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Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Chhavi Bajpai Manish Gaur J Roselin Suganthi Vinayagam S S. Kaliappan Manoj Senthil K Department of Computer Science & Engineering Centre for Advanced Studies Lucknow India Department of Computer Science & Engineering Institute of Engineering and Technology Lucknow India Department of ECE K. Ramakrishnan College of Engineering Trichirapalli India Department of Bioscience Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Research and Development Lovely Professional University Jalandhar India Department of Electronics and Communication Engineering Kongu Engineering College Erode India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Having a certified plant pathologist visually inspect the diseased leaves is now the gold standard for disease diagnosis in plants. This is because symptoms are present in the vast majority of plant illnesses. Because manual disease diagnosis is slow and results are highly dependent on the skill of the pathologist, this is an ideal domain for computer-aided diagnostic *** one of the suggested methods are preprocessing, step two is feature extraction, and step three is training the model. Pictures are acquired, then processed, enhanced, resized, segmented, and finally converted from RGB to HSI as part of the preprocessing phase. The topic of this study is the extraction of numerous features for the purpose of leaf disease categorization. Hexagons of colors are retrieved for classification purposes. The model was trained using Spectral Graph Theory. On average, this state-of-the-art technique achieves a higher accuracy rate of 92.48% than CNN and SVM.

关键词： Support vector machines Training Accuracy Computational modeling Crops Color Feature extraction Graph theory Medical diagnosis Diseases

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New Decision-Making Technique Based on Hurwicz Criteria for Fuzzy Ranking

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computers, Materials & Continua 2022年第12期73卷 4595-4609页

作者： Deepak Sukheja Javaid Ahmad Shah G.Madhu K.Sandeep Kautish Fahad A.Alghamdi Ibrahim.S.Yahia El-Sayed M.El-Kenawy Ali Wagdy Mohamed Department of Computer Science and Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadIndia Department of Mathematics Dr.APJ Abdul Kalam University Indore(M.P)India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadIndia LBEF Campus Kathmandu44600Nepal Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Laboratory of Nano-Smart Materials for Science and Technology(LNSMST) Department of PhysicsFaculty of ScienceKing Khalid UniversityP.O.Box 9004Abha 61413Saudi Arabia Research Center for Advanced Materials Science(RCAMS) King Khalid UniversityP.O.Box 9004Abha 61413Saudi Arabia Nanoscience Laboratory for Environmental and Biomedical Applications(NLEBA) Semiconductor Lab.Department of PhysicsFaculty of EducationAin Shams UniversityRoxyCairo 11757Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Sciences Engineering The American University in CairoEgypt

Efficient decision-making remains an open challenge in the research community,and many researchers are working to improve accuracy through the use of various computational *** this case,the fuzzification and defuzzification processes can be very *** is an effective process to get a single number from the output of a fuzzy *** defuzzification as a center point of this research paper,to analyze and understand the effect of different types of vehicles according to their *** this paper,the multi-criteria decision-making(MCDM)process under uncertainty and defuzzification is discussed by using the center of the area(COA)or ***,to find the best solution,Hurwicz criteria are used on the defuzzified ***-making technique is proposed using Hurwicz criteria for triangular and trapezoidal fuzzy *** proposed technique considers all types of decision makers’perspectives such as optimistic,neutral,and pessimistic which is crucial in solving decisionmaking problems.A simple case study is used to demonstrate and discuss the Centroid Method and Hurwicz Criteria for measuring risk attitudes among *** significance of the proposed defuzzification method is demonstrated by comparing it to previous defuzzification procedures with its application.

关键词： Defuzzification decision-making fuzzy numbers Hurwicz multicriteria decision-making ranking order

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Assistive Technical Communication of Montenegrin eServices: a Case Study 27

Assistive Technical Communication of Montenegrin eServices: ...

引用

27th International Conference on Information Technology, IT 2023

作者： Simon, Aniko Lakovic, Luka Kovacevic, Pavle Kara, Peter A. Ognjanovic, Ivana Sendelj, Ramo Reich, Christoph Roganovic, Milovan Mantas, John Bokor, Laszlo Sigma Technology Budapest1093 Hungary University of Donja Gorica Faculty for Information Systems and Technologies Podgorica81000 Montenegro Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science School of Computer Science and Mathematics Faculty of Science Engineering and Computing LondonKT1 2EE United Kingdom University of Donja Gorica Humanistic Studies Podgorica81000 Montenegro Furtwangen University Institute of Data Science Cloud Computing and It Security Furtwangen78120 Germany Clinical Centre of Montenegro Clinic for Neurology Podgorica81000 Montenegro National and Kapodistrian University of Athens Faculty of Nursing School of Health Sciences Goudi 11527 Greece

ISBN: (纸本)9798350397512

With the advancement of information technology in the recent decades, digital and online services have become essential components of everyday life in Europe. Montenegro is no different in this regard. However, as digital literacy in the country is still in a developing phase in comparison with most countries of the EU, a higher portion of its citizens may rely on assistive technical communication. In this paper, we provide a case study on the assistive technical communication of Montenegrin eServices. The work addresses the sectors of online banking, healthcare services, higher education, national administrative services, and utilities. Our findings highlight the diversity in terms of implemented assistive technical communication, and distinguish usage contexts on the level of adequacy. Yet as the functionalities of Montenegrin eServices are expected to gradually expand in the upcoming years, assistive technical communication must aim to handle the higher extents of service complexity. © 2023 IEEE.

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Integrating Artificial Intelligence for Sustainable and Adaptable Architecture

Integrating Artificial Intelligence for Sustainable and Adap...

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International Conference on Computational and Characterization Techniques in Engineering & sciences (CCTES)

作者： Valapula Lalitha Regidi Suneetha Basi Reddy A Nilesh R. Mate Syeeda Mujeebunnisa Department of CSE(AI&ML) Sai Spurthi Institute of Technology India Department of ECE Sanketika Vidya Parishad Engineering College Visakhapatnam India Department of Computer Science and Engineering School of Computing Mohan Babu University Tirupati India Centre for Distance and Online Education Bharati Vidyapeeth (Deemed to be University) Pune India School of Science and Computer Studies CMR University Bengaluru India

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

In nature, flexibility is essential, and AI may enhance it in architecture. The article integrates AI to develop self-learning buildings that can adapt to future obstacles. This research aims to create structures that use sensors to gather environmental data and respond. Phases comprise this study's strategy. In Phase 1, AI in architecture is extensively researched. That study in Phase 1 guided Phase 2's building design. The parametric building design in phase 2 uses machine learning and computational design techniques. Grasshopper scripting and Rhino modelling were used to create an algorithm that would create shapes that would both biomimetic the process of coral growth and be tailored to the project's chosen location. The selection procedure for the produced experimental investigations is shown in Phase 3. To determine which type used the least amount of energy, many evaluations were conducted, including measurements of sunshine, radiation, and shadows. Phase 4 involves developing the shape to improve the building's efficiency. Phase 5 involves conducting performance assessments to demonstrate that the final form is highly adaptable and climatic or ecologically sensitive. This building's radiation exposure, according to the research, is between 200 and 300 kWh/m 2 . According to the shadow study, the building shape casts a shadow for eight hours. According to the analysis, the building's shape makes it more adaptive by reducing its energy use. An AI engine technology is used in the last stage to forecast the building's future growth. By incorporating technology into building design, we may create flexible structures that reduce building energy use and contribute to the creation of a sustainable world

关键词： Phase measurement Shape Architecture Shape measurement Buildings Energy measurement computer architecture Energy efficiency Sensors Artificial intelligence

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A Study on Effective Clustering Methods and Optimization Algorithms for Big Data Analytics

A Study on Effective Clustering Methods and Optimization Alg...

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2020 International Conference on Smart Electronics and Communication, ICOSEC 2020

作者： Karthika, D. Kalaiselvi, K. Vels Institute of Science Technology Advanced Studies Department of Computer Science Chennai Tamil Nadu India

ISBN: (数字)9781728154619

ISBN: (纸本)9781728154619

High-dimensional information is labeled through massive dimensions of structures, disseminates advanced difficulties that to be understood in around all on its part these periods. As the dimensions of datasets grow, the model data representations development into sparse and density of range growing into the extra task. It cannot achieve suitable consequences however, handling higher-dimensional data. However, falling the dimensional subspace similarly progresses extremely challenging issues. This broadside conveys a limited about effective clustering, Swarm Intelligence algorithms, and optimization approaches. It consistently focuses on a comprehensive summary of clustering performances with their advantages and disadvantages specified in recent works. Optimization methods and their comparative studies are deliberated with their performances. The scope of the forthcoming exertion to include the popular clustering approaches and optimization algorithms are used to find the performance analysis over different real-world datasets and it also deliberated after the work.. © 2020 IEEE.

关键词： Clustering algorithms

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SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network

arXiv

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arXiv 2024年

作者： Guo, Weiyu Sun, Ying Xu, Yijie Qiao, Ziyue Yang, Yongkui Xiong, Hui Artificial Intelligence Thrust HKUST Guangzhou China School of Computing and Information Technology Great Bay University China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China Department of Computer Science and Engineering HKUST Hong Kong Guangzhou HKUST Fok Ying Tung Research Institute China

Surface electromyography (sEMG) based gesture recognition offers a natural and intuitive interaction modality for wearable devices. Despite significant advancements in sEMG-based gesture recognition models, existing methods often suffer from high computational latency and increased energy consumption. Additionally, the inherent instability of sEMG signals, combined with their sensitivity to distribution shifts in real-world settings, compromises model robustness. To tackle these challenges, we propose a novel SpGesture framework based on Spiking Neural Networks, which possesses several unique merits compared with existing methods: (1) Robustness: By utilizing membrane potential as a memory list, we pioneer the introduction of Source-Free Domain Adaptation into SNN for the first time. This enables SpGesture to mitigate the accuracy degradation caused by distribution shifts. (2) High Accuracy: With a novel Spiking Jaccard Attention, SpGesture enhances the SNNs’ ability to represent sEMG features, leading to a notable rise in system accuracy. To validate SpGesture’s performance, we collected a new sEMG gesture dataset which has different forearm postures, where SpGesture achieved the highest accuracy among the baselines (89.26%). Moreover, the actual deployment on the CPU demonstrated a latency below 100ms, well within real-time requirements. This impressive performance showcases SpGesture’s potential to enhance the applicability of sEMG in real-world scenarios. The code is available at https://***/guoweiyu/SpGesture/. © 2024, CC BY-NC-ND.

关键词： Gesture recognition

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Empirical Study of Computational Intelligence Approaches for the Early Detection of Autism Spectrum Disorder 5th

Empirical Study of Computational Intelligence Approaches for...

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5th International Conference on Intelligent computing and Applications, ICICA 2019

作者： Khatun, Mst. Arifa Ali, Md. Asraf Ahmed, Md. Razu Noori, Sheak Rashed Haider Sahayadhas, Arun Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Software Engineering Daffodil International University Dhaka Bangladesh Artificial Intelligence Research Lab Vels Institute of Science Technology and Advanced Studies Chennai India

ISBN: (纸本)9789811555657

The objective of the research is to develop a predictive model that can significantly enhance the detection and monitoring performance of Autism Spectrum Disorder (ASD) using four supervised learning techniques. In this study, we applied four supervised-based classification techniques to the clinical ASD data obtained from 704 patients. Then, we compared the four machine learning (ML) algorithms performance across tenfold cross-validation, ROC curve, classification accuracy, F1 measure, precision, recall, and specificity. The analysis findings indicate that Support Vector Machine (SVM) achieved the uppermost performance than the other classifiers in terms of accuracy (85%), f1 measure (87%), precision (87%), and recall (88%). Our work presents a significant predictive model for ASD that can effectively help the ASD patients and medical practitioners. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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$\text{MR}^{2}$-Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance

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IEEE Journal of Biomedical and Health Informatics 2024年第1期29卷 482-494页

作者： Haiting Mao Yuhui Ma Dan Zhang Yanda Meng Shaodong Ma Yuchuan Qiao Huazhu Fu Caifeng Shan Da Chen Yitian Zhao Jiong Zhang Laboratory of Advanced Theranostic Materials and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China School of Cyber Science and Engineering Ningbo University of Technology Ningbo China Department of Computer Science University of Exeter Exeter U.K. Institution of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China Institute of High Performance Computing (IHPC) A*STAR Singapore School of Intelligence Science and Technology Nanjing University Nanjing China Qilu University of Technology Jinan China

Optical coherence tomography angiography (OCTA) plays a crucial role in quantifying and analyzing retinal vascular diseases. However, the limited field of view (FOV) inherent in most commercial OCTA imaging systems poses a significant challenge for clinicians, restricting the possibility to analyze larger retinal regions of high resolution. Automatic stitching of OCTA scans in adjacent regions may provide a promising solution to extend the region of interest. However, commonly-used stitching algorithms face difficulties in achieving effective alignment due to noise, artifacts and dense vasculature present in OCTA images. To address these challenges, we propose a novel retinal OCTA image stitching network, named $\text{MR}^{2}$ -Net, which integrates multi-scale representation learning and dynamic location guidance. In the first stage, an image registration network with a progressive multi-resolution feature fusion is proposed to derive deep semantic information effectively. Additionally, we introduce a dynamic guidance strategy to locate the foveal avascular zone (FAZ) and constrain registration errors in overlapping vascular regions. In the second stage, an image fusion network based on multiple mask constraints and adjacent image aggregation (AIA) strategies is developed to further eliminate the artifacts in the overlapping areas of stitched images, thereby achieving precise vessel alignment. To validate the effectiveness of our method, we conduct a series of experiments on two delicately constructed datasets, i.e., OPTOVUE-OCTA and SVision-OCTA. Experimental results demonstrate that our method outperforms other image stitching methods and effectively generates high-quality wide-field OCTA images, achieving a structural similarity index (SSIM) score of 0.8264 and 0.8014 on the two datasets, respectively.

关键词： Feature extraction Image stitching Retina Image registration Convolutional codes Bioinformatics Representation learning

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Mary Kenneth Keller: First US PhD in computer science

arXiv

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arXiv 2022年

作者： Head, Jennifer O'Leary, Dianne P. Archivist Sisters of Charity of the Blessed Virgin Mary DubuqueIA United States Computer Science Department Institute for Advanced Computer Studies University of Maryland United States

In June 1965, Sister Mary Kenneth Keller, BVM, received the first US PhD in computer science, and this paper outlines her life and accomplishments. As a scholar, she has the distinction of being an early advocate of learning-by-example in artificial intelligence. Her main scholarly contribution was in shaping computer science education in high schools and small colleges. She was an evangelist for viewing the computer as a symbol manipulator, for providing computer literacy to everyone, and for the use of computers in service to humanity. She was far ahead of her time in working to ensure a place for women in technology and in eliminating barriers preventing their participation, such as poor access to education and daycare. She was a strong and spirited woman, a visionary in seeing how computers would revolutionize our lives. A condensation of this paper appeared as, "The Legacy of Mary Kenneth Keller, First U.S. Ph.D. in computer science," Jennifer Head and Dianne P. O'Leary, IEEE Annals of the History of computing 45(1):55-63, January-March *** Codes 68.03 © 2022, CC BY-NC-ND.

关键词： Education computing

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Optimal Bilinear Equalizer for Cell-Free Massive MIMO Systems over Correlated Rician Channels

arXiv

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arXiv 2024年

作者： Wang, Zhe Zhang, Jiayi Björnson, Emil Niyato, Dusit Ai, Bo State Key Laboratory of Advanced Rail Autonomous Operation China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Computer Science KTH Royal Institute of Technology Stockholm114 28 Sweden College of Computing & Data Science Nanyang Technological University 639798 Singapore

In this paper, we explore the low-complexity optimal bilinear equalizer (OBE) combining scheme design for cell-free massive multiple-input multiple-output networks with spatially correlated Rician fading channels. We provide a spectral efficiency (SE) performance analysis framework for both the centralized and distributed processing schemes with bilinear equalizer (BE)-structure combining schemes applied. The BE-structured combining is a set of schemes that are constructed by the multiplications of channel statistics-based BE matrices and instantaneous channel estimates. Notably, we derive closed-form achievable SE expressions for centralized and distributed BE-structured combining schemes. We propose one centralized and two distributed OBE schemes: Centralized OBE (C-OBE), Distributed OBE based on Global channel statistics (DG-OBE), and Distributed OBE based on Local channel statistics (DL-OBE), which maximize their respective SE expressions. OBE matrices in these schemes are tailored based on varying levels of channel statistics. Notably, we obtain new and insightful closed-form results for the C-OBE, DG-OBE, and DL-OBE combining schemes. Numerical results demonstrate that the proposed OBE schemes can achieve excellent SE, even in scenarios with severe pilot contamination. Copyright © 2024, The Authors. All rights reserved.

关键词： Fading channels

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