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 Cluster...
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.
Categorical data classification and clustering are essential to many fields, including pattern recognition, data mining, knowledge discovery, and machine learning. It is crucial to understand how to provide categorica...
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Traditional talking head synthesis algorithms decompose the lips and head pose information from the facial landmark points based on the spatial point registration. In this paper, we show that the hypothesis of the tra...
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Network coding is an applicable technique to enhance the performance of wireless relay networks, in which intermediate nodes are utilized to expand the coverage range and increase communication reliability. The utiliz...
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As the prevalence of Online Social Networks (OSNs) are created, it is apparent that questions related to ethics and privacy become more ambiguous and this paper aims at giving an overview on privacy concomitants and e...
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Electronic Medical Records (EMRs), while integral to modern healthcare, present challenges for clinical reasoning and diagnosis due to their complexity and information redundancy. To address this, we proposed medIKAL ...
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An Internet of Things based smart irrigation system for terrace plants is a cutting-edge solution designed to automate and optimize the watering process, ensuring efficient use of water and promoting healthier plant g...
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This paper proposes an adaptive multispectral pedestrian detection method that leverages multispectral data and optimizes both channel attention and spatial attention mechanisms. To address varying illumination intens...
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This paper presents a study conducted to classify emotions in social media texts using machine learning. With the rapid increase in the amount of data in digital media, efficient and highly accurate methods for analyz...
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This paper proposes a Salp Swarm Algorithm (SSA), a unique optimization technique for the synergistic integration of renewable energy and High Voltage Direct Current (HVDC) technology to enhance the performance of mul...
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ISBN:
(纸本)9789819770038;9789819770045
This paper proposes a Salp Swarm Algorithm (SSA), a unique optimization technique for the synergistic integration of renewable energy and High Voltage Direct Current (HVDC) technology to enhance the performance of multi-objective economic emission dispatch (MODED). The primary aim is to optimize both the economic and environmental aspects of power systems. A mathematical model for MODED based on Wind-Solar-Thermal integrated energy has been carefully constructed, considering variables like the valve point effect, equality constraints, and inequality constraints. The study determines optimal generation levels and associated costs for six thermal generating units under various power demands, exploring diverse scenarios such as Economic Dispatch for High Voltage-Alternating Current (HVAC) with Losses, Economic Dispatch for HVDC with Losses, Economic Dispatch for HVDC addressing challenges related to voltage instability, protection difficulties and losses in DC systems, Economic Dispatch HVAC & HVDC with Losses and Economic Dispatch for HVAC & HVDC with Renewable Energy (RE). To validate the model, tests have been conducted on the IEEE 30 Bus System with a substantial presence of renewable energy.
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