Basic Version Research Articles

Improved machine learning models with a similarity-based approach for remaining useful life prediction

Abstract Cost efficiency is a critical factor in the competitive aviation sector. These efficiency factors force airline operators to develop new approaches in their organizations. Predictive maintenance helps to build scheduling maintenance programs for airline operators or MROs. Scheduled maintenance programs benefit cost efficiency in the aviation sector. Predictive maintenance methods predict the failure time of any equipment. Predictions can be made by analyzing the sensor values from equipment. In this paper, we predicted the remaining useful life (RUL) of turbofan engines using machine learning models and a similarity-based approach. Sensor datasets from the Prognostics Data Repository of NASA, called CMAPPS, were utilized. Using the FD0002 sub-dataset, a health index (HI) was created, and models were trained. Once the models were trained, train and test HIs were estimated. The predicted test HI was matched with the predicted train HI based on a similarity-based approach, and then a RUL prediction was made. The results obtained were compared with the actual results to calculate the accuracy, and the algorithm that resulted in the maximum accuracy was identified. We selected six machine learning algorithms and also created an ensemble model by averaging the predictions of six machine learning algorithms for comparing prediction accuracy. The different algorithms were compared to obtain the prediction model with the closest prediction of remaining useful lifecycle in terms of the number of life cycles. This experiment showed us the effect of the similarity-based approach on the basic version of machine learning models for RUL prediction.

Image Deblurring Using Non Linear Activation Free Network

Abstract: While picture restoration has made significantstrides in recent years, the sophisticated techniques employed are becoming more intricate. This makes a proper comparison difficult. In this research, we propose a straightforward approachthat outperforms these intricate ones in terms of accuracy while requiring less computational resources. We discovered that complex activation functions such as GELU, Softmax, ReLU, andSigmoid are not really needed. Therefore, we developed a more basic version that does not need them, which we call NAFNet.We put our approach to the test on challenging tasks such as noise reduction and image correction. It performed much better, far better than the sophisticated techniques, and used a lot less processing power.

Using the reverse geometry method for warpage compensation on changing meshes with interpolation methods

AbstractIn the manufacturing process of injection molding, the geometric accuracy of the produced part is affected by shrinkage and warpage. To support efforts to compensate for these effects, this paper presents an extension of the numerical compensation approach known as the reverse geometry method. The reverse geometry method is based on the numerical forward simulation of the displacement field resulting from shrinkage and warpage. It is an iterative method that performs node‐based compensation in each step. The mention of node‐based compensation already indicates that the method is associated with a computational mesh. In particular, in its basic version, it is linked to a specific mesh that must be kept identical during all iteration steps. This requirement is not always compatible with commercial simulation tools for injection molding, which enforce automatic remeshing between simulations. We present an interpolation method that allows to handle changing meshes and illustrate the method with two practical examples.

Optimizing Healthcare Flexible Spending Account Contributions Using Inventory Management Theories: An Interdisciplinary Study

The healthcare Flexible Spending Account (FSA) offers employees significant tax benefits by allowing the use of pre-tax funds for healthcare expenses, but it also carries the risk of forfeiting unspent funds. To address the challenge of maximizing tax savings while minimizing the risk of forfeiture, this study applies inventory management and economic theories to develop a heuristic for optimizing FSA contributions. Both basic and extended versions of FSAs are examined, alongside the impact of marginal tax rates on decision-making. A simulation model demonstrates the effectiveness of the proposed heuristic, with results showing minimal deviations from the optimal solutions—less than 0.42% for the basic version and 3.11% for the extended version, and performance differences of less than 0.005% and 0.08%, respectively. By integrating operations management, economic theories, and personal finance research, this study introduces a novel decision-support tool for optimizing FSA contributions, while also laying the groundwork for future research in this interdisciplinary field.

Применение имитационного моделирования в процессах постройки судна

This article provides an example of the application of the method of simulation modeling of ship construction processes in AnyLogic software. The process is briefly described and the logistics of building a barge produced at shipyards is characterized, and a map of the production process is prepared. In conclusion, three possible modernization options were proposed, which consist in technological, organizational improvements and a variant combining both of these solutions. AnyLogic software was used for a comparative analysis of the proposed options in relation to the process in the basic version. This method allows you to obtain accurate data for making informed decisions without the need for physical tests. The use of simulation modeling is a key tool for optimizing shipbuilding processes and further development of the industry.

The determination of bisphenols contained in food-related products with increased accuracy provided by the H-point Standard Addition Method (HPSAM)-based methodology

The basic version of the H-point standard addition method and its variants have been developed with an increased number of measurement conditions (from two to five conditions allowed for differentiation of sensitivity). The methodology adapted to the signal increment and generalized versions was used for the determination of the harmful compounds from the group of bisphenols (bisphenol A, S, and F) using high-performance liquid chromatography with a diode array detector. This approach in theoretical and experimental studies allowed for obtaining high-quality results after eliminating all types of interference effects: multiplicative, additive, and nonlinear. The analysis of food-related samples, such as store receipts and canned food, confirmed the effectiveness of the developed methodology. The analytical results were distinguished by very good accuracy (RE<5 %, RV∼100 %) and precision (CV≤4 %). The approach can be successfully applied to various analytical systems (RGB model) and is characterized by a high greenness value (AGREE approach).

Feasibility and Engagement of a Mobile App Preparation Program (Kwit) for Smoking Cessation in an Ecological Context: Quantitative Study.

Mobile health apps can facilitate access to effective treatment and therapeutic information services. However, the real-world effectiveness of mobile apps for smoking cessation and their potential impact in everyday settings remain unclear. In an ecological context, this study aimed to estimate the engagement rate of a mobile app-based smoking cessation preparation program and its potential impact on users' willingness, ability, and readiness to quit smoking. A total of 2331 "organic users" (ie, users who discover and install a mobile app on their own, without any prompts) chose 1 of 2 program versions of the mobile app (Kwit): the basic version or the premium version. Both versions were identical in design, with 4 more evidence-based content items and strategies in the premium version. Outcomes were analyzed based on automated data registered in the app (engagement rate, motivation to quit, motivation type, motivation levels, and satisfaction level). Mann-Whitney and χ2 tests were used to compare the results of both groups. As expected, in the ecological context, a high dropout rate was observed at different moments. A significant difference was observed between the 2 versions (n=2331; χ21=5.4; P=.02), with a proportionally higher engagement rate in the premium version (premium=4.7% vs basic=2%). Likewise, differences were also observed between the 2 groups in terms of reasons to quit (n=2331; χ24=19; P≤.001; V=0.08), motivation type (n=2331; χ27=14.7; P=.04), and motivation level. Users of the app's premium version more frequently reported "well-being" (23.3% vs 17.9%) and "planning a pregnancy" (7.4% vs 4.4%) as their primary reasons for quitting smoking compared to those with the basic version. Moreover, they reported being more likely to be driven in the smoking cessation process by intrinsic motivation (premium=28% vs basic=20.4%), as well as feeling significantly more willing (z score=156,055; P≤.001; Cohen d=0.15), able (z score=172,905; P=.04; Cohen d=0.09), and ready (z score=166,390; P=.005; Cohen d=0.12) to stop smoking than users who had the basic version before completion of the preparation program. Among participants who finished each version of the program (premium: 9/189, 4.8%; basic: 47/2142, 2.19%), significant improvements in motivation levels were observed in both groups, although in different areas for each group (willingness levels for the premium group and ability for the basic group). These results suggest that even in ecological contexts where engagement rates are meager, the Kwit preparation program can address ambivalence by increasing willingness to change, self-confidence, and readiness to quit among its users, especially those who feel less able to do so. Further development and evaluations are needed to better understand determinants for regular mobile health apps.

Динамическая модель харвестера, оснащенного канатной анкерной системой, при проведении лесозаготовительных работ на крутом склоне

The efficiency of using logging machines for work in mountainous or hilly areas characterized by the presence of steep slopes depends on many factors, among which the quantitative parameters of the dynamic state of both the harvester itself and the anchor system play a priority role to ensure the safe operation of these technological machines. This article considers a complex spatial dynamic model that combines into a common interconnected system all the main components of the simulated phenomenon, including directly a harvester with a hydraulic manipulator mounted on it, a movable assortment in space, an anchor system consist-ing of an anchor rope and a winch, an anchor tree for attaching an anchor rope and the soil of the support surface. The dynamic mathematical model of such a six-component system includes 35 generalized coordinates that determine the linear and angular displacements of the mass centers of the listed system components. A system of 35 differential equations constructed using the Lagrange’s equation was solved by the 4-th-order Runge-Kutta method. For this purpose, a computer program has been developed, the description of which is contained in the article. In relation to the basic version of the simulated system with quantitative initial characteristics focused on the characteristics of a three-axle wheeled harvester with a 6K6 wheel formula, calculations of oscillatory processes for dynamic parameters determining the loading of the anchor system and the safety of harvester operation in the process of assortment manipulation were carried out.

A-Star (A*) with Map Processing for the Global Path Planning of Autonomous Underwater and Surface Vehicles Operating in Large Areas

The global path planning system is one of the basic systems ensuring the autonomous operation of unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs) in a complex aquatic environment. The A* path planning algorithm is one of the most well-known algorithms used to obtain an almost optimal path, avoiding obstacles even in a complex environment containing objects with specific shapes and non-uniform arrangements. The main disadvantage of this algorithm is the computational cost of path calculation. This article presents a new approach based on the image processing of the map before determining the path using A*. The results of numerical research based on a large-sized map expressing the port area confirm the proposed method’s effectiveness, which reduces the calculation time by over 500 times with a slight increase in the path length compared to the basic version of the A* algorithm. Based on the obtained results, the proposed approach also increases the path’s safety by designating narrow and risky areas as closed to vehicle movement. For this reason, the method seems suitable for use in global path planning for autonomous underwater vehicles (AUVs) and autonomous surface vehicles (ASVs) operating in large areas.

SPA-GPT: General Pulse Tailor for Simple Power Analysis Based on Reinforcement Learning

In side-channel analysis of public-key algorithms, we usually classify operations based on the differences in power traces produced by different basic operations (such as modular square or modular multiplication) to recover secret information like private keys. The more accurate the segmentation of power traces, the higher the efficiency of their classification. There exist two commonly used methods: one is equidistant segmentation, which requires a fixed number of basic operations and similar trace lengths for each type of operation, leading to limited application scenarios; the other is peak-based segmentation, which relies on personal experience to configure parameters, resulting in insufficient flexibility and poor universality. In this paper, we propose an automated trace segmentation method based on reinforcement learning applicable to a wide range of common implementation of public-key algorithms. The introduction of reinforcement learning, which doesn’t need labels, into trace processing for side-channel analysis marks its debut in this field. Our method has good universality on the traces with varying segment lengths and differing peak heights. By using prioritized experience replay optimized Deep Q-Network algorithm, we reduce the required number of parameters to one, which is the key length. We also employ various techniques to improve the segmentation effectiveness, such as clustering algorithm and enveloped-based feature enhancement. We validate the effectiveness of the new method in nine scenarios involving hardware and software implementations of different public-key algorithms executed on diverse platforms such as microcontrollers, SAKURA-G, and smart cards. Specifically, one of these implementations is protected by time randomization countermeasures. Experimental results show that a basic version of our method can correctly segment most traces. The enhanced version is capable of reconstructing the sequence of operations during trace segmentation, achieving an accuracy rate of 100% for the majority of the traces. For traces that cannot be entirely restored, we utilize reward values of reinforcement learning to correct errors and achieve fully recovery. We also conducted comparative experiments with supervised seq2seq methods, revealing our approach’s 42% higher accuracy in operation recovery and 96% faster time efficiency. In addition, we applied our method to the post-quantum cryptography Kyber, and successfully recovered an intermediate value crucial for deriving the secret key. Besides, power traces collected from these devices have been uploaded as open databases, which are available for researchers engaged in public-key algorithms to conduct related experiments or verify our method.

Formulation of Energy Bars by using Sunflower Seeds

The study discusses the popularity and nutritional benefits of snack foods, with a focus on granola bars as a versatile and nutrient-dense option. The importance of energy bars for athletes and individuals with busy lifestyles is highlighted. The study aims to develop a high-protein, high-energy nutritional bar using plant sources. Oats are emphasized for their rich nutrient profile, including carbohydrates, fiber, proteins and various bioactive compounds. Dates and almonds contribute additional nutrients and health benefits. Sunflower seeds are recognized for their therapeutic benefits, while honey is for its antibacterial and nutritional properties. The energy bars, including a basic version and two variations, were analyzed for various nutritional parameters. The moisture content exhibited slight increments, measuring from 6.83±0.01, to 7.03±0.01, while the ash content showed minimal differences at 0.05±0.01. Energy content increased from 380±0.032 to 410±0.026, and protein content ranged from 9.17±0.01 to 9.19±0.01. Fat composition showed marginal variations while the fiber content was measured at 6.67±0.01, 6.77±0.01 and 6.78±0.01 grams. Ascorbic acid concentrations increased from 0.7±0.015 to 0.81±0.0026, while thiamine and riboflavin concentrations showed slight fluctuations. Sensory evaluation revealed that T2 (30% honey) scored highest in various categories, including color (8.5±0.527), taste (8.6±0.516), texture (8.2±0.788), flavor (8.5±0.707), appearance (8.5±0.527) and overall acceptability (8.6±0.516). T2 emerged as the most preferred, followed by T1 (25% honey) and T3 (35% honey).

Effect of aerobic exercise program on neuropathic pain and quality of life in person with paraplegia: study protocol for a randomized controlled trial

BackgroundIndividuals with spinal cord injury (SCI) often suffer from neuropathic pain which is often disabling and negatively affects function, participation, and quality of life (QoL). Pharmacological treatments lack efficacy in neuropathic pain reduction hence studying alternatives to drug treatment is necessary. Preclinical evidence of various aerobic exercises has shown positive effects on neuropathic pain but scientific studies investigating its effect in the SCI human population are limited.MethodologyThis study is a double-blind, parallel, two-group, randomized controlled trial with an interventional study design that aims to evaluate the effectiveness of aerobic exercise program on neuropathic pain and quality of life (QoL) in individuals with chronic paraplegia. Thirty individuals with chronic paraplegia with the neurological level of injury from T2 to L2 will be recruited from the rehabilitation department at a super specialty hospital based on the inclusion criteria. Using a 1:1 allocation ratio, the participants will be randomly assigned to one of the two groups. The intervention group will perform high-intensity interval training (HIIT) aerobic exercise using an arm ergometer based on their peak heart rate, and the control group will perform free-hand arm aerobic exercise. In both groups, the intervention will be delivered as 30-min sessions, four times a week for 6 weeks.Outcome measuresInternational Spinal Cord Injury Pain Basic Data Set Version 3.0 will be used for diagnosing and assessing neuropathic pain and its interference with day-to-day activities, mood, and sleep. The International Spinal Cord Society (ISCoS) QoL basic data set will be used to assess QoL, and 6-min push test distance will be used to assess peak heart rate and aerobic capacity.DiscussionThe effectiveness of the aerobic exercise program will be assessed based on the changes in neuropathic pain score and its interference with day-to-day activities, mood, sleep, QoL, and aerobic capacity after 3 weeks mid-intervention and after 6 weeks post-intervention. The trial will provide new knowledge about the effectiveness of the aerobic exercise program in improving neuropathic pain and QoL in individuals with chronic paraplegia.Trial registrationClinical Trials Registry-India CTRI/2023/08/056257. Registered on 8 August 2023.

A global argument-based algorithm for finding complex zeros and poles to investigate plasma kinetic instabilities

Root-finding is a common problem in various fields of physics and mathematics. The basic version of this problem can be formulated as an equation f(z)=0 where z∈ℂ and f is a meromorphic function on a complex plane ℂ. In some cases, a conjugated problem has to be solved as well to investigate the properties of the inspected system: f(z)−1=0. Iterative Householder-like methods show high convergence rate, however, the convergence itself is strongly dependent on the input parameters such as an initial guess. If the function f is complicated enough, there can be no prior information about its zeros and poles, and thus, no way to correctly pick the initial guess. The aim of the algorithm proposed in this article is to find all zeros and poles inside a selected region without any information about the local behavior of the function f. Additionally, the method is generalized to a parametric problem with continuous solutions: f(z)→f(z;p) where p∈Rd, d∈N∪{0}. The basis of the algorithm consists of a triangulation process and an implementation of the Cauchy’s argument principle to inspect the constructed subregions. The refinement process is accompanied by an absolute value gradient ∇ln|f| analysis that significantly decreases the number of points needed to correctly identify the locations of all zeros and poles. The algorithm is presented as a hybrid class for d∈{0,1} that can be directly used to solve corresponding problems.

Analysis of asymmetric VR games – Steam platform case study

The paper presents research on the topic of asymmetric virtual reality (VR) games. These types of applications are in the development phase when it comes to their presence on the market, range, amount, and popularity. This research discusses the original topic, as it is still a niche compared to video games and even to VR applications on the market. The article presents a quantitative analysis of asymmetric VR applications available in the international market. One of the popular gaming platforms, Steam, was chosen as a subject for the case study in this investigation. The objectives of the conducted research include, first, a quantitative analysis and presentation of up-to-date data on asymmetric VR games available on Steam; then, providing and systematizing new knowledge about the asymmetric VR term, identifying the nature of asymmetric VR games, and finally, recognition of the current situation and the latest trends within the concept of asymmetric VR. Based on the results, it was concluded that the dominating genre of asymmetric VR was action (49.4 %), indie (46.0 %) and casual (45.4 %), followed by simulation (37.4 %). Most of the games were available in English (96.6 %), and far behind English, there were French and German languages (30.5 %), and then Spanish – Spain (28.2 %), Russian (27 %), Japanese (25.9 %), simplified Chinese (25.3 %) and others. The analysis of user re-views on Steam that asymmetric VR receive favorable feedback, with ‘very positive’ as the most prevalent label, representing 35.0 % of analyzed games. Notably, only four games achieved the ‘overwhelmingly positive’ label, including ‘Keep Talking and Nobody Explodes’ in the basic version and in the version with soundtrack (97 % positive reviews), ‘Rock Life: The Rock Simulator’ (95 % positive reviews), and ‘IronWolf VR’ (95 % positive reviews). Last but not least, the paper describes the features of the analyzed asymmetric VR application. The results of the research make a contribution to the field and provide new knowledge on the following: the new subarea of VR, the nature of asymmetric VR (author's concept), human behavior and interaction in asymmetric virtual gameplay, and communication in asymmetric VR.

Analysis of the possibility of increasing the level of reliability of fire alarms systems through integration with video-based flame detection system

Classic Fire Alarm Systems (FAS) are characterized by a high level of false alarms in relation to the number of confirmed reports. To increase the level of reliability of operation of this type of system, it was proposed to integrate it with a Video-Based Flame Detection System (VBFDS). For this purpose, a video-based fire detection algorithm was designed. In addition, methods popular in the literature for increasing the reliability of such systems, such as color filtering, the Tracking Growth Object (TGO) factor, and the use of the Naive-Bayes (NB) classifier, were tested. The purpose of the article is to analyze these methods in comparison with the basic version of the algorithm, as well as the possibility of integrating Video-Based Flame Detection System (VBFDS) with classic FAS.

Adaptive crossover-based marine predators algorithm for global optimization problems

Abstract The Marine Predators Algorithm (MPA) is a swarm intelligence algorithm developed based on the foraging behavior of the ocean’s predators. This algorithm has drawbacks including, insufficient population diversity, leading to trapping in local optima and poor convergence. To mitigate these drawbacks, this paper introduces an enhanced MPA based on Adaptive Sampling with Maximin Distance Criterion (AM) and the horizontal and vertical crossover operators – i.e., Adaptive Crossover-based MPA (AC-MPA). The AM approach is used to generate diverse and well-distributed candidate solutions. Whereas the horizontal and vertical crossover operators maintain the population diversity during the search process. The performance of AC-MPA was tested using 51 benchmark functions from CEC2017, CEC2020, and CEC2022, with varying degrees of dimensionality, and the findings are compared with those of its basic version, variants, and numerous well-established metaheuristics. Additionally, 11 engineering optimization problems were utilized to verify the capabilities of the AC-MPA in handling real-world optimization problems. The findings clearly show that AC-MPA performs well in terms of its solution accuracy, convergence, and robustness. Furthermore, the proposed algorithm demonstrates considerable advantages in solving engineering problems, proving its effectiveness and adaptability.

The effect of Baduanjin exercise on cognitive function in elderly people: A systematic review based on near-infrared spectroscopy technology

To systematically evaluate the application of near-infrared spectroscopy technology in the study of the effect of Baduanjin exercise on cognitive function in elderly people. Relevant literature was retrieved from PubMed, Web of Science core database, ScienceDirect, Wanfang, VIP, and CNKI from 2014 to June 2023, and relevant data were extracted. A total of 1 valid literature was obtained, published in 2022, sourced from the medical journal FRONTIERS IN PUBLIC HEALTH, with an impact factor of 6.46. This journal belongs to JCR Q1 area, and the SCI basic version of the Chinese Academy of Sciences is in the Q3 area of medicine. The inclusion criteria for the subjects of this study were age 60 years, experience of Baduanjin exercise for 3 years, and MMSE score 24 points. This study, based on functional near-infrared spectroscopy technology, explores the effects of Baduanjin imagery and Baduanjin exercise on cognitive function in elderly people. Baduanjin exercise can increase brain connectivity, improve brain structural connections, and enhance brain function in elderly people. These three factors are also the main reasons for Baduanjin exercise to promote the improvement of cognitive function, including increasing brain gray matter volume, brain functional area connections, etc. Baduanjin exercise can improve specific cognitive functions by increasing gray matter volume. Baduanjin exercise can regulate the functional connections of the cognitive control network in elderly people and improve their memory.

Holographic origin of TCC and the distance conjecture

One of the unique features of quantum gravity is the lack of local observables and the completeness of boundary observables. We show that the existence of boundary observables for particles with masses limt−∞mH=∞\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\underset{t-\\infty }{\\lim}\\frac{m}{H}=\\infty $$\\end{document} in scalar fieldcosmologies where a(t) ∼ tp is equivalent to TCC, which implies p ≤ 1. Moreover, the mass of weakly-coupled particles must decay like m ≲ t1 − 2p to ensure that they yield non-trivial boundary observables. This condition can be expressed in terms of the scalar field that drives the cosmology as m ≲ exp(−cϕ) where c depends on the scalar potential. The strongest bound we find is achieved for V~exp−2ϕ/d−2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ V\\sim \\exp \\left(-2\\phi /\\sqrt{d-2}\\right) $$\\end{document} where c=1/d−2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ c=1/\\sqrt{d-2} $$\\end{document}. These results connect some of the most phenomenologically interesting Swampland conjectures to the most basic version of holography.

Generating Euler Diagrams Through Combinatorial Optimization

AbstractCan a given set system be drawn as an Euler diagram? We present the first method that correctly decides this question for arbitrary set systems if the Euler diagram is required to represent each set with a single connected region. If the answer is yes, our method constructs an Euler diagram. If the answer is no, our method yields an Euler diagram for a simplified version of the set system, where a minimum number of set elements have been removed. Further, we integrate known wellformedness criteria for Euler diagrams as additional optimization objectives into our method. Our focus lies on the computation of a planar graph that is embedded in the plane to serve as the dual graph of the Euler diagram. Since even a basic version of this problem is known to be NP‐hard, we choose an approach based on integer linear programming (ILP), which allows us to compute optimal solutions with existing mathematical solvers. For this, we draw upon previous research on computing planar supports of hypergraphs and adapt existing ILP building blocks for contiguity‐constrained spatial unit allocation and the maximum planar subgraph problem. To generate Euler diagrams for large set systems, for which the proposed simplification through element removal becomes indispensable, we also present an efficient heuristic. We report on experiments with data from MovieDB and Twitter. Over all examples, including 850 non‐trivial instances, our exact optimization method failed only for one set system to find a solution without removing a set element. However, with the removal of only a few set elements, the Euler diagrams can be substantially improved with respect to our wellformedness criteria.

Modeling and Analysis of Dekker-Based Mutual Exclusion Algorithms

Mutual exclusion is a fundamental problem in concurrent/parallel/distributed systems. The first pure-software solution to this problem for two processes, which is not based on hardware instructions like test-and-set, was proposed in 1965 by Th.J. Dekker and communicated by E.W. Dijkstra. The correctness of this algorithm has generally been studied under the strong memory model, where the read and write operations on a memory cell are atomic or indivisible. In recent years, some variants of the algorithm have been proposed to make it RW-safe when using the weak memory model, which makes it possible, e.g., for multiple read operations to occur simultaneously to a write operation on the same variable, with the read operations returning (flickering) a non-deterministic value. This paper proposes a novel approach to formal modeling and reasoning on a mutual exclusion algorithm using Timed Automata and the Uppaal tool, and it applies this approach through exhaustive model checking to conduct a thorough analysis of the Dekker’s algorithm and some of its variants proposed in the literature. This paper aims to demonstrate that model checking, although necessarily limited in the scalability of the number N of the processes due to the state explosions problem, is effective yet powerful for reasoning on concurrency and process action interleaving, and it can provide significant results about the correctness and robustness of the basic version and variants of the Dekker’s algorithm under both the strong and weak memory models. In addition, the properties of these algorithms are also carefully studied in the context of a tournament-based binary tree for N≥2 processes.