Finite Automaton Model Research Articles

Analysis of solid-state NMR data facilitated by MagRO_NMRViewJ with Graph_Robot: Application for membrane protein and amyloid.

Solid-state NMR (ssNMR) methods have continued to be developed in recent years for the efficient assignment of signals and 3D structure modeling of biomacromolecules. Consequently, we are approaching an era in which vigorous applications of these methods are more widespread in research, including functional elucidation of biomacromolecules and drug discovery. However, multidimensional ssNMR methods are not as advanced as solution NMR methods, especially for automated data analysis. This article describes how a newly developed Graph_Robot module, implemented in MagRO-NMRViewJ, evolved from integrated tools for NMR data analysis named Kujira (developed by Kobayashi et al. [1]). These packaged tools systematically utilize flexible, sophisticated, yet simple libraries that facilitate only for solution-NMR data analysis, offering an intuitive interface accessible even to novice users. In this study, semi-automated assignments of backbone and side chain signals of ssNMR datasets for uniformly 13C/15N labeled aquaporin Z and 42-residue amyloid-β fibril were examined as examples to demonstrate how Graph_Robot can expedite the visual inspection and handling of multidimensional ssNMR spectral data. In addition, the functionality of the Graph_Robot system enables a computer to interpret the behavior of magnetization transfer based on a finite automaton model.

Quantum word embedding for machine learning

The accelerated progress in quantum computing has enabled a new form of machine intelligence that runs on quantum hardware, which holds great promise for more powerful computational models in various learning tasks. An emergent application of Quantum Machine Intelligence (QMI) is Quantum Natural Language Processing (QNLP). This paper proposes a multi-dimensional, finite automaton model for quantum word embedding (QWE) via the Galois field. We demonstrated the model to three applications: (1) English vocabulary, (2) amino acid-based genetic codes, and (3) DNA-based genetic codes. The numerical results obtained from the proposed algorithm for the English vocabulary indicate that it produces more representative word features than Word2Vec based on the word distance metric. Second, the proposed algorithm is also utilized to model RNA-Protein interaction based on the latent distance of a given molecule, which is demonstrated on three large datasets, namely RPI369, RPI1807, and RPI2241. Finally, two embedding techniques for DNA-based genetic codes are proposed in this work: Two-state Lackadaisical Encoding (TCE) and Topological-Cyclic Encoding (TLE). These techniques enable extracting relevant features for the efficacy score of gRNAs used in the CRISPR-Cas 9 system, demonstrated on 15 datasets, compared to 12 mathematical features. We make our implementation available at https://github.com/namnguyen0510/Quantum-Embedding-of-Word/tree/main.

STUDY OF FINITE AUTOMATES USED IN CRYPTOGRAPHY

The article provides an overview of cryptographic systems based on finite automata. Theoretical materials of domestic scientists in foreign publications on finite-automaton cryptography have been studied. For a better understanding of the operation of various types of finite automata models, definitions of the main concepts were given: finite automaton – recognizer, finite automaton - converter, reversibility with a delay, inverse automaton, permutation and composition of finite automata. Further in the article, cryptographic algorithms based on automata without an exit were described, their advantages and disadvantages were noted. At the end, information is given about finite automata models, which are based on an automaton with an exit. The advantages of the finite automaton model over the existing algorithms of classical cryptography are revealed. The study allows us to make a conclusion about the prospects of using finite automata as the basis for cryptographic algorithms.

Real-time, constant-space, constant-randomness verifiers

We study the class of languages that have membership proofs which can be verified by real-time finite-state machines using only a constant number of random bits, regardless of the size of their inputs. Since any further restriction on the verifiers would preclude the verification of nonregular languages, this is the tightest computational budget which allows the checking of externally provided proofs to have meaningful use. We provide a full characterization of this class of languages in terms of a restricted version of the one-way nondeterministic multihead finite automaton model. For any k>0, there exist languages that cannot be recognized by any k-head one-way nondeterministic finite automaton, but that are nonetheless real-time verifiable in this sense. The set of nonpalindromes, which cannot be recognized by any one-way multihead deterministic finite automaton, is also demonstrated to be verifiable within these restrictions.

Rethinking the Operation Pattern for Anomaly Detection in Industrial Cyber–Physical Systems

Anomaly detection has been proven to be an efficient way to detect malicious behaviour and cyberattacks in industrial cyber–physical systems (ICPSs). However, most detection models are not entirely adapted to the real world as they require intensive computational resources and labelled data and lack interpretability. This study investigated the traffic behaviour of a real coal mine system and proposed improved features to describe its operation pattern. Based on these features, this work combined the basic deterministic finite automaton (DFA) and normal distribution (ND) models to build an unsupervised anomaly detection model, which uses a hierarchical structure to pursue interpretability. To demonstrate its capability, this model was evaluated on real traffic and seven simulated attack types and further compared with nine state-of-the-art works. The evaluation and comparison results show that the proposed method achieved a 99% F1-score and is efficient in detecting sophisticated attacks. Furthermore, it achieved an average 17% increase in precision and a 12% increase in F1-Score compared to previous works. These results confirm the advantages of the proposed method. The work further suggests that future works should investigate operation pattern features rather than pursuing complex algorithms.

Dynamic Performance Analysis of STEP System in Internet of Vehicles Based on Queuing Theory.

The Internet of vehicles (IoV) is an important research area of the intelligent transportation systems using Internet of things theory. The complex event processing technology is a basic issue for processing the data stream in IoV. In recent years, many researchers process the temporal and spatial data flow by complex event processing technology. Spatial Temporal Event Processing (STEP) is a complex event query language focusing on the temporal and spatial data flow in Internet of vehicles. There are four processing models of the event stream processing system based on the complex event query language: finite automata model, matching tree model, directed acyclic graph model, and Petri net model. In addition, the worst-case response time of the event stream processing system is an important indicator of evaluating the performance of the system. Firstly, this paper proposed a core algorithm of the temporal and spatial event stream processing program based on STEP by Petri net model. Secondly, we proposed a novel method to estimate the worst-case response time of the event stream processing system, which is based on stochastic Petri net and queuing theory. Finally, through the simulation experiment based on queuing theory, this paper proves that the data stream processing system based on STEP has good dynamic performance in processing the spatiotemporal data stream in Internet of vehicles.

Quotients and atoms of reversible languages

We consider several reversible finite automaton models which have been introduced over decades, and study some properties of their languages. In particular, we look at the question whether the quotients and atoms of a specific class of reversible languages also belong to that class or not. We consider bideterministic automata, reversible deterministic finite automata (REV-DFAs), reversible multiple-entry DFAs (REV-MeDFAs), and several variants of reversible nondeterministic finite automata (REV-NFAs). It is known that the class of REV-DFA languages is strictly included in the class of REV-MeDFA languages. We show that the classes of complete REV-DFA languages and complete REV-MeDFA languages are the same. We also prove that differently from the general case of a REV-DFA language, the minimal DFA for a complete REV-DFA language is a complete REV-DFA. We observe that atoms of any regular language are accepted by REV-NFAs with a single initial and a single final state. We also study atoms of atoms of regular languages and show that any atom of an atom of a regular language is a union of atoms of that language.

Formally proving whether the software implementation of models applied in instrumentation and control systems conform to the specified requirements

Research objective is to study the possibility to formally validate whether the model’s software implementation meets all the specified requirements of the systems, the model of which can be represented in the form of finite-state automata. Research relevance. At one of the first stages, the development of software for instrumentation and control systems provides for the creation of the system model. The model is based on the terms of reference, specification, and various a priori information. Most of the models for engineering systems in the modern mining industry (conveyor systems, ventilation systems, etc.) can be described in terms of the finite state automaton model. Such a model can be applied to solve diverse tasks. The next step is to implement the model in whole or in part. In this context, the task arises to determine the model’s software implementation conformity to its initial description. Results. One way to solve the task is to formally prove that the software model possesses the properties which are provided in the specification (description) of the initial model. By the example of the mine conveyor system, the paper illustrates the application of the method which consists in the software implementation of the corresponding finite-state automaton model, forecasting whether the model possesses the properties through theorems and their subsequent proof by applying special software. Conclusions. Formal methods of specification, development, and verification of system models’ software implementation together with other methods make it possible to improve the quality and reliability of solutions under development.

Automated State-Machine-Based Analysis of Hostname Verification in IPsec Implementations

Owing to the advent and rapid development of Internet communication technology, network security protocols with cryptography as their core have gradually become an important means of ensuring secure communications. Among numerous security protocols, certificate authentication is a common method of identity authentication, and hostname verification is a critical but easily neglected process in certificate authentication. Hostname verification validates the identity of a remote target by checking whether the hostname of the communication partner matches any name in the X.509 certificate. Notably, errors in hostname verification may cause security problems with regard to identity authentication. In this study, we use a model-learning method to conduct security testing for hostname verification in internet protocol security (IPsec). This method can analyze the problems entailed in implementing hostname verification in IPsec by effectively inferring the deterministic finite automaton model that can describe the matching situation between the certificate subject name and the hostname for different rules. We analyze two popular IPsec implementations, Strongswan and Libreswan, and find five violations. We use some of these violations to conduct actual attack tests on the IPsec implementation. The results show that under certain conditions, attackers can use these flaws to carry out identity impersonation attacks and man-in-the-middle attacks.

A Markov-Based Intrusion Tolerance Finite Automaton

It is inevitable for networks to be invaded during operation. The intrusion tolerance technology comes into being to enable invaded networks to provide the necessary network services. This paper introduces an automatic learning mechanism of the intrusion tolerance system to update network security strategy, and derives an intrusion tolerance finite automaton model from an existing intrusion tolerance model. The proposed model was quantified by the Markov theory to compute the stable probability of each state. The calculated stable probabilities provide the theoretical guidance and basis for administrators to better safeguard network security. Verification results show that it is feasible, effective, and convenient to integrate the Markov model to the intrusion tolerance finite automaton.

System management technology for technical maintenance of transport and technological machines

The paper considers the generalized structure of maintenance system, including, in the general case, the protection subsystem, the functional diagnostics subsystem, the test diagnostics subsystem, the maintenance and repair subsystem. The technical implementation of the listed subsystems is possible in the form of tools built into the object and in the form of tools external to the object. For the generalized structure of the transport and technological machines maintenance system, the possible ratios of the volumetric characteristics of built-in and external subsystems are analyzed (using the simplest analytical expression). The possibility of formalizing the control process of a generalized system of technical maintenance of autonomous objects within the framework of a finite-automaton model is discussed. In accordance with this model, it is proposed, first, to consider the on-board maintenance system as an operational automaton; second, each of its subsystems should be considered as a separate internal automaton that implements its own technological algorithm; third, the interaction of the four automata should be organized within the control automaton for the above-mentioned operating automaton. The algorithm for the functioning of this control automaton has been synthesized.

HealthWalks

Can health conditions be inferred from an individual's mobility pattern? Existing research has discussed the relationship between individual physical activity/mobility and well-being, yet no systematic study has been done to investigate the predictability of fine-grained health conditions from mobility, largely due to the unavailability of data and unsatisfactory modelling techniques. Here, we present a large-scale longitudinal study, where we collect the health conditions of 747 individuals who visit a hospital and tracked their mobility for 2 months in Beijing, China. To facilitate fine-grained individual health condition sensing, we propose HealthWalks, an interpretable machine learning model that takes user location traces, the associated points of interest, and user social demographics as input, at the core of which a Deterministic Finite Automaton (DFA) model is proposed to auto-generate explainable features to capture useful signals. We evaluate the effectiveness of our proposed model, which achieves 40.29% in micro-F1 and 31.63% in Macro-F1 for the 8-class disease category prediction, and outperforms the best baseline by 22.84% in Micro-F1 and 31.79% in Macro-F1. In addition, deeper analysis based on the SHapley Additive exPlanations (SHAP) showcases that HealthWalks can derive meaningful insights with regard to the correlation between mobility and health conditions, which provide important research insights and design implications for mobile sensing and health informatics.

Primeneniya gejmifikatsii v protsesse upravleniya obucheniem, adaptatsiej i razvitiem personala [Gamification applications in the process of managing personnel training, adaptation and development

The article examines the possibility of using elements of gamification in personnel management processes, such as: selecting candidates, ensuring the process of adaptation of new employees, managing training and development of employees. The introduction and use of gamification in the automation of these processes is proposed in order to increase the indicators of motivation, retention and involvement of personnel. Practical examples of the application of this tool in innovative companies are given. The mechanics of collaboration (cooperation), promotion, progress, appointments, and competition are analyzed the point of view of their effective application in corporate personnel management systems. It is proposed to use a competency-based approach to identify the knowledge, skills and abilities that a particular employee lacks and the efforts of managers of any company should be directed to the development and acquisition of which. A model of finite automaton is described, the development of which is crucial to formalize the processesunder consideration, analyze them, search for problem situations, modify, design information systems for monitoring and managing personnel training. Game mechanics are considered from the event approach point of view, the development of a certain game mechanics reaction in case of a certain event. In this case, the process of passing the training course can be represented as a finite deterministic automaton. The main task of developing the game mechanics reaction is to encourage the user to perform actions that will bring his current state closer to the final one. It is concluded that the use of gamification reduces the amount of routine actions necessary for the implementation of training, adaptation and development of personnel, make them more transparent and understandable for both employees and the company, minimize the time to implement these processes and, as a result, reduce their cost.

IETF-based Finite Automaton for Service Composition in Service Function Chaining

The Service Function Chaining (SFC) is an architecture to orchestrate network services by creating and deploying the rule-based service function chains and steering network traffic through them. One of the main tasks in SFC is the optimal composition of the service functions and checking the validation of the composed service chain based on the predefined rules. As the problem of optimal chain composition is NP hard, in this paper a Finite Automaton (FA) model is proposed to limit the solution space by considering the practical scenarios. Since the chaining rules depend on the substrate physical platform, the proposed FA is based on the data centre, mobile, and security scenarios introduced by Internet Engineering Task Force (IETF). Subsequently, Finite Automaton Matcher (FAM) shows that the proposed FA is an acceptable tool for validating the correctness of the composed service chain. Experimental results and complexity analysis show that this method reduces the number of service chain compositions and therefore the time complexity significantly.

Multi-Mode Switching Control of the EPS With Hybrid Power Supply

Electric power steering system (EPS) with traditional power supply can't provide enough power for heavy-duty vehicle to turn at low speed. To solve the problem, a novel EPS with hybrid power supply was constructed. In this paper, firstly, mathematical model of the EPS with hybrid power supply was established including model of hybrid power supply system and basic model of EPS. Then the power mode recognition was obtained according to the certain threshold of steering resistance torque, state of charge (SOC) of super-capacitor and output voltage of the vehicle power supply, and the corresponding finite automaton model was built. The EPS system with hybrid power supply was regarded as a hybrid system due to continuous event in a single mode and discrete event during mode switching process, thus the multi-mode switching control strategy was proposed. Taken the different characteristics of hybrid power supply in different power modes into account, the corresponding local controllers were designed which were consisted of fuzzy-PID controller, active disturbance rejection controller (ADRC) and sliding mode controller. Besides, the fuzzy supervisory controller was also designed to ensure the stability of the hybrid system during mode switching process. The simulation results show that the local controllers can achieve fast and accurate track of target current in each power mode, and the fuzzy supervisor can effectively ensure the stability of the switching process, which demonstrates the feasibility of the control strategy.

Order-Preserving Languages for the Supervisory Control of Automated Manufacturing Systems

Automated manufacturing systems (AMSs) consist of computer-controlled interconnected manufacturing components (MCs) that are used to transport and process different product types. Each product type requires a certain sequence of processing steps in different MCs. Hereby, multiple product types can share processing steps on the same MC and the paths of different products types can overlap. In this paper we consider the modeling of AMSs in the scope of supervisory control for discrete event systems (DES). On the one hand, a suitable AMS model must allow the representation of sequential and concurrent processing steps in MCs. On the other hand, such model must be able to track different product types traveling through the AMS so as to process the products correctly. While previous work is commonly concerned with the first requirement, this paper identifies that the existing literature lacks a general treatment of the second requirement. Accordingly, we first introduce order-preserving (OP) languages that preserve the order of different product types in MCs and we propose a suitable finite state automaton model for OP languages. Then, we show that the composition of OP languages again leads to an OP language. That is, modeling MCs by OP languages, an OP model of a complete AMS that is suitable for supervisory control is obtained. In addition, it is possible to use both OP models and non-OP models for general AMSs, where MCs have different properties. We demonstrate the applicability of the proposed modeling technique by a flexible manufacturing system example.

A Survey about various Generations of Lexical Analyzer

Lexical analysis helps the interactivity and visualization for active learning that can improve difficult concepts in automata. This study gives a view on different lexical analyzer generators that has been implemented for different purposes in finite automata. It also intends to give a general idea on the lexical analyzer process, which will cover the automata model that is used in the various reviews. Some concepts that will be described are finite automata model, regular expression and other related components. Also, the advantages and disadvantages of lexical analyzer will be discussed.Â

Simulation of artificial intelligence in a computer game

Artificial intelligence, implemented in the space of a computer game, will allow performing a variety of practice-oriented tasks and time-consuming algorithms: finding ways, avoiding obstacles, conducting combat, choosing the appropriate strategy, simulating emotions, dialogue, etc. The main problem that should be solved when developing an appropriate gaming application is to simulate the mechanism for controlling all possible functions of the game object. The research methodology includes: analysis of scientific works of Russian and foreign authors; the method of system information analysis, the method of mathematical and information modeling; computer experiment method, as a kind of computational; decision making algorithms. The paper presents a solution to the problem, including the informed choice of a decision-making algorithm, and the design of a model of a fuzzy finite automaton that combines the advantages of a model of a generating finite automaton and fuzzy logic. Based on the results of testing the implemented model, a conclusion was formulated about the main advantage of the artificial intelligence model for the gaming application - its ability to make an unusual decision in the arisen game situation.

A Novel Machine Translation Method based on Stochastic Finite Automata Model for Spoken English

Stochastic finite automata have been applied to a variety of fields, machine trans-lation is one of them. It can learn from data and build model automatically from training sets. Stochastic finite automata are well adapted for the constrained inte-gration of pairs of sentences for language processing. In this paper, a novel ma-chine translation method based on stochastic finite automata is proposed. The method formalized rational grammars by using stochastic finite automata. Through given pairs of source and target utterances, our proposed method will produce a series of conventional rules from which a stochastic rational grammar would be inferred, and the grammar is finally converted into a finite state automa-ton. The efficacy and accuracy of our proposed method is evaluated by a large number of English-Chinese and Chinese-English machine translation experi-ments.

Numerical microstructure prediction by a coupled finite element cellular automaton model for selective electron beam melting

Selective Electron Beam Melting (SEBM) refers to an additive manufacturing process of building near net shaped components layer wise by iteratively melting of metal powder using an electron beam. Due to the preheating of the material and very high scan velocities of the electron beam, the process allows large processing windows defined by different process strategies. This variety enables the adjustment of part properties by, e.g., targeting certain microstructures. However, this variety has its disadvantage in the need for costly trial and error experiments. Therefore, numerical predictions are inevitable in locating promising process parameter combinations.We present the weak coupling of a Finite-Element (FE) model with a cellular automaton (CA) model to predict the microstructure evolution during SEBM. We use an FE model for the computation of the heat input, since the temperature history mainly influences the subsequent microstructure evolution. The FE model provides precomputed temperature fields for our sophisticated CA-based crystal growth model, which successfully predicts bulk material microstructures. The compound is validated by accurately reproducing the microstructure of an additively build cylinder from CMSX-4 powder, a nickel based superalloy. Special emphasize is laid on the accurate prediction of the microstructure both in the shell as well as the core of the cylinder.