Computational Methods for Agricultural Research: Advances and Applications brings computing solutions to ancient practices and modern concerns, sowing the seeds for a sustainable, constant food supply. This book treats subjects as old modeling flood patterns and predicting potential climates to distinctly 21st century topics such as pesticide leaching models and the impact of agricultural policy. All of these studies utilize cutting-edge computational techniques of interest to both academics and practitioners in agriculture but also computational modeling researchers, creating a reference practical significance.

Probabilistic modeling represents a subject spanning many branches of mathematics, economics, and computer science to connect pure mathematics with applied sciences. Operational research also relies on this connection to enable the improvement of business functions and decision making. Analyzing Risk through Probabilistic Modeling in Operations Research is an authoritative reference publication discussing the various challenges in management and decision science. Featuring exhaustive coverage on a range of topics within operational research including, but not limited to, decision analysis, data mining, process modeling, probabilistic interpolation and extrapolation, and optimization methods, this book is an essential reference source for decision makers, academicians, researchers, advanced-level students, technology developers, and government officials interested in the implementation of probabilistic modeling in various business applications.

Applications and Developments in Grid, Cloud, and High Performance Computing provides insight into the current trends and emerging issues by investigating grid and cloud evolution, workflow management, and the impact new computing systems have on the education fields as well as the industries. This book is practical for both researchers and IT professionals.

The book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES-STS 2019). Modern transportation systems have undergone a rapid transformation in recent years. This has produced a range of vehicle technology innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations and breakthroughs in Smart Transportation Systems, as well as transport infrastructure modeling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.

This book explores Ambient Intelligence as applied to the classroom, while especially focusing on the use of personalized education to optimize the learning process. In the years to come, the dynamics of learning spaces in higher education will need to evolve and adapt to a constantly changing digital society, as learners and educators alike attune their learning competences and teaching skills. Ambient Intelligence is another way that Artificial Intelligence is being utilized in a plethora of real-world situations, amongst which classrooms and other learning spaces offer fitting settings and ideal environments for employing this assistive technology. The book presents a complete and novel approach to deploying the Ambient Intelligent Classroom, based on three interrelated aspects - the Social, the Technological and the Educational, - in order to provide a rich three-dimensional learning environment. This book is intended for education technologists and AI researchers, as well as for those tech-savvy readers interested in applying technology to the future of learning spaces. Educators in particular will find valuable insights and guidelines on how to shape the evolution of their own classroom.

This book covers the discrete mathematics as it has been established after its emergence since the middle of the last century and its elementary applications to cryptography. It can be used by any individual studying discrete mathematics, finite mathematics, and similar subjects. Any necessary prerequisites are explained and illustrated in the book. As a background of cryptography, the textbook gives an introduction into number theory, coding theory, information theory, that obviously have discrete nature. Designed in a "self-teaching" format, the book includes about 600 problems (with and without solutions) and numerous, practical examples of cryptography. FEATURES Designed in a "self-teaching" format, the book includes about 600 problems (with and without solutions) and numerous examples of cryptography Provides an introduction into number theory, game theory, coding theory, and information theory as background for the coverage of cryptography Covers cryptography topics such as CRT, affine ciphers, hashing functions, substitution ciphers, unbreakable ciphers, Discrete Logarithm Problem (DLP), and more

One aspect of common sense reasoning is reasoning about normal cases, e.g. a physician will first try to interpret symptoms by a common disease, and will take more exotic possibilities only later into account. Such "normality" can be encoded, e.g. by
a relation, where case A is considered more normal than case B. This gives a standard semantics or interpretation to nonmonotonic reasoning (a branch of common sense reasoning), or, more formally, to nonmonotonic logics. We consider in this book the repercussions such normality relations and similar
constructions have on the resulting nonmonotonic logics, i.e. which types of logic are adequate for which kind of relation, etc.
We show in this book that some semantics correspond nicely to some logics, but also that other semantics do not correspond to any logics of the usual form.
Key features:
- provides a coherent picture of several formalisms of nonmonotonic logics.
- gives completeness and incompleteness results for many variants of preferential, distance based, and other semantics.
- gives probably the first systematic investigation of definability preservation and its consequences.
- gives new proof techniques for completeness results.
- is centered on semantics

Computational Modelling of Nanoparticles highlights recent advances in the power and versatility of computational modelling, experimental techniques, and how new progress has opened the door to a more detailed and comprehensive understanding of the world of nanomaterials. Nanoparticles, having dimensions of 100 nanometers or less, are increasingly being used in applications in medicine, materials and manufacturing, and energy. Spanning the smallest sub-nanometer nanoclusters to nanocrystals with diameters of 10s of nanometers, this book provides a state-of-the-art overview on how computational modelling can provide, often otherwise unobtainable, insights into nanoparticulate structure and properties. This comprehensive, single resource is ideal for researchers who want to start/improve their nanoparticle modelling efforts, learn what can be (and what cannot) achieved with computational modelling, and understand more clearly the value and details of computational modelling efforts in their area of research.

The utilization of information and communication technologies in almost all spheres of modern society has changed the social picture in significant ways while simultaneously leading to tensions with regard to traditional ethical and legal practices-particularly given the global context of its application. Where these technologies impact on the practice and implementation of healthcare, it is vital to recognize the extent and nature of the ethical and social impact both at the level of professional practice and the patient. Ethical, Legal and Social Issues in Medical Informatics presents a fundamental compendium of research on the ethical, social, and legal issues facing the healthcare industry as it adopts information technologies to provide fast, efficient, and cost effective healthcare. An essential resource for every reference library, this comprehensive book offers a multidisciplinary perspective, drawing from the expertise of a wide variety of global industries including law, ethics, medicine, philosophy, and computer science.

Accessible to all readers, including students of secondary school and amateur technology enthusiasts, Robotics, Mechatronics, and Artificial Intelligence simplifies the process of finding basic circuits to perform simple tasks, such as how to control a DC or step motor, and provides instruction on creating moving robotic parts, such as an "eye" or an "ear." Though many companies offer kits for project construction, most experimenters want to design and build their own robots and other creatures specific to their needs and goals. With this new book by Newton Braga, hobbyists and experimenters around the world will be able to decide what skills they want to feature in a project and then choose the right "building blocks" to create the ideal results.
In the past few years the technology of robotics, mechatronics, and artificial intelligence has exploded, leaving many people with the desire but not the means to build their own projects. The author's fascination with and expertise in the exciting field of robotics is demonstrated by the range of simple to complex project blocks he provides, which are designed to benefit both novice and experienced robotics enthusiasts. The common components and technology featured in the project blocks are especially beneficial to readers who need practical solutions that can be implemented easily by their own hands, without incorporating expensive, complicated technology.
Accessible to technicians and hobbyists with many levels of experience, and written to provide inexpensive and creative fun with robotics
Appeals to all sorts of technology enthusiasts, including those involved with electronics, computers, home automation, mechanics, and other areas.

This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profi table cloud manufacturing will be gathered to present advanced and specialized research in the selected area.

This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.

The association of personal time management research with calendar applications has remained a relatively under-researched area due to the complexity and challenges it faces. ""Temporal Structures in Individual Time Management: Practices to Enhance Calendar Tool Design"" covers the latest concepts, methodologies, techniques, tools, and perspectives essential to understanding individual time management experiences. Emphasizing personal temporal structure usage involving calendar tools, this book provides both qualitative and quantitative evidences and insights valuable for researchers and practitioners in enhancing current electronic calendar systems design and implementation.

As the most natural and convenient means of conveying or transmitting information, images play a vital role in our daily lives. Image processing is now of paramount importance in the computer vision research community, and proper processing of two-dimensional (2D) real-life images plays a key role in many real-life applications as well as commercial developments. Intelligent Multidimensional Data and Image Processing is a vital research publication that contains an in-depth exploration of image processing techniques used in various applications, including how to handle noise removal, object segmentation, object extraction, and the determination of the nearest object classification and its associated confidence level. Featuring coverage on a broad range of topics such as object detection, machine vision, and image conversion, this book provides critical research for scientists, computer engineers, professionals, researchers, and academicians seeking current research on solutions for new challenges in 2D and 3D image processing.

As global communities are attempting to transform into more efficient and technologically-advanced metropolises, artificial intelligence (AI) has taken a firm grasp on various professional fields. Technology used in these industries is transforming by introducing intelligent techniques including machine learning, cognitive computing, and computer vision. This has raised significant attention among researchers and practitioners on the specific impact that these smart technologies have and what challenges remain. Applications of Artificial Intelligence for Smart Technology is a pivotal reference source that provides vital research on the implementation of advanced technological techniques in professional industries through the use of AI. While highlighting topics such as pattern recognition, computational imaging, and machine learning, this publication explores challenges that various fields currently face when applying these technologies and examines the future uses of AI. This book is ideally designed for researchers, developers, managers, academicians, analysts, students, and practitioners seeking current research on the involvement of AI in professional practices.

This book comprises the proceedings of the 4th International Conference on Computational Engineering (ICCE 2017), held in Darmstadt, Germany on September 28-29, 2017. The conference is intended to provide an interdisciplinary meeting place for researchers and practitioners working on computational methods in all disciplines of engineering, applied mathematics and computer science. The aims of the conference are to discuss the state of the art in this challenging field, exchange experiences, develop promising perspectives for future research and initiate further cooperation. Computational Engineering is a modern and multidisciplinary science for computer-based modeling, simulation, analysis, and optimization of complex engineering applications and natural phenomena. The book contains an overview of selected approaches from numerics and optimization of Partial Differential Equations as well as uncertainty quantification techniques, typically in multiphysics environments. Where possible, application cases from engineering are integrated. The book will be of interest to researchers and practitioners of Computational Engineering, Applied Mathematics, Engineering Sciences and Computer Science.

In this third edition of Vehicle Accident Analysis & Reconstruction Methods, Raymond M. Brach and R. Matthew Brach have expanded and updated their essential work for professionals in the field of accident reconstruction. Most accidents can be reconstructed effectively using of calculations and investigative and experimental data: the authors present the latest scientific, engineering, and mathematical reconstruction methods, providing a firm scientific foundation for practitioners. Accidents that cannot be reconstructed using the methods in this book are rare. In recent decades, the field of crash reconstruction has been transformed through the use of technology. The advent of event data records (EDRs) on vehicles signaled the era of modern crash reconstruction, which utilizes the same physical evidence that was previously available as well as electronic data that are measured/captured before, during, and after the collision. There is increased demand for more professional and accurate reconstruction as more crash data is available from vehicle sensors. The third edition of this essential work includes a new chapter on the use of EDRs as well as examples using EDR data in accident reconstruction. Early chapters feature foundational material that is necessary for the understanding of vehicle collisions and vehicle motion; later chapters present applications of the methods and include example reconstructions. As a result, Vehicle Accident Analysis & Reconstruction Methods remains the definitive resource in accident reconstruction.

This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) in Boston, MA, March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

"This book is a boon to technology professionals who are responsible for global integration projects. Faced with the mind-boggling complexities of standardizing global data, global processes and global e-commerce, even the most experienced professionals are often at a loss. James Bean has created an extraordinary compilation of standards information, and provided his insight on how to resolve complex integration problems. This book will benefit IT community at large, and I would encourage both specialists and novices alike to bring this book into their personal libraries." -- Arka Mukherjee, Ph.D., CEO, Global IDs Inc.
A practitioner's guide to developing global e-commerce sites, focusing on the design and engineering of Web forms for global data collection and alignment with widely recognized international standards, XML structures, and XML vocabularies. The author describes the globalization problem, identifies common design errors, provides a representative scenario, and introduces effective solutions and techniques.
Structured around a practical, "real-world" theme, this book is written for the hands-on practicioner in any mid- to large-sized company engaging in international ecommerce (B2C, B2B, etc.)
* Presents effective techniques for flexible and extensible data capture
* Provides techniques for using the most recognized international data standards and describes the synergies, value and importance of XML as a transaction definition medium
* Only book on the subject written from a software engineering point of view

There is a broad consensus amongst law firms and in-house legal departments that next generation "Legal Tech" - particularly in the form of Blockchain-based technologies and Smart Contracts - will have a profound impact on the future operations of all legal service providers. Legal Tech startups are already revolutionizing the legal industry by increasing the speed and efficiency of traditional legal services or replacing them altogether with new technologies. This on-going process of disruption within the legal profession offers significant opportunities for all business. However, it also poses a number of challenges for practitioners, trade associations, technology vendors, and regulators who often struggle to keep up with the technologies, resulting in a widening regulatory "gap." Many uncertainties remain regarding the scope, direction, and effects of these new technologies and their integration with existing practices and legacy systems. Adding to the challenges is the growing need for easy-to-use contracting solutions, on the one hand, and for protecting the users of such solutions, on the other. To respond to the challenges and to provide better legal communications, systems, and services Legal Tech scholars and practitioners have found allies in the emerging field of Legal Design. This collection brings together leading scholars and practitioners working on these issues from diverse jurisdictions. The aim is to introduce Blockchain and Smart Contract technologies, and to examine their on-going impact on the legal profession, business and regulators.

This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.

This book presents original, peer-reviewed research papers from the 4th Purple Mountain Forum -International Forum on Smart Grid Protection and Control (PMF2019-SGPC), held in Nanjing, China on August 17-18, 2019. Addressing the latest research hotspots in the power industry, such as renewable energy integration, flexible interconnection of large scale power grids, integrated energy system, and cyber physical power systems, the papers share the latest research findings and practical application examples of the new theories, methodologies and algorithms in these areas. As such book a valuable reference for researchers, engineers, and university students.