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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Sharmili, K.C. Suja, G.P. Pandian, E. Walid, Md. Abul Ala Arunachalam, Sripriya Babu, G.Charles Computer Science Stella Maris College 17 Cathedral Road Chennai India Computer Science Muslim Arts College Thiruvithancode629174 India Sri Muthukumaran Institute of Technology Mangadu Master of Computer Application Chennai69 India Department of Computer Science and Engineering Khulna9203 Bangladesh Computer Applications-PG School of Computing Sciences VELS Institute of Science Technology & Advanced Studies - VISTAS Velan Nagar P.V. Vaithiyalingam Road Pallavaram Chennai600 117 India GRIET Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350397253

In recent years, Alzheimer's disease has become a major health concern. Over 45 million individuals worldwide suffer from this illness. Alzheimer's disease is a neurodegenerative illness of unidentified etiology and process that causes cognitive deterioration, and it mostly affects the elderly. Dementia, the gradual and irreversible loss of brain cells, is the leading cause of Alzheimer's disease. Those with this illness lost the ability to think, read, and do other basic tasks. A machine learning system may aid in this situation by making accurate predictions about the onset of illness. Dementia diagnosis in a broad patient population is the major objective. This research presents the findings and analysis of many Machine Learning models for identifying dementia. To alleviate this obstacle and help in the diagnosis of AD will create a deep-learning architecture that uses stacked auto-encoders and a softmax output layer. The proposed technique can analyze numerous classes in a single setting, unlike earlier procedures, and only needs a small number of labeled training samples and basic domain expertise to get started. In the present studies, a substantial improvement in performance when it came to classifying all diagnostic subgroups. Using the proposed technique can run these time series through a Convolutional Neural Network (CNN) and ResNet50 model to extract the distinguishing patterns across stages. With an F1-score of 0.99 and an accuracy of 99.91 percent, the CNN-based technique outperformed the standard feature-based classifiers by a significant margin. © 2023 IEEE.

关键词： Convolutional neural networks

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Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform

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computers, Materials & Continua 2022年第7期72卷 1357-1372页

作者： Nguyen A.Tuan D.Akila Souvik Pal Bikramjit Sarkar Thien Khai Tran G.Mothilal Nehru Dac-Nhuong Le Faculty of Information Technology Ho Chi Minh City University of Foreign Languages-Information TechnologyHo Chi Minh City70000Vietnam Department of Information Technology Vels Institute of ScienceTechnology&Advanced StudiesChennai600117India Department of Computer Science and Engineering Sister Nivedita UniversityKolkata700156India Department of Computer Science and Engineering JIS College of EngineeringNadia741235India Institute of Research and Development Duy Tan UniversityDanang550000Vietnam School of Computer Science Duy Tan UniversityDanang550000Vietnam

This article presents a new scheme for dynamic data optimization in IoT(Internet of Things)-assisted sensor *** various components of IoT assisted cloud platform are *** addition,a new architecture for IoT assisted sensor networks is ***,a model for data optimization in IoT assisted sensor networks is proposed.A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization(MIDDO)algorithm for IoT assisted sensor network is proposed in this *** proposed algorithm considers every node data and utilized membership function for the optimized data *** proposed framework is compared with two stage optimization,dynamic stochastic optimization and sparsity inducing optimization and evaluated in terms of reliability ratio,coverage ratio and sensing *** optimization was performed based on the availability of cloud resource,sensor energy,data flow volume and the centroid of each *** was inferred that the proposed MIDDO algorithm achieves an average performance ratio of 76.55%,reliability ratio of 94.74%,coverage ratio of 85.75%and sensing error of 0.154.

关键词： Data optimization IoT sensor network reliability membership sensor energy

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Insurance Plan for Service Assurance in Cloud Computing Market with Incomplete Information

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Journal of Communications and Information Networks 2022年第1期7卷 11-22页

作者： Yanru Zhang Chunxiao Jiang Nguyen H.Tran Shengrong Bu FeiRichard Yu Zhu Han College of Computer Science and Engineering the University of Electronic Science and Technology of ChinaChengdu 611731China Shenzhen Institute for Advanced Study UESTCLonghuaShenzhen 518110China Tsinghua Space Center Tsinghua UniversityBeijing 10084China School of Computer Science the University of SydneySydneyNew South WalesAustralia Department of Engineering Brock UniversityONCanada School of Information Technology Depart.of Systems and Computer EngineeringCarleton UniversityOttawa K1S 5B6ONCanada Department of Electrical and Computer Engineering the University of HoustonHouston 77004TXUSA

Nowadays,cloud computing has been identified as new opportunities for migrating to the expected agility,reuse,and adaptive capabilities that can support the ever changing IT trends and ***,the rapid evolution of those technologies also comes with open issues such as security,privacy,integrity,quality of services,and their possible detrimental *** this work,the concept of insurance is introduced to compensate the cloud computing customers when encountering those failures if service providers(SPs)have insurance ***,we consider the situation when the insurer is unable to see the system failure risk levels of the SPs,which is usually seen as an incomplete information market,in contrast with the optimal situation in a complete information ***,an insurance-based cloud computing architecture is proposed to build a monetary credit system in which the cloud computing SP pays a premium for a certain coverage to the ***,problem is formulated to solve the optimal insurance plan in complete and incomplete information markets,together with detail analysis of insurance policies in both cases are ***,simulation results show the properties of the two insurance plans and parameters that affect the design of the insurance plan.

关键词： service assurance cloud computing market incomplete information game theory insurance plan

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MIXING SOLUTIONS IN BITCOIN AND ETHEREUM ECOSYSTEMS: A REVIEW AND TUTORIAL

arXiv

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arXiv 2023年

作者： Arbabi, Alireza Shojaeinasab, Ardeshir Bahrak, Behnam Najjaran, Homayoun Department of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Victoria Victoria Canada Tehran Institute for Advanced Studies Tehran Iran Department of Mechanical Engineering University of Victoria Victoria Canada

This manuscript presents an exhaustive review of blockchain-based mixing services, aiming to fill the existing gap between academic innovations and real-world implementations. Starting with an identification of the core functionalities and techniques employed by mixing services, the paper delves into detailed explanations of these operational mechanisms. It further outlines an evaluation framework tailored for a rigorous assessment, highlighting the key vulnerabilities and strengths of various solutions. In addition, the study identifies potential attack vectors that compromise these services. The paper explores the dual nature of mixing services: while they contribute to the preservation of privacy—a cornerstone of blockchain technologies—they can also facilitate illicit activities. By addressing key research questions, this study not only offers a comprehensive overview of the current state of mixing services but also sets the stage for future academic discourse in this evolving field. © 2023, CC BY-NC-ND.

关键词： Blockchain

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Web Based Cyber Attack Detection for Industrial System (PLC) Using Deep Learning

Web Based Cyber Attack Detection for Industrial System (PLC)...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： A. Yasir Kalaivani Kathirvelu M. K. Arif Department of Computer Science and Engineering School of Engineering Vels Institute of Science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

Web apps are frequently targeted by cyber-attacks due to their network access and security flaws. Instances of attacks targeting online applications might pose significant risks. The issue of cyber security continues to pose a significant barrier in Industry 5.0 scenarios, since cyber-attacks have the potential to result in severe outcomes such as production disruptions, data breaches, and even physical injuries. In order to tackle this difficulty, this study suggests a novel deep-learning approach for identifying web-based assaults in the context of Industry 5.0. The investigation explores transformer models, which are methods used in deep learning, for their capacity to accurately classify attacks and detect unusual behavior. The results of this research demonstrated the higher performance of the suggested transformer-based system, surpassing earlier methods in terms of accuracy, precision, and recall. Deep learning plays a crucial role in effectively tackling cyber security issues in Industry 5.0 settings.

关键词： Deep learning Instruments Production Transformers Robustness Security Fifth Industrial Revolution

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Interactive Agriculture relying on Artificial Intelligence and Convolution Neural Network 2

Interactive Agriculture relying on Artificial Intelligence a...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, electrical and Electronics, ICIITCEE 2024

作者： Nandhini, J. Mohanapriya, D. Kalaiarasi, G. Lakshmipriya, N. Arunprasath, M.M. Jai Shriram Engineering College Department of Electronics and Communication Engineering Tamil Nadu Tiruppur India Vignan's Foundation for Science Technology & Research Department of Advanced Computer Science and Engineering Andrapradesh Guntur India Jai Shriram Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Tiruppur India Ksr Institute for Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Tiruchengode India

ISBN: (纸本)9798350306415

Crop production is more complicated than farming, as it involves a lot of labor and very specific humid conditions in both the soil as well as the atmosphere in which to grow them. Farming has been made easier by technology, such as smart irrigation and precise plant nutrition, but these systems have a drawback: they spray water uniformly on all crops, even if some of them need little. An agricultural smart spraying system minimizes the impact on the environment while targeting chemical spray applications. In smart sprayers, which in most cases also have a targeted detection and spraying system, the targeted sensor forms the basis of precision spraying management. Despite the fact that excess water can be sprayed, it is not recommended. A crop can be protected against being affected by possible rots if moisture sensors and float sensors are used as part of the Intelligent Spraying System. Using this technology, it is possible to stop crops from being destroyed by climate change. The crop won't be harmed by pest sickness because of using Convolutional Neural Network (CNN) algorithm. This paper examines the conventional techniques for identifying plant diseases and pests. Agriculture productivity is seriously threatened by agricultural illnesses and insect pests. If pests are not found and identified quickly, they might result in considerable economic losses. So by using CNN those disease are classified in earlier stage and crops are being protected. © 2024 IEEE.

关键词： Artificial Intelligence CNN Image Processing Smart Irrigation

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Driver Health Monitoring System to Identify Cardiac Problems in Drivers using Live ECG Signal

Driver Health Monitoring System to Identify Cardiac Problems...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： M. K. Arif Kalaivani Kathirvelu A. Yasir Department of Computer Science and Engineering School of Engineering Vels Institute of Science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

According to contemporary estimations, a significant proportion of elderly drivers are prone to experiencing accidents or collisions due to their diverse health states during the act of driving. Currently, individuals in the middle-age and younger demographics are encountering comparable challenges. Research indicates that drivers who experienced crashes caused by medical emergencies are not influenced by vehicle design or the integrity of the road, as seen by the sort of crashes and the manner in which they occurred. This research presents a comparison and measurement of heart rate and heart variability data for the occurrence of heart disease, stroke, or any emergency situation. The methods employed include the use of electrocardiogram (ECG) and Photo Plethysmo Graphy (PPG) *** enhanced performance of deep learning over conventional machine learning methods in addressing various artificial intelligence tasks, including image processing, computer vision, object detection, speech recognition, and medical imaging, has propelled deep learning to become the dominant term in the field of Artificial Intelligence applications

关键词： Deep learning Wrist Technological innovation Speech recognition Electrocardiography Task analysis Monitoring

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Relationship of IQ with Causal Connections Between Brain Salient Network Regions

Relationship of IQ with Causal Connections Between Brain Sal...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Mina Ghoorchian Hamid Soltanian-Zadeh Mir Mohsen Pedram Mohsen Mir Mohammad Sadeghi Department of Cognitive Science Institute for Cognitive Science Studies Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran

ISBN: (数字)9798331529710

ISBN: (纸本)9798331529727

IQ is one of the indicators that has always been of interest to psychiatrists, doctors and cognitive science researchers. Since this index plays a key role in people’s lives and also in the occurrence of brain abnormalities, many studies have been conducted on it. In this paper, we used the resting state magnetic resonance imaging data available in the HCP database to classify people into three groups with low, medium, and high IQ and applied machine learning methods on the matrix of causal connections between related network regions. We applied brain highlights. We calculated the matrix of causal relationships in this network by the spDCM algorithm and then obtained the differences of the three groups using the ANOVA statistical test and 6 edges out of 169 edges with p-value <0.05 were found to be significantly different, according to the order of the edges, this difference is in the relationship between rMCC-rvIPFC, rInsula-rvIPFC, rInsula-rPutamen, rInsulaIIPG, IIPG-rSFG, IIPG-rSFG. In the next step, we used the algorithms of support machines and nearest neighbors to classify these three groups. Finally, using the support vector regression algorithm, we predicted the IQ from the edge values with RMSE=5.41 and MAE=3.59. The results of this research indicate a significant relationship between IQ and the salient network of the brain.

关键词： Support vector machines Neuroimaging Visualization Accuracy Machine learning algorithms Medical treatment Prediction algorithms Classification algorithms Indexes Analysis of variance

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A Novel Optimization Technique for Designing Frequency Reconfigurable Pixelated Planar Antenna

A Novel Optimization Technique for Designing Frequency Recon...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Qiao, Tianrui Tang, Shiwen Rao, Junhui Zhang, Yujie Chiu, Chi-Yuk Cheng, Qingsha S. Murch, Ross Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Institute for Advanced Study The Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9781665442282

A novel method incorporating joint perturbation sensitivity analysis is proposed in this paper to design frequency reconfigurable planar antennas with a pixelated surface. Using our method, an antenna design having two switched working frequency bands and omnidirectional radiation patterns, is optimized. The simulation results verify its efficacy and potential computation efficiency. © 2023 IEEE.

关键词： Sensitivity analysis

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Retraction Notice: A Survey of advanced Learning Techniques Used for Initial Detection of vital Human organs Disorders through Iris

Retraction Notice: A Survey of Advanced Learning Techniques ...

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International Conference on Smart Structures and Systems (ICSSS)

作者： M Sandhiya A S Aneetha Department of Computer Science and Engineering VELS Institute of Science Technology & Advanced Studies (VISTAS)

ISBN: (数字)9798350384208

ISBN: (纸本)9798350384215

An approach of early detection that makes use of an optimization technique that was brought about by learning techniques. Artificial intelligence technology breakthroughs that can scan a patient’s body and diagnose the conditions they have would be expected by certain doctors. To gain a deeper understanding of the human body, iridology is an applied health practice. Images of iris can be acquired and interpreted using a variety of innovative techniques. Information on the human body and organ health is contained in Iris. Iridology is an academic discipline that examines the strengths and limitations of iris tissue to gain insight into the health of the body’s various organs. Iridology has grown more well-liked and trustworthy as a result of the quick growth of picture processing. Many iridology-based methods have been created recently that use certain iris features to detect the human disorders. The information contained herein displays every iris recognition method that has been studied along with the precision of each region. Future iridology research’ design and methodological decisions can be influenced by the studies outcomes.

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