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2023 IEEE International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2023

作者： Sangeetha, A. Krishnan, R. Santhana Kumar, G. Praveen Julie, E. Golden Ganesh, R. Karthik Robinson, Y. Harold PSNA College of Engineering and Technology Department of Information Technology Dindigul India SCAD College of Engineering and Technology Department of Electronics and Communication Engineering Tirunelveli India V.S.B Engineering College Department of Information Technology Karur India Anna University Department of Computer Science and Engineering Regional Campus Tirunelveli India SCAD College of Engineering and Technology Department of Computer Science and Engineering Tirunelveli India Francis Xavier Engineering College Department of Computer Science and Engineering Tirunelveli India

ISBN: (纸本)9798350397208

Swimming has become one of the major routines nowadays among people. People mostly use swimming pools for exercise or recreation. According to statistics one hour of swimming burns 30% more calories than one hour of running. So many people prefer swimming to keep their body fit. But few people use the swimming pool without having proper swimming skills. This leads to loss of their lives. Around the world nearly 42 people drown per hour. The pH level of water in the swimming pool should be between 7.4 to 7.6. The high pH water can cause rashes on human skin and scaling on pool equipment. Low pH causes eye irritation, skin irritation etc. Hence, a smart system is required to monitor the pH level of the water and to track the condition of the swimmers inside the pool. So with the support of few sensors and Arduino, an automatic swimming pool monitoring system, which is capable of sensing the pH level of the water available in swimming pool and condition of the swimmers is developed. The proposed system will also update all the observed status in the cloud with the support of the Internet facility. © 2023 IEEE.

关键词： Swimming pools

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Enhanced Metaheuristics-Based Clustering Scheme for Wireless Multimedia Sensor Networks

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computers, Materials & Continua 2022年第11期73卷 4179-4192页

作者： R.Uma Mageswari Sara A.Althubiti Fayadh Alenezi E.Laxmi Lydia Gyanendra Prasad Joshi Woong Cho Department of Computer Science and Engineering Vardhaman College of Engineering(Autonomous)HyderabadTelangana501218India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea

Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended *** the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target *** existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia *** energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network *** this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for *** proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum *** proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance *** simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.

关键词： Wireless multimedia sensor networks clustering spider monkey optimization algorithm energy efficiency metaheuristics quantum computing

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Hybrid particle swarm optimization algorithm for traveling salesman problem based on ternary optical computer 4

Hybrid particle swarm optimization algorithm for traveling s...

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4th International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Sun, Shaojiang Tong, Yihui Qi, Baofeng Wang, Zhehe Wang, Xianchao School of Computer and Information Engineering Fuyang Normal University Fuyang236600 China School of Computer Science and Technology Hainan Tropical Ocean University Sanya572000 China

In recent years, as a novel computer, the ternary optical computer (TOC) has attracted many attentions because of its own mega-parallelism. And with the development of optical computing technology, the exploration of applications based on TOC is also advancing. Travel Salesman problem (TSP) is a classical combinatorial optimization problem, which is also a NP problem. How to solve this problem quickly and efficiently is the major research direction. Particle swarm optimization algorithm (PSO) are prone to premature convergence and insufficient local search capability. To deal with the shortcomings of the problem, we promoted a hybrid algorithm that the hybrid particle swarm optimization algorithm (HPSO) to solve the problem. By introducing greedy strategy, the algorithm generates excellent populations. And the improved Metropolis criterion is added to individual learning and population learning to accept inferior solutions with certain probability, which can effectively increase the population diversity and the mutation adopts the 2-opt optimization strategy, which can solve the path crossing problem effectively, enhance the local optimization capability of the algorithm, and find higher quality solutions. At last, the results show that HPSO solves the TSP with fast convergence speed and high quality of the optimal solution. © 2024 The Authors.

关键词： Particle swarm optimization (PSO)

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Development of a Prediction System for Criminality and Suicidal in Sri Lanka 5

Development of a Prediction System for Criminality and Suici...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Ranasinghe, D.P.D. Fernando, R.D.T.S. Girambe, D.G. Arambegama, D.M.H.K.D. Chathurika, Bhagyanie Jayasinghe, Dulani Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350358131

This research confronts the growing challenges of rising suicide rates and crime in Sri Lanka through a dual approach, harnessing advanced machine learning and time series analysis. The innovative methodology, merging 'Feature Importance Weighting and Ensemble of Diverse Trees with the Random Forest Regressor,' achieves impressive accuracy of 93% for factors and 94% for methods. Additionally, the accuracy rates of 94% for education and 93% for occupationbased predictions enhance this comprehensive approach, offering a profound understanding of suicidal incidents and enabling precise prevention strategies. Simultaneously this study employs an ensemble of AutoRegressive Integrated Moving Average (ARIMA) models for crime prediction. This approach consistently attains high accuracy, often surpassing 90%, such as 96% and 97%. Utilizing multiple models enhances predictive accuracy and hotspot identification, granting law enforcement and policymakers flexibility to address enduring yearly hotspots and evolving dynamic hotspots. This research bridges the comprehension of suicide and crime dynamics in Sri Lanka, providing invaluable insights for evidence-based policies and targeted interventions. © 2023 IEEE.

关键词： Forecasting

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A structural variation genotyping algorithm enhanced by CNV quantitative transfer

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Frontiers of computer science 2022年第6期16卷 159-165页

作者： Tian ZHENG Xinyang QIAN Jiayin WANG Department of Computer Science and Technology School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an710049China Institute of Data Science and Information Quality Shaanxi Engineering Research Center of Medical and Health Big DataXi’an Jiaotong UniversityXi’an710049China

Genotyping of structural variations considering copy number variations(CNVs)is an infancy and challenging ***,a prevalent form of critical genetic variations that cause abnormal copy numbers of large genomic regions in cells,often affect transcription and contribute to a variety of *** characteristics of CNVs often lead to the ambiguity and confusion of existing genotyping features and algorithms,which may cause heterozygous variations to be erroneously genotyped as homozygous variations and seriously affect the accuracy of downstream *** the allelic copy number increases,the error rate of genotyping increases *** instances with different copy numbers play an auxiliary role in the genotyping classification problem,but some will seriously interfere with the accuracy of the *** by these,we propose a transfer learning-based method to genotype structural variations accurately considering *** method first divides the instances with different allelic copy numbers and trains the basic machine learning framework with different genotype *** maximizes the weights of the instances that contribute to classification and minimizes the weights of the instances that hinder correct *** adjusting the weights of the instances with different allelic copy numbers,the contribution of all the instances to genotyping can be maximized,and the genotyping errors of heterozygote variations caused by CNVs can be *** applied the proposed method to both the simulated and real datasets,and compared it to some popular algorithms including GATK,Facets and *** experimental results demonstrate that the proposed method outperforms the others in terms of accuracy,stability and *** source codes have been uploaded at github/TrinaZ/CNVtransfer for academic use only.

关键词： genotyping copy number variations transfer earning

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Clinical Decision Support System Using Recurrent Neural Network 1

Clinical Decision Support System Using Recurrent Neural Netw...

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1st International Conference on Data, Computation and Communication, ICDCC 2024

作者： Periya Nayaki, A. Arrchit Ramana, M.S. Prithivi Raj, S.D. Thanabal, M.S. Jeyakumar, N.K. Velammal College of Engineering and Technology Department of Information Technology Madurai India PSNA College of Engineering and Technology Department of Computer Science and Engineering Dindigul India

ISBN: (纸本)9798331532956

This project presents the development of a CDSS (Clinical Decision Support System) utilizing deep learning techniques, specifically focusing on Recurrent Neural Networks (RNNs) and LSTM (Bidirectional Long Short-Term Memory) networks. The system is designed to predict medical conditions based on 132 clinical symptoms and target prognoses. A variety of models, including Support Vector Machine, Decision Tree, K-Nearest Neighbors, deep learning architectures, and Logistic Regression were trained and evaluated for performance using key metrics such as recall, precision, F1-score, and accuracy. Among the models, the Bidirectional LSTM network outperformed traditional machine learning methods demonstrating its more advanced ability to handle sequential clinical data has an accuracy of 90.16%. This research highlights the potential of deep learning models in improving diagnostic accuracy and reliability, offering promising advancements for clinical decision-making systems. © 2024 IEEE.

关键词： Classification Deep Network LSTM Prognosis Recurrent Neural Network

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A Review of Implementing Exploring Mobile Edge Computing within the Framework of 5G and 6G Networks

A Review of Implementing Exploring Mobile Edge Computing wit...

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2023 International Conference on Advances in Computation, Communication and information technology, ICAICCIT 2023

作者： Batra, Raman Kumar, Sanjeev Bargavi, Manju Noida Institute of Engineering and Technology Department of Mechanical Engineering Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350344387

The integration of edge computing is critical to the development of Beyond 5G (B5G) and 6G networks, as the volume of data and processing demands continue to rise. Using the radio access network (RAN), mobile edge computing (MEC) is essential for putting advanced cloud computing features in close proximity to end users. Even though MEC and its possible applications have been thoroughly studied, there hasn't been much conversation about the crucial elements required for MEC to be deployed successfully in order to satisfy various application demands. The important considerations that must be made while establishing edge infrastructure in B5G and 6G networks are outlined in this article. These factors include things like user density, server location, capacity, edge architecture, and security protocols. Moreover, it includes concrete assessments of edge computing-dependent applications, such forecasting and video conversion using deep learning. Additionally, the study provides insightful viewpoints that clarify open research questions related to edge computing within the framework of 6G networks. © 2023 IEEE.

关键词： and Cloud computing Distributed computing Edge processing Next-generation 6G communication networks

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Structural RC computer aided intelligent analysis and computational performance via experimental investigations

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Structural engineering and Mechanics 2024年第3期90卷 253-261页

作者： Huang, Y.C. Lulios, TuMuli Chang, Chu-Ho Noor, M. Nasir Shao, Jen-Chung Chiu, Chien-Liang Lee, Tsair-Fwu Wang, Renata Information Technology Faculty Duy Tân University 254 Nguyen Van Linh Danang Viet Nam Princess Margaret Hospital Funafuti Island Private Mail Bag Tuvalu College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung Taiwan College of Maritime National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Medical Physics and Informatics Laboratory of Electronics Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Information and Research Center of China 1/9 Road: 2 Block: D Section: 15 Dhaka1216 Bangladesh

This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam’s directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures. © 2024 Techno-Press, Ltd.

关键词： Boundary conditions

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On-Road Drivers and People with Visual Impairments: Real-Time Machine Learning-based Speed Breaker and Pothole Detection 15

On-Road Drivers and People with Visual Impairments: Real-Tim...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Fathima, Chahath A. Suhas, G.K. Bhagappa Deepak, N.R. Research center for Computer & Information Sciences Akshaya Institute of Technology Affiliated to Visvesvaraya Technological University Tumkur India Research center for Computer & Information Sciences Brindavan College of Engineering Affiliated to visvesvaraya technological university Bangalore India Department of Computer Science Engineering Atria Institute of Technology Karnataka Bengaluru India

ISBN: (纸本)9798331300579

Although well-maintained roads are an important source of transportation, their economic impact is rarely felt in a ***, drivers who aren't convinced of their safety are seriously at risk from potholes and speed ***, poor night vision, inaccurate speed breaker signage, and the driver's carelessness all contributed to this *** of these elements harm the vehicle's suspension system in addition to having an impact on drivers who are on the *** days, cars with reduced ground clearance have trouble on uneven *** this paper, we proposed to use a Recurrent Neural Network (RNN) in a machine learning method to create a device that can identify bumps and *** device uses an ESP32 GPS Speedometer to locate these bumps and potholes and transmits the position, along with speed, latitude, and longitude values, to a database via *** device also chooses to save the data it collects in the *** the aid of machine learning, it can be classified into various categories based on *** also has a speech module that allows audio notifications to be played over the *** research suggests using a Recurrent Neural Network (RNN), a machine learning method, to train parameters autonomously in order to enhance vehicle suspension health and prevent driver fatigue. © Grenze Scientific Society, 2024.

关键词： Recurrent neural networks

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Comparing and Contrasting Automated Reasoning Techniques in Comparative information Analysis 2

Comparing and Contrasting Automated Reasoning Techniques in ...

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Thaware, Shailesh J. Mishra, Awakash Sharma, Ritu Karthigaikumar, P. Neetha, S.S. Vijayaraghavan, P. Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Karpagam College of Engineering Department of Electronics and Communication Engineering Coimbatore641032 India Department of Computer Science and Information Technology Karnataka Bangalore India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai India

ISBN: (纸本)9798350308846

This technical abstract discusses the software program of various automated reasoning techniques for comparative statistics evaluation. Automatic reasoning uses hard and fast predetermined algorithms to analyze a given set of information. Within comparative statistics analysis, such algorithms may be used to find similarities, versions, and patterns among numerous information sets. The distinct varieties of automated reasoning strategies for comparative statistics analysis are rule-based reasoning, feature optimization, regression analysis, gadget learning, and Bayesian techniques. For every one of those techniques, the paper will communicate how they provide precise blessings for comparative statistics evaluation and how they'll be achieved in beautiful datasets. Furthermore, it'll evaluate and assess the benefits and shortcomings of each of those techniques. This technical abstract offers a top-level view of the capabilities and annoying conditions of the diverse automatic reasoning strategies applicable to comparative statistics evaluation. © 2023 IEEE.

关键词： comparative evaluation predetermined similarities software

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