Concise Metals Engineering Data Book
Author: Joseph R. Davis
Publisher: ASM International
Published: 1997-01-01
Total Pages: 257
ISBN-13: 161503983X
DOWNLOAD EBOOKPosts
Data-Driven Science and Engineering
Author: Steven L. Brunton
Publisher: Cambridge University Press
Published: 2022-05-05
Total Pages: 615
ISBN-13: 1009098489
DOWNLOAD EBOOKA textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
ASME Engineer's Data Book
Author: Clifford Matthews
Publisher: American Society of Mechanical Engineers
Published: 2005
Total Pages: 388
ISBN-13:
DOWNLOAD EBOOKThis greatly expanded second edition of this popular and handy reference book includes over 100 new pages, including extensive coverage of Section VIII of the ASME Pressure Vessel Code. Divided into 22 sections, this pocket-sized volume is an exhaustive "quick reference" of up-to-date engineering data and rules. It includes: essential mathematics; units; engineering design processes and principles; basic mechanical design; motion; mechanics of materials; material failure; thermodynamics; fluid mechanics; fluid equipment; vessel codes and standards; materials; machine elements; design and production tools; project engineering; computer-aided engineering; welding; non-destructive examination; corrosion; surface protection; metallurgical terms; and engineering associations and organizations.
Perspectives on Data Science for Software Engineering
Author: Tim Menzies
Publisher: Morgan Kaufmann
Published: 2016-07-14
Total Pages: 410
ISBN-13: 0128042613
DOWNLOAD EBOOKPerspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community's leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. - Presents the wisdom of community experts, derived from a summit on software analytics - Provides contributed chapters that share discrete ideas and technique from the trenches - Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data - Presented in clear chapters designed to be applicable across many domains
Data-Driven Engineering Design
Author: Ang Liu
Publisher: Springer Nature
Published: 2021-10-09
Total Pages: 203
ISBN-13: 3030881814
DOWNLOAD EBOOKThis book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design. Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation. Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.
Data Network Engineering
Author: Tim King
Publisher: Springer Science & Business Media
Published: 1999-07-31
Total Pages: 360
ISBN-13: 9780792385943
DOWNLOAD EBOOKIt is certain that, over the next few years, data traffic will dwarf voice traffic on telecommunications networks. Growth in data-traffic volumes far exceeds that for voice, and is driven by increased use of applications such as e-mail attachments, remote printing and fileserver access, and the now omnipresent World Wide Web. The growth of data networking to connect computers with each other and with their peripheral devices began in earnest in the 1970s, took off in the 1980s and exploded in the 1990s. The early 21st century will see ever faster, more cost effective networks providing flexible data access into ever more businesses and homes. Since the 1970s there have been great advances in technology. For the past twenty years the processing power of computers has continued to grow with no hint of slowing - recall the oft-cited Moore's Law claiming that this power doubles every 18 months. Advances in the data networking equipment required to support the data traffic generated have been enormous. The pace of development from early X. 25 and modem technology through to some of the advanced equipment functionality now available is breathtaking - it is sometimes hard to believe that the practical router is barely ten years old! This book provides an overview of the advanced data networking field by bringing together chapters on local area networks, wide area networks and their application.
Data Engineering on Azure
Author: Vlad Riscutia
Publisher: Simon and Schuster
Published: 2021-08-17
Total Pages: 334
ISBN-13: 1617298921
DOWNLOAD EBOOKBuild a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data
Data Analytics for Engineering and Construction Project Risk Management
Author: Ivan Damnjanovic
Publisher: Springer
Published: 2019-05-23
Total Pages: 382
ISBN-13: 3030142515
DOWNLOAD EBOOKThis book provides a step-by-step guidance on how to implement analytical methods in project risk management. The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes. The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts’ judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory. The book is organized in three parts and fourteen chapters. In Part I the authors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution.
The Rails Way
Author: Obie Fernandez
Publisher: Pearson Education
Published: 2007-11-16
Total Pages: 951
ISBN-13: 032163019X
DOWNLOAD EBOOKThe expert guide to building Ruby on Rails applications Ruby on Rails strips complexity from the development process, enabling professional developers to focus on what matters most: delivering business value. Now, for the first time, there’s a comprehensive, authoritative guide to building production-quality software with Rails. Pioneering Rails developer Obie Fernandez and a team of experts illuminate the entire Rails API, along with the Ruby idioms, design approaches, libraries, and plug-ins that make Rails so valuable. Drawing on their unsurpassed experience, they address the real challenges development teams face, showing how to use Rails’ tools and best practices to maximize productivity and build polished applications users will enjoy. Using detailed code examples, Obie systematically covers Rails’ key capabilities and subsystems. He presents advanced programming techniques, introduces open source libraries that facilitate easy Rails adoption, and offers important insights into testing and production deployment. Dive deep into the Rails codebase together, discovering why Rails behaves as it does— and how to make it behave the way you want it to. This book will help you Increase your productivity as a web developer Realize the overall joy of programming with Ruby on Rails Learn what’s new in Rails 2.0 Drive design and protect long-term maintainability with TestUnit and RSpec Understand and manage complex program flow in Rails controllers Leverage Rails’ support for designing REST-compliant APIs Master sophisticated Rails routing concepts and techniques Examine and troubleshoot Rails routing Make the most of ActiveRecord object-relational mapping Utilize Ajax within your Rails applications Incorporate logins and authentication into your application Extend Rails with the best third-party plug-ins and write your own Integrate email services into your applications with ActionMailer Choose the right Rails production configurations Streamline deployment with Capistrano
Engineering Data on Mixing
Author: Reiji Reiji Mezaki
Publisher: Elsevier
Published: 1999-11-19
Total Pages: 781
ISBN-13: 0080531008
DOWNLOAD EBOOKThis book is a compilation of the engineering data on mixing, which have appeared in the major technical journals of chemical engineering and bioengineering since 1975. That year marked the beginning of a period of rapid advancement in the science and technology of mixing, with rather reliable results for both theoretical and experimental studies. In addition, some important earlier articles which have been, and still are being referred to, are included.Designs of both agitators and tanks still depend primarily on art and experience. In light of this it was felt that the data on mixing should be compiled and presented in a systematic manner to assist in design and analysis of agitated tanks, and to provide easier access to mixing data for various engineering activities. Although computer-aided searches of pertinent data bases can be of assistance to chemical engineers and bioengineers in their studies, they are sometimes time-consuming and often costly. Furthermore inadequate selection of key words can jeopardize the searches. This book offers an alternative method of surveying mixing data which interests readers. The first chapter presents a variety of results for the experimental measurements of flow patterns in stirred tanks. Most of the measurements were made by using modern Laser-Doppler techniques. This chapter is useful for the prediction of flow patterns in tanks with many different geometries, various types of agitators, and fluids of diverse physical and rheological properties, plus valuable data for the validation of results obtained by CFD simulations. Chapters 2 through 5 deal with data for traditional chemical engineering subjects and Chapter 6 summarizes a number of scale-up relations developed over the years for various systems. These include liquid, solid-liquid, liquid-liquid, gas-liquid, and solid-liquid-gas systems. Chapter 7 provides data related to multiphase processes, and most importantly, drop size and drop-size distributions and bubble-size distributions. These two subjects have not been treated systematically either in text books or in handbooks on stirred-tank mixing, although the results of both experimental and theoretical investigations have been reported on many occasions. Finally gas-inducing mechanically agitated systems are dealt with. The applications of this type of agitation system will become increasingly attractive from the standpoint of rationalization of stirred-tank operations as well as environmental protection.
