Finite Automation Research Articles

Finite automated system to design a high efficiency LLC resonant converter system for 3 kW. PV solar array

A combination of electrical circuit design and the Finite Automation model leads to improved efficiency in terms of memory usage, computation time, and overall performance. LLC resonant converters are known for their high efficiency and ability to convert DC voltage from solar panels into the desired AC voltage for grid-tied or off-grid PV systems. However, designing, testing, and implementing LLC in a PV system requires careful consideration of various factors, including voltage and current requirements, resonant frequency, and compliance with standards and regulations. Eight cases are taken for this purpose with a special case of a 3kW-PV module. The major parameters for the LLC resonant Converter were 480-500V. as output voltage for 36-40V. input voltage range with a 39V. nominal voltage. The calculated coefficients for these values were as follows: A = C = 7.29, B = -50.58, D = -0.25, and E = -11. Combining LLC circuit design with FA, it is providing 94.5 % efficiency through selecting precise parameters that minimized overall calculated losses such as conductive and switching types. The right path and accepted words for different cases are given to provide several solutions with the correct path of design. ZVS and ZCS have been obtained through precise selection process of phase shift between Half Bridge of LLC circuit achieved by this design.

Сокращение расхода электроэнергии грузовыми магистральными электровозами 2(3)ЭС5С при работе в энергоэффективном режиме по итогам эксплуатационных испытаний

Purpose: To evaluate the reduction in power specific consumption by freight mainline loco-motives 2(3)ES5S when operating in power-efficient mode (automatic speed control in com-bination with discrete-adaptive switch on/off of Traction Electric Drive depending on an in-stantaneous load), obtained from the results of operational tests. Methods: Array records analysis of on-board recorder made it possible to establish the nature of the dependence of locomotive efficiency degree from its power consumption. Way for controlling multi-engine traction electric drive efficiency in traction mode has been developed and patented. Computer modeling has allowed to obtain preliminary estimate to increase power efficiency. Speed au-tomatic controller block is built using finite automation theory method. The proposed changes, aimed at locomotive power efficiency improvement, have been introduced into top-level con-trol system. Final ratings of power consumption have been obtained during operational trials. Results: The analysis of results obtained during two trips on about 7-thousand-ton mass trains along section with hilly profile of 108 km length is presented. Ceteris paribus, during second trip, when electric locomotive was operating in power-efficient mode (discrete-adaptive con-trol of operating traction drive number in combination with speed automatic control), specific consumption reduction of electric power for traction was achieved on 25% in comparison with the first trip when all 12 traction motors were constantly working. Practical importance: Long-term development program of JSC Russian Railways provides for cost consistent reduc-tion for electric power that’s a purchased (consumed) product. In particular, optimization is planned in such direction as reducing specific consumption of power and fuel for train trac-tion.

Porosity of the porous carbonate rocks in the Jingfengqiao-Baidiao area based on finite automata.

This study is based on the processing of computed microtomography images of rock samples. In this study, a finite automation is constructed using the grey value, red-green-blue (RGB) value and Euler number of polarized images of carbonate rocks from the Jingfengqiao–Baidiao area. The finite automaton is used to perform black and white binary processing of the polarized images of the carbonate rocks. The porosity of the carbonate rock is calculated based on the black and white binarization processing results of the polarized images of the carbonate rocks. The obtained porosity is compared with the carbonate porosity obtained by use of the traditional carbonate research method. When the two porosities are close, the image processing threshold of the finite automata is considered to be credible. Based on the finite automata established using the image processing threshold, the black and white binary images of the polarized images of the carbonate rocks are used to establish a rock pore image using ImageJ2X. The polarized images of the carbonate rocks are classified according to their RGB values using the finite automata for the porosity classification, and the obtained images are used as textures to paste onto a cube to construct a three-dimensional data model of the carbonate rocks. This study also uses 16S rDNA analysis to verify the formation mechanism of the carbonate pores in the Jingfengqiao–Baidiao area. The results of the 16S rDNA analysis show that the pores in the carbonate rocks in the Jingfengqiao–Baidiao area are closely related to microorganisms, represented by denitrifying bacteria.

A Brief Survey and Implementation on Refinement for Intent-Driven Networking

Intent-driven networking (IDN) is emerging because the traditional network is complicated and error-prone when configured. As the key step of IDN, intent refinement is an alternative approach to convert intents from declarative language to a machine-readable policy, which possesses important scientific significance and application value. In this article, we first present a generic architecture to illustrate the process and functions of IDN. Then we give a definition of intent refinement to make the concept clear. In order to propose a standard classification method of intent refinement, we review the typical intent refinement schemes and distinguish them according to target users, input methods, and refinement approaches. Finally, in order to refine different kinds of intent, we design an intelligent intent refinement system based on natural language processing and deterministic finite automation. In summary, intent refinement plays a crucial role in IDN, which provides a convenient northbound interface for different users to express their communication requirements. Therefore, it is of vital importance to summarize its common methods and explore more straightforward and intelligent ways to enhance its utility.

ATrie Group Join: A Parallel Star Group Join and Aggregation for In-Memory Column-Stores

This article presents a new holistic and efficient approach to big data analysis. We introduce a new parallel algorithm, known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ATrie Group Join (ATGJ)</i> , that integrates join, grouping and aggregation operations to accelerate big data analytical workloads in in-memory column-stores. ATGJ performs a single scan of the fact columns and uses a mixture of data and task parallelism for the optimal use of computing resources. It uses a novel technique to perform group-by and aggregation realising the grouping attributes as a tree shaped deterministic finite automation known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Aggregate Trie</i> or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ATrie</i> . ATrie facilitates grouping of attributes and processing of data in tight loops that significantly improves the performance on modern hardware. Unlike other competing algorithms, use of ATrie avoids the creation of multiple data structures with the increasing number of dimension tables and grouping attributes. Also, we demonstrate that ATGJ performs efficiently even when the ATrie becomes bushy. We evaluated the algorithm using Star Schema Benchmark (SSBM) to show that it is significantly faster and scales better than other algorithms for the number of concurrent threads, the number of group-by attributes, the data set size and the query complexity.

Morphemic analysis of Uzbek nouns with Finite State Techniques

The article developed a mathematical model that describes the morphemic description of the structure of nouns in the Uzbek language. The developed model takes into account all forms of word-forming suffixes, affixes and creating word forms that belong to the lexical category of nouns. For the created mathematical model of word forms, an algorithm for morphemic parsing and determining the pre-ownership of word forms using finite automation is developed.

Distributed ATrie Group Join: Towards Zero Network Cost

The combination of powerful parallel frameworks and on-demand commodity hardware in distributed computing has made both analytics and decision support systems canonical to enterprises of all sizes. The unprecedented volumes of data stacked by companies present challenges to process analytical queries efficiently. This data is often organised as star schema, in which star join and group-by are ubiquitous and expensive operations. Although parallel frameworks such as Apache Spark facilitate join and group-by, the implementation can only process two tables at a time and fail to handle the excessive network communication, disk spills and multiple scans of data. In this paper, we present Distributed ATrie Group Join (DATGJ), a fast distributed star join and group-by algorithm for column-stores. DATGJ uses divide and broadcast-based joining technique where the fact table columns are partitioned equally and fast hash table (FHT) for each dimension table are broadcasted. This technique helps it avoid cross communication between workers and disk spills. DATGJ performs a single scan of partitioned fact table columns and use FHT to join data. FHT uses Robin Hood hashing with the upper limit on number of probes and achieve significant speed up during join. DATGJ performs group-by and aggregation leveraging progressive materialisation and realising grouping attributes as a tree shaped deterministic finite automation known as Aggregate Trie or ATrie. We evaluated our algorithm using Star Schema Benchmark (SSBM) to show that it is 1.5X to 6X faster than the most prominent approaches while having zero data shuffle and consistently perform well with addition of resources and in memory-constrained scenarios.

Design of Reversible Number Generator using Finite State Automation Realization

Objective: The objective of this paper is to realize an n-bit reversible number generator. Several designs of number generator and their corresponding constraints with feedback controller and initial state have also been discussed. Method/Analysis: The proposed design is validated by simulating the results in Verilog HDL. Findings: In this paper a design is presented to implement an n bit number generator as a finite state automation, using reversible logic for the implementation of the transition network. A realizable circuit is designed to implement the n-bit number generator using feedback controllers. Novelty/Improvement: With the use of reversible logic, the designed circuit reaches all the possible states and consumes no power.

Topological Analysis of Network Systems for Intrusion Detections

An understanding of how well networks will respond to ongoing attack threats is an important task in formulating strategies to protect unauthorized network activities. The study of topological properties of network architecture sheds some light in this effort. The purpose of this paper is to study several scenarios that address topological structures and related analyses of network systems to begin the appropriate discussion towards this question. Analysis of the probabilistic state finite automation and its probability distribution theory play a pivotal role in the discussion.

Path-based keyword search over XML streams

Purpose – In purpose of this paper is to propose a novel scheme to process XPath-based keyword search over Extensible Markup Language (XML) streams, where one can specify query keywords and XPath-based filtering conditions at the same time. Experimental results prove that our proposed scheme can efficiently and practically process XPath-based keyword search over XML streams. Design/methodology/approach – To allow XPath-based keyword search over XML streams, it was attempted to integrate YFilter (Diao et al., 2003) with CKStream (Hummel et al., 2011). More precisely, the nondeterministic finite automation (NFA) of YFilter is extended so that keyword matching at text nodes is supported. Next, the stack data structure is modified by integrating set of NFA states in YFilter with bitmaps generated from set of keyword queries in CKStream. Findings – Extensive experiments were conducted using both synthetic and real data set to show the effectiveness of the proposed method. The experimental results showed that the accuracy of the proposed method was better than the baseline method (CKStream), while it consumed less memory. Moreover, the proposed scheme showed good scalability with respect to the number of queries. Originality/value – Due to the rapid diffusion of XML streams, the demand for querying such information is also growing. In such a situation, the ability to query by combining XPath and keyword search is important, because it is easy to use, but powerful means to query XML streams. However, none of existing works has addressed this issue. This work is to cope with this problem by combining an existing XPath-based YFilter and a keyword-search-based CKStream for XML streams to enable XPath-based keyword search.

Revisiting State Blow-Up: Automatically Building Augmented-FA While Preserving Functional Equivalence

Regular expression matching, a central task in deep packet inspection and other networking applications, has been traditionally implemented through finite automata. Thanks to their limited per-character processing and memory bandwidth requirements, deterministic finite automata (DFA) are a natural choice for memory-based implementations. In the presence of large datasets of complex patterns, however, DFA suffer from the well-known state explosion problem. Specifically, state explosion can take place during DFA generation when the considered patterns contain bounded and unbounded repetitions of wildcards or large character sets. Several alternative FA representations have been proposed to address this problem. However, these proposals all suffer from one or more of the following problems: some can avoid state explosion only on datasets of limited size and complexity; some have prohibitive worst-case memory bandwidth requirements or processing time; and some can only guarantee functional equivalence for restricted classes of regular expressions and require the user to manually filter out unsupported patterns. In this work we propose JFA, a finite automation that uses state variables to avoid state explosion, and is functionally equivalent to the corresponding DFA. Functional equivalence is guaranteed by construction without requiring user intervention. We also provide optimization techniques to both limit the amount of state variables required and provide a lower bound for the JFA traversal time.

Research of Network System Reconfigurable Model Based on the Finite State Automation

Since the network analysis model based on the system state exists the issues of network survivability safety, fault tolerance and dynamic ability are adapted to the environment changes, in this paper, network system model based on the finite state automation has reconfigurable quality. The model first puts forward the concept of reconfigurable network systems and reveals its robustness, evolution and the basic attributes of survivability. By establishing a hierarchical model of system state, the system robust behavior, evolution behavior and survival behavior are described. Secondly, network topology reconfigurable measurement as an example, puts forward the quantitative reconfigurable metrics. At last, the example verification. Experiments show that the proposed reconfigurable quantitative indicators of reconfigurable resistance model for [1.391, 1.140, 1.591] prove that the network is an efficient reconfigurable network topology, which can effectively adapt the dynamic changes in the environment

Algorithm for minimizing determination finite automation based on information system

At present,Determination Finite Automation(DFA) minimization more focuses on theoretical research,and there are not many algorithms easy to achieve.Therefore,the method of minimization of determination finite automation was researched.First,DFA was converted into information system;and then the information system was simplified,which was based on the partition of equivalence classes;at last the simplified information system was converted into minimized DFA.Concerning the above process,an algorithm of minimizing DFA based on strategy of divide and conquer was proposed.In the average case,the time complexity and space complexity of the algorithm are O(n log n) and O(n) respectively.Finally,an example was used to explain the feasibility of the proposed algorithm.

Minimization of fuzzy finite automata

In this paper we show that a fuzzy finite automation M 1 has an equivalent minimal fuzzy finite automation M. We also show that M can be chsen so that if M 2 is equivalent to M 1, then M is a homomorphic image of M 2.

Finitely Repeated Games with Finite Automata

In honor of R. J. Aumann's 65th birthday The paper studies the implications of bounding the complexity of the strategies players may select, on the set of equilibrium payoffs in repeated games. The complexity of a strategy is measured by the size of the minimal automation that can implement it. A finite automation has a finite number of states and an initial state. It prescribes the action to be taken as a function of the current state and a transition function changing the state of the automaton as a function of its current state and the present actions of the other players. The size of an automaton is its number of states. The main results imply in particular that in two person repeated games, the set of equilibrium payoffs of a sequence of such games, G(n), n = 1, 2, …, converges as n goes to infinity to the individual rational and feasible payoffs of the one shot game, whenever the bound on one of the two automata sizes is polynomial or subexponential in n and both, the length of the game and the bounds of the automata sizes are at least n. A special case of such result justifies cooperation in the finitely repeated prisoner's dilemma, without departure from strict utility maximization or complete information, but under the assumption that there are bounds (possibly very large) to the complexity of the strategies that the players may use.

Effective learning in recurrent max–min neural networks

Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ max–min activation functions have been a subject of interest in recent years. Since max–min functions are not strictly differentiable, we propose a mathematically sound learning method based on using Fourier convergence analysis of side-derivatives to derive a gradient descent technique for max–min error functions. We then propose a novel recurrent max–min neural network model that is trained to perform grammatical inference as an application example. Comparisons made between this model and recurrent sigmoidal neural networks show that our model not only performs better in terms of learning speed and generalization, but that its final weight configuration allows a deterministic finite automation (DFA) to be extracted in a straightforward manner. In essence, we are able to demonstrate that our proposed gradient descent technique does allow max–min neural networks to learn effectively.

Sur les automates circulaires et la conjecture de Černý

A resect word takes all states of a finite automation to a single state. Cerný conjectured that every n-state automaton admitting a reset word admits a short reset word, i.e. one of length at most (n - 1) 2 . In this paper, we generalize our earliest result (the proof of the conjecture about biaised circular automata) to all circular automata.

A Process Algebra Foundation for Reasoning about Core ELLA

A process algebraic foundation has been developed for formal analysis of synchronous hardware designs represented through the commercially available hardware design language, ELLA. An underlying semantic foundation, based on input/output trace sets, is presented first through the use of state machines. Such a representation enables direct application of standard, fully automated trace equivalence checking tools. However, to overcome the computational limitations imposed by such analysis methods, the input/ output trace semantics is represented through a synchronous process algebra, EPA. Primitive processes in EPA denote the behaviour of primitive hardware components, such as delays or multiplexers, with composition operators corresponding to the different ways in which behaviours may be built. Of particular significance is the parallel composition operator which captures the machinery for building networks from other components/networks. Actions in EPA are structured and signify the state of input and output signals. This structure, however, is abstracted by developing an algebra for the actions. In particular, parallel composition on processes neatly lifts to a special (synchronous) product operation on actions. The EPA representation forms a good basis for semi-automated high-level symbolic manipulation and reasoning tools. First, the original design structure can be maintained, thus easing the problems of user level feedback from tools. Secondly, the application of EPA to ELLA enables a deterministic finite automation form for EPA terms. This provides a route to tractable symbolic verification and simulation, using a state evolution method to establish strong bisimulation properties. The method has been successfully applied to classes of unbounded state space systems.

Regular unimodal systems and factors of finite automata

Dynamical systems at the edge of chaos, which have been considered as models of self-organization phenomena, are marked by their ability to perform nontrivial computations. To distinguish them from systems with limited computing power, we formulate two simplicity criteria for general dynamical systems, and apply them to unimodal systems on real interval. We say that a dynamical system is regular, if it yields a regular language when observed through arbitrary almost disjoint cover. Finite automata are regarded as dynamical systems on zero-dimensional spaces and their factors yield another class of simple dynamical systems. These two criteria coincide on subshifts, since a subshift is regular iff it is a factor of a finite automation (sofic systems), A unimodal system on real interval is regular if it has only a finite number of periodic points, and nonrecursive otherwise. On the other hand each S-unimodal system with finite, periodic or preperiodic kneading sequence is a factor of a finite automaton. Thus preperiodic S-unimodal systems are factors of finite automata which are not regular.

Confluent linear numeration systems

Numeration systems where the basis is defined by a linear recurrence with integer coefficients are considered. A rewriting system is associated with the recurrence. In this paper we study the case when it is confluent. We prove that the function of normalization which transforms any representation of an integer into the normal one — obtained by the usual algorithm — can be realized by a finite automation which is the composition of a left subsequential transducer and of a right subsequential transducer associated with the rewriting system. Addition of integers in a confluent linear numeration system is also computable by a finite automaton. These results extend to the representation of real numbers in basis θ, where θ is the dominant root of the characteristic polynomial of the recurrence.