Yanchun Zhang

This textbook introduces new business concepts on cloud environments such as secure, scalable anonymity and practical payment protocols for the Internet of things and Blockchain technology. The protocol uses electronic cash for payment transactions. In this new protocol, from the viewpoint of banks, consumers can improve anonymity if they are worried about disclosure of their identities in the cloud. Currently, there is not a book available that has reported the techniques covering the protocols with anonymizations and Blockchain technology. Thus this will be a useful book for universities to purchase. This textbook provides new direction for access control management and online business, with new challenges within Blockchain technology that may arise in cloud environments. One is related to the authorization granting process. For example, when a role is granted to a user, this role may conflict with other roles of the user or together with this role; the user may have orderive a high level of authority. Another is related to authorization revocation. For instance, when a role is revoked from a user, the user may still have the role. Experts will get benefits from these challenges through the developed methodology for authorization granting algorithm, and weak revocation and strong revocation algorithms.

This textbook introduces new business concepts on cloud environments such as secure, scalable anonymity and practical payment protocols for the Internet of things and Blockchain technology. The protocol uses electronic cash for payment transactions. In this new protocol, from the viewpoint of banks, consumers can improve anonymity if they are worried about disclosure of their identities in the cloud. Currently, there is not a book available that has reported the techniques covering the protocols with anonymizations and Blockchain technology. Thus this will be a useful book for universities to purchase. This textbook provides new direction for access control management and online business, with new challenges within Blockchain technology that may arise in cloud environments. One is related to the authorization granting process. For example, when a role is granted to a user, this role may conflict with other roles of the user or together with this role; the user may have orderive a high level of authority. Another is related to authorization revocation. For instance, when a role is revoked from a user, the user may still have the role. Experts will get benefits from these challenges through the developed methodology for authorization granting algorithm, and weak revocation and strong revocation algorithms.

Due to the lack of a uniform schema for Web documents and the sheer amount and dynamics of Web data, both the effectiveness and the efficiency of information management and retrieval of Web data is often unsatisfactory when using conventional data management techniques. Web community, defined as a set of Web-based documents with its own logical structure, is a flexible and efficient approach to support information retrieval and to implement various applications. Zhang and his co-authors explain how to construct and analyse Web communities based on information like Web document contents, hyperlinks, or user access logs. Their approaches combine results from Web search algorithms, Web clustering methods, and Web usage mining. They also detail the necessary preliminaries needed to understand the algorithms presented, and they discuss several successful existing applications. Researchers and students in information retrieval and Web search find in this all the necessary basics and methods to create and understand Web communities. Professionals developing Web applications will additionally benefit from the samples presented for their own designs and implementations.

This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engineering, and business. In recent years this problem has gained importance due to the increasing availability of more sensitive sensors in science and engineering and due to the wide-spread use of computers in corporations which have increased the amount of time-series data collected by many magnitudes. An important feature of this book is the exploration of different approaches to handle and identify time dependent biomedical images. Biomedical imaging analysis and processing techniques deal with the interaction between all forms of radiation and biological molecules, cells or tissues, to visualize small particles and opaque objects, and to achieve the recognition of biomedical patterns. These are topics of great importance to biomedical science, biology, and medicine. Biomedical imaging analysis techniques can be applied in many different areas to solve existing problems. The various requirements arising from the process of resolving practical problems motivate and expedite the development of biomedical imaging analysis. This is a major reason for the fast growth of the discipline.

This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems. The proposed methods enable the extraction of this vital information from EEG signals in order to accurately detect abnormalities revealed by the EEG. New methods will relieve the time-consuming and error-prone practices that are currently in use. Common signal processing methodologies include wavelet transformation and Fourier transformation, but these methods are not capable of managing the size of EEG data. Addressing the issue, this book examines new EEG signal analysis approaches with a combination of statistical techniques (e.g. random sampling, optimum allocation) and machine learning methods. The developed methods provide better results than the existing methods. The book also offers applications of the developedmethodologies that have been tested on several real-time benchmark databases.This book concludes with thoughts on the future of the field and anticipated research challenges. It gives new direction to the field of analysis and classification of EEG signals through these more efficient methodologies. Researchers and experts will benefit from its suggested improvements to the current computer-aided based diagnostic systems for the precise analysis and management of EEG signals.

This book presents advances in biomedical imaging analysis and processing techniques using time dependent medical image datasets for computer aided diagnosis. The analysis of time-series images is one of the most widely appearing problems in science, engineering, and business. In recent years this problem has gained importance due to the increasing availability of more sensitive sensors in science and engineering and due to the wide-spread use of computers in corporations which have increased the amount of time-series data collected by many magnitudes. An important feature of this book is the exploration of different approaches to handle and identify time dependent biomedical images. Biomedical imaging analysis and processing techniques deal with the interaction between all forms of radiation and biological molecules, cells or tissues, to visualize small particles and opaque objects, and to achieve the recognition of biomedical patterns. These are topics of great importance to biomedical science, biology, and medicine. Biomedical imaging analysis techniques can be applied in many different areas to solve existing problems. The various requirements arising from the process of resolving practical problems motivate and expedite the development of biomedical imaging analysis. This is a major reason for the fast growth of the discipline.

This book presents advanced methodologies in two areas related to electroencephalogram (EEG) signals: detection of epileptic seizures and identification of mental states in brain computer interface (BCI) systems. The proposed methods enable the extraction of this vital information from EEG signals in order to accurately detect abnormalities revealed by the EEG. New methods will relieve the time-consuming and error-prone practices that are currently in use. Common signal processing methodologies include wavelet transformation and Fourier transformation, but these methods are not capable of managing the size of EEG data. Addressing the issue, this book examines new EEG signal analysis approaches with a combination of statistical techniques (e.g. random sampling, optimum allocation) and machine learning methods. The developed methods provide better results than the existing methods. The book also offers applications of the developedmethodologies that have been tested on several real-time benchmark databases.This book concludes with thoughts on the future of the field and anticipated research challenges. It gives new direction to the field of analysis and classification of EEG signals through these more efficient methodologies. Researchers and experts will benefit from its suggested improvements to the current computer-aided based diagnostic systems for the precise analysis and management of EEG signals.

This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.

This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.

Due to the lack of a uniform schema for Web documents and the sheer amount and dynamics of Web data, both the effectiveness and the efficiency of information management and retrieval of Web data is often unsatisfactory when using conventional data management techniques. Web community, defined as a set of Web-based documents with its own logical structure, is a flexible and efficient approach to support information retrieval and to implement various applications. Zhang and his co-authors explain how to construct and analyse Web communities based on information like Web document contents, hyperlinks, or user access logs. Their approaches combine results from Web search algorithms, Web clustering methods, and Web usage mining. They also detail the necessary preliminaries needed to understand the algorithms presented, and they discuss several successful existing applications. Researchers and students in information retrieval and Web search find in this all the necessary basics and methods to create and understand Web communities. Professionals developing Web applications will additionally benefit from the samples presented for their own designs and implementations.