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1.


    Satapathy, Ranjan.
    Sentiment Analysis in the Bio-Medical Domain [[electronic resource] :] : techniques, Tools, and Applications / / Ranjan. Satapathy, Cambria, Erik., Hussain, Amir. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXIV, 134 p. 45 illus., 33 illus. in color. - Б. ц.
Рубрики: Medicine.
   Computational intelligence.
   Computer science.
   Biomedicine, general.
   Computational Intelligence.
   Computer Science, general.
Анотація: The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain. The readers will discover the following key novelties: 1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.; 2) ensemble of machine learning and computational creativity; 3) development of microtext analysis techniques to overcome the inconsistency in social communication. It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining.

Перейти: https://doi.org/10.1007/978-3-319-68468-0

Дод.точки доступу:
Cambria, Erik.; Hussain, Amir.; Satapathy, Ranjan. \.\; SpringerLink (Online service)
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2.


    Liao, Huchang.
    Hesitant Fuzzy Decision Making Methodologies and Applications [[electronic resource] /] : монография / Huchang. Liao, Xu, Zeshui. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIII, 275 p. 19 illus., 8 illus. in color. - Б. ц.
    Зміст:
Preface --
1 Hesitant Fuzzy Set and Its Extensions --
2 Novel Correlation and Entropy Measures for Hesitant Fuzzy Set --
3 Multiple Criteria Decision Making with Hesitant Fuzzy Hybrid Weighted Aggregation Operators --
4 Hesitant Fuzzy Multiple Criteria Decision Making with Complete Weight Information --
5 Hesitant Fuzzy Multiple Criteria Decision Making with Incomplete Weights --
6 Decision Making with Hesitant Fuzzy Preference Relation.
Рубрики: Operations research.
   Decision making.
   Computational intelligence.
   Operating systems (Computers).
   Operations Research/Decision Theory.
   Computational Intelligence.
   Operating Systems.
Анотація: This book offers a comprehensive and systematic introduction to the latest research on hesitant fuzzy decision-making theory. It includes six parts: the hesitant fuzzy set and its extensions, novel hesitant fuzzy measures, hesitant fuzzy hybrid weighted aggregation operators, hesitant fuzzy multiple-criteria decision-making with incomplete weights, hesitant fuzzy multiple criteria decision-making with complete weights information, and the hesitant fuzzy preference relation based decision-making theory. These methodologies are implemented in various fields such as decision-making, medical diagnosis, cluster analysis, service quality management, e-learning management and environmental management. A valuable resource for engineers, technicians, and researchers in the fields of fuzzy mathematics, operations research, information science, management science and engineering, it can also be used as a textbook for postgraduate and senior undergraduate students.

Перейти: https://doi.org/10.1007/978-981-10-3265-3

Дод.точки доступу:
Xu, Zeshui.; Liao, Huchang. \.\; SpringerLink (Online service)
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3.


   
    Hybrid Intelligence for Social Networks [[electronic resource] /] : монография / ed. Banati, Hema. [et al.]. - 1st ed. 2017. - [S. l. : s. n.]. - XIV, 327 p. 142 illus., 105 illus. in color. - Б. ц.
    Зміст:
Social Networks: Fundamentals and Applications --
MapReduce-Based K-FA Algorithm for Detecting Communities in Social Networks --
Group Search Optimization Strategy for Community Detection in Complex Networks --
Strategizing Information Dissemination in Real-Life Networks --
Nature-Inspired Heuristics Approach to Partitioning Complex Interaction Networks --
ROGO: Recommendations on the Go for Travel Tweeters --
Analysing Social Interaction Networks: Improving Teaching Learning Pedagogies --
Adapting Trustworthy Social Web Environments for the Cloud --
Enhanced Black-Hole Algorithm for Viral Marketing --
Comparative Analysis of Network Visualization Tools --
Enacting a Prioritized Health Awareness Campaign for Social Web Users --
Identifying Clusters in Complex Dynamic Social Networks Using Evolutionary Algorithms --
Using Intuitionistic Fuzzy Sets to Prioritize Relationships Among Facebook Users --
A Predictive Approach to Ranking Academic Articles. .
Рубрики: Artificial intelligence.
   Computational intelligence.
   Application software.
   Artificial Intelligence.
   Computational Intelligence.
   Computer Appl. in Social and Behavioral Sciences.
Анотація: This book explains aspects of social networks, varying from development and application of new artificial intelligence and computational intelligence techniques for social networks to understanding the impact of social networks. Chapters 1 and 2 deal with the basic strategies towards social networks such as mining text from such networks and applying social network metrics using a hybrid approach; Chaps. 3 to 8 focus on the prime research areas in social networks: community detection, influence maximization and opinion mining. Chapter 9 to 13 concentrate on studying the impact and use of social networks in society, primarily in education, commerce, and crowd sourcing.  The contributions provide a multidimensional approach, and the book will serve graduate students and researchers as a reference in computer science, electronics engineering, communications, and information technology. .

Перейти: https://doi.org/10.1007/978-3-319-65139-2

Дод.точки доступу:
Banati, Hema. \ed.\; Bhattacharyya, Siddhartha. \ed.\; Mani, Ashish. \ed.\; Koppen, Mario. \ed.\; SpringerLink (Online service)
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4.


   
    Brain-Computer Interface Research [[electronic resource] :] : a State-of-the-Art Summary 6 / / ed.: Guger, Christoph., Allison, Brendan., Lebedev, Mikhail. - 1st ed. 2017. - [S. l. : s. n.]. - VI, 134 p. 49 illus., 44 illus. in color. - Б. ц.
    Зміст:
Introduction (C. Guger et al.) --
Advances in BCI: A Neural Bypass Technology to Reconnect the Brain to the Body (G. Sharma et al.) --
Re(con)volution: Accurate Response Prediction for Broad-Band Evoked Potential-Based BCIs (J. Thielen et al.) --
Intracortical Microstimulation as a Feedback Source for BCI Users (S. Flesher et al.) --
A Minimally Invasive Endovascular Stent-Electrode Array for Chronic Recordings of Cortical Neural Activity (T. J. Oxley et al.) --
Visual Cue-Guided Rat Cyborg (Y. Wang et al.) --
Predicting Motor Intentions with Closed-Loop BCIs (M. Schultze-Kraft et al.) --
Sixteen Commands and 40 Hz Carrier Frequency Code-Modulated Visual Evoked Potential BCI (D. Aminaka et al.) --
Precise and Reliable Activation of Cortex with Micro-Coils (S. Woo Lee et al.) --
Towards Online Functional Brain Mapping and Monitoring During Awake Craniotomy Surgery Using ECoG-Based Brain-Surgeon Interface (BSI) (L. Yao et al.).
Рубрики: User interfaces (Computer systems).
   Neurosciences.
   Medical physics.
   Radiation.
   Computational intelligence.
   User Interfaces and Human Computer Interaction.
   Neurosciences.
   Medical and Radiation Physics.
   Computational Intelligence.
Анотація: This book presents compact and informative descriptions of the most promising new projects in brain-computer interface (BCI) research. As in earlier volumes in this series, the contributions come from many of the best-known groups in BCI research. Each of these chapters provides an overview of a project that was nominated for the most prestigious award in the BCI community: the Annual BCI Research Award. The book also contains an introduction and discussion with a review of major trends reflected in the awards. This volume also introduces a new type of contribution, namely a chapter"Trends in BCI Research" that summarizes a top trend in the BCI research community. This year's "Trends in BCI Research" addresses BCI technology to help patients with disorders of consciousness (DOC) and related conditions, including new work that goes beyond communication to diagnosis and even prediction.

Перейти: https://doi.org/10.1007/978-3-319-64373-1

Дод.точки доступу:
Guger, Christoph. \ed.\; Allison, Brendan. \ed.\; Lebedev, Mikhail. \ed.\; SpringerLink (Online service)
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5.


    Youn, Chan-Hyun.
    Cloud Broker and Cloudlet for Workflow Scheduling [[electronic resource] /] : монография / Chan-Hyun. Youn, Chen, Min., Dazzi, Patrizio. ; . - 1st ed. 2017. - [S. l. : s. n.]. - IX, 212 p. 92 illus., 48 illus. in color. - Б. ц.
    Зміст:
1 Integrated Cloud Broker System and Its Experimental Evaluation --
2 VM Placement via Resource Brokers in a Cloud Datacenter --
3 Cost Adaptive Workflow Resource Broker in Cloud --
4 A Cloud Broker System for Connected Car Services with an Integrated Simulation Framework --
5 Mobile Device as Cloud Broker for Computation Offloading at Cloudlets --
6 Opportunistic Task Scheduling over Co-Located Clouds --
7 Mobility-Aware Resource Scheduling Cloudlets in Mobile Environment --
8 Machine-learning based approaches for cloud brokering. .
Рубрики: Computer organization.
   Computational intelligence.
   Software engineering.
   Application software.
   Information technology.
   Business—Data processing.
   Computer Systems Organization and Communication Networks.
   Computational Intelligence.
   Software Engineering/Programming and Operating Systems.
   Information Systems Applications (incl. Internet).
   IT in Business.
Анотація: This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT). Due to dynamic situations in user demand and cloud resource status, scalability has become crucial in the execution of complex scientific applications. Therefore, data analysts and computer scientists must grasp workflow management issues in order to better understand the characteristics of cloud resources, allocate these resources more efficiently and make critical decisions intelligently. Thus, this book addresses these issues through discussion of some novel approaches and engineering issues in cloud broker systems and cloudlets for workflow scheduling. This book closes the gaps between cloud programmers and scientific applications designers, describing the fundamentals of cloud broker system technology and the state-of-the-art applications in implementation and performance evaluation. The books gives details of scheduling structures and processes, providing guidance and inspiration for users including cloud programmers, application designers and decision makers with involvement in cloud resource management.

Перейти: https://doi.org/10.1007/978-981-10-5071-8

Дод.точки доступу:
Chen, Min.; Dazzi, Patrizio.; Youn, Chan-Hyun. \.\; SpringerLink (Online service)
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6.


   
    Applications of Cognitive Computing Systems and IBM Watson [[electronic resource] :] : 8th IBM Collaborative Academia Research Exchange / / ed.: Contractor, Danish., Telang, Aaditya. - 1st ed. 2017. - [S. l. : s. n.]. - VII, 98 p. 38 illus. - Б. ц.
    Зміст:
Chapter 1. Introduction --
Chapter 2. Research Papers --
Chapter 3. Hackathon Applictions --
Chapter 4. Watson Cognitive Challenge Applications --
Chapter 5. Conclusion.  .
Рубрики: User interfaces (Computer systems).
   Artificial intelligence.
   Computational intelligence.
   User Interfaces and Human Computer Interaction.
   Artificial Intelligence.
   Computational Intelligence.
Анотація: This book presents reports and methods that demonstrate the ease with which cognitive applications can be built using IBM Watson application program interfaces (APIs). It includes application reports from two IBM Watson API-based competitions – Hackathon (24 hours) and a Challenge task (~3 months). It also features a selection of papers presented at I-CARE 2016, the IBM Collaborative Academia Research Exchange event, from the areas of “Theory and Cognitive Computing”, “Data Platforms and Systems,” and “Societal Applications.” IBM has a long tradition of research collaboration with colleagues in academia, and I-CARE is an annual event initiated in 2009 to promote collaborative innovation and learning, and explore new ways of fostering a culture of innovation. I-CARE’s main goal is to “amalgamate” the thought leadership in Indian academia with that in industry, and foster a symbiotic environment for establishing a rich research culture in India. The 8th edition of I-CARE presents a collection of thought-provoking ideas and novel Indian research projects related to three crucial areas: cognitive computing, systems and platforms that support large-scale data processing and practical systems that are designed for the public good.

Перейти: https://doi.org/10.1007/978-981-10-6418-0

Дод.точки доступу:
Contractor, Danish. \ed.\; Telang, Aaditya. \ed.\; SpringerLink (Online service)
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7.


   
    Autonomy and Artificial Intelligence: A Threat or Savior? [[electronic resource] /] : монография / ed. Lawless, W.F. [et al.]. - 1st ed. 2017. - [S. l. : s. n.]. - XIV, 318 p. 102 illus., 86 illus. in color. - Б. ц.
    Зміст:
Preface --
Introduction --
Reexamining Computational Support for Intelligence Analysis: A Functional Design for a Future Capability --
Task Allocation Using Parallelized Clustering and Auctioning Algorithms for Heterogeneous Robotic Swarms Operating on a Cloud Network --
Human Information Interaction, Artificial Intelligence, and Errors --
Verification Challenges for Autonomous Systems --
Conceptualizing Over trust in Robots: Why Do People Trust a Robot That Previously Failed? --
Research Considerations and Tools for Evaluating Human-Automation Interaction with Future Unmanned Systems --
Robot autonomy: some technical issues --
How Children with Autism and Machines Learn to Interact --
Semantic Vector Spaces for Broadening Consideration of Consequences --
On the Road to Autonomy: Evaluating and Optimizing Hybrid Team Dynamics --
Cyber-security and Optimization in Smart “Autonomous” Buildings --
Evaluations: Autonomy and Artificial Intelligence: A threat or savior?
Рубрики: Artificial intelligence.
   Robotics.
   Automation.
   Computational intelligence.
   Artificial Intelligence.
   Robotics and Automation.
   Computational Intelligence.
Анотація: This book explores how Artificial Intelligence (AI), by leading to an increase in the autonomy of machines and robots, is offering opportunities for an expanded but uncertain impact on society by humans, machines, and robots. To help readers better understand the relationships between AI, autonomy, humans and machines that will help society reduce human errors in the use of advanced technologies (e.g., airplanes, trains, cars), this edited volume presents a wide selection of the underlying theories, computational models, experimental methods, and field applications. While other literature deals with these topics individually, this book unifies the fields of autonomy and AI, framing them in the broader context of effective integration for human-autonomous machine and robotic systems. The contributions, written by world-class researchers and scientists, elaborate on key research topics at the heart of effective human-machine-robot-systems integration. These topics include, for example, computational support for intelligence analyses; the challenge of verifying today’s and future autonomous systems; comparisons between today’s machines and autism; implications of human information interaction on artificial intelligence and errors; systems that reason; the autonomy of machines, robots, buildings; and hybrid teams, where hybrid reflects arbitrary combinations of humans, machines and robots. The contributors span the field of autonomous systems research, ranging from industry and academia to government. Given the broad diversity of the research in this book, the editors strove to thoroughly examine the challenges and trends of systems that implement and exhibit AI; the social implications of present and future systems made autonomous with AI; systems with AI seeking to develop trusted relationships among humans, machines, and robots; and the effective human systems integration that must result for trust in these new systems and their applications to increase and to be sustained.

Перейти: https://doi.org/10.1007/978-3-319-59719-5

Дод.точки доступу:
Lawless, W.F. \ed.\; Mittu, Ranjeev. \ed.\; Sofge, Donald. \ed.\; Russell, Stephen. \ed.\; SpringerLink (Online service)
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8.


    Kubat, Miroslav.
    An Introduction to Machine Learning [[electronic resource] /] : монография / Miroslav. Kubat ; . - 2nd ed. 2017. - [S. l. : s. n.]. - XIII, 348 p. 85 illus., 3 illus. in color. - Б. ц.
    Зміст:
1 A Simple Machine-Learning Task --
2 Probabilities: Bayesian Classifiers --
Similarities: Nearest-Neighbor Classifiers --
4 Inter-Class Boundaries: Linear and Polynomial Classifiers --
5 Artificial Neural Networks --
6 Decision Trees --
7 Computational Learning Theory --
8 A Few Instructive Applications --
9 Induction of Voting Assemblies --
10 Some Practical Aspects to Know About --
11 Performance Evaluation --
12 Statistical Significance --
13 Induction in Multi-Label Domains --
14 Unsupervised Learning --
15 Classifiers in the Form of Rulesets --
16 The Genetic Algorithm --
17 Reinforcement Learning.
Рубрики: Data mining.
   Artificial intelligence.
   Big data.
   Computational intelligence.
   Data Mining and Knowledge Discovery.
   Artificial Intelligence.
   Big Data/Analytics.
   Computational Intelligence.
Анотація: This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms. This revised edition contains three entirely new chapters on critical topics regarding the pragmatic application of machine learning in industry. The chapters examine multi-label domains, unsupervised learning and its use in deep learning, and logical approaches to induction as well as Inductive Logic Programming. Numerous chapters have been expanded, and the presentation of the material has been enhanced. The book contains many new exercises, numerous solved examples, thought-provoking experiments, and computer assignments for independent work.

Перейти: https://doi.org/10.1007/978-3-319-63913-0

Дод.точки доступу:
Kubat, Miroslav. \.\; SpringerLink (Online service)
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9.


    Urbanowicz, Ryan J.
    Introduction to Learning Classifier Systems [[electronic resource] /] : монография / Ryan J. Urbanowicz, Browne, Will N. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIII, 123 p. 27 illus., 4 illus. in color. - Б. ц.
    Зміст:
LCSs in a Nutshell --
LCS Concepts --
Functional Cycle Components --
LCS Adaptability --
Applying LCSs.
Рубрики: Artificial intelligence.
   Computational intelligence.
   Mathematical optimization.
   Bioinformatics.
   Control engineering.
   Robotics.
   Mechatronics.
   Computers.
   Artificial Intelligence.
   Computational Intelligence.
   Optimization.
   Computational Biology/Bioinformatics.
   Control, Robotics, Mechatronics.
   Theory of Computation.
Анотація: This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, and then walk through the components of LCS that form this rule-based evolutionary algorithm. The applicability and adaptability of these methods is highlighted by providing descriptions of common methodological alternatives for different components that are suited to different types of problems from data mining to autonomous robotics. The authors have also paired exercises and a simple educational LCS (eLCS) algorithm (implemented in Python) with this book. It is suitable for courses or self-study by advanced undergraduate and postgraduate students in subjects such as Computer Science, Engineering, Bioinformatics, and Cybernetics, and by researchers, data analysts, and machine learning practitioners.

Перейти: https://doi.org/10.1007/978-3-662-55007-6

Дод.точки доступу:
Browne, Will N.; Urbanowicz, Ryan J. \.\; SpringerLink (Online service)
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10.


   
    Game Dynamics [[electronic resource] :] : best Practices in Procedural and Dynamic Game Content Generation / / ed.: Korn, Oliver., Lee, Newton. - 1st ed. 2017. - [S. l. : s. n.]. - X, 177 p. 92 illus., 77 illus. in color. - Б. ц.
    Зміст:
Introduction --
A Very Short History of Dynamic and Procedural Content Generation --
Procedural Content Generation in the Game Industry --
Design, Dynamics, Experience (DDE): An Advancement of the MDA Framework for Game Design --
Procedural Synthesis of Gunshot Sounds based on Physically Motivated Models --
Dynamics Player Pairing: Quantifying the Effects of Competitive vs. Cooperative Attitudes --
FaceMaker: A Procedural Face Generator to Foster Character Design Research --
A Primer on Procedural Character Generation for Games and Real Time Applications --
Procedural Terrain Generation: A Case Study from the Game Industry --
Procedural Adventure Generation: The Quest of Meeting Shifting Design Goals with Flexible Algorithms.
Рубрики: User interfaces (Computer systems).
   Computational intelligence.
   Application software.
   User Interfaces and Human Computer Interaction.
   Computational Intelligence.
   Computer Appl. in Arts and Humanities.
Анотація: This book offers a compendium of best practices in game dynamics. It covers a wide range of dynamic game elements ranging from player behavior over artificial intelligence to procedural content generation. Such dynamics make virtual worlds more lively and realistic and they also create the potential for moments of amazement and surprise. In many cases, game dynamics are driven by a combination of random seeds, player records and procedural algorithms. Games can even incorporate the player’s real-world behavior to create dynamic responses. The best practices illustrate how dynamic elements improve the user experience and increase the replay value. The book draws upon interdisciplinary approaches; researchers and practitioners from Game Studies, Computer Science, Human-Computer Interaction, Psychology and other disciplines will find this book to be an exceptional resource of both creative inspiration and hands-on process knowledge.

Перейти: https://doi.org/10.1007/978-3-319-53088-8

Дод.точки доступу:
Korn, Oliver. \ed.\; Lee, Newton. \ed.\; SpringerLink (Online service)
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11.


   
    Brain-Computer Interface Research [[electronic resource] :] : a State-of-the-Art Summary 5 / / ed.: Guger, Christoph., Allison, Brendan., Ushiba, Junichi. - 1st ed. 2017. - [S. l. : s. n.]. - VI, 136 p. 43 illus., 40 illus. in color. - Б. ц.
    Зміст:
Introduction (C. Guger at al.) --
An ECoG-Based BCI Based on Auditory Attention to Natural Speech (P. Brunner et al.) --
Motor Imagery BCI with Auditory Feedback as a Mechanism for Assessment and Communication in Disorders of Consciousness (D. Coyle et al.) --
Towards Continuous Speech Recognition for BCI (C. Herff et al.) --
Recovery of Brain Function by Neuroprostheses: A Challenge for Neuroscience and Technology (R. Hogri et al.) --
Estimation of Intracranial P300 Speller Sites with Magnetoencephalography (MEG) - perspectives for Non-invasive Navigation of Subdural Grid Implantation (M. Korostenskaja et al.) --
Brain-Machine Interface Development for Finger Movement Control (T.M. Lal et al.) --
Brain-Computer Interface Controlling Cyborg: A Functional Brain-to-Brain Interface between Human and Cockroach (G. Li et al.) --
A Brain-Computer-Interface to Combat Musculoskeletal Pain (N. Mrachacz-Kersting et al.) --
BCI-based Facilitation of Cortical Activity Associated to Gait Onset after Single Event Multi-Level Surgery in Cerebral Palsy (J.I. Serrano et al.) --
Conclusion (C. Guger et al.).
Рубрики: User interfaces (Computer systems).
   Neurosciences.
   Medical physics.
   Radiation.
   Computational intelligence.
   User Interfaces and Human Computer Interaction.
   Neurosciences.
   Medical and Radiation Physics.
   Computational Intelligence.
Анотація: This book describes the prize-winning brain-computer-interface (BCI) projects honored in the community's most prestigious annual award. BCIs enable people to communicate and control their limbs and/or environment using thought processes alone. Research in this field continues to develop and expand rapidly, with many new ideas, research groups, and improved technologies having emerged in recent years. The chapters in this volume feature the newest developments from many of the best labs worldwide. They present both non-invasive systems (based on the EEG) and intracortical methods (based on spikes or ECoG), and numerous innovative applications that will benefit new user groups.

Перейти: https://doi.org/10.1007/978-3-319-57132-4

Дод.точки доступу:
Guger, Christoph. \ed.\; Allison, Brendan. \ed.\; Ushiba, Junichi. \ed.\; SpringerLink (Online service)
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12.


   
    Engineering Applications of Neural Networks [[electronic resource] :] : 18th International Conference, EANN 2017, Athens, Greece, August 25–27, 2017, Proceedings / / ed. Boracchi, Giacomo. [et al.]. - 1st ed. 2017. - [S. l. : s. n.]. - XIX, 737 p. 225 illus. - Б. ц.
    Зміст:
ANN in engineering applications --
Classification pattern recognition --
Deep learning convolutional ANN --
Deep learning image analysis --
Fuzzy - neuro fuzzy --
Learning generalization --
Learning in financial applications --
Medical AI applications --
Optimization data mining --
Recommendation systems --
Robotics and machine vision --
MHDW2017 --
5GPINE2017.
Рубрики: Artificial intelligence.
   Data mining.
   Optical data processing.
   Application software.
   Computational intelligence.
   Computers.
   Law and legislation.
   Artificial Intelligence.
   Data Mining and Knowledge Discovery.
   Computer Imaging, Vision, Pattern Recognition and Graphics.
   Computer Applications.
   Computational Intelligence.
   Legal Aspects of Computing.
Анотація: This book constitutes the refereed proceedings of the 18th International Conference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes papers presented at the 6th Mining Humanistic Data Workshop (MHDW 2017) and the 2nd Workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE).

Перейти: https://doi.org/10.1007/978-3-319-65172-9

Дод.точки доступу:
Boracchi, Giacomo. \ed.\; Iliadis, Lazaros. \ed.\; Jayne, Chrisina. \ed.\; Likas, Aristidis. \ed.\; SpringerLink (Online service)
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13.


    Gupta, P. K.
    Predictive Computing and Information Security [[electronic resource] /] : монография / P. K. Gupta, Tyagi, Vipin., Singh, S.K. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXI, 162 p. 57 illus. - Б. ц.
    Зміст:
Introduction --
Predictive Computing and Information Security: A Technical Review --
Predictive Computing --
Cloud Based Predictive Computing --
IoT based Predictive Computing --
Information Security --
Cloud Based Information Security --
IoT Based Information Security --
Applications of Predictive Computing --
Appendix.
Рубрики: Computer security.
   Data structures (Computer science).
   Data mining.
   Application software.
   Computational intelligence.
   Information storage and retrieval.
   Systems and Data Security.
   Data Structures and Information Theory.
   Data Mining and Knowledge Discovery.
   Information Systems Applications (incl. Internet).
   Computational Intelligence.
   Information Storage and Retrieval.
Анотація: This book describes various methods and recent advances in predictive computing and information security. It highlights various predictive application scenarios to discuss these breakthroughs in real-world settings. Further, it addresses state-of-art techniques and the design, development and innovative use of technologies for enhancing predictive computing and information security.   Coverage also includes the frameworks for eTransportation and eHealth, security techniques, and algorithms for predictive computing and information security based on Internet-of-Things and Cloud computing. As such, the book offers a valuable resource for graduate students and researchers interested in exploring predictive modeling techniques and architectures to solve information security, privacy and protection issues in future communication.

Перейти: https://doi.org/10.1007/978-981-10-5107-4

Дод.точки доступу:
Tyagi, Vipin.; Singh, S.K.; Gupta, P.K. \.\; SpringerLink (Online service)
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14.


    Liao, Wenhe.
    Subdivision Surface Modeling Technology [[electronic resource] /] : монография / Wenhe. Liao, Liu, Hao., Li, Tao. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XVI, 307 p. 193 illus. - Б. ц.
    Зміст:
Introduction --
Splines and Subdivision --
Meshes and Subdivision --
Analysis of Subdivision Surface --
n-sided Patches and Subdivision Surfaces --
Energy Optimization Method and Subdivision Surfaces --
Interactive Shape Editing for Subdivision Surfaces --
Intersection and trimming of subdivision surfaces --
Subdivision Surfaces and Curve Networks --
Fitting Unstructured Triangle Meshes --
Subdivision Surfaces Based Poisson Mesh Edit.
Рубрики: Computer simulation.
   Geometry.
   Computer-aided engineering.
   Computational intelligence.
   Mathematics.
   Visualization.
   Discrete mathematics.
   Simulation and Modeling.
   Geometry.
   Computer-Aided Engineering (CAD, CAE) and Design.
   Computational Intelligence.
   Visualization.
   Discrete Mathematics.
Анотація: This book offers a comprehensive introduction to Subdivision Surface Modeling Technology focusing not only on fundamental theories but also on practical applications. It furthers readers’ understanding of the contacts between spline surfaces and subdivision surfaces, enabling them to master the Subdivision Surface Modeling Technology for analyzing subdivision surfaces. Subdivision surface modeling is a popular technology in the field of computer aided design (CAD) and computer graphics (CG) thanks to its ability to model meshes of any topology. The book also discusses some typical Subdivision Surface Modeling Technologies, such as interpolation, fitting, fairing, intersection, as well as trimming and interactive editing. It is a valuable tool, enabling readers to grasp the main technologies of subdivision surface modeling and use them in software development, which in turn leads to a better understanding of CAD/CG software operations.

Перейти: https://doi.org/10.1007/978-981-10-3515-9

Дод.точки доступу:
Liu, Hao.; Li, Tao.; Liao, Wenhe. \.\; SpringerLink (Online service)
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15.


   
    Representation and Reality in Humans, Other Living Organisms and Intelligent Machines [[electronic resource] /] : монография / ed.: Dodig-Crnkovic, Gordana., Giovagnoli, Raffaela. - 1st ed. 2017. - [S. l. : s. n.]. - XVI, 378 p. 48 illus., 28 illus. in color. - Б. ц.
    Зміст:
Life Versus Engineering --
Representation in Signal Processing in Biological Systems --
The Realism of Human and Machine Cognitive Ontologies --
Visual Representations for Object Recognition --
Semantic Information Content and Measure in Cognitive Sciences --
Reality Construction in Cognitive Agent Through Infocomputation --
Modelling Empty Representations --
Cognition, Information and Subjective Computation --
Information Integration --
The Social Dimension of Human Representation --
Mind and Machine --
Exploiting Body Morphology for Control --
A Logic for Ontologies and Semantic Search Engines --
Models, Maps and Metaphors --
Matter, Representation and Motion in the Phenomenology of the Mind --
Enactive Criticisms of Infocomputationalism --
Rationality and Representation.
Рубрики: Artificial intelligence.
   Philosophy and science.
   Computational intelligence.
   Artificial Intelligence.
   Philosophy of Science.
   Computational Intelligence.
Анотація: This book enriches our views on representation and deepens our understanding of its different aspects. It arises out of several years of dialog between the editors and the authors, an interdisciplinary team of highly experienced researchers, and it reflects the best contemporary view of representation and reality in humans, other living beings, and intelligent machines. Structured into parts on the cognitive, computational, natural sciences, philosophical, logical, and machine perspectives, a theme of the field and the book is building and presenting networks, and the editors hope that the contributed chapters will spur understanding and collaboration between researchers in domains such as computer science, philosophy, logic, systems theory, engineering, psychology, sociology, anthropology, neuroscience, linguistics, and synthetic biology.

Перейти: https://doi.org/10.1007/978-3-319-43784-2

Дод.точки доступу:
Dodig-Crnkovic, Gordana. \ed.\; Giovagnoli, Raffaela. \ed.\; SpringerLink (Online service)
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16.


   
    Transactions on Computational Collective Intelligence XXVII [[electronic resource] /] : монография / ed. Mercik, Jacek. - 1st ed. 2017. - [S. l. : s. n.]. - XII, 209 p. 36 illus. - Б. ц.
    Зміст:
Kalai-Smorodinsky Balances for n-Tuples of Interfering Elements --
Reason vs. Rationality: From Rankings to Tournaments in Individual Choice --
A Note on Positions and Power of Players in Multicameral Voting Games --
On Ordering a Set of Degressively Proportional Apportionments --
Preorders in Simple Games --
Sub-coalitional approach to values --
The Effect of Brexit on the Balance of Power in the European Union Council: An Approach Based on Pre-coalitions --
Comparison of voting methods used in some classical music competitions --
Determinants of the perception of opportunity --
Free-riding in Common Facility Sharing --
Simulating Crowd Evacuation with Socio-Cultural, Cognitive, and Emotional Elements --
Group Approximation of Task Duration and Time Buffers in Scrum --
Inspirations.
Рубрики: Artificial intelligence.
   Computational intelligence.
   Software engineering.
   Computers.
   Computer simulation.
   Artificial Intelligence.
   Computational Intelligence.
   Software Engineering.
   Computation by Abstract Devices.
   Simulation and Modeling.
   Information Systems and Communication Service.
Анотація: These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-seventh issue is a special issue with 13 selected papers from the Second Seminar on Quantitative Methods of Group Decision Making.

Перейти: https://doi.org/10.1007/978-3-319-70647-4

Дод.точки доступу:
Mercik, Jacek. \ed.\; SpringerLink (Online service)
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17.


   
    Probabilistic Prognostics and Health Management of Energy Systems [[electronic resource] /] : монография / ed.: Ekwaro-Osire, Stephen., Goncalves, Aparecido Carlos., Alemayehu, Fisseha M. - 1st ed. 2017. - [S. l. : s. n.]. - X, 277 p. 121 illus. - Б. ц.
    Зміст:
Part I: Trends and Applications --
Chapter 1. Probabilistic Prognostics and Health Management: A Brief Summary --
Chapter 2. Introduction to Data-driven Methodologies for Prognostics and Health Management --
Chapter 3. Prognostics and Health Management of Wind Turbines – Current Status and Future Opportunities --
Chapter 4. Overview on Gear Health Prognostics --
Chapter 5. Probabilistic Model-Based Prognostics Using Meshfree Modeling --
Chapter 6. Cognitive Architectures for Prognostic Health Management --
Part II Modeling and Uncertainty Quantification --
Chapter 7. A Review of Crack Propagation Modeling using Peridynamics --
Chapter 8. Modeling and Quantification of Physical Systems Uncertainties in a Probabilistic Framework --
Chapter 9. Towards a More Robust Understanding of the Uncertainty of Wind Farm Reliability --
Chapter 10. Data Analysis in Python: Anonymized Features and Imbalanced Data Target --
Chapter 11. The Use of Trend Lines Channels and Remaining Useful Life Prediction. Chapter --
12. The Derivative as a Probabilistic Synthesis of Past and Future Data and Remaining Useful Life Prediction --
Part III Condition Monitoring --
Chapter 13. Monitoring and Fault Identification in Aeronautical Structures Using an Wavelet-Artificial Immune System Algorithm --
Chapter 14. An Illustration of Some Methods to Detect Faults in Geared Systems using a Simple Model of Two Meshed Gears --
Chapter 15. Condition Monitoring of Structures under Non-Ideal Excitation using Low Cost Equipment --
Chapter 16. Maintenance Management and Case Studies in the Luis Carlos Prestes Thermoelectric Power Plant --
Chapter 17. Stiffness Nonlinearity in Structural Dynamics: Our Friend or Enemy?.
Рубрики: Energy systems.
   Quality control.
   Reliability.
   Industrial safety.
   Computational intelligence.
   Probabilities.
   Thermodynamics.
   Heat engineering.
   Heat transfer.
   Mass transfer.
   Energy Systems.
   Quality Control, Reliability, Safety and Risk.
   Computational Intelligence.
   Probability Theory and Stochastic Processes.
   Engineering Thermodynamics, Heat and Mass Transfer.
Анотація: This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty. Renewable and non-renewable sources of energy are being used to supply the demands of societies worldwide. These sources are mainly thermo-chemo-electro-mechanical systems that are subject to uncertainty in future loading conditions, material properties, process noise, and other design parameters.It book informs the reader of existing and new ideas that will be implemented in RUL prediction of energy systems in the future. The book provides case studies, illustrations, graphs, and charts. Its chapters consider engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics.

Перейти: https://doi.org/10.1007/978-3-319-55852-3

Дод.точки доступу:
Ekwaro-Osire, Stephen. \ed.\; Goncalves, Aparecido Carlos. \ed.\; Alemayehu, Fisseha M. \ed.\; SpringerLink (Online service)
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18.


    Khamehchi, Ehsan.
    Gas Allocation Optimization Methods in Artificial Gas Lift [[electronic resource] /] : монография / Ehsan. Khamehchi, Mahdiani, Mohammad Reza. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XII, 46 p. 21 illus. - Б. ц.
    Зміст:
1. Introduction --
2. The Fitness Function of Gas Allocation Optimization --
3. Constraint Optimization --
4. Optimization Algorithms.
Рубрики: Fossil fuels.
   Geophysics.
   Geotechnical engineering.
   Computational intelligence.
   Fossil Fuels (incl. Carbon Capture).
   Geophysics/Geodesy.
   Geotechnical Engineering & Applied Earth Sciences.
   Computational Intelligence.
Анотація: This Brief offers a comprehensive study covering the different aspects of gas allocation optimization in petroleum engineering. It contains different methods of defining the fitness function, dealing with constraints and selecting the optimizer; in each chapter a detailed literature review is included which covers older and important studies as well as recent publications. This book will be of use for production engineers and students interested in gas lift optimization.

Перейти: https://doi.org/10.1007/978-3-319-51451-2

Дод.точки доступу:
Mahdiani, Mohammad Reza.; Khamehchi, Ehsan. \.\; SpringerLink (Online service)
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19.


   
    Recent Contributions in Intelligent Systems [[electronic resource] /] : монография / ed. Sgurev, Vassil. [et al.]. - 1st ed. 2017. - [S. l. : s. n.]. - X, 390 p. 92 illus., 23 illus. in color. - Б. ц.
    Зміст:
Low-Level Image Processing Based on Interval-Valued Fuzzy Sets and Scale-Space Smoothing --
Generalized Net Representation of Dataflow Process Networks --
Wireless Sensor Positioning ACO Algorithm --
Time Accounting Artificial Neural Networks for Biochemical Process Models --
Periodic Time-varying Observer-based Learning Control of A/F Ratio in Multi-cylinder IC Engines --
Fuzzy T-S Model Based Design of Min-Max Control for Uncertain Nonlinear Systems --
Modeling Parallel Optimization of the Early Stopping Method of Multilayer Perceptron --
Intelligent Controls for Switched Fuzzy Systems: Synthesis via Non-standard Lyapunov Functions --
A New Architecture for an Adaptive Switching Controller Based on Hybrid Multiple T-S Models --
Optimization of Linear Objective Function under min-Probabilistic Sum Fuzzy Linear Equations Constraint --
Intuitionistic Fuzzy Logic Implementation to Assess Purposeful Model Parameters Genesis --
Dynamic Representation and Interpretation in a Multiagent 3D Tutoring System --
Generalized Net Model of the Scapulohumeral Rhythm --
Method for Interpretation of Functions of Propositional Logic by Specific Binary Markov Processes --
Generalized Net Models of Academic Promotion and Doctoral Candidature --
Modeling Telehealth Services with Generalized Nets --
State-Space Fuzzy-Neural Predictive Control --
Free Search and Particle Swarm Optimisation Applied to Global Optimisation Numerical Tests From Two to Hundred Dimensions.-Intuitionistic Fuzzy Sets Generated by Archimedean Metrics and Ultrametrics.-Production Rule and Network Structure Models for Knowledge Extraction from Complex Processes Under Uncertainty.
Рубрики: Computational intelligence.
   Artificial intelligence.
   Computational Intelligence.
   Artificial Intelligence.
Анотація: This volume is a brief, yet comprehensive account of new development, tools, techniques and solutions in the broadly perceived “intelligent systems”. New concepts and ideas concern the development of effective and efficient models which would make it possible to effectively and efficiently describe and solve processes in various areas of science and technology. Special emphasis is on the dealing with uncertainty and imprecision that permeates virtually all real world processes and phenomena, and has to properly be modeled by formal and algorithmic tools and techniques so that they be adequate and useful. The papers in this volume concern a wide array of possible techniques exemplified by, on the one hand, logic, probabilistic, fuzzy, intuitionistic fuzzy, neuro-fuzzy, etc. approaches. On the other hand, they represent the use of such systems modeling tools as generalized nets, optimization and control models, systems analytic models, etc. They concerns a variety of approaches, from pattern recognition, image analysis, education system modeling, biological and medical systems modeling, etc.

Перейти: https://doi.org/10.1007/978-3-319-41438-6

Дод.точки доступу:
Sgurev, Vassil. \ed.\; Yager, Ronald R. \ed.\; Kacprzyk, Janusz. \ed.\; Atanassov, Krassimir T. \ed.\; SpringerLink (Online service)
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20.


   
    Recent Developments in Intelligent Systems and Interactive Applications [[electronic resource] :] : proceedings of the International Conference on Intelligent and Interactive Systems and Applications (IISA2016) / / ed.: Xhafa, Fatos., Patnaik, Srikanta., Yu, Zhengtao. - 1st ed. 2017. - [S. l. : s. n.]. - XVI, 469 p. 225 illus. - Б. ц.
    Зміст:
Testing Paper Optimization Based on Improved Particle Swarm Optimization --
The Null Space Pursuit Algorithm Based on an Arbitrary Order Differential Operator --
An Iterative Method for the Least Squares Anti-bisymmetric Solution of the Matrix Equation --
A Label-Correlated Multi-Label Classification Algorithm Based on Spearman Rank Correlation Coefficient --
Research on Static Performance of Water-Lubricated Hybrid Bearing with Constant Flow Supply --
A Case-based Reasoning Method with Relative Entropy and TOPSIS Integration --
Research of Chemical Fabric Style Prediction System Based on Integrated Neural Network --
A Novel Session Identification Scheme with Tabbed Browsing --
Research into Information Security Strategy Practices for Commercial Banks in Taiwan --
An Improved Virtualization Resource Migration Strategy and Its Application in Data Center --
Null Space Diversity Fisher Discriminant Analysis for Face Recognition --
Automatic Color Detection of Grape Based on Vision Computing Method --
A Novel Design of Sharp MDFT Filter Banks With Low Complexity based on DPSO-MFO algorithm --
Information navigation system of pulse radar employing augmented reality. .
Рубрики: Computational intelligence.
   Artificial intelligence.
   Computational Intelligence.
   Artificial Intelligence.
Анотація: This book provides the latest research findings and developments in the field of interactive intelligent systems, addressing diverse areas such as autonomous systems, Internet and cloud computing, pattern recognition and vision systems, mobile computing and intelligent networking, and e-enabled systems. It gathers selected papers from the International Conference on Intelligent and Interactive Systems and Applications (IISA2016) held on June 25–26, 2016 in Shanghai, China. Interactive intelligent systems are among the most important multi-disciplinary research and development domains of artificial intelligence, human–computer interaction, machine learning and new Internet-based technologies. Accordingly, these systems embrace a considerable number of application areas such as autonomous systems, expert systems, mobile systems, recommender systems, knowledge-based and semantic web-based systems, virtual communication environments, and decision support systems, to name a few. To date, research on interactive intelligent systems has largely focused either on the realisation of the systems’ capabilities or on the cognitive processes and/or behaviour of their users. With the rapid development of Internet-based technologies, the design of interactive intelligent systems is facing many emerging issues and challenges such as investigating the ways that artificial agents and human intelligence can collaborate for better performance, understanding user requirements and user cognitive processes, safeguarding user privacy, etc. .

Перейти: https://doi.org/10.1007/978-3-319-49568-2

Дод.точки доступу:
Xhafa, Fatos. \ed.\; Patnaik, Srikanta. \ed.\; Yu, Zhengtao. \ed.\; SpringerLink (Online service)
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