The National Conference on Recent Innovations in Emerging Computer Technologies (NCRIECT-2023) was held on the 9th and 10th of May 2023 at Kalinga University, Raipur. The conference was aimed at bringing together researchers, scholars, academicians, and industry professionals to discuss the latest advancements and innovations in the field of computer technologies. The conference began with an opening ceremony, where the chief guests and dignitaries were welcomed by the organizers. The keynote address was delivered by a renowned expert in the field of computer technologies, who spoke about the importance of innovation in driving progress and growth in the industry. This was followed by technical sessions, where researchers and professionals presented their papers on various topics related to computer technologies. The technical sessions covered a wide range of topics, including but not limited to artificial intelligence, machine learning, data science, computer networks, security and privacy, computer graphics and visualization, software engineering, and emerging technologies. The presentations were well-received by the audience, who actively participated in the discussions and provided valuable feedback to the presenters. Apart from the technical sessions, the conference also featured a panel discussion on the topic of "The Future of Computer Technologies". The panel comprised experts from academia and industry, who shared their insights and perspectives on the future direction of the field. The discussion covered various topics, such as the impact of emerging technologies like blockchain and quantum computing, the role of artificial intelligence and machine learning in shaping the future of work, and the challenges and opportunities in ensuring the ethical use of technology. Overall, the conference provided a platform for researchers and professionals to share their ideas, insights, and experiences, and to collaborate and network with their peers. The organizers thanked all the participants and sponsors for their support in making the conference a success, and announced plans to host a follow-up event next year.

This book features high-quality papers presented at the International Conference on Computational Intelligence and Informatics (ICCII 2018), which was held on 28–29 December 2018 at the Department of Computer Science and Engineering, JNTUH College of Engineering, Hyderabad, India. The papers focus on topics such as data mining, wireless sensor networks, parallel computing, image processing, network security, MANETS, natural language processing and Internet of things.

The book is a collection of papers presented at First Doctoral Symposium on Natural Computing Research (DSNCR 2020), held during 8 August 2020 in Pune, India. The book covers different topics of applied and natural computing methods having applications in physical sciences and engineering. The book focuses on computer vision and applications, soft computing, security for Internet of Things, security in heterogeneous networks, signal processing, intelligent transportation system, VLSI design and embedded systems, privacy and confidentiality, big data and cloud computing, bioinformatics and systems biology, remote healthcare, software security, mobile and pervasive computing, biometrics-based authentication, natural language processing, analysis and verification techniques, large scale networking, distributed systems, digital forensics, and human–computer interaction.

This book presents the proceedings of the International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2022. The conference provides an interdisciplinary forum for researchers, professional engineers and scientists, educators, and technologists to discuss, debate, and promote research and technology in the upcoming areas of computing, information, communication, and their applications. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.

This book covers complete spectrum of the ICT infrastructure elements required to design, develop and deploy the ICT applications at large scale. Considering the focus of governments worldwide to develop smart cities with zero environmental footprint, the book is timely and enlightens the way forward to achieve the goal by addressing the technological aspects. In particular, the book provides an in depth discussion of the sensing infrastructure, communication protocols, computation frameworks, storage architectures, software frameworks, and data analytics. The book also presents the ICT application-related case studies in the domain of transportation, health care, energy, and disaster management, to name a few. The book is used as a reference for design, development, and large-scale deployment of ICT applications by practitioners, professionals, government officials, and engineering students.

This book includes high-quality research papers presented at the Fourth International Conference on Innovative Computing and Communication (ICICC 2021), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 20–21, 2021. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.

OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications. The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs. Other essential features of the book include: provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data; explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models; gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application; emphasizes validating and evaluating predictive models; provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics; discusses the challenges and limitations of predictive modeling in healthcare; highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models. Audience The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.