For a more detailed treatment of these and other special induction machine applications, see Reference 21, for example. Discussion of the Synchronous Induction Motor will be deferred till Section 8.6. Operation in Dynamic Braking and ...

Author: J. Hindmarsh

Publisher: Elsevier

ISBN: 9781483294926

Category: Technology & Engineering

Page: 692

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A self-contained, comprehensive and unified treatment of electrical machines, including consideration of their control characteristics in both conventional and semiconductor switched circuits. This new edition has been expanded and updated to include material which reflects current thinking and practice. All references have been updated to conform to the latest national (BS) and international (IEC) recommendations and a new appendix has been added which deals more fully with the theory of permanent-magnets, recognising the growing importance of permanent-magnet machines. The text is so arranged that selections can be made from it to give a short course for non-specialists, while the book as a whole will prepare students for more advanced studies in power systems, control systems, electrical machine design and general industrial applications. Includes numerous worked examples and tutorial problems with answers.

Furthermore, machine vision systems are continuously deployed in new application fields, in part because computers get faster all the time and thus enable applications to be solved that were out of reach just a few years ago.

Author: Carsten Steger

Publisher: John Wiley & Sons

ISBN: 9783527812899

Category: Science

Page: 516

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The second edition of this successful machine vision textbook is completely updated, revised and expanded by 35% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new camera and image acquisition interfaces, 3D sensors and technologies, 3D reconstruction, 3D object recognition and state-of-the-art classification algorithms. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13.

Fernandez R., “Predicting time series with a local support vector regression machine", In [19]. 8. Osuna E., Freund R., and Girosi F., “Support Vector Machines: Training and Applications”, A.I. Memo No. 1602, Artificial Intelligence ...

Author: Georgios Paliouras

Publisher: Springer Science & Business Media

ISBN: 9783540424901

Category: Computers

Page: 324

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In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The first ten chapters assess the current state of the art of machine learning, from symbolic concept learning and conceptual clustering to case-based reasoning, neural networks, and genetic algorithms. The second part introduces the reader to innovative applications of ML techniques in fields such as data mining, knowledge discovery, human language technology, user modeling, data analysis, discovery science, agent technology, finance, etc.

Machine learning has become a fundamental tool in applied science. Many if not most state-of-the-art technological innovations now involve machine learning to a greater or lesser extent. Fields of its application are extremely diverse.

Author: Saad Subair

Publisher: Springer Nature

ISBN: 9783030378301

Category: Technology & Engineering

Page: 280

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This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning.

Imputation techniques to account for missing data in support of intelligent transportation systems applications (Tech. ... In K. W. Tobin Jr. (Ed.), Machine vision applications in industrial inspection VIII, Proceedings of SPIE (Vol.

Author: Olivas, Emilio Soria

Publisher: IGI Global

ISBN: 9781605667676

Category: Computers

Page: 852

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"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

All such questions are being answered through application of machine learning. The hidden patterns that can be evaluated with calculations and consistently broken down to recognize patterns that may impact loaning and guaranteeing what ...

Author: Puneet Mathur

Publisher: Apress

ISBN: 9781484237878

Category: Computers

Page: 379

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Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you’ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You’ll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will LearnDiscover applied machine learning processes and principles Implement machine learning in areas of healthcare, finance, and retail Avoid the pitfalls of implementing applied machine learning Build Python machine learning examples in the three subject areas Who This Book Is For Data scientists and machine learning professionals.

These datasets are used for machine learning applications [1]. The organizations/institutes collect the feedback from the users, but it is very difficult to segregate them into positive and negative feedback. For this purpose, they ask ...

Author: Ankur Choudhary

Publisher: Springer Nature

ISBN: 9789811630675

Category: Computers

Page: 738

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The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications.

12 Balancing of Machinery 12.1 Introduction Machine design topics discussed prior to this chapter have focused primarily on how to design machines to perform a specific task. Another important aspect to consider in the design of ...

Author: James Doane

Publisher: John Wiley & Sons

ISBN: 9781118541340

Category: Mathematics

Page: 552

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The aim of this book is to motivate students into learning Machine Analysis by reinforcing theory and applications throughout the text. The author uses an enthusiastic ‘hands-on’ approach by including photos of actual mechanisms in place of abstract line illustrations, and directs students towards developing their own software for mechanism analysis using Excel & Matlab. An accompanying website includes a detailed list of tips for learning machine analysis, including tips on working homework problems, note taking, preparing for tests, computer programming and other topics to aid in student success. Study guides for each chapter that focus on teaching the thought process needed to solve problems by presenting practice problems are included, as are computer animations for common mechanisms discussed in the text.

Machine learning [11] is one of the most active research areas that has succeeded in many applications and fields such as image recognition, speech recognition, medical diagnosis, smart building, and container orchestration.

Author: Aboul Ella Hassanien

Publisher: Springer Nature

ISBN: 9783031039188

Category:

Page:

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Bzdok D, Altman N, Krzywinski M (2018) Statistics versus machine learning. Nat Methods 15(4) 2. ... Tioga Press, Palo Alto, CA Langley P, Simon HA (1995) Applications of machine learning and rule induction. Technical Report 95-1, ...

Author: Anand J. Kulkarni

Publisher: Springer Nature

ISBN: 9789811509940

Category: Technology & Engineering

Page: 197

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This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.