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Territorial surveillance plays a constantly increasing role in security. However, completely automatic surveillance using autonomous robots is hard to implement and maintain. Current methods described in literature propose systems that include direct communication of the robots or the use of a centralised system to coordinate the robots. These systems are prone to equipment failure and/or malicious attacks to the centralised system. In this paper, we propose a bioinspired algorithm that allows indirect communication between the robots that are considered minimally equipped. This is achieved by applying a parallel and distributed technique inspired by the emergent behaviour of social insects, namely ant colonies. In particular, the development of a collective memory for robots and areas covered is achieved subsequently through self-organisation of the autonomous robots to a continuous dynamic coverage of the test space. The algorithm is shown to have a robust behaviour and competitive performance. Several simulations run for various space sizes, different number of robots, different pheromone evaporation rates as well various percentages of space covered by obstacles. In all cases the efficacy of the proposed algorithm has been successfully proven when compared with other well known techniques. (a) Routes of 3 robots using multiple and different pheromones, (b) representation of the space that has seen covered by the robots of (a). [ABSTRACT FROM AUTHOR]

The continuous increment in the performance of classical computers has been driven to its limit. New ways are studied to avoid this oncoming bottleneck and many answers can be found. An example is the Belousov-Zhabotinsky (BZ) reaction which includes some fundamental and essential characteristics that attract chemists, biologists, and computer scientists. Interaction of excitation wave-fronts in BZ system, can be interpreted in terms of logical gates and applied in the design of unconventional hardware components. Logic gates and other more complicated components have been already proposed using different topologies and particular characteristics. In this study, the inherent parallelism and simplicity of Cellular Automata (CAs) modeling is combined with an Oregonator model of light-sensitive version of BZ reaction. The resulting parallel and computationally-inexpensive model has the ability to simulate a topology that can be considered as a one-bit full adder digital component towards the design of an Arithmetic Logic Unit (ALU). [ABSTRACT FROM AUTHOR]

Theoretical constructs of logical gates implemented with plant roots are morphological computing asynchronous devices. Values of Boolean variables are represented by plant roots. A presence of a plant root at a given site symbolises the logical True , an absence the logical False . Logical functions are calculated via interaction between roots. Two types of two-inputs–two-outputs gates are proposed: a gate 〈 x , y 〉 → 〈 xy , x + y 〉 where root apexes are guided by gravity and a gate 〈 x , y 〉 → 〈 x ¯ y , x 〉 where root apexes are guided by humidity. We propose a design of binary half-adder based on the gates. [ABSTRACT FROM AUTHOR]

In this paper, an automated electronic system able to reproduce the complex dynamic behaviors of the train movement is presented. In specific, a Cellular Automaton (CA) model was developed in order to provide efficient control of the railway traffic flow under different complicated situations such as trains of greater and different speed and length, priority at level crossings, more than one station platforms, different and probably longer station dwell times, possible deceleration for sudden cause, i.e. railway blockage, etc. Furthermore, in order to take full advantage of the inherent parallelism and fundamental features of the CAs, the proposed model was implemented on Field Programmable Gate Array (FPGA). 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 latter also includes a high performance Global Positioning System (GPS) wireless communication module for the monitoring of train activity in the under study railway. This 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 CA model. Finally, some real case experiments took place in the railway network of Eastern Macedonia-Thrace of Greece and the experimental results validate the calibration of the CA model as well as of the proposed electronic system and their ability to control train movement. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

An introduction is presented which discusses various topics within the issue including analogy between propositional logic and Cellular Automata (CA) theory, the dynamics of Stochastic Elementary CA and the Cellular Automata for Research and Industry (ACRI) 2014 Conference on CA.

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. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

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. (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Highlights: [•] A new way to maximize the coverage of an examined floor plan in a dynamic fashion. [•] Bio-inspired bee and spider agents for evolving crowd analysis. [•] Utilize simulated pedestrian data to observe the density of crowd areas. [•] Three new challenging floor plans are now examined. [•] Three algorithms are compared along the proposed method for their performance. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented which discusses various papers published within the issue, including one on cellular automata (CA) modeling of enteric nervous system colonization, one on a characterization of DNA tile computing via a CA approach, and another on a CA approach to lossless visual multimedia content encryption.

Abstract: 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 2 n ×n (n×2 n ) 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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 the most 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. [ABSTRACT FROM PUBLISHER]

Abstract: 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. [Copyright &y& Elsevier]

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 I-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. [ABSTRACT FROM AUTHOR]

The article presents a hardware implementation of a fuzzy-modified ant colony processor which is said to be suitable for image retrieval. In this study, the proposed method by the researchers 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. Researchers found that the fuzzy processor exhibits a level of inference performance of 800 K fuzzy logic inferences per second with 24 rules.

This article presents a study regarding the increasing complexity of computer networks calls for developing new models for their simulation. It examines a system for modeling and simulation of computer networks based on cellular automata. It discusses that system reliability evaluation, algorithms for connectivity evaluation, and shortest path computation in a computer network have been implemented. The system was developed and designed as an interactive tool that offers automated modeling with the assistance of a dynamic and user-friendly graphical environment.

Quantum-dot Cellular Automata (QCA) technology has been considered as one promising solution to deal with the beyond Moore's law and after von Neumann's computing architecture issues, bringing advantages such as high performance and low energy consumption. In this paper, we focus on the implementation in QCA technology of one of the most well-known Cellular Automaton (CA), namely the Game of Life (GoL). GoL introduced by John Conway is one of the most interesting CA, due to the abilities of self-production and computational universality. In this work, a novel fault-tolerant implementation of GoL in programmable crossbar architecture is proposed delivering the computation universality of the GoL in a plausible way. For the provided design, fault-tolerant majority and inverter gates are also presented in a programmable crossbar architecture. Such an implementation provides the QCA circuits designers with an almost endless library of ready-to-use applications, in various scientific fields. Extensive performance evaluation coupled with appropriate simulation results validate the efficacy of the proposed QCA design depicting appropriately the inherent complexity of the GoL rules and structures. [ABSTRACT FROM AUTHOR]

One of the most famous problems in computer science and cellular automata (CAs) is the Firing Squad Synchronization Problem (FSSP). In the FSSP, a one-dimensional CA with just a single active cell (initially called "General") eventually reaches a state in which all the CA cells (called "soldiers" in analogy to real-world firing squad) are simultaneously active. Since the introduction of the FSSP as a well known problem in the 60's, and during the last decades, many FSSP solution algorithms have been proposed in the literature. Nevertheless, the inherited error correction capabilities of these algorithms have not been extensively studied. In this paper, an error detection and correction algorithm that utilizes the patterns appearing in 1-D Mazoyer's 8-state solution is analyzed and presented. Furthermore, the patterns of 2-D Umeo's FSSP algorithm are also thoroughly investigated. In such a case, extra patterns emerge from CA cells grouping, during the application of 1-D FSSP solution to 2-D CA grid, enhancing the error tolerance of the proposed algorithm, i.e. almost every possible error can be detected. Finally, another version, even more efficient, of error detection and correction algorithm with memory effect considering previous CA states usage, is also introduced. Although the usage of previous CA states results to increased utilization of computational resources, at the same time it enables the proposed algorithm to detect every possible error state in every possible CA cell, advancing significantly the algorithm's performance. [ABSTRACT FROM AUTHOR]

This study presents a novel solution for ambient assisted living (AAL) applications that utilizes spiking neural networks (SNNs) and reconfigurable neuromorphic processors. As demographic shifts result in an increased need for eldercare, due to a large elderly population that favors independence, there is a pressing need for efficient solutions. Traditional deep neural networks (DNNs) are typically energy-intensive and computationally demanding. In contrast, this study turns to SNNs, which are more energy-efficient and mimic biological neural processes, offering a viable alternative to DNNs. We propose asynchronous cellular automaton-based neurons (ACANs), which stand out for their hardware-efficient design and ability to reproduce complex neural behaviors. By utilizing the remote supervised method ( R e S u M e ), this study improves spike train learning efficiency in SNNs. We apply this to movement recognition in an elderly population, using motion capture data. Our results highlight a high classification accuracy of 83.4 % , demonstrating the approach's efficacy in precise movement activity classification. This method's significant advantage lies in its potential for real-time, energy-efficient processing in AAL environments. Our findings not only demonstrate SNNs' superiority over conventional DNNs in computational efficiency but also pave the way for practical neuromorphic computing applications in eldercare. [ABSTRACT FROM AUTHOR]

The use of Cellular Automata (CA) in combination with Learning Automata (LA) has demonstrated effectiveness in handling hard-to-be-solved problems. Due to their capacity to learn and adapt, as well as their inherent parallelism, they can expedite the problem-solving process for a range of problems, such as challenging logic puzzles. One such puzzle is Sudoku, which poses a combinatorial optimization challenge of great difficulty and complexity. In this study, a Sudoku puzzle was represented as an Irregular Learning Cellular Automaton (ILCA), using a reward and penalty algorithm to resolve it. Simulations for an amount of 400 puzzles were performed, while the results demonstrate that the proposed algorithm operates effectively, highlighting the concurrent and learning capabilities of the ILCA structure. Furthermore, two different performance enhancement methods are investigated, namely learning rates method and selective probability reset rule, which are able to increase the initial performance by 26.8 % and to achieve an overall 99.3 % resolution rate. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented which discusses various papers published within the issue, including "Modelling and Simulation of Complex Cellular Automata Using Cell-DEVS," "Modeling Pedestrian Behavior With Cell-DEVS," and "Graph Cellular Automata Approach to the Maximum Lifetime Coverage Problem in Wireless Sensor Networks."

This study validated muscle activation estimations generated by OpenSim during the gait of elderly fallers. Ten healthy elderly participants walked on an instrumented treadmill, monitored by motion capture, force platforms, and 12 surface EMG sensors. Static optimization was used to calculate muscle activations, evaluated through cosine similarity, comparing them with EMG signals from 12 muscles of the right leg. Findings revealed varied similarity levels across muscles and gait phases. During stance phase, tibialis anterior (TIBA), peroneus longus (PERL), soleus (SOL), gastrocnemius lateralis (GASL), semitendinosus (SEMI), tensor fasciae latae (TFL), and rectus femoris (RECF) demonstrated poor similarity (cosim < 0.6), while gluteus medius (GMED), biceps femoris long head (BFLH), and vastus lateralis (VL) exhibited moderate similarity (0.6 ≤ cosim ≤ 0.8), and gluteus maximus (GMAX) and vastus medialis (VASM) displayed high similarity (cosim > 0.8). During the swing phase, only SOL demonstrated inadequate similarity, while GASL, GMAX, GMED, BFLH, SEMI, TFL, RECF, and VASL exhibited moderate similarity, and TIBA, PERL, and VASM showed high similarity. Comparing the different 10% intervals of the gait cycle generally produced more favorable similarity results. For most of the muscles and intervals, good agreement was found. Moderate agreement was estimated in the cases of TIBA (0–10%), PERL (60–70%), GASL (60–70%), TFL (10–20%), RECF (0–10%, 80–100%), and GMED (50–60%). Bad agreement was found in the cases of SOL (60–70%), GASL (0–10%), and TFL (0–10%). In conclusion, the study's validation outcomes were acceptable in most cases, underlining the potential for user-friendly musculoskeletal modeling routines to study muscle output during elderly gait. [ABSTRACT FROM AUTHOR]

Games-of-chance require high-levels of trust between participants that is often uncertain and difficult to enforce. The unique characteristics introduced by the blockchain technology can be leveraged to inform a verifiable but transparent pseudo-random generation process that at the same time eliminates the need of an external trustee service or oracle to guarantee the fair execution of the process. We propose a process that builds on a one-dimensional Cellular Automaton (CA) where the evolution of the CA aligns to the evolution of a blockchain. Given an initial seed defined as the point in time where the evolution of the CA is triggered, the set of transition rules, along with the finite number of evolution steps, any external oracle is able to verify and backtrack (but not predict) the outcome of the process. The effectiveness of the implemented system is confirmed by the use of various statistical testing suites that confirm the existence of a set of statistical properties required to produce sufficient pseudo-random number sequences. [ABSTRACT FROM AUTHOR]

An estimation of the electric sources in the heart was conducted using a novel method, based on Huygens' Principle, aiming at a direct estimation of equivalent bioelectric sources over the heart's surface in real time. The main scope of this work was to establish a new, fast approach to the solution of the inverse electrocardiography problem. The study was based on recorded electrocardiograms (ECGs). Based on Huygens' Principle, measurements obtained from the surfaceof a patient's thorax were interpolated over the surface of the employed volume conductor model and considered as secondary Huygens' sources. These sources, being non-zero only over the surface under study, were employed to determine the weighting factors of the eigenfunctions' expansion, describing the generated voltage distribution over the whole conductor volume. With the availability of the potential distribution stemming from measurements, the electromagnetics reciprocity theorem is applied once again to yield the equivalent sources over the pericardium. The methodology is self-validated, since the surface potentials calculated from these equivalent sources are in very good agreement with ECG measurements. The ultimate aim of this effort is to create a tool providing the equivalent epicardial voltage or current sources in real time, i.e., during the ECG measurements with multiple electrodes. [ABSTRACT FROM AUTHOR]

Various synchronization algorithms have been introduced in literature during the last decades to deal with the firing squad synchronization problem on cellular automata (CA). Among others defective CA algorithms, where the CA cell is able to transmit information without previous processing, have been also presented. In our case, originating from the classical Mazoyer’s paper, where a minimum-time solution is presented with 6 states, a one-dimensional CA where one cell may permanently fail is presented. In the proposed algorithm, the defective cell can neither process nor transmit information any longer, while it is considered that such dynamic defects may become apparent in any time step of computation. A thorough analysis of the synchronization, in terms of location and time at which cell fails, for the cells found in both sides of defective cell is delivered to decipher the corresponding maximal possible number of synchronized cells in each part of the cut, due to defect, CA array. The proposed algorithm is properly extended to consider more than one defective cells that may occur in the under study one-dimensional CA. Based on the aforementioned analysis, we provide the generalization of synchronization with multiple totally defective cells, while application examples of the generalized CA algorithm in case of two defective cells are also presented. Finally, another intriguing aspect refers to handling of states that could be tentatively characterized as unknown, in a confrontation similar to the previous defective state but also different, since now this(these) cell(s) are not stated as faulty but unknown. As a result, a new one-dimensional CA with less states, compared to the previous CA defective algorithms, able to synchronize the maximal possible number of cells in each part occurs. [ABSTRACT FROM AUTHOR]

Cellular Automata (CA) have been considered one of the most pronounced parallel computational tools in the recent era of nature and bio-inspired computing. Taking advantage of their local connectivity, the simplicity of their design and their inherent parallelism, CA can be effectively applied to many image processing tasks. In this paper, a CA approach for efficient salt-n-pepper noise filtering in grayscale images is presented. Using a 2D Moore neighborhood, the classified "noisy" cells are corrected by averaging the non-noisy neighboring cells. While keeping the computational burden really low, the proposed approach succeeds in removing high-noise levels from various images and yields promising qualitative and quantitative results, compared to state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

A kombucha is a tea and sugar fermented by over sixty kinds of yeasts and bacteria. This symbiotic community produces kombucha mats, which are cellulose-based hydrogels. The kombucha mats can be used as an alternative to animal leather in industry and fashion once they have been dried and cured. Prior to this study, we demonstrated that living kombucha mats display dynamic electrical activity and distinct stimulating responses. For use in organic textiles, cured mats of kombucha are inert. To make kombucha wearables functional, it is necessary to incorporate electrical circuits. We demonstrate that creating electrical conductors on kombucha mats is possible. After repeated bending and stretching, the circuits maintain their functionality. In addition, the abilities and electronic properties of the proposed kombucha, such as being lighter, less expensive, and more flexible than conventional electronic systems, pave the way for their use in a diverse range of applications. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Microbial Fuel Cell (MFC) is a bio-electrochemical transducer converting waste products into electricity using microbial communities. Cellular Automaton (CA) is a uniform array of finite-state machines that update their states in discrete time depending on states of their closest neighbors by the same rule. Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. We provide a theoretical design of such a parallel processor by implementing CA in MFCs. We have chosen Conway’s Game of Life as the ‘benchmark’ CA because this is the most popular CA which also exhibits an enormously rich spectrum of patterns. Each cell of the Game of Life CA is realized using two MFCs. The MFCs are linked electrically and hydraulically. The model is verified via simulation of an electrical circuit demonstrating equivalent behaviours. The design is a first step towards future implementations of fully autonomous biological computing devices with massive parallelism. The energy independence of such devices counteracts their somewhat slow transitions—compared to silicon circuitry—between the different states during computation. [ABSTRACT FROM AUTHOR]

The spatial search problem is an interesting and important problem in computer science and especially the area of algorithms. The objective is a marked site to be found in a finite physical space, that can be modeled as a finite lattice or a graph. Many approaches have been developed to address this problem. Classical random walks and quantum walks are efficient models that address the spatial search problem. Quantum walks is a universal model of quantum computation and can be mapped directly to quantum circuits and consequently executed on quantum computers. Quantum walks utilized for quantum search proved to achieve significantly lower hitting times than their classical counterpart, classical random walks. The evolution space for the quantum walks as well as the classical random walks is up until now a free space. In our approach, we introduce external electrical potentials to the evolution space. We study the evolution of discrete time quantum and classical random walks in such potential spaces and the probability — hitting time on finding marked sites. We considered the differences in applied potential among neighboring sites as weights for the lattice — graph. We introduce these weights to the evolution space as an operator for the discrete time quantum walk and as coin probabilities for the classical random walk. Our results show that quantum walks again, evolve faster in the evolution space with the applied potential. Quantum walks also achieve better probability — hitting time on finding the marked site in the potential space. With the introduction of electrical potentials, quantum walks evolving in potential spaces, can lead to the development of novel quantum algorithms, where input parameters can be introduced as external potentials. • Extended discrete time quantum walk model. • Electrical potentials as weights to the evolution space of the quantum walk. • Quantum and classical random walks spatial search in potential spaces. [ABSTRACT FROM AUTHOR]

In this study, we introduce an application of a Cellular Automata (CA)-based system for monitoring and estimating the spread of epidemics in real world, considering the example of a Greek city. The proposed system combines cellular structure and graph representation to approach the connections among the area's parts more realistically. The original design of the model is attributed to a classical SIR (Susceptible–Infected–Recovered) mathematical model. Aiming to upgrade the application's effectiveness, we have enriched the model with parameters that advances its functionality to become self-adjusting and more efficient of approaching real situations. Thus, disease-related parameters have been introduced, while human interventions such as vaccination have been represented in algorithmic manner. The model incorporates actual geographical data (GIS, geographic information system) to upgrade its response. A methodology that allows the representation of any area with given population distribution and geographical data in a graph associated with the corresponding CA model for epidemic simulation has been developed. To validate the efficient operation of the proposed model and methodology of data display, the city of Eleftheroupoli, in Eastern Macedonia—Thrace, Greece, was selected as a testing platform (Eleftheroupoli, Kavala). Tests have been performed at both macroscopic and microscopic levels, and the results confirmed the successful operation of the system and verified the correctness of the proposed methodology. [ABSTRACT FROM AUTHOR]

This study presents an application that estimates all possible paths within an urban environment and proposes the optimal one according to objective criteria and individualized options. The application grounds its functionality on a Cellular Automaton (CA) that models the area of interest and provides the rule that activates the processing of input data. The model incorporates the term walkability as a discrete magnitude that integrates qualitative features of pedestrian mobility. The proposed application fosters sustainable forms of movement at a local level that undoubtedly improves the human physical status and upgrades civilian living conditions. In the context of this paper, we provide a thorough description of the operational principles of the model, and we test its validity by applying it in Xanthi, a medium size city located in northeastern Greece. Finally, we describe variants of the initial scenario to demonstrate the sensibility of the model in external assessments as well as its resilience in biasing manipulations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 arc triggered by simple rules applied locally to each of the group members. These CA rules arc 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. [ABSTRACT FROM AUTHOR]