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Full Description
The book presents selected papers from the International Conference on Data Science and Communication (ICTDsC 2023) organized by the Department of Electronics and Communication Engineering and Department of Engineering Science and Humanities (DESH) Siliguri Institute of Technology, India during 23 - 24 March 2023 in Siliguri, India. The book covers state-of-the-art research insights on artificial intelligence, machine learning, big data, data analytics, cyber security and forensic, network and mobile security, advanced computing, cloud computing, quantum computing, electronics system, Internet of Things, robotics and automations, blockchain and software technology, and digital technologies for future.
Contents
Compensation Effect in the Collisional Turbulent Plasma.- Role of pre-processing in gene selection using DNA microarray gene expression data.- Determination of Suitable Frequency for Underground Electromagnetic wave propagation.- A Comparative Study on Speech Emotion Recognition using Machine Learning.- Early Prediction of Urban Flood Using ML and IoT.- Development of Low power and Area Efficient Multi-Core Memory Controller Using AXI4-Lite Interface Protocol.- Improved Analog Costas Loop with Fuzzy Logic Controller.- Authentication Framework for an IoT Ecosystem.- Design and Analysis of 28 GHz Microstrip Patch Antenna for 5G Network.- Upper bounds of worldwide infected cases due to COVID-19 from the perspective of bitopology.- Prediction Model for Precision Agriculture using Machine Learning.- Analysis and Implementation of Resonative Tuning Fork Sensor in Ash Hopper for Economical Ash Air Compressor Operation with Integrated IoT System.- Challenges and Approaches in Arabic Sentiment Analysis: A Review.- Performance Based Comparative Analysis Of Naive Bayes Variations For Text Classification.- Coreference Resolution in the Assamese Language: A Pioneering Attempt.- Application for Simulating OWASP Vulnerabilities.- A Comparative Study of Disease Detection in Potato Plants Using Machine Learning and Deep Learning Method.- An Enhancement in Accuracy for Breast Cancer Prediction Using Machine Learning And Deep Learning Model.- Fractal Features For Texture Analysıs.
