This book is organized in 2 volumes and 6 parts. Part I is Big Data Analytics, which is about new advances of analysis, statistics, coordination and data mining of big data; Part II is Information Systems Management, which is about the development of big data information system or cloud platform. Part III is Computing Methodology with Big Data, which is about the improvements of traditional computation technologies in the background of big data; Part IV is Uncertainty Decision Making, which is about the decision making methods with various uncertain information, such as fuzzy, random, rough, gray, unascertained. Part V is Intelligence Algorithm.

Prepare for Microsoft Certification Exam 70-483: Programming in C#. The “What, Why, and How” of each concept is presented along with quick summaries, code challenges, and exam questions to review and practice key concepts.

This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work.

This book provides a comprehensive collection of methods and approaches for using formal methods within Human-Computer Interaction (HCI) research, the use of which is a prerequisite for usability and user-experience (UX) when engineering interactive systems.

Learn how to deploy Raspberry Pi computers in a classroom or lab situation and how to navigate the hardware and software choices you face.

This book focuses on emerging issues in usability, interface design, human computer interaction and user experience, with a special emphasis on the research aimed at understanding human-interaction and usability issues with products, services and systems for improved experience. It covers modeling as well as innovative design concepts, with a special emphasis to user-centered design, and design for special populations, particularly the elderly. Virtual reality, digital environments, heuristic evaluation and feedback of devices’ interfaces (visual and haptic) are also among the topics covered in this book.

Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process.

The book will be a complete and self-sufficient source both for primary and secondary audience. Starting from basic concepts to state-of-the art implementation, it will be a constant source of help both for practitioners and researchers.

This volume summarizes the author’s work on social information seeking (SIS), and at the same time serves as an introduction to the topic. Sometimes also referred to as social search or social information retrieval, this is a relatively new area of study concerned with the seeking and acquiring of information from social spaces on the Internet. It involves studying situations, motivations, and methods involved in seeking and sharing of information in participatory online social sites, such as Yahoo! Answers, WikiAnswers, and Twitter, as well as building systems for supporting such activities.

This book illustrates how to use description logic-based formalisms to their full potential in the creation, indexing, and reuse of multimedia semantics. To do so, it introduces researchers to multimedia semantics by providing an in-depth review of state-of-the-art standards, technologies, ontologies, and software tools.

Learn Intel 64 assembly language and architecture, become proficient in C, and understand how the programs are compiled and executed down to machine instructions, enabling you to write robust, high-performance code.

In this course, you'll be provided with a high-level overview of what threat modeling is, how it can be used, and potential challenges you may face when attempting to use threat modeling for your day to day activities, projects, or environments.

In this course, you'll discover when and how to choose a declarative versus a programmatic solution for any development task in Salesforce.

Domain-driven design includes many established patterns and practices. This course, you'll cover an in-depth guideline into implementing the specification pattern in C#.

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