Informatics and Management Science VI PDF Download

Author: Wenjiang Du
Publisher: Springer Science & Business Media
ISBN: 1447148053
Category : Technology & Engineering
Languages : en
Pages : 775

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Book Description
The International Conference on Informatics and Management Science (IMS) 2012 will be held on November 16-19, 2012, in Chongqing, China, which is organized by Chongqing Normal University, Chongqing University, Shanghai Jiao Tong University, Nanyang Technological University, University of Michigan, Chongqing University of Arts and Sciences, and sponsored by National Natural Science Foundation of China (NSFC). The objective of IMS 2012 is to facilitate an exchange of information on best practices for the latest research advances in a range of areas. Informatics and Management Science contains over 600 contributions to suggest and inspire solutions and methods drawing from multiple disciplines including: · Computer Science · Communications and Electrical Engineering · Management Science · Service Science · Business Intelligence

Author: Yuanlong Cao
Publisher: Springer Nature
ISBN: 3031324439
Category : Computers
Languages : en
Pages : 443

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Book Description
This book constitutes the refereed post-conference proceedings of the 12th EAI International Conference on Mobile Networks and Management, MONAMI 2022, which took place virtually during October 29-31, 2022. The 31 full papers were carefully reviewed and selected from 78 submissions. The papers are divided into groups of content as follows: Innovative Artificial Intelligence Applications for Smart City; The New Era of Computer Network by using Machine Learning; Advanced Technologies in Edge and Fog Computing; Emerging Technologies in Mobile Networks and Management; and Recent Advances in Communications and Computing.

Author: Minos Garofalakis
Publisher: Springer
ISBN: 354028608X
Category : Computers
Languages : en
Pages : 528

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Book Description
This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.

Author: Xi Chen
Publisher: Springer Nature
ISBN: 3031019261
Category : Business & Economics
Languages : en
Pages : 444

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Book Description
This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.

Author: Lisa Pike Masteralexis
Publisher: Jones & Bartlett Learning
ISBN: 9780763726232
Category : Business & Economics
Languages : en
Pages : 512

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Book Description
This textbook describes the skill sets needed by the professional sports manager, and surveys the various subdisciplines within the sports management field. The 21 chapters discuss financial and legal principles, high school and collegiate sports, facility and event management, broadcasting, and the health and fitness industry. The second edition u

Author: Christian Jensen
Publisher: Springer Science & Business Media
ISBN: 3540213120
Category : Computers
Languages : en
Pages : 388

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Book Description
This book constitutes the refereed proceedings of the Second International Conference on Trust Management, iTrust 2004, held in Oxford, UK, in March/April 2004. The 21 revised full papers and 6 revised short papers presented together with 3 invited contributions were carefully reviewed and selected from 48 submissions. Besides technical topics in distributed and open systems, issues from law, social sciences, business, and philosophy are addressed in order to develop a deeper and more fundamental understanding of the issues and challenges in the area of trust management in dynamic open systems.

Author: Adela Del Río Ortega
Publisher: Springer Nature
ISBN: 3030664988
Category : Computers
Languages : en
Pages : 403

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Book Description
This book constitutes revised papers from the International Workshops held at the 18th International Conference on Business Process Management, BPM 2020, during September 13-18, 2020. The conference was planned to take place in Seville, Spain, but changed to an online format due to the COVID-19 pandemic. Papers from the following workshops are included: Workshop on Security and Privacy-Enhanced Business Process Management (SPBP 2020) Workshop on Social and Human Aspects of Business Process Management (BPMS2 2020) Workshop on Business Processes Meet the Internet-of Things (BP-Meet-IoT 2020) Workshop on Artificial Intelligence for Business Process Management (AI4BPM 2020) Workshop BPM in the Era of Digital Innovation and Transformation (BPMinDIT 2020) Workshop on Business Process Intelligence (BPI 2020) Workshop on Declarative, Decision and Hybrid Approaches to Processes (DEC2H 2020) Each of the seven workshops focused on particular aspects of business process management, either from a technical or from a domain perspective. Overall, after a thorough review process there were 28 full and 1 short paper selected from 53 submissions.

Author: Hongjun Lu
Publisher: Springer
ISBN: 354045151X
Category : Computers
Languages : en
Pages : 458

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Book Description
Database research and development has been remarkably successful over the past three decades. Now the field is facing new challenges posted by the rapid advances of technology, especially the penetration of the Web and Internet into everyone's daily life. The economical and financial environment where database systems are used has been changing dramatically. In addition to being able to efficiently manage a large volume of operational data generated internally, the ability to manage data in cyberspace, extract relevant information, and discover knowledge to support decision making is critical to the success of any organization. In order to provide researchers and practitioners with a forum to share their experiences in tackling problems in managing and using data, information, and knowledge in the age of the Internet and Web, the First International Conference on Web-Age Information Management (WAIM 2000) was held in Shanghai, China, June 21-23. The inaugural conference in its series was well received. Researchers from 17 countries and regions, including Austria, Australia, Bahrain, Canada, China, France, Germany, Japan, Korea, Malaysia, The Netherlands, Poland, Singapore, Spain, Taiwan, UK, and USA submitted their recent work. Twenty-seven regular and 14 short papers contained in these proceedings were presented during the two-day conference. These papers cover a large spectrum of issues, from classical data management such as object-oriented modeling, spatial and temporal databases to recent hits like data mining, data warehousing, semi-structured data, and XML.

Author: Orin Thomas
Publisher: Pearson Education
ISBN: 0735627169
Category : Computers
Languages : en
Pages : 932

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Book Description
This two-in-one training kit delivers in-depth preparation plus practice for the required exam for the new MCTS: Microsoft Exchange Server 2010, configuring certification. Ace exam prep--and build real-world job skills--with lessons, labs, and practice tests.

Author: Simon Thompson
Publisher: Simon and Schuster
ISBN: 1638352062
Category : Computers
Languages : en
Pages : 270

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Book Description
Guide machine learning projects from design to production with the techniques in this unique project management guide. No ML skills required! In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including: Understanding an ML project’s requirements Setting up the infrastructure for the project and resourcing a team Working with clients and other stakeholders Dealing with data resources and bringing them into the project for use Handling the lifecycle of models in the project Managing the application of ML algorithms Evaluating the performance of algorithms and models Making decisions about which models to adopt for delivery Taking models through development and testing Integrating models with production systems to create effective applications Steps and behaviors for managing the ethical implications of ML technology Managing Machine Learning Projects is an end-to-end guide for delivering machine learning applications on time and under budget. It lays out tools, approaches, and processes designed to handle the unique challenges of machine learning project management. You’ll follow an in-depth case study through a series of sprints and see how to put each technique into practice. The book’s strong consideration to data privacy, and community impact ensure your projects are ethical, compliant with global legislation, and avoid being exposed to failure from bias and other issues. About the Technology Ferrying machine learning projects to production often feels like navigating uncharted waters. From accounting for large data resources to tracking and evaluating multiple models, machine learning technology has radically different requirements than traditional software. Never fear! This book lays out the unique practices you’ll need to ensure your projects succeed. About the Book Managing Machine Learning Projects is an amazing source of battle-tested techniques for effective delivery of real-life machine learning solutions. The book is laid out across a series of sprints that take you from a project proposal all the way to deployment into production. You’ll learn how to plan essential infrastructure, coordinate experimentation, protect sensitive data, and reliably measure model performance. Many ML projects fail to create real value—read this book to make sure your project is a success. What's Inside Set up infrastructure and resource a team Bring data resources into a project Accurately estimate time and effort Evaluate which models to adopt for delivery Integrate models into effective applications About the Reader For anyone interested in better management of machine learning projects. No technical skills required. About the Author Simon Thompson has spent 25 years developing AI systems to create applications for use in telecoms, customer service, manufacturing and capital markets. He led the AI research program at BT Labs in the UK, and is now the Head of Data Science at GFT Technologies. Table of Contents 1 Introduction: Delivering machine learning projects is hard; let’s do it better 2 Pre-project: From opportunity to requirements 3 Pre-project: From requirements to proposal 4 Getting started 5 Diving into the problem 6 EDA, ethics, and baseline evaluations 7 Making useful models with ML 8 Testing and selection 9 Sprint 3: system building and production 10 Post project (sprint O)