Mealy Machine Research Articles

Unprecedented Security Analysis Results for a Novel Key Expansion Algorithm Based on Protein Sequences, Dynamic Mealy Machine, and 3D Logistic Map

Unprecedented Security Analysis Results for a Novel Key Expansion Algorithm Based on Protein Sequences, Dynamic Mealy Machine, and 3D Logistic Map

Optimization of the Microprogram Mealy Machine Circuit Based on LUT and EMB

Optimization of the Microprogram Mealy Machine Circuit Based on LUT and EMB

Active model learning of stochastic reactive systems (extended version)

AbstractBlack-box systems are inherently hard to verify. Many verification techniques, like model checking, require formal models as a basis. However, such models often do not exist, or they might be outdated. Active automata learning helps to address this issue by offering to automatically infer formal models from system interactions. Hence, automata learning has been receiving much attention in the verification community in recent years. This led to various efficiency improvements, paving the way toward industrial applications. Most research, however, has been focusing on deterministic systems. In this article, we present an approach to efficiently learn models of stochastic reactive systems. Our approach adapts $$L^*$$ L ∗ -based learning for Markov decision processes, which we improve and extend to stochastic Mealy machines. When compared with previous work, our evaluation demonstrates that the proposed optimizations and adaptations to stochastic Mealy machines can reduce learning costs by an order of magnitude while improving the accuracy of learned models.

Free Choice in Quantum Theory: A p-adic View.

In this paper, it is rigorously proven that since observational data (i.e., numerical values of physical quantities) are rational numbers only due to inevitably nonzero measurements errors, the conclusion about whether Nature at the smallest scales is discrete or continuous, random and chaotic, or strictly deterministic, solely depends on experimentalist's free choice of the metrics (real or p-adic) he chooses to process the observational data. The main mathematical tools are p-adic 1-Lipschitz maps (which therefore are continuous with respect to the p-adic metric). The maps are exactly the ones defined by sequential Mealy machines (rather than by cellular automata) and therefore are causal functions over discrete time. A wide class of the maps can naturally be expanded to continuous real functions, so the maps may serve as mathematical models of open physical systems both over discrete and over continuous time. For these models, wave functions are constructed, entropic uncertainty relation is proven, and no hidden parameters are assumed. The paper is motivated by the ideas of I. Volovich on p-adic mathematical physics, by G. 't Hooft's cellular automaton interpretation of quantum mechanics, and to some extent, by recent papers on superdeterminism by J. Hance, S. Hossenfelder, and T. Palmer.

A Mealy Machine for Mechanic Dynamic Aesthetic (MDA) Gamification Model of Educator Career System in Indonesian Higher Education Institutions

The purpose of this study is to develop a mechanic dynamic aesthetic (MDA) gamification model for higher education institutions (HEIs’) educator career system (ECS). A mealy machine or finite state machine (FSM) is used to model the ECS gamification mechanic because the academic degrees targeted by the educators are finite and assumed to be the states that they must accomplish during their journey as professional educators. A program is created to simulate the Mealy machine and the results are checked by an ECS reviewer team. MDA-ECS is the result of a new ECS gamification model implemented in Indonesian HEIs. The proposed gamification model’s mechanic is a five-tuple Mealy machine, which consists of four elements: (career) states, start states, inputs, outputs, and transitions. The four functional degrees (FDs): Associate Lecturer, Lecturer, Associate Professor, and Professor: represent the states of the machine. Credit points from the four aspects of 3D-HEI collected by the educator are the machine’s inputs, while the grade of FDs, reward, and punishment are the outputs, and thus the gamification. The simulation showed that the mealy machine met the informational and affective aspects of the ECS regulation in Indonesian HEIs.

Energy management and harmonic compensation of micro‐grids via multi‐agent systems based on decentralized control architecture

AbstractHere, a new energy management strategy based on a multi‐agent structure is presented by introducing hybrid control of AC micro‐grid (MG), where current harmonics compensation is also considered. This energy management strategy is based on Mealy machine in a multi‐agent system (MAS), which is implemented by generating coordination signals and sending them to the renewable energy sources (RES). In RES, maximum power point tracking (MPPT) or reverse of Hill‐climbing (RHC) is used based on these received coordination signals to limit the exchange power between the MG and the grid. Also, the multi‐agent structure of shunt active power filters (SAPFs) and passive filters have been studied in power MGs. The comparison of MG current harmonic compensation by these filters by fast Fourier transform (FFT) algorithm has been investigated in the proposed network. The simulation results show that the proposed energy management system (EMS) with proper management of MG different agents has been able to have a suitable performance for hybrid distributed generation (DG) systems. Also, the SAPF with better and more appropriate harmonic compensation than the SC‐RC‐LCL passive filter can eliminate the harmonic pollution of MG and be used with high performance in hybrid DG systems.

Toward a Human-Readable State Machine Extraction

The target of sequential reverse engineering is to extract the state machine of a design. Sequential reverse engineering of a gate-level netlist consists of the identification of so-called state flip-flops (sFFs), as well as the extraction of the state machine. The second step can be solved with an exact approach if the correct sFFs and the correct reset state are provided. For the first step, several more or less heuristic approaches exist. This work investigates sequential reverse engineering with the objective of a human-readable state machine extraction. A human-readable state machine reflects the original state machine and is not overloaded by additional design information. For this purpose, the work derives a systematic categorization of sFF sets, based on properties of single sFFs and their sets. These properties are determined by analyzing the degrees of freedom in describing state machines as the well-known Moore and Mealy machines. Based on the systematic categorization, this work presents an sFF set definition for a human-readable state machine, categorizes existing sFF identification strategies, and develops four post-processing methods. The results show that post-processing predominantly improves the outcome of several existing sFF identification algorithms.

Observation and Distinction: Representing Information in Infinite Games

We compare two approaches for modelling imperfect information in infinite games by using finite-state automata. The first, more standard approach views information as the result of an observation process driven by a sequential Mealy machine. In contrast, the second approach features indistinguishability relations described by synchronous two-tape automata. The indistinguishability-relation model turns out to be strictly more expressive than the one based on observations. We present a characterisation of the indistinguishability relations that admit a representation as a finite-state observation function. We show that the characterisation is decidable, and give a procedure to construct a corresponding Mealy machine whenever one exists.

МОДЕЛИРОВАНИЕ ДИСКРЕТНЫХ СИСТЕМ УПРАВЛЕНИЯ НА ОСНОВЕ АВТОМАТОВ МИЛИ И МУРА В САПР PROTEUS 8

In the course of the works, discrete control systems based on Mealy and Moore machines in Proteus 8 CAD have been designed and modeled. The author analyzes functional capabilities of the VSM (virtual simulation environment) of the Proteus Design Suite virtual modeling environment by Labcenter Electronics. Its application is considered to be useful for developing models and testing discrete systems.

The Walking Robot Control System that is Adaptive to Changes in the Kinematics

The walking mobile robots (WMR) have recently become widely popular in robotics. They are especially useful in the extreme cases: search and rescue operations; cargo delivery over highly rough terrain; building a map. These robots also serve to explore and describe a partially or completely non-deterministic workspace, as well as to explore areas that are dangerous to human life. One of the main requirements for these WMR is the robustness of its control system. It allows WMR to maintain the operability when the characteristics of the support surface change as well as under more severe conditions, in particular, loss of controllability or damage of the supporting limb (SL). We propose to use the principles of genetic programming to create a WMR control system that allows a robot to adapt to possible changes in its kinematics, as well as to the characteristics of the support surface on which it moves. This approach does not require strong computational power or a strict formal classification of possible damage to the WMR. This article discusses two main WMR control modes: standard, which accord to a serviceable kinematics, and emergency, in which one or more SL drives are damaged or lost controllability. As an example, the structure of the control system of the WMP is proposed, the kinematics of which is partially destroyed in the process of movement. We developed a method for controlling such robot, which is based on the use of a genetic algorithm in conjunction with the Mealy machine. Modeling of modes of movement of WMR with six SL was carried out in the V-REP program for two cases of injury: absent and not functioning limb. We present the results of simulation of emergency gaits for these configurations of WMP and the effectiveness of the proposed method in the case of damage to the kinematic scheme. We also compared the performance of the genetic algorithm for the damaged WMR with the standard control algorithm.

Protocol State Machine Reverse Engineering with a Teaching-Learning Approach

In this work, we propose a novel solution to the problem of inferring the state machine of an unknown protocol. We extend and improve prior results on inferring Mealy machines, and present a new algorithm that accesses and interacts with a networked system that runs the unknown protocol in order to infer the Mealy machine representing the protocol's state machine. To demonstrate the viability of our approach, we provide an implementation and illustrate the operation of our algorithm on a simple example protocol, as well as on two real-world protocols, Modbus and MQTT.

Development of a sequence automaton for recognition of deviations indicators in diagnosis of natural systems

Much attention is now being paid to the development of automated devices for rapid disease diagnosis in veterinary medicine and medicine in general. One of the directions in medical instrumentation designing is the development of methods for automated disease diagnosis. This article is devoted to the automatization of pathology detection in histological analysis. The topology of pathologies of morphostructural changes in cells may have a tree-like structure, which makes the development of methods, software and hardware implementation of tools relevant for determination of the disease pathology. The three-level pathology system of structural changes in cell tissues obtained by histological analysis has been studied. It was suggested to use sequential logic, based on the Mealy machine, for the development of automated system for pathology indicators detection. Hartley binary measure for this topology of structural changes in tissues has been calculated and the indicator encoding has been given. The method of automated diagnosis based on the analysis of pathology indicators has been developed. An example of building an automatic recognition machine of pathology indicators on hard logics considered. It is relevant when using programmable logic device. The logical equations implemented in the combination scheme of the device are obtained. Simulation modeling to identify pathology indicators is performed. It is suggested to use the developed method of determining the disease indicators when designing the automated histological analyzer.

Addressing the Limitation of JFLAP Mealy Machine for Binary Increments

Addressing the Limitation of JFLAP Mealy Machine for Binary Increments

The Smart Black Box: A Value-Driven High-Bandwidth Automotive Event Data Recorder

Autonomous vehicles require reliable and resilient sensor suites and ongoing validation through fleet-wide data collection. This paper proposes a Smart Black Box (SBB) to augment traditional low-bandwidth data logging with value-driven high-bandwidth data capture. The SBB caches short-term histories of data as buffers through a deterministic Mealy machine based on data value and similarity. Compression quality for each frame is determined by optimizing the trade-off between value and storage cost. With finite storage, prioritized data recording discards low-value buffers to make room for new data. This paper formulates SBB compression decision making as a constrained multi-objective optimization problem with novel value metrics and filtering. The SBB has been evaluated on a traffic simulator which generates trajectories containing events of interest (EOIs) and corresponding first-person view videos. SBB compression efficiency is assessed by comparing storage requirements with different compression quality levels and event capture ratios. Performance is evaluated by comparing results with a traditional first-in-first-out (FIFO) recording scheme. Deep learning performance on images recorded at different compression levels is evaluated to illustrate the reproducibility of SBB recorded data.

A Novel Design of Mealy Machine Equivalence in Vlsi Technology

In this paper begin of a Novel Design of Mealy Machine Equivalence in VLSI Technology. The pattern in structure and assembling of extremely huge scale incorporated circuit shows a progressing move towards littler gadgets on expanding wafer measurements. CMOS has become a common innovation because of its rapid and pressing thickness combined with low power utilization. New advances have risen to additionally expand circuit speed and to lessen structure and innovation limitations. Models are joined bipolar-CMOS (BICMOS) and CMOS in silicon on the cover (SOI). Other than the mass delivered standard chips exclusively custom-fitted application explicit IC (ASICs) and framework approaches with on-chip coordinated sensors or high power actuators gain significance. These improvements present difficulties in the progression of pillar testing techniques, for example, rapid or high spatial goals on 200 mm width wafers. We have mapped this paper to the Mealy machine equivalence Verilog HDL Code in the Xilinx Vivado Compiler Version v2014.2 (64-bit) and find the Power, utilization report, and Area, Power in Table One, utilization report in Table Two and Area in Table Three.

Transducer Function In Vending Machine Simulation Design

A vending machine is a substitute for a cashier or admin in the form of a machine so that buyers simply enter coins and the machine will issue them according to the request. Moore machine and mealy machines as a process for processing buyer orders which are translated into machine orders. Based on the test results of coins entered 1000 and 500, the drink can be chosen according to the price of the drink.

Metapsychological consequences of the conscious brainstem: A critique of the conscious id

ABSTRACTIn this article, the thesis that the id is conscious [Solms, (2013a) The conscious id. Neuropsychoanalysis, 15(1), 5–19] is scrutinized by carving out a crucial implicit assumption on which the argument relies. The validity of this assumption is then assessed in two ways: first by an analysis of Freud’s description of the relation between the mental apparatus and the brain, second by analyzing the neuropsychoanalytical implications of the Mealy machine [Mealy, 1955. A method for synthesizing sequential circuits. Bell Labs Technical Journal, 34(5), 1045–1079] – a mathematical model that is used to describe the relation between the software and hardware of computers. The result of my assessment is that Solms’s implicit assumption faces serious objections and therefore the conclusion that the id is conscious cannot be upheld. In the remaining article I develop, based on the neuroscientific findings on which Solms developed his thesis [Solms & Panksepp, 2012. The “id” knows more than the “ego” admits: Neuropsychoanalytic and primal consciousness perspectives on the interface between affective and cognitive neuroscience. Brain Sciences, 2(2), 147–175], a concurrent adaptation of the structural model. This is achieved by an analysis of Freud's development of his metapsychological theory from 1899 to 1923, with a strong focus on the conceptualization of consciousness that underwent, as I shall work out, a major change. The result is a new metapsychological model that, so I claim, gets rid of a crucial weak spot of the structural model [Freud, 1923. The ego and the id. Standard Edition, 19, 12–59] and allows the integration of different neuropsychological theories.

Evaluating the Learning of Automata through the Use of Recurrent Neural Networks

This paper presents the computational potentialities, demonstrating the learning capacity and extrapolation of recurrent neural networks (RNN) through the learning study of finite automata. Initially, the generalized delta rule is presented for a recurrent network. In addition, the theoretical basis on Finite Automata, Moore Machine and Mealy Machine are presented, showing the equivalence between them. We formalized the problem of parity using a Moore Machine and its equivalent Mealy Machine. We proceeded simulation and the results are presented for the problem and simulation of Tomita languages 1 and 2, testing the extrapolation capacity of each RNN. The results indicated that the neural networks with recurrent architectures have a good capacity of extrapolation for the simulated problems.

Realization of information technology of character recognition based on competing cellular automata

We examined the possibility of applying cellular automata to solve the problem on recognition of text characters. For this purpose, we introduced the notion of competing cellular automata and developed algorithms of their functioning and interaction. In order to implement the proposed algorithms, we created modeling software. It allowed us to evaluate effectiveness of the cellular-automaton algorithms to conduct experiments on text character recognition using the English alphabet and to demonstrate a number of advantages in comparison with other methods. We investigated a description of the solution to the problem on selecting the structural attributes in the images of text characters, which directly affect the quality of recognition. In the present work, it is proposed to use a set of cellular automata constructed on the diagrams of states of Moore and Mealy machines for each type of cellular automata, to determine the end points, junctions and cycles in characters. We considered operation of the modeling program. The advantages of the given technology are the simplicity of rules of interaction, easy parallelization of the process of recognition, the possibility of recognition of distorted and partially overlapping characters. We compared performance quality and efficiency of the commercially available system ABBYY FineReader, which has demonstrated high performance indicators of the developed recognition technology

Comparative study of Moore and Mealy machine models adaptation in black soap production

Information and Communications Technology has influenced the need for automated machines that can carry out important production procedures and, automata models are among the computational models used in design and construction of industrial processes. The production process of the popular African Black Soap (ABS), which is widely used for the alleviation of various skin ailments among other uses, is still mostly done manually. In this paper, an automata model was developed for ABS manufacturing process using Moore and Mealy Finite State Machines. Simulation of standard input of raw materials into the machine was achieved using Input-Output methodology with pseudo random number generated input data. The output of this methodology served as the actual fractional contents of the raw ingredients fed into the Moore and Mealy machine. The automata models were simulated for ten runs using application developed with Microsoft Visual C#. The performance of each machine was assessed in order to determine, the most efficient of the machines using execution time as parameter. The simulation results showed that the Mealy Machine is faster than the Moore Machine as evident by the time overhead of over 3hrs in the production time process of ABS. http://dx.doi.org/10.4314/njt.v36i2.36