Methods for detecting protein-protein interactions (PPIs) have given researchers a global picture of protein interactions on a genomic scale. ""Biological Data Mining in Protein Interaction Networks"" explains bioinformatic methods for predicting PPIs, as well as data mining methods to mine or analyze various protein interaction networks. A defining body of research within the field, this book discovers underlying interaction mechanisms by studying intra-molecular features that form the common denominator of various PPIs.

This volume includes outstanding scientific articles on documents written in ancient languages such as Tocharian, Sogdian, Khotanese, and Old Uyghur. Its chief aims are to contribute to the present state of research by adding essential findings on newly discovered historical documents; to present a multi-dimensional investigation of diverse aspects including the history, religion, art, literature, and social life along the Silk Road; and to outline potential future research directions for non-Han literature studies and inspire research into other aspects, such as economics and comparative studies.

Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department s history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional failure story, PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Read here all about how departments such as at Berkeley, Chicago, Harvard, and Stanford started and how they got to where they are today. The book should also be of interests to scholars in the field of disciplinary history. "

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP. Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjunction with existing computational tools to analyse neural activity, which is monitored through different sensors such as spike trains, local filed potentials and EEG. The analysis of neural activity can yield vital insights into the function of the brain. This book highlights the contribution of signal processing in the area of computational neuroscience by providing a forum for researchers in this field to share their experiences to date.

This book presents outstanding articles addressing various aspects related to the ancient Silk Road, in particular the cultural, political, and economic interactions that took place among the civilizations and cultures on the Eurasian continent. In addition, the articles help to reveal the hallmark features of cultural communication in Inner Asia in different historical periods. The book develops a new approach to studying the civilizations of the Silk Road, promotes interdisciplinary and multi-dimensional research, sets a new direction for Chinese ancient classics and western sinology, and presents the latest discoveries, including both archaeological finds and historical documents.

This thesis reports on innovations in the design and direct synthesis of graphene-based woven fabric (GWF) and multi-layer graphene/porous carbon woven fabric films (MLG/PC) by means of chemical vapor deposition (CVD), using woven copper mesh and nickel mesh as the template. Further, it presents the successful applications of these materials as a platform for solar cells, super capacitors and sensors, making it especially of interest to researchers and graduate students in the fields of materials sciences, nanotechnology and renewable energy.

This book proposes that the short-term goal of the current reform of the international monetary system should be a combination of controlling 'imbalances' and 'the risk of the dollar', namely using the balance of payments coordination mechanism to suppress risks by exchange rate cooperation. The reforms of international reserve currencies, international financial institutions, and international financial regulation provide a good external environment for the stable development of the world economy. The book discusses the mechanisms that will continue to support the hegemony of the US dollar and the US dollar system in the future, including the commodity dollar return mechanism, the international debt repayment mechanism, the petroleum dollar pricing mechanism and the dollar rescue mechanism in financial crisis. The book predicts that the current international currency system dominated by the US dollar will remain sustainable for a long time. Finally, the book proposes four strategies for China's participation in the reform of the international monetary system.

Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data.

Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.

This book presents outstanding articles addressing various aspects related to the ancient Silk Road, in particular the cultural, political, and economic interactions that took place among the civilizations and cultures on the Eurasian continent. In addition, the articles help to reveal the hallmark features of cultural communication in Inner Asia in different historical periods. The book develops a new approach to studying the civilizations of the Silk Road, promotes interdisciplinary and multi-dimensional research, sets a new direction for Chinese ancient classics and western sinology, and presents the latest discoveries, including both archaeological finds and historical documents.

This volume includes outstanding scientific articles on documents written in ancient languages such as Tocharian, Sogdian, Khotanese, and Old Uyghur. Its chief aims are to contribute to the present state of research by adding essential findings on newly discovered historical documents; to present a multi-dimensional investigation of diverse aspects including the history, religion, art, literature, and social life along the Silk Road; and to outline potential future research directions for non-Han literature studies and inspire research into other aspects, such as economics and comparative studies.

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP. Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjunction with existing computational tools to analyse neural activity, which is monitored through different sensors such as spike trains, local filed potentials and EEG. The analysis of neural activity can yield vital insights into the function of the brain. This book highlights the contribution of signal processing in the area of computational neuroscience by providing a forum for researchers in this field to share their experiences to date.

This thesis reports on innovations in the design and direct synthesis of graphene-based woven fabric (GWF) and multi-layer graphene/porous carbon woven fabric films (MLG/PC) by means of chemical vapor deposition (CVD), using woven copper mesh and nickel mesh as the template. Further, it presents the successful applications of these materials as a platform for solar cells, super capacitors and sensors, making it especially of interest to researchers and graduate students in the fields of materials sciences, nanotechnology and renewable energy.

Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department's history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional failure story, PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Read here all about how departments such as at Berkeley, Chicago, Harvard, and Stanford started and how they got to where they are today. The book should also be of interests to scholars in the field of disciplinary history.

Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisheries science and economics. The wide-ranging practical importance of MCMC has sparked an expansive and deep investigation into fundamental Markov chain theory. The Handbook of Markov Chain Monte Carlo provides a reference for the broad audience of developers and users of MCMC methodology interested in keeping up with cutting-edge theory and applications. The first half of the book covers MCMC foundations, methodology, and algorithms. The second half considers the use of MCMC in a variety of practical applications including in educational research, astrophysics, brain imaging, ecology, and sociology. The in-depth introductory section of the book allows graduate students and practicing scientists new to MCMC to become thoroughly acquainted with the basic theory, algorithms, and applications. The book supplies detailed examples and case studies of realistic scientific problems presenting the diversity of methods used by the wide-ranging MCMC community. Those familiar with MCMC methods will find this book a useful refresher of current theory and recent developments.

This book constitutes the proceedings of the 9th CCF Conference on Big Data, BigData 2021, held in Guangzhou, China, in January 2022. Due to the COVID-19 pandemic BigData 2021 was postponed to 2022. The 21 full papers presented in this volume were carefully reviewed and selected from 66 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications.

This book constitutes refereed proceedings of the Second International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format. The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various areas such as healthcare services, smart home applications, and more.

This book constitutes the refereed proceedings at PAKDD Workshops 2015, held in conjunction with PAKDD, the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Ho Chi Minh City, Vietnam, in May 2015. The 23 revised papers presented were carefully reviewed and selected from 57 submissions. The workshops affiliated with PAKDD 2015 include: Pattern Mining and Application of Big Data (BigPMA), Quality Issues, Measures of Interestingness and Evaluation of data mining models (QIMIE), Data Analytics for Evidence-based Healthcare (DAEBH), Vietnamese Language and Speech Processing (VLSP).