Soft Computing and Signal Processing

V. Sivakumar Reddy is Professor at the Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, and has more than 25 years of teaching and research experience. He completed his B.E. in Electronics and Communication Engineering from S.V. University, his M.Tech. in Digital Systems at JNT University and his Ph.D. in Electronics & Communication Engineering at IIT Kharagpur. His areas of research interest include multi-media signal processing and communication protocols. He has published more than 180 papers in peer-reviewed journals and reputed conferences. He is a member of several academic bodies, such as IETE, IEEE, ISTE and CSI. He is also a reviewer for several IEEE journals. He was awarded as “Best Teacher” in three consecutive academic years with citation and cash award. He is the recipient of “India Jewel Award” for outstanding contribution to the research in the field of Engineering and Technology. V. Kamakshi Prasad isProfessor in the Department of Computer Science & Engineering in JNTU Hyderabad, he completed his Ph.D. in speech recognition at the Indian Institute of Technology Madras and his M.Tech. in Computer Science & Technology at Andhra University in 1992. He has more than 23 years of teaching and research experience. His areas of research and teaching interest include speech recognition and processing, image processing, pattern recognition, ad hoc networks and computer graphics. He has published several books, chapters and research papers in peer-reviewed journals and conference proceedings. He is also an editorial board member of the International Journal of Wireless Networks and Communications and a member of several academic committees.  Jiacun Wang received a Ph.D. in Computer Engineering from Nanjing University of Science and Technology (NJUST), China, in 1991. He is currently Professor at the Computer Science and Software Engineering Department at Monmouth University, West Long Branch, New Jersey. From 2001 to 2004, he was a member of scientific staff at Nortel Networks in Richardson, Texas. Prior to joining Nortel, he was a research associate at the School of Computer Science, Florida International University (FIU) at Miami and Associate Professor at NJUST. He has published numerous books and research papers and is Associate Editor of several international journals. He has also served as a program chair, a program co-chair, a special sessions chair and a program committee member for several international conferences. He is the secretary of the Organizing and Planning Committee of the IEEE SMC Society and has been a senior member of IEEE since 2000. KTV Reddy, an Alumni of IIT Bombay, is presently working as Dean of the Faculty of Engineering and Technology, Datta Meghe institute of Medical science (Deemed to be University), Sawangi (Meghe), Wardha, Maharashtra, India. He has been teaching for 30 years. He was the presiding officer for the JEE, GATE, NEET, and other all-India exams. He has served as an advisor, general chair, and convener at over 200 national and international conferences and workshops. He gave over 150 expert talks. He has published more than 150 publications. He is an editor for the Journal of Signal and Image Processing (Tailor and Francis) and a reviewer for IEEE journals and conferences. For the years 2017-201, he served as president of the Institution of Electronics and Telecommunications Engineers (IETE) in New Delhi, India.

Chapter 1. Microservice Architecture Observability Tool Analysis.- Chapter 2. Decentralized payment architecture for e-commerce and utility transactions with Government verified identities.- Chapter 3. Detection of Phishing Website using Intelligent Machine Learning Classifiers.- Chapter 4. Bidirectional Gated Recurrent Unit (BiGRU) based Bitcoin Price Prediction by News Sentiment Analysis.- Chapter 5. How AI Algorithms are being used in Applications.- Chapter 6. A Framework for Identifying Theft Detection using Multiple-instance Learning.- Chapter 7. An Efficient Reversible Data Hiding Based on Prediction Error Expansion.- Chapter 8. Deriving Insights from COVID-19.- Chapter 9. Smoke Detection in Forest Using Deep Learning.- Chapter 10. Pneumothorax Segmentation using Feature Pyramid Network and MobileNet Encoder through Radiography Images.- Chapter 11. Visual Learning with Dynamic Recall.- Chapter 12. Machine learning for drug discovery using ag-glomerative hierarchical clustering.-Chapter 13. Automated Photomontage Generation with Neural Style Transfer.- Chapter 14. Machine Learning Model Development Using Computational Neurology.- Chapter 15. Graph Theory based user profile extraction and community detection in Linkedin- A study. etc.