Using a unique in-depth, case-based approach, Cengage's NEW PERSPECTIVES COLLECTION, MICROSOFT (R) 365 (R) & EXCEL (R) 2021 COMPREHENSIVE helps you prepare for the Microsoft (R) Office (R) Specialist (MOS) certification exam -- and success in your future career. As you apply Microsoft (R) Office (R) skills to real-world business scenarios based on Burning Glass market insights, you will sharpen your critical-thinking and problem-solving skills. Professional tips and insights incorporated throughout provide context and relevancy to real-world practice, while ProSkills Boxes help strengthen your employability skills, including written and verbal communication. The text also offers updated coverage of Microsoft (R) 365 (R) features as well as enhanced support for Mac users. In addition, MindTap and up-to-date SAM (Skills Assessment Manager) online resources provide interactive study tools to help maximize your study time -- and results.

This comprehensive and timely publication aims to be an essential reference source, building on the available literature in the field of Gamification for the economic and social development of countries while providing further research opportunities in this dynamic and growing field. Thus, the book aims to provide the opportunity for a reflection on this important issue, increasing the understanding of the importance of Gamification in the context of organizations' improvements, providing relevant academic work, empirical research findings and, an overview of this relevant field of study. This text will provide the resources necessary for policymakers, technology developers, and managers to adopt and implement solutions for a more digital era.

Numerical partial differential equations (PDEs) are an important part of numerical simulation, the third component of the modern methodology for science and engineering, besides the traditional theory and experiment. This volume contains papers that originated with the collaborative research of the teams that participated in the IMA Workshop for Women in Applied Mathematics: Numerical Partial Differential Equations and Scientific Computing in August 2014.

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval. The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book. This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.

As Service-Oriented Computing (SOC) gains a wider global acceptance, the need for understanding its life cycle becomes inevitable, not only for developers, but also for users. Service Life Cycle Tools and Technologies: Methods, Trends and Advances compiles the latest research on SOC life cycles, detailing methodologies and applications in this emerging field. The development of service-oriented applications not only depends on constructing service providers, but also composition and delivery. Service requesters, service providers, and developers, alike, will benefit from the views and models in a service life cycle. This volume offers research that has been conducted in both industry and academia to address issues in the SOC domain, including service discovery, service composition, and service management. It serves as a vital reference for those on either side of the service field.

Interest in the area of control of systems defined by partial differential Equations has increased strongly in recent years. A major reason has been the requirement of these systems for sensible continuum mechanical modelling and optimization or control techniques which account for typical physical phenomena. Particular examples of problems on which substantial progress has been made are the control and stabilization of mechatronic structures, the control of growth of thin films and crystals, the control of Laser and semi-conductor devices, and shape optimization problems for turbomachine blades, shells, smart materials and microdiffractive optics. This volume contains original articles by world reknowned experts in the fields of optimal control of partial differential equations, shape optimization, numerical methods for partial differential equations and fluid dynamics, all of whom have contributed to the analysis and solution of many of the problems discussed. The collection provides a state-of-the-art overview of the most challenging and exciting recent developments in the field. It is geared towards postgraduate students and researchers dealing with the theoretical and practical aspects of a wide variety of high technology problems in applied mathematics, fluid control, optimal design, and computer modelling.

The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection of short articles - most of which having a review component - describing the state-of-the art of Nonparametric Statistics at the beginning of a new millennium.

Key features:

algorithic approaches
wavelets and nonlinear smoothers
graphical methods and data mining
biostatistics and bioinformatics
bagging and boosting
support vector machines
resampling methods
"

This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)-an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation.

Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas. There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of applied work, and these contributions have been externally refereed to the high quality standards of leading journals in the field.

This book offers a systematic introduction to an understanding-oriented approach to multimedia content analysis. It integrates the visual understanding and learning models into a unified framework, within which the visual understanding guides the model learning while the learned models improve the visual understanding. More specifically, it discusses multimedia content representations and analysis including feature selection, feature extraction, image tagging, user-oriented tag recommendation and understanding-oriented multimedia applications. The book was nominated by the University of Chinese Academy of Sciences and China Computer Federation as an outstanding PhD thesis. By providing the fundamental technologies and state-of-the-art methods, it is a valuable resource for graduate students and researchers working in the field computer vision and machine learning.

Recent decades have seen a very rapid success in developing numerical methods based on explicit control over approximation errors. It may be said that nowadays a new direction is forming in numerical analysis, the main goal of which is to develop methods ofreliable computations. In general, a reliable numerical method must solve two basic problems: (a) generate a sequence of approximations that converges to a solution and (b) verify the accuracy of these approximations. A computer code for such a method must consist of two respective blocks: solver and checker.
In this book, we are chiefly concerned with the problem (b) and try to present the main approaches developed for a posteriori error estimation in various problems.
The authors try to retain a rigorous mathematical style, however, proofs are constructive whenever possible and additional mathematical knowledge is presented when necessary. The book contains a number of new mathematical results and lists a posteriori error estimation methods that have been developed in the very recent time.
- computable bounds of approximation errors
- checking algorithms
- iteration processes
- finite element methods
- elliptic type problems
- nonlinear variational problems
- variational inequalities

Effective technologies and tools for e-collaboration are central to the development and evolution of modern work and educational landscapes. Studies on the design, implementation, and evaluation of e-collaboration applications help individuals and businesses in their pursuit of effective tools for increasingly virtual modes of communication. Advancing Collaborative Knowledge Environments: New Trends in E-Collaboration discusses the latest findings in knowledge-intensive, collaborative environments, focusing on frameworks and solutions for improving collaboration online. Uniting research on the effectiveness of instant messaging, the role of presence and awareness in real-time collaboration, and other key concepts, this reference is useful for those interested in frameworks for new collaboration technologies, as well as existing users of new technologies and applications.

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted form this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.

In order to be useful and transfer adequate knowledge skills to the learner, a multimedia program design needs to have a sound pedagogical base. Technology-Assisted Problem Solving for Engineering Education: Interactive Multimedia Applications explores best practices in assisting students in understanding engineering concepts through interactive and virtual environments. A critical mass of leading international findings, this advanced publication delivers quality research using learning and consultancy for developing tactics to decipher dilemmas within the field.

This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students working with linear state space models, and who are familiar with linear algebra and possess some knowledge of statistics.

The first wave of Overwatch cinematics captured the imagination of millions of fans around the world. After the game released in 2016, Blizzard Entertainment embarked on a new mission to take cinematic storytelling to the next level. From the intense, action-packed rush of "Shooting Star" to the somber, noble ethos of "Honor and Glory," the creative team wanted to highlight a different side of the game's beloved heroes. In pursuit of their objectives, the crew added new artists in the mix, devised novel methods for making movies, and ventured into formats they hadn't tried before, such as in-game cinematics and stop-motion animation. Covering all the official Overwatch cinematics made from 2017-2020, including the Overwatch 2 announcement trailer, The Cinematic Art of Overwatch: Volume II showcases hundreds of pieces of never-before-seen artwork and documents the epic creative journey that Blizzard took to bring these films to life.

This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.

Excel-erate your productivity with the only guide you'll need to the latest versions of Microsoft Excel Microsoft Excel offers unsurpassed functionality and accessibility for data exploration and analysis to millions of users around the world. And learning to unlock its full potential is easier than you can imagine with help from Excel All-in-One For Dummies. Follow along with Excel expert and veteran author Paul McFedries as he walks you through every feature and technique you need to know to get the most out of this powerful software. You'll learn how to design worksheets, use formulas and functions, collaborate with colleagues and review their work, create charts and graphics, manage and analyze data, and create macros. Plus, you'll discover all the capabilities Microsoft has included in the newest versions of Excel, including dark mode and accessibility features. This indispensable reference allows you to: Get a firm grasp of Excel basics with the book's step-by-step guides before moving on to more advanced topics, like data analysis Access up-to-date information on all the new versions of Excel, including the ones bundled with Microsoft 365, Office 2021, and the LTSC/Enterprise Edition Enjoy the convenience of a single, comprehensive resource detailing everything you need to know about Excel Perfect for people coming to Excel for the very first time, Excel All-in-One For Dummies, Office 2021 Edition is also a must-read resource for anyone looking for a refresher on foundational or advanced Excel techniques.

The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.

"By guiding teachers and their students through the workings of Excel, this book ultimately leads to high-ordered decision making about data management and interpretation?a compelling reality of the 21^st century."
Nancy Tanner Edwards, Professor of Education
Missouri Western State College
St. Joseph, MO

  Make Microsoft Excel™ work for you?in the classroom and at your desk!

Using Excel in the Classroom is the essential how-to for teachers at all grade levels, filled with specific, classroom-tested templates, and techniques that teachers need most!

This book covers the key advances in computerized facial beauty analysis, with an emphasis on data-driven research and the results of quantitative experiments. It takes a big step toward practical facial beauty analysis, proposes more reliable and stable facial features for beauty analysis and designs new models, methods, algorithms and schemes while implementing a facial beauty analysis and beautification system. This book also tests some previous putative rules and models for facial beauty analysis by using computationally efficient mathematical models and algorithms, especially large scale database-based and repeatable experiments.The first section of this book provides an overview of facial beauty analysis. The base of facial beauty analysis, i.e., facial beauty features, is presented in part two. Part three describes hypotheses on facial beauty, while part four defines data-driven facial beauty analysis models. This book concludes with the authors explaining how to implement their new facial beauty analysis system.This book is designed for researchers, professionals and post graduate students working in the field of facial beauty analysis, computer vision, human-machine interface, pattern recognition and biometrics. Those involved in interdisciplinary fields with also find the contents useful. The ideas, means and conclusions for beauty analysis are valuable for researchers and the system design and implementation can be used as models for practitioners and engineers.