Search Results for "data-processing"

Data Processing

Data Processing

Made Simple

  • Author: Susan Wooldridge
  • Publisher: Elsevier
  • ISBN: 1483105245
  • Category: Technology & Engineering
  • Page: 256
  • View: 7284
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Data Processing: Made Simple, Second Edition presents discussions of a number of trends and developments in the world of commercial data processing. The book covers the rapid growth of micro- and mini-computers for both home and office use; word processing and the 'automated office'; the advent of distributed data processing; and the continued growth of database-oriented systems. The text also discusses modern digital computers; fundamental computer concepts; information and data processing requirements of commercial organizations; and the historical perspective of the computer industry. The computer hardware and software and the development and implementation of a computer system are considered. The book tackles careers in data processing; the tasks carried out by the data processing department; and the way in which the data processing department fits in with the rest of the organization. The text concludes by examining some of the problems of running a data processing department, and by suggesting some possible solutions. Computer science students will find the book invaluable.

Quantitative Data Processing in Scanning Probe Microscopy

Quantitative Data Processing in Scanning Probe Microscopy

SPM Applications for Nanometrology

  • Author: Petr Klapetek
  • Publisher: Elsevier
  • ISBN: 0128133481
  • Category: Science
  • Page: 416
  • View: 8014
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Quantitative Data Processing in Scanning Probe Microscopy: SPM Applications for Nanometrology, Second Edition describes the recommended practices for measurements and data processing for various SPM techniques, also discussing associated numerical techniques and recommendations for further reading for particular physical quantities measurements. Each chapter has been revised and updated for this new edition to reflect the progress that has been made in SPM techniques in recent years. New features for this edition include more step-by-step examples, better sample data and more links to related documentation in open source software. Scanning Probe Microscopy (SPM) techniques have the potential to produce information on various local physical properties. Unfortunately, there is still a large gap between what is measured by commercial devices and what could be considered as a quantitative result. This book determines to educate and close that gap. Associated data sets can be downloaded from http://gwyddion.net/qspm/ Features step-by-step guidance to aid readers in progressing from a general understanding of SPM principles to a greater mastery of complex data measurement techniques Includes a focus on metrology aspects of measurements, arming readers with a solid grasp of instrumentation and measuring methods accuracy Worked examples show quantitative data processing for different SPM analytical techniques

Ruby Data Processing

Ruby Data Processing

Using Map, Reduce, and Select

  • Author: Jay Godse
  • Publisher: Apress
  • ISBN: 148423474X
  • Category: Computers
  • Page: 98
  • View: 7909
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Gain the basics of Ruby’s map, reduce, and select functions and discover how to use them to solve data-processing problems. This compact hands-on book explains how you can encode certain complex programs in 10 lines of Ruby code, an astonishingly small number. You will walk through problems and solutions which are effective because they use map, reduce, and select. As you read Ruby Data Processing, type in the code, run the code, and ponder the results. Tweak the code to test the code and see how the results change. After reading this book, you will have a deeper understanding of how to break data-processing problems into processing stages, each of which is understandable, debuggable, and composable, and how to combine the stages to solve your data-processing problem. As a result, your Ruby coding will become more efficient and your programs will be more elegant and robust. What You Will Learn Discover Ruby data processing and how to do it using the map, reduce, and select functions Develop complex solutions including debugging, randomizing, sorting, grouping, and more Reverse engineer complex data-processing solutions Who This Book Is For Those who have at least some prior experience programming in Ruby and who have a background and interest in data analysis and processing using Ruby.

Stream Data Processing: A Quality of Service Perspective

Stream Data Processing: A Quality of Service Perspective

Modeling, Scheduling, Load Shedding, and Complex Event Processing

  • Author: Sharma Chakravarthy,Qingchun Jiang
  • Publisher: Springer Science & Business Media
  • ISBN: 0387710035
  • Category: Computers
  • Page: 324
  • View: 2626
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The systems used to process data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.

Fast Data Processing With Spark

Fast Data Processing With Spark

  • Author: Holden Karau
  • Publisher: Packt Publishing Ltd
  • ISBN: 1782167072
  • Category: Computers
  • Page: 120
  • View: 6511
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This book will be a basic, step-by-step tutorial, which will help readers take advantage of all that Spark has to offer.Fastdata Processing with Spark is for software developers who want to learn how to write distributed programs with Spark. It will help developers who have had problems that were too much to be dealt with on a single computer. No previous experience with distributed programming is necessary. This book assumes knowledge of either Java, Scala, or Python.

Hyperspectral Data Processing

Hyperspectral Data Processing

Algorithm Design and Analysis

  • Author: Chein-I Chang
  • Publisher: John Wiley & Sons
  • ISBN: 1118269772
  • Category: Technology & Engineering
  • Page: 1164
  • View: 5958
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Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author’s first book, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, without much overlap. Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging. Hyperspectral Data Processing contains eight major sections: Part I: provides fundamentals of hyperspectral data processing Part II: offers various algorithm designs for endmember extraction Part III: derives theory for supervised linear spectral mixture analysis Part IV: designs unsupervised methods for hyperspectral image analysis Part V: explores new concepts on hyperspectral information compression Parts VI & VII: develops techniques for hyperspectral signal coding and characterization Part VIII: presents applications in multispectral imaging and magnetic resonance imaging Hyperspectral Data Processing compiles an algorithm compendium with MATLAB codes in an appendix to help readers implement many important algorithms developed in this book and write their own program codes without relying on software packages. Hyperspectral Data Processing is a valuable reference for those who have been involved with hyperspectral imaging and its techniques, as well those who are new to the subject.

NMR Data Processing

NMR Data Processing

  • Author: Jeffrey C. Hoch,Alan Stern
  • Publisher: Wiley-Liss
  • ISBN: 9780471039006
  • Category: Science
  • Page: 230
  • View: 3767
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NMR DATA PROCESSING Jeffrey C. Hoch and Alan S. Stern Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful nondestructive technique for exploring the structure of matter. In recent years, NMR instrumentation has become increasingly sophisticated, and the software used to acquire and process NMR data continues to expand in scope and complexity. This software has always been difficult to understand, and, until now, it seemed likely to remain that way. NMR Data Processing examines and explains the techniques used to process, present, and analyze NMR data. It provides a complete account of the fundamentals of spectrum analysis and establishes a framework for applying those fundamentals to real NMR data. It also details, in clear and concise language, the basic principles underlying the complex software needed to analyze the data. Two chapters are devoted to the fundamentals and applications of discrete Fourier transform (DFT) in NMR, which was crucial to the development of modern NMR spectroscopy. A large part of the book focuses on increasingly important non-DFT methods, which obtain higher sensitivity and resolution. Other topics covered include: * Data formats * Processing for multidimensional experiments * Parametric modeling of NMR signals * Standard techniques-apodization, zero-filling, the Hilbert transform * Artifacts-aliasing, leakage, solvent signals * Advanced processing techniques-LP, MaxEnt, Bayesian analysis Jeffrey C. Hoch and Alan S. Stern conclude their in-depth look at this rapidly growing field by exploring methods for analyzing processed data, including visualization, quantification, and error analysis. Readers are provided with a solid foundation for developing new methods of their own. NMR Data Processing is an important tool for students learning basic principles for the first time, technicians troubleshooting data processing problems, and professional researchers developing new techniques. It will help all NMR users acquire a true grasp of the methods behind the process, avoid the pitfalls of misapplication and misinterpretation, and exploit the full power of NMR software.

Large Scale and Big Data

Large Scale and Big Data

Processing and Management

  • Author: Sherif Sakr,Mohamed Gaber
  • Publisher: CRC Press
  • ISBN: 1466581506
  • Category: Computers
  • Page: 636
  • View: 3232
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Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

Data Processing in Archaeology

Data Processing in Archaeology

  • Author: J. D. Richards,N. S. Ryan
  • Publisher: CUP Archive
  • ISBN: 9780521257695
  • Category: Social Science
  • Page: 232
  • View: 4041
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This book aims to give archaeologists a non-technical but thorough grounding in the use of computers.

Business data processing systems

Business data processing systems

  • Author: Lawrence Orilia,Nancy B. Stern,Robert A. Stern
  • Publisher: John Wiley & Sons
  • ISBN: 9780471656951
  • Category: Business & Economics
  • Page: 310
  • View: 4019
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100 years of data processing

100 years of data processing

the punchcard century

  • Author: Frederick G. Bohme,J. Paul Wyatt,United States. Bureau of the Census. Data User Services Division
  • Publisher: N.A
  • ISBN: N.A
  • Category: Social Science
  • Page: 24
  • View: 3843
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Data Processing and Information Technology

Data Processing and Information Technology

  • Author: Carl French
  • Publisher: Cengage Learning EMEA
  • ISBN: 9781844801008
  • Category: Computers
  • Page: 501
  • View: 8207
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This book provides a comprehensive and straightforward coverage of data processing and information technology. It is widely used as a course text on many professional and non-professional business and accountancy courses, and assumes no previous knowledge of the subject. This book provides a comprehensive and straightforward coverage of data processing and information technology. It is widely used as a course text on many professional and non-professional business and accountancy courses, and assumes no previous knowledge of the subject.

Basic data processing

Basic data processing

  • Author: Richard W. Lott
  • Publisher: Prentice Hall
  • ISBN: N.A
  • Category: Computers
  • Page: 290
  • View: 4587
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Monitoring the Comprehensive Nuclear-Test-Ban Treaty: Data Processing and Infrasound

Monitoring the Comprehensive Nuclear-Test-Ban Treaty: Data Processing and Infrasound

  • Author: Zoltan A. Der,Robert H. Shumway,Eugene T. Herrin
  • Publisher: Springer Science & Business Media
  • ISBN: 9783764366766
  • Category: Science
  • Page: 278
  • View: 2363
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On September 10, 1996, The United Nations General Assembly adopted the Copmprehensive Nuclear-Test-Ban Treaty (CTBT), prohibiting nuclear explosions worldwide, in all environments. The treaty calls for a global verification system, including a network of 321 monitoring stations distributed around the globe, a data communications network, an international data center (IDC), and on-site inspections, to verify compliance. This volume presents certain recent research results pertaining on methods used to process data recorded by instruments of the International Monitoring System (IMS) and addressing recording infrasound signals generated by atmospheric explosions. Six papers treating data processing provide an important selection of topics expected to contribute to improving our ability to successfully monitor a CTBT. Five papers concerning infrasound include descriptions of ways in which that important research area can contribute to CTBT monitoring, the automatic processing of infrasound data, and site conditions that serve to improve the quality of infrasound data.

Business Data Processing & Computer Applications

Business Data Processing & Computer Applications

  • Author: N.A
  • Publisher: APH Publishing
  • ISBN: 9788176486491
  • Category:
  • Page: N.A
  • View: 7484
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Practical Real-time Data Processing and Analytics

Practical Real-time Data Processing and Analytics

Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka

  • Author: Shilpi Saxena,Saurabh Gupta
  • Publisher: Packt Publishing Ltd
  • ISBN: 1787289869
  • Category: Computers
  • Page: 360
  • View: 7254
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A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.

Radar Data Processing With Applications

Radar Data Processing With Applications

  • Author: He You,Xiu Jianjuan,Guan Xin
  • Publisher: John Wiley & Sons
  • ISBN: 1118956869
  • Category: Technology & Engineering
  • Page: 560
  • View: 1249
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A systematic introduction to the theory, development and latest research results of radar data processing technology • Presents both classical theory and development methods of radar data processing • Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory • Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar • Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command

Image Processing and Data Analysis

Image Processing and Data Analysis

The Multiscale Approach

  • Author: Jean-Luc Starck,Fionn D. Murtagh,Albert Bijaoui
  • Publisher: Cambridge University Press
  • ISBN: 9780521599146
  • Category: Science
  • Page: 287
  • View: 6843
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Powerful techniques have been developed in recent years for the analysis of digital data, especially the manipulation of images. This book provides an in-depth introduction to a range of these innovative, avante-garde data-processing techniques. It develops the reader's understanding of each technique and then shows with practical examples how they can be applied to improve the skills of graduate students and researchers in astronomy, electrical engineering, physics, geophysics and medical imaging. What sets this book apart from others on the subject is the complementary blend of theory and practical application. Throughout, it is copiously illustrated with real-world examples from astronomy, electrical engineering, remote sensing and medicine. It also shows how many, more traditional, methods can be enhanced by incorporating the new wavelet and multiscale methods into the processing. For graduate students and researchers already experienced in image processing and data analysis, this book provides an indispensable guide to a wide range of exciting and original data-analysis techniques.

Data processing

Data processing

a user's approach

  • Author: Hooshang M. Beheshti,Melvin R. Mattson
  • Publisher: Reston
  • ISBN: N.A
  • Category: Computers
  • Page: 551
  • View: 3580
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Computational Neural Networks for Geophysical Data Processing

Computational Neural Networks for Geophysical Data Processing

  • Author: M.M. Poulton
  • Publisher: Elsevier
  • ISBN: 9780080529653
  • Category: Science
  • Page: 352
  • View: 9846
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This book was primarily written for an audience that has heard about neural networks or has had some experience with the algorithms, but would like to gain a deeper understanding of the fundamental material. For those that already have a solid grasp of how to create a neural network application, this work can provide a wide range of examples of nuances in network design, data set design, testing strategy, and error analysis. Computational, rather than artificial, modifiers are used for neural networks in this book to make a distinction between networks that are implemented in hardware and those that are implemented in software. The term artificial neural network covers any implementation that is inorganic and is the most general term. Computational neural networks are only implemented in software but represent the vast majority of applications. While this book cannot provide a blue print for every conceivable geophysics application, it does outline a basic approach that has been used successfully.