Proceedings of Fifth International Conference on Computer and Communication Technologies

Dr. Rama Devi Boddu received the Ph.D. from the JNTUH College of Engineering, Hyderabad, Telangana, India, in April 2016. She completed her M.Tech. in Digital Communication Engineering in 2007 from Kakatiya University, Warangal (KITSW).  She joined the faculty of electronics and communication engineering at KITSW in 2007. From January 19, 2019, to December 16, 2021, she was the head of the Department of Electronics and Communication Engineering at KITSW. At present, she is working as a professor in the Department of ECE. She published more than 40 papers in various journals and conferences. She published three books and had two Indian patents granted to her. She acted as an editor and program chair for the Springer International conferences IC3T 2022 and ICDECT 2021. She acted as a session chair for various international conferences. Dr.  T.  Kishore Kumar earned his Ph.D. in signal processing in 2004. He headed the Department of Electronics andCommunication Engineering at NIT Warangal from 2015 to 2017. He was also the head of the Institute Computer Center, NIT Warangal, from 2018 to 2020. He was a visiting professor at ESIGELEC University in France in 2009, a visiting professor at TALLINN University, Estonia, for a semester for an MS in Computer Science, and a visiting professor at the Asian Institute of Technology, Bangkok, in 2019 under the Secondment of Indian Faculty by MHRD, Govt. of India. He worked as a technical officer in the Cabinet Secretariat, Prime Minister's Office, Government of India. He is a member of the Central Council Board (CCB) and a member of the Andhra Pradesh State Council for Higher Education (APSCHE). Dr. Manda Raju received his Ph.D. from Kakatiya University, Telangana, India, in 2017. In2009, he received his M.Tech in Instrumentation and Control Systems from JNTU Kakinada. He has 23 years of teaching experience. He published more than 35 papers in various journals and conferences. She published four books. He has been guiding two research scholars. His areas of interest include wireless communication and signal processing for communications. He is a member of IETE, a member of ISTE, a member of IAENG, and a senior member of IRED.Dr. K Srujan Raju obtained his Doctorate in Computer Science in the area of network security. He has more than 20 years of experience in academics and research. His research interest areas include computer networks, information security, data mining, cognitive radio networks and image processing, and other programming languages. He has undergone specific training conducted by Wipro Mission 10X & NITTTR, Chennai, which helped his involvement with students and is very conducive for solving their day-to-day problems. He has guided various student clubs for activities ranging from photography to Hackathon. He mentored more than 100 students for incubating cutting-edge solutions. He has organized many conferences, FDPs, workshops, and symposiums. He has established the Centre of Excellence in IoT and Data Analytics. Dr. Mathini Sellathurai is currently the dean of Science and Engineering and the head of the Signal Processing for Intelligent Systems and Communications Research Group, Heriot-Watt University, Edinburgh, UK and leading research in signal processing for Radar and wireless communications networks. Prof. Sellathurai has five years of industrial research experience. She held positions with Bell-Laboratories, New Jersey, USA and with the Canadian (Government) Communications Research Centre, Ottawa, Canada. She was an associate editorship for the IEEE Transactions on Signal Processing (2005–2018) and IEEE Signal Processing for Communications Technical Committee member (2013–2018). She was an organizer for the IEEE International Workshop on Cognitive Wireless Systems, IIT Delhi, India, 2009, 2010, and 2013; and the general chair of the 2016 IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Edinburgh, UK.

• Implementation of Digital Down Conversion Technique Using FPGA for Atmospheric RADAR Application.- Predictive Data Analysis to Support Decision-making based on Long-term Impacts of Disasters.- Generative Adversarial Networks: Challenges, Solutions, and Evaluation Metrics.- Improving Accuracy and Robustness in Depression Detection with Ensemble Learning and Optimization Techniques.- Spatial-Spectral Features based Dimensionality Reduction Technique for Robust Multivariate Image Classification Improving Breast Cancer Prognosis with DL-based Image Classification.- A Lightweight Encryption Method for Preserving E-Health Care Data Privacy Using Dual Signature on Twisted Edwards Curves.- Intrusion Classification and Detection System using Machine Learning Models on NSL-KDD Dataset.- A comprehensive review of the Application of Green House Using the Internet of Things.- Controlling Power Point Slide Presentations Through Hand Gestures.- Design of Multiband GaN HEMT power amplifier for Radar applications.- SqueezeNet based Model for Subject Identification from Off-Angle Iris Image.- Brain Tumor Detection and Segmentation using Deep Learning Models with Dual Attention Mechanism.- Exploring Machine Learning Algorithms for Accurate Breast Cancer Classification: A Comparative Analysis using F2 Metric.- Optimizing Gene Expression analysis using Clustering Algorithms.- Prevention and Mitigation of Intrusion using an efficient ensemble classification in Fog computing.- Fake News Detector using Machine Learning.- Electric vehicle energy management system using fuzzy logic controller.- Optimized Fall Detection Algorithm with Adaptive Sum Vector Magnitude and Axis-Weighted Features from Wearable Accelerometer Data.- Deep Learning Based Real-Time Face Mask Detection for Human using Novel YOLOv2 with Higher Accuracy.- Smart University Application: Internet of Things(IoT) Based Smart and Random Method to Collect Waste Management System in a University Campus By Using Ant Colony Optimization(ACO) Algorithm.- Tomato leaf Disease Detection and Classification by using Novel CNN model.