Official art book of the PS5 launch game Marvel's Spider-Man: Miles Morales, featuring concept art created during the development of the game.

Be greater, be yourself as Miles Morales swings onto the scene in his own video game for the first time. Learning the ropes as Spider-Man in Peter Parker s absence, Miles must find the balance between keeping his new home, Harlem, safe and rising up to take on new challenges and enemies that test his abilities and loyalties to the limit.

The creative process of this much-anticipated game is captured in Marvel s Spider-Man: Miles Morales The Art of the Game. This lush, hardback book showcases the remarkable concept art and in-game renderings created by the talented development team creating the game in collaboration with Marvel. Characters, locations, tech, gadgets, Spider suits and much more are presented in all their incredible detail, accompanied by unique insights from the artists and developers behind the game.

This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image, audio, video, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling comprehensive visual classification to fill the semantic gap by exploring large-scale data, offering a promising frontier for detailed multimedia understanding, as well as extract patterns and making effective decisions by analyzing the large collection of data.

This work contains an up-to-date coverage of the last 20 years' advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods. This book is intended for econometrics and statistics postgraduates, professors and researchers in economics departments, business schools, statistics departments, or any research centre in the same fields, especially econometricians.

Use Excel 365 and Excel 2021 core features to build spreadsheets that solve business problems and deliver reliable answers. Drawing on his unsurpassed experience, Paul McFedries helps you make the most of formulas and functions, including recent improvements ranging from dynamic arrays to XLOOKUP and LET. McFedries' step-by-step projects walk you through handling key tasks, from building timesheets to projecting cash flow and aging receivables. His practical examples and clear instructions demystify intermediate-to-advanced-level formula construction, and help you leverage Excel's most useful functions in your everyday work. Becoming an Excel expert has never been easier! By reading this book, you will: Improve business analyses by adding intelligence and knowledge to your models Replace cumbersome formulas with convenient predefined functions Use modern lookups to make your formulas more powerful and flexible Simplify complex calculations with dynamic arrays in Excel 365 and Excel 2021 Use conditional formatting to reveal anomalies, problems, or opportunities Calculate loan payments, interest costs, terms, and amortization schedules Project the future value of investments, and plan to achieve investment goals Master essential discounting and cash-flow analysis tools, including NPV and IRR Sort, filter, and analyze any tabular data, from customers to inventory Easily analyze huge datasets with PivotTable calculations Perform sophisticated what-if analyses, scenario planning, and forecasting Optimize profit, cost, or operational efficiency with Solver About This Book For everyone who wants to get more done with Microsoft Excel in less time For business and financial professionals, entrepreneurs, students, and others who need to efficiently manage and analyze data

Multimedia Document Systems in Perspectives brings together in one place important contributions and up-to-date research results in this fast moving area. Multimedia Document Systems in Perspectives serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

This book provides the foundation and understanding necessary for proper design of databases for today's distributed and multi-database architectures. Introductory chapters help novices understand essential topics such as SQL, relational databases, transaction processing, and deadlock detection, while subsequent sections dealing with homogeneous, distributed databases, heterogeneous multi-databases, and federated databases enable readers to understand the complexities of distributed database design. Packed with over 200 illustrations, 50 equations, and two full chapters of examples.

COOP 2010 is the 9th edition of the International Conference on Designing Cooperative Systems, being the second European conference in the field of Computer Supported Cooperative Work after ECSCW. The conference brings together researchers who contribute to the analysis and design of cooperative systems and their integration in organizational community, public and other settings, and their implications for policy and decision making. Cooperative systems design requires a deep understanding of collective activities, involving both artifacts and social practices. Contributions are solicited from a wide range of domains contributing to the fields of cooperative systems design and evaluation: CSCW, HCI, Information Systems, Knowledge Engineering, Multi-agents, organizational and management sciences, sociology, psychology, anthropology, ergonomics, linguistics.

This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems. The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first summarized in this book, which offers a comprehensive preamble for further problem-oriented chapters. The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks. Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful.

Over the past thirty years, with improvements in optics, electronics, and computer technology, great strides have been made in the quantitative analysis of the visual system. A number of books on eye movement research have been written that have dealt with specific aspects of either eye movement control. However, none of these books provide a comprehensive overview of multiple aspects of the visual system. Moreover, few of these books contain modeling and detailed quantitative analyses of the visual system. Further, since the major books are almost ten years old, there is a need for an update to include the most recent research findings. It is with these considerations in mind that we have carefully compiled this updated, comprehensive, and quantitative model-based edited book on various components of the visual system. Some of the best vision scientists in the world in their respective fields have contributed to chapters in this book. They have expertise in a wide variety of fields, including bioengineering, basic and clinical visual science, medicine, neurophysiology, optometry, and psychology. Their combined efforts have resulted in a high quality book that covers modeling and quantitative analysis of optical, neurosensory, oculomotor, perceptual and clinical systems. It includes only those techniques and models that have such fundamentally strong physiological, control system, and perceptual bases that they will serve as foundations for models and analysis techniques in the future. The book is aimed first towards seniors and beginning graduate students in biomedical engineering, neurophysiology, optometry, and psychology, who will gain a broad understanding of quantitative analysisof the visual system. In addition, it has sufficient depth in each area to be useful as an updated reference and tutorial for graduate and post-doctoral students, as well as general vision scientists.

The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020. The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product

The COVID-19 pandemic affected a wide range of global sectors, but one of the most important is education. The transition from classroom to computer screen was a difficult one for many Asian students, parents, and teachers. Since this transition, global education systems now mostly depend on online technology. It is crucial that the impact of the pandemic on education is not only examined from a Western point of view, but also from Eastern perspectives. The Handbook of Research on Asian Perspectives of the Educational Impact of COVID-19 provides the current issues the education sector is facing in the aftermath of the COVID-19 pandemic. This book investigates the issues and challenges the education sector is facing as well as the future directions needed to provide education in a more effective way. Covering topics such as academic perspectives, university-level employees, and leadership challenges, this book is a dynamic resource for students, teachers, pre-service teachers, school administrators, education providers, faculty, researchers, policymakers, and academicians.

Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative -omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries.

Each year hundreds of new drugs are approved for the marketplace. The approval of a single new drug is the result of years of screening tens of thousands of compounds, performing pre-clinical research on their effects, and designing, implementing, and analyzing the results of clinical trials. This book provides a general guide to statistical methods used in the pharmaceutical industry, and is aimed at graduate students and researchers who want to know more about statistical applications in all phases of the drug development process. The 19 chapters authored by over 30 statisticians working in the industry follow the general sequence of drug development, from pre-clinical research and saftey assessment to dose finding, safety studies, large clinical trials, analysis of health economic data, and fianlly manufacturing and production. Special topics such as single patient analysis and the impact of patient compliance show the broad spectrum of applications of data analysis methods. Each chapter illustrates a practical problem using data from actual studies by describing the study, the data, the methods, and the results. All of the analyses are done with S-PLUS, and the data and code are provided both in appendices to the chapters and on the companion Springer-Verlag web site, making it possible to reproduce the results and extend the analyses. Prior knowledge of the software is not required to follow the analyses. Steven P. Millard is a statistical consultant and also Manager of Consulting Services for MathSoft, Inc. (Data Analysis Products Division.) He has applied statistical methods to projects ranging from quality control in bioassay to measuring water quality to automating home appraisal, and has taught courses in S-PLUS for over 10 years. He is the author of the book Environmental Statistics with S-PLUS (CRC Press) as well as the S-PLUS add-in module ENVIRONMENTALSTATS for S-PLUS. Andreas Krause is a statistical consultant in the pharmaceutical industry and works for Novartis Pharma AG. He has extensive experience in graphical and numerical data analysis as well as programming, has taught numerous classes with and on S-PLUS, and is an S_PLUS user from the early days on. He is also author of the book The Basics of S and S-PLUS (Springer).

Crafted to resemble a set of Abstergo case files, this immersive and interactive book provides a glimpse into the technology that allows characters to inhabit the lives of their ancestors - a cornerstone of the Assassin's Creed narrative. In-depth and beautifully illustrated, the Assassin's Creed Manual will grant a never-before-seen look at the inner workings of the fictional corporation at the heart of the blockbuster franchise.

This book presents high-quality research in the field of 3D imaging technology. The second edition of International Conference on 3D Imaging Technology (3DDIT-MSP&DL) continues the good traditions already established by the first 3DIT conference (IC3DIT2019) to provide a wide scientific forum for researchers, academia and practitioners to exchange newest ideas and recent achievements in all aspects of image processing and analysis, together with their contemporary applications. The conference proceedings are published in 2 volumes. The main topics of the papers comprise famous trends as: 3D image representation, 3D image technology, 3D images and graphics, and computing and 3D information technology. In these proceedings, special attention is paid at the 3D tensor image representation, the 3D content generation technologies, big data analysis, and also deep learning, artificial intelligence, the 3D image analysis and video understanding, the 3D virtual and augmented reality, and many related areas. The first volume contains papers in 3D image processing, transforms and technologies. The second volume is about computing and information technologies, computer images and graphics and related applications. The two volumes of the book cover a wide area of the aspects of the contemporary multidimensional imaging and the related future trends from data acquisition to real-world applications based on various techniques and theoretical approaches.

This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.

This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the basics of Bayesian data analysis and its Python implementation are presented. Since surveys are widely used as the primary method to collect data, and ultimately information, on attitudes, interests, and opinions of customers and constituents, these tools are vital for private or public sector policy decisions. As a compact volume, this book uses case studies to illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives: Demonstrate how to extract actionable, insightful, and useful information from survey data; and Introduce Python and Pandas for analyzing survey data.

This book introduces the fundamentals of research methods and how they apply to the discipline of urban and regional planning. Written at a level appropriate for upper-level undergraduate and beginning master's level students, the text fills a gap in the literature for textbooks on urban planning. Additionally, the book can be used as a reference for planning practitioners and researchers when analyzing quantitative and qualitative data in urban and regional planning and related fields. The volume does not assume advanced knowledge of mathematical formulas. Rather, it begins with the essentials of research methods, such as the identification of the research problems in planning, the literature review, data collection and presentation, descriptive data analysis, and report of findings. Its discipline-specific topics include field research methods, qualitative data analysis, economic and demographic analysis, evaluation research, and methods in sub-disciplines such as land use planning, transportation planning, environmental planning, and housing analysis. Designed with instruction in mind, this book features downloadable materials, including learning outcomes, chapter highlights, chapter review questions, datasets, and certain Excel models. Students will be able to download review questions to enhance the learning process and datasets to practice methods.

This is the third edition of the first ever book to explore the exciting field of augmented reality art and its enabling technologies. The new edition has been thoroughly revised and updated, with 9 new chapters included. As well as investigating augmented reality as a novel artistic medium, the book covers cultural, social, spatial and cognitive facets of augmented reality art. It has been written by a virtual team of 33 researchers and artists from 11 countries who are pioneering in the new form of art, and contains numerous colour illustrations showing both classic and recent augmented reality artworks. Intended as a starting point for exploring this new fascinating area of research and creative practice, it will be essential reading not only for artists, researchers and technology developers, but also for students (graduates and undergraduates) and all those interested in emerging augmented reality technology and its current and future applications in art.

This is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly comprehend multivariate data analysis. Arranged so that readers can intuitively grasp the purposes for which multivariate analysis procedures are used, the book also offers clear explanations of those purposes, with numerical examples preceding the mathematical descriptions. Supporting the modern matrix formulations by highlighting singular value decomposition among theorems in matrix algebra, this book is useful for undergraduate students who have already learned introductory statistics, as well as for graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis. The book begins by explaining fundamental matrix operations and the matrix expressions of elementary statistics. Then, it offers an introduction to popular multivariate procedures, with each chapter featuring increasing advanced levels of matrix algebra. Further the book includes in six chapters on advanced procedures, covering advanced matrix operations and recently proposed multivariate procedures, such as sparse estimation, together with a clear explication of the differences between principal components and factor analyses solutions. In a nutshell, this book allows readers to gain an understanding of the latest developments in multivariate data science.

This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications. Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail. A custom Python package is available for download, allowing students to reproduce these examples and explore others. The first chapters of the text focus on analyzing variability, probability models, and distribution functions. Next, the authors introduce statistical inference and bootstrapping, and variability in several dimensions and regression models. The text then goes on to cover sampling for estimation of finite population quantities and time series analysis and prediction, concluding with two chapters on modern data analytic methods. Each chapter includes exercises, data sets, and applications to supplement learning. Modern Statistics: A Computer-Based Approach with Python is intended for a one- or two-semester advanced undergraduate or graduate course. Because of the foundational nature of the text, it can be combined with any program requiring data analysis in its curriculum, such as courses on data science, industrial statistics, physical and social sciences, and engineering. Researchers, practitioners, and data scientists will also find it to be a useful resource with the numerous applications and case studies that are included. A second, closely related textbook is titled Industrial Statistics: A Computer-Based Approach with Python. It covers topics such as statistical process control, including multivariate methods, the design of experiments, including computer experiments and reliability methods, including Bayesian reliability. These texts can be used independently or for consecutive courses. The mistat Python package can be accessed at https://gedeck.github.io/mistat-code-solutions/ModernStatistics/ "In this book on Modern Statistics, the last two chapters on modern analytic methods contain what is very popular at the moment, especially in Machine Learning, such as classifiers, clustering methods and text analytics. But I also appreciate the previous chapters since I believe that people using machine learning methods should be aware that they rely heavily on statistical ones. I very much appreciate the many worked out cases, based on the longstanding experience of the authors. They are very useful to better understand, and then apply, the methods presented in the book. The use of Python corresponds to the best programming experience nowadays. For all these reasons, I think the book has also a brilliant and impactful future and I commend the authors for that." Professor Fabrizio RuggeriResearch Director at the National Research Council, ItalyPresident of the International Society for Business and Industrial Statistics (ISBIS)Editor-in-Chief of Applied Stochastic Models in Business and Industry (ASMBI)

This book discusses quantum theory as the theory of random (Brownian) motion of small particles (electrons etc.) under external forces. Implying that the Schroedinger equation is a complex-valued evolution equation and the Schroedinger function is a complex-valued evolution function, important applications are given. Readers will learn about new mathematical methods (theory of stochastic processes) in solving problems of quantum phenomena. Readers will also learn how to handle stochastic processes in analyzing physical phenomena.