Advances in Computational Intelligence and Its Applications

It is with great pleasure and enthusiasm that we welcome you to the International Conference on Advances in Computational Intelligence and its Applications (ICACIA-2023). In the ever-evolving landscape of technology, computational intelligence stands as a cornerstone, shaping the future of diverse fields and industries. This conference serves as a nexus for researchers, academicians, and industry experts to converge, exchange ideas, and explore the latest advancements in the realm of computational intelligence.

Table of Contents:
1. A Non Conventional Pre-Processing Method for Financial Risk Analysis Data 2. An Analytical Study of Sentimental Analysis During COVID-19 Pandemic 3. SQL Injection Attacks: Exploiting Vulnerabilities in Database Systems 4. Energy Efficient Clock Synchronization Method in IoT Applications 5. Farm to Home: An e-commerce Application for Farmers and Consumers 6. Smart Farming: The Future of Agriculture 7. Literature Review Energy Efficient i Street Lighting System 8. Robotics in Medical and Health Care: A Critical Review 9. Automatic Speed Control of Vehicles at Accident Zone10. Crime Detection Using Vehicle Number Plate 11. Automated Speech Analysis for Early Identification and Prediction of Depression: A Comprehensive Study 12. An Ensemble Approach for Pneumonia Detection from Chest X-rays 13. A Novel Concurrent Data Collection Protocol for IoT Networks 14. Implementation of Converting Indian Sign Language into Indian Language Using IoT-based Machine Learning Algorithms 15. A Comprehensive Survey on Deep Fake Object Creation and Detection: Challenges, and Future Directions 16. Development of Renal Tumor Accuracy Prediction Model Using Machine Learning Algorithms 17. Attendence System based on Viola-Jones Algorithm and PCA 18. Encipher Image Transmission Through MIMO System with Rayleigh Fading Environment Using AES Encryption Algorithm 19. A Comparative Study of Stock Return’s Analysis and Prediction with the Impact of Macroeconomic Variables Using SVM and LSTM 20. Machine Learning Model for Improving the Overall Equipment Effectiveness in Industrial Manufacturing Sites 21. Hashgraph and Fog Computing Based Novel Framework for Online Teaching-Learning and Content Delivery 22. A Review of Churn Prediction in Telecommunication Industry 23. Speech Emotion Recognition (SER) on Live Calls While Creating Events 24. Predicting Malignancy from Breast Histopathological Images Using Deep Neural Networks and Baseline Classifiers 25. Framework for Home Layout Design by Semantic Parsing of Text 26. URL Phishing Prediction with GUI Implementation Using Machine Learning 27. Smart Farming with Fire Security System 28. Generation of 3D Images from Single View 2D Images Using Autoencoder 29. Attention Based Bidirectional LSTM Model for Data-to-text Generation 30. A Conceptualized Study on Blockchain Technological Algorithms, Cyber-Attacks and Application Perceptions 31. Computation of Environmental Deterioration by Observation of Annual NDVI Changes32. Comparative Analysis of Deep Learning Techniques for Fast Detection of COVID-19 Using CXR Images 33. Accident Evasion and Warning System 34. Crowd Counting for Risk Management Using Deep Learning 35. Tamil Character-Size Reduction Method for Storage of Large Amount of Data 36. Stochastic Modelling and Real Time Solution for SCPP Problem for the Internet of Vehicles (IoV) 37. Security Level Detection of Cryptosystems Using Machine Learning 38. Colorization of Black and White Image and Video Using CNN 39. Detection Mechanism for the Analysis of Malicious Script to Safeguard the Networked Systems 40. An Electromyography Based System for Sitting and Walking Postures 41. Comparison of Latency Minimisation Techniques and Performance Evaluation for Application Mapping in RTNoC (Real Time Network on Chip) 42. Classification of Customers Using Machine Learning 43. Phishing Website Detection Using Machine Learning 44. VANET Routing Protocol Using Particle Swarm Optimization

About the Author :
Dr. Sheikh Fahad Ahmad received his Ph.D. degree in Computer Science and Engineering from Babu Banarasi Das University Lucknow, U.P. in the year 2020. He received his M. Tech and B.Tech in Computer Science & Engineering in the year 2013 and 2008 respectively from Integral University, Lucknow, U.P. India. He is currently working as an Associate Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad. He has more than 13 years of teaching experience in reputed Universities. He is also the member of Editorial Boards, Program and Technical Committees of many International Journals as well as he is in the advisory committees of many International Journals. Currently he is supervising six candidates in PhD Program and he has around 30 International Publications and 3 Patents. His research areas include Sound analysis, Pattern Recognition, Machine Learning, and Data Science. Dr. Shadab Siddiqui received his Ph.D. degree in Computer Science and Engineering from Babu Banarasi Das University Lucknow, U.P. in the year 2021. He received his M. Tech (Computer Science) 2014 Integral University, Lucknow, U.P. India. He is currently working as an Assistant Professor in Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad. Total Experience of 10 Years in Academics. His research interest includes Cloud Computing, Artificial Intelligence and Wireless Sensor Networks. Also, reviewer in various International Journals and Conferences. Dr. Rajib Debnath received his Bachelor of Technology (Information Technology) degree from Bengal Institute of Technology and Management, Shantiniketan, West Bengal, India, in 2010. Masters in Technology (Computer Science and Engineering) and Doctor of Philosophy (Ph.D) under Computer Science and Engineering Department of Tripura University (A Central University), Suryamaninagar, Tripura, India in 2012 and 2022 respectively. Currently working as an Assistant Professor in Koneru Lakshmaiah Education Foundation (Deemed to be University) Hyderabad, India. His topics of interest are related to the field of Computer Vision, Object Detection, Machine Learning, Image and Video Processing etc. Dr. Kakali Das received her Bachelor of Engineering (Computer Science and Engineering) degree from Tripura Institute of Technology, Tripura, India in 2012, Masters in Technology (Computer Science and Engineering) degree from Tripura University (A Central University), Suryamaninagar, Tripura, India in 2014, and Doctor of Philosophy (Ph.D) degree under Computer Science and Engineering Department of Tripura University (A Central University), Suryamaninagar, Tripura, India. Currently working as an Assistant Professor in Koneru Lakshmaiah Education Foundation (Deemed to be University) Hyderabad, India. Her topics of interest are related to the field of Medical Image Processing, Infrared Imaging, Machine Learning, Computer Vision etc. Dr. Figlu Mohanty received her Ph.D. degree in Computer Science and Engineering from IIIT Bhubaneswar, Odisha in the year 2020. She received her M.Tech degree in Computer Science and Information Security from KIIT University, Bhubaneswar, Odisha, India. She is currently working as an Associate Professor in Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad. Her research interest includes Medical Imaging, Pattern Recognition, Machine Learning, Image Processing, and Data Science. Dr. Sumit Hazra received his Ph.D. degree in Computer Science and Engineering from NIT Rourkela, Odisha in the year 2023. He received his M. Tech degree in Computer Science and Engineering from VIT University, Vellore, India. He is currently working as an Assistant Professor in Department of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation, Hyderabad. His research interests include Gait Analysis, Cognitive Science, Artificial Intelligence, Pattern Recognition, Computer Vision and so on.