Automotive Manufacturing Processes discusses basic principles and operational procedures of automotive manufacturing processes, issues in the automotive industry like material selection, and troubleshooting. Every chapter includes specific learning objectives, multiple-choice questions to test conceptual understanding of the subject and put theory into practice, review questions, solved problems, and unsolved exercises. It covers important topics including material decision-making processes, surface hardening processes, heat treatment processes, effects of friction and velocity distribution, the metallurgical spectrum of forging, and surface finishing processes. Features: Discusses automotive manufacturing processes in a comprehensive manner with the help of applications. Provides case studies addressing issues in the automotive industry and manufacturing operations in the production of vehicles. Discussion on material properties while laying emphasis on the materials and processing parameters. Covers applications and case studies of the automotive industry. The text will be useful for senior undergraduates, graduate students and academic researchers in areas including automobile engineering, industrial and manufacturing engineering and mechanical engineering.
This book introduces the principles and practices in automotive systems, including modern automotive systems that incorporate the latest trends in the automobile industry. The fifteen chapters present new and innovative methods to master the complexities of the vehicle of the future. Topics like vehicle classification, structure and layouts, engines, transmissions, braking, suspension and steering are illustrated with modern concepts, such as battery-electric, hybrid electric and fuel cell vehicles and vehicle maintenance practices. Each chapter is supported with examples, illustrative figures, multiple-choice questions and review questions. Aimed at senior undergraduate and graduate students in automotive/automobile engineering, mechanical engineering, electronics engineering, this book covers the following: Construction and working details of all modern as well as fundamental automotive systems Complexities of operation and assembly of various parts of automotive systems in a simplified manner Handling of automotive systems and integration of various components for smooth functioning of the vehicle Modern topics such as battery-electric, hybrid electric and fuel cell vehicles Illustrative examples, figures, multiple-choice questions and review questions at the end of each chapter
Web mining is the application of data mining strategies to excerpt learning from web information, i.e. web content, web structure, and web usage data. With the emergence of the web as the predominant and converging platform for communication, business and scholastic information dissemination, especially in the last five years, there are ever increasing research groups working on different aspects of web mining mainly in three directions. These are: mining of web content, web structure and web usage. In this context there are good number of frameworks and benchmarks related to the metrics of the websites which is certainly weighty for B2B, B2C and in general in any e-commerce paradigm. Owing to the popularity of this topic there are few books in the market, dealing more on such performance metrics and other related issues. This book, however, omits all such routine topics and lays more emphasis on the classification and clustering aspects of the websites in order to come out with the true perception of the websites in light of its usability. In nutshell, Web Mining: A Synergic Approach Resorting to Classifications and Clustering showcases an effective methodology for classification and clustering of web sites from their usability point of view. While the clustering and classification is accomplished by using an open source tool WEKA, the basic dataset for the selected websites has been emanated by using a free tool site-analyzer. As a case study, several commercial websites have been analyzed. The dataset preparation using site-analyzer and classification through WEKA by embedding different algorithms is one of the unique selling points of this book. This text projects a complete spectrum of web mining from its very inception through data mining and takes the reader up to the application level. Salient features of the book include: Literature review of research work in the area of web miningBusiness websites domain researched, and data collected using site-analyzer toolAccessibility, design, text, multimedia, and networking are assessedDatasets are filtered further by selecting vital attributes which are Search Engine Optimized for processing using the Weka attributed toolDataset with labels have been classified using J48, RBFNetwork, NaïveBayes, and SMO techniques using WekaA comparative analysis of all classifiers is reported Commercial applications for improving website performance based on SEO is given
Web mining is the application of data mining strategies to excerpt learning from web information, i.e. web content, web structure, and web usage data. With the emergence of the web as the predominant and converging platform for communication, business and scholastic information dissemination, especially in the last five years, there are ever increasing research groups working on different aspects of web mining mainly in three directions. These are: mining of web content, web structure and web usage. In this context there are good number of frameworks and benchmarks related to the metrics of the websites which is certainly weighty for B2B, B2C and in general in any e-commerce paradigm. Owing to the popularity of this topic there are few books in the market, dealing more on such performance metrics and other related issues. This book, however, omits all such routine topics and lays more emphasis on the classification and clustering aspects of the websites in order to come out with the true perception of the websites in light of its usability.In nutshell, Web Mining: A Synergic Approach Resorting to Classifications and Clustering showcases an effective methodology for classification and clustering of web sites from their usability point of view. While the clustering and classification is accomplished by using an open source tool WEKA, the basic dataset for the selected websites has been emanated by using a free tool site-analyzer. As a case study, several commercial websites have been analyzed. The dataset preparation using site-analyzer and classification through WEKA by embedding different algorithms is one of the unique selling points of this book. This text projects a complete spectrum of web mining from its very inception through data mining and takes the reader up to the application level. Salient features of the book include: Literature review of research work in the area of web miningBusiness websites domain researched, and data collected using site-analyzer toolAccessibility, design, text, multimedia, and networking are assessedDatasets are filtered further by selecting vital attributes which are Search Engine Optimized for processing using the Weka attributed toolDataset with labels have been classified using J48, RBFNetwork, NaïveBayes, and SMO techniques using WekaA comparative analysis of all classifiers is reportedCommercial applications for improving website performance based on SEO is given
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