The book presents the proceedings of the 10th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2022), held at NIT Mizoram, Aizawl, Mizoram, India during 18 19 June 2022. Researchers, scientists, engineers, and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. These proceedings are divided into two volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This volume is a valuable resource for postgraduate students in various engineering disciplines.

Presents research works in intelligent data engineering and analytics Results of FICTA 2022 held at NIT Mizoram, Aizawl, Mizoram, India Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Dr. Vikrant Bhateja is associate professor in Department of Electronics & Communication Engineering (ECE), Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM), Lucknow (Affiliated to AKTU) and also the Dean (Academics) in the same college. He is doctorate in ECE (Bio-Medical Imaging) with a total academic teaching experience of 19 years with around 180 publications in reputed international conferences, journals and online book chapter contributions; out of which 31 papers are published in SCIE indexed high impact factored journals. Among the international conference publications, four papers have received "Best Paper Award". Among the SCIE publications, one paper published in Review of Scientific Instruments (RSI) Journal (under American International Publishers) has been selected as "Editor Choice Paper of the Issue" in 2016. He has been instrumental in chairing/co-chairing around 25 international conferences in India and abroad as Publication/TPC chair and edited 45 book volumes from Springer-Nature as a corresponding/co-editor/author on date. He has delivered nearly 20 keynotes, invited talks in international conferences, ATAL, TEQIP and other AICTE sponsored FDPs and STTPs. He is Editor-in-Chief of IGI Global--International Journal of Natural Computing and Research (IJNCR) an ACM & DBLP indexed journal since 2017. He has guest edited Special Issues in reputed SCIE indexed journals under Springer-Nature and Elsevier. He is Senior Member of IEEE and Life Member of CSI.

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. Now he is Reader at Middlesex University London, Fellow of the Institute of Mathematics and its Application (IMA), and a co-Editor of the Springer Tracts in Nature-Inspired Computing. He has published more than 250 peer-reviewed research papers with more than 65,000 citations, and he has been on the prestigious list of highly-cited researchers (Clarivate Analytics/Web of Sciences) for six consecutive years (2016-2021).

Jerry Chun-Wei Lin received his Ph.D. from the Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan in 2010. He is currently a full Professor with the Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. He has published more than 400 research articles in top-tier journals and conferences, 12 edited books, as well as 33 patents (held and filed, 3 US patents). His research interests include data analytics, soft computing, artificial intelligence/machine learning, optimization, IoT, and privacy preserving and security technologies. He is the Editor-in-Chief of the International Journal of Data Science and Pattern Recognition. He has recognized as the most cited Chinese Researcher respectively in 2018, 2019, and 2020 by Scopus/Elsevier. He is the Fellow of IET (FIET), senior member for both IEEE and ACM.

Dr. Ranjita Das is currently serving as a Head and Assistant Professor, Department of Computer Science and Engineering, National Institute of Technology Mizoram. She has joined the National Institute of Technology Mizoram in the year 2011. She did her PhD. from NIT Mizoram, M. Tech from Tezpur University, and B. Tech. from NIT Agartala. She has over 10 years of teaching experience. Her research was in the area of Pattern Recognition, Information retrieval, Computational biology, and Machine learning. She has published 20 journal and International conference papers in various journals with SCI impact factors, SCOPUS index, and also in Conf proceedings of Springer, IEEE, etc. She has two ongoing sponsored projects funded by DBT and SERB. Under her supervision presently ten research scholars are doing research work. She was recipient of Best paper awards in the conferences IEEE-INDICON-2017, ICACCP-2019, IC4E-2020.

Inhalt
SIFT Application Separates Motion Characteristics and Identifies Symbols on Tires.- Localization and classification of thoracic abnormalities from chest radiographs using deep ensemble model.- Comparative Study on Different Approaches for Understanding the Privacy Policies.- A framework for the development of Intrusion detection system using Deep Learning.- A Self Explainable Face Anti-Spoofing Solution based on Depth-Estimation.- A Naïve Approach for Mutation Detection using Color Encodings and String Matching Techniques.- Particulate Matter Concentration Estimation from Images Based on Convolution Neural Network.- Brain Tumor Prediction from MRI Images using an ensemble model based on EcientNet-B2, B4, and ResNet34 architectures.- Automatic Abnormality Detection in Musculoskeletal Radiographs using Ensemble of Pre-trained Networks.- Ablation study of Indian Automatic Vehicle Number Plate Recognition model trained over Synthetic dataset.- An Approach of Hate Speech Identification onTwitter Corpus.- A Fuzzy C-Means Based Clustering Protocol to Improve QoS of Multi Sink WSNs.- A Descriptive Analysis of Reddit Comments using Data Analytics Approach.- Streamflow forecasting using novel ANFIS-GWO approach.- A Novel COVID-19 Based Optimization Algorithm (C-19BOA) for Multimodal Optimization Processes.- A Survey on Medical Image Analysis Using Deep Learning.- Improving English-Assamese Neural Machine Translation using Transliteration-based Approach.- Prediction of Air Quality using Machine Learning.- Inter domain text classification: A hybrid approach.- Sentimental Analysis of Twitter Users' Text Using Machine Learning. <p