Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides general knowledge on all aspects of uncertainties in the weather prediction models in a single, easy to use reference. The book illustrates particular uncertainties in observations and data assimilation, as well as the errors associated with numerical integration methods. Stochastic methods in parameterization of subgrid processes are also assessed, as are uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer. Through a better understanding of the uncertainties to watch for, readers will be able to produce more precise and accurate forecasts. This is an essential work for anyone who wants to improve the accuracy of weather and climate forecasting and interested parties developing tools to enhance the quality of such forecasts.

Everyday Innovators explores the active role of people, collectively and individually, in shaping the use of information and communication technologies. It examines issues around acquiring and using that knowledge of users, how we should conceptualise the role of users and understand the forms and limitations of their participation.

• To what extent should we think of users as being innovative and creative?
• To what extent is this routine or exceptional, confined to particular group of users or part of many people 's experience of technologies?
• Where does the nature of the ICT or the particularities of its design impose constraints on the active role that users can play in their interaction with devices and services?
• Where do the horizons and orientations of the users influence or limit what they want and expect of their ICTs and how they use them?

This book enables a cross-fertilisation of perspectives from different disciplines and aims to provide new insights into the role of users, drawing out both applied and theoretical implications

This book provides an accessible introduction and practical guidelines to apply asymmetric multidimensional scaling, cluster analysis, and related methods to asymmetric one-mode two-way and three-way asymmetric data. A major objective of this book is to present to applied researchers a set of methods and algorithms for graphical representation and clustering of asymmetric relationships. Data frequently concern measurements of asymmetric relationships between pairs of objects from a given set (e.g., subjects, variables, attributes,...), collected in one or more matrices. Examples abound in many different fields such as psychology, sociology, marketing research, and linguistics and more recently several applications have appeared in technological areas including cybernetics, air traffic control, robotics, and network analysis. The capabilities of the presented algorithms are illustrated by carefully chosen examples and supported by extensive data analyses. A review of the specialized statistical software available for the applications is also provided. This monograph is highly recommended to readers who need a complete and up-to-date reference on methods for asymmetric proximity data analysis.

The nonequilibrium behavior of nanoscopic and biological systems, which are typically strongly fluctuating, is a major focus of current research. Lately, much progress has been made in understanding such systems from a thermodynamic perspective. However, new theoretical challenges emerge when the fluctuating system is additionally subject to time delay, e.g. due to the presence of feedback loops. This thesis advances this young and vibrant research field in several directions. The first main contribution concerns the probabilistic description of time-delayed systems; e.g. by introducing a versatile approximation scheme for nonlinear delay systems. Second, it reveals that delay can induce intriguing thermodynamic properties such as anomalous (reversed) heat flow. More generally, the thesis shows how to treat the thermodynamics of non-Markovian systems by introducing auxiliary variables. It turns out that delayed feedback is inextricably linked to nonreciprocal coupling, information flow, and to net energy input on the fluctuating level.

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.

An Introduction to Stata for Health Researchers, Fifth Edition updates this classic book that has become a standard reference for health researchers. As with previous editions, readers will learn to work effectively in Stata to perform data management, compute descriptive statistics, create meaningful graphs, fit regression models, and perform survival analysis. The fifth edition adds examples of performing power, precision, and sample-size analysis; working with Unicode characters; managing data with ICD-9 and ICD-10 codes; and creating customized tables. With many worked examples and downloadable datasets, this text is the ideal resource for hands-on learning, whether for students in a statistics course or for researchers in fields such as epidemiology, biostatistics, and public health who are learning to use Stata's tools for health research.

30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries.

"As esports has grown, the need for professional legal representation has grown with it. Justin's Essential Guide to the Business & Law of Esports & Professional Video Gaming provides a great baseline and will help prevent the legal horror stories of esports in the past." Mitch Reames, AdWeek and Esports Insider "Justin's exploration of the business and law side of the esports sector fills a gap of knowledge that is an absolute necessity in truly understanding the esports space." Kevin Hitt, The Esports Observer The Essential Guide to the Business & Law of Esports & Professional Video Gaming covers everything you need to know about the past, present, and future of esports and professional video gaming. The book is written by one of the foremost attorneys and business practitioners in today's esports and professional gaming scene, Justin M. Jacobson, Esq. This guide is meant to provide you with an in-depth look at the business and legal matters associated with the esports world. * Includes coverage of the stakeholders in the esports business "ecosystem," including the talent, the teams, the publishers, and the event organizers. * Explores various legal fields involved with esports, including intellectual property, employment and player unions, business investments and tax "write-offs," immigration and visas, event operation tips, social media and on-stream promotions, and much more. * The most current book on the market, with actual contract provisions modeled on existing major esports player, coach, shoutcaster, and sponsorship agreements. About the Author Justin M. Jacobson, Esq. is an entertainment and esports attorney located in New York City. For the last decade, he has worked with professional athletes, musicians, producers, DJs, record labels, fashion designers, as well as professional gamers, streamers, coaches, on-air talent, and esports organizations. He assists these creative individuals with their contract, copyright, trademark, immigration, tax, and related business, marketing, and legal issues. He is a frequent contributor to many industry publications and has been featured on a variety of entertainment, music, and esports publications and podcasts, including Business Insider, The Esports Observer, Esports Insider, Tunecore, and Sport Techie. Justin has positioned himself as a top esports business professional working with talent in a variety of franchise leagues including the Overwatch League, Overwatch Contenders, and Call of Duty Pro League as well as in many popular competitive titles such as Fortnite, CS:GO, Gears of War, Halo, Super Smash Brothers, Rainbow 6, PUBG, Madden, and FIFA and mobile games such as Brawlhalla, Clash of Clans, and Call of Duty mobile. Previously, he worked with various esports talent agencies as well as in an official capacity on behalf of several esports teams and brands.

Attacks on information systems and applications have become more prevalent with new advances in technology. Management of security and quick threat identification have become imperative aspects of technological applications. Information Technology Risk Management and Compliance in Modern Organizations is a pivotal reference source featuring the latest scholarly research on the need for an effective chain of information management and clear principles of information technology governance. Including extensive coverage on a broad range of topics such as compliance programs, data leak prevention, and security architecture, this book is ideally designed for IT professionals, scholars, researchers, and academicians seeking current research on risk management and compliance.

This thesis presents a revolutionary technique for modelling the dynamics of a quantum system that is strongly coupled to its immediate environment. This is a challenging but timely problem. In particular it is relevant for modelling decoherence in devices such as quantum information processors, and how quantum information moves between spatially separated parts of a quantum system. The key feature of this work is a novel way to represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and process tensor approaches to quantum mechanics. The tensor network methodology developed here has proven to be extremely powerful: For many situations it may be the most efficient way of calculating open quantum dynamics. This work is abounds with new ideas and invention, and is likely to have a very significant impact on future generations of physicists.

Design Science Research is a powerful paradigm enabling researchers to make important contributions to society and industry. Simply stated, the goal of DSR is to generate knowledge on how to find innovative solutions to important problems in the form of models, methods, constructs and instantiations. Over the past 20 years, the design science research (DSR) paradigm has developed into an established paradigm in Information Systems Research and it is of strong uptake in many other disciplines, including Management Science and Computer Science. This book provides a collection of twelve DSR cases, presented by experienced researchers in the field. It offers readers access to real-world DSR studies, together with the authors' reflections on their research processes. These cases will support researchers who want to engage in DSR, and represent a valuable addition to existing introductions to DSR methods and processes. Readers will learn from the hands-on experiences of respected experts who have conducted extensive DSR in a range of application contexts.

THE GUIDE FOR ANYONE AFRAID TO LEARN STATISTICS & ANALYTICS UPDATED WITH NEW EXAMPLES & EXERCISES This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldn't learn these data analysis subjects because they were too technical or too mathematical, this book is for you! This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel. You'll use downloadable data sets and spreadsheet solutions, template-based solutions you can put right to work. Using this book, you will understand the important concepts of statistics and analytics, including learning the basic vocabulary of these subjects. Create tabular and visual summaries and learn to avoid common charting errors Gain experience working with common descriptive statistics measures including the mean, median, and mode; and standard deviation and variance, among others Understand the probability concepts that underlie inferential statistics Learn how to apply hypothesis tests, using Z, t, chi-square, ANOVA, and other techniques Develop skills using regression analysis, the most commonly-used Inferential statistical method Explore results produced by predictive analytics software Choose the right statistical or analytic techniques for any data analysis task Optionally, read the "Equation Blackboards," designed for readers who want to learn about the mathematical foundations of selected methods

This book gathers a selection of invited and contributed lectures from the European Conference on Numerical Mathematics and Advanced Applications (ENUMATH) held in Lausanne, Switzerland, August 26-30, 2013. It provides an overview of recent developments in numerical analysis, computational mathematics and applications from leading experts in the field. New results on finite element methods, multiscale methods, numerical linear algebra and discretization techniques for fluid mechanics and optics are presented. As such, the book offers a valuable resource for a wide range of readers looking for a state-of-the-art overview of advanced techniques, algorithms and results in numerical mathematics and scientific computing.

This book shows how information theory, probability, statistics, mathematics and personal computers can be applied to the exploration of numbers and proportions in music. It brings the methods of scientific and quantitative thinking to questions like: What are the ways of encoding a message in music and how can we be sure of the correct decoding? How do claims of names hidden in the notes of a score stand up to scientific analysis? How many ways are there of obtaining proportions and are they due to chance? After thoroughly exploring the ways of encoding information in music, the ambiguities of numerical alphabets and the words to be found "hidden" in a score, the book presents a novel way of exploring the proportions in a composition with a purpose-built computer program and gives example results from the application of the techniques. These include information theory, combinatorics, probability, hypothesis testing, Monte Carlo simulation and Bayesian networks, presented in an easily understandable form including their development from ancient history through the life and times of J. S. Bach, making connections between science, philosophy, art, architecture, particle physics, calculating machines and artificial intelligence. For the practitioner the book points out the pitfalls of various psychological fallacies and biases and includes succinct points of guidance for anyone involved in this type of research. This book will be useful to anyone who intends to use a scientific approach to the humanities, particularly music, and will appeal to anyone who is interested in the intersection between the arts and science.With a foreword by Ruth Tatlow (Uppsala University), award winning author of Bach's Numbers: Compositional Proportion and Significance and Bach and the Riddle of the Number Alphabet."With this study Alan Shepherd opens a much-needed examination of the wide range of mathematical claims that have been made about J. S. Bach's music, offering both tools and methodological cautions with the potential to help clarify old problems." Daniel R. Melamed, Professor of Music in Musicology, Indiana University

Continuous improvements in digitized practices have created opportunities for businesses to develop more streamlined processes. This not only leads to higher success in day-to-day production, but it increases the overall success of businesses. Always-On Enterprise Information Systems for Modern Organizations is a critical scholarly resource that examines how EIS implementations support business processes and facilitate this in today's e-business environment. Featuring coverage on a broad range of topics such as customer relations management, supply chain management, and business intelligence, this book is geared towards professionals, researchers, managers, consultants, and university students interested in emerging developments for business process management.

This book provides an in-depth investigation of the quality relevant perceptual video space in the domain of videotelephony. The author presents an extensive investigation and quality modeling of the underlying video quality dimensions and the overall quality. The author examines the underlying quality dimensions and describes a method for subjective evaluation as well as the instrumental estimation of video quality in videotelephony. The book presents a new subjective test method in the field of video quality assessment. Further, it explains the experimental examination of the underlying video quality dimensions and the subjective-based, as well as instrumental-based quality estimation. Provides an investigation of the underlying quality dimensions of video in videotelephony; Presents insights into a new subjective test method, standardized as ITU-T Rec. P.918; Includes insights into the subjective and instrumental video quality estimation.

This book is concerned exclusively with discrete-time queues and their applications to the performance modeling of communication and computer networks. Since most modern networks operate on the basis of time slotting, and transmit information in fixed length (packets or cells), it thus becomes natural to model such networks in discrete-time by associating a time slot in a physical network with the unit time in the corresponding discrete-time model. The book shows how, in this way, very accurate models that faithfully reproduce the stochastic behaviour of a communication or computer network can be constructed.

The treatment is self contained, and progresses from basic probability theory and discrete-time queueing networks. These latter are applied to model the performance of numerous wide area satellite networks and local area networks, ranging in complexity from simple Aloha schemes to the timed token protocol of the FDDI network. The main objective of this book is to present a unified method for modeling any network access protocol as a discrete-time queueing network and t develop efficient solution techniques for these models. A significant number of the models and their solutions which are included have not previously appeared in the open literature.

The text should prove useful to practitioners and researchers concerned with communication and computer network performance modeling, or anyone wanting a sound understanding of the application of discrete-time technique to this subject area.

This book reports on research findings and practical lessons featuring advances in: digital and interaction design; graphic design and branding; design strategies and methodologies; design education; society and communication in design practice; and other related areas. Gathering the proceedings of the 4th International Conference on Digital Design and Communication, Digicom 2020, held virtually on November 5-6, 2020, the book describes cutting-edge perspectives on and analysis of and solutions to challenges digital communication is currently presenting to society, institutions and brands. It offers a timely guide and a source of inspiration for designers of all kinds, including graphic, digital and web designers, UI, UX and social media designers, and to researchers, advertisers, artists, and entrepreneurs, as well as brand or corporate communication managers.

Incorporating recent developments in control and systems research, "Linear Control Theory" provides the fundamental theoretical background needed to fully exploit control system design software. This logically-structured text opens with a detailed treatment of the relevant aspects of the state space analysis of linear systems. End-of-chapter problems facilitate the learning process by encouraging the student to put his or her skills into practice. Features include:

• The use of an easy to understand matrix variational technique to develop the time-invariant quadratic and LQG controllers
• A step-by-step introduction to essential mathematical ideas as they are needed, motivating the reader to venture beyond basic concepts
• The examination of linear system theory as it relates to control theory
• The use of the PBH test to characterize eigenvalues in the state feedback and observer problems rather than its usual role as a test for controllability or observability
• The development of model reduction via balanced realization
• The employment of the L2 gain as a basis for the development of the H??? controller for the design of controllers in the presence of plant model uncertainty

This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.

A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source. Key features: Allows you to learn R and Python in parallel Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools - data.table and pandas Provides a concise and accessible presentation Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc. Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective.