Search

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]

Computational acceleration for image processing tasks on the edge is becoming increasingly important for many applications. This work presents a new neuro-inspired architecture which incorporates inmemory computing properties for image processing complex computational tasks in addition to analog memory. The proposed architecture was based on segmented crossbar topology, which, as it turns out, reduces many phenomena that affect the performance on such systems. The extended architectural capabilities of this structure were also tested in a systematic analysis that was performed on a novel depth map extraction application from a single defocused image. All results were validated through Spice simulations using a novel moving barrier memristor model. [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]

During the last years, a well studied biological substrate, namely Physarum polycephalum, has been proven efficient on finding appropriate and efficient solutions in hard to solve complex mathematical problems. The plasmodium of P. polycephalum is a single-cell that serves as a prosperous bio-computational example. Consequently, it has been successfully utilized in the past to solve a variety of path problems in graphs and combinatorial problems. In this work, this interesting behaviour is mimicked by a robust unconventional computational model, drawing inspiration from the notion of Cellular and Learning Automata. Namely, we employ principles of Cellular Automata (CAs) enriched with learning capabilities to develop a robust computational model, able of modelling appropriately the aforementioned biological substrate and, thus, capturing its computational capabilities. CAs are very efficient in modelling biological systems and solving scientific problems, owing to their ability of incarnating essential properties of a system where global behaviour arises as an effect of simple components, interacting locally. The resulting computational tool, after combining CAs with learning capabilities, should be appropriate for modelling the behaviour of living organisms. Thus, the inherent abilities and computational characteristics of the proposed bio-inspired model are stressed towards the experimental verification of Physarum's ability to model Logic Gates, while trying to find minimal paths in properly configured mazes with food sources. The presented simulation results for various Logic Gates are found in good agreement, both qualitatively and quantitatively, with the corresponding experimental results, proving the efficacy of this unconventional bio-inspired model and providing useful insights for its enhanced usage in various computing applications. [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]

The reaction-diffusion (RD) models describe the change in the behavior of one or more chemical substances through space and time. The RD interaction can create waves of chemical concentration when the chemical systems used are far from equilibrium. The velocity and direction of those waves can be controlled and altered using excitable media or inhibitors. In particular, excitable media are spatially distributed systems characterized by their ability to propagate signals undamped over long distances, while inhibitors are used to reduce the propagation of those signals. The behavior of chemical oscillators are based on such media. The concept of this article is the proposal of a Cellular Automaton (CA) model which exploits the wave propagation characteristics on an excitable medium using inhibitors to create a switching element which is capable of distinguishing two binary states and present a form of amplification, like a basic transistor. In such a sense an unconventional chemical made device with properties similar to the conventional basic element of todays electronics, namely CMOS transistor is conceived. Furthermore, and in order to properly explore the potential of the proposed device, we design a combination of two of those transistors to prove that they can reproduce Boolean algebra by creating two of the most well known and important component, i.e. the inverter NOT logic gate and the universal logic gate NAND. [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]

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]

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.

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 state-programming 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 threshold-type switching model of a bipolar voltage-controlled memristor. Such realization of in-memory computations could lead to faster arithmetic algorithms in future memristive ALUs. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including memristor models, circuits, and architectures.

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]

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. [ABSTRACT FROM AUTHOR]

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 Cellu-lar 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 micro-organism Physarum polycephalum, namely its olfaction, its propaga-tion and foraging process. The Physarum's sense of olfaction corre-sponds 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. [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.

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]

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]

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]