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arXiv 2024年

作者： Chvátal, Vašek de Rancourt, Noé Quintero, Guillermo Gamboa Kantor, ida Szabó, Péter G.N. Department of Computer Science and Software Engineering Concordia University Montreal Canada Department of Applied Mathematics Charles University Prague Czech Republic Univ. Lille CNRS UMR 8524 Laboratoire Paul Painlevé LilleF-59000 France Computer Science Institute of Charles University Prague Czech Republic Department of Engineering Mathematics Faculty of Engineering and Information Technology University of Pécs Pécs Hungary Department of Computer Science and Information Theory Budapest University of Technology and Economics Hungary

Richmond and Richmond (American Mathematical Monthly 104 (1997), 713–719) proved the following theorem: if, in a metric space with at least five points, all triangles are degenerate, then the space is isometric to a subset of the real line. We prove that the hypothesis is unnecessarily strong: in a metric space on n points, fewer than 7n2/6 suitably placed degenerate triangles suffice. However, fewer than n(n − 1)/2 degenerate triangles, no matter how cleverly placed, never *** Codes 30L99, 51F99, 54E99 © 2024, CC BY.

关键词： Topology

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Enhancing ioT-Based Smart Farming Security with a Hybrid GRU intrusion Detection System

Enhancing IoT-Based Smart Farming Security with a Hybrid GRU...

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interdisciplinary Approaches in Technology and Management for Social innovation (iATMSi), iEEE Conference on

作者： Sivakumar Nagarajan S. Vijay S. Karthi RVS Praveen Ramesh Vijaya Babu K Burri Naresh Technical Architect I & I Software Inc Bethlehem USA Department of Data Science Sacred Heart College (Autonomous) Tamilnadu India Department of Computer Science and Engineering V.S.B. Engineering College Karur Tamilnadu India Director Digital Engineering & Assurance LTIMindtree Limited Hyderabad Telangana India SRKR Engineering College Bhimavaram Andhra Pradesh India Department of CSE - Cyber Security CVR College of Engineering Hyderabad Telangana India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The growing use of ioT devices in smart agriculture makes the industry vulnerable to several cyber risks. This study introduces an innovative hybrid intrusion Detection System (iDS) utilising Gated Recurrent Units (GRUs) to improve the security of ioT-enabled smart agriculture. compared to current LSTM and CNN-based intrusion detection systems, the proposed model effectively incorporates sequential data dependencies, hence minimising false positives and enhancing detection accuracy. Experimental findings indicate that the suggested model surpasses conventional techniques, with an accuracy of 97.5%, an F1 score of 0.96, and a recall of 0.97. These developments create a strong, efficient, and scalable solution for safeguarding ioT-based agricultural systems from cyber-attacks.

关键词： Smart agriculture Technological innovation Accuracy Computational modeling Scalability intrusion detection internet of Things Object recognition Protection Long short term memory

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Design of a Lower Limb Exoskeleton Rehabilitation Robot System Based on Forward Dynamics Simulation

Design of a Lower Limb Exoskeleton Rehabilitation Robot Syst...

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Cognitive Computing and Complex Data (iCCD), international Conference on the

作者： Yudong Fang Yuefei Wang Liucun Zhu Zhen Liu Lei Shi Muxin Du Jianchu Lin School of Mechanical and Marine Engineering Beibu Gulf University Qinzhou China Sentinel Institute of Science and Technology Beibu Gulf University Qinzhou China Nagasaki Institute of Applied Science Nagasaki Japan Guangzhou Shiyuan Electronic Technology Company Limited Guangzhou China Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai'an China

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

Lower limb exoskeleton rehabilitation robots can effectively improve the rehabilitation of stroke patients and can substantially reduce the workload of rehabilitation therapists and improve work efficiency. in this paper, we propose a method to investigate the influence of muscle groups on the hip joint during the gait cycle through kinetic modeling simulation. The method is validated using electromyographic signals (EMG). The patients are treated according to their gait characteristics. Simulation with OpenSim; optimisation by Scone controller; joint motion change curves were analysed by Matlab simulation to verify the correctness of the mathematical model, and the simulation showed excellent following effect. The feasibility of the theory is verified, and a new scheme is proposed for the treatment of stroke patients.

关键词： Limbs Exoskeletons Stroke (medical condition) Muscles Assistive robots Mathematical models Kinetic theory MATLAB Robots Optimization

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A New Multi-Agent Feature Wrapper Machine Learning Approach for Heart Disease Diagnosis

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computers, Materials & Continua 2021年第4期67卷 51-71页

作者： Mohamed Elhoseny Mazin Abed Mohammed Salama A.Mostafa Karrar Hameed Abdulkareem Mashael S.Maashi Begonya Garcia-Zapirain Ammar Awad Mutlag Marwah Suliman Maashi Department of Computer Science College of Computer Information TechnologyAmerican University in the Emirates503000United Arab Emirates College of Computer Science and Information Technology University of AnbarRamadi31001Iraq Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia College of Agriculture Al-Muthanna UniversitySamawah66001Iraq Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia eVIDA Lab University of DeustoBilbao48007Spain Department of Pure Science Ministry of EducationGeneral Directorate of CurriculaBaghdadIraq Department of Medical Laboratory Science Faculty of Applied Medical ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia

Heart disease(HD)is a serious widespread life-threatening *** heart of patients with HD fails to pump sufcient amounts of blood to the entire *** the occurrence of HD early and efciently may prevent the manifestation of the debilitating effects of this disease and aid in its effective *** methods for diagnosing HD are sometimes unreliable and insufcient in analyzing the related *** an alternative,noninvasive medical procedures based on machine learning(ML)methods provide reliable HD diagnosis and efcient prediction of HD ***,the existing models of automated ML-based HD diagnostic methods cannot satisfy clinical evaluation criteria because of their inability to recognize anomalies in extracted symptoms represented as classication features from patients with *** this study,we propose an automated heart disease diagnosis(AHDD)system that integrates a binary convolutional neural network(CNN)with a new multi-agent feature wrapper(MAFW)*** MAFW model consists of four software agents that operate a genetic algorithm(GA),a support vector machine(SVM),and Naïve Bayes(NB).The agents instruct the GA to perform a global search on HD features and adjust the weights of SVM and BN during initial classication.A nal tuning to CNN is then performed to ensure that the best set of features are included in HD *** CNN consists of ve layers that categorize patients as healthy or with HD according to the analysis of optimized HD *** evaluate the classication performance of the proposed AHDD system via 12 common ML techniques and conventional CNN models by using across-validation technique and by assessing six evaluation *** AHDD system achieves the highest accuracy of 90.1%,whereas the other ML and conventional CNN models attain only 72.3%–83.8%accuracy on ***,the AHDD system proposed herein has the highest capability to identify patients with *** system can be used by medical

关键词： Heart disease machine learning multi-agent feature wrapper model heart disease diagnosis HD cleveland datasets convolutional neural network

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A Fuzzy Logic-Based Computational Framework for Precision Triage in Androgenetic Alopecia: A Simulated Biomarker-Driven Approach

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international Journal of Computational intelligence Systems 2025年第1期18卷 1-30页

作者： Al-Samarraay, Mohammed S. Magableh, Aws A. Mahmood, Rana i. Joudar, Shahad Sabbar Zahid, idrees A. Al-Obaidi, Jameel R. Al-Saffar, Ali Z. Albahri, A. S. Albahri, O. S. Alamoodi, A. H. Abdullah, Mohd Faizal Nizam Lee Electrical and Electronic Engineering Department College of Engineering Gulf University Sanad Bahrain Faculty of Information Technology and Computer Sciences Department of Information Systems Yarmouk University Irbid Jordan Department of Software Engineering Prince Sultan University Riyadh Saudi Arabia Department of Biomedical Engineering College of Engineering Al-Nahrain University Jadriya Baghdad Iraq University of Technology Baghdad Iraq Department of Biology Faculty of Science and Mathematics Universiti Pendidikan Sultan Idris Tanjong Malim Malaysia Applied Science Research Center Applied Science Private University Amman Jordan Department of Molecular and Medical Biotechnology College of Biotechnology Al-Nahrain University Baghdad Iraq Technical Engineering College Imam Ja’afar Al-Sadiq Baghdad Iraq University of Information Technology and Communications (UOITC) Baghdad Iraq Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq Victorian Institute of Technology Melbourne Australia GUST Engineering and Applied Innovation Research Center (GEAR) Gulf University for Science and Technology Mishref Kuwait Department of Mathematics Faculty of Science and Mathematics Universiti Pendidikan Sultan Idris Tanjong Malim Malaysia

Androgenetic alopecia (AGA) is a common cause of hair loss affecting both men and women. Although its precise etiology remains uncertain, genetic and hormonal factors are recognized as major contributors. This study introduces a computational intelligence framework employing fuzzy logic and multi-criteria decision-making (MCDM) to simulate a robust triage system for AGA management. Using a simulated dataset of 100 AGA patients, we applied the fuzzy-weighted zero-inconsistency (FWZiC) method to assign weights to 11 bioactive criteria associated with AGA. These weights informed a novel triage procedure for alopecia patients (TPAP), which stratified patients into seven severity levels (level 1: minor; level 7: severe). This study presents a computationally intelligent triage model tailored for AGA, emphasizing the applicability of fuzzy MCDM techniques in medical decision support. The TPAP framework can assist in resource allocation and treatment planning, paving the way for personalized and timely interventions in hair loss management.

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Overview of Hormonal Substances Used in Fish Reproduction 10

Overview of Hormonal Substances Used in Fish Reproduction

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10th E-Health and Bioengineering Conference, EHB 2022

作者： Nica, Aurelia Simionov, ira-Adeline Antache, Alina Cristea, Dragos-Sebastian Petrea, Stefan-Mihai Cristea, Victor Food Science Food Engineering Biotechnology and Aquaculture Department Food Science and Engineering Faculty „Dunărea de Jos" University of Galati Domnească Street no. 47 Galați800008 Romania Faculty of Automation Computer Sciences Electronics and Electrical Engineering "Dunarea de Jos" University of Galati 111 Domneascǎ Street Galaţi800201 Romania Faculty of Economics and Business Administration "Dunarea de Jos" University of Galati 47 Domneascǎ Street Galaţi800201 Romania Applied Science Department Transboarding Faculty "Dunărea de Jos" University of Galaţi Galați800008 Romania

ISBN: (纸本)9781665485579

The process of fish breeding is extensively applied in fish farms and it is influenced by either environmental factors (in case of natural reproduction) and by the use of exogenous hormones (in case of artificial reproduction). Reproducing some species under controlled conditions without hormonal preparations is not possible. Many hormonal agents have been previously described in the scientific literature as beneficial in the fish breeding process. The effectiveness of these agents varies. This paper reviews some of the basic hormonal substances and describes the results of artificial reproduction. The most frequently encountered substances that give the best results are: Carp pituitary homogenate (CPH), Ovopel and Ovaprim. it can be concluded that in order to ensure the success of reproduction, the doses applied are particularly important, as well as the way of administration of the agent. © 2022 iEEE.

关键词： Fish

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Understanding the use of message passing interface in exascale proxy applications

Understanding the use of message passing interface in exasca...

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作者： Sultana, Nawrin Rüfenacht, Martin Skjellum, Anthony Bangalore, Purushotham Laguna, ignacio Mohror, Kathryn Department of Computer Science and Software Engineering Auburn University AuburnAL United States Department of Computer Science and Engineering University of Tennessee at Chattanooga ChattanoogaTN United States Department of Computer Science University of Alabama at Birmingham BirminghamAL United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA United States

The Exascale Computing Project (ECP) focuses on the development of future exascale-capable applications. Most ECP applications use the message passing interface (MPi) as their parallel programming model with mini-apps serving as proxies. This paper explores the explicit usage of MPi in such ECP proxy applications. We empirically analyze 14 proxy applications from the ECP Proxy Apps Suite. We use the MPi profiling interface (PMPi) to collect MPi usage patterns in ECP proxy apps. Our analysis shows that a small subset of features from MPi is commonly used in the proxies of exascale-capable applications, even when they reference third-party libraries. This study is intended to provide a better understanding of the use of MPi in current exascale applications. The findings can help focus software investments made for exascale systems in the MPi middleware including optimization, fault-tolerance, tuning, and hardware-offload. © 2020 John Wiley & Sons Ltd

关键词： Message passing

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Machine learning for Autopsy reports Forensic using Text Classification Techniques 2

Machine learning for Autopsy reports Forensic using Text Cla...

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2nd international Conference on Computing and information Technology, iCCiT 2022

作者： Shahid, Muhammad Rehman Munir, Asim ifraheem, Layeba Aldabbas, Hamza Wadood, Abdul Alwada'n, Tariq University of Faisalabad Departmental of Computational Sciences Faislabad Pakistan International Islamic University Department of Computer Science and Software Engineering Islamabad Pakistan Al-Balqa Applied University Prince Abdullah Bin Ghazi Faculty of Information and Communication Technology Al-Salt Jordan School of Computing Engineering Digital Technologies Teesside University Middlesbrough United Kingdom

ISBN: (纸本)9781665436052

A forensic autopsy is a surgical process in which experts collect a deceased body's internal and external information. These death certificates are the source of timely warnings of an increase in disease activity. it's only helpful if accurate and quantitative data is available. Therefore, the Classification of plain text medical autopsy reports reduces the time consumption and irregularities. The motive is to design an automatic text classification system that classifies plain text autopsy reports. Therefore, a methodology proposes using different Automatic Text Classification Techniques (ATC). This technique has embedded Feature Extraction, Feature Representation, and Feature Reduction techniques. These techniques use for the construction of classification models that classify the text of autopsy reports. Data sets collected from these types will be helpful in future experiments. Finally, the performance of the classifier measures by using different Evaluation parameters. These Evaluation Measures are Precision, Recall, Accuracy, and F-measure. © 2022 iEEE.

关键词： Support vector machines

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Single Loop Control of a Common DC-Bus-Configured Traction Motor Emulator Using State Feedback Linearization Method

Single Loop Control of a Common DC-Bus-Configured Traction M...

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2021 iEEE Southern Power Electronics Conference, SPEC 2021

作者： Kadam, Arvind H. Williamson, Sheldon S. Group Faculty of Engineering and Applied Science Department of Electrical Computer and Software Engineeirng 2000 Simcoe Street North OshawaONL1G 0C5 Canada

ISBN: (纸本)9781665436236

Nowadays, the LCL (inductor-capacitor-inductor) filter is an integral part of every power electronic converter system operating on current control. Though higher order, the LCL filter due to its high harmonic suppression capability are widely adopted in back-to-back converter systems or grid connected converter systems. Normally, with LCL filter, the control system follows double closed loop with outer loop controlling DC voltage and inner loop controlling AC current. However, for some special applications like common DC-bus-configured motor emulator (ME) system, the DC bus voltage is not required to be controlled. in addition, the presence of LCL filter introduces cross coupling of flux and torque component in case of AC motor emulation. The double closed loop control is generally adopted to decouple torque and flux components, however the controller design is more complex process. Therefore, this paper presents a single loop control of a common DC-bus-configured ME system with LCL filter based on state feedback linearization method. The decoupling equations in direct and quadrature axis are derived here. The simulation results presented for a 2.0 kW PMSM motor validate the stability as well as closed loop operation of the system with single loop control. © 2021 iEEE.

关键词： Synchronous motors

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Optimal Resource Utilization in Hyperledger Fabric: A Comprehensive SPN-Based Performance Evaluation Paradigm

Optimal Resource Utilization in Hyperledger Fabric: A Compre...

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iEEE Symposium on Network Operations and Management

作者： Carlos Melo Glauber Gonçalves Francisco A. Silva Leonel Feitosa iure Fé André Soares Eunmi Choi Tuan Anh Nguyen Dugki Min Applied Research on Distributed Systems Lab (PASID) Federal University of Piauí (UFPI) Brazil School of Software College of Computer Science Kookmin University Seoul South Korea Konkuk Aerospace Design-Airworlhiness Research Inslilule (KADA) Konkuk Universily Seoul Soulh Korea Department of Computer Science and Engineering Konkuk University Seoul South Korea

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Hyperledger Fabric stands as a leading framework for permissioned block-chain systems, ensuring data security and audit-ability for enterprise applications. As applications on this platform grow, understanding its complex configuration concerning various block-chain parameters becomes vital. These configurations significantly affect the system’s performance and cost. in this research, we introduce a Stochastic Petri Net (SPN) model to analyze Hyper-ledger Fabric’s performance, considering variations in block-chain parameters, computational resources, and transaction rates. We provide case studies to validate the utility of our model, aiding block-chain administrators in determining optimal configurations for their applications. A key observation from our model highlights the block size’s role in system response time. We noted an increased mean response time, between 1 to 25 seconds, due to variations in transaction arrival rates.

关键词： Performance evaluation Distributed ledger Computational modeling Data security Petri nets Stochastic processes Fabrics

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