The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligence.

This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, due to the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).

Computer simulation of fluid flows requires numerical solution of Partial Differential Equations (PDEs) which involves discretization methods such as Finite Volume Method (FVM). These methods produce a large system of linear equations which are difficult to solve. Iterative (Krylov Subspace) solvers are one of the best ways to deal with such large systems. These systems need huge amount of memory as well as they are computationally expensive. Modern supercomputers facilitate to run the simulations on multiprocessors by writing efficient parallel algorithms for iterative solvers. This book provides good background of Krylov Subspace solvers and computational methods for multiphase fluid flows. Furthermore, detailed discussions on developing parallel algorithms for these solvers have been provided using the special data structures facilitating inter-processor communications. It is a very useful book for advanced undergraduate and graduate students, who want to gain knowledge about parallel numerical algorithms applicable to Computation Fluid Dynamics (CFD) problems.