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This book constitutes the refereed proceedings of the 26th Annual International Cryptology Conference, CRYPTO 2006, held in Santa Barbara, California, USA in August 2006. The 34 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 250 submissions. The papers address all current foundational, theoretical and research aspects of cryptology, cryptography, and cryptanalysis as well as advanced applications.
The present book is a festschrift in honor of Luigia Carlucci Aiello. The 18 articles included are written by former students, friends, and international colleagues, who have cooperated with Luigia Carlucci Aiello, scientifically or in AI boards or committees. The contributions by reputed researchers span a wide range of AI topics and reflect the breadth and depth of Aiello's own work.
New Directions in Cognitive Information Retrieval presents an exciting new direction for research into cognitive oriented information retrieval (IR) research, a direction based on an analysis of the user’s problem situation and cognitive behavior when using the IR system. This contrasts with the current dominant IR research paradigm which concentrates on improving IR system matching performance. The chapters describe the leading edge concepts and models of cognitive IR that explore the nexus between human cognition, information and the social conditions that drive humans to seek information using IR systems. Chapter topics include: Polyrepresentation, cognitive overlap and the boomerang effect, Multitasking while conducting the search, Knowledge Diagram Visualizations of the topic space to facilitate user assimilation of information, Task, relevance, selection state, knowledge need and knowledge behavior, search training built into the search, children’s collaboration for school projects, and other cognitive perspectives on IR concepts and issues.
The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.
High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life science, neural networks, and neuromorphic engineering. The book is organized into two main sections. The first section covers Big Data architectures, including cloud computing systems, and heterogeneous accelerators. It also covers emerging 3D IC design principles for memory architectures and devices. The second section of the book illustrates emerging and practical applications of Big Data across several domains, including bioinformatics, deep learning, and neuromorphic engineering. Features Covers a wide range of Big Data architectures, including distributed systems like Hadoop/Spark Includes accelerator-based approaches for big data applications such as GPU-based acceleration techniques, and hardware acceleration such as FPGA/CGRA/ASICs Presents emerging memory architectures and devices such as NVM, STT- RAM, 3D IC design principles Describes advanced algorithms for different big data application domains Illustrates novel analytics techniques for Big Data applications, scheduling, mapping, and partitioning methodologies Featuring contributions from leading experts, this book presents state-of-the-art research on the methodologies and applications of high-performance computing for big data applications. About the Editor Dr. Chao Wang is an Associate Professor in the School of Computer Science at the University of Science and Technology of China. He is the Associate Editor of ACM Transactions on Design Automations for Electronics Systems (TODAES), Applied Soft Computing, Microprocessors and Microsystems, IET Computers & Digital Techniques, and International Journal of Electronics. Dr. Chao Wang was the recipient of Youth Innovation Promotion Association, CAS, ACM China Rising Star Honorable Mention (2016), and best IP nomination of DATE 2015. He is now on the CCF Technical Committee on Computer Architecture, CCF Task Force on Formal Methods. He is a Senior Member of IEEE, Senior Member of CCF, and a Senior Member of ACM.
Neuromodulation: Comprehensive Textbook of Principles, Technologies, and Therapies, Second Edition, serves as a comprehensive and in-depth reference textbook covering all aspects of the rapidly growing field of neuromodulation. Since the publication of the first edition seven years ago, there has been an explosion of knowledge in neuromodulation, optogenetics, bioelectronics medicine and brain computer interfacing. Users will find unique discussions of the fundamental principles of neuromodulation and therapies, and how they are applied to the brain, spinal cord, peripheral nerves, autonomic nerves and various organs. The book focuses on comprehensive coverage of spinal cord stimulation, non-interventional and interventional brain stimulation, peripheral nerve stimulation, and the emerging fields of neuromodulation, including optogenetics and bioelectronics medicine. - Provides a comprehensive reference that covers all aspects of the growing field of neuromodulation - Written by international, leading authorities in their respective fields of neuromodulation, pain management, functional neurosurgery and biomedical engineering - Includes new chapters on optogenetics, bioelectronics medicine and brain computer interfacing
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.
The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.