General Fractional Derivatives with Applications in Viscoelasticity introduces the newly established fractional-order calculus operators involving singular and non-singular kernels with applications to fractional-order viscoelastic models from the calculus operator viewpoint. Fractional calculus and its applications have gained considerable popularity and importance because of their applicability to many seemingly diverse and widespread fields in science and engineering. Many operations in...

This book intends to examine the relationship between East Asia and Southeast Asia across three themes: historical perspectives, economic flows of capital and people, and socio-cultural connections. While a substantial number of chapters in the book focus on overseas Chinese (living in Indonesia) and their connections with China and Taiwan historically and contemporarily, they also provide in-depth knowledge of international relationship between East Asia and Southeast Asia.Part On...

This text provides a comprehensive and state-of-the-art overview of the evaluation and management of liver mass lesions. Major topics covered include epidemiology, the use of different imaging modalities in the differential diagnosis of liver lesions, the use of biomarkers and immunohistochemical stains for diagnosis, and treatment of the different types of liver masses. These include hepatocellular adenoma and hepatocellular carcinoma, fibrolamellar carcinoma, cholangiocarcinoma, hemangio...

This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural ...

This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics.While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep ...

This book highlights the latest research in computational intelligence and its applications. It covers both conventional and trending approaches in individual chapters on Fuzzy Systems, Intelligence in Robotics, Deep Learning Approaches, Optimization and Classification, Detection, Inference and Prediction, Hybrid Methods, Emerging Intelligence, Intelligent Health Care, and Engineering Data- and Model-Driven Applications. All chapters are based on peer-reviewed contributions presented at th...