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Published by LAP Lambert Academic Publishing, 2012
ISBN 10: 3848405652 ISBN 13: 9783848405657
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Taschenbuch. Condition: Neu. Analgesic,Antipyretic, Anti-arthritic activity of T.Procumbens leaves | Evaluation of Analgesic, Antipyretic and Antiarthritic activity of Tridax procumbens leaves extract | Deepak Kumar Jain (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783848405657 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Published by LAP Lambert Academic Publishing, 2012
ISBN 10: 3659147761 ISBN 13: 9783659147760
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Taschenbuch. Condition: Neu. Antihypothyroidism activity of leaves of Cassia fistula Linn. on rats | Evaluation of Antihypothyroidism activity of leaves of Cassia fistula Linn. on rats | Deepak Kumar Jain (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659147760 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Seller: Basi6 International, Irving, TX, U.S.A.
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Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659147761 ISBN 13: 9783659147760
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Published by LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845440449 ISBN 13: 9783845440446
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Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659886408 ISBN 13: 9783659886409
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Add to basketHRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Language: English
Published by John Wiley & Sons Inc, 2026
ISBN 10: 1394355289 ISBN 13: 9781394355280
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. Gain a competitive edge in the semiconductor industry with this essential guide, which provides the practical insights and machine learning techniques needed to optimize the fabrication of hybrid nanodevices for integrated circuits. Enhancing Hybrid Nanodevice Fabrication Efficiency Using Machine Learning explores the intersection of advanced manufacturing techniques and machine learning applications in the field of nanotechnology, specifically focusing on hybrid nanodevices for integrated circuits. This book provides a comprehensive understanding of how machine learning algorithms and techniques can optimize the fabrication processes of hybrid nanodevices, improving their efficiency, reliability, and performance in integrated circuit applications. The book begins with an introduction to the fundamentals of hybrid nanodevice fabrication and the role of machine learning in enhancing these processes. It then delves into various machine learning algorithms and models used for process optimization, quality control, and predictive maintenance in integrated circuit fabrication. Case studies and practical examples illustrate real-world applications of machine learning in improving yield, reducing costs, and accelerating time-to-market for hybrid nanodevices. It also addresses the pressing need for a comprehensive guide on machine learning applications in nanodevice fabrication. It provides researchers, engineers, and industry professionals with practical insights for implementing machine learning techniques to tackle challenges such as variability reduction, defect detection, and process optimization. By bridging the gap between theory and practice, the book equips readers with the knowledge and tools necessary to leverage machine learning for a competitive advantage in the semiconductor industry. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by John Wiley & Sons Inc, 2026
ISBN 10: 1394355289 ISBN 13: 9781394355280
Seller: CitiRetail, Stevenage, United Kingdom
Hardcover. Condition: new. Hardcover. Gain a competitive edge in the semiconductor industry with this essential guide, which provides the practical insights and machine learning techniques needed to optimize the fabrication of hybrid nanodevices for integrated circuits. Enhancing Hybrid Nanodevice Fabrication Efficiency Using Machine Learning explores the intersection of advanced manufacturing techniques and machine learning applications in the field of nanotechnology, specifically focusing on hybrid nanodevices for integrated circuits. This book provides a comprehensive understanding of how machine learning algorithms and techniques can optimize the fabrication processes of hybrid nanodevices, improving their efficiency, reliability, and performance in integrated circuit applications. The book begins with an introduction to the fundamentals of hybrid nanodevice fabrication and the role of machine learning in enhancing these processes. It then delves into various machine learning algorithms and models used for process optimization, quality control, and predictive maintenance in integrated circuit fabrication. Case studies and practical examples illustrate real-world applications of machine learning in improving yield, reducing costs, and accelerating time-to-market for hybrid nanodevices. It also addresses the pressing need for a comprehensive guide on machine learning applications in nanodevice fabrication. It provides researchers, engineers, and industry professionals with practical insights for implementing machine learning techniques to tackle challenges such as variability reduction, defect detection, and process optimization. By bridging the gap between theory and practice, the book equips readers with the knowledge and tools necessary to leverage machine learning for a competitive advantage in the semiconductor industry. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Published by TAYLOR & FRANCIS NP EXCLUSIVE(CBS), 2025
ISBN 10: 1032825278 ISBN 13: 9781032825274
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Condition: New. Brand New! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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First Edition
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Published by Springer Nature Switzerland, Springer International Publishing, 2025
ISBN 10: 3031800559 ISBN 13: 9783031800559
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Considering the interest of researchers and academicians, editors here aim to present this book in a multidimensional perspective that will be covering Healthcare Recommender Systems in depth, considering pattern recognition techniques using amalgamation of emerging technologies. It aims to cover all topics ranging from discussion of recommender system to efficient management to recent research challenges and issues. Editors aim to present the book in a self-sufficient manner and in order to achieve this, the book has been organized into various chapters.The prime focus of the book is to explore the various issues, challenges, and research directions of pattern recognition in Healthcare Recommender Systems. The table of contents is designed in a manner so as to provide the reader with a broad list of its applications. Additionally, the book addresses the transformations in the area of Healthcare Recommender Systems. Thus, the book plans to discuss the recent research trends and advanced topics in the field of healthcare automation system which will be of interest to industry experts, academicians and researchers working in this area. Hence, the editors aim is to cover diversity in the domain while achieving completeness.
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Hardcover. Condition: Brand New. 496 pages. In Stock.
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Published by Springer Nature Singapore, Springer Nature Singapore Jun 2024, 2024
ISBN 10: 9819921562 ISBN 13: 9789819921560
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. Neuware -This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders.This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features:¿ Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection.¿ Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders.¿ Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.