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Analytics and Tech Mining for Engineering Managers

Author : Scott W. Cunningham

Publisher : Momentum Press

Page : 129 pages

File Size : 24,92 MB

Release : 2016-06-20

Category : Technology & Engineering

ISBN : 1606505114

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Book Description

This book offers practical tools in Python to students of innovation, as well as competitive intelligence professionals, to track new developments in science, technology, and innovation. The book will appeal to both—tech-mining and data science audiences. For tech-mining audiences, Python presents an appealing, all-in-one language for managing the tech-mining process. The book is a complement to other introductory books on the Python language, providing recipes with which a practitioner can grow a practice of mining text. For data science audiences, this book gives a succinct overview over the most useful techniques of text mining. The book also provides relevant domain knowledge from engineering management; so, an appropriate context for analysis can be created. This is the first book of a two-book series. This first book discusses the mining of text, while the second one describes the analysis of text. This book describes how to extract actionable intelligence from a variety of sources including scientific articles, patents, pdfs, and web pages. There is a variety of tools available within Python for mining text. In particular, we discuss the use of pandas, BeautifulSoup, and pdfminer.



Advanced Analytics in Mining Engineering

Author : Ali Soofastaei

Publisher : Springer Nature

Page : 746 pages

File Size : 24,22 MB

Release : 2022-02-23

Category : Business & Economics

ISBN : 3030915891

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Book Description

In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.





Business Fundamentals for Engineering Managers

Author : C.M. Chang

Publisher : Momentum Press

Page : 179 pages

File Size : 27,68 MB

Release : 2014-08-31

Category : Technology & Engineering

ISBN : 1606504797

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Book Description

Engineering managers and professionals make a long and lasting impact in the industry by regularly developing technology-based projects, as related to new product development, new service innovation or efficiency-centered process improvement, or both—to create strategic differentiation and operational excellence for their employers. They need certain business fundamentals that enable them to make decisions, based on both technology and business perspectives, leading to new or improved product or service offerings, which are technically feasible, economically viable, marketplace acceptable, and customer enlightening. This book consists of three sets of business fundamentals. The chapter “Cost Accounting and Control” discusses service and product costing, activity-based costing to define overhead expenses, and risk analysis and cost estimation under uncertainty. The chapter “Financial Accounting and Analysis” delineates the key financial statements, financial analyses, balanced scorecard, ratio analysis, and capital asset valuation—including operations, opportunities, and acquisition and mergers. The chapter “Marketing Management” reviews marketing functions, marketing forecasting, marketing segmentation, customers, and other factors affecting marketing in making value-adding contributions. The new business vocabulary and useful analysis tools presented will enable engineering managers to become more effective when interacting with senior management, and to prepare themselves for assuming higher-level corporate responsibilities.



Data Mining: Concepts and Techniques

Author : Jiawei Han

Publisher : Elsevier

Page : 740 pages

File Size : 33,1 MB

Release : 2011-06-09

Category : Computers

ISBN : 0123814804

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Book Description

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data



Data Analytics Applied to the Mining Industry

Author : Ali Soofastaei

Publisher : CRC Press

Page : 273 pages

File Size : 21,64 MB

Release : 2020-11-12

Category : Computers

ISBN : 0429781776

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Book Description

Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors



Tech Mining

Author : Alan L. Porter

Publisher : John Wiley & Sons

Page : 384 pages

File Size : 40,94 MB

Release : 2004-11-26

Category : Technology & Engineering

ISBN : 0471698458

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Book Description

Tech Mining makes exploitation of text databases meaningful tothose who can gain from derived knowledge about emergingtechnologies. It begins with the premise that we have theinformation, the tools to exploit it, and the need for theresulting knowledge. The information provided puts new capabilities at the hands oftechnology managers. Using the material present, these managers canidentify and access the most valuable technology informationresources (publications, patents, etc.); search, retrieve, andclean the information on topics of interest; and lower the costsand enhance the benefits of competitive technological intelligenceoperations.



Innovation Management and New Product Development for Engineers, Volume II

Author : Rob Dekkers

Publisher : Momentum Press

Page : 216 pages

File Size : 42,68 MB

Release : 2018-08-31

Category : Technology & Engineering

ISBN : 1947083937

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Book Description

Whereas innovation has become part of daily language, in practice, realizing new product and new service development is a complex and daunting task for engineers, design engineering managers, managers, and those involved in other functions in organizations. Most books on innovation management approach this topic from a managerial or economic perspective; this text takes the actual design and engineering processes as starting point. To this purpose, it relates product design and engineering processes and their management to sources of innovation, collaboration with suppliers, and knowledge providers (for example, inventors and universities), and users. The managerial aspects get ample attention as well as the socioeconomic aspects in the context of product design and engineering. For this wide range of topics, the book provides both theoretical underpinning and practical guidance. Readers and students will benefit from this book by not only understanding the key mechanisms for innovation but also by the practical guidance it offers. The author uses diagrams, models, methods, and steps to guide readers to a better understanding of innovation projects. This practical approach and the link to theory make the book valuable to practitioners as well as engineering students.



Innovation Management and New Product Development for Engineers, Volume I

Author : Rob Dekkers

Publisher : Momentum Press

Page : 217 pages

File Size : 18,83 MB

Release : 2018-08-31

Category : Technology & Engineering

ISBN : 1946646857

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Book Description

Whereas innovation has become part of daily language, in practice, realizing new product and new service development is a complex and daunting task for engineers, design engineering managers, managers, and those involved in other functions in organizations. Most books on innovation management approach this topic from a managerial or economic perspective; this text takes the actual design and engineering processes as starting point. To this purpose, it relates product design and engineering processes and their management to sources of innovation, collaboration with suppliers, and knowledge providers (for example, inventors and universities), and users. The managerial aspects get ample attention as well as the socioeconomic aspects in the context of product design and engineering. For this wide range of topics, the book provides both theoretical underpinning and practical guidance. Readers and students will benefit from this book by not only understanding the key mechanisms for innovation but also by the practical guidance it offers. The author uses diagrams, models, methods, and steps to guide readers to a better understanding of innovation projects. This practical approach and the link to theory make the book valuable to practitioners as well as engineering students.



Anticipating Future Innovation Pathways Through Large Data Analysis

Author : Tugrul U. Daim

Publisher : Springer

Page : 366 pages

File Size : 12,70 MB

Release : 2016-07-25

Category : Business & Economics

ISBN : 3319390562

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Book Description

This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes: The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I). The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests. Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP. Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.