inspired us to investigate visually guided intelligent mobile robots. In order to understand and reason about its environment, an intelligent robot needs to be aware of the three-dimensional status of this environment. The problem with vision, though, is that perceived image is a two-dimensional input. Recovering 3D-information has been in the focus of attention of the computer vision community for a few decades now, yet no all-satisfying method has been found so far. Most attention in this area has been on stereo-vision based methods, which use the displacement of objects in two (or more) images. Where stereo vision must be seen as a spatial integration of multiple viewpoints to recover depth, it is also possible to perform a temporal integration. The problem arising in this situation is known as the “Structure from Motion” (SfM) problem and deals with extracting 3-dimensional information about the environment from the motion of its projection onto a two-dimensional surface. In this paper, we investigate the possibilities of stereo and structure from motion approaches. It is not the aim to compare both theories of depth reconstruction with the goal of designating a winner and a loser. Both methods have their merits and defects. The thorough, year-long research in the field indicates that accurate depth perception requires a combination of methods rather than a sole one. In fact, cognitive research has shown that the human brain uses no less than 12 different cues to estimate depth. Therefore, we finally introduce a methodology to integrate stereo and structure from motion approaches.
In this paper, a two-dimensional Cellular Automata (CA) model simulates the evacuation process of a crowd responding to fire spread. The crowd consists of individuals and its behaviour is modelled by the response of each individual to a rule that directs him/her to the nearest exit. Furthermore, fire spreading and movements of the crowd members while approaching the fire are successfully simulated. Empirical studies and socio-psychological concepts that attempt to explain how individuals act under fire threat have been considered. Characteristic features of crowd dynamics, such as incoherent pedestrian motion, blockings in front of exits and mass behaviour are effectively simulated. An efficient user-friendly interface has been equipped with parameters defining the arrangement of the area, crowd formation and fire features. Finally, the model is executed fast on a pc and can be used for planning evacuation strategies under fire threat or as part of a real-time decision support system.
Nowadays, embedded consumer devices are expected to support demanding applications in terms of performance and energy consumption. For implementing such applications on Network-on-Chips (NoCs) a design methodology for performing exploration at system-level is needed, in order to select the optimal application-specific NoC architecture. In this paper we present a methodology for designing application-specific NoC platforms at system-level. The methodology is based on the exploration of different NoC aspects (e.g. topology, routing algorithms etc.) and is supported by a flexible NoC simulator. In this work we apply our methodology to applications modeled with Cellular Automata (CA).
Stereo vision, resulting in the knowledge of deep information in a scene, is of great importance in the field of machine vision, robotics and image analysis. As a result, in order to address the problem of matching points between two images of a stereo pair several algorithms have been proposed so far. In this paper, an explicit analysis of the existing stereo matching methods, up to date, is presented in full detail. The algorithms found in literature can be grouped into those producing sparse output and those giving a dense result, while the later can be classified as local (area-based) and global (energy-based). The presented algorithms are discussed in terms of speed, accuracy, coverage, time consumption and disparity range. Comparative test results concerning different image sizes as well as different stereo data sets are presented. Furthermore, the usage of advanced computational intelligence techniques such as neural networks and cellular automata in the development and application of such algorithms is also considered. However, due to the fact that the resulting depth calculation is a computationally demanding procedure, most of the presented algorithms perform poorly in real-time applications. Towards this direction, the development of real-time stereo matching algorithms, able to be efficiently implemented in dedicated hardware is of great interest in the contexts of 3D reconstruction, simultaneous localization and mapping (SLAM), virtual reality, robot navigation and control. Some possible implementations of stereo-matching algorithms in hardware for real-time applications are also discussed in details.
In this paper a new image retrieval algorithm is proposed which aims to discard irrelevant images and increase the amount of relevant ones in a large database. This method utilizes a two-stage ant colony algorithm employing in parallel color, texture and spatial information. In the first stage, the synergy of the low-level descriptors is considered to be a group of ants seeking the optimal path to the “food” which is the most similar image to the query, whilst settling pheromone on each of the images that they confront in the high similarity zone. In the second stage additional queries are made by using the highest ranked images as new queries, resulting in an aggregate deposition of pheromone through which the final retrieval is performed. The results prove the system to be satisfactorily efficient as well as fast.
In order to understand the functioning of organisms at the molecular level, we need to know the genes which are expressed in the organism (when, where and how). The regulation of gene expression is achieved through gene regulatory networks of interactions between DNA, RNA, proteins, and small molecules. As most gene regulatory networks of interest involve many components connected through positive and negative feedback interlocking loops, an intuitive understanding of their dynamics is hard to obtain. As a consequence, computer tools for the study of genetic regulatory networks will be valuable. In this paper, we present a computational tool for gene regulatory networks. Our results demonstrate the utility of the specific computational tool in the quantitative analysis of the gene regulatory networks. Finally, the proposed tool allows the user to change several of its parameters, in order to study various hypotheses concerning the analysis of the genetic network under consideration.
Cellular Automata (CA), characterised by their massive parallelism, constitute a powerful tool for modelling and simulating complex natural phenomena. A two-dimensional (2-d) CA dynamic system constituted of cells-charges has been proposed for the simulation of the earthquake process. The CA model has been calibrated with the use of real data. The calibration incorporates major seismic characteristics of the area under test. The simulation results are found in good quantitative and qualitative agreement with the recorded Gutenberg–Richter (GR) scaling relations. The model is enriched with a powerful multi-parameter interface that enables the user to load real data from different regions. The present paper examines the on-chip realization of the model. The CA implemented utilizes an array of 34×34 cells. The local CA rule, the value of the potential threshold and the number of cycles the CA has to be iterated, i.e. the number of earthquake events, constitute the input data. Furthermore, the initial seed of the aforementioned implementation, which in some extend correspond to the seismic features of the area under test, is loaded in a semi-parallel way and the process is completed in 34 time-steps. The automatic response of the processor provides the corresponding GR scaling law of the under study area. Apart from the CA cell and interconnections implementation, a number of arithmetic units are required, in order to perform multiplications, shifts and subtractions. Except for multiplications, the other operations present trivial realization complexity. Consequently, the proposed CA implementation would be advantageous in terms of compactness, portability, high-speed, low-cost and it could be easily incorporated in an efficient seismographic system.
Crowd safety and comfort in highly congested places not only depend on the design and the function of the place, but also on the behaviour of each individual. In this paper, an integrated evacuation system is described. The proposed system comprises three stages. The main stage includes an efficient computational tool based on Cellular Automata (CA) capable of simulating main features of pedestrian dynamics during the evacuation of large areas, sup-ported by a multi-parameterised graphical-user interface (GUI). Moreover, an image-processing tracking algorithm is used for the calibration of the system providing all the necessary information about the number of individuals and their distribution in the under test area. Finally, the VLSI implementation of the proposed model is straightforward due to the simplicity of the CA rule, thus leading to the design of a dedicated processor.
As device lots become more and more expensive, the importance of technology computer-aided design (TCAD) is increasing. TCAD can be used to simulate device fabrication and performance and to avoid processing experimental lots. Cellular Automata (CAs) have been applied successfully to the simulation of several physical systems and semiconductor processes, and have been extensively used as VLSI architecture. This paper describes a TCAD system for the simulation of the two-dimensional oxidation process in integrated circuit fabrication. The TCAD system is fully automated and is also able to support, the hardware implementation of the corresponding CA algorithm, leading to its execution by dedicated parallel processor. The simulation results are in good qualitative and quantitative agreement with experimental data reported in literature. The proposed system produces as output the corresponding VHDL code, which leads directly to the FPGA implementation of the CA algorithm.
Gene networks are collections of gene–gene regulatory relations in a genome (or a subset thereof). Gene networks are useful to rationalize phenomena in terms of how external perturbations propagate through the expression of genes. On the other hand, computing network interactions and dynamical rules from experimental data comprising large numbers of genes becomes possible, in many cases, by harnessing advanced mathematical, statistical, and machine learning methods of pattern analysis and inference. In this paper we propose a computational tool, based on Cellular Automata (CAs), which is able to study, in correspondence to the observed data, the regulatory pathways that are represented as influence matrix. The proposed tool exhibits the properties of the regularly computing inferred networks, as well as their cognitive dynamics from the large-scale experimental data. More specifically, the tool takes into account the number of related genes which can count up to thousands incorporating both long-range interactions and short-range gene interactions, and consequently it handles successfully the resulting simulated data. It should be also mentioned that a user-friendly interface that enables easy and effective interaction between the user and the proposed tool has been also developed and presented in this paper.
The movement of large numbers of people is important in many situations, such as the evacuation of a building in an emergency. In this paper, pedestrian dynamics during the evacuation of large areas is simulated using a computational intelligent technique, based on Cellular Automata. The characteristic feature of the proposed model is that the crowd consists of independent parts rather than treated as homogeneous mass. The crowd behaviour is artificially formatted by the response of each of these parts to the rule according to which each pedestrian reaches one of the possible exits. Furthermore, an efficient graphical user interface has been developed, in order to study various hypotheses concerning the pedestrians’ activity features. Collisions among pedestrians have been encountered while collective effects prominent at crowd behaviour have been also realised during simulation. Finally, the presence of fixed as well as user-defined moveable obstacles has been taken into account.
In this paper a one dimensional (1-d) Cellular Automaton (CA) for pseudorandom number generation (PRNG) and its reconfigurable hardware implementation are presented. The proposed 1-d CA based on the real time clock sequence (analytical time description) can generate high-quality random numbers which can pass all of the statistical tests of DIEHARD and NIST which seem to be the most powerfully complete general test suites for randomness. After describing our implementation in field-programmable gate array (FPGA), through experiments, we have identified the efficiency of the presented CA that performs exceptionally well compared to most known CA PRNGs reported in literature. More specifically, our CA implementation outperforms all the previous CA and LFSR PRNGs both in hardware implementation and timing characteristics. Such a CA can be efficiently implemented for PRNG reasons in every real time clock application with finally no silicon overhead.
Cellular Automata (CA), characterised by their massive parallelism, constitute a powerful tool for modelling and simulating complex natural phenomena, which are represented by complicated non-linear differential equations and can hardly be approached by standard numerical methods. A two-dimensional CA dynamic system comprised of cells-charges was recently proposed for the simulation of the earthquake process. In this paper, the study has been focused on a seismic energy based estimation of the initial conditions as well as on the enrichment of the recorded data that is used in order to test the model. Applying a retrospective approach as far as it concerns the validation of the Gutenberg – Richter relation of the recorded number of earthquakes at a certain region, the initial values of the CA cells play a significant role. Using the recorded data, the seismic energy that has been released during a certain time period is being evaluated for each cell. This value acts as a weight factor either enforcing or weakening the initial condition of the corresponding cell. Furthermore, the data that is used concern an area of moderate seismicity, namely the region of Macedonia and Thrace. A satisfactory number of strong (M6) earthquakes are included, thus increasing the credibility of the conclusions about the seismic properties of the area. The model optimizes the simulation results, which are compared with the Gutenberg – Richter scaling relations derived by the use of real data, as well as it expands its validity in broader and different regions of increased hazard. Finally, the user-friendly interface of the model has been enriched to further enhance its prominent features of low storage requirements, small processing time and extended parameterisation.
An increasingly popular model of regulation is to represent networks of genes as if they directly affect each other. Although such gene networks are phenomenological because they do not explicitly represent the proteins and metabolites that mediate cell interactions, they are a logical way of describing phenomena observed with transcription profiling. In this paper we present a computational tool, based on Genetic Algorithms (GAs), which is able to predict with observed data the regulatory pathways that are represented as influence matrix. The ability to create gene networks from experimental data and use them to reason about their dynamics and design principles will increase our understanding of cellular function.
A tool for simulation and modeling of wired/wireless computer networks based on Cellular Automata (CAs), is presented. More specifically, a two-dimensional NaSch CA model for computer network simulation has been developed and implemented in the proposed tool. Furthermore, algorithms for connectivity evaluation, system reliability evaluation and shortest path computation in a wired/wireless computer network have also been implemented. The Net_CA system was designed and developed as an interactive tool that offers automated modeling with the assistance of a dynamic and user friendly graphical environment. The simulation algorithms developed in the present work offer high flexibility. Furthermore, connection reliability and other important parameters are inputs to the algorithms rendering Net_CA a very reliable and fast simulator for wireless networks, ad hoc networks and, generally, for low connection reliability networks.
DNA sequence is essential to all forms of life and is of fundamental importance to the whole of biology. In this paper a Cellular Automata (CA) classical model for backtracking the DNA sequence evolution with the help of Genetic Algorithms (GAs) is constructed. A simulator for DNA sequence evolution by extracting CA rules is developed based on this model. This simulator has a user-friendly interface and the user can change several of its parameters, in order to study various hypotheses concerning DNA evolution models.
Content-based Image Retrieval (CBIR) is generally known as a collection of techniques for retrieving images on the basis of features, such as color, texture and shape. An efficient tool in CBIR is that of image histograms. In this paper a new image retrieval method is proposed with the use of histograms in conjunction with cellular automata (CAs). The main thrust of this paper is the classification of the images in the database by CAs and the retrieval of the desired images by a simple histogram extracted from the hue component of the HSV color space. Moreover, because of the CAs local rule simplicity, the VLSI implementation of the proposed CA algorithm is straightforward.
Among others, stereo vision analysis deals with the extraction of depth in a scene, using the disparity between the images acquired by a stereo camera setup. The disparity calculation for the whole of an image is mostly a computation demanding procedure, commonly being performed by dedicated hardware. In this paper a hardware architecture for real time extraction of disparity maps is proposed, capable of processing images of 1MPixels in less than 25ms. The produced disparity maps are intended to be used for real-time navigation of a mobile platform, as well as in other time critical application which demand 3D information.
Stereo vision analysis deals with the extraction of 3D coordinates of a scene, using images acquired by a stereo camera setup. We propose a three stage technique for the accurate retrieval of dense disparity maps. A major advantage of this new technique is that it can be implemented straightforwardly in hardware.
Seismicity is an extended geophysical characteristic of Greek dominion. There are certain areas of high seismic activity, as well as, regions of low seismicity where strong earthquakes are rather rare events. Consequently, it is of great interest to study the earthquake process in Greece even for areas considered to be of low seismicity. In this paper, the study of the earthquake activity of an area at the Northeast of Greece, centred at Xanthi, Thrace, extended over a region of a scaling radius during a certain time period, is presented. A two-dimensional cellular automaton (CA) dynamic system constituted of cells-charges is proposed for the simulation of the earthquake process. The proposed model is constructed in order to simulate earthquake activity in correspondence to the quasi-static two-dimensional version of the Burridge-Knopoff spring-block model of earthquakes, as well as, to the Olami-Feder-Christensen (OFC) earthquake model. The aforementioned CA model has been calibrated based on the seismicity of the above-mentioned region, the density of the recorded events as well as the corresponding initial conditions. The simulation results are found in good quantitative and qualitative agreement with the Gutenberg–Richter (GR) scaling relations emerged by the use of the recorded data over these co-centric circular regions. Finally, the CA model has a user-friendly interface and enables the user to change several of its parameters, in order to study various hypotheses concerning the seismicity of the region under consideration.
In this paper a potential – based model for earthquake simulation that is a two-dimensional cellular automaton dynamic system constituted of cells-charges, is presented. The proposed model is constructed in order to simulate earthquake activity in correspondence to the quasi-static two-dimensional version of the Burridge-Knopoff spring-block model of earthquakes, as well as, to the Olami-Feder-Christensen (OFC) earthquake model. The simulation results are found in good quantitative and qualitative agreement with the Gutenberg–Richter (GR) scaling relation predictions. Numerical results for various cascade (earthquake) sizes and different critical states are presented. Furthermore, the parameter of different neighbourhood in the proposed model is also explored.
The continuous miniaturization and the increased complexity of today’s integrated circuits has led to a demand for faster simulation algorithms for physical processes. A method for designing a dedicated processor, which executes a cellular automaton (CA) algorithm that simulates the selected locally interacting system or physical process, using a genetic algorithm (GA), is described in this paper. An application example of the proposed method namely forest fire spreading is also presented. Starting from a CA with continuous state space which simulates the physical process, each time, the GA is used to find a CA with discrete state space, having the smallest possible lattice size and the smallest possible number of discrete states, the results of which are as close as possible to the results of the CA with continuous state space. The dedicated processor that executes the discrete CA algorithm was designed to the level of a silicon compiler output. This processor can be used as a part of a decision support system.
Ecological systems are generally considered among the most complex ones, because they are characterized by a large number of diverse components, nonlinear interactions, scale multiplicity, and spatial heterogeneity. In this paper a methodology for modeling ecological systems using cellular automata (CAs) is presented. The proposed methodology establishes the ability to capture the essential features-characteristics of the ecological system under consideration, and translate them into a suitable form, in order to obtain an effective CA model. The CA models obtained are of crucial importance in ecological engineering, and they could be used as decision support systems in environmental emergency response. Further, a complete description of the details of this methodology is specified, in order to help other researchers reproduce published simulation experiments. Forest fire spreading and oil slick movement and spreading are considered as possible applications of the proposed methodology. The models obtained can serve as a basis for the development of algorithms to simulate environmental and biological systems based on real data. Moreover, Application Specific Integrated Circuits (ASICs) that would execute and speed up the corresponding algorithms could be designed with the help of VHSIC Hardware Description Language (VHDL).
An algorithm for the direct conversion of Boolean expressions into VHSIC Hardware Description Language (VHDL) is proposed for the first time. This algorithm can handle complicated Boolean expressions, producing automatically synthesizable VHDL code. The conversion algorithm developed in this work, has as input the Boolean expressions defined by the user, and as output the corresponding VHDL code. No previous knowledge of VHDL is required by the user of this algorithm, since the conversion algorithm produces directly the VHDL synthesizable code. To facilitate the use of this algorithm, a CAD tool with a user-friendly graphical interface has been developed. The VHDL code, thus obtained, can be introduced as input to any commercial VLSI CAD system. As a result, the research workers may use the synthesizable VHDL codes produced as components to design hierarchically their higher-level digital circuits.
The development of next-generation VLSI circuits with deep submicron technologies has demanded fundamental understanding of the wafer surface reaction kinetics. Technology computer-aided design (TCAD) is essential for modeling real fabrication processes accurately, and allowing predictive simulation during technology research and development. This paper describes a two-dimensional Chemical Vapor Deposition (CVD) process TCAD system based on cellular automata (CAs). The proposed TCAD system can handle the complicated boundary and initial conditions imposed by defects and provide SEM-like cross sectional views. The simulated profiles obtained are in very good agreement with experimental and simulation results found in the literature. Furthermore, a user-friendly interface that enables easy and effective interaction between the user and the TCAD system has been developed.
Photolithography, oxidation and deposition are the most important process steps during integrated circuit (IC) fabrication. As the ICs are pushed deeper into the submicrometer region, the presence of non-planarity and defects are becoming major yield detractors. In this work, we have studied these effects using a two-dimensional technology computer-aided design (TCAD) system based on cellular automata (CAs), which we have named CA_TCAD. CA_TCAD comprises a photolithography, an oxidation and a deposition simulator. The photolithography simulator has been tested, verified, and calibrated, with a series of experiments with periodic and isolated lines on negative resist coated Si wafers, using a stepper and a Deep UV source at 248nm. The other two simulators can provide SEM-like cross sectional views and the simulated profiles obtained are in very good agreement with experimental results found in the literature.
An adaptive Genetic algorithm for VLSI circuit partitioning and another for VLSI circuit placement are presented in this paper. These Genetics algorithms are able to modify some of their own parameters during the search, based on their performance. These parameters are: population size, crossover rate and mutation rate. The algorithms are applied to partitioning and placement of a circuit, respectively, and their performance is compared with the performance of a non-adaptive Genetic algorithm. The proposed Genetic algorithms lead to significantly superior solutions in less computation time.
A new oxidation simulator for technology computer aided design (TCAD) is presented in this paper. The solution, on a cellular automaton lattice of the equations that describe the oxidation process has enabled the proposed simulator to handle the complicated boundary and initial conditions imposed by the advancement of the Si-SiO2 and SiO2-air fronts during oxidation in unbounded as well as in bounded domains. The simulator reproduced successfully the oxidation profiles in the case of the presence of contamination on the Si surface. The effects of oxidation through a mask have also been successfully simulated and the simulation results are in very good agreement with experimental data.
In this paper, two Genetic Algorithms (GAs) are presented. The first GA solves the VLSI circuit partitioning problem, while the second one solves the VLSI circuit placement problem. Numerical results of the execution of the two GAs are depicted.
preload preload preload