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AI can be all too human: quick to judge, capable of error, vulnerable to bias. It's made by humans after all. Humans design the systems and tools that make new forms of AI faster. Humans are the data sources that make AI smarter. Humans will make decisions about how to use AI. The laws and standards, the tools, the ethics. Who benefits. Who gets hurt. Made by Humans explores our role in automation and the responsibilities we must take on. Roaming from Australia to the UK and the US, Broad talks to world-leading experts in AI and history about what we need to do next. A personal, thought-provoking examination of humans as data and humans as the designers of systems that try to understand us.
Reuse and integration are defined as synergistic concepts, where reuse addresses how to minimize redundancy in the creation of components; while, integration focuses on component composition. Integration supports reuse and vice versa. These related concepts support the design of software and systems for maximizing performance while minimizing cost. Knowledge, like data, is subject to reuse; and, each can be interpreted as the other. This means that inherent complexity, a measure of the potential utility of a system, is directly proportional to the extent to which it maximizes reuse and integration. Formal methods can provide an appropriate context for the rigorous handling of these synergistic concepts. Furthermore, formal languages allow for non ambiguous model specification; and, formal verification techniques provide support for insuring the validity of reuse and integration mechanisms. This edited book includes 12 high quality research papers written by experts in formal aspects of reuse and integration to cover the most recent advances in the field. These papers are extended versions of some of the best papers, which were presented at the IEEE International Conference on Information Reuse and Integration and the IEEE International Workshop on Formal Methods Integration - both of which were held in San Francisco in August 2014.
This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.
This book focuses on soft computing techniques for enhancing voltage security in electrical power networks. Artificial neural networks (ANNs) have been chosen as a soft computing tool, since such networks are eminently suitable for the study of voltage security. The different architectures of the ANNs used in this book are selected on the basis of intelligent criteria rather than by a "brute force" method of trial and error. The fundamental aim of this book is to present a comprehensive treatise on power system security and the simulation of power system security. The core concepts are substantiated by suitable illustrations and computer methods. The book describes analytical aspects of operation and characteristics of power systems from the viewpoint of voltage security. The text is self-contained and thorough. It is intended for senior undergraduate students and postgraduate students in electrical engineering. Practicing engineers, Electrical Control Center (ECC) operators and researchers will also find the book useful.
This book includes the extended and revised versions of a set of selected papers from the First NAFOSTED Conference on Information and Computer Science (NICS'2014), held at Le Quy Don Technical Academy, Hanoi, Vietnam from 13/Mar./2014 to 14/Mar./2014. The conference was co-organized by The National Foundation for Science and Technology Development (NAFOSTED) and Le Quy Don Technical Academy. The purpose of the NICS conference series is to promote scientific publications in the country and to provide a platform for high quality academic exchange among scientists in the fields of computer science, information and communication. The conference includes five tracks, namely "Computer Science", "Artificial Intelligence", "Network Systems", "Software Engineering", and "Information Systems". The papers in this book are among the best contributions at NICS'2014 taken into account the quality of their presentation at the conference and the recommendation of the two experts in the extra round of independent review.
This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k-nearest neighbors and bayesian classifiers. Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.
This volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selfish decision makers. The chapters are written by leading experts from different disciplines, all considering the many sources of imperfection in decision making, and always with an eye to decreasing the myriad discrepancies between theory and real world human decision making. Topics addressed include uncertainty, deliberation cost and the complexity arising from the inherent large computational scale of decision making in these systems. In particular, analyses and experiments are presented which concern: * task allocation to maximize "the wisdom of the crowd"; * design of a society of "edutainment" robots who account for one anothers' emotional states; * recognizing and counteracting seemingly non-rational human decision making; * coping with extreme scale when learning causality in networks; * efficiently incorporating expert knowledge in personalized medicine; * the effects of personality on risky decision making. The volume is a valuable source for researchers, graduate students and practitioners in machine learning, stochastic control, robotics, and economics, among other fields.
This book is about the formulations, theoretical investigations, and practical applications of new stochastic models for fundamental concepts and operations of the discipline of risk management. It also examines how these models can be useful in the descriptions, measurements, evaluations, and treatments of risks threatening various modern organizations. Moreover, the book makes clear that such stochastic models constitute very strong analytical tools which substantially facilitate strategic thinking and strategic decision making in many significant areas of risk management. In particular the incorporation of fundamental probabilistic concepts such as the sum, minimum, and maximum of a random number of continuous, positive, independent, and identically distributed random variables in the mathematical structure of stochastic models significantly supports the suitability of these models in the developments, investigations, selections, and implementations of proactive and reactive risk management operations. The book makes extensive use of integral and differential equations of characteristic functions, mainly corresponding to important classes of mixtures of probability distributions, as powerful analytical tools for investigating the behavior of new stochastic models suitable for the descriptions and implementations of fundamental risk control and risk financing operations. These risk treatment operations very often arise in a wide variety of scientific disciplines of extreme practical importance.
This book provides an interdisciplinary collection of views on the ethical challenges and opportunities of workplaces in the Internet of things. Current developments within Ubiquitous computing (ubicomp) systems designed for the workplace are introduced and philosophical, organizational and socio-ethical considerations of ubicomp in workplaces are provided. Suggestions regarding the rules that should be respected in order to favor an adequate implementation of ubicomp in the workplace are offered, considering both intra-organizational but also wider societal concerns. The interdisciplinary collection of contributions invites the reader to engage in the discussion of ubicomp in everyday working environments.
The second international conference on INformation Systems Design and Intelligent Applications (INDIA - 2015) held in Kalyani, India during January 8-9, 2015. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of two different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano-computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.
This book constitutes the refereed proceedings of the 12th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2017, held in Zadar, Croatia, in May 2017. The 35 revised full papers presented together with 4 keynote lectures were carefully reviewed and selected from 46 submissions. The papers deal with environmental challenges and try to provide solutions using forward-looking and leading-edge IT technology. They are organized in the following topical sections: air and climate; water and hydrosphere; health and biosphere; risk and disaster management; information systems; and modelling, visualization and decision support.
With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also useful for those who are interested in using artificial intelligence in power system optimization.
This book constitutes the refereed proceedings of the 18th International Conference on Principles of Distributed Systems, OPODIS 2014, Cortina d'Ampezzo, Italy, in December 2014. The 32 papers presented together with two invited talks were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on consistency; distributed graph algorithms; fault tolerance; models; radio networks; robots; self-stabilization; shared data structures; shared memory; synchronization and universal construction.
Living with Robots recounts a foundational shift in the field of robotics, from artificial intelligence to artificial empathy, and foreshadows an inflection point in human evolution. Today's robots engage with human beings in socially meaningful ways, as therapists, trainers, mediators, caregivers, and companions. Social robotics is grounded in artificial intelligence, but the field's most probing questions explore the nature of the very real human emotions that social robots are designed to emulate. Social roboticists conduct their inquiries out of necessity-every robot they design incorporates and tests a number of hypotheses about human relationships. Paul Dumouchel and Luisa Damiano show that as roboticists become adept at programming artificial empathy into their creations, they are abandoning the conventional conception of human emotions as discrete, private, internal experiences. Rather, they are reconceiving emotions as a continuum between two actors who coordinate their affective behavior in real time. Rethinking the role of sociability in emotion has also led the field of social robotics to interrogate a number of human ethical assumptions, and to formulate a crucial political insight: there are simply no universal human characteristics for social robots to emulate. What we have instead is a plurality of actors, human and nonhuman, in noninterchangeable relationships. As Living with Robots shows, for social robots to be effective, they must be attentive to human uniqueness and exercise a degree of social autonomy. More than mere automatons, they must become social actors, capable of modifying the rules that govern their interplay with humans.
This book constitutes the thoroughly refereed post-conference proceedings of the 1st International Conference on Swarm Intelligence Based Optimization, ICSIBO 2014, held in Mulhouse, France, in May 2014. The 20 full papers presented were carefully reviewed and selected from 48 submissions. Topics of interest presented and discussed in the conference focuses on the theoretical progress of swarm intelligence metaheuristics and their applications in areas such as: theoretical advances of swarm intelligence metaheuristics, combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization, artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm, hybridization of algorithms, parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles, adaptation and applications of swarm intelligence principles to real world problems in various domains.
This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2014, held in Granada, Spain, in April 2014, colocated with the Evo* 2014 events EuroGP, EvoCOP, and EvoMUSART. The 79 revised full papers presented were carefully reviewed and selected from 128 submissions. EvoApplications 2014 consisted of the following 13 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), EvoSTOC (evolutionary algorithms in stochastic and dynamic environments), and EvoBio (EC and related techniques in bioinformatics and computational biology).
This book constitutes the thoroughly refereed papers of the 8th Chinese Conference on The Semantic Web and Web Science, CSWS 2014, held in Wuhan, China, in August 2014. The 22 research papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in topical sections such as ontology reasoning and learning; semantic data generation and management; and semantic technology and applications.
This book constitutes the refereed proceedings of the Third International Conference, TPNC 2014, held in Granada, Spain, in December 2014. The 22 revised full papers presented in this book were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on nature-inspired models of computation; synthesizing nature by means of computation; nature-inspired materials; and information processing in nature.
This book covers the latest advances in Big Data technologies and provides the readers with a comprehensive review of the state-of-the-art in Big Data processing, analysis, analytics, and other related topics. It presents new models, algorithms, software solutions and methodologies, covering the full data cycle, from data gathering to their visualization and interaction, and includes a set of case studies and best practices. New research issues, challenges and opportunities shaping the future agenda in the field of Big Data are also identified and presented throughout the book, which is intended for researchers, scholars, advanced students, software developers and practitioners working at the forefront in their field.
The volume LNCS 8866 constitutes the refereed proceedings of the 11th International Symposium on Neural Networks, ISNN 2014, held in Hong Kong and Macao, China on November/ December 2014. The 71 revised full papers presented were carefully reviewed and selected from 119 submissions. These papers cover all major topics of the theoretical research, empirical study and applications of neural networks research as follows. The focus is on following topics such as analysis, modeling, and applications.
This volume constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2014, and Ontologies, Databases, and Applications of Semantics, ODBASE 2014, held as part of OTM 2014 in October 2014 in Amantea, Italy. The 39 full papers presented together with 12 short papers and 5 keynotes were carefully reviewed and selected from a total of 115 submissions. The OTM program covers subjects as follows: process designing and modeling, process enactment, monitoring and quality assessment, managing similarity, software services, improving alignment, collaboration systems and applications, ontology querying methodologies and paradigms, ontology support for web, XML, and RDF data processing and retrieval, knowledge bases querying and retrieval, social network and collaborative methodologies, ontology-assisted event and stream processing, ontology-assisted warehousing approaches, ontology-based data representation, and management in emerging domains.
This monograph demonstrates the interplay between Shannon information and semantic information in cognition. It shows that Shannon's information acts as driving force for the formation of semantic information; and vice versa, namely, that semantic information participates in the formation of Shannonian information. The authors show that in cognition, Shannonian and semantic information are interrelated as two aspects of a cognitive process termed as information adaptation. In the latter the mind/brain adapts to the environment by the deflating and/or inflating of the information conveyed by the environment. In the process of information adaptation, quantitative variations in Shannon's information entail different meanings while different meanings affect the quantity of information. The book illustrates the above conceptually and mathematically by reference to three cognitive processes: pattern recognition, face learning and the recognition of a moving object.
The book gives a comprehensive overview of the state-of-the-art research and engineering in theory and application of Lattice Automata in design and control of autonomous Robots. Automata and robots share the same notional meaning. Automata (originated from the latinization of the Greek word " ") as self-operating autonomous machines invented from ancient years can be easily considered the first steps of robotic-like efforts. Automata are mathematical models of Robots and also they are integral parts of robotic control systems. A Lattice Automaton is a regular array or a collective of finite state machines, or automata. The Automata update their states by the same rules depending on states of their immediate neighbours. In the context of this book, Lattice Automata are used in developing modular reconfigurable robotic systems, path planning and map exploration for robots, as robot controllers, synchronisation of robot collectives, robot vision, parallel robotic actuators. All chapters are written in an accessible manner and lavishly illustrated. The book will help computer and robotic scientists and engineers to understand mechanisms of decentralised functioning of robotic collectives and to design future and emergent reconfigurable, parallel and distributed robotic systems.
Prostheses, assistive systems, and rehabilitation systems are essential to increasing the quality of life for people with disabilities. Research and development over the last decade has resulted in enormous advances toward that goal-none more so than the development of intelligent systems and technologies.
The focus of this volume is comprised of the fundamentals, models, and information technologies (IT) methods and tools for disaster prediction and mitigation. A more detailed list of topics includes mathematical and computational modeling of processes leading to or producing disasters, modeling of disaster effects, IT means for disaster mitigation, including data mining tools, knowledge-based and expert systems for use in disaster circumstances, GIS-based systems for disaster prevention and mitigation and equipment for disaster-prone areas. A specific type or class of disasters (natural or human-made), however will not be part of the main focus of this work. Instead, this book was conceived to offer a comprehensive, integrative view on disasters, seeking to determine what various disasters have in common. Because disaster resilience and mitigation involve humans, societies and cultures, not only technologies and economic models, special attention was paid in this volume to gain a comprehensive view on these issues, as a foundation of the IT tool design.
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