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18th international KES conference on Agents and Multi-Agent systems: Technologies and Applications, KES-AMSTA 2024

18th International KES Conference on Agents and Multi-Agent ...

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18th international KES conference on Agents and Multi-Agent systems: Technologies and Applications, KES-AMSTA 2024

ISBN: (纸本)9789819764686

The proceedings contain 34 papers. The special focus in this conference is on Agents and Multi-Agent systems: Technologies and Applications. The topics include: Fair Path Generation for Formation Control Combining Ant Colony and Particle Swarm Optimizations;preference Definition in a Multi-agent System Approach for User-Centric internet of Things Smart Environments;AI-Driven Nitrogen Stress Management in Cereal Crops via Drone technology;agent-based Simulation for Withdrawal of Energy-Inefficient Housing;resource Limitations of Business Process Simulations: Literature Study;data Augmentation for Business Process Alignment: Proof of Concept and Experimental Design;smart Scheduling in Urban Traffic: A Multi-Agent System for Dynamic Vanpooling;analysis of the Impact on Area Prices Using Propensity Score Matching, Considering the Proportions of Photovoltaic and Thermal Power Generation Simultaneously;consideration of Building a Simulator to Evaluate Methods to Maximize the Effectiveness of Advertising to Households;Human-AI-Collaboration SECI Model: The Knowledge Management Model of the Experts’ Tacit Knowledges with Augmented LLM-based AI;modeling Agent Awareness After Hierarchical Managerial Training;development of An Application for Extracting Needs Related to Actual Gas Use Using Text Mining;Impact of Intelligent systems in the Home Office on Employee Satisfaction—Lessons Learned from the COVID-19 Pandemic;agile Methodologies in Software Development: A Study of Effective Management Strategies for Companies in the Digital Era;predictive Analysis of Cyclical Sales Data;EMG signal Classification Using Machine Learning for Augmentative Assistance in Cerebral Palsy;wellnessWave—Platform for the Digitization of the Romanian Public Medical System;TRIAGE Predictive Model based on Artificial Neural Networks and Deep Learning;platform for Automated Assessment of Obstetric Ultrasounds, Using Machine Learning;identification of Fonts in Unstructured Environments Through Deep Lea

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15th EAI international conference on Bio-inspired Information and Communications Technologies, BICT 2024

15th EAI International Conference on Bio-inspired Informatio...

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15th EAI international conference on Bio-inspired Information and Communications Technologies, BICT 2024

ISBN: (纸本)9783031815980

The proceedings contain 16 papers. The special focus in this conference is on Bio-inspired Information and Communication Technologies. The topics include: Optimizing Drug Delivery Strategies by Pathway Analysis for Waveform Modulation-based Molecular Communication;Enhancing DNA-based IoBNT Throughput and Reducing Congestion with Yin-Yang Coding;a Molecular Communication Model Driven by Magnetic Field Force;CDM based on Izhikevich Neuron Model;multi-user Diffusive Molecular Communication systems with A Passive Relay Node: Receiver Design and Performance Analysis;machine Learning-based Detection Time Estimation for Molecular Communication;taming signal-Dependent Counting Noise with Machine Learning for Molecular Communication;energy-Efficient Transmitter Creation in Molecular Communication;a Method for Determining Relay Node Location in Molecular Communication;glycemic Oscillation Decomposition-based Personalized Blood Glucose Prediction with Continuous Glucose Monitoring;A Compact Bio-inspired Microstrip Antenna (Bi-MPA) for Medical Microwave Imaging Applications;image Encryption and Decryption Algorithm based on DNA Sequence: Performance Analysis of Channel Fusion Processing;Optimizing the Classification of SSVEP signals in Brain-Computer Interfaces: A Novel Sliding Window Data Segmentation Method based on Weighted Voting Mechanism;spontaneous Motion of Nanorobots Inspired Computational technology for Tumor Boundary Exploration.

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12th international conference on Recent Trends in Computing, ICRTC 2024

12th International Conference on Recent Trends in Computing,...

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12th international conference on Recent Trends in Computing, ICRTC 2024

ISBN: (纸本)9789819789450

The proceedings contain 34 papers. The special focus in this conference is on Recent Trends in Computing. The topics include: Deep Learning-based Prediction of Human Ageing Related Proteins;the Insight of Clustering Algorithms for Emerging Networking Paradigms;Revolutionizing Cardiovascular Health: Exploring the Potential of AI-Driven Approaches in Diagnosing Arrhythmia Disorders;humor Detection in Telugu Social Media Text Using Cost-Sensitive Learning and Indian Language Embeddings;empirical Comparison of Sleep Disorder Prediction Using Machine Learning Techniques;securing Smart Grids: Decentralized Anomaly Detection Using Federated Learning and Recurrent Neural Networks;machine Learning-Powered Intrusion Detection for Network Security;secure Chat System: Harnessing the Power of Hybrid Encryption for Enhanced Security and Confidentiality;deep Neural Networks for Early Diabetes Mellitus Prediction;advancements in image Deblurring and Performance Metrics Using Deep Learning Technique;emotion-Levitating Music Recommendation System Through Real-Time Facial Recognition;smartVoice TrashMate: The Intelligent Voice-Controlled Trash Bin;an Innovative image Enhancement Algorithm for Color Filter Array images: A Novel Approach;Enhancing Secure and Efficient Communication in Free-Space Optical Networks Using Spectral Amplitude Coding - OCDMA technology;enhancing Citrus Fruit Classification and Quality Assessment Through Advanced Machine Learning Techniques;connecting Health for a Better Tomorrow Through internet of Medical Things;image Processing in Retail Marketing: Innovations for Customer Engagement, Sales, and Operational Efficiency;Leaf Checker: AI-based Plant Diagnostic Tool Using Alexnet and Mobilenet;ioT-Supported Indoor Navigation System Using Machine Learning Technique;a Customizable Virtual Assistant Enhanced with Vision and Speech Capabilities;An Unequal Cluster-based Routing Mechanism Using Lyrebird Optimization Algorithm to Achieve Network Longevity in WSNs.

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12th international conference on Recent Trends in Computing, ICRTC 2024

12th International Conference on Recent Trends in Computing,...

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12th international conference on Recent Trends in Computing, ICRTC 2024

ISBN: (纸本)9789819788354

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Dual Space DTR-net Learning based Heart Disease Prediction 3

Dual Space DTR-net Learning based Heart Disease Prediction

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3rd international conference on Intelligent Data Communication Technologies and internet of Things, IDCIoT 2025

作者： Maragatham, T. Vanitha, K. Sivarajan, R. Department of Computer Technology-PG Kongu Engineerning College Erode India Department of CSE Karpagam Academy of Higher Education Coimbatore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

The biggest cause of death worldwide is a heart attack. If a heart attack can be identified early and treated right away, many lives can be spared. In this study, we suggest a wireless ECG sensor connected to an in-dash ECG monitoring system as the basis for a heart attack detection and alert system. We employ an artificial neural network (DTR Net) pretrained model on ECG signals for heart attack detection. When a heart attack is discovered, the system immediately uses a satellite communication system to notify co-passengers, local hospitals, and paramedics. The suggested solution comprises a wireless ECG sensor that is fastened to the driver’s body and sends ECG signals to an ECG monitoring system built into the car’s dashboard. signal processing methods are used to extract the characteristics after the ECG signals have undergone preprocessing to reduce noise and artefacts. The DTR Net model for heart attack detection is then fed the retrieved features. To precisely identify the existence of a heart attack, the DTR Net model is trained using a substantial dataset of ECG signals. When the DTR Net model recognizes a heart attack, the system immediately sends out a satellite communication system alert to co-passengers, local hospitals, and ambulances. This enables quick medical care to be given, possibly saving lives. In conclusion, our suggested approach for early heart attack detection and alerting in automobiles, which combines a wireless ECG sensor with an DTR Net model, is reliable and effective. By automatically alerting local hospitals, ambulances, and fellow passengers, the technology makes sure that immediate medical assistance is given, potentially saving lives. The technology can reduce fatalities and improve road safety by enabling immediate medical care. © 2025 IEEE.

关键词： Satellite communication systems

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9th EAI international conference on IoT as a Service, IoTaaS 2023

9th EAI International Conference on IoT as a Service, IoTaaS...

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9th EAI international conference on IoT as a Service, IoTaaS 2023

ISBN: (纸本)9783031705069

The proceedings contain 33 papers. The special focus in this conference is on IoT as a Service. The topics include: Highway Obstacle Recognition based on Improved YOLOv7 and Defogging Algorithm;cloud Gaming Resource Management Platform based on Edge Intelligence;hardware-Efficient Polar Decoder for 5G internet of Things Communication;Design and Optimization of a Solar-Powered IRS and Relay Assisted MEC System;highway image Enhancement Method based on Jade;method and Practice of Borehole Group Detection in Borehole Drilling based on Six-Axis Sensing;Deep Reinforcement Learning-based Channel and Power Allocation in Multibeam LEO Satellite systems;CSI-based signal Reconstruction for WiFi Localization;an Indoor Navigation Algorithm Using Multi-dimensional Euclidean Distance and the Adaptive Particle Filter;Research on the PID Controllers Algorithm of the Quad Rotor;based on the Nonlinear State Equations of 6-DOF Robot with Application to Autonomous Flight;a Study on Collaborative Lane Change Decision Making of Multi-automated Vehicles based on Deep Graph Reinforcement Learning;a Short Term Traffic Prediction Model based on Deep Capture of Temporal Periodic Drift;multi-agent Reinforcement Learning for Cooperative On-Ramp Merging of Connected Automated Vehicles;SVM Multi-class Classification Method for Device Identification Using Eye Diagram Parameters;users Collaborative Computing for Hierarchical Federated Learning based on Incentive Mechanism;spatio-Temporal Traffic Prediction of Wireless Communication Network based on Multi-source Data;flying Ad-Hoc Network Routing Protocol based on Backward Algorithm;A Novel HPSO-IGWO Algorithm for Rapidly Searching Optimal Fire Rescue Paths based on IoT Architecture;A Hybrid WOA-MTCNN Algorithm for Accurate Face Detection based on IoT Architecture.

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EMG-based prosthetic arm 1st

EMG-based prosthetic arm

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1st international conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Kumar, Nishit Ranjan, Ravi Singh, Sachin Pal, Purnima Department of Electronics & Communication Engineering Noida Institute of Engineering and Technology Noida India

ISBN: (纸本)9781032874036

Advancements in electromyography (EMG) technology have open the wayfor the development of advanced prosthetic arms aimed at providing enhanced functionality and more natural control for individuals with upper limb amputations. This paper provides an overview of an EMG-based prosthetic arm system designed to improve the interaction between users and their prosthetic limbs. The proposed system relies on surface EMG signals produced from muscles in the user’s remaining limb. These signals are captured by a set of electrodes were placed on the skin surface and processed using machine learning algorithms to interpret the user’s intended movements. Through analysis of EMG signal patterns and amplitudes, the system can accurately identify desired actions such as grasping, releasing, and manipulating objects. Incorporating state of art actuation mechanisms and sensory feedback systems, the EMG-based prosthetic arm aims to deliver a more experienced and knowledgeable user. By employing advanced motor control algorithms, the prosthetic armcan replicate human limb movements and exert appropriate forces." Moreover, sensoryfeedback components such as pressure sensors and tactile interfaces allow users to perceive forces and textures during object manipulation, thereby enhancing dexterity and overall functionality. Extensive user trials involving individuals with upper limb amputations have been conducted to evaluate the effectiveness of the EMG-based prosthetic arm system. The results demonstrate notable enhancements in users’ ability to control the prosthetic arm, carry out daily tasks, and experience a sense of embodiment. © 2025 the Author(s).

关键词： Sensory feedback

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A Cooperative Spectrum Sensing Method based on Feature Extraction and Fusion Clustering 14th

A Cooperative Spectrum Sensing Method Based on Feature Extr...

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14th EAI international conference on Wireless and Satellite systems, WiSATS 2024

作者： Li, Jian Li, Yue Chen, Xiaoxu Heilongjiang University Harbin150080 China

ISBN: (纸本)9783031861956

To improve the performance of spectrum sensing at low SNR, a collaborative spectrum sensing method based on feature extraction and fusion clustering is proposed (FEFC). First, the sampling matrix of the received signal is vectorially decomposed to obtain the I and Q component signals. Second, Cholesky decomposition is applied to the covariance matrices of the I and Q signals to fully extract their features and construct the two dimensional feature vectors. The K-Means clustering algorithm is used to optimize the initial parameters of the Gaussian Mixture Model (GMM), effectively preventing it from falling into local minima under low SNR. Finally, the feature vectors of the signals are classified using GMM clustering optimized by the K-Means algorithm to obtain the final spectrum sensing results. Simulation results show that this method reduces the convergence time of GMM and improves the accuracy of model classification. It effectively enhances the performance of spectrum sensing compared to other mainstream methods. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： signal to noise ratio

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An Important and Successful Multi-image Stereography-based Secret Communication System for Military Applications 12th

An Important and Successful Multi-image Stereography-Based S...

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12th international conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2024

作者： Ravi, C.N. Suhasini, T.S. Narasimharao, Jonnadula Mahendar, A. Amruthraj, B. Venkateswara Reddy, R. Department of Computer Science and Engineering CMR Engineering College Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India Department of Computer Science and Engineering CMR Technical Campus Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India Department of Computer Science and Engineering CMR College of Engineering and Technology Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601387

A significant factor in data transfer is computer science. Security considerations make it difficult to transmit sensitive data or have conversations via the internet. Typically, cryptography is used to transmit text-based underground messages and conceal in sequence. These days, there are numerous methods for concealing information on any media. A technique like this is steganography. The creation of a covert communication system that uses multi-image steganography will enable safe communication among the dispatcher and the recipient free from hacker intervention. image steganography is the main technique for information hiding. It involves integrating the cipher text within a picture called the cover picture that is very difficult for strangers to view through an unassisted eye. Within a cover image, the concealed data may take the shape of any kind of text, picture, music, or even video. The secret code is split up into several pieces and etched into several cover images, according to the conceptual notion of multi-image steganography. Thus, in order to make it extremely difficult for the hackers to hide the data, we suggested two image steganography concepts. In order to create a safe and protected system, this learning suggest by means of the Advanced Encryption Standard (AES) approach of cryptography with the Least Significant Bit (LSB) method of steganography. Here, a symmetric key—which is used by both the sender and the recipient to encrypt and decode data—is used by both parties. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Stereo image processing

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SelaFD:Seamless Adaptation of Vision Transformer Fine-tuning for Radar-based Human Activity Recognition

SelaFD:Seamless Adaptation of Vision Transformer Fine-tuning...

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2025 IEEE international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Wang, Yijun Wang, Yong Xu, Chendong Yao, Shuai Wu, Qisong Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

ISBN: (纸本)9798350368741

Human Activity Recognition (HAR) such as fall detection has become increasingly critical due to the aging population, necessitating effective monitoring systems to prevent serious injuries and fatalities associated with falls. This study focuses on fine-tuning the Vision Transformer (ViT) model specifically for HAR using radar-based Time-Doppler signatures. Unlike traditional image datasets, these signals present unique challenges due to their non-visual nature and the high degree of similarity among various activities. Directly fine-tuning the ViT with all parameters proves suboptimal for this application. To address this challenge, we propose a novel approach that employs Low-Rank Adaptation (LoRA) fine-tuning in the weight space to facilitate knowledge transfer from pre-trained ViT models. Additionally, to extract fine-grained features, we enhance feature representation through the integration of a serial-parallel adapter in the feature space. Our innovative joint fine-tuning method, tailored for radar-based Time-Doppler signatures, significantly improves HAR accuracy, surpassing existing state-of-the-art methodologies in this domain. Our code is released at https://***/wangyijunlyy/SelaFD. © 2025 IEEE.

关键词： Fine-Tuning Human Activity Recognition Time-Doppler Vision Transformer

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