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2024 3rd international conference on Smart Technologies and systems.for Next Generation computing, ICSTSN 2024

2024 3rd International Conference on Smart Technologies and ...

引用

3rd international conference on Smart Technologies and systems.for Next Generation computing, ICSTSN 2024

ISBN: (纸本)9798350391565

The proceedings contain 99 papers. The topics discussed include: parsed region feature extraction method for hepatocellular carcinoma detection using medical images;predicting cyber-attacks and identifying perpetrators using machine learning techniques;enhanced real-time abnormal event detection in video surveillance for safety and security;an analysis of frequency response in integrated power system using power electronics controller tuned with whale optimization technique;classification of Alzheimer’s disease with generated MRI images using randomized CNN;data mining framework for discovering and clustering phenotypes of atypical diabetic lung;analyzing depression in social media: a study of basic deep learning algorithms and transformer model with a comparative approach;and gamifying language learning: applying augmented reality and gamification strategies for enhanced English language acquisition.

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An Adaptive Load Balancing Strategy for distributed Machine Learning 3

An Adaptive Load Balancing Strategy for Distributed Machine ...

引用

3rd international conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2023

作者： Min, Haozhe Xue, Meiting Zhu, Weibo Zeng, Yan Zhao, Nailiang Zhang, Jilin Hangzhou Dianzi University College of Cyberspace HangZhou China Hangzhou Dianzi University School of Computer Seience and Techrology HangZhou China

ISBN: (纸本)9798350302356

Within a distributed deep learning training system, variances in performance among computing nodes, as well as the influence of external environmental factors, can result in training interruptions or reduced convergence speed. As such, this paper presents an approach to address this issue by proposing a dynamic task allocation strategy among nodes, aimed at mitigating the impact of performance discrepancies on the training efficiency of distributed deep learning systems. This proposed approach is referred to as the 'Auto weight-based load balancing strategy' (Auto-WLBS) and involves dynamically adjusting the task allocation among computing nodes based on their performance characteristics. In order to maximize computing power while minimizing the lag effect on the training of the entire system, Auto-WLBS partitions and alters the errands by introductory division and halfway alteration. Combined with LSP model, AW-LSP model is proposed. Finally, a comparative experiment was conducted on the cifar10 and cifar100 datasets, and Auto-WLBS was experimentally verified from the perspective of model training loss function changes, model accuracy, and training time. The experimental findings demonstrate that compared to the BSP model, SSP model, and LSP model, the AW-LSP model has a smaller communication overhead, and the communication overhead can be reduced by up to 23.70%. Compared with the SSP model and the LSP model, the model accuracy can be improved by up to 14.5% and 8.6%, respectively. © 2023 IEEE.

关键词： computing power

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distributed Fault Diagnosis System Based on Machine Learning 3

Distributed Fault Diagnosis System Based on Machine Learning

引用

3rd international conference on Intelligent computing, Communication and Convergence, ICI3C 2023

作者： Guan, Mengru Fu, Yanyou Wang, Zhaoyue Zhang, Jiaqian Sias University Henan China

ISBN: (纸本)9798350343922

This research focuses on the development of a machine learning-based distributed fault diagnosis system that aims to improve the accuracy and real-time detection of faults in large-scale distributed systems. By deeply analysing key information such as log data, performance metrics, and network traffic of distributed systems. we design adaptable machine learning algorithms to handle distributed environments of complexity and large scale. In our research, we pay special attention to real-time fault diagnosis to detect and diagnose faults in a timely manner by monitoring and analysing the data flow of distributed systems.in real time, thus minimising the potential impact on the system. The proposed machine learning algorithms are not only able to handle large-scale datasets efficiently, but also have the flexibility to adapt to different system architectures and network topologies, while exhibiting good scalability and robustness. In addition, we attempt to introduce an augmented learning approach to enable the fault diagnosis system to actively learn and optimise in order to maintain an efficient fault diagnosis capability in a dynamic and distributed environment. This innovative approach is expected to further improve the system's adaptability to emerging fault modes, thereby enhancing the system's intelligence and self-optimisation capabilities. Overall, this study introduces advanced techniques in machine learning for fault diagnosis in the field of distributed systems.and lays the foundation for a more accurate, real-time and intelligent fault diagnosis system. © 2023 IEEE.

关键词： Adversarial machine learning

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Troll and Abuser Identification in Social Media for Code-Mixed English, Bangla, and Banglish Text Analysis Using LLMs 3

Troll and Abuser Identification in Social Media for Code-Mix...

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3rd international conference on Intelligent computing and Next Generation Networks, ICNGN 2024

作者： Nezami, Mohammad Arif Nurul Huda, Mohammad Masters of Science in CSE United International University Dhaka Bangladesh Dept. of CSE & Head of Dept United International University Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798331529222

Social networking platforms have become our center for daily communication. These networks removed all the barriers that used to exist by providing open platform for sharing thoughts, keeping in touch with friends, and even voicing for what we believe in. Unfortunately, this has also opened the door for trolls and online bullies to run rampant. Along with democratizing communication, these platforms have created a distinctive vocabulary, such as the widespread usage of emojis, which are particularly well-liked by younger audiences."Banglish" a hybrid language that combines Bengali and English is widely used by Bengalis around the world. It creates serious difficulties for traditional content filtering systems. This study examines how to identify trolls and abusive content in Banglish text using sophisticated large language models (LLMs), such as OpenAI GPT-4, Google Gemini, and Meta LLaMA. Our goal is to use these models to improve the security and reduce the toxicity of social media environments, ensuring a more secure online experience for all users. ©2024 IEEE.

关键词： Social networking (online)

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Real-Time Sign Language Recognition using Machine Learning and CNN-based EfficientNetB3 for Accessible Communication 3

Real-Time Sign Language Recognition using Machine Learning a...

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3rd international conference on Automation, computing and Renewable systems. ICACRS 2024

作者： Mizan, Zabir Ibna Aidelkhani, Farzam Reza, Khandaker Tasfia Bhuiyan, Tanbir Hasan Alom, Munzirul Tuhin, Saiful Islam Dhaka Bangladesh Dhaka Bangladesh Dhaka Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798331532420

This research analyzes the challenges faced by Sign Language Recognition (SLR) systems.by evaluating the performance of EfficientNetB3, Inception-v3, and GoogLeNet models. Using a dataset of 27,000 American Sign Language (ASL) images across 27 classes, EfficientNetB3 emerged as the top performer. After fine-tuning the model with the full dataset, it achieved a test accuracy of 99.53%. We then integrated this optimized model into a real-time, user-friendly Android app for sign language recognition, offering a valuable tool for enhancing communication accessibility, particularly for the deaf and hard-of-hearing. This research work contributes to advancing SLR and promoting inclusive communication. © 2024 IEEE.

关键词： Convolutional neural networks

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proceedings - 2024 3rd international Joint conference on Information and Communication Engineering, JCICE 2024

Proceedings - 2024 3rd International Joint Conference on Inf...

引用

3rd international Joint conference on Information and Communication Engineering, JCICE 2024

ISBN: (纸本)9798350388725

The proceedings contain 46 papers. The topics discussed include: building a cancer type prediction model based on machine learning algorithms by analyzing the origin genes of multiple cancers including prostate cancer;cross-domain specific emitter identification based on domain adversarial multi-constraint;a robust defense algorithm for backdoor erasure based on attention alignment in federated learning;research and design of data link twin system;a simple image denoising method associated with image edge protection;research on optimal allocation of integrated resources of mergers and acquisitions based on distributed cloud computing;power control based on deep Q learning in heterogeneous networks;HybridTrajNet: enhancing pedestrian trajectory prediction with multi-scale attention and large selective kernel;and a method for essential proteins identification by integrating topological and biological characteristics in PPI network.

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3rd international conference on Intelligent computing Techniques for Smart Energy systems. ICTSES 2023

3rd International Conference on Intelligent Computing Techni...

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3rd international conference on Intelligent computing Techniques for Smart Energy systems. ICTSES 2023

ISBN: (纸本)9789819784639

The proceedings contain 50 papers. The special focus in this conference is on Intelligent computing Techniques For Smart Energy systems. The topics include: Analysis of Fault and Current-Limiting Methods in the Power System;UDS for Data Communication in Temperature Monitoring;approximation in the Weighted Lipschitz Class by (C,α,θ)(E,q) Mean of Its Fourier Series;demand Response and Load Profile Analysis in Modern Electricity systems.First-Principles Study of the Structural, Optical and Electronic Properties of Zinc Blende GaN Through PBEsol and TB-mBJ Functionals;optimization-Based Cost Analysis for Energy Management System in Microgrids;classification and Prediction of Knee Osteoarthritis by Deep Learning Approach;Predicting Stock Price and Market Direction Using Statistical and LSTM Models;Comprehensive Evaluation of Time Management with Balancing Resistors in Passive Cell Balancing Using the 1RC Model;PAWnnect: Pioneering IoT-ML Driven Pet Monitoring;transactive Energy Management for Microgrids: Peer-To-Peer Trading Using Stackelberg Game Approach;Unravelling the Mind's Emotions: A Review of EEG-Based Emotion Detection Using Machine Learning and Deep Learning;unlocking IoT Security: Enabling the Future with Lightweight Cryptographic Ciphers;Optimal Design of Nano Scale Voltage Amplifier Using Evolutionary Techniques for DG-MOSFET;flower Patterned with Elliptical Petals Multiband Microstrip Fractal Patch Antenna for Wireless Applications;Optimal Scheduling of Solar PV Generators and Network Assets in Distribution Network;revolutionizing Biomedical Engineering with Microcontroller Applications: A Comprehensive Review;investigation of Battery Temperature Impact on High Voltage Cable of Electric Vehicles;deep Learning Technique for Computer Vision-Based Pose Estimation for Augmented Reality;Rectangular Shape Patch Antenna with Defected Ground Plane for 5G Sub 6 GHz Wireless Communication systems.

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3rd international conference on Intelligent computing Techniques for Smart Energy systems. ICTSES 2023

3rd International Conference on Intelligent Computing Techni...

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3rd international conference on Intelligent computing Techniques for Smart Energy systems. ICTSES 2023

ISBN: (纸本)9789819784288

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Research on Network Security Protection Techniques for the Central Station Side of distributed Power Dispatch and Control systems 3

Research on Network Security Protection Techniques for the C...

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2023 IEEE 3rd international conference on Data Science and Computer Application, ICDSCA 2023

作者： Zhang, Xiao Wang, Youhuai Zhang, Wenlu State Grid Hubei Electric Power Co. Ltd. Wuhan China

ISBN: (纸本)9798350341546

This research focuses on the study of network security protection techniques for the central station side of distributed power dispatch and control systems. It covers various aspects such as vulnerability discovery, information interaction security, device management, and threat tracing. The aim is to propose an integrated, multi-dimensional, and multi-level security protection system that combines active and passive data security measures and security analysis methods to ensure the safety and reliability of the distributed power dispatch and control systems. © 2023 IEEE.

关键词： Device Management distributed Power Dispatch and Control System Information Interaction Security Network Security Vulnerability Discovery

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Design and implementation of 5G communication device for distributed energy monitoring 24

Design and implementation of 5G communication device for dis...

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3rd international conference on Cryptography, Network Security and Communication Technology (CNSCT)

作者： Sun, Jingchao Zheng, Fei Wu, Yujun Wang, Chaotai Guilin Univ Elect Technol Guilin Peoples R China

ISBN: (纸本)9798400716959

With the continuous development and expansion of new energy devices, the user group using distributed energy technology is also expanding. distributed Multi-energy systems.(D-MES) can sustainably transform the energy supply of buildings, regions, and communities by integrating multiple energy-saving technologies, renewable energy sources, and electricity, gas, and thermal networks to provide heating, cooling, and electricity services[9].distributed energy monitoring device is also more and more development prospects, especially in the country, due to energy and environmental issues more and more people's attention, the construction and use of new energy devices have been strongly supported by the government,distributed energy monitoring devices have become an important part of the stable operation of the distributed energy system. In this paper, a distributed energy monitoring device based on 5G technology is proposed. Through the interconnection of monitoring equipment and energy equipment, real-time data collection, analysis and control are realized. The device combines the distributed energy system and 5G communication technology, and has the advantages of flexibility, high efficiency and security. Through the analysis of experiments and application cases, it has also been verified.

关键词： distributed energy monitoring device 5G communication embedded system

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