Knowledge is a valuable resource that must be managed well for any organization to thrive. Proper knowledge management can improve business processes by creating value, yet the available tools meant to aid in the creation, collection, and storage of information have drastically changed since the emergence of social media. By using this collaborative online application for engaging with information, organizations are able to precisely decimate knowledge to the correct audience. Harnessing Social Media as a Knowledge Management Tool addresses the challenges and rewards of the proper use of social media, as well as the key enablers and barriers of its application. This publication endeavors to provide thorough insight into the role of social media in knowledge management from both an organizational and individual perspective. This book elucidates emerging strategies perfect for policy makers, managers, advertisers, academics, students, and organizations who wish to optimize performance.

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This book gives a review of the principles, methods and techniques of important and emerging research topics and technologies in Channel Coding, including theory, algorithms, and applications. Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic. With this reference source you will: Quickly grasp a new area of research Understand the underlying principles of a topic and its applications Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved

Including the latest Microsoft 365 features and enhanced support for Mac users, Cengage's Illustrated Series (R) Collection, Microsoft (R) Office 365 (R) & PowerPoint (R) 2021 Comprehensive, 2nd edition, helps you quickly master the nuances of Microsoft (R) Office. Its concise, student-friendly approach uses a proven two-page layout that allows you to work through an entire task without turning the page. Each module begins with a brief overview of the principles covered while large, full-color screen images illustrate what you see on your computer. Module Learning Objectives are mapped to Microsoft Office Specialist (MOS) certification objectives, and module scenarios are based on Burning Glass market insights data -- helping you sharpen the critical skills you need for real-world success. In addition, MindTap and SAM (Skills Assessment Manager) online resources help maximize your study time -- and results.

Annual Reports in Computational Chemistry provides timely and critical reviews of important topics in computational chemistry as applied to all chemical disciplines. Topics covered include quantum chemistry, molecular mechanics, force fields, chemical education, and applications in academic and industrial settings. Focusing on the most recent literature and advances in the field, each article covers a specific topic of importance to computational chemists.

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Big Mechanisms in Systems Biology: Big Data Mining, Network Modeling, and Genome-Wide Data Identification explains big mechanisms of systems biology by system identification and big data mining methods using models of biological systems. Systems biology is currently undergoing revolutionary changes in response to the integration of powerful technologies. Faced with a large volume of available literature, complicated mechanisms, small prior knowledge, few classes on the topics, and causal and mechanistic language, this is an ideal resource. This book addresses system immunity, regulation, infection, aging, evolution, and carcinogenesis, which are complicated biological systems with inconsistent findings in existing resources. These inconsistencies may reflect the underlying biology time-varying systems and signal transduction events that are often context-dependent, which raises a significant problem for mechanistic modeling since it is not clear which genes/proteins to include in models or experimental measurements. The book is a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in an in-depth understanding on how to process and apply great amounts of biological data to improve research.

In today's digital world, the huge amount of data being generated is unstructured, messy, and chaotic in nature. Dealing with such data, and attempting to unfold the meaningful information, can be a challenging task. Feature engineering is a process to transform such data into a suitable form that better assists with interpretation and visualization. Through this method, the transformed data is more transparent to the machine learning models, which in turn causes better prediction and analysis of results. Data science is crucial for the data scientist to assess the trade-offs of their decisions regarding the effectiveness of the machine learning model implemented. Investigating the demand in this area today and in the future is a necessity. The Handbook of Research on Automated Feature Engineering and Advanced Applications in Data Science provides an in-depth analysis on both the theoretical and the latest empirical research findings on how features can be extracted and transformed from raw data. The chapters will introduce feature engineering and the recent concepts, methods, and applications with the use of various data types, as well as examine the latest machine learning applications on the data. While highlighting topics such as detection, tracking, selection techniques, and prediction models using data science, this book is ideally intended for research scholars, big data scientists, project developers, data analysts, and computer scientists along with practitioners, researchers, academicians, and students interested in feature engineering and its impact on data.

The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.

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With near-universal internet access and ever-advancing electronic devices, the ability to facilitate interactions between various hardware and software provides endless possibilities. Though internet of things (IoT) technology is becoming more popular among individual users and companies, more potential applications of this technology are being sought every day. There is a need for studies and reviews that discuss the methodologies, concepts, and possible problems of a technology that requires little or no human interaction between systems. The Handbook of Research on the Internet of Things Applications in Robotics and Automation is a pivotal reference source on the methods and uses of advancing IoT technology. While highlighting topics including traffic information systems, home security, and automatic parking, this book is ideally designed for network analysts, telecommunication system designers, engineers, academicians, technology specialists, practitioners, researchers, students, and software developers seeking current research on the trends and functions of this life-changing technology.

Advances in Computers, the latest volume in the series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

Can you imagine swapping your body for a virtual version? This technology-based look at the afterlife chronicles America's fascination with death and reveals how digital immortality may become a reality. The Internet has reinvented the paradigm of life and death: social media enables a discourse with loved ones long after their deaths, while gaming sites provide opportunities for multiple lives and life forms. In this thought-provoking work, author Kevin O'Neill examines America's concept of afterlife—as imagined in cyberspace—and considers how technologies designed to emulate immortality present serious challenges to our ideas about human identity and to our religious beliefs about heaven and hell. The first part of the work—covering the period between 1840 and 1860—addresses post-mortem photography, cemetery design, and spiritualism. The second section discusses Internet afterlife, including online memorials and cemeteries; social media legacy pages; and sites that curate passwords, bequests, and final requests. The work concludes with chapters on the transhumanist movement, the philosophical and religious debates about Internet immortality, and the study of technologies attempting to extend life long after the human form ceases.