This book discusses all aspects of money laundering, starting from traditional approach to financial crimes to artificial intelligence-enabled solutions. It also discusses the regulators approach to curb financial crimes and how syndication among financial institutions can create a robust ecosystem for monitoring and managing financial crimes. It opens with an introduction to financial crimes for a financial institution, the context of financial crimes, and its various participants. Various types of money laundering, terrorist financing, and dealing with watch list entities are also part of the discussion. Through its twelve chapters, the book provides an overview of ways in which financial institutions deal with financial crimes; various IT solutions for monitoring and managing financial crimes; data organization and governance in the financial crimes context; machine learning and artificial intelligence (AI) in financial crimes; customer-level transaction monitoring system; machine learning-driven alert optimization; AML investigation; bias and ethical pitfalls in machine learning; and enterprise-level AI-driven Financial Crime Investigation (FCI) unit. There is also an Appendix which contains a detailed review of various data sciences approaches that are popular among practitioners. The book discusses each topic through real-life experiences. It also leverages the experience of Chief Compliance Officers of some large organizations to showcase real challenges that heads of large organizations face while dealing with this sensitive topic. It thus delivers a hands-on guide for setting up, managing, and transforming into a best-in-class financial crimes management unit. It is thus an invaluable resource for researchers, students, corporates, and industry watchers alike.

This book bridges the widening gap between two crucial constituents of computational intelligence: the rapidly advancing technologies of machine learning in the digital information age, and the relatively slow-moving field of general-purpose search and optimization algorithms. With this in mind, the book serves to offer a data-driven view of optimization, through the framework of memetic computation (MC). The authors provide a summary of the complete timeline of research activities in MC - beginning with the initiation of memes as local search heuristics hybridized with evolutionary algorithms, to their modern interpretation as computationally encoded building blocks of problem-solving knowledge that can be learned from one task and adaptively transmitted to another. In the light of recent research advances, the authors emphasize the further development of MC as a simultaneous problem learning and optimization paradigm with the potential to showcase human-like problem-solving prowess; that is, by equipping optimization engines to acquire increasing levels of intelligence over time through embedded memes learned independently or via interactions. In other words, the adaptive utilization of available knowledge memes makes it possible for optimization engines to tailor custom search behaviors on the fly - thereby paving the way to general-purpose problem-solving ability (or artificial general intelligence). In this regard, the book explores some of the latest concepts from the optimization literature, including, the sequential transfer of knowledge across problems, multitasking, and large-scale (high dimensional) search, systematically discussing associated algorithmic developments that align with the general theme of memetics. The presented ideas are intended to be accessible to a wide audience of scientific researchers, engineers, students, and optimization practitioners who are familiar with the commonly used terminologies of evolutionary computation. A full appreciation of the mathematical formalizations and algorithmic contributions requires an elementary background in probability, statistics, and the concepts of machine learning. A prior knowledge of surrogate-assisted/Bayesian optimization techniques is useful, but not essential.

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.

Numerical Methods with MATLAB provides a highly-practical reference work to assist anyone working with numerical methods. A wide range of techniques are introduced, their merits discussed and fully working MATLAB code samples supplied to demonstrate how they can be coded and applied. Numerical methods have wide applicability across many scientific, mathematical, and engineering disciplines and are most often employed in situations where working out an exact answer to the problem by another method is impractical. Numerical Methods with MATLAB presents each topic in a concise and readable format to help you learn fast and effectively. It is not intended to be a reference work to the conceptual theory that underpins the numerical methods themselves. A wide range of reference works are readily available to supply this information. If, however, you want assistance in applying numerical methods then this is the book for you.

A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain's ability to generalize in optimization - particularly in population-based evolutionary algorithms - have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems, each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.

Nanotechnology Environmental Health and Safety informs the readers about the quantitative analysis and the safety issues of nanotechnology in the healthcare research. It throws light on the relation between nanotechnology and the occupational health and enumerates the various risks and benefits for medical diagnosis and treatment. Also discussed in the book nanotechnology-related environment, health, and safety research, the ergonomic challenges for nanotechnology safety and health practices, the ethical and scientific issues of nanotechnology in the workplace, management of nanomaterials safety in research environment, risk assessment and risk management of nanomaterials in the workplace and the prospects of using nanotechnology for food preservation, safety, and security.

Applications of Quantum Dots starts with a basic introduction that includes the characterization, usage and preparation in biological systems. Quantum dots have a broad spectrum of applications and this text book has covered the major applications like uncovering active precursors in colloidal quantum dot synthesis or designing artificial 2D crystals with site and size controlled quantum dots. The readers can also get the information regarding the recent developments in quantum dots/cnt co-sensitized organic solar cells and accumulation and distribution of non-targeted and anti-cd44-conjugated quantum dots in distinct phenotypes of breast cancer. Further the book also highlights the potential use of quantum dots in flow cytometry.

Applications of Carbon Nano Dots examines the uses and potential of this revolutionary discovery in field of science and technology, including features of carbon mano dots like luminescence mechanism and designing of carbon dots photoluminescence through organo-functional silane grafting. Also, the synthesis of luminescent carbon dots with ultrahigh quantum yield has also been discussed in detail. Readers are provided with latest information on carbon quantum dots or carbon nano dots including designing, synthesis and applications.

This new book in the advances in material systems for application in medicine and biology entitled: Micro and Nanosystem for Biotechnology will address the novel application of micro and nanosystems in biological research, diagnostics and therapeutics. Speci?cally the book will address research aspects related to material in imaging and biological research, nano materials as a bio-sensing tool, oligonucleotides and biopolymer as nano building blocks, nano materials for drug delivery, medicinal and therapeutic application and cyto-toxicity of nano-materials. The detailed discussion in the book intends to present speci? cally biological, diagnostic and medical problems with their potential solution by nano technology or materials. For example in the diagnostics and imaging ?eld the will discuss the contribution of q-dots as imaging tools, ?uorescent labels, their application as donor in FRET pair and more. Gold nanoparticles will be presented as SERS and electrochemical enhancers. In the therapeutic ?eld the book will present the biomimic reconstituted high density lipoprotein nanosystem for enhanced vegf gene therapy of myocardial ischemia. The subject of forming functional nano structures from biological building block, as engineered nanomedicine with alendronic acid corona improves targeting to osteosarcoma. This will be shown as building block for molecular machines, functional networks or unique origami structures. In these subjects this volume is expanding the possible application of micro and nano systems in the major ?eld of medicine and biology. In this respect this book is unique, since it would arise from the biological problems to the systems possible solution and not vice versa.

Chitosan nanoparticles have recently been developed for peptides, proteins, and nucleic acid delivery. This book introduces chitosan nanoparticles in the broadest scale possible by showing their optical/chemical characterization with their applicability illustrating different method of preparation and applications. Their potential for the delivery of drugs at the ocular level was investigated. This is not a straight textbook but a guided tour of the different form of chitosan nanoparticles which we hope will arouse the reader's curiosity so that they will engage more profoundly with the subject.

Taking novel theoretical and practical approaches this book aims to emphasize that surface composition and chemistry are key parameters in nanoparticle properties and applications even though their characterization is seldom adequately performed. The importance of the nanoparticle characterization in the control of their properties is summarized and the role of the nanoparticle surface chemistry in various applications as well. A brief summary of the usual techniques for surface studies is presented along with the challenging performance required from the analytical instruments.