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Intelligentes Gesamtmaschinenmanagement für elektrische Antriebssysteme

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Book Series: Karlsruher Schriftenreihe Fahrzeugsystemtechnik / Institut für Fahrzeugsystemtechnik ISSN: 18696058 ISBN: 9783731507741 Year: Volume: 60 Pages: XVI, 150 p. DOI: 10.5445/KSP/1000081063 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Technology (General)
Added to DOAB on : 2019-07-28 18:37:01
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Innovative electric propulsion systems are increasingly applied to off-highway machines, to gain efficiency optimization of the work process. This book focuses on the aspect of work process optimization and achieves forward-looking results through the use of intelligent, adaptive overall machine management.

Clinical Text Mining: Secondary Use of Electronic Patient Records

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ISBN: 9783319785028 9783319785035 Year: Pages: 181 DOI: https://doi.org/10.1007/978-3-319-78503-5 Language: English
Publisher: Springer Grant: Riksbankens Jubileumsfond; Stockholm University
Subject: Medicine (General)
Added to DOAB on : 2018-06-22 15:52:54
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This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records.It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Recent Applications in Data Clustering

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ISBN: 9781789235265 9781789235272 Year: Pages: 248 DOI: 10.5772/intechopen.71315 Language: English
Publisher: IntechOpen
Subject: Computer Science
Added to DOAB on : 2019-10-03 07:51:51

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Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented.

Data Mining

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ISBN: 9781789235968 9781789235975 Year: Pages: 190 DOI: 10.5772/intechopen.71371 Language: English
Publisher: IntechOpen
Subject: Computer Science
Added to DOAB on : 2019-10-03 07:51:51

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This book on data mining explores a broad set of ideas and presents some of the state-of-the-art research in this field. The book is triggered by pervasive applications that retrieve knowledge from real-world big data. Data mining finds applications in the entire spectrum of science and technology including basic sciences to life sciences and medicine, to social, economic, and cognitive sciences, to engineering and computers. The chapters discuss various applications and research frontiers in data mining with algorithms and implementation details for use in real-world. This can be through characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, etc. The intended audience of this book will mainly consist of researchers, research students, practitioners, data analysts, and business professionals who seek information on the various data mining techniques and their applications.

Machine Learning and Biometrics

Authors: --- --- --- --- et al.
ISBN: 9781789235906 9781789235913 Year: Pages: 146 DOI: 10.5772/intechopen.71297 Language: English
Publisher: IntechOpen
Subject: Computer Science
Added to DOAB on : 2019-10-03 07:51:51

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We are entering the era of big data, and machine learning can be used to analyze this deluge of data automatically. Machine learning has been used to solve many interesting and often difficult real-world problems, and the biometrics is one of the leading applications of machine learning. This book introduces some new techniques on biometrics and machine learning, and new proposals of using machine learning techniques for biometrics as well. This book consists of two parts: ""Biometrics"" and ""Machine Learning for Biometrics."" Parts I and II contain four and three chapters, respectively. The book is reviewed by editors: Prof. Jucheng Yang, Prof. Dong Sun Park, Prof. Sook Yoon, Dr. Yarui Chen, and Dr. Chuanlei Zhang.

Application of Artificial Neural Networks in Geoinformatics

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ISBN: 9783038427421 9783038427414 Year: Pages: VI, 222 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Sciences
Added to DOAB on : 2018-04-27 16:05:32
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Recently, a need has arisen for prediction techniques that can address a variety of problems by combining methods from the rapidly developing field of machine learning with geoinformation technologies such as GIS, remote sensing, and GPS. As a result, over the last few decades, one particular machine learning technology, known as artificial neural networks, has been successfully applied to a wide range of fields in science and engineering. In addition, the development of computational and spatial technologies has led to the rapid growth of geoinformatics, which specializes in the analysis of spatial information. Thus, recently, artificial neural networks have been applied to geoinformatics and have produced valuable results in the fields of geoscience, environment, natural hazards, natural resources, and engineering. Hence, this Special Issue of the journal Applied Sciences, “Application of Artificial Neural Networks in Geoinformatics,” was successfully planned, and we here publish a collection of papers detailing novel contributions that are of relevance to these topics.

Transfer Entropy

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ISBN: 9783038429197 9783038429203 Year: Pages: VIII, 326 Language: Englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2018-08-24 17:15:19
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Statistical relationships among the variables of a complex system reveal a lot about its physical behavior. Therefore, identification of the relevant variables and characterization of their interactions are crucial for a better understanding of a complex system. Linear methods, such as correlation, are widely used to identify these relationships. However, information-theoretic quantities, such as mutual information and transfer entropy, have been proven to be superior in the case of nonlinear dependencies. Mutual information quantifies the amount of information obtained about one random variable through the other random variable, and it is symmetric. As an asymmetrical measure, transfer entropy quantifies the amount of directed (time-asymmetric) transfer of information between random processes and, thus, it is related to concepts, such as the Granger causality. This Special Issue includes 16 papers elucidating the state of the art of data-based transfer entropy estimation techniques and applications, in areas such as finance, biomedicine, fluid dynamics and cellular automata. Analytical derivations in special cases, improvements on the estimation methods and comparisons between certain techniques are some of the other contributions of this Special Issue. The diversity of approaches and applications makes this book unique as a single source of invaluable contributions from experts in the field.

Neutrosophic Multi-Criteria Decision Making

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ISBN: 9783038972884 9783038972891 Year: Pages: 206 DOI: 10.3390/books978-3-03897-289-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Physics (General)
Added to DOAB on : 2018-10-12 10:17:26
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Neutrosophic logic and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in Multi-Criteria Decision-Making, computational intelligence, multiple-attribute decision-making, image processing, medical diagnosis, fault diagnosis, optimization design, and so on. Neutrosophic logic, set, probability, statistics, etc., are, respectively, generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics and so on.This Special Issue gathers 11 original research papers that report on the state of the art and recent advancements in Multi-Criteria Decision-Making using neutrosophic environment in computing, artificial intelligence, big and small data mining, group decision-making problems, pattern recognition, information processing, image processing, and many other practical achievements.

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