Application of Artificial Intelligence in Early Detection of Lung Cancer presents the most up-to-date computer-aided diagnosis techniques used to effectively predict and diagnose lung cancer. The presence of pulmonary nodules on lung parenchyma is often considered an early sign of lung cancer, thus using machine and deep learning technologies to identify them is key to improve patients’ outcome and decrease the lethal rate of such disease. The book discusses topics such as basics of lung cancer imaging, pattern recognition techniques, deep learning, and nodule detection and localization. In addition, the book discusses risk prediction based on radiological analysis and 3D modeling. This is a valuable resource for cancer researchers, oncologists, graduate students, radiologists, and members of biomedical field who are interested in the potential of AI technologies in the diagnosis of lung cancer.

This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. The emergence of Industry 4.0 has witnessed the deployment of reconfigurable hardware or field programmable gate arrays (FPGAs) in diverse embedded applications. These are associated with the execution of several real-time tasks arranged in schedules. However, they are associated with several issues. Development of fully and partially reconfigurable task schedules are discussed that eradicates the existing problems. However, such real-time task schedules may be jeopardized due to hardware threats. Analysis of such threats is discussed and self-aware security techniques are proposed that can detect and mitigate such threats at runtime.

This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. The emergence of Industry 4.0 has witnessed the deployment of reconfigurable hardware or field programmable gate arrays (FPGAs) in diverse embedded applications. These are associated with the execution of several real-time tasks arranged in schedules. However, they are associated with several issues. Development of fully and partially reconfigurable task schedules are discussed that eradicates the existing problems. However, such real-time task schedules may be jeopardized due to hardware threats. Analysis of such threats is discussed and self-aware security techniques are proposed that can detect and mitigate such threats at runtime.

The volume on Data Management, Analytics and Innovations presents the latest high-quality technical contributions and research results in the areas of data management and smart computing, big data management, artificial intelligence and data analytics along with advances in network technologies. It deals with the state-of-the-art topics and provides challenges and solutions for future development. Original, unpublished research work highlighting specific research domains from all viewpoints are contributed from scientists throughout the globe. This volume is mainly designed for professional audience, composed of researchers and practitioners in academia and industry.

This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17-19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.

The textbook is designed for B.Tech students of Electrical/Mechanical/Industrial Engineering and M.Tech students of Power System/Energy Engineering/Energy Management. It will also be useful for MBA courses on Energy Management conducted by some universities through distance education mode. The book, now in its Second Edition, offers an exhaustive discussion of the energy analysis methodologies and tools to optimize the utilization of energy and how to enhance efficiency during conversion of energy from one form to another. It illustrates the energy analysis methods used in factories, transportation systems and buildings highlighting the various forms of use. It also discusses the thermodynamic principles of energy conversion and constitution of energy balance equation for such systems. The book examines the energy costs in our everyday life in terms of energy inputs in food cultivation. It also discusses similar energy costs of using fuels, other goods and services in our daily life. KEY FEATURES: Includes numerous questions and answers on Energy Management Contains problems and solutions on Energy Management Provides MCQs for the preparation of certified energy auditor examination conducted by the Bureau of Energy Efficiency, Government of India Includes Case Studies