Finite State Research Articles

Multi-physics finite state fully coupled modeling of mechanism-free induced-strain actuated ornithopters

As per de Gennes’ predictions, a superconducting layer placed between two ferromagnetic insulators can drive an antiferromagnetic exchange coupling between them. Using two ferromagnetic insulating GdN layers having dissimilar switching fields sandwiching a superconducting Vanadium thin film, we demonstrate evidence of such exchange coupling. We demonstrate that such an exchange coupling promotes switching between zero and finite resistance states of Vanadium. Our devices hold either a finite resistance or a zero-resistance state at zero magnetic field, dependent on their magnetic field history. Moreover, we demonstrate the absolute switching effect, thus making such devices suitable for application at the lowest temperatures as non-volatile cryogenic memory useful for futuristic quantum circuits and for several other superconducting spintronic applications.

Abstract The increase in salt concentration of electrolytes has been known as a simple but effective approach to restrain solvent activity and regulate solvation structure, thus enabling the long‐term interfacial stability of batteries. Nevertheless, the ion electrostatic intercalations and finite coordination states have frustrated the efforts to further elevate the salt solubility. Here, we break the upper limit of lithium‐salt dissolution through a molecule engineering strategy, in which the solvent with three ether‐oxygen groups provides multi‐coordination sites and the intrinsically inert diluents with low steric hindrance are activated to shield electrostatic repulsion. As a result, a series of localized ultrahigh‐concentration electrolytes (LUCEs) are prepared with a molar ratio of Li + to the solvent as high as 1.8. The LUCEs are endowed with high Li + transference number of 0.682, high Coulombic efficiency for lithium plating/stripping up to 99.97%, and high oxidation stability over 6.5 V. Meanwhile, the scarce free solvent promotes the formation of a robust inorganic‐rich interphase on both the lithium anode and a high‐voltage cathode, which enables the operation of Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 batteries over 180 cycles (>80% capacity retention) under a lean lithium source (20 µm) and high‐loading cathode (3.885 mAh cm −2 ). Our work elucidates the underlying mechanism of salt dissolution chemistry and offers an affordable method for stabilizing energy‐dense electrochemical storage devices.

The increase in salt concentration of electrolytes has been known as a simple but effective approach to restrain solvent activity and regulate solvation structure, thus enabling the long-term interfacial stability of batteries. Nevertheless, the ion electrostatic intercalations and finite coordination states have frustrated the efforts to further elevate the salt solubility. Here, we break the upper limit of lithium-salt dissolution through a molecule engineering strategy, in which the solvent with three ether-oxygen groups provides multi-coordination sites and the intrinsically inert diluents with low steric hindrance are activated to shield electrostatic repulsion. As a result, a series of localized ultrahigh-concentration electrolytes (LUCEs) are prepared with a molar ratio of Li+ to the solvent as high as 1.8. The LUCEs are endowed with high Li+ transference numberof 0.682, high Coulombic efficiency for lithium plating/stripping up to 99.97%, and high oxidation stability over 6.5V. Meanwhile, the scarce free solvent promotes the formation of a robust inorganic-rich interphase on both the lithium anode and a high-voltage cathode, which enables the operation of Li||LiNi0.8Co0.1Mn0.1O2 batteries over 180 cycles (>80% capacity retention) under a lean lithium source (20µm) and high-loading cathode (3.885 mAh cm-2). Our work elucidates the underlying mechanism of salt dissolution chemistry and offers an affordable method for stabilizing energy-dense electrochemical storage devices.

ABSTRACTRobotic systems in practical applications are subject to various uncertainties, including sensor measurement errors, parameter variations, and external disturbances, which can compromise system performance and stability. Additionally, ensuring operational safety is crucial to prevent harm to both personnel and the surrounding environment. To address these challenges, this paper proposes a novel robust constraint‐following control method incorporating inequality constraints, based on the Udwadia–Kalaba (U‐K) equation, to enhance the reliability and safety of complex mechanical systems. First, the dynamic equation of selective compliance assembly robot arm (SCARA) robots is derived using the U‐K equation. Then, employing a diffeomorphism approach, the finite state variables are mapped to infinite state variables via a tangent function, ensuring that the joint displacement of the SCARA robot remains within a bounded range. Based on this transformed mathematical model, a robust constraint‐following controller is designed. The Lyapunov method is then utilized to establish the uniform boundedness and uniform ultimate boundedness of the controlled system. Finally, the proposed control algorithm is validated through numerical simulations and experimental testing on a SCARA robot platform.

This study aims to develop an educational game titled "Introduction to the North Sumatra State Museum" to enhance young people's understanding of Indonesia's history, culture, and natural wealth. The game was developed using RPG Maker MV to create an accessible 2D educational game and applies the Finite State Machine (FSM) method to manage interactions with non-player characters (NPCs). A qualitative approach was used, with data collected through questionnaires distributed to 30 respondents aged 15–25. The evaluation focused on gameplay, functionality, and cross-platform compatibility. Results showed that 76% of respondents felt engaged during gameplay, while 74% agreed that the game was effective as an educational tool. Additionally, 74% of respondents stated that the game is suitable to be used as a learning medium for introducing the North Sumatra State Museum.

The dataflow model of computation is well-established in many application areas, including image encoding and decoding. This model consists of actors that process data and communication channels that transmit data between actors. However, when mapping these models to the systems on which they will be executed and synthesizing the necessary code, the number of actors often exceeds the number of execution units by a significant amount. This results in increased overhead for data buffering and communication between actors. To address this issue and adapt the model to the target execution system, we propose a technique that combines static and dynamic actors defined in the CAL actor language. This technique is based on actors’ composition within the dataflow network and creates a new composite CAL actor. When merging actors, we consider the actions of the actors, including their CAL scheduling mechanisms, finite state machines, priorities, and guards. We derive conditions under which connected actors can be merged to form a new CAL-compliant actor. Preliminary experiments show performance improvements of up to 3.6x compared to unoptimized code.

Getting to know the heroes including remembering their services is very important as a form of respect and in order to foster a sense of nationalism, a sense of nationhood and patriotism. therefore, more appropriate and interesting media are needed that can be used by the generation in this millennial era to get to know and remember the heroism of the independence fighters, especially the national heroes. This study uses the Luther-Sutopo Multimedia Development Life Cycle (MDLC) method which has six stages, namely from the concept design stage, collecting materials for the manufacturing process, testing applications, to distributing applications. For testing the application using the SUS method. The Finite State Machine (FSM) method in this game application is applied in compiling puzzles, there are scores and times when the user succeeds in placing each puzzle piece according to its actual position, then the score will increase. The purpose of this study is to design and build an educational game to get to know Indonesian national heroes based on Android for elementary school students in grade 3. The results of the study obtained an average score of 68%. These results can be categorized as good, acceptable with an OK predicate on usability.

This paper describes a new abstract interpretation-based approach to verify temporal safety properties of recursive, higher-order programs. While prior works have provided theoretical impact and some automation, they have had limited scalability. We begin with a new automata-based "abstract effect domain" for summarizing context-sensitive dependent effects, capable of abstracting relations between the program environment and the automaton control state. Our analysis includes a new transformer for abstracting event prefixes to automatically computed context-sensitive effect summaries, and is instantiated in a type-and-effect system grounded in abstract interpretation. Since the analysis is parametric on the automaton, we next instantiate it to a broader class of history/register (or "accumulator") automata, beyond finite state automata to express some context-free properties, input-dependency, event summation, resource usage, cost, equal event magnitude, etc. We implemented a prototype evDrift that computes dependent effect summaries (and validates assertions) for OCaml-like recursive higher-order programs. As a basis of comparison, we describe reductions to assertion checking for higher-order but effect-free programs, and demonstrate that our approach outperforms prior tools Drift, RCaml/Spacer, MoCHi, and ReTHFL. Overall, across a set of 23 benchmarks, Drift verified 12 benchmarks, RCaml/Spacer verified 6, MoCHi verified 11, ReTHFL verified 18, and evDrift verified 21; evDrift also achieved a 6.3x, 5.3x, 16.8x, and 6.4x speedup over Drift, RCaml/Spacer, MoCHi, and ReTHFL, respectively, on those benchmarks that both tools could solve.

SMAC is a newly proposed MAC family built based on the finite state machine (FSM) of the SNOW-V series, targeting the high speed requirements in 5G and beyond. In this paper, we study the committing security of the SMAC family. We first theoretically reduce the committing security of SMAC to the properties of the underlying components, including the Davies-Meyer construction and the compress function. We then propose practical key-committing attacks against SMAC-1, SMAC-3/4, and SMAC- 1 × n , as well as a theoretical attack against SMAC-1/2 with complexity far below the birthday bound. To enhance the committing security of SMAC, we further suggest two variants of SMAC that can resist our attacks. Our results shed some light on how to design highly efficient MACs with robust committing security.

Abstract We consider a family of measure preserving transformations, which act on a common probability space and are chosen at random by a stationary ergodic Markov chain. This setting defines an instance of a random dynamical system, which may be described in terms of a step skew product. In many contexts it is desirable to know whether ergodicity of the family implies ergodicity of the skew product. Introducing the notion of strict irreducibility for Markov kernels we shall characterize the class of Markov chains for which the aforementioned implication holds true. We thereby extend a sufficient condition of Bufetov for the case of finite state Markov chains to general state spaces and show that it is in fact also necessary. As an application we obtain an explicit description of the limit in ergodic theorems for a suitable class of random transformations.

Bio-robots, a novel type of robots created based on brain-machine interface, have shown great potential in search and rescue tasks. However, current research focuses on the bio-robot itself, such as locomotion, localization and navigation, but lacks interactions with the external environment. In this paper, we proposed a new system for rat robot to autonomously explore the border of unknown field out of sight, and then get the boundary map. We invented a wearable backpack, which is an embedded system with laser-ranging sensors, IMU and ultra-wide band (UWB) module, for the rat robot. Based on the wearable system, a classification method for motion states based on random forest (RF) and a navigation algorithm based on finite state machine (FSM) were developed for the autonomous exploration of border and tested in the locomotion experiment. Besides, with the localization and distance data from UWB and laser-ranging sensors, we mapped the distribution of the border, using Ramber-Douglas-Peucker (RDP) algorithm. The results show that the system could effectively navigate the rat robot to explore the field and accurately detect the border. The accuracy of classification reaches 97.86% and the error rate of border detection is 5.90%. This work provides a novel technology that has potential for practical applications such as prospect for minerals and search tasks.&#xD.

The human factor in security is more important when they become the carriers of attacks on enterprises. Phishing attacks can be classified as insider attacks when the employees unintentionally participate in the attack propagation. Since complete user training is a myth, enterprises must implement detection tools for phishing attacks on their network perimeters. This research discusses a two-phase model for phishing URL detection, in which the first phase identifies the properties of URLs that detect phishing and their relative weight using logistic regression. The second phase checks the probability of a new URL being categorized as phishing using the knowledge achieved during the first phase using the dynamically created Finite state machines. The model defines a malicious score (MS), which can be used to check any URL in real-time to identify whether it is phishing or not. The model described in this work has been experimented with different benchmarking datasets to verify the performance. The model provided a decent result in classifying a URL as phishing or naive. The malicious score (MS) defined by this model can be used to evaluate any URL and can be used as a filtering mechanism for end-point phishing URL detection. The key contribution is towards developing a two-phase model which evaluates the URL with the help of self-crafted features without reliance on a feature set. This accommodates the model's hyper-competitive phishing URL detection area in cyber security.

This research aims to address the issue of static and unengaging educational history games for players with diverse skill levels. To this end, a 2D platformer game titled "Parahyangan" was developed, implementing a Dynamic Difficulty Adjustment (DDA) system based on a Finite State Machine (FSM), which allows the difficulty level to adapt to the player's performance. Using the Game Development Life Cycle (GDLC) methodology, the game was designed and quantitatively tested through a User Acceptance Test (UAT) with 85 respondents. The analysis shows that the game was well-received, falling into the "Good" category with a total satisfaction score of 77.55%. The core DDA feature was proven to be functional and well-accepted by the players. The user interface was identified as a major strength, while level progression was noted as an area for improvement. It is concluded that the implementation of DDA using an FSM is an effective solution for creating a more personalized, engaging, and sustainable learning medium for history that maintains player involvement.

Hip arthroplasty is a common orthopaedic surgery. Cementless hip prostheses are currently more common, especially in young and active patients. The number of procedures and revisions is expected to increase with life expectancy. Aseptic loosening (AL) is the main cause of failure. Osteoinductive coatings improve long-term implant stability by enhancing osseointegration. This study aimed to develop a computational framework for predicting AL, considering both the biomechanical factors involved in the osseointegration process and the biological response to osteoinductive materials. A Finite Element model of a human femur implanted with a cementless hip stem was coupled with a Finite State Machine to simulate osseointegration and tissue fibrotisation. The osteoinductive coating was modelled by adjusting the maximum gap at the bone-implant interface that can be bridged by newly formed bone, as well as the bone growth rate. To explore population variability, a total of 27 cases were simulated, including three diff.

<p><strong>Context and relevance.</strong> In the work programs of the disciplines «Theory of Algorithms», «Compilation Methods», «Discrete Mathematics» and others included in the educational programs of specialties in information technology, the concepts of algorithm, finite automata and formal languages occupy an important place. Mastering these concepts requires abstract thinking abilities from students and often cause significant difficulties. <strong>Purpose</strong>. Improve the quality of assimilation of educational material in disciplines related to the concept of an algorithm using special software tools for visualization and modeling of various finite state machines. <strong>Hypothesis</strong>. The use of training simulators to demonstrate algorithm models allows the teacher to present the material as clearly as possible, and it is better for students to master the material and gain skills in solving problems in algorithm theory. <strong>Methods and materials</strong>. The study examined existing software tools for constructing graphs, diagrams of automata, Turing machines. The analysis revealed the shortcomings of individual tools, namely: limited capabilities, inconvenient interface, the need to comply with licensing. <strong>Results.</strong> A web application «FSM-Desiner» has been developed, which plays the role of a training simulator in algorithm theory. The application has a simple interface, the ability to build and simulate finite state machines, store memory machines and Turing machines. The experience of using the simulator showed that students began to cope with tasks better. In addition, it turned out that students had difficulty using artificial intelligence when solving problems, and this was easily detected. <strong>Conclusions</strong>. The use of the training simulator confirmed the importance of using special software tools for mastering the material on the theory of algorithms.</p>

Relevance. The growing demand for autonomous mobile systems capable of independent navigation and parking is driven by several critical factors. Firstly, the rapid robotization in logistics, security, delivery, and service industries necessitates reliable mechanisms for precise positioning of mobile platforms in spatially constrained environments. Secondly, in the context of autonomous vehicle development, the issue of automatic parking becomes a priority for enhancing safety, reducing energy consumption, and minimizing human involvement in control processes. Currently, a significant number of studies focus on the implementation of automatic parking systems; however, most of them either rely on high-cost sensors (such as LiDARs or deeplearning-based cameras) or fail to ensure the required accuracy under dynamic or unfamiliar environmental conditions. Against this backdrop, the use of ultrasonic sensors represents an effective alternative, enabling a necessary level of adaptability and sensitivity while maintaining low system cost. The relevance of this research is further reinforced by the need to develop a universal control model that is scalable, adaptive, and easily integrable into various types of mobile platforms. This work focuses not only on the theoretical formulation of the control model but also on its experimental validation using data from ultrasonic sensors that reflect the physical environment in real time. Therefore, the development of a mobile robot parking control model based on ultrasonic sensors is a timely and important task that combines scientific novelty with practical significance for the advancement of autonomous systems. The object of research. A parking control system for a mobile robot that operates based on data obtained from ultrasonic distance sensors. This system comprises both hardware components, such as ultrasonic sensors, actuators, and controllers, and software that implements algorithms for environmental analysis, decision-making related to parking maneuvers, and motion control. Purpose of the article. This article presents a comprehensive review of contemporary models for mobile robot parking control based on distance sensor data. The objective is to identify and critically evaluate effective approaches to sensor integration, control algorithm design, and architectural implementation of such systems. Particular attention is given to analyzing their applicability in real-world environments, with the aim of outlining development prospects that enhance system accuracy, reliability, and adaptability under dynamic and constrained conditions. Research results. As a result of the conducted review, it has been established that modern mobile robot parking control systems encompass a wide range of modeling approaches, varying in both mathematical complexity and sensor configurations. The analysis reveals that the choice of control model is directly influenced by the availability of computational resources, the robot’s chassis type, and the nature of the operational environment. Particular attention is given to the comparative assessment of sensors, with ultrasonic sensors remaining dominant in short-range positioning systems due to their low cost, ease of integration, and reliability in controlled conditions. Conversely, LiDAR sensors have demonstrated superior accuracy and spatial resolution, although they present higher implementation and maintenance complexity. Cameras and infrared sensors are regarded as supplementary data sources, functioning effectively only within well-defined conditions and with appropriate software support. The findings of the review confirm that an effective parking control system for mobile robots relies on a holistic approach that integrates sensor selection, control model design, algorithmic implementation, and system architecture. Such integration enables high accuracy and operational reliability even in complex, dynamic, or constrained environments. Conclusions. Effective mobile robot parking control is based on the integration of reliable sensor systems, particularly ultrasonic sensors and adaptive decision-making algorithms. Ultrasonic sensors remain the most suitable option for low-cost and simple systems, whereas hybrid approaches involving LiDAR or camera-based solutions offer higher precision. Among the control algorithms, finite state machines, fuzzy logic, and machine learning methods have demonstrated the greatest effectiveness. The most optimal system architecture is modular, with a clear separation between sensing, computation, and actuation layers, which ensures adaptability, accuracy, and operational stability under real-world conditions.

This paper presents the design and evaluation of a lightweight, minimally actuated lower limb exoskeleton that emphasizes hip–knee coordination for natural and efficient gait assistance. The system adopts a hip-only motorized actuation strategy in combination with an electromagnetically controlled knee locking mechanism, ensuring rigid stability during stance while providing compliant assistance during swing. To support sit-to-stand transitions, a gas spring–ratchet mechanism is integrated, which remains disengaged in the seated position, delivers assistive torque during rising, and provides cushioning during the descent to enhance safety and comfort. The control framework fuses foot pressure and thigh-mounted IMU signals for finite state machine (FSM)-based gait phase detection and employs a fuzzy PID controller to achieve adaptive hip torque regulation with coordinated hip–knee control. Preliminary human-subject experiments demonstrate that the proposed design enhances lower-limb coordination, reduces muscle activation, and improves gait smoothness. By integrating a minimal-actuation architecture, a practical sit-to-stand assist module, and an intelligent control strategy, this exoskeleton strikes an effective balance between mechanical simplicity, functional support, and gait naturalness, offering a promising solution for everyday mobility assistance in elderly or mobility-impaired users.

This paper introduces Echo, a 2D top-down shooter game that combines rhythm elements with action gameplay to study how games can improve thinking skills and coordination. The gameplay links to synchronising player inputs with musical beats. The rhythm-triggered shooting mechanics (RTSM) system is designed as the core technology to bridge rhythmic precision with gameplay engagement. The RTSM system uses Unity’s Kore plugin to obtain audio-visual synchronisation to ensure in-game actions (e.g., shooting, evasion) match musical timing. To enable adaptive gameplay, the game architecture integrates finite state machines for managing enemy behaviour and observer patterns to dynamically adjust environments (e.g., tempo shifts, and enemy spawn rates) in response to player performance. Further refinement is carried out through a dynamic beat-mapping algorithm (DBMA), which analyses real-time player accuracy to adjust difficulties. Hence, the game can tailor challenges to individual skills. Evaluation of the RTSM system involves two aspects: skill development and engagement. Beat synchronisation offsets (measured in milliseconds) are measured to quantify player accuracy, with lower deviations indicating improved rhythmic precision. Engagement metrics include session duration, retry rates, and task persistence, which reflect player motivation. These data points are cross-referenced to identify correlations between rhythmic mastery and sustained participation. Results showed that Echo exemplifies the pedagogical value of integrating rhythmic elements into conventional game genres. The RTSM system aligns with cognitive load theory by breaking down complex tasks into beat-synchronised actions, while its adaptive difficulty mirrors constructivist principles of scaffolded learning. This synergy between entertainment and skill-based objectives highlights the potential of hybrid game design to foster experiential learning.

By precisely timed optical excitation of their spin, optical emitters such as semiconductor quantum dots or atoms can be harnessed as sources of linear photonic cluster states. This significantly reduces the required resource overhead to reach fault-tolerant optical quantum computing. Here, we develop an algorithm that analytically tracks the global density matrix through the process of the protocol for generating linear-cluster states by Lindner and Rudolph. From this we derive a model to calculate the entangling gate fidelity and the state fidelity of the generated linear optical cluster states. Our model factors in various sources of error, such as spin decoherence and the finite excited state lifetime. Additionally, we highlight the presence of partial reinitialization of spin coherence with each photon emission, eliminating the hard limitation of coherence time. Our framework provides valuable insight into the cost-to-improvement trade-offs for device design parameters as well as the identification of optimal working points. For a combined state-of-the-art quantum dot with a spin coherence time of {T}_{2}^{*}=535 ns and an excited state lifetime of tau =23 ps, we show that a near-unity entangling gate fidelity as well as near-unity state fidelity for 3-photon and 7-photon linear cluster states can be reached.Graphical