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Proceedings - international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

Proceedings - International Conference on Computing, Power, ...

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5th IEEE international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

ISBN: (纸本)9798350383522

the proceedings contain 359 papers. the topics discussed include: classification and structuring of DL-based method for finding Alzheimer's disease through MRI images;impact of social media on the professional development of health professionals;use of sensor networks with self-organizing algorithm to increase the agricultural productivity;cyberbullying : research challenges and opportunities;improving brain tumor detection and classification using intelligent methods;rotten and fresh fruits classification using deep learning;structured implementation of ML algorithms for cardiovascular disease detection;enhanced retail shopper behavioral analysis using human machine interaction and model validation;java-powered digital healthcare management: innovating medical administration systems;and applicability of machine learning in waste water quality detection.

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5th international conference on Trends in Computational and Cognitive Engineering, TCCE 2023

5th International Conference on Trends in Computational and ...

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5th international conference on Trends in Computational and Cognitive Engineering, TCCE 2023

ISBN: (纸本)9789819719228

the proceedings contain 49 papers. the special focus in this conference is on Trends in Computational and Cognitive Engineering. the topics include: BScFilter: A Deep Learning Approach for Sports Comments Filtering in a Resource Constraint Language;HABE Secure Access at Cloud-Healthcare Database;comparative Analysis of Nature-Inspired algorithms for Task Assignment Problem;A Novel Approach for Object Recognition in Hazy Scenes: Integrating YOLOv7 Architecture with Boundary-Constrained Dehazing;dynamic Multihead Attention for Enhancing Neural Machine Translation Performance;scratch Vision Transformer Model for Diagnosis Grape Leaf Disease;multilevel Association Mining with Particle Swarm Optimization: A Comprehensive Approach for High-Utility Itemset Discovery;attention-Based Neural Machine Translation for Multilingual Communication;use of Deep Learning to Handle Early-Stage Business Data;an Efficient Text-Based Document Categorization with k-Means and Cuckoo Search Optimization;potato Leaf Disease Detection and Classification Using Deep Learning;parkinson’s Disease Detection Using Machine Learning;Comparative Analysis of ML Models for Brain Tumor Detection;Machine Learning-Based Prediction of COVID-19: A Robust Approach for Early Diagnosis and Treatment;the Prediction of Diabetes Using Machine Learning in the Healthcare System;a Fuzzy-Based Vision Transformer Model for Tea Leaf Disease Detection;towards Federated-Deep Learning-Based Glaucoma Detection from Color fundus Images;Inventing the Potential of a High-Frequency EEG, Namely Dodecanogram (DDG): Human Subjects’ Study;real-Time Prediction of Diabetes Complications Using Regression-Based Machine Learning Models;exploring Open Access Cybersecurity Datasets for Machine Learning-Based Cyberattack Detection;design and Development of a Reliable Blockchain-Based Pension System;Comparative Analysis of CatBoost Against Machine Learning algorithms for Classification of Altered NSL-KDD;enhancing Scalability in Sharding Blo

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5th international conference on Computing, Communications, and Cyber Security, IC4S 2023

5th International Conference on Computing, Communications, a...

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5th international conference on Computing, Communications, and Cyber Security, IC4S 2023

ISBN: (纸本)9789819725496

the proceedings contain 68 papers. the special focus in this conference is on Computing, Communications, and Cyber Security. the topics include: Compact and High-Gain RFID Reader Antennas for Future Internet of things Applications;Enabling Modern IoT Solutions with RFID Devices via an Integrated Feeding Network-Fed Ultra-Wide HPBW Patch Antenna Array;A Compact and Extremely Stiffness CPW-Fed Metal-Only Patch Antenna Array for Unlimited Lifetime 2U CubeSat Mission Capabilities;Jeans-Based UWB UHF Textile Patch Antenna for IoT Applications;Design and Fabrication of PCB-Based Proximity Sensors for Application in Automatic Railway Crossing System;feaTrim-ViT: Vision Transformer Trimming with One Shot Neural Architecture Search in Continuous Optimisation Space and Efficient Feature Selection;detecting Depressive Symptoms on Social Media: A Comprehensive Review of Methodologies and Strategies for Suicide Prevention;enhancing Video Content Accessibility through YouTube Transcript Summarization;Enhanced Rear-End Collision Detection and Localization Scheme Using LSTM, DRNN, and DNN in Fog-Based Internet of Vehicles;security threats and Data Protection Methods Used in Cloud Computing: A Review;load Balancing algorithms for Cloud Computing Performance: A Review;seamless Mobility: Innovating the Digital Service Landscape in Telecom Industry;Pandemic Pulse: Unveiling Insights with the Global Health Tracker through AI and ML;CNN-Based Model for Real-Time Identification of Face Masks;a Systematic Review of Deepfake Detection Using Learning Techniques and Vision Transformer;probabilistic Forecasting Prediction Model for Anticipating Days with Elevated Air Pollution;optimizing Graph Colorings: Unleashing the Power of Heuristic algorithms for Enhanced Problem-Solving;a Load Balancing Approach Using Binary Search;enhancing Software Reliability through Hybrid Metaheuristic Optimization.

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UAV Maritime Search and Rescue Based on Improved A∗ and RCPP algorithms for Path Planning 5

UAV Maritime Search and Rescue Based on Improved A∗ and RCP...

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5th IEEE international conference on Power, Intelligent Computing and Systems, ICPICS 2023

作者： Guo, Yanlu Yi, Jian Hao, Jun Houston International Institute Dalian Maritime University Dalian China

ISBN: (纸本)9798350333442

the purpose of this paper is to realize the path planning of the search and rescue process of the UAV at sea. the first part of this paper wonder to find local optimal path planning from the UAV launch base station to the target area. Meanwhile the next part is to find full-coverage optimal path planning of the UAV in the target area, and to ensure the minimum energy consumption in the process of achieving the goal. For local path planning, this paper adopts the A∗ algorithm as the main algorithm and integrates the DWA algorithm to improve it, for the purpose to reduce the number of UAV turns and turn angles while achieving dynamic obstacle avoidance during the flight. For full-range path planning, this paper adopts the RCPP algorithm to achieve full-area coverage of the UAV on various irregular sea areas, and the energy efficiency of the UAV flight can be improved by determining the best starting and ending points. through the implementation of the two-part algorithm, it can meet the speed and accuracy requirements of maritime UAV search and rescue, ensure the shortest search and rescue time, and achieve the most efficient energy utilization. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Enhancing Natural Language Processing in Multilingual Chatbots for Cross-Cultural Communication 5

Enhancing Natural Language Processing in Multilingual Chatbo...

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5th international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Orosoo, Myagmarsuren Goswami, Indrajit Alphonse, Fredrick Ruban Fatma, Gulnaz Rengarajan, Manikandan Kiran Bala, B. Mongolian National University of Education Alliance University General Management Strategy and Hrm Alliance Bengaluru562106 India School of Business Alliance University General Management Strategy and Hrm Alliance Bengaluru562106 India Institute of Finance and International Management Department of Languages Bengaluru India Jazan University Dept. of English Jazan Saudi Arabia R&d Institute of Science and Technology Vel Tech Rangarajan Dr. Sagunthala Tamil Nadu Chennai6000627 India K.Ramakrishnan College of Engineering Department of Artificial Intelligence and Data Science Trichy India

ISBN: (纸本)9798350385649

In order to promote smooth cross-cultural communication, this research focuses on improving Natural Language Processing (NLP) features within multilingual Chabots. the need for efficient communication across various linguistic and cultural barriers has grown as the world becomes more interconnected. In this context, multilingual Chabot's are essential tools that facilitate easy communication between users of various cultural backgrounds. In order to better understand and respond to a wide range of linguistic details, idioms, and cultural allusions, the research explores ways to improve NLP algorithms. this research investigates how machine learning techniques can be integrated to improve the Chabot's ability to adapt to various linguistic patterns, enabling it to acquire new language skills over time. By implementing an extensive and flexible approach, the proposed approach seeks to transform Natural Language Processing in Multilingual Chatbots for Cross-Cultural Communication. In order to identify language-specific patterns and specifications, the methodology starts with the collection of a diverse dataset that is representative of linguistic variations and cultural contexts. It then uses advanced linguistic analysis techniques like phonetic analysis. the next step is cultural context modelling, which entails building a database enhanced with cultural allusions and language variations unique to a given context that are obtained from various sources. Transfer learning, reinforcement learning for dialogue, and modern algorithms such as Multilingual Unsupervised and Supervised Embeddings (MUSE) for cross-lingual embeddings are all included in machine learning integration. In order to obtain information about language precision and cultural sensitivity, the methodology incorporates interactive surveys and sentiment analysis into a strong user feedback mechanism. the proposed model achieved 98% performance. © 2024 IEEE.

关键词： Embeddings

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

5th International Conference on Data Science, Machine Learni...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

ISBN: (纸本)9789819780426

the proceedings contain 128 papers. the special focus in this conference is on Data Science, Machine Learning and Applications. the topics include: Digitization of Monuments – An Impact on the Tourist Experience with Special Reference to Hampi;resume Parser Using Machine Learning;IOT Based Smart Hydroponics System;comparative Study of Machine Learning and Deep Learning Techniques for Cancer Disease Detection;High thruput Modulation Approaches Used in Next Generation WiF’s Under Multi-impairments Environments with MATLAB Codes;skin Disease Detection;root Vegetable Crop Recommendation System Based on Soil Properties and Environmental Factors;deep Learning Model Development for an Automatic Healthcare Edge Computing Application;Empathetic Conversations in Mental Health: Fine-Tuning LLMs for Supportive AI Interactions;exploring Block Chain Technology with Applications, and Future Prospects;a Comprehensive Review of Soft Computing Enabled Techniques for IoT Security: State-of-the-Art and Challenges Ahead;Performance Analysis of Machine Learning algorithms on Imbalanced Datasets Using SMOTE Technique;An AI Based Nutrient Tracking and Analysis System;power Saving Mechanism for Street Lights System Using IoT;Automatic Login System Using ATTINY85 IC;forecasting Stock Prices: A Comparative Analysis of Machine Learning, Deep Learning, and Statistical Approaches;smart Vision Bot;robots in Logistics: Apprehension of Current Status and Future Trends in Indian Warehouses;smart Healthcare: Enhancing Patient Well-Being with IoT;Detection of B-ALL Using CNN Model and Deep Learning;a Comprehensive Analysis for Advancements and Challenges in Deep Learning Models for Image Processing;a Comprehensive Survey on Enhancing Patient Care through Deep Learning and IoT-Enabled Healthcare Innovations;attention-Based Image Caption Generation.

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A Comparative Analysis of Point Sampling Strategies in Point-based 3D Object Detection 5

A Comparative Analysis of Point Sampling Strategies in Point...

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5th international conference on Image, Video Processing, and Artificial Intelligence, IVPAI 2023

作者： Zhu, Rui Li, Kin fun Guo, Chenchen Huang, Jinmin University of Victoria 3800 Finnerty Road Victoria Canada Akasha Technology Inc. 485c Garbally Road Victoria Canada

ISBN: (纸本)9781510674660

Point-based 3D object detection has been receiving increasing attention as it can preserve the geometric information of a point cloud and avoid quantization errors or information loss caused by voxelization or projection. Point sampling plays an important role in point-based 3D detectors yet has not been thoroughly explored. In this paper, we conduct a comparative analysis of three point sampling strategies to gain a deep understanding of the effect that each strategy imposes on the final performance and intermediate stages of the network. We introduce density-aware sampling and semantic-aware sampling strategies and fit them into the backbone of a lightweight and effective baseline model, aiming to reduce the density imbalance of the point cloud and better utilize semantic information. the density-aware strategy effectively balances the density but the inference time is not suitable for real-time application. Semantic-aware sampling biased on foreground points achieves a 0.19% improvement over the baseline. Analysis on statistics and visualization reveals future research direction. We build our models on the MMDetection3D platform and evaluate performance on the KITTI dataset. © 2024 SPIE. All rights reserved.

关键词： Object detection

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

5th International Conference on Data Science, Machine Learni...

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5th international conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

ISBN: (纸本)9789819780303

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Music Generation with AI technology: Is It Possible? 5

Music Generation with AI technology: Is It Possible?

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5th IEEE international conference on Electronics Technology, ICET 2022

作者： Tang, Haowen Gu, Yikun Yang, Xinyu BNU-HKBU United International Colloge Division of Science and Technology Zhuhai China

ISBN: (纸本)9781665485081

Music generation techniques have made tremendous progress in recent years. through deep learning neural network frameworks, algorithms can generate music that rivals humans. However, current music generation models lack mainstream algorithms and specifications, including algorithm design criteria and model evaluation criteria, and exactly how to evaluate that music generated by a deep learning model is a good piece of music. In this case, we did a literature review for the three most common deep learning models currently used in music generation. these three models are Biaxial-LSTM, DeepJ and MuseGAN. We compared their application scenarios and model evaluation methods to provide a reference standard for subsequent researchers. © 2022 IEEE.

关键词： Music

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Load Shifting of Residential Load for Demand Side Management Using Tunicate Swarm Algorithm 5

Load Shifting of Residential Load for Demand Side Management...

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5th international conference on Data Analytics for Business and Industry, ICDABI 2024

作者： Vaidya, P.D. Gochhait, Saikat Gunasekar, tharmalingam Raghavendran, Prabakaran Lovely Professional University Department of Electrical Engineering Punjab India Constituent of Symbiosis International Symbiosis Institute of Digital and Telecom Management Pune India Vel Tech Rangarajan Dr.Sagunthala R and D Institute of Science and Technology Department of Mathematics Chennai India

ISBN: (纸本)9798350368710

Demand Side Management (DSM) is a critical strategy in the improvement of efficiency and reliability of the electrical system in smart grids. One of the effective DSM strategies is load shifting, which involves changing the timing of electricity consumption to off-peak hours. this paper gives a new approach to load shifting within residential areas through the Tunicate Swarm Algorithm. the TSA is an algorithm inspired by the swarming behavior of marine organisms called tunicates. these organisms are well known for their efficiency in movement and resource use. It is desired, within the scope of the proposed method, to optimize schedules for household appliances towards minimal electricity cost and minimal peak demand. TSA-based load-shifting technique: simulation result comparison with classical techniques - genetic algorithm and particle swarm optimization. It should be stated that the simulation results show a comparison of the performance of this proposed TSA-based technique about cost reduction and the mitigation of peak demand, which outperformed both GA and PSO. the results obtained in this study demonstrated that the TSA-based technique offers much potential for effective residential load management in smart grids, where quantifiable benefits could be derived in terms of energy savings and system stability. In the future, work will focus on real-world implementation and integration with other DSM strategies to enhance the overall efficiency of the electrical grid. this research adds to the ever-increasing bank of bio-inspired algorithms for energy management and acts as a springboard toward further areas of investigation in the field. © 2024 IEEE.

关键词： Cost reduction

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