This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the "Challenge of Big Data and Applications of Statistics," in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.

Knowledge-based (KB) technology is being applied to complex problem-solving and critical tasks in many application domains. Concerns have naturally arisen as to the dependability of knowledge-based systems (KBS). As with any software, attention to quality and safety must be paid throughout development of a KBS and rigorous verification and validation (V&V) techniques must be employed. Research in V&V of KBS has emerged as a distinct field only in the last decade and is intended to address issues associated with quality and safety aspects of KBS and to credit such applications with the same degree of dependability as conventional applications. In recent years, V&V of KBS has been the topic of annual workshops associated with the main AI conferences, such as AAAI, IJACI and ECAI. Validation and Verification of Knowledge Based Systems contains a collection of papers, dealing with all aspects of KBS V&V, presented at the Fifth European Symposium on Verification and Validation of Knowledge Based Systems and Components (EUROVAV'99 - http: //www.dnv.no/research/safekbs/eurovav99/) which was held in Oslo in the summer of 1999, and was sponsored by Det Norske Veritas and the British Computer Society's Specialist Group on Expert Systems (SGES).

This book provides a new direction in the field of nano-optics and nanophotonics from information and computing-related sciences and technology. Entitled by "Information Physics and Computing in NanosScale Photonics and Materials", IPCN in short, the book aims to bring together recent progresses in the intersection of nano-scale photonics, information, and enabling technologies. The topic will include (1) an overview of information physics in nanophotonics, (2) DNA self-assembled nanophotonic systems, (3) Functional molecular sensing, (4) Smart fold computing, an architecture for nanophotonics, (5) semiconductor nanowire and its photonic applications, (6) single photoelectron manipulation in imaging sensors, (6) hierarchical nanophotonic systems, (8) photonic neuromorphic computing, and (9) SAT solver and decision making based on nanophotonics.

Current database technology and computer hardware allow us to gather, store, access, and manipulate massive volumes of raw data in an efficient and inexpensive manner. In addition, the amount of data collected and warehoused in all industries is growing every year at a phenomenal rate. Nevertheless, our ability to discover critical, non-obvious nuggets of useful information in data that could influence or help in the decision making process, is still limited. Knowledge discovery (KDD) and Data Mining (DM) is a new, multidisciplinary field that focuses on the overall process of information discovery from large volumes of data. The field combines database concepts and theory, machine learning, pattern recognition, statistics, artificial intelligence, uncertainty management, and high-performance computing. To remain competitive, businesses must apply data mining techniques such as classification, prediction, and clustering using tools such as neural networks, fuzzy logic, and decision trees to facilitate making strategic decisions on a daily basis. Knowledge Discovery for Business Information Systems contains a collection of 16 high quality articles written by experts in the KDD and DM field from the following countries: Austria, Australia, Bulgaria, Canada, China (Hong Kong), Estonia, Denmark, Germany, Italy, Poland, Singapore and USA.

Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment on the design of multiobjective evolutionary algorithms and their applications in domains covering areas such as control and scheduling. Emphasizing both the theoretical developments and the practical implementation of multiobjective evolutionary algorithms, a profound mathematical knowledge is not required.

Written for a wide readership, engineers, researchers, senior undergraduates and graduate students interested in the field of evolutionary algorithms and multiobjective optimization with some basic knowledge of evolutionary computation will find this book a useful addition to their book case.

The amalgamation of post-quantum cryptography in cyber-physical systems makes the computing system secure and also generates opportunities in areas like smart contracts, quantum blockchain, and smart security solutions. Sooner or later, all computing and security systems are going to adopt quantum-proof cryptography to safeguard these systems from quantum attacks. Post-quantum cryptography has tremendous potential in various domains and must be researched and explored further to be utilized successfully. Advancements in Quantum Blockchain With Real-Time Applications considers various concepts of computing such as quantum computing, post-quantum cryptography, quantum attack-resistant blockchain, quantum blockchains, and multidisciplinary applications and real-world use cases. The book also discusses solutions to various real-world problems within the industry. Covering key topics such as cybersecurity, data management, and smart society, this reference work is ideal for computer scientists, industry professionals, academicians, practitioners, scholars, researchers, instructors, and students.

The world of text mining is simultaneously a minefield and a gold mine. It is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain umesolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identified, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the field of Text Mining -especially in relation to IT- and whether there still remain areas to be covered."

This book develops and describes a general methodology that can be applied to any complex human activity (activity with a non-trivial, multi-level internal structure). The structural components of complex activities are considered, and their logical, cause-and-effect, and process structures are functionally described. Considerable attention is paid to organization and management, uncertainties, and the lifecycles of activities, as well as the actors, subject matter, resources, knowledge, and methods involved. Several typical examples are used throughout the text to illustrate the implementation of common approaches involving the functioning of work groups, organizational units, projects, and organizations in general: a retail bank, an aircraft manufacturer, a fire department, and a nuclear power plant. In addition, the book employs a system of connected technical models, in order to ensure that the results are of practical applicability for both experts on the ground and scholars engaged in research on the general principles of how activities (practical, scientific, etc.) are organized or on the management of socio-technical systems.

As the global economy turns more and more service oriented, Information Technology-Enabled Services (ITeS) require greater understanding. Increasing numbers and varieties of services are provided through IT. Furthermore, IT enables the creation of new services in diverse fields previously untouched. Because of the catalyzing nature of internet technology, ITeS today has become more than "Outsourcing" of services. This book illustrates the enabling nature of ITeS with its entailment of IT, thus contributing to the betterment of humanity. The scope of this book is not only for academia but also for business persons, government practitioners and readers from daily lives. Authors from a variety of nations and regions with various backgrounds provide insightful theories, research, findings and practices in various fields such as commerce, finance, medical services, government and education. This book opens up a new horizon with the application of Internet-based practices in business, government and in daily lives. Information Technology-Enabled Services works as a navigator for those who sail to the new horizon of service oriented economies.

This second edition provides a systematic introduction to the work and views of the emerging patent-search research and innovation communities as well as an overview of what has been achieved and, perhaps even more importantly, of what remains to be achieved. It revises many of the contributions of the first edition and adds a significant number of new ones. The first part "Introduction to Patent Searching" includes two overview chapters on the peculiarities of patent searching and on contemporary search technology respectively, and thus sets the scene for the subsequent parts. The second part on "Evaluating Patent Retrieval" then begins with two chapters dedicated to patent evaluation campaigns, followed by two chapters discussing complementary issues from the perspective of patent searchers and from the perspective of related domains, notably legal search. "High Recall Search" includes four completely new chapters dealing with the issue of finding only the relevant documents in a reasonable time span. The last (and with six papers the largest) part on "Special Topics in Patent Information Retrieval" covers a large spectrum of research in the patent field, from classification and image processing to translation. Lastly, the book is completed by an outlook on open issues and future research. Several of the chapters have been jointly written by intellectual property and information retrieval experts. However, members of both communities with a background different to that of the primary author have reviewed the chapters, making the book accessible to both the patent search community and to the information retrieval research community. It also not only offers the latest findings for academic researchers, but is also a valuable resource for IP professionals wanting to learn about current IR approaches in the patent domain.

"The book...has enough depth for even a seasoned professional to pick up enough tips to pay back the price of the book many times over." -Dr. Paul Dorsey, President, Dulcian, Inc., Oracle Magazine PL/SQL Developer of the Year 2007, and President Emeritus, New York Oracle Users Group "This is a fascinating guide into the world of Oracle SQL with an abundance of well-collected examples. Without a doubt, this book is helpful to beginners and experts alike who seek alternative ways to resolve advanced scenarios."-Oleg Voskoboynikov, Ph.D., Database Architect The World's #1 Hands-On Oracle SQL Workbook-Fully Updated for Oracle 11g Crafted for hands-on learning and tested in classrooms worldwide, this book illuminates in-depth every Oracle SQL technique you'll need. From the simplest query fundamentals to regular expressions and with newly added coverage of Oracle's powerful new SQL Developer tool, you will focus on the tasks that matter most. Hundreds of step-by-step, guided lab exercises will systematically strengthen your expertise in writing effective, high-performance SQL. Along the way, you'll acquire a powerful arsenal of useful skills-and an extraordinary library of solutions for your real-world challenges with Oracle SQL. Coverage includes 100% focused on Oracle SQL for Oracle 11 g, today's #1 database platform-not "generic" SQL! Master all core SQL techniques including every type of join such as equijoins, self joins, and outer joins Understand Oracle functions in depth, especially character, number, date, timestamp, interval, conversion, aggregate, regular expressions, analytical, and more Practice all types of subqueries, such as correlated and scalar subqueries, and learn about set operators and hierarchical queries Build effective queries and learn fundamental Oracle SQL Developer and SQL*Plus skills Make the most of the Data Dictionary and create tables, views, indexes, and sequences Secure databases using Oracle privileges, roles, and synonyms Explore Oracle 11 g's advanced data warehousing features Learn many practical tips about performance optimization, security, and architectural solutions Avoid common pitfalls and understand and solve common mistakes For every database developer, administrator, designer, or architect, regardless of experience!

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Constraints and Databases contains seven contributions on the rapidly evolving research area of constraints and databases. This collection of original research articles has been compiled as a tribute to Paris C. Kanellakis, one of the pioneers in the field. Constraints have long been used for maintaining the integrity of databases. More recently, constraint databases have emerged where databases store and manipulate data in the form of constraints. The generality of constraint databases makes them highly attractive for many applications. Constraints provide a uniform mechanism for describing heterogenous data, and advanced constraint solving methods can be used for efficient manipulation of constraint data. The articles included in this book cover the range of topics involving constraints and databases; join algorithms, evaluation methods, applications (e.g. data mining) and implementations of constraint databases, as well as more traditional topics such as integrity constraint maintenance. Constraints and Databases is an edited volume of original research comprising invited contributions by leading researchers.

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.

Databases and database systems in particular, are considered as kerneIs of any Information System (IS). The rapid growth of the web on the Internet has dramatically increased the use of semi-structured data and the need to store and retrieve such data in a database. The database community quickly reacted to these new requirements by providing models for semi-structured data and by integrating database research to XML web services and mobile computing. On the other hand, IS community who never than before faces problems of IS development is seeking for new approaches to IS design. Ontology based approaches are gaining popularity, because of a need for shared conceptualisation by different stakeholders of IS development teams. Many web-based IS would fail without domain ontologies to capture meaning of terms in their web interfaces. This volume contains revised versions of 24 best papers presented at the th 5 International Baltic Conference on Databases and Information Systems (BalticDB&IS'2002). The conference papers present original research results in the novel fields of IS and databases such as web IS, XML and databases, data mining and knowledge management, mobile agents and databases, and UML based IS development methodologies. The book's intended readers are researchers and practitioners who are interested in advanced topics on databases and IS."

Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. They offer frameworks for critically evaluating the ingredients and the ethical considerations needed to apply data science productively, illustrated by extensive application examples. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world.

Here is the ideal field guide for data warehousing implementation. This book first teaches you how to build a data warehouse, including defining the architecture, understanding the methodology, gathering the requirements, designing the data models, and creating the databases. Coverage then explains how to populate the data warehouse and explores how to present data to users using reports and multidimensional databases and how to use the data in the data warehouse for business intelligence, customer relationship management, and other purposes. It also details testing and how to administer data warehouse operation.

Health information about patients is critical; currently, health records are saved in databases controlled by individual users, organizations, or large groups of organizations. As there are many malicious users, this information is not shared with other organizations due to security issues and the chance of the data being modified or tampered with. Blockchain can be used to securely exchange healthcare data, which can be accessed by organizations sharing the same network, allowing doctors/practitioners to provide better care for patients. The key properties of decentralization, such as immutability and transparency, improve healthcare interoperability. This book brings forth the prospects and research trends of Blockchain in healthcare, so that Researchers, Database professionals, Academia, and Healthcare professionals across the world can know/use the concept of Blockchain in healthcare. The book provides the fundamental and technical details of Blockchain, the applications of Blockchain in healthcare, hands-on chapters for graduate/postgraduate/doctoral students/healthcare professionals to secure healthcare data of patients, and research challenges and future work directions for researchers in healthcare.

The edited volume deals with different contours of data science with special reference to data management for the research innovation landscape. The data is becoming pervasive in all spheres of human, economic and development activity. In this context, it is important to take stock of what is being done in the data management area and begin to prioritize, consider and formulate adoption of a formal data management system including citation protocols for use by research communities in different disciplines and also address various technical research issues. The volume, thus, focuses on some of these issues drawing typical examples from various domains. The idea of this work germinated from the two day workshop on "Big and Open Data - Evolving Data Science Standards and Citation Attribution Practices", an international workshop, led by the ICSU-CODATA and attended by over 300 domain experts. The Workshop focused on two priority areas (i) Big and Open Data: Prioritizing, Addressing and Establishing Standards and Good Practices and (ii) Big and Open Data: Data Attribution and Citation Practices. This important international event was part of a worldwide initiative led by ICSU, and the CODATA-Data Citation Task Group. In all, there are 21 chapters (with 21st Chapter addressing four different core aspects) written by eminent researchers in the field which deal with key issues of S&T, institutional, financial, sustainability, legal, IPR, data protocols, community norms and others, that need attention related to data management practices and protocols, coordinate area activities, and promote common practices and standards of the research community globally. In addition to the aspects touched above, the national / international perspectives of data and its various contours have also been portrayed through case studies in this volume.

Databases have been designed to store large volumes of data and to provide efficient query interfaces. Semantic Web formats are geared towards capturing domain knowledge, interlinking annotations, and offering a high-level, machine-processable view of information. However, the gigantic amount of such useful information makes efficient management of it increasingly difficult, undermining the possibility of transforming it into useful knowledge.

The research presented by De Virgilio, Giunchiglia and Tanca tries to bridge the two worlds in order to leverage the efficiency and scalability of database-oriented technologies to support an ontological high-level view of data and metadata. The contributions present and analyze techniques for semantic information management, by taking advantage of the synergies between the logical basis of the Semantic Web and the logical foundations of data management. The book's leitmotif is to propose models and methods especially tailored to represent and manage data that is appropriately structured for easier machine processing on the Web.

After two introductory chapters on data management and the Semantic Web in general, the remaining contributions are grouped into five parts on Semantic Web Data Storage, Reasoning in the Semantic Web, Semantic Web Data Querying, Semantic Web Applications, and Engineering Semantic Web Systems. The handbook-like presentation makes this volume an important reference on current work and a source of inspiration for future development, targeting academic and industrial researchers as well as graduate students in Semantic Web technologies or database design.

During the last several years there has been a signi?cant coalescence of interest in Open Source Geospatial (OSG) or, as it is also known and referred to in this book, Free and Open Source for Geospatial (FOSS4G) software technology. This interest has served to fan embers from pre-existing FOSS4G efforts, that were - cused on both standalone desktop geographic information systems (GIS), such as GRASS, libraries of geospatial utilities, such as GDAL, and Web-based mapping applications, such as MapServer. The impetus for the coalescence of disparate and th independent project-based efforts was the formal incorporation on February 27 , 2006 of a non-pro?t organization known as the Open Source Geospatial Foun- tion (OSGeo). Full details concerning the foundation, including its mission sta- ment, goals, evolving governance structure, approved projects, Board of Directors, journal, and much other useful information are available through the Foundation's website (http://www. osgeo. org). This book is not about OSGeo, yet it is dif?cult to produce a text on FOSS4G - proaches to spatial data handling without, in some way or another, encountering the activities and personalities of OSGeo. Of the current books published on this topic the majority are written by authors with very close connections to OSGeo. For - ample, Tyler Mitchell who is the Executive Director of the Foundation, is author of one of the ?rst books on FOSS4G approaches ('Web Mapping Illustrated' (2005)).

Autonomous agents or multiagent systems are computational systems in which several computational agents interact or work together to perform some set of tasks. These systems may involve computational agents having common goals or distinct goals. Real-Time Search for Learning Autonomous Agents focuses on extending real-time search algorithms for autonomous agents and for a multiagent world. Although real-time search provides an attractive framework for resource-bounded problem solving, the behavior of the problem solver is not rational enough for autonomous agents. The problem solver always keeps the record of its moves and the problem solver cannot utilize and improve previous experiments. Other problems are that although the algorithms interleave planning and execution, they cannot be directly applied to a multiagent world. The problem solver cannot adapt to the dynamically changing goals and the problem solver cannot cooperatively solve problems with other problem solvers. This book deals with all these issues. Real-Time Search for Learning Autonomous Agents serves as an excellent resource for researchers and engineers interested in both practical references and some theoretical basis for agent/multiagent systems. The book can also be used as a text for advanced courses on the subject.

Hypertext/hypermedia systems and user-model-based adaptive systems in the areas of learning and information retrieval have for a long time been considered as two mutually exclusive approaches to information access. Adaptive systems tailor information to the user and may guide the user in the information space to present the most relevant material, taking into account a model of the user's goals, interests and preferences. Hypermedia systems, on the other hand, are `user neutral': they provide the user with the tools and the freedom to explore an information space by browsing through a complex network of information nodes. Adaptive hypertext and hypermedia systems attempt to bridge the gap between these two approaches. Adaptation of hypermedia systems to each individual user is increasingly needed. With the growing size, complexity and heterogeneity of current hypermedia systems, such as the World Wide Web, it becomes virtually impossible to impose guidelines on authors concerning the overall organization of hypermedia information. The networks therefore become so complex and unstructured that the existing navigational tools are no longer powerful enough to provide orientation on where to search for the needed information. It is also not possible to identify appropriate pre-defined paths or subnets for users with certain goals and knowledge backgrounds since the user community of hypermedia systems is usually quite inhomogeneous. This is particularly true for Web-based applications which are expected to be used by a much greater variety of users than any earlier standalone application. A possible remedy for the negative effects of the traditional `one-size-fits-all' approach in the development of hypermedia systems is to equip them with the ability to adapt to the needs of their individual users. A possible way of achieving adaptivity is by modeling the users and tailoring the system's interactions to their goals, tasks and interests. In this sense, the notion of adaptive hypertext/hypermedia comes naturally to denote a hypertext or hypermedia system which reflects some features of the user and/or characteristics of his system usage in a user model, and utilizes this model in order to adapt various behavioral aspects of the system to the user. This book is the first comprehensive publication on adaptive hypertext and hypermedia. It is oriented towards researchers and practitioners in the fields of hypertext and hypermedia, information systems, and personalized systems. It is also an important resource for the numerous developers of Web-based applications. The design decisions, adaptation methods, and experience presented in this book are a unique source of ideas and techniques for developing more usable and more intelligent Web-based systems suitable for a great variety of users. The practitioners will find it important that many of the adaptation techniques presented in this book have proved to be efficient and are ready to be used in various applications.

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trust metrics and security, scheduling in distributed heterogenous computing environments, semantic Web service composition, social simulation, and software agents for WSNs.

Modern medicine generates, almost daily, huge amounts of heterogeneous data. For example, medical data may contain SPECT images, signals lik e ECG, clinical information like temperature, cholesterol levels, etc., as well as the physician's interpretation. Those who deal with such data understand that there is a widening gap between data collection a nd data comprehension. Computerized techniques are needed to help huma ns address this problem. This volume is devoted to the relatively youn g and growing field of medical data mining and knowledge discovery. As more and more medical procedures employ imaging as a preferred diagno stic tool, there is a need to develop methods for efficient mining in databases of images. Other significant features are security and confi dentiality concerns. Moreover, the physician's interpretation of image s, signals, or other technical data, is written in unstructured Englis h which is very difficult to mine. This book addresses all these speci fic features.