Computing Technologies and Applications

Computing Technologies and Applications（Demystifying Technologies for Computational Excellence）

计算技术与应用：为社会5.0铺路
计算机应用

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作者

出版社

Chapman and Hall/CRC

出版时间

2021年11月10日

装帧

精装

ＩＳＢＮ

9780367763701

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页码

358

开本

0 x 0 x 0 cm

语种

英文

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Making use of digital technology for social care is a major responsibility of the computing domain. Social care services require attention for ease in social systems, e-farming, and automation, etc.Thus, the book focuses on suggesting software solutions for supporting social issues, such as health care, learning about and monitoring for disabilities, and providing technical solutions for better living. Technology is enabling people to have access to advances so that they can have better health. To undergo the digital transformation, the current processes need to be completely re-engineered to make use of technologies like the Internet of Things (IoT), big data analytics, artificial intelligence, and others. Furthermore, it is also important to consider digital initiatives in tandem with their cloud strategy instead of treating them in isolation.At present, the world is going through another, possibly even stronger revolution: the use of recent computing models to perform complex cognitive tasks to solve social problems in ways that were previously either highly complicated or extremely resource intensive.This book not only focuses the computing technologies, basic theories, challenges, and implementation but also covers case studies. It focuses on core theories, architectures, and technologies necessary to develop and understand the computing models and their applications. The book also has a high potential to be used as a recommended textbook for research scholars and post-graduate programs.The book deals with a problem-solving approach using recent tools and technology for problems in health care, social care, etc. Interdisciplinary studies are emerging as both necessary and practical in universities. This book helps to improve computational thinking to "understand and change the world’. It will be a link between computing and a variety of other fields.

Section 1: Cloud Computing 1. Cloud Management and Operations Jagruti Shah 2. Real Time Edge Computing Girish Talmale, Urmila Shrawankar 3. Fog Computing: Architecture, Issues, Challenges, Applications and Case Study Pradnya Borkar, Reena Thakur, Dheeraj Rane 4. Mobile Web Service Architecture in Cloud Environment Anil Anandrao Dudhe, Swati Sunil Sherekar Section 2: Internet of Things 5. Internet of Things: essential IoT business guide with Different Case studies Nutan Hemant Deshmukh 6. Research issues in IOT Sayali Sapkal, Sandhya Arora 7. Intrusion Detection Systems for Internet of Things: Techniques, Datasets and Challenges Priya Maidamwar, Mahip M. Bartere and Prasad P. Lokulwar 8. Case study of Smart Farming using IoT Ameya Shahu, Chetan Wagh, Ritik Drona, Rohit Suryawanshi, Santosh Kagne and Shrinit Patil Section 3: Data Science, Deep Learning and Machine Learning 9. Stochastic Computing for Deep Neural Network Sunny Bodiwala, Nirali Nanavati 10. Convolution Neural Network and its Advances: Overview and Applications Jyoti Raghatwan, Sandhya Arora 11. Convolutional Neural Network: A systemic Review and its Application using Keras Shilpa Bhalerao, Maya Ingle 12. Big data Analytics: Applications, issues and challenges Snehlata Dongre, Kapil Wankhade, Latesh Malik 13. AR Powered Computer Science Education Sagar Rane, Anant Kaulage, Sanjeev Wagh 14. Information Technology for Decision Support in College Degree Planning Robert R. Meyer, Athula D. A. Gunawardena, Sobitha Samaranayake, Vivek Deshpande, Kirthi Premadasa 15. Attention-Based Image Captioning and Evalution Methods Khushboo Khurana 16. Smart vehicle monitoring and control using Arduino and Machine Learning: A case Study Reena Thakur, Muskan Qureshi, Sakshi Sarile, Laveena Tahiliani, Shreya Pandit 17. Deep Learning approach to Pedestrian Detection: An Evaluation of the State of the Art Kamal Hajari, Ujwalla Gawande, Prof. Yogesh Golhar 18. Crop Yield Forecast Using Hybrid Framework Of Deep CNN With RNN Technique Radha Rammohan, Niveditha Vr, Amandeep Singh, Yuvarani T

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