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Ransomware, particularly crypto ransomware, has emerged as the go-to malware for threat actors aiming to compromise data on Android devices as well as in general. In this paper, we present a ransomware detection technique based on behaviours observed in the system calls performed by the malware. We first describe our repeatable and extensible methodology for extracting the system call log and patterns. We then identify and present some common high-level system call behavioural patterns exhibited by crypto ransomware, and evaluate these patterns. We further describe the implementation of a streaming implementation that utilises regular expressions for modelling malware behaviours and finite state machines for detecting crypto ransomware behaviours in real time. The success of our proof of concept evaluation allows us to envision our proposed technique applied as part of a self-protection system on Android phones against malware. [ABSTRACT FROM AUTHOR]

We consider the problem of finding a "treasure" at an unknown point of an n-dimensional infinite grid, n ≥ 3 , by initially collocated finite automaton (FA) agents. Recently, the problem has been well characterized for 2 dimensions for deterministic as well as randomized FA agents, both in synchronous and semi-synchronous models (Brandt et al. in Proceedings of 32nd International Symposium on Distributed Computing (DISC) LIPCS 121:13:1–13:17, 2018; Emek et al. in Theor Comput Sci 608:255–267, 2015). It has been conjectured that n + 1 randomized FA agents are necessary to solve this problem in the n-dimensional grid (Cohen et al. in Proceedings of the 28th SODA, SODA '17, pp 207–224, 2017). In this paper we disprove the conjecture in a strong sense: we show that three randomized synchronous FA agents suffice to explore an n-dimensional grid for anyn. Our algorithm is optimal in terms of the number of the agents. Our key insight is that a constant number of FA agents can, by their positions and movements, implement a stack, which can store the path being explored. We also show how to implement our algorithm using: four randomized semi-synchronous FA agents; four deterministic synchronous FA agents; or five deterministic semi-synchronous FA agents. We give a different, no-stack algorithm that uses 4 deterministic semi-synchronous FA agents for the 3-dimensional grid. This is provably optimal in the number of agents and the exploration cost, and surprisingly, matches the result for 2 dimensions. For n ≥ 4 , the time complexity of the stack-based algorithms mentioned above is exponential in distance D of the treasure from the starting point of the agents. We show that in the deterministic case, one additional finite automaton agent brings the time down to a polynomial. We also show that any algorithm using 3 synchronous deterministic FA agents in 3 dimensions must travel beyond Ω (D 3 / 2) from the origin. Finally, we show that all the above algorithms can be generalized to unoriented grids. More specifically, six deterministic semi-synchronous FA agents are sufficient to locate the treasure in an unoriented n-dimensional grid. [ABSTRACT FROM AUTHOR]

In text classifier models, the complexity of recurrent neural networks (RNNs) is very high because of the vast state space and uncertainty of transitions, which makes the RNN classifier's explainability insufficient. It is almost impossible to explain the large-scale RNN directly. A feasible method is to generalize the rules undermining it, that is, model abstraction. To deal with the low efficiency and excessive information loss in existing model abstraction for RNNs, this work proposes a PSO (Particle Swarm Optimization)-based model abstraction and explanation generation method for RNNs. Firstly, the k-means clustering is applied to preliminarily partition the RNN decision process state. Secondly, a frequency prefix tree is constructed based on the traces, and a PSO algorithm is designed to implement state merging to address the problem of vast state space. Then, a PFA (probabilistic finite automata) is constructed to explain the RNN structure with preserving the origin RNN information as much as possible. Finally, the quantitative keywords are labeled as an explanation for classification results, which are automatically generated with the abstract model PFA. We demonstrate the feasibility and effectiveness of the proposed method in some cases. [ABSTRACT FROM AUTHOR]

Purpose: Wiswesser Line Notation (WLN) is a old line notation for encoding chemical compounds for storage and processing by computers. Whilst the notation itself has long since been surpassed by SMILES and InChI, distribution of WLN during its active years was extensive. In the context of modernising chemical data, we present a comprehensive WLN parser developed using the OpenBabel toolkit, capable of translating WLN strings into various formats supported by the library. Furthermore, we have devised a specialised Finite State Machine l, constructed from the rules of WLN, enabling the recognition and extraction of chemical strings out of large bodies of text. Available open-access WLN data with corresponding SMILES or InChI notation is rare, however ChEMBL, ChemSpider and PubChem all contain WLN records which were used for conversion scoring. Our investigation revealed a notable proportion of inaccuracies within the database entries, and we have taken steps to rectify these errors whenever feasible. Scientific contribution: Tools for both the extraction and conversion of WLN from chemical documents have been successfully developed. Both the Deterministic Finite Automaton (DFA) and parser handle the majority of WLN rules officially endorsed in the three major WLN manuals, with the parser showing a clear jump in accuracy and chemical coverage over previous submissions. The GitHub repository can be found here: https://github.com/Mblakey/wiswesser. [ABSTRACT FROM AUTHOR]

We generalize the theory of linked partition ideals due to Andrews using finite automata in formal language theory and apply it to prove three Rogers-Ramanujan type identities for modulus 14 that were posed by Nandi through a vertex operator theoretic construction of the level 4 standard modules of the affine Lie algebra A(2) 2 . [ABSTRACT FROM AUTHOR]

Hopfield attractor networks are robust distributed models of human memory, but they lack a general mechanism for effecting state-dependent attractor transitions in response to input. We propose construction rules such that an attractor network may implement an arbitrary finite state machine (FSM), where states and stimuli are represented by high-dimensional random vectors and all state transitions are enacted by the attractor network's dynamics. Numerical simulations show the capacity of the model, in terms of the maximum size of implementable FSM, to be linear in the size of the attractor network for dense bipolar state vectors and approximately quadratic for sparse binary state vectors. We show that the model is robust to imprecise and noisy weights, and so a prime candidate for implementation with high-density but unreliable devices. By endowing attractor networks with the ability to emulate arbitrary FSMs, we propose a plausible path by which FSMs could exist as a distributed computational primitive in biological neural networks. [ABSTRACT FROM AUTHOR]

Let t (n) denote the number of 1-bits in the base-2 representation of n , taken modulo 2. We show how to prove the classic conjecture of Leo Moser, on the rarefied sum ∑ 0 ≤ i < n (− 1) t (3 i) , using tools from automata theory and logic. The same technique can be used to prove results about analogous sums. [ABSTRACT FROM AUTHOR]

We define a tree pattern border array as a property of linearised trees analogous to border arrays from the string domain. We consider tree patterns with node wildcards and subtree wildcards. Then we use the tree pattern border array in a new forward tree pattern matching algorithm for ordered ranked trees. The algorithm finds all occurrences of a single linearised tree pattern in a linearised input tree. As with the classical Morris–Pratt algorithm for searching in strings, the tree pattern border array is used to determine shift lengths in the searching phase of the tree pattern matching algorithm. We compare this new algorithm with the best performing previously existing algorithms based on backward linearised tree pattern matching algorithms, (non-)linearised tree pattern matching algorithms using finite tree automata or stringpath matchers. We show that our new algorithm outperforms other tree pattern matching algorithms in single tree pattern matching. [ABSTRACT FROM AUTHOR]

String assembling systems are biologically inspired mechanisms that generate strings from copies out of finite sets of assembly units. The underlying mechanism is based on piecewise assembly of a double-stranded sequence of symbols, where the upper and lower strand have to match. The generation is additionally controlled by the requirement that the first symbol of a unit has to be the same as the last symbol of the strand generated so far, as well as by the distinction of assembly units that may appear at the beginning, during, or at the end of the assembling process and by a length restriction on the units. We investigate the power of these model-inherent control mechanisms by considering variants where one or more of these mechanisms are relaxed. The generative capacities and the relative power of the variants are our main interest. In particular, we prove that the power gained in the different control mechanisms may yield strictly more powerful systems and incomparable capacities. Additionally, we generalize these systems to multi-stranded systems. We obtain a strong connection to one-way multi-head finite automata and show an infinite, dense, and strict strand hierarchy. Finally, we examine the closure properties of the different variants of string assembling systems. [ABSTRACT FROM AUTHOR]

This paper introduced the automata field concept and studied its characteristics. In particular, we define new operations by converting finite automata to finite automata field. Additionally, we examine the properties of finite automata field and their relation to field. We also define substructures of the automata field, including sub-automata field and automata field homomorphism. [ABSTRACT FROM AUTHOR]

Thermal energy storage (TES) devices use phase change materials (PCMs) to store and release thermal energy. Control-oriented models are needed to predict the behavior of TES devices and experimental validation is necessary to demonstrate the predictive capabilities of these models. This paper presents an experimental validation of a switched moving boundary (MB) approach for modeling TES devices, where the dynamics of the device are captured with fewer states than traditional models. A graph-based modeling approach is used to model heat flow, while the moving boundary captures the time-varying liquid and solid regions of the TES. The model uses a finite state machine (FSM) to switch between four modes of operation based on the state-of-charge (SOC) of the TES. Results show that the switched MB approach has similar accuracy and lower computational cost compared to traditional modeling approaches when predicting the SOC of an experimental TES device. [ABSTRACT FROM AUTHOR]

This article shows that the universal generation problem for Optimality Theory (OT) is PSPACE-complete. While prior work has shown that universal generation is at least NP-hard and at most EXPSPACE-hard, our results place universal generation in between those two classes, assuming that NP ≠ PSPACE. We additionally show that when the number of constraints is bounded in advance, universal generation is at least NL-hard and at most NP NP -hard. Our proofs rely on a close connection between OT and the intersection non-emptiness problem for finite automata, which is PSPACE-complete in general and NL-complete when the number of automata is bounded. Our analysis shows that constraint interaction is the main contributor to the complexity of OT: The ability to factor transformations into simple, interacting constraints allows OT to furnish compact descriptions of intricate phonological phenomena. [ABSTRACT FROM AUTHOR]

Text mining is crucial for analyzing unstructured and semi-structured textual documents. This paper introduces a fast and precise text mining method based on a finite automaton to extract knowledge domains. Unlike simple words, multi-word units (such as credit card) are emphasized for their efficiency in identifying specific semantic areas due to their predominantly monosemic nature, their limited number and their distinctiveness. The method focuses on identifying multi-word units within terminological ontologies, where each multi-word unit is associated with a sub-domain of ontology knowledge. The algorithm, designed to handle the challenges posed by very long multi-word units composed of a variable number of simple words, integrates user-selected ontologies into a single finite automaton during a fast pre-processing step. At runtime, the automaton reads input text character by character, efficiently locating multi-word units even if they overlap. This approach is efficient for both short and long documents, requiring no prior training. Ontologies can be updated without additional computational costs. An early system prototype, tested on 100 short and medium-length documents, recognized the knowledge domains for the vast majority of texts (over 90%) analyzed. The authors suggest that this method could be a valuable semantic-based knowledge domain extraction technique in unstructured documents. [ABSTRACT FROM AUTHOR]

Earlier protection methods mainly focused on using communication channels to transmit trip signals between the protective devices (PDs), with no solutions provided in the case of communication failure. Therefore, this paper introduces a dual-layer protection system to ensure secure protection against fault events in the Distribution Systems (DSs), particularly in light of communication failures. The initial layer uses the Total Harmonic Distortion (THD), the estimates of the amplitude voltages, and the zero-sequence grid voltage components, functioning as a fault sensor, to formulate an adaptive algorithm based on a Finite State Machine (FSM) for the detection and isolation of faults within the grid. This layer primarily relies on communication protocols for effective coordination. A Second-Order Generalized Integrator (SOGI) expedites the derivation of the estimated variables, ensuring fast detection with minimal computational overhead. The second layer uses the behavior of the positive- and negative-sequence components of the grid voltages during fault events to locate and isolate these faults. In the event that the first layer exposes a communication failure, the second layer will automatically be activated to ensure secure protection as it operates, using the local information of the Protective devices (PDs), without the need for communication channels to transmit trip signals between the PDs. The proposed protection system has been assessed using simulations with MATLAB/Simulink and providing experimental results considering an IEEE 9-bus standard radial system. The obtained results confirm the capability of the system for identifying and isolating different types of faults, varying conditions, and modifications to the grid configuration. The results show good behavior of the initial THD-based layer, with fast time responses ranging from 6 to 8.5 ms in all the examined scenarios. In contrast, the sequence-based layer exhibits a protection time response of approximately 150 ms, making it a viable backup option in the event of a communication failure. [ABSTRACT FROM AUTHOR]

The object of research is the processes of effective search for information in a set of textual data. The subject of the research is the fuzzy search method, which will allow to effectively solve the problem of searching for information in a set of textual data. The paper considers the process of developing a fuzzy search method, which consists of 9 consecutive steps and is required for a quick search for matches in a large set of text data. Based on this method, it is proposed to create a fuzzy search system that will solve the problem of finding the most relevant documents from a set of such documents. The proposed fuzzy search method combines the advantages of algorithms based on deterministic finite automata and algorithms based on dynamic programming for calculating the Damerau-Levenshtein distance. Such a combination allows to implement the symbol similarity table in an optimal way. As part of the work, an approach for creating a symbol similarity table was proposed and an example of such a table was created for symbols from the English alphabet, which allows to find the degree of similarity between two symbols with constant asymptotics and to convert the current symbol into its basic counterpart. For document filtering, a metric was developed to evaluate the correspondence of text data to a search phrase, which simultaneously takes into account the number of found and not found characters and the number of found and not found words. The Damerau-Levenstein algorithm allows to find the edit distance between two words, taking into account the following types of errors: substitution, addition, deletion, and transposition of characters. The work proposed a modification of this algorithm by using a similarity table to more accurately estimate the editing distance between two words. The developed method makes it possible to create a fuzzy search system that will help find the desired results faster and increase the relevance of the obtained results by sorting them according to the values of the proposed test data similarity metric. [ABSTRACT FROM AUTHOR]

Recently, Solecki [Forum Math. Sigma 7 (2019), p. 40] introduced the notion of Ramsey monoid to produce a common generalization to theorems such as Hindman's theorem, Carlson's theorem, and Gowers' FIN_k theorem. He proved that an entire class of finite monoids is Ramsey. Here we improve this result, enlarging this class and finding a simple algebraic characterization of finite Ramsey monoids. We extend in a similar way a result of Solecki regarding a second class of monoids connected to the Furstenberg-Katznelson Ramsey theorem. The results obtained suggest a possible connection with Schützenberger's theorem and finite automata theory. [ABSTRACT FROM AUTHOR]

Wireless sensors and actor networks (WSANs) have been widely used in various fields, from basic data collection to precise real-time control and monitoring, including battlefield monitoring, rescue, and exploration. The actor nodes in a WSAN play a key role in processing and transmitting data, and because of the harsh environmental conditions encountered, network node failures are prone to occur. The failure of an actor causes a loss of connectivity with its neighbor nodes, resulting in network splits and failure to deliver messages between nodes. Therefore, determining how to quickly and autonomously recover network connectivity while minimizing the moving distance of backup nodes and the number of relocated nodes is crucial. In this paper, we propose a dynamic weight-based connectivity recovery (DWCR) method to minimize the total moving distance of actor nodes, the number of relocated nodes, the total messages sent, and the coverage loss rate. The proposed DWCR method involves selecting a backup node for each critical node by dynamically adjusting the weight. If a critical node fails, the backup node starts to move to restore the connectivity of the failed node. The simulation results indicate that the proposed DWCR method outperforms the recovery through inward motion (RIM) method and other methods in terms of minimizing the total moving distance, the number of relocated nodes, and the total messages sent. However, because the RIM algorithm requires the relocation of more nodes during the network process, the DWCR algorithm is slightly inferior to the RIM algorithm in terms of coverage loss rate. Nevertheless, the DWCR algorithm still outperforms the distributed actor recovery algorithm and the distributed autonomous connectivity restoration method based on finite state machine algorithm. [ABSTRACT FROM AUTHOR]

Discrete states linked together by events can describe a series of classical video game scenarios. Therefore, the formal concept of automata seems appropriate for describing such games. However, as simple finite automata need to keep track of past events, they are less appropriate for complex designs. By contrast, push-down automata featuring a stack present better capabilities in this context. This paper discusses an enhanced version of the classic PAC-MAN game with push-down automata. The modular design of this game allows the extraction of discrete states, and its minimalist concept enables various approaches and new versions without sacrificing its original essence. Using push-down automata expanded the game with new features, allowing an enhanced game experience. The automaton controls all aspects of the game, ensuring a consistent gameplay. The presented project demonstrates the capabilities of push-down automata in the gaming industry and their potential in future game development projects. [ABSTRACT FROM AUTHOR]

In this letter, a high‐speed and low‐latency Ron Rivest‐4 (RC4) encryption algorithm is designed based on SMIC 14 nm process. Since the key issue of limiting the throughput of RC4 encryption algorithm is the swapping operation of S‐box, this proposed design is capable of achieving four swapping operations of S‐box within a clock cycle by utilizing fully combinational logic designs and advanced computations. All 256 swapping operations of key scheduling algorithm (KSA) can be done in 64 clock cycles. Moreover, the novel design greatly improves the encryption efficiency of RC4 since each clock cycle offers 4 bytes of key stream. The whole area can be further optimized by reusing the existing modules, and a lightweight countermeasure is embedded into the RC4 design to break the correlation between the processed data and power dissipation against differential power analysis (DPA) attacks. Finally, the whole design is assessed by the SMIC 14 nm process design kits (PDK). The corresponding clock frequency, throughput, area, and latency, respectively, are achieved as 1 GHz, 32 Gbps, 51,596 μm2, and 74 clock cycles. [ABSTRACT FROM AUTHOR]

Summary: This brief proposes a new lightweight authenticated encryption algorithm SIMON‐GCM for Internet of Things (IoT) security, which realizes the combination of SIMON block cipher and Galois/Counter Mode (GCM). The designed SIMON circuit supports 128/192/256‐bit key size, which improves the flexibility and enlarges the range of applications. Moreover, the scheme of 32‐cycle Galois field (GF) multiplier in GF(2128) is adopted to effectively reduce the hardware cost of the Galois Hash (GHASH) function in GCM. At the same time, a finite state machine (FSM) is used to run the SIMON and GHASH modules in parallel, thus shortening the authenticated encryption time. The whole circuit is designed and implemented in field programmable gate array (FPGA) platforms. It is measured to yield a throughput of 32.4 Gbps when consuming 331 slices in Artix‐7. Compared with the existing authenticated encryption algorithms, the proposed algorithm achieves lower resource consumption and better flexibility. [ABSTRACT FROM AUTHOR]

Concepts of generalized commutative intuitionistic fuzzy finite state machines and generalized switching intuitionistic fuzzy finite state machines are proposed in this paper, and properties of these two kinds of intuitionistic fuzzy finite state machines are investigated. By using the conditions associated with generalized commutativity, a kind of congruences of intuitionistic fuzzy finite state machines is defined. Homomorphic properties of generalized commutative intuitionistic fuzzy finite state machine are also discussed. Moreover, products of generalized commutative intuitionistic fuzzy finite state machines and products of generalized switching intuitionistic fuzzy finite state machines are studied, and some related properties are proved. [ABSTRACT FROM AUTHOR]

We present an application of strategy synthesis to enforce spatial properties. This is achieved by implementing a toolchain that enables the tools CATLib and VoxLogicA to interact in a fully automated way. The Contract Automata Library (CATLib) is aimed at both composition and strategy synthesis of games modelled in a dialect of finite state automata. The Voxel-based Logical Analyser (VoxLogicA) is a spatial model checker for the verification of properties expressed using the Spatial Logic of Closure Spaces on pixels of digital images. We provide examples of strategy synthesis on automata encoding motion of agents in spaces represented by images, as well as a proof-of-concept realistic example based on a case study from the railway domain. The strategies are synthesised with CATLib, while the properties to enforce are defined by means of spatial model checking of the images with VoxLogicA. The combination of spatial model checking with strategy synthesis provides a toolchain for checking and enforcing mobility properties in multi-agent systems in which location plays an important role, like in many collective adaptive systems. We discuss the toolchain's performance also considering several recent improvements. [ABSTRACT FROM AUTHOR]

The process of electrospinning is over a century old, yet novel material and method achievements, and later the addition of nanomaterials in polymeric solutions, have spurred a significant increase in research innovations with several unique applications. Significant improvements have been achieved in the development of electrospun nanofibrous matrices, which include tailoring compositions of polymers with active agents, surface functionalization with nanoparticles, and encapsulation of functional materials within the nanofibers. Recently, sequentially combining fabrication of nanofibers with 3D printing was reported by our group and the synergistic process offers fiber membrane functionalities having the mechanical strength offered by 3D printed scaffolds. Recent developments in electrospun nanofibers are enumerated here with special emphasis on biomedical technologies, chemical and biological sensing, and energy harvesting aspects in the context of e-textile and tactile sensing. Energy harvesting offers significant advantages in many applications, such as biomedical technologies and critical infrastructure protection by using the concept of finite state machines and edge computing. Many other uses of devices using electrospun nanofibers, either as standalone or conjoined with 3D printed materials, are envisaged. The focus of this review is to highlight selected novel applications in biomedical technologies, chem.-bio sensing, and broadly in energy harvesting for use in internet of things (IoT) devices. The article concludes with a brief projection of the future direction of electrospun nanofibers, limitations, and how synergetic combination of the two processes will open pathways for future discoveries. [ABSTRACT FROM AUTHOR]

The design of System-on-Chip systems using synchronous circuits involves complex clock distribution strategies, which envisage challenges for designers to integrate large-scale systems. Globally Asynchronous Locally Synchronous architectures containing asynchronous port controllers encapsulated in the self-timed wrapper have been adopted in this work. These port controllers communicate through Asynchronous Finite State Machines defined by Signal Transition Graphs are implemented adopting the C element. This GALS architecture implemented for the point-to-point interface can also be modified for the multipoint interface. The proposed methodology uses a two-phase handshake protocol to communicate between two Locally Synchronous modules as it has fewer signal transitions, which, in turn, reduces latency. In this paper, the Queue Direct Memory Access subsystem is implemented using the Vivado simulator on UltraScale+™ device at a maximum frequency of 257.4MHz, and various parameters are reported. A comparison shows that the proposed wrapper has improved latency time of 53%, with a reduction in power dissipated by 27% and an increase in gate count by 13%. [ABSTRACT FROM AUTHOR]

The problem of scheduling household appliances with the availability of renewable energy is the biggest challenge in the smart home energy management system. The components such as renewable energy resources, household appliances, utility grid, storage batteries are pooled into a nonlinear, time-varying, indefinite, and dynamic structure that is impossible to control and refine. For this, real-time pricing is applied in most nations to withstand the burden on the grid. This requires attention to utilize renewable energy effectively. In this paper, a load scheduling method to schedule the loads based on the availability of solar energy and customer preferences is presented. First, the availability of solar energy is forecasted ahead one day using Regression Analysis. Second, the finite state machine approach-based load scheduling algorithm is implemented and tested using MATLAB Simulink and Lab VIEW. LabVIEW-based GUI is developed to visualize the MATLAB schedule for loads. The problem is divided into several states with the availability of solar power, and if solar power is unavailable, grid power is utilized. The loads preferred by the consumers are scheduled in alignment with the production of solar power with the finite state machine scheduling algorithm. Also, the loads considered are able to consume instantaneous energy with the instantaneous production of energy, thereby reducing CO2 emission by not consuming power from the grid. Finally, the loads are scheduled accordingly, and it is concluded that coordination can be established between energy providers, and the system proposed can flatten out the load profile. [ABSTRACT FROM AUTHOR]

Regular path query is a technique of using regular expressions to query graph data, usually uses finite state automata to achieve query matching. The matching result of the existing regular path query method is a sequence of vertex pairs, and the structure of the graph is not fully preserved. In order to solve this problem, this paper proposed a method of structured regular path query for graph data. By structuring constraints between different sequences, the query results could be transformed from paths to subgraphs. For this purpose, the method firstly defined a structured regular path query language, and then designed a structured query parsing and a matching algorithm based on this structure. Experimental results on simulated and real datasets verify the influence of network size on query speed. This paper compared the proposed method with the control group. Experimental results show that the proposed method can realize structured query under the premise of satisfying regular expression constraints. [ABSTRACT FROM AUTHOR]

Due to the growing interest in climbing, increasing importance has been given to research in the field of non-invasive, camera-based motion analysis. While existing work uses invasive technologies such as wearables or modified walls and holds, or focuses on competitive sports, we for the first time present a system that uses video analysis to automatically recognize six movement errors that are typical for novices with limited climbing experience. Climbing a complete route consists of three repetitive climbing phases. Therefore, a characteristic joint arrangement may be detected as an error in a specific climbing phase, while this exact arrangement may not considered to be an error in another climbing phase. That is why we introduced a finite state machine to determine the current phase and to check for errors that commonly occur in the current phase. The transition between the phases depends on which joints are being used. To capture joint movements, we use a fourth-generation iPad Pro with LiDAR to record climbing sequences in which we convert the climber's 2-D skeleton provided by the Vision framework from Apple into 3-D joints using the LiDAR depth information. Thereupon, we introduced a method that derives whether a joint moves or not, determining the current phase. Finally, the 3-D joints are analyzed with respect to defined characteristic joint arrangements to identify possible motion errors. To present the feedback to the climber, we imitate a virtual mentor by realizing an application on the iPad that creates an analysis immediately after the climber has finished the route by pointing out the detected errors and by giving suggestions for improvement. Quantitative tests with three experienced climbers that were able to climb reference routes without any errors and intentionally with errors resulted in precision–recall curves evaluating the error detection performance. The results demonstrate that while the number of false positives is still in an acceptable range, the number of detected errors is sufficient to provide climbing novices with adequate suggestions for improvement. Moreover, our study reveals limitations that mainly originate from incorrect joint localizations caused by the LiDAR sensor range. With human pose estimation becoming increasingly reliable and with the advance of sensor capabilities, these limitations will have a decreasing impact on our system performance. [ABSTRACT FROM AUTHOR]

Micro-Electro-Mechanical System (MEMS) capacitive accelerometers have received extensive attention in recent years due to their excellent performance indicators; especially in the fields of noise, power consumption, and bias instability, great development and progress have been made. In the field of noise, effective noise reduction is achieved by introducing oversampling modulation technology combined with digital noise reduction technology. In power consumption, the power consumption of the accelerometer is effectively reduced by using the successive approximation structure in the interface circuit and using the finite state machine for precise control. In bias instability, the effects of temperature offset and zero-point drift are suppressed by using a hybrid topology connection structure in the interface circuit, and an effective reduction of bias instability is achieved. In this paper, the research and progress of MEMS capacitive accelerometer in the field of noise, power consumption and bias instability are reviewed, and the articles published in recent years are listed and summarized and prospected. [ABSTRACT FROM AUTHOR]

High-performance computers are used for computation-intensive tasks. It is essential for these systems to simultaneously execute several computation-intensive tasks for efficient and timely system utilization. Since typical tasks have a longer runtime, it is essential to determine the runtime of each task prior to execution and schedule them accordingly. We propose a method for predicting the runtime of MPI-based software. Initially, we analyze the source code of the software by translating the code to finite automata and measuring the state complexity. Next, the runtime of software is trained using a deep neural network (DNN) along with its state complexity. Herein, we propose three models based on DNN, statistics and their hybrid. DNN model is superior in comparison. Additionally, the adaptability of our method is demonstrated by showing that our method can adapt on new environment with 90% accuracy on various software. [ABSTRACT FROM AUTHOR]

The object of research is fuzzy search algorithms based on Damerau-Levenshtein automata and Levenshtein automata. The paper examines and compares solutions based on finite state machines for efficient and fast finding of words and lines with a given editing distance in large text data using the concept of fuzzy search. Fuzzy search algorithms allow finding significantly more relevant results than standard explicit search algorithms. However, such algorithms usually have a higher asymptotic complexity and, accordingly, work much longer. Fuzzy text search using Damerau-Levenshtein distance allows taking into account common errors that the user may have made in the search term, namely: character substitution, extra character, missing character, and reordering of characters. To use a finite automaton, it is necessary to first construct it for a specific input word and edit distance, and then perform a search on that automaton, discarding words that the automaton will not accept. Therefore, when choosing an algorithm, both phases should be taken into account. This is because building a machine can take a long time. To speed up one of the machines, SIMD instructions were used, which gave a speedup of 1–10 % depending on the number of search words, the length of the search word and the editing distance. The obtained results can be useful for use in various industries where it is necessary to quickly and efficiently perform fuzzy search in large volumes of data, for example, in search engines or in autocorrection of errors. [ABSTRACT FROM AUTHOR]

We prove that the limit dynamics of any finite automata network under the parallel update schedule correspond exactly to the fixed points of a so-called strictly one-way cellular automaton. This correspondence is proven to be exact, as any strictly one-way cellular automaton can be transformed into a corresponding automata network, the limit dynamics of the latter corresponding exactly to the fixed points of the former. This transformation is operated using output functions, which have been developed in the author's previous works. [ABSTRACT FROM AUTHOR]

Nowadays chaos-based cryptography systems are widely used to protect sensitive data. A variety of chaos-based cryptosystems with software implementation has been published in the literature. However, due to the rapid growth of connected devices, the development of hardware secure and low-resource cryptographic systems is necessary. In this paper, we enhance the design of one of our software cryptosystems and then we address its FPGA-based implementation. The improvement in the design consists essentially to introduce an Initial Vector (IV) entry to the Chaotic Pseudo Random Number Generator (CPRNG) thus allowing to generate a new dynamic keys for the confusion layer (using a modified 2-D cat map) and diffusion layer (using a logistic map) with each new execution of the system. The CPRNG is formed by XORred a discrete Skew Tent Map (STM) with a discrete Piecewise Linear Chaotic Map (PWLCM). The proposed cryptosystem, which operates in Cipher Block Chaining (CBC) mode, is controlled by a Finite State Machine (FSM) to ensure that both the encryption and decryption are performed by the same reconfigurable architecture. The system is implemented on a Xilinx XC7Z020 ZYNQ FPGA platform. The results obtained in terms of hardware implementation costs (logic resources, throughput, and efficiency) and in terms of security against cryptographic attacks demonstrate the effectiveness of the proposed chaos-based cryptosystem. [ABSTRACT FROM AUTHOR]

The early detection of cyber threats with cyber-attacks adapted to the nature of information systems is a crucial cybersecurity problem. This problem and the task of recognizing normal and abnormal states and behavior of various processes in information systems are closely related. An additional condition is often the absence of templates, signatures, or rules of normal behavior that would allow the use of existing statistical or other known data analysis methods. We analyze the existing and propose a new method for detecting abnormal behavior without using signatures based on the finite state machine (FSM) model and the Security Information and Events Management (SIEM) system. [ABSTRACT FROM AUTHOR]

State identification is the well-known problem in the automata theory that is aimed to determining the current or initial state of a system under test and this fact is widely used in the model-based testing of software and hardware systems. When modern systems are modeled, it is necessary to take into account the timed aspects and for this reason classical Finite State Machines (FSM) are extended by clock variables. In this work, we study the homing problem for FSMs with timeouts (TFSM). For this purpose, we introduce the notion of a timed homing sequence (HS) that is different from that for classical FSMs and propose a method for checking the existence and deriving a timed HS if it exists. A proposed method is based on the FSM abstraction of a TFSM, i.e. on a classical FSM that partially describes the behavior of a corresponding TFSM and inherits many of its properties. Since timeouts allow the system to move from state to state without input impact, we define a timed HS as a sequence that sets a TFSM to a stable state where the system can stay infinitely long waiting for an input. [ABSTRACT FROM AUTHOR]

Symbolic time series analysis (STSA) plays an important role in the investigation of continuously evolving dynamical systems, where the capability to interpret the joint effects of multiple sensor signals is essential for adequate representation of the embedded knowledge. This technical brief develops and validates, by simulation, an STSA-based algorithm to make timely decisions on dynamical systems for information fusion and pattern classification from ensembles of multisensor time series data. In this context, one of the most commonly used methods has been neural networks (NN) in their various configurations; however, these NN-based methods may require large-volume data and prolonged computational time for training. An alternative feasible method is the STSA-based probabilistic finite state automata (PFSA), which has been shown in recent literature to require significantly less training data and to be much faster than NN for training and, to some extent, for testing. This technical brief reports a modification of the current PFSA methods to accommodate (possibly heterogeneous and not necessarily tightly synchronized) multisensor data fusion and (supervised learning-based) pattern classification in real-time. Efficacy of the proposed method is demonstrated by fusion of time series of position and velocity sensor data, generated from a simulation model of the forced Duffing equation. [ABSTRACT FROM AUTHOR]

The problem of extending model checking from finite state machines to procedural programs has fostered much research toward the definition of temporal logics for reasoning on context-free structures. The most notable of such results are temporal logics on Nested Words, such as CaRet and NWTL. Recently, Precedence Oriented Temporal Logic (POTL) has been introduced to specify and prove properties of programs coded trough an Operator Precedence Language (OPL). POTL is complete w.r.t. the FO restriction of the MSO logic previously defined as a logic fully equivalent to OPL. POTL increases NWTL's expressive power in a perfectly parallel way as OPLs are more powerful that nested words. In this article, we produce a model checker, named POMC, for OPL programs to prove properties expressed in POTL. To the best of our knowledge, POMC is the first implemented and openly available model checker for proving tree-structured properties of recursive procedural programs. We also report on the experimental evaluation we performed on POMC on a nontrivial benchmark. [ABSTRACT FROM AUTHOR]

In the mid-1930s, the English mathematician and logician Alan Turing invented an imaginary machine which could emulate the process of manipulating finite symbolic configurations by human computers. His machine launched the field of computer science and provided a foundation for the modern-day programmable computer. A decade later, building on Turing's machine, the American-Hungarian mathematician John von Neumann invented an imaginary self-reproducing machine capable of open-ended evolution. Through his machine, von Neumann answered one of the deepest questions in Biology: Why is it that all living organisms carry a self-description in the form of DNA? The story behind how two pioneers of computer science stumbled on the secret of life many years before the discovery of the DNA double helix is not well known, not even to biologists, and you will not find it in biology textbooks. Yet, the story is just as relevant today as it was eighty years ago: Turing and von Neumann left a blueprint for studying biological systems as if they were computing machines. This approach may hold the key to answering many remaining questions in Biology and could even lead to advances in computer science. [ABSTRACT FROM AUTHOR]

When realized on computational devices with finite quantities of memory, feedforward artificial neural networks and the functions they compute cease being abstract mathematical objects and turn into executable programs generating concrete computations. To differentiate between feedforward artificial neural networks and their functions as abstract mathematical objects and the realizations of these networks and functions on finite memory devices, we introduce the categories of general and actual computabilities and show that there exist correspondences, i.e., bijections, between functions computable by trained feedforward artificial neural networks on finite memory automata and classes of primitive recursive functions. [ABSTRACT FROM AUTHOR]

Stochastic-computing-based artificial neural networks (SC-ANNs) can be used to perform hardware- and energy-efficient neuromorphic computing. We have been developing SC-ANNs using an energy-efficient superconductor logic family, namely, adiabatic quantum-flux-parametron (AQFP) logic. AQFP logic is suitable as a building block for SC-ANNs since it can perform stochastic operations with extremely small energy dissipation. In this Letter, we propose and demonstrate a sigmoid function generator (SFG) for AQFP SC-ANNs, which we refer to as the AQFP SFG. An SFG is an important circuit in neural networks that generates outputs from the sum of weighted inputs in accordance with the sigmoid function. The AQFP SFG performs the sigmoid function using a finite state machine based on an AQFP buffer coupled to a flux storage loop. We experimentally demonstrate that the AQFP SFG generates output signals from stochastic bitstreams in accordance with the sigmoid function and that the characteristics of the sigmoid function can be controlled by a bias current. Furthermore, we show that the AQFP SFG operates with small power dissipation due to its simple structure. [ABSTRACT FROM AUTHOR]

Non-Playable Characters (NPCs) are essential for creating a fully immersive video game experience. However, their behaviours are typically programmed using rigid methods such as Finite State Machines and Behaviour Trees. These methods are hard to maintain, struggle with implementing intricate cooperative behaviours, and patterns in NPC behaviour can easily be exploited by human players. Machine Learning and Reinforcement Learning (RL) methods in particular, offer a solution to these challenges by allowing dynamic and real-time NPC responses to human player actions and other characters in the game. This work describes and extends upon a Curriculum-based RL approach to train a single model for multiple agents representing vehicles to respect traffic regulations. These vehicles learn to navigate a road network which includes a traffic lights crossroad intersection and a roundabout junction. A comparison of our simulated data against datasets obtained from real world data is conducted; results demonstrate that the learned models have similar trends to the real-world data. • Multi-agent simulation for game characters navigating a road network. • Reinforcement Learning in game design can generate compelling agent behaviours. • Curricula can help reinforcement learning process to learn complex behaviours. • Macroscopic behaviour of agents matches real world data. [ABSTRACT FROM AUTHOR]

The paper is devoted to the problem of deriving synchronizing and homing experiments for nondeterministic Input/Output automata; corresponding input sequences are widely used in testing (non-initialized) discrete event systems. In active testing, there is an opportunity to set a system under test into a known initial state; in passive testing, a known current state allows to reduce the number of properties to be checked. In the paper, we note that such experiments for Input/Output automata are different from so-called "gedanken" experiments with classical Finite State Machines; the existence check conditions of such experiments are established for a predefined discipline of applying inputs and a method for its derivation is proposed when such an experiment exists. The obtained results allow to reduce the problem of deriving synchronizing and homing experiments for Input/Output automata to the well developed problem of deriving such experiments for appropriate classes of Finite State Machines. [ABSTRACT FROM AUTHOR]

Given an input tree and a tree pattern, the inexact tree pattern matching problem is about finding all subtrees in the input tree that match the tree pattern with up to k errors. To measure the number of errors between two labeled ordered trees, we use the 1-degree edit distance that uses operations node relabel, leaf insert, and leaf delete. The proposed solution is based on a finite automaton that reads a given input tree represented in linear, prefix bar, notation. First, we show its construction for a constrained variant of 1-degree edit distance where leaf insert/delete operations cannot be applied to the tree pattern recursively. Then, we extend this approach to both unit cost and non-unit cost 1-degree edit distance. The deterministic version of the proposed finite automaton finds all inexact occurrences of the tree pattern in time linear to the size of the input tree. However, since the size of such automaton can be exponential in the number of nodes of the tree pattern, it is practical only for small patterns. Therefore, we also consider the dynamic programming approach as a way of simulating the nondeterministic finite automaton. This approach comes with the space complexity O (m k) and time complexity O (k m n) where m is the number of nodes of the tree pattern, n is the number of nodes of the input tree, and k is the maximum number of errors allowed. [ABSTRACT FROM AUTHOR]

This paper proposes the conceptual design method for a hybrid-actuated lower limb exoskeleton based on energy consumption simulation. Firstly, the human-machine coupling model is established in OpenSim based on the proposed three passive assistance schemes. On this basis, the method of simulating muscle driving is used to find out the scheme that can reduce the metabolic rate the most with 3 passive springs models. Then, an active-passive cooperative control strategy is designed based on the finite state machine to coordinate the operation of the power mechanism and the passive energy storage structure and improve the mobility of the wearer. In the end, a simulation experiment based on the human-machine coupled model with the addition of active actuation is proceeded to evaluate its assistance performance according to reducing metabolic rate. The results show that the average metabolic cost decreased by 7.2% with both spring and motor. The combination of passive energy storage structures with active actuators to help the wearer overcome the additional consumption of energy storage can further reduce the body's metabolic rate. The proposed conceptual design method can also be utilized to implement the rapid design of a hybrid-actuated lower limb exoskeleton. [ABSTRACT FROM AUTHOR]