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arXiv 2025年

作者： Hanks, Tyler Riess, Hans Cohen, Samuel Gross, Trevor Hale, Matthew Fairbanks, James Department of Computer and Information Science and Engineering United States Department of Mechanical and Aerospace Engineering University of Florida United States Deparment of Electrical and Computer Engineering Georgia Institute of Technology United States

Techniques for coordination of multi-agent systems are vast and varied, often utilizing purpose-built solvers or controllers with tight coupling to the types of systems involved or the coordination goal. In this paper, we introduce a general unified framework for heterogeneous multi-agent coordination using the language of cellular sheaves and nonlinear sheaf Laplacians, which are generalizations of graphs and graph Laplacians. Specifically, we introduce the concept of a nonlinear homological program encompassing a choice of cellular sheaf on an undirected graph, nonlinear edge potential functions, and constrained convex node objectives, which constitutes a standard form for a wide class of coordination problems. We use the alternating direction method of multipliers to derive a distributed optimization algorithm for solving these nonlinear homological programs. To demonstrate the applicability of this framework, we show how heterogeneous coordination goals including combinations of consensus, formation, and flocking can be formulated as nonlinear homological programs and provide numerical simulations showing the efficacy of our distributed solution *** Codes 93A16, 93B45, 55N30 © 2025, CC BY.

关键词： Laplace transforms

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Combination of AHP and TOPSIS methods for the ranking of information security controls to overcome its obstructions under fuzzy environment

Combination of AHP and TOPSIS methods for the ranking of inf...

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作者： Tariq, Muhammad Imran Tayyaba, Shahzadi Ali Mian, Natash Sarfraz, Muhammad Shahzad De-La-Hoz-Franco, Emiro Butt, Shariq Aziz Santarcangelo, Vito Rad, Dana V. Department of Computer Science Superior University Lahore Pakistan Deparment of Computer Engineering University of Lahore Lahore Pakistan School of Computer and Information Technology Beaconhouse National University Lahore Pakistan Department of Computer Science National University of Computer and Emerging Sciences Chiniot-Faisalabad Campus Islamabad Pakistan Universidad de la Costa CUC Colombia IInformatica S.r.l.s. - Corso Italia 77 Trapani Italy Aurel Vlaicu University of Arad Romania

The organizations utilizing the cloud computing services are required to select suitable information Security Controls (ISCs) to maintain data security and privacy. Many organizations bought popular products or traditional tools to select ISCs. However, selecting the wrong information security control without keeping in view severity of the risk, budgetary constraints, measures cost, and implementation and mitigation time may lead to leakage of data and resultantly, organizations may lose their user's information, face financial implications, even reputation of the organization may be damaged. Therefore, the organizations should evaluate each control based on certain criteria like implementation time, mitigation time, exploitation time, risk, budgetary constraints, and previous effectiveness of the control under review. In this article, the authors utilized the methodologies of the Multi Criteria Decision Making (MCDM), Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to help the cloud organizations in the prioritization and selection of the best information security control. Furthermore, a numerical example is also given, depicting the step by step utilization of the method in cloud organizations for the prioritization of the information security controls. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Analytic hierarchy process

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Developing SPIM-TA: a maturity-level framework for systematic process improvement in software testing automation

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Ain Shams Engineering Journal 2025年第8期16卷

作者： Muhammad Faisal Abrar Yasser Alharbi Muhammad Alsaffar Shah Hussain Muhammad Saqib Jawad Khan Youngmoon Lee College of Computer Science & Engineering University of Ha’il Ha’il 2440 Saudi Arabia Department of Information and Computer Science University of Ha’il Ha'il 2440 Saudi Arabia Department of Mathematics College of Science University of Ha’il Ha’il 2440 Saudi Arabia Department of Software Engineering University of Engineering & Technology Peshawar 25000 Pakistan School of Computing Gachon University Seongnam 13120 Republic of Korea Deparment of Robotics Hanyang University Ansan 15588 Republic of Korea

The growing complexity and demands for high-quality software underlined the need for robust automated software testing frameworks. However, lack of skilled personnel, cost of testing automation, and maintenance of script along with others oppose the widespread adoption of automation in testing. The work proposed by this study is in line with the development of Systematic Process Improvement Model for Testing Automation, abbreviated as SPIM-TA. The model is inspired from Capability Maturity Model Integration (CMMI) and Software Outsourcing Vendor Readiness Model (SOVRM) maturity-level-based framework. The research was done based on a four-phased methodology. In the first phase, a systematic literature review identified 14 critical challenges in software testing automation with practices or solutions for each of these challenges. In the second round, a survey questionnaire is used to validate these findings in industrial context and extract more practical insights from case studies. This dual approach had ensured both academic rigor and the relevance of the practices with industry. The third one involved developing SPIM-TA by incorporating insights that come from the SLR and those results of the survey as well. The framework defines five maturity levels, systematically addressing the identified challenges and providing a structured pathway for organizations to enhance their automation processes. In the fourth phase, case studies of industrial applications were carried out to evaluate SPIM-TA’s efficiency. The applicability, scalability, and impact of the framework on testing automation in the real world were assessed using the Motorola Assessment Tool. The findings illustrate the systematic way SPIM-TA will help overcome the automation challenge, so that organizations can reach more advanced levels of maturity and efficiency in their testing processes. In the first place, the present study closes the gap between academia and industry but at the same time paves the fou

关键词： Automated Software Testing SPIM-TA framework Systematic Process Improvement

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An analysis of voltage source inverter switches fault classification using short time Fourier transform

arXiv

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arXiv 2021年

作者： Manap, Mustafa Nikolovski, Srete Skamyin, Aleksandr Karim, Rony Sutikno, Tole Jopri, Mohd Hatta Faculty of Electrical & Electronic Engineering Technology Universiti Teknikal Malaysia Melaka Malacca Malaysia Power Engineering Department Faculty of Electrical Engineering Computer Science and Information Technology University of Osijek Osijek31000 Croatia Department of Electric Power and Electromechanics Saint Petersburg Mining University Saint Petersburg Russia GmbH Germany Deparment of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta Indonesia Yogyakarta Indonesia

The dependability of power electronics systems, such as three-phase inverters, is critical in a variety of applications. Different types of failures that occur in an inverter circuit might affect system operation and raise the entire cost of the manufacturing process. As a result, detecting and identifying inverter problems for such devices is critical in industry. This study presents the short-time Fourier transform (STFT) for fault classification and identification in three-phase type, voltage source inverter (VSI) switches. Time-frequency representation (TFR) represents the signal analysis of STFT, which includes total harmonic distortion, instantaneous RMS current, RMS fundamental current, total non harmonic distortion, total waveform distortion and average current. The features of the faults are used with a rule-based classifier based on the signal parameters to categorise and detect the switch faults. The suggested method's performance is evaluated using 60 signals containing short and open circuit faults with varying characteristics for each switch in VSI. The classification results demonstrate the proposed technique is good to be implemented for VSI switches faults classification, with an accuracy classification rate of 98.3%. © 2021, CC BY.

关键词： Signal analysis

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Deep learning for football outcomes prediction based on football rating system

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AIP Conference Proceedings 2022年第1期2644卷

作者： Nazim Razali Aida Mustapha Nureize Arbaiy Pei-Chun Lin 1Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Malaysia 2Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia 84600 Pagoh Johor Malaysia 3Deparment of Information Engineering and Computer Science Feng Chia University No. 100 Wenhwa Rd Taichung Taiwan

The prediction models of association football can be categorized into three natural clusters, which are the statistical models, the machine learning and probabilistic graphical models and rating systems. The prediction may focus on matches outcomes prediction (win, draw and lose) or the number of goals scored obtained by home and away team. Match result prediction is very important as a benchmark for the management team to assess the chances of winning, drawing and losing for a particular team before the match starts. In the 2017 soccer challenge, the conventional machine learning and ensemble methods, as well as probabilistic graphical models such as k-Nearest Neighbor (k-NN), Gradient Boosting Tree (GBT) and Bayesian Networks (BN) have been a choice of researchers that participate the challenge and successfully dominate the challenge. Even so, there are some well-known techniques such as Neural Networks (NN) and Deep Neural Networks (DNN) that are left in this challenge although this technique has advantages in producing good results in many fields including solving real world problems which the results are comparable and sometimes superior to expert knowledge in some cases. In this paper, we propose a football match outcome prediction based on pi-rating system using TabNet, a DNN architecture for tabular data. The experiment cover two parts namely: (1) generates pi-rating system from 216,743 instances of raw football dataset and (2) predicts 206 football match outcomes using TabNet. As a result, the proposed prediction model based on the pi-rating system using TabNet successfully overcomes the existing model for football match outcomes for both scoring rules, in terms of accuracy and Rank Probability Score (RPS). The findings from this study are important because they can be used for future researchers in developing new football match outcome prediction models that incorporate several new features along with other features. This is important to improve the predic

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Modelling smart energy consumption with hybrid demand management in off-grid electrical system considering techno-economic indices

Science and Technology for Energy Transition (STET)

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science and technology for Energy Transition (STET) 2024年第1期79卷

作者： Rui-Ming, Fang Liao, Qiangqiang Askar, Shavan Pallathadka, Harikumar Sapaev, I.B. Baldaniya, Lalji Chahar, Mamata Saini, Suman Kapila, Ish Jewahery, Hassan Farhan, Mohsen Aued Mohmmedi, M. Information Systems Engineering Department Erbil Technical Engineering College Erbil Polytechnic University Erbil Iraq Manipur International University Manipur Imphal India Department Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Institute National Research University Tashkent Uzbekistan Scientific Researcher University of Tashkent for Applied Sciences Str. Gavhar 1 Tashkent100149 Uzbekistan Scientific Researcher Western Caspian University Baku Azerbaijan Marwadi University Research Centre Department of Pharmacy Faculty of Health Science Marwadi University Gujarat Rajkot360003 India Deparment of Chemistry NIMS Institute of Engineering & Technology NIMS University Rajasthan Jaipur India Department of Applied Sciences Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab Jhanjeri140307 India Centre for Research Imapct & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Computer Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Babylon Babylon Iraq Department of Management Al-Nisour University College Nisour Seq. Karkh Baghdad Iraq Department of Electrical Engineering Islamic Azad University Branch of Central Tehran Tehran Iran

This study proposes day-ahead power scheduling for electrical systems in off-grid mode, emphasizing consumer involvement. Bi-Demand Side Management (DSM) approaches like strategic conversion and demand shifting are proposed for consumer involvement. Multiple objectives are modelled to voltage profile improvement and reduce the operation energy cost. The non-dominated solutions of the voltage of buses and operation energy cost are generated by enhanced epsilon-constraint technique, simultaneously. The General Algebraic Modeling System (GAMS) software is proposed for solving optimization problems. A combination of decision-making methods like weight sum and fuzzy procedures are implemented for finding optimal solution non-dominated solutions. The proposed method's effectiveness is confirmed through numerical simulations carried out on several case studies that utilize the 33-bus electrical system. The findings illustrate the substantial effectiveness of demand-side participation in improving power dispatch and the optimal rate of multiple objectives. By using DSM, operation cost is reduced by 21.58% and the voltage index is improved by 13.36% than the lack of implementing DSM. © The Author(s), published by EDP sciences, 2024.

关键词： Demand response

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Optimal Thermometers with Spin Networks

arXiv

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arXiv 2022年

作者： Abiuso, Paolo Erdman, Paolo Andrea Ronen, Michael Noé, Frank Haack, Géraldine Perarnau-Llobet, Martí ICFO – Institut de Ciències Fotoǹiques The Barcelona Institute of Science and Technology Castelldefels Barcelona08860 Spain Department of Applied Physics University of Geneva Geneva1211 Switzerland Institute for Quantum Optics and Quantum Information - IQOQI Vienna Austrian Academy of Sciences Boltzmanngasse 3 ViennaA-1090 Austria Freie Universität Berlin Department of Mathematics and Computer Science Arnimallee 6 Berlin14195 Germany Deparment of Physics University of Konstanz KonstanzD-78457 Germany Microsoft Research AI4Science Karl-Liebknecht Str. 32 Berlin10178 Germany Freie Universität Berlin Department of Physics Arnimallee 6 Berlin14195 Germany Rice University Department of Chemistry HoustonTX77005 United States

The heat capacity C of a given probe is a fundamental quantity that determines, among other properties, the maximum precision in temperature estimation. In turn, C is limited by a quadratic scaling with the number of constituents of the probe, which provides a fundamental limit in quantum thermometry. Achieving this fundamental bound with realistic probes, i.e. experimentally amenable, remains an open problem. In this work, we tackle the problem of engineering optimal thermometers by using networks of spins. Restricting ourselves to two-body interactions, we derive general properties of the optimal configurations and exploit machine-learning techniques to find the optimal couplings. This leads to simple architectures, which we show analytically to approximate the theoretical maximal value of C and maintain the optimal scaling for short- and long-range interactions. Our models can be encoded in currently available quantum annealers, and find application in other tasks requiring Hamiltonian engineering, ranging from quantum heat engines to adiabatic Grover’s search. Copyright © 2022, The Authors. All rights reserved.

关键词： Probes

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Detection and Classification of Breast Cancer Using improved Grey Wolf Algorithm

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IOP Conference Series: Materials science and Engineering 2021年第1期1084卷

作者： T Senthil J Deepika R. Nithya Assistant Professor Deparment of Electronics and Communication Engineering EngineeringBannari Amman institute of TechnologySathyamangalam ErodeTamilnadu India Assistant professor.Department of Information Technology Engineering Bannari Amman institute of TechnologySathyamangalam ErodeTamilnadu India Assistant professor.Department of Computer Science Engineering Engineering Bannari Amman institute of TechnologySathyamangala ErodeTamilnadu India

Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in significantly less number, there's motivation to expand a mechanized forecast machine for early expectation and visualization of malignancy. The sort of considerate and threatening tumor are accomplished the use of type methodologies of device becoming acquainted with wherein the device is found from the past records and predicts the sorts of late sources of info. This paper is an overall report on the execution of models utilizing Logistic Regression, Support Vector Machine (SVM) and Gray wolf algorithm(GWO). The outcomes are assessed with the exactness, accuracy, affectability, explicitness and False Positive Rate boundaries for every calculation and are thought about. These procedures are coded in Java and executed in MATLAB, the Image handling Environment. Our investigations have demonstrated that Gray wolf is the best for prescient examination with an exactness of 92.7%.We surmise from our test results that SVM is the appropriate calculation for expectation and in general Gray wolf has performed well close to SVM.

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Convolutional neural network for motorbike detection in dense traffic 6

Convolutional neural network for motorbike detection in dens...

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6th IEEE International Conference on Communications and Electronics, IEEE ICCE 2016

作者： Huynh, Chi-Kien Le, Thanh-Sach Hamamoto, Kazuhiko Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam Deparment of Information Media Technology School of Information and Telecommuncation Engineering Tokai University Japan

ISBN: (纸本)9781509019311

Motorbike detection is not a novel problem. However, as it is not a common vehicle in most countries in the world, there is barely enough research on vision-based methods for motorbike detection, even more so for motorbike detection in dense clusters. In this work, we proposed a detection method that is able to overcome fair occlusions in traffic images. The method is centered around a robust model: The convolutional neural network (CNN) with multiple layers. The CNN model has been proven to achieve state-of-The-Art results in multiple vision tasks. Although having a straightforward mechanic, the CNN we constructed is able to achieve positive and stable results throughout a difficult test dataset for motorbike detection. © 2016 IEEE.

关键词： Statistical tests

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Towards multi-functional light-weight long-term real-time coastal ocean observation system 11

Towards multi-functional light-weight long-term real-time co...

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11th ACM International Conference on Underwater Networks and Systems, WUWNet 2016

作者： Jiang, Zhenfeng Ma, Yanming Chen, Jiali Wang, Zigeng Peng, Zheng Liu, Jun Han, Guitao Smart Ocean Industry Research Institute Nantong Jiangsu226000 China Computer Science and Engineering Department University of Connecticut StorrsCT06269 United States Computer Science Deparment City College of New York NY10031 United States Computer Science and Technology Department Jilin University Changchun Jilin130012 China State Key Laboratory of Robotics Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

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