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Intelligent Computing and Innovation on Data Science Proceedings of ICTIDS 2019: Proceedings of ICTIDS 2019
Abstract
This book covers both basic and high-level concepts relating to the intelligent computing paradigm and data sciences in the context of distributed computing, big data, data sciences, high-performance computing and Internet of Things.
It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure and privacy-aware systems in high-performance computing and IoT applications. In this context, the book serves as a useful guide for industry practitioners, and also offers beginners a comprehensive introduction to basic and advanced areas of intelligent computing. Further, it provides a platform for researchers, engineers, academics and industrial professionals around the globe to showcase their recent research concerning recent trends. Presenting novel ideas and stimulating interesting discussions, the book appeals to researchers and practitioners working in the field of information technology and computer science.
Cloud Computing is increasingly being recognized as a valuable virtual resource-sharing solution. Due to its ability to provide solutions across different industries, the number of Cloud computing users has grown substantially. Load balancing distributes the workload across multiple servers to optimize resource utilization and prevent overload, while fault tolerance ensures that the system can continue to function even in the event of failures. In an e-healthcare system, where downtime or errors can have severe consequences for patients, fault tolerance and load balancing become even more critical. Load-balancing techniques are of utmost importance in enhancing the effectiveness of cloud servers. We have comprehensively examined the primary elements that impact fault tolerance in load-balancing task migration within cloud computing. These factors have been assessed by employing various methods to evaluate their influence on fault tolerance in load balancing. By implementing these techniques, e-healthcare systems can improve their ability to handle traffic surges and ensure patient safety and satisfaction
Cardiovascular diseases currently present a key health concern, contributing to an increase in death rates worldwide. In this phase of increasing mortality rates, healthcare represents a major field of research, and the knowledge acquired from this analysis of health information will assist in the early identification of disease. The retrieval of medical information is becoming increasingly important to make an early diagnosis and provide timely treatment. Medical image segmentation and classification is an emerging field of research in medical image processing. In this research, the data collected from an Internet of Things (IoT)-based device, the health records of patients, and echocardiogram images are considered. The images are pre-processed and segmented, and then further processed using deep learning techniques for classification as well as forecasting the risk of heart disease. Segmentation is attained via fuzzy C-means clustering (FCM) and classification using a pretrained recurrent neural network (PRCNN). Based on the findings, the proposed approach achieves 99.5% accuracy, which is higher than the current state-of-the-art techniques.
E-learning has proven to be the best method for corporations, primarily when MNCs conduct training programmes for their workforce worldwide. In e-learning, a teacher no longer directs students; instead, a step-by-step guide has replaced the teacher. The idea of web 2.0, lifelong learning, open education, and social constructivism is often linked with this term. Librarians can benefit from e-learning as well as students and researchers. Staff training through additional online programmes assists employees in learning the latest ideas, handling new challenges, and meeting reader demands. E-learning is becoming more and more popular each year at universities across Canada. E-learning is a practical and effective option to practice on-the-job abilities, such as web searching, and address problems that stem from Internet resources. E-learning programmes can be custom-tailored to the profile, requirements, and collection features of academic libraries. Using e-learning in an academic library may provide many genuine benefits for users and instructors while also helping the institution. According to a new study by the University of Guelph's Department of Library and Information Technology, E-learning is essential for the growth of library facilities. India has 35 million students enrolled in higher education, compared to China's 51.6 million. The government is dedicated to achieving inclusive education, which necessitates an e-Learning system. Online learning must be prioritised to achieve the NEP 2020 goal of 50% GER by 2035. Some conventional institutions have twice the amount of ODL courses registered. The UGC must simplify its laws and streamline rules, says Naveen Thakur-Ganjibayyan.
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