Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human-robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: Introduces several new contributions to the representation and management of humans in autonomous robotic systems; Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; Engages with the potential repercussions of cognitive computing and HRI in the real world.

With recent advancements in electronics, specifically nanoscale devices, new technologies are being implemented to improve the properties of automated systems. However, conventional materials are failing due to limited mobility, high leakage currents, and power dissipation. To mitigate these challenges, alternative resources are required to advance electronics further into the nanoscale domain. Carbon nanotube field-effect transistors are a potential solution yet lack the information and research to be properly utilized. Major Applications of Carbon Nanotube Field-Effect Transistors (CNTFET) is a collection of innovative research on the methods and applications of converting semiconductor devices from micron technology to nanotechnology. The book provides readers with an updated status on existing CNTs, CNTFETs, and their applications and examines practical applications to minimize short channel effects and power dissipation in nanoscale devices and circuits. While highlighting topics including interconnects, digital circuits, and single-wall CNTs, this book is ideally designed for electrical engineers, electronics engineers, students, researchers, academicians, industry professionals, and practitioners working in nanoscience, nanotechnology, applied physics, and electrical and electronics engineering.

The advancement of information and communication technology has led to a multi-dimensional impact in the arenas of law, regulation, and governance. The laws, rules and regulations of the digital domain remain a challenge with the transformation of technology. The Constitution of many countries have declared data protection as a fundamental right. Such a trend is evident not only by the current reform of data protection law aimed at modernizing the global regulatory framework but also by the judiciary in landmark judgments. Furthermore, the legal domain must face many challenges with the speed of technological innovations due to abject global latitude, massive scale of content exchange and data collection, and the relative secrecy issues of internet users. Thus, it is essential to continue discussions involving policies and law that regulate and monitor these activities and anticipate new laws that should be implemented to protect users. This book will focus on the complex relationships of technology and law, both in terms of substantive legal responses to legal, social, and ethical issues arising in connection with growing public engagement with technology and the procedural impacts and transformative potential of technology on traditional and emerging forms of dispute resolution. This book will also provide a broader foundation upon which academics and professionals in the fields could improve current security activities and contribute to the protection of the nation.

When a little boy paints his nails with his mum's nail polish, he discovers the most important thing of all: the magic of being his true self. As the long Indian summer days stretch ahead of him, a young boy looks forward to his favourite time - painting-your-nails-time. He knows that when he dips his brush into those magical bottles of nail polish, he will find a colour to express his every mood and feeling. Purple is the colour of magic and mystery. White is the colour of endless possibilities. At times, his Papa frowns and says, "What have you done to your nails?" At other times, he says, "Why don't you paint on paper instead?" But the little boy knows that painting his nails makes his hands look beautiful. This colour-filled story celebrates the joy of finding out who you are and embracing the courage to be yourself.

Trust and Technology in B2B E-Commerce: Practices and Strategies for Assurance focuses on various trust issues that emerge from deployment of various e-commerce technologies in inter-organizational relationships. Some of these issues relate to security, privacy, authentication, non-repudiation, quality of web interface, system performance and infrastructure, environmental factors. The objective of this book is to examine technology-related trust issues relating to security, privacy, authentication, non-repudiation, quality of web interface, system performance and infrastructure, environmental factors. This book contributes to the ongoing process of developing a framework for understanding the process of building trust in B2B e-commerce.

The notion of the "Silk Road" that the German geographer Ferdinand von Richthofen invented in the 19th century has lost attraction to scholars in light of large amounts of new evidence and new approaches. The handbook suggests new conceptual and methodological tools for researching ancient economic exchange in a global perspective with a strong focus on recent debates on the nature of pre-modern empires. The interdisciplinary team of Chinese, Indian and Graeco-Roman historians, archaeologists and anthropologists that has written this handbook compares different forms of economic development in agrarian and steppe regions in a period of accelerated empire formation during 300 BCE and 300 CE. It investigates inter-imperial zones and networks of exchange which were crucial for ancient Eurasian connections. Volume I provides a comparative history of the most important empires forming in Northern Africa, Europe and Asia between 300 BCE and 300 CE. It surveys a wide range of evidence that can be brought to bear on economic development in the these empires, and takes stock of the ways academic traditions have shaped different understandings of economic and imperial development as well as Silk-Road exchange in Russia, China, India and Western Graeco-Roman history.

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data's immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

Tips to Succeed in Oral Exam. Examination Techniques Diagnostic Investigations Clinical Ophthalmology Ocular Pharmacology Ophthalmic Surgery. Ocular Pathology General Medicine. Problem-Solving Paper List of Abbreviations.

Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information.

Certain types of pesticides are widely used in agriculture in all parts of the world due to their relatively low cost, broad spectrum of activity, and high efficiency. These pollutants contaminate not only the surrounding soils and water but, in many cases, also enter into the drinking water. The Handbook of Research on the Adverse Effects of Pesticide Pollution in Aquatic Ecosystems provides emerging research exploring the theoretical and practical aspects of the prevention of accumulation of toxic pollutants such as agrochemicals and organochlorine pesticides in aquatic ecosystems and applications within ecology and agriculture. Featuring coverage on a broad range of topics such as pesticide monitoring, metabolites, and risk assessment, this book is ideally designed for scientists, researchers, engineers, policymakers, agricultural specialists, industrialists, academicians, and students seeking current research on the risks of water contaminants in small ecosystems.

This book offers a unique balance between a basic introductory knowledge of bioinformatics and a detailed study of algorithmic techniques. Bioinformatics and RNA: A Practice-Based Approach is a complete guide on the fundamental concepts, applications, algorithms, protocols, new trends, challenges, and research results in the area of bioinformatics and RNA. The book offers a broad introduction to the explosively growing new discipline of bioinformatics. It covers theoretical topics along with computational algorithms. It explores RNA bioinformatics, which contribute to therapeutics and drug discovery. Implementation of algorithms in a DotNet Framework with code and complete insight on the state-of-the-art and recent advancements are presented in detail. The book targets both novice readers as well as practitioners in the field. FEATURES Offers a broad introduction to the explosively growing new discipline of bioinformatics Covers theoretical topics and computational algorithms Explores RNA bioinformatics to unleash the potential from therapeutics to drug discovery Discusses implementation of algorithms in DotNet Frameworks with code Presents insights into the state of the art and recent advancements in bioinformatics The book is useful to undergraduate students with engineering, science, mathematics, or biology backgrounds. Researchers will be equally interested.

This book addresses the Internet of Things (IoT), an essential topic in the technology industry, policy, and engineering circles, and one that has become headline news in both the specialty press and the popular media. The book focuses on energy efficiency concerns in IoT and the requirements related to Industry 4.0. It is the first-ever "how-to" guide on frequently overlooked practical, methodological, and moral questions in any nations' journey to reducing energy consumption in IoT devices. The book discusses several examples of energy-efficient IoT, ranging from simple devices like indoor temperature sensors, to more complex sensors (e.g. electrical power measuring devices), actuators (e.g. HVAC room controllers, motors) and devices (e.g. industrial circuit-breakers, PLC for home, building or industrial automation). It provides a detailed approach to conserving energy in IoT devices, and comparative case studies on performance evaluation metrics, state-of-the-art approaches, and IoT legislation.

With the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark's scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance.

This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics. Key Features: Comprehensive coverage of the fundamentals of big data analytics In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems. Practical examples and case studies to help readers understand complex concepts. Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture Discussion of challenges and legal frameworks involved in big data analytics. Clear and concise language that is easy to understand. This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.

This volume brings together information on the available and newly emerging technologies related to using plant compounds that have a beneficial role in food production. It is divided into sections focusing on phytochemistry of cereals and legumes, phytochemistry of medicinal plants, and technological advances in phytochemical study. Topics include the role of anti-nutritional substances of legumes in human health and on the elimination of such through technological processing sorghum phytochemicals and their processing and use in the development of food products production of nutraceuticals and functional foods of pharmaceutical importance T. cordifolia in the development of its therapeutic use in the food, health, and pharmacology industries polyphenolic compounds of plants, including their biosynthesis process, their classification, function, and role as bioactive compounds

This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.

This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.