One of the activities of the University Curricula Subcommittee of the Computational Intelligence Society's Education Committee is maintaining a world-wide directory of courses in computational intelligence.
This directory is now available as a searchable online database, at http://ucs.ais.ac.nz/
This is a prototype of a system where educators can submit details of their courses, search existing courses, and engage in discussions with other educators about the listed courses. Anyone may access and search the database, although users must register to submit new courses or leave comments.
This system was developed as a student project by the following students:
The project was supervised by Mike Watts. Mike is the Head of the Information Technology Programme at Auckland Institute of Studies, who are kindly hosting the system.
News and announcements from the IEEE Computational Intelligence Society
Friday, 19 December 2014
Monday, 8 December 2014
CEMiSG 2015 2nd International Workshop on Computational Energy Management in Smart Grids 12-17 July 2015, Killarney, Ireland
Scope
The exploitation of natural resources by the increasing world population represents an urgent issue to face for humanity. Electrical Energy represents a relevant example from this perspective and the strong demand coming from developed and developing countries shoved the scientists worldwide to intensify their studies on renewable energy resources, especially in the last two decades. At the same time, we have also registered a remarkable increment of the complexity of the electrical grid at diverse levels in order to include variegated and distributed generation and storage sites.As a consequence of these aspects, a growing interest has been oriented in the last few years to the development of smart systems able to optimally manage the usage and the distribution of energy among the population with the objective of minimizing wasting and the economic impact, considering the different needs of the heterogeneous grid costumers and the different peculiarities of energy sources. Several ways of intervention are feasible, as the ones indicated in the US Energy Independence and Security Act of 2007.
This motivated the recent spread of advanced technological solutions developed with the objective to introduce intelligence within the energy grid, both at academic and commercial levels. However, the social relevance of the topic makes the need of deepening the studies and providing more and more performing solutions always lively, thus asking for a constant multidisciplinary coordinated action to the scientific communities operating in the Electrical and Electronic Engineering, Computational Intelligence, Digital Signal Processing and Communications research fields.
Narrowing the focus to the interests of our scientific community, the organizers of this Workshop, as inside the IJCNN2015 conference, wants to explore the new frontiers and challenges within the Computational Intelligence research area for the optimal usage and management of energy resources in Smart Grid applicative scenarios.
Topics
- Computational Intelligence for Smart Grids
- Neural Networks based algorithms for Complex Energy Systems
- Deep Learning strategies for Energy Efficiency
- Soft Computing based Algorithms in Energy Applications
- Learning Systems for Smart Grid Optimization
- Learning-based Control of Renewable Energy Generators
- Fast Optimization at diverse Grid levels
- Smart Home Energy Management
- Energy Resource Allocation and Task Scheduling
- Building Energy Consumption Forecasting
- Demand-side Management
- Short-term Load Forecasting
- Neural Networks for Time Series Prediction in Smart Grids
- Non-Intrusive Load Monitoring
- Hybrid Battery Management
Organizers
Stefano SquartiniUniversità Politecnica delle Marche, Italy
s.squartini@univpm.it
Derong Liu
Chinese Academy of Sciences, China
derongliu@gmail.com
www.cemisg2015.org
Francesco Piazza
Università Politecnica delle Marche, Italy
f.piazza@univpm.it
Dongbin Zhao
Chinese Academy of Sciences, China
dongbin.zhao@ia.ac.cn
Haibo He
University of Rhode Island, USA
he@ele.uri.edu
Technical Program Committee
- Giacomo Boracchi, Italy
- Nelson Kagan, Brazil
- Paul Kaufmann, Germany
- Elias Kyriadikes, Cyprus
- Andrew Kusiak, USA
- Ginaluca Ippoliti Italy
- Chengdong Li, China
- Kang Li, UK
- Danilo Mandic, UK
- Stephen Matthews, UK
- Salman Mohagheghi, USA
- Hugo Morais, France
- Peter Palensky, Austria
- Dianwei Qian, China
- Wei Qiao, USA
- Marco Raugi, Italy
- Pierluigi Siano, Italy
- Gerard Smit, Netherlands
- Dipti Srinivasan, Singapore
- Kumar Venayagamoorthy, USA
- Markus Wagner, Australia
- Qinglai Wei, China
Submission Guidelines
Prospective authors are invited to submit papers according to the IEEE format. All submissions should be according to the specifications of IJCNN2015. Accepted contributions will be part of the IJCNN2015 conference proceedings.Important Dates
- 15th January 2015: Due date for paper submission
- 15th March 2015: Notification to authors
- 15th April 2016: Camera-ready deadline for accepted papers
- 12th - 17th July 2014: Workshop Days
Sunday, 7 December 2014
IEEE Transactions on Evolutionary Computation Volume 18, Number 6, December 2014
1. Parameter Optimization Algorithms for Evolving Rule Models Applied to Freshwater Ecosystems
Author(s): Cao, H. ; Recknagel, F. ; Orr, P.T.
Page(s): 793 - 806
2. An Analysis of $N!K$ Landscapes: Interaction Structure, Statistical Properties, and Expected Number of Local Optima
Author(s): Buzas, J. ; Dinitz, J.
Page(s): 807 - 818
3. The Effect of Memory Size on the Evolutionary Stability of Strategies in Iterated Prisoner's Dilemma
Author(s): Li, J. ; Kendall, G.
Page(s): 819 - 826
4. An Evolutionary Multiobjective Approach to Sparse Reconstruction
Author(s): Li, L. ; Yao, X. ; Stolkin, R. ; Gong, M. ; He, S.
Page(s): 827 - 845
5. A New Memetic Algorithm With Fitness Approximation for the Defect-Tolerant Logic Mapping in Crossbar-Based Nanoarchitectures
Author(s): Yuan, B. ; Li, B. ; Weise, T. ; Yao, X.
Page(s): 846 - 859
6. Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Author(s): Lai, X. ; Zhou, Y. ; He, J. ; Zhang, J.
Page(s): 860 - 872
7. Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets
Author(s): Barros, R.C. ; Basgalupp, M.P. ; Freitas, A.A. ; de Carvalho, A.C.P.L.F.
Page(s): 873 - 892
8. Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data
Author(s): Bhowan, U. ; Johnston, M. ; Zhang, M. ; Yao, X.
Page(s): 893 - 908
9. Stable Matching-Based Selection in Evolutionary Multiobjective Optimization
Author(s): Li, K. ; Zhang, Q. ; Kwong, S. ; Li, M. ; Wang, R.
Page(s): 909 - 923
Author(s): Cao, H. ; Recknagel, F. ; Orr, P.T.
Page(s): 793 - 806
2. An Analysis of $N!K$ Landscapes: Interaction Structure, Statistical Properties, and Expected Number of Local Optima
Author(s): Buzas, J. ; Dinitz, J.
Page(s): 807 - 818
3. The Effect of Memory Size on the Evolutionary Stability of Strategies in Iterated Prisoner's Dilemma
Author(s): Li, J. ; Kendall, G.
Page(s): 819 - 826
4. An Evolutionary Multiobjective Approach to Sparse Reconstruction
Author(s): Li, L. ; Yao, X. ; Stolkin, R. ; Gong, M. ; He, S.
Page(s): 827 - 845
5. A New Memetic Algorithm With Fitness Approximation for the Defect-Tolerant Logic Mapping in Crossbar-Based Nanoarchitectures
Author(s): Yuan, B. ; Li, B. ; Weise, T. ; Yao, X.
Page(s): 846 - 859
6. Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Author(s): Lai, X. ; Zhou, Y. ; He, J. ; Zhang, J.
Page(s): 860 - 872
7. Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets
Author(s): Barros, R.C. ; Basgalupp, M.P. ; Freitas, A.A. ; de Carvalho, A.C.P.L.F.
Page(s): 873 - 892
8. Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data
Author(s): Bhowan, U. ; Johnston, M. ; Zhang, M. ; Yao, X.
Page(s): 893 - 908
9. Stable Matching-Based Selection in Evolutionary Multiobjective Optimization
Author(s): Li, K. ; Zhang, Q. ; Kwong, S. ; Li, M. ; Wang, R.
Page(s): 909 - 923
Saturday, 6 December 2014
IEEE Transactions on Fuzzy Systems, Volume 22, Number 6, December 2014
1. The
Bounded Capacity of Fuzzy Neural Networks (FNNs) Via a New Fully
Connected Neural Fuzzy Inference System (F-CONFIS) With Its Applications
Author(s): Wang, J. ; Wang, C.-H. ; Chen, C.L.P.
Page(s): 1373 - 1386
2. Joint Block Structure Sparse Representation for Multi-Input–Multi-Output (MIMO) T–S Fuzzy System Identification
Author(s): Luo, M. ; Sun, F. ; Liu, H.
Page(s): 1387 - 1400
3. Robust $L_{bm infty}$-Gain Fuzzy Disturbance Observer-Based Control Design With Adaptive Bounding for a Hypersonic Vehicle
Author(s): Wu, H.-N. ; Liu, Z.-Y. ; Guo, L.
Page(s): 1401 - 1412
4. A Novel Model-Based Controller for Polymer Extrusion
Author(s): Abeykoon, C.
Page(s): 1413 - 1430
5. Logic Connectives for Soft Sets and Fuzzy Soft Sets
Author(s): Ali, M.I. ; Shabir, M.
Page(s): 1431 - 1442
6. A Collaborative Fuzzy Clustering Algorithm in Distributed Network Environments
Author(s): Zhou, J. ; Philip Chen, C.L. ; Chen, L. ; Li, H.-X.
Page(s): 1443 - 1456
7. Multilabel Text Categorization Based on Fuzzy Relevance Clustering
Author(s): Lee, S.-J. ; Jiang, J.-Y.
Page(s): 1457 - 1471
8. Construction of Neurofuzzy Models For Imbalanced Data Classification
Author(s): Gao, M. ; Hong, X. ; Harris, C.J.
Page(s): 1472 - 1488
9. A Banzhaf Function for a Fuzzy Game
Author(s): Tan, C. ; Jiang, Z.-Z. ; Chen, X. ; Ip, W.H.
Page(s): 1489 - 1502
10. Stability Analysis of Switched Fuzzy Systems Via Model Checking
Author(s): Ding, Z. ; Zhou, Y. ; Zhou, M.
Page(s): 1503 - 1514
11. Edge-Detection Method for Image Processing Based on Generalized Type-2 Fuzzy Logic
Author(s): Melin, P. ; Gonzalez, C.I. ; Castro, J.R. ; Mendoza, O. ; Castillo, O.
Page(s): 1515 - 1525
12. Fault Tolerant Controller Design for T–S Fuzzy Systems With Time-Varying Delay and Actuator Faults: A K-Step Fault-Estimation Approach
Author(s): Huang, S.-J. ; Yang, G.-H.
Page(s): 1526 - 1540
13. A Scene Image is Nonmutually Exclusive—A Fuzzy Qualitative Scene Understanding
Author(s): Lim, C.H. ; Risnumawan, A. ; Chan, C.S.
Page(s): 1541 - 1556
14. Incremental Fuzzy Clustering With Multiple Medoids for Large Data
Author(s): Wang, Y. ; Chen, L. ; Mei, J.-P.
Page(s): 1557 - 1568
15. Multipolar Aggregation Operators in Reasoning Methods for Fuzzy Rule-Based Classification Systems
Author(s): Mesiarova-Zemankova, A.
Page(s): 1569 - 1584
16. Cluster-Centric Fuzzy Modeling
Author(s): Pedrycz, W. ; Izakian, H.
Page(s): 1585 - 1597
17. An Intelligent Second-Order Sliding-Mode Control for an Electric Power Steering System Using a Wavelet Fuzzy Neural Network
Author(s): Lin, F.-J. ; Hung, Y.-C. ; Ruan, K.-C.
Page(s): 1598 - 1611
18. Anomaly Detection and Characterization in Spatial Time Series Data: A Cluster-Centric Approach
Author(s): Izakian, H. ; Pedrycz, W.
Page(s): 1612 - 1624
19. Extension of the Fuzzy Integral for General Fuzzy Set-Valued Information
Author(s): Anderson, D.T. ; Havens, T.C. ; Wagner, C. ; Keller, J.M. ; Anderson, M.F. ; Wescott, D.J.
Page(s): 1625 - 1639
20. A Probabilistic Framework for Interval Type-2 Fuzzy Linguistic Summarization
Author(s): Boran, F.E. ; Akay, D. ; Yager, R.R.
Page(s): 1640 - 1653
21. On the Generalized Local Stability and Local Stabilization Conditions for Discrete-Time Takagi–Sugeno Fuzzy Systems
Author(s): Lee, D.H. ; Joo, Y.H.
Page(s): 1654 - 1668
22. Priorities of Intuitionistic Fuzzy Preference Relation Based on Multiplicative Consistency
Author(s): Liao, H. ; Xu, Z.
Page(s): 1669 - 1681
23. Backward Fuzzy Rule Interpolation
Author(s): Jin, S. ; Diao, R. ; Quek, C. ; Shen, Q.
Page(s): 1682 - 1698
Author(s): Wang, J. ; Wang, C.-H. ; Chen, C.L.P.
Page(s): 1373 - 1386
2. Joint Block Structure Sparse Representation for Multi-Input–Multi-Output (MIMO) T–S Fuzzy System Identification
Author(s): Luo, M. ; Sun, F. ; Liu, H.
Page(s): 1387 - 1400
3. Robust $L_{bm infty}$-Gain Fuzzy Disturbance Observer-Based Control Design With Adaptive Bounding for a Hypersonic Vehicle
Author(s): Wu, H.-N. ; Liu, Z.-Y. ; Guo, L.
Page(s): 1401 - 1412
4. A Novel Model-Based Controller for Polymer Extrusion
Author(s): Abeykoon, C.
Page(s): 1413 - 1430
5. Logic Connectives for Soft Sets and Fuzzy Soft Sets
Author(s): Ali, M.I. ; Shabir, M.
Page(s): 1431 - 1442
6. A Collaborative Fuzzy Clustering Algorithm in Distributed Network Environments
Author(s): Zhou, J. ; Philip Chen, C.L. ; Chen, L. ; Li, H.-X.
Page(s): 1443 - 1456
7. Multilabel Text Categorization Based on Fuzzy Relevance Clustering
Author(s): Lee, S.-J. ; Jiang, J.-Y.
Page(s): 1457 - 1471
8. Construction of Neurofuzzy Models For Imbalanced Data Classification
Author(s): Gao, M. ; Hong, X. ; Harris, C.J.
Page(s): 1472 - 1488
9. A Banzhaf Function for a Fuzzy Game
Author(s): Tan, C. ; Jiang, Z.-Z. ; Chen, X. ; Ip, W.H.
Page(s): 1489 - 1502
10. Stability Analysis of Switched Fuzzy Systems Via Model Checking
Author(s): Ding, Z. ; Zhou, Y. ; Zhou, M.
Page(s): 1503 - 1514
11. Edge-Detection Method for Image Processing Based on Generalized Type-2 Fuzzy Logic
Author(s): Melin, P. ; Gonzalez, C.I. ; Castro, J.R. ; Mendoza, O. ; Castillo, O.
Page(s): 1515 - 1525
12. Fault Tolerant Controller Design for T–S Fuzzy Systems With Time-Varying Delay and Actuator Faults: A K-Step Fault-Estimation Approach
Author(s): Huang, S.-J. ; Yang, G.-H.
Page(s): 1526 - 1540
13. A Scene Image is Nonmutually Exclusive—A Fuzzy Qualitative Scene Understanding
Author(s): Lim, C.H. ; Risnumawan, A. ; Chan, C.S.
Page(s): 1541 - 1556
14. Incremental Fuzzy Clustering With Multiple Medoids for Large Data
Author(s): Wang, Y. ; Chen, L. ; Mei, J.-P.
Page(s): 1557 - 1568
15. Multipolar Aggregation Operators in Reasoning Methods for Fuzzy Rule-Based Classification Systems
Author(s): Mesiarova-Zemankova, A.
Page(s): 1569 - 1584
16. Cluster-Centric Fuzzy Modeling
Author(s): Pedrycz, W. ; Izakian, H.
Page(s): 1585 - 1597
17. An Intelligent Second-Order Sliding-Mode Control for an Electric Power Steering System Using a Wavelet Fuzzy Neural Network
Author(s): Lin, F.-J. ; Hung, Y.-C. ; Ruan, K.-C.
Page(s): 1598 - 1611
18. Anomaly Detection and Characterization in Spatial Time Series Data: A Cluster-Centric Approach
Author(s): Izakian, H. ; Pedrycz, W.
Page(s): 1612 - 1624
19. Extension of the Fuzzy Integral for General Fuzzy Set-Valued Information
Author(s): Anderson, D.T. ; Havens, T.C. ; Wagner, C. ; Keller, J.M. ; Anderson, M.F. ; Wescott, D.J.
Page(s): 1625 - 1639
20. A Probabilistic Framework for Interval Type-2 Fuzzy Linguistic Summarization
Author(s): Boran, F.E. ; Akay, D. ; Yager, R.R.
Page(s): 1640 - 1653
21. On the Generalized Local Stability and Local Stabilization Conditions for Discrete-Time Takagi–Sugeno Fuzzy Systems
Author(s): Lee, D.H. ; Joo, Y.H.
Page(s): 1654 - 1668
22. Priorities of Intuitionistic Fuzzy Preference Relation Based on Multiplicative Consistency
Author(s): Liao, H. ; Xu, Z.
Page(s): 1669 - 1681
23. Backward Fuzzy Rule Interpolation
Author(s): Jin, S. ; Diao, R. ; Quek, C. ; Shen, Q.
Page(s): 1682 - 1698
Call for Papers FUZZ-IEEE 2015 Special Session "Linguistic summarization and description of data"
Linguistic summaries and description of data aim to extract and represent knowledge in the form of a collection of natural language sentences. The objective is to obtain a text, as if it was produced by a human expert, describing the most relevant aspects of data for a certain user in a specific context. Automatic generations of data summaries have gained increased relevance with the advent of possibilities to store and acquire data as well as relations between them. In this realm, not only specialized users (e.g. in decision support systems) are interested in this type of approach, but non-specialized users also show interest in receiving understandable information that is supported by data. Linguistic summaries commonly use fuzzy set theory to model linguistic variables and incorporate different forms of imprecision in a collection of natural language sentences. In many approaches they can be considered as quantifier based sentences, hence linguistic summaries constitute a perfect application for new developments in the domain of fuzzy quantifiers. Furthermore, linguistic summaries have been related to fuzzy rule systems. Linguistic summaries and description of data is related to other research areas such as knowledge discovery in databases and intelligent data analysis, flexible query answering systems for data, human-machine interaction, uncertainty management, heuristics and metaheuristics, natural language generation or processing. More recently, this field has been related to different paradigms, namely the linguistic description of complex phenomena and computing with words paradigms. The objective of this special session is to provide a forum for researchers, from the above indicated areas, to present recent developments in linguistic summarizes and description of data as well as discuss how these different approaches can complement each other for the task of building such systems. Topics of interest include, but are not restricted to: Protoforms and fuzzy concepts for the linguistic summaries and fuzzy description. Quality assessment of linguistic summaries and fuzzy description. Techniques and algorithms for generating linguistic summaries and descriptions of data.Ontologies for data summarization. Logical approaches for modeling linguistic expressions. Modeling uncertainty for linguistic summaries and fuzzy description. User preference/interest modeling for linguistic summaries and fuzzy description. Applications of linguistic summaries and fuzzy description. Natural language generation for data summarization. Machine Learning applied to data summarization. Linguistic information extraction from visual information Context-awareness in data summarization and description, and natural language generation.
Anna Wilbik received the Ph.D. degree in computer science from the Systems Research Institute, Polish Academy of Science, Warsaw, Poland, in 2010. She is currently an Assistant Professor with the Information Systems Group of the School of Industrial Engineering at the Eindhoven University of Technology. She is alumnus of TOP500 Innovators: Science - Management – Commercialization Program. In 2011, she was a Post-doctoral Fellow with the Department of Electrical and Computer Engineering, University of Missouri, Columbia, USA. Her research interests include linguistic summaries, data analysis, machine learning, and computational intelligence. He has published about 50 papers in international journals and conferences and was part of organization of a few conferences in the area of IT and computational intelligence.
Rui Jorge Almeida
Rui received his 5 year degree and M.Sc. in Mechanical Engineering both from Instituto Superior Técnico, Universidade de Lisboa, Portugal, in 2005 and 2006 respectively. In 2014 he received is PhD in Econometrics from the Erasmus University of Rotterdam. Since 2013 Rui joined the Information Systems Group of the School of Industrial Engineering at the Eindhoven University of Technology, as an assistant professor. During his PhD, Rui received several grants to perform short term research visits, including an IEEE-CIS Walter Karplus Student Research Grant in 2012 for a short term research visit at Laboratoire d’Informatique de Paris 6, Université Pierre et Marie Curie, France, where he worked on linguistic summaries of patient data to detect medical events. Rui has also been part of the organization of several special sessions, workshops and conferences on international level in the area of financial engineering and soft computing.
Nicolas Marin
Nicolas Marin received the M.S. and Ph.D. degrees in computer science, both from the University of Granada, Spain, in 1998 and 2001, respectively. Since 2005 he is Associate Professor at the Department of Computer Science and Artificial intelligence of the University of Granada. He has participated in the teams of ten research projects, including a project in the area of Linguistic Description of Data that he has led. He has published about 100 papers in international journals and conferences. He has co-edited several special issues in the area of Intelligent Databases and Information Systems and LinguisticDescription of Data and organized several special sessions on these topics in national and international conferences, and has been advisor of three Ph.D. Thesis in these fields.
Daniel Sanchez
Daniel Sanchez received the M.S. and Ph.D. degrees in computer science, both from the University of Granada, Spain, in 1995 and 1999, respectively. Since 2001 he is Associate Professor at the Department of Computer Science and Artificial intelligence of the University of Granada. He has participated in the teams of more than ten research projects, including a national project in the area of Linguistic Description of Visual Information that he has led. He has published more than 100 papers in international journals and conferences, 32 of them in indexed journals (SCI-JCR). He has co-edited an special issue in the International Journal of Intelligent Systems (IJIS) about “Fuzzy Bags, Cardinality, and Quantification”. He has organized several workshops and special sessions about Soft Computing and Applications in Data Mining and Computer Vision in national and international conferences, and has been advisor of five Ph.D. Thesis in these fields. He is currently one of the coordinators of the DAMI Working group on Data Mining and Machine Learning of EUSFLAT (European Society for Fuzzy Logic and Technology).
Information Systems, School of Industrial Engineering,
Eindhoven University of Technology
e-mail: a.m.wilbik@tue.nl
Rui Jorge Almeida
Information Systems, School of Industrial Engineering,
Eindhoven University of Technology
e-mail: rjalmeida@tue.nl
Daniel Sánchez
Department of Computer Science and Artificial Intelligence,
University of Granada
e-mail: daniel@decsai.ugr.es
Nicolás Marín Ruiz
Department of Computer Science and Artificial Intelligence,
University of Granada
e-mail: nicm@decsai.ugr.es
Short biography of the organizer(s) and contact information:
Anna WilbikAnna Wilbik received the Ph.D. degree in computer science from the Systems Research Institute, Polish Academy of Science, Warsaw, Poland, in 2010. She is currently an Assistant Professor with the Information Systems Group of the School of Industrial Engineering at the Eindhoven University of Technology. She is alumnus of TOP500 Innovators: Science - Management – Commercialization Program. In 2011, she was a Post-doctoral Fellow with the Department of Electrical and Computer Engineering, University of Missouri, Columbia, USA. Her research interests include linguistic summaries, data analysis, machine learning, and computational intelligence. He has published about 50 papers in international journals and conferences and was part of organization of a few conferences in the area of IT and computational intelligence.
Rui Jorge Almeida
Rui received his 5 year degree and M.Sc. in Mechanical Engineering both from Instituto Superior Técnico, Universidade de Lisboa, Portugal, in 2005 and 2006 respectively. In 2014 he received is PhD in Econometrics from the Erasmus University of Rotterdam. Since 2013 Rui joined the Information Systems Group of the School of Industrial Engineering at the Eindhoven University of Technology, as an assistant professor. During his PhD, Rui received several grants to perform short term research visits, including an IEEE-CIS Walter Karplus Student Research Grant in 2012 for a short term research visit at Laboratoire d’Informatique de Paris 6, Université Pierre et Marie Curie, France, where he worked on linguistic summaries of patient data to detect medical events. Rui has also been part of the organization of several special sessions, workshops and conferences on international level in the area of financial engineering and soft computing.
Nicolas Marin
Nicolas Marin received the M.S. and Ph.D. degrees in computer science, both from the University of Granada, Spain, in 1998 and 2001, respectively. Since 2005 he is Associate Professor at the Department of Computer Science and Artificial intelligence of the University of Granada. He has participated in the teams of ten research projects, including a project in the area of Linguistic Description of Data that he has led. He has published about 100 papers in international journals and conferences. He has co-edited several special issues in the area of Intelligent Databases and Information Systems and LinguisticDescription of Data and organized several special sessions on these topics in national and international conferences, and has been advisor of three Ph.D. Thesis in these fields.
Daniel Sanchez
Daniel Sanchez received the M.S. and Ph.D. degrees in computer science, both from the University of Granada, Spain, in 1995 and 1999, respectively. Since 2001 he is Associate Professor at the Department of Computer Science and Artificial intelligence of the University of Granada. He has participated in the teams of more than ten research projects, including a national project in the area of Linguistic Description of Visual Information that he has led. He has published more than 100 papers in international journals and conferences, 32 of them in indexed journals (SCI-JCR). He has co-edited an special issue in the International Journal of Intelligent Systems (IJIS) about “Fuzzy Bags, Cardinality, and Quantification”. He has organized several workshops and special sessions about Soft Computing and Applications in Data Mining and Computer Vision in national and international conferences, and has been advisor of five Ph.D. Thesis in these fields. He is currently one of the coordinators of the DAMI Working group on Data Mining and Machine Learning of EUSFLAT (European Society for Fuzzy Logic and Technology).
Contact Addresses:
Anna WilbikInformation Systems, School of Industrial Engineering,
Eindhoven University of Technology
e-mail: a.m.wilbik@tue.nl
Rui Jorge Almeida
Information Systems, School of Industrial Engineering,
Eindhoven University of Technology
e-mail: rjalmeida@tue.nl
Daniel Sánchez
Department of Computer Science and Artificial Intelligence,
University of Granada
e-mail: daniel@decsai.ugr.es
Nicolás Marín Ruiz
Department of Computer Science and Artificial Intelligence,
University of Granada
e-mail: nicm@decsai.ugr.es
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers IJCNN 2015 Special Session "Emerging Methodologies for Big Data Integration"
Over the years, huge quantities of data have been generated by large-scale scientific experiments (biomedical, “omic”, imaging, astronomical, etc.), big industrial companies and on the web. One of the main characteristics of such Big Data is that they are multi-view, i.e. there are multiple sources (in the “omics” sciences, experiments related to mRNA, miRNA etc.), relate the same patterns (in this case patients) or multi-domain (in biomedical applications for examples, “omics, imaging and clinical data).
As a consequence, new methodologies based on neural networks, machine and statistical learning, computation Intelligence and others, have been proposed to integrate these kinds of big data and to elicit relevant information to infer novel models and correlations.
The aim of the special session is to solicit new approaches to real world scientific and industrial big data integration, as well as applications of above mentioned Big Data methodologies.
THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IJCNN 2015, January 15th 2015.
All the submissions will be peer-reviewed with the same criteria used for other contributed papers.
Perspective authors will submit their papers through the IJCNN2015 conference submission system at http://www.ijcnn.org/
Please make sure to select the Special Session "Emerging Methodologies for Big Data Integration " from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list;
Templates and instructions for authors will be provided on the IJCNN webpage http://www.ijcnn.org/
All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the conference proceedings.
Further information about IJCNN 2015 can be found at http://www.ijcnn.org/
and about the special session at
http://neuronelab.unisa.it/emerging-methodologies-for-big-data-integration/
As a consequence, new methodologies based on neural networks, machine and statistical learning, computation Intelligence and others, have been proposed to integrate these kinds of big data and to elicit relevant information to infer novel models and correlations.
The aim of the special session is to solicit new approaches to real world scientific and industrial big data integration, as well as applications of above mentioned Big Data methodologies.
Topics
Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics:- Multi-view learning
- Multi-view clustering
- data fusion
- data integration
- multi-view data applications
- multi domain data applications
THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IJCNN 2015, January 15th 2015.
All the submissions will be peer-reviewed with the same criteria used for other contributed papers.
Perspective authors will submit their papers through the IJCNN2015 conference submission system at http://www.ijcnn.org/
Please make sure to select the Special Session "Emerging Methodologies for Big Data Integration " from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list;
Templates and instructions for authors will be provided on the IJCNN webpage http://www.ijcnn.org/
All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the conference proceedings.
Further information about IJCNN 2015 can be found at http://www.ijcnn.org/
and about the special session at
http://neuronelab.unisa.it/emerging-methodologies-for-big-data-integration/
Organizers
- Amir Hussain Professor of Computing Science and founding Director of the Cognitive Signal-Image Processing and Control Systems Research (COSIPRA) Laboratory, University of Stirling, UK
- Giovanni Montana Professor and Chair in Biostatistics and Bioinformatics, Biomedical Engineering Department, King’s College, London, UK
- Francesco Carlo MorabitoProfessor and Chair of the Neurolab, Dipartimento DICEAM, Università Mediterranea di Reggio Calabria, Italy
- Roberto TAGLIAFERRIProfessor and Chair of the Neuronelab, Dipartimento di Informatica, Università di Salerno, Italy
Technical Program Committee
- Elia Mario Biganzoli, Università di Milano, Italy
- Erik Cambria, NTU, Singapore
- Ciro Donalek, Caltech, CA, USA
- Anna Esposito, Seconda Università di Napoli, Italy
- Marcos Faundez-Zanuy, Escola Universitaria Politecnica de Mataro (Tecnocampus), Spain
- Alexander Gelbukh, National Polytechnic Institute, Mexico
- Dario Greco, FIOH, Finland
- Newton Howard, MIT Media Lab, USA
- Pietro Liò, University of Cambridge, UK
- Bin Luo, Anhui University, China
- Mufti Mahmud, Antwerp University, Belgium
- Riccardo Rizzo, CNR, Italy
- Domenico Ursino, Università Mediterranea di Reggio Calabria, Italy
- Alfredo Vellido, Universidad Politécnica de Cataluña, Spain
- Pierangelo Veltri, Università "Magna Graecia" di Catanzaro, Italy
- Jonathan Wu, University of Windsor, Canada
- Yunqing Xia, Tsinghua University, China
- Erfu Yang, University of Strathclyde, UK
Thursday, 4 December 2014
Call for Papers FUZZ-IEEE Special Session "Fuzzy Logic on Technology Management"
Technology management is one of the emerging academic fields in the world. Fuzzy logic approaches have a significant place in the field of technology and technology management with its highly complex structure. In the literature, many studies are placed such as technology knowledge management, innovation management, technology acquisition, R&D management, technology strategy, technology investment, technology marketing, technology protection, technology models and technology planning. Therefore, fuzzy logic based applications are diverse in technology management processes. Due to technology integrates every steps of human activities and human manages the technology, fuzzy logic based applications contribute the technology management in terms of commercial and technological perspectives.The session of “Fuzzy Logic for Technology and Technology Management” will contribute to today’s needs of academic world. We believe this session will be benefitted by several precious articles.
Email address: bekirs66@gmail.com
Affiliation: Istanbul Technical University
Postal address: Denizcilik Fakültesi Sahil Cad. 34940 Tuzla, Istanbul, Turkey
Telephone number: (+90) 0216 395 45 01-1223
Topics:
It invites researchers from different related fields and gathers the most recent studies including but not limited to:- Fuzzy-logic based technology management framework, activities and application
- Technology management processes
- Technology management methodologies, tools
- Technology Lifecycle
- Technology Capabilities, Dynamic Capability
- Rapid Technological Change
- Technology Transfer
- Information Technology
- Technology Analysis and Strategic Management
- Project Management
- Technology Acquisition
- Technology Forecasting
- Creativity and Innovation Management
- Impacts of technological Opportunities
- Technology Integration
- Technology Intelligence
- Technology Selection
- Technology Roadmap
- Open, Reverse Innovation
- Technology Feasibility
Short biography of the organizer(s) and contact information:
Bekir Sahin (PhD) is a Research Assistant in Maritime Transportation Engineering Management (MTME) Department of Maritime Faculty, Istanbul Technical University (ITU) in Turkey. His MS degree from Engineering Technology department at University of Houston. His BS degree is from MTME department at Istanbul University. His research area of interest are; Technology Management of Shipping, Engineering Technology, Risk Assessment of Navigation, Marine Accident Analysis, Ice navigation.Contact information:
Name: Bekir SahinEmail address: bekirs66@gmail.com
Affiliation: Istanbul Technical University
Postal address: Denizcilik Fakültesi Sahil Cad. 34940 Tuzla, Istanbul, Turkey
Telephone number: (+90) 0216 395 45 01-1223
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy transforms: theory and applications to data analysis and processing"
Fuzzy (F)-transforms successfully link various transforms (Fourier, Laplace, integral, Wavelet, etc.) with fuzzy approximation models. The general idea is to bring an original model into a special space where succeeding computations are easier. In particular, the F-transform transforms an infinitary object (a real function) into a finitary one (a finite vector). Another specific feature of the F-transform consists in including a fuzzy partition in its formal representation.
In the recent ten years, the theory of F-transform became an important constituent in the field of computational intelligence. It has a well justified theory and many sophisticated applications in image, signal and time series processing. Moreover, it can be successfully used in numerical methods for differential and integro-differential equations including the case when uncertainty is included in their formulation. The exceptional feature of the F-transform is that it successively and efficiently copes with classical problems as well as with problems that are affected by uncertainty or vagueness.
In image and signal processing, the F-transform effectively solves problems connected with up- (down-) scaling, reconstruction, edge detection, fusion, registration, etc. In time series analysis, the F-transform is used for trend extraction. In big data area, it works as a successful method of pattern recognition.
The F-transform propagates usefullness and effectiveness of fuzzy methods on all levels of data processing.
We invite contributions that extend traditional ways of data analysis and propose adequate methods for various kinds of data processing including, but not limited to the following topics:
Email address: irina.perfilieva@osu.cz
Affiliation: University of Ostrava
Postal address: Institute for Research and Applications of Fuzzy Modeling,
University of Ostrava, 30 dubna 22, 701 03 Ostrava 1, Czech Republic
Telephone number: +420-597-091408
Name: Jin Hee Yoon
Email address: jin9135@sejong.ac.kr
Affiliation: Sejong university, School of Statistics and Mathematics
Postal address: #102 Dasan-gwan Sejojng University Gunja -Dong Gwangjin-
Gu Seoul, South Korea
Telephone number: +82-2-3408-3916
In the recent ten years, the theory of F-transform became an important constituent in the field of computational intelligence. It has a well justified theory and many sophisticated applications in image, signal and time series processing. Moreover, it can be successfully used in numerical methods for differential and integro-differential equations including the case when uncertainty is included in their formulation. The exceptional feature of the F-transform is that it successively and efficiently copes with classical problems as well as with problems that are affected by uncertainty or vagueness.
In image and signal processing, the F-transform effectively solves problems connected with up- (down-) scaling, reconstruction, edge detection, fusion, registration, etc. In time series analysis, the F-transform is used for trend extraction. In big data area, it works as a successful method of pattern recognition.
The F-transform propagates usefullness and effectiveness of fuzzy methods on all levels of data processing.
Objectives and topics:
The aim of this special session is to present recent developments and trends in the theory and applications of the F-transform, including all mentioned above. Beside theoretical aspects, the session will be focused on advanced applications in data analysis including handling big data.We invite contributions that extend traditional ways of data analysis and propose adequate methods for various kinds of data processing including, but not limited to the following topics:
- Theoretical aspects of the F-transform and its higher degree versions,
- Inverse F-transform and how to improve its approximation quality,
- Numerical methods on the basis of F-transform,
- Big data processing on the basis of the F-transform,
- Time series analysis and forecasting including:
- time series trend extraction, local trend estimation and their models,
- fuzzy time series, granular time series and their models,
- forecasting methods: regression, fuzzy regression, fuzzy/linguistic IF-THEN rules.
Short biography of the organizer(s) and contact information:
Irina Perfilieva
Professor Irina Perfilieva, Ph.D., received the degrees of M.S. (1975) and Ph.D (1980) in Applied Mathematics from the Lomonosov State University in Moscow, Russia. At present, she is a full professor of Applied Mathematics in the University of Ostrava, Czech Republic. At the same time she is a head of Theoretical Research Department in the University of Ostrava, Institute for Research and Applications of Fuzzy Modeling. She is the author and co-author of four books on mathematical principles of fuzzy sets and fuzzy logic, the co-editor of one book and many special issues of scientific journals. She has published over 250 papers in the area of multi-valued logic, fuzzy logic, fuzzy approximation and fuzzy relation equations. She is a member of editorial boards of the following journals:- Int. Journal of Fuzzy Sets and Systems,
- Transactions on Fuzzy Systems,
- Journal of Applied Computational Intelligence,
- Iranian Journal of Fuzzy Systems,
- Journal of Uncertain Systems,
- International Journal of Computational Intelligence Systems,
- Journal of Intelligent technologies and applied statistics,
- Journal of Uncertainty in Mathematics Science,
- Journal of Fuzzy Information and Engineering.
Jin Hee Yoon
Jin Hee Yoon, Ph.D., received the degrees of B.S, M.S. and Ph.D (1980) in Mathematics at Yonsei University, Seoul, South Korea. Currently, she is a visiting professor of School of Mathematics and Statistics in Sejong University of Seoul, South Korea. She has been working as a organizer and committee of several international conferences, also has been working as an editor of some international journals including prestigious journal. She is going to be listed in Marquis Who’s who in the world, 2015. Also, she got awarded for Outstanding keynote speech at 11th Iranian Conference on Intelligent Systems (ICIS2013). Her research interests are Fuzzy time series, Forecasting based on F-transform, Fuzzy regression, Financial forecasting.Contact information:
Name: Irina PerfilievaEmail address: irina.perfilieva@osu.cz
Affiliation: University of Ostrava
Postal address: Institute for Research and Applications of Fuzzy Modeling,
University of Ostrava, 30 dubna 22, 701 03 Ostrava 1, Czech Republic
Telephone number: +420-597-091408
Name: Jin Hee Yoon
Email address: jin9135@sejong.ac.kr
Affiliation: Sejong university, School of Statistics and Mathematics
Postal address: #102 Dasan-gwan Sejojng University Gunja -Dong Gwangjin-
Gu Seoul, South Korea
Telephone number: +82-2-3408-3916
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Advances in fuzzy modeling and control for mobile robots"
The use of fuzzy techniques is of great advantage for mobile robots operating especially in uncertain or hazardous environments, or for rescue robots operating in disaster areas. The features of fuzzy logic make it particularly suitable especially for problems posed by autonomous robot operation, Fuzzy techniques in mobile robotics are of growing interest not only in low level control but also in the fields of
This special session includes papers with new research ideas, methods and recent advances and applications, that are related to fuzzy modeling and control for mobile robotics. Papers on, but not limited to, the following topics together with classical and advanced fuzzy techniques are welcome:
We encourage submissions of papers, which have not been published or submitted to any other conference, about theoretical advances in these core areas as well as papers which deal with some practical insights resulting from experiments or implementations.
Adj. Prof. at AASS, Univ. Örebro since 2004. Until 2004 Principal Research Scientist Siemens R&D Munich, Dipl. Ing. 1975. Since 1982 robotic research. Dr. Ing. 1981, Dr. sc. techn. 1989. Since 1991 fuzzy logic task force at Siemens AG. Author /co-author, edit/co-edit. 15 books/ chapters, 46 articles, 53 Conf. proceeds. 14 patents. Spokesman of fuzzy group 1994-2002. Associate. ed. IEEE Trans. Fuzzy Syst. 1994-2004, Information Sciences since 2014. Res: intell. cont.,robotics, mobile robots
rub.palm@t-online.de
0049 89 2605263 (priv.)
The same deadline as for the regular papers to be submitted to the Fuzz IEEE 2015 will be observed. However, the potential contributors are requested to send at their earliest convenience (November 9, 2014) an e-mail message, addressed to rub.palm@t-online.de confirming the intent to submit a paper and giving its tentative title and a list of the authors. Submitted papers must comply with the Fuzz IEEE 2015 guidelines for submission. Papers submitted to this special session will go through the normal reviewing process. The accepted papers will be published in the conference proceedings.
- higher control levels
- pattern recognition
- vision-based control
- localization
- mapping
- motion planning
- navigation
- obstacle avoidance
This special session includes papers with new research ideas, methods and recent advances and applications, that are related to fuzzy modeling and control for mobile robotics. Papers on, but not limited to, the following topics together with classical and advanced fuzzy techniques are welcome:
- Autonomous Vehicles
- Multi-robot systems
- Rehabilitation Robotics
- Aerial Robotics
- Underwater Robotics
- Multi-legged robots
- Wheeled vehicles
We encourage submissions of papers, which have not been published or submitted to any other conference, about theoretical advances in these core areas as well as papers which deal with some practical insights resulting from experiments or implementations.
Short biography of the organizer(s) and contact information:
Rainer Palm Oerebro University, SwedenAdj. Prof. at AASS, Univ. Örebro since 2004. Until 2004 Principal Research Scientist Siemens R&D Munich, Dipl. Ing. 1975. Since 1982 robotic research. Dr. Ing. 1981, Dr. sc. techn. 1989. Since 1991 fuzzy logic task force at Siemens AG. Author /co-author, edit/co-edit. 15 books/ chapters, 46 articles, 53 Conf. proceeds. 14 patents. Spokesman of fuzzy group 1994-2002. Associate. ed. IEEE Trans. Fuzzy Syst. 1994-2004, Information Sciences since 2014. Res: intell. cont.,robotics, mobile robots
rub.palm@t-online.de
0049 89 2605263 (priv.)
The same deadline as for the regular papers to be submitted to the Fuzz IEEE 2015 will be observed. However, the potential contributors are requested to send at their earliest convenience (November 9, 2014) an e-mail message, addressed to rub.palm@t-online.de confirming the intent to submit a paper and giving its tentative title and a list of the authors. Submitted papers must comply with the Fuzz IEEE 2015 guidelines for submission. Papers submitted to this special session will go through the normal reviewing process. The accepted papers will be published in the conference proceedings.
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy Interpolation"
Fuzzy interpolation provides a flexible means to perform reasoning in the presence of insufficient knowledge that is represented as sparse fuzzy rule bases. It enables approximate inferences to be carried out from a rule base that does not cover a given observation. Fuzzy interpolation also provides a way to simplify complex systems models and/or the process of fuzzy rule generation. It allows the reduction of the number of rules needed, thereby speeding up parameter optimisation and runtime efficiency.
The topics of this special session will include but are not limited to:
Qiang Shen holds the Established Chair of Computer Science and is Director of the Institute of Mathematics, Physics and Computer Science at Aberystwyth University, UK. He has a PhD in Knowledge-Based Systems and a DSc in Computational Intelligence. He is a long-serving associate editor of two IEEE flagship Journals (Cybernetics and Fuzzy Systems) and an editorial board member of several other leading international periodicals (e.g., Fuzzy Sets and Systems). He has chaired and given keynote lectures at many prestigious international and national conferences, including serving as the General Chair of FUZZ-IEEE 2007 and Tutorial Chair of WCCI 2008 and WCCI 2014. He was a founding member of IEEE CIS Fuzzy Systems Technical Committee. He has authored 2 research monographs and over 340 peer-reviewed papers, including an Outstanding Transactions Paper Award from IEEE. He has first-supervised over 40 PDRAs/PhDs, including one UK Best PhD Distinguished Dissertation Award winner. He is a UK REF 2014 panel member for research assessment in Computer Science and Informatics, and was a London 2012 Olympic Torch Relay torchbearer, carrying the Olympic torch in celebration of the centenary of Alan Turing.
qqs@aber.ac.uk
Laszlo Koczy is a Professor at Szechenyi Istvan University (SZE, Gyor) and Budapest University of Technology and Economics (BME), Hungary. He has a PhD and a DSc, both in Electrical/Control Engineering. Among others, he is an associate editor of IEEE Transactions on Fuzzy Systems and Fuzzy Sets and Systems, International Journal of Fuzzy Systems, Journal of Advanced Computational Intelligence, and International Journal of Fuzzy Systems. He has chaired and given keynote lectures at many prestigious international and national conferences, including acting as the General Chair of FUZZ-IEEE 2004, Special Session Chair of WCCI 2012 and Panel Chair of FUZZ-IEEE 2013. He served in the International Fuzzy Systems Association as President, and has been Administrative Committee member of IEEE Computational
Intelligence Society for two cycles and another two cycles a member of the IEEE Systems Council. He has published over 460 refereed papers and several text books on the subject. At SZE he is the president of the University Doctoral Council, and he was recently appointed member of the Hungarian Accreditation Board for Higher Education by the Prime Minister, where he chairs the Engineering Panel and is a member of the Supervisory Committee of the National Doctoral Council.
Shyi-Ming Chen is a Distinguished Professor with the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taiwan. Previously he served as Dean of the College of Electrical Engineering and Computer Science at Jinwen University of Science and Technology, and Vice President of the National Taichung University of Education, Taiwan. He is an associate editor of IEEE Transactions on Fuzzy Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, and Information Sciences, and is an editorial board member of many other international journals (e.g., International Journal of Fuzzy Systems). He is currently Chair of the IEEE SMC Society’s Technical Committee on Intelligent Internet Systems and was the President of the Taiwanese Association for Artificial Intelligence (TAAI) from 2005 to 2009. He has published more than 430 papers in referred journals, conference proceedings and book chapters. He has received numerous honours and awards, including an Outstanding Paper Award from Journal of Information and Education. He has first-supervised many PhDs and received a number of awards for outstanding PhD supervision from TAAI, Taiwan Fuzzy Systems Association and others.
Ying Li is a Professor with the School of Computer Science at Northwest Polytechnical University (which is a top rated research-led University in China). She is the Vice Chairman of Shaanxi Provincial Key Laboratory for Speech and Image Information Processing (SAIIP) in China. She has published extensively in many top journals and conferences, held 11 patents and applied her work to many challenging problem domains, including environment surveillance, mine detection, and automatic target recognition and tracking. Her original work on sparse representation decomposition, target detection, image denoising, and feature extraction and segmentation has been awarded with grants from a number of major funding bodies in China, including National Natural Science Foundation. She has co-chair a number of international conferences, including as the Programme Committee Chair of IScIDE 2011.
Objectives and Topics:
The aim of this special session is to provide a forum:- To disseminate and discuss recent and significant research efforts in the development of fuzzy interpolation and related techniques,
- To promote both theoretical and practical applications of fuzzy interpolation, and
- To foster integration of fuzzy interpolation with other computational intelligence techniques.
The topics of this special session will include but are not limited to:
- Fuzzy interpolation
- Fuzzy extrapolation
- Fuzzy interpolative learning
- Fuzzy systems simplification
- Fuzzy set transformation
- Fuzzy set representation
- Fuzzy interpolation application
- Fuzzy function approximation
- Hybrid fuzzy interpolation Systems
- Comparative studies of interpolation methods
Short biography of the organizer(s) and contact information:
All four proposers have organised at least one special session on fuzzy interpolation at a previous FUZZ-IEEE.Qiang Shen holds the Established Chair of Computer Science and is Director of the Institute of Mathematics, Physics and Computer Science at Aberystwyth University, UK. He has a PhD in Knowledge-Based Systems and a DSc in Computational Intelligence. He is a long-serving associate editor of two IEEE flagship Journals (Cybernetics and Fuzzy Systems) and an editorial board member of several other leading international periodicals (e.g., Fuzzy Sets and Systems). He has chaired and given keynote lectures at many prestigious international and national conferences, including serving as the General Chair of FUZZ-IEEE 2007 and Tutorial Chair of WCCI 2008 and WCCI 2014. He was a founding member of IEEE CIS Fuzzy Systems Technical Committee. He has authored 2 research monographs and over 340 peer-reviewed papers, including an Outstanding Transactions Paper Award from IEEE. He has first-supervised over 40 PDRAs/PhDs, including one UK Best PhD Distinguished Dissertation Award winner. He is a UK REF 2014 panel member for research assessment in Computer Science and Informatics, and was a London 2012 Olympic Torch Relay torchbearer, carrying the Olympic torch in celebration of the centenary of Alan Turing.
qqs@aber.ac.uk
Laszlo Koczy is a Professor at Szechenyi Istvan University (SZE, Gyor) and Budapest University of Technology and Economics (BME), Hungary. He has a PhD and a DSc, both in Electrical/Control Engineering. Among others, he is an associate editor of IEEE Transactions on Fuzzy Systems and Fuzzy Sets and Systems, International Journal of Fuzzy Systems, Journal of Advanced Computational Intelligence, and International Journal of Fuzzy Systems. He has chaired and given keynote lectures at many prestigious international and national conferences, including acting as the General Chair of FUZZ-IEEE 2004, Special Session Chair of WCCI 2012 and Panel Chair of FUZZ-IEEE 2013. He served in the International Fuzzy Systems Association as President, and has been Administrative Committee member of IEEE Computational
Intelligence Society for two cycles and another two cycles a member of the IEEE Systems Council. He has published over 460 refereed papers and several text books on the subject. At SZE he is the president of the University Doctoral Council, and he was recently appointed member of the Hungarian Accreditation Board for Higher Education by the Prime Minister, where he chairs the Engineering Panel and is a member of the Supervisory Committee of the National Doctoral Council.
Shyi-Ming Chen is a Distinguished Professor with the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taiwan. Previously he served as Dean of the College of Electrical Engineering and Computer Science at Jinwen University of Science and Technology, and Vice President of the National Taichung University of Education, Taiwan. He is an associate editor of IEEE Transactions on Fuzzy Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, and Information Sciences, and is an editorial board member of many other international journals (e.g., International Journal of Fuzzy Systems). He is currently Chair of the IEEE SMC Society’s Technical Committee on Intelligent Internet Systems and was the President of the Taiwanese Association for Artificial Intelligence (TAAI) from 2005 to 2009. He has published more than 430 papers in referred journals, conference proceedings and book chapters. He has received numerous honours and awards, including an Outstanding Paper Award from Journal of Information and Education. He has first-supervised many PhDs and received a number of awards for outstanding PhD supervision from TAAI, Taiwan Fuzzy Systems Association and others.
Ying Li is a Professor with the School of Computer Science at Northwest Polytechnical University (which is a top rated research-led University in China). She is the Vice Chairman of Shaanxi Provincial Key Laboratory for Speech and Image Information Processing (SAIIP) in China. She has published extensively in many top journals and conferences, held 11 patents and applied her work to many challenging problem domains, including environment surveillance, mine detection, and automatic target recognition and tracking. Her original work on sparse representation decomposition, target detection, image denoising, and feature extraction and segmentation has been awarded with grants from a number of major funding bodies in China, including National Natural Science Foundation. She has co-chair a number of international conferences, including as the Programme Committee Chair of IScIDE 2011.
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers IJCNN 2015 Special Session "Distributed Learning Algorithms, Techniques, and Implementations for Internet-of-Things"
Updated: New submission deadline February 5th, 2015.
This special session aims at presenting novel approaches to distributed learning for Internet-of-Things, both from the theoretical and practical perspectives of computational intelligence schemes.
For more information, please visit IJCNN'2015 CFP website: http://www.ijcnn.org/call-for-papers, or our Special Session CFP: https://sites.google.com/site/ijcnn2015distlearniot/ . All submissions will be peer-reviewed with the same criteria used for other contributed papers.
Paper Decision notification: March 15th, 2015
Camera-ready submission: April 15th, 2015
Conference Dates: July 12 - 17th, 2015
Thundercloud Research Lab
Faculty of Information Science and Technology (FIST)
Multimedia University
Melaka, Malaysia
Email: anang.amin@mmu.edu.my
Asad I. Khan
Faculty of Information Technology
Monash University
Clayton, VIC, Australia
Email: Asad.Khan@monash.edu
Benny B. Nasution
Politeknik Negeri Medan
Medan, Indonesia
Email: benny.nasution@polmed.ac.id
Aim and Motivation:
Many learning algorithms and techniques were developed with the requirements of single application in mind, such as e-commerce, search, and vision. Internet-of-Things (IoT) presents a great challenge to existing computational intelligence schemes such as machine learning and neural networks due to its data and compute complexity. IoT devices, such as sensors, cameras, and actuators commonly produce distributed, sparse and highly complex data representations that require these intelligent schemes to adapt and adjust, with limited resource availability. The ability to perform learning in distributed manner will enable better resource coordination and utilisation in handling complex computations in such resource-constrained environment.This special session aims at presenting novel approaches to distributed learning for Internet-of-Things, both from the theoretical and practical perspectives of computational intelligence schemes.
Topics:
This includes but is not restricted to the following topics:- Parallel and distributed computational intelligence algorithms and techniques:
- Deep learning
- Hierarchical learning
- Associative memory
- Sparse distributed memory
- Machine learning
- Neural networks
- Hybrid approaches
- IoT Analytics
- Autonomous IoT
- Resource utilisation and coordination
- Control and communication systems
- Intelligent IoT applications and services
Paper Submission:
The format of paper and submission procedure should be followed as specified on the IJCNN 2015 website. Accepted special session papers will be included in the conference proceedings. Submissions to this special session should follow the following instructions:- Go to http://ieee-cis.org/conferences/ijcnn2015/upload.php to submit your paper to IJCNN 2015.
- Be sure to set the "Main research topic" to "SS35 - Distributed Learning Algorithms, Techniques, and Implementations for Internet-of-Things".
For more information, please visit IJCNN'2015 CFP website: http://www.ijcnn.org/call-for-papers, or our Special Session CFP: https://sites.google.com/site/ijcnn2015distlearniot/ . All submissions will be peer-reviewed with the same criteria used for other contributed papers.
IMPORTANT DATES
Paper submission UPDATED: February 5th, 2015Paper Decision notification: March 15th, 2015
Camera-ready submission: April 15th, 2015
Conference Dates: July 12 - 17th, 2015
Organizers:
Anang Hudaya Muhamad AminThundercloud Research Lab
Faculty of Information Science and Technology (FIST)
Multimedia University
Melaka, Malaysia
Email: anang.amin@mmu.edu.my
Asad I. Khan
Faculty of Information Technology
Monash University
Clayton, VIC, Australia
Email: Asad.Khan@monash.edu
Benny B. Nasution
Politeknik Negeri Medan
Medan, Indonesia
Email: benny.nasution@polmed.ac.id
Call for Papers FUZZ-IEEE Special Session "Recent Advances in Fuzzy Control System Design and Analysis"
The aim of this special session is to present the state-of-the-art results in the area of theory and applications of fuzzy control system design and analysis, and to get together well-known and potential researchers in this area. Fuzzy control system design and analysis provide a systematic and efficient approach to controlling of nonlinear plants and analysis of nonlinear control systems. Fuzzy control system has been employed to deal with a wide range of nonlinear control systems such as continuous-time, discrete-time, hybrid, sampled-data, time-delay, switching, adaptive control systems and so on. A number of results on this area have appeared in the literature. However, there is still room for improvement of the existing results in order to propose new techniques for control of nonlinear systems. In the proposed special session, the focus is mainly on the fuzzy control system design and analysis with emphasis on the theory and applications. The important problems and difficulties on the fuzzy control systems will be addressed, their concepts will be provided and methodologies will be proposed to take care of the nonlinear systems using the fuzzy control system approaches.
Keywords of the session: Fuzzy Control System, Fuzzy Model, Nonlinear Control
Email: yoneyama@ee.aoyama.ac.jp
Jun Yoneyama received the B.Eng. and M.Eng. degrees from the Department of Electrical Engineering, Waseda University. He received Ph.D. degree from the Department of Electrical Engineering, University of California, Los Angeles, 1996. In 1996, he joined the Department of Electrical and Electronic Engineering in Shizuoka University, Japan. In 2000, he joined as an Associate Professor in Aoyama Gakuin University and is currently a Full Professor.
His current research interests include robust control and intelligent control systems. He has served as a program committee member for some international conferences and an editor for some international journals. He now serves as a leader for task force term: Fuzzy Control Theory and Its Application in IEEE Computational Intelligence Society. He is a member of The Institute of Electrical and Electronics Engineers (IEEE), Japan Society for Fuzzy Theory and Intelligence Informatics (SOFT), The Society of Instrument and Control Engineers (SICE), The Institute of Electrical Engineers of Japan, and The Robot Society of Japan.
Keywords of the session: Fuzzy Control System, Fuzzy Model, Nonlinear Control
Short biography of the organizer(s) and contact information:
Organizer: Professor Jun Yoneyama, Aoyama Gakuin UniversityEmail: yoneyama@ee.aoyama.ac.jp
Jun Yoneyama received the B.Eng. and M.Eng. degrees from the Department of Electrical Engineering, Waseda University. He received Ph.D. degree from the Department of Electrical Engineering, University of California, Los Angeles, 1996. In 1996, he joined the Department of Electrical and Electronic Engineering in Shizuoka University, Japan. In 2000, he joined as an Associate Professor in Aoyama Gakuin University and is currently a Full Professor.
His current research interests include robust control and intelligent control systems. He has served as a program committee member for some international conferences and an editor for some international journals. He now serves as a leader for task force term: Fuzzy Control Theory and Its Application in IEEE Computational Intelligence Society. He is a member of The Institute of Electrical and Electronics Engineers (IEEE), Japan Society for Fuzzy Theory and Intelligence Informatics (SOFT), The Society of Instrument and Control Engineers (SICE), The Institute of Electrical Engineers of Japan, and The Robot Society of Japan.
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy Logic for Economics and Finance"
We invite original submissions for the special session of The 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015) dealing with the implementation of fuzzy sets and fuzzy logic for economic and financial phenomenon.
There is a growing academic interest on using fuzzy set approach and fuzzy logic framework for economic and financial problems. Since most of the economic phenomenon are subject to uncertainty and human error, fuzziness is an unavoidable nature of business life. Forecasting, asset management, investment appraisal, risk assessment and many other business problems are investigated in the literature, and there is still a gap between the theory of economics (also finance) and the power of engineering. Fuzzy logic approach is capable of handling various practical problems while it requires to be supported with the theoretical basis of fundamental economics. A special session titled "Fuzzy Logic for Economics and Finance" would be timely and contributing as well as attractive for scholars in the field. Proper use of fuzzy set theory and methods for merging economic theory and fuzzy logic are some emerging topics in the engineering research. Therefore, we expect a particular volume of papers contributing to the session. Papers dealing with inconsistency between the theory of economics/finance and fuzzy aided engineering applications are particularly welcomed.
http://fuzzieee2015.org/submission/
Ph.D.
IMARC, Kobe University, Kobe 658-0022 Japan
Department of Ship and Marine Technology,
Izmir Katip Celebi University, Cigli 35620, Izmir, Turkey
E-mail: duruokan@yahoo.com
Emrah Bulut, Ph.D.
Department of Business Administration, Yildiz Technical University,
34349, Istanbul, Turkey.
E-mail: bltemrah@gmail.com
There is a growing academic interest on using fuzzy set approach and fuzzy logic framework for economic and financial problems. Since most of the economic phenomenon are subject to uncertainty and human error, fuzziness is an unavoidable nature of business life. Forecasting, asset management, investment appraisal, risk assessment and many other business problems are investigated in the literature, and there is still a gap between the theory of economics (also finance) and the power of engineering. Fuzzy logic approach is capable of handling various practical problems while it requires to be supported with the theoretical basis of fundamental economics. A special session titled "Fuzzy Logic for Economics and Finance" would be timely and contributing as well as attractive for scholars in the field. Proper use of fuzzy set theory and methods for merging economic theory and fuzzy logic are some emerging topics in the engineering research. Therefore, we expect a particular volume of papers contributing to the session. Papers dealing with inconsistency between the theory of economics/finance and fuzzy aided engineering applications are particularly welcomed.
Topics
- Forecasting
- Fuzzy Time Series Analysis
- Financial Data Mining
- Risk Management
- Pricing of Structured Securities
- Asset Allocation
- Trading Systems
- Hedging Strategies
- Behavioral Finance
- Portfolio Optimization
- Algorithmic Trading
- Agent-based Computational Economics
- Testing, Benchmarking, Robustness Checks
- Intelligent Trading Agents
Deadline
The deadline for submissions to this special session is 08 February 2014.Information for Authors
Information on the format and templates for papers can be found on the conference website below:http://fuzzieee2015.org/submission/
Session Chairs
Okan DuruPh.D.
IMARC, Kobe University, Kobe 658-0022 Japan
Department of Ship and Marine Technology,
Izmir Katip Celebi University, Cigli 35620, Izmir, Turkey
E-mail: duruokan@yahoo.com
Emrah Bulut, Ph.D.
Department of Business Administration, Yildiz Technical University,
34349, Istanbul, Turkey.
E-mail: bltemrah@gmail.com
Wednesday, 3 December 2014
Call for Papers IJCNN 2015 Special Session "Biologically Inspired Computational Vision"
Introduction:
Constructive understanding of computational principles of visual information processing, perception and cognition is one of the most fundamental challenges of contemporary science. Deeper insight into biological vision helps to advance intelligent systems research to achieve robust performance similar to biological systems. Biological inspiration indicates that sensory processing, perception, and action are intimately linked at various levels in animal vision. Implementing such integrated principles in artificial systems may help us achieve better, faster and more efficient intelligent systems. This session provides an integrated platform to present original ideas, theory, design, and applications of computational vision.- Topics of interest include, but are not limited to the following:Theoretical approaches and modeling in computational vision
- Neuronal mechanisms of visual processing
- Low level vision and its relationship to biological machinery
- Artificial learning systems for image and information processing and evidential reasoning for recognition
- Intelligent search in communications networks
- Modeling issues in ATM networks, agent-oriented computing architectures
- Perception of shape, shadows, poses, color and illumination in object recognition
- Tracking for inferring shapes and 3D motions
- Active visual perception, attention and robot vision
- Functional Magnetic Resonance Imaging (fMRI) studies of visual segmentation and perception
- Application of computational vision in areas of
- Automated target identification and acquisition systems in defense and industry
- Biomedical imaging
- 3D photography
- Face recognition
- Learning to segment camouflaged objects
- Motor actions and robotics
- Image databases and indexing
- Hardware implementation of computational vision
- Any other topics related to biological approaches in computer vision
Organizer:
Khan M. Iftekharuddin, Old Dominion University, USAProfessor and Chair, Department of Electrical and Computer Engineering
http://www.eng.odu.edu/visionlab/
Program Committee:
- Vijayan Asari, University of Dayton, USA
- Azzedine Beghdadi, University Paris, 13, France
- Salim Bouzerdoum, University of Wollongong, Australia
- Ke Chen, University of Manchester, UK
- Yoonsuck Choe, Texas A&M University, USA
- Robert Kozma, University of Memphis, USA
- Minho Lee, Kyungpook National University, Korea
- Zicheng Liu, Microsoft Research, USA
- Bertram Shi, Hong Kong University of Science and Technology, Hong Kong
- Rufin VanRullen, CNRS, Toulouse, France
Submission instructions:
- Go to http://ieee-cis.org/conferences/ijcnn2015/upload.php to submit a paper to IJCNN 2015.
- Be sure to set the "Main research topic" to this special session. (The special sessions are found at the bottom of the list.)
Call for Papers FUZZ-IEEE Special Session "Applications of fuzzy set theory in clustering, classification and regression analysis"
Tools for regression analysis, clustering and classification can become very powerful if combined with the application of fuzzy set theory. The application of fuzzy set theory can be utilized for to estimate the relationship among variables in environments where uncertainty exists-though the uncertainty might be overlooked during data collection or for the simplification purpose. In real-world applications, this uncertainty may derive from the granularity of information for generalization purposes, the influence of human subjective judgement and partially available information, due to miss-recording or inaccurate measurements. One of the effective ways of capturing the useful information in such environments is with the application of fuzzy set theory.
This special session aims at discussing innovative approaches that utilize the application of fuzzy set theory for classification, clustering and regression analysis to engineering problems. Since the application clustering, classification and regression analysis is widely applicable in operations research and complex systems analysis; we invite all the related researchers from the fields of computer science and engineering, economy, finance, marketing, social sciences, and healthcare.
Topics of interest include, but are not limited to the theory and applications of:
Mehmet A. Orgun (Macquarie University, Australia) mehmet.orgun@mq.edu.au
Fikret Gürgen (Bogazici University, Turkey) gurgen@boun.edu.tr
Witold Pedrycz (University of Alberta, Canada) wpedrycz@ualberta.ca
Mashaalah Mashinchi (Kerman University, Iran) mashinchi@uk.ac.ir
Kusum Deep (Indian Institute of Technology, India) kusumfma@iitr.ernet.in
This special session aims at discussing innovative approaches that utilize the application of fuzzy set theory for classification, clustering and regression analysis to engineering problems. Since the application clustering, classification and regression analysis is widely applicable in operations research and complex systems analysis; we invite all the related researchers from the fields of computer science and engineering, economy, finance, marketing, social sciences, and healthcare.
Topics of interest include, but are not limited to the theory and applications of:
- Fuzzy regression analysis
- Fuzzy clustering
- Fuzzy classification
- Outlier detection methods which utilize fuzzy set theory
- Designing new similarity/model fitting measures for least squared fuzzy regression models
- The application of hybrid optimization for fuzzy regression, clustering or classification methods
Short biography of the organizer(s) and contact information:
Hadi Mashinchi (Simavita Pty Ltd, Australia) hmashinchi@simavita.com, hadimashinchi@gmail.comMehmet A. Orgun (Macquarie University, Australia) mehmet.orgun@mq.edu.au
Fikret Gürgen (Bogazici University, Turkey) gurgen@boun.edu.tr
Witold Pedrycz (University of Alberta, Canada) wpedrycz@ualberta.ca
Mashaalah Mashinchi (Kerman University, Iran) mashinchi@uk.ac.ir
Kusum Deep (Indian Institute of Technology, India) kusumfma@iitr.ernet.in
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy Applications in Wireless Sensor Networks"
Recent technological advances in Communication Information Systems (CIS) and especially in MEMS (Micro Electro-Mechanical Systems) have made the production and deployment of tiny, battery-powered nodes (units) which communicate over wireless links possible. A Wireless Sensor Network (WSN) is comprised of such units at varying numbers, where each single unit is connected to one or generally several units. An early deployment aim is to use these sensors in a passive way for indoor applications. These kinds of early nodes had the ability to sense scalar data such as temperature, humidity, pressure, and location of surrounding objects. However, recently available sensor nodes have higher computation capability, higher storage space, and better power solutions with respect to their predecessors and their primary usage area has shifted from indoor to outdoor appli! cations. With these advances, it is nowadays possible to see a sensor network deployed for daily activities such as environmental monitoring, healthcare monitoring, and security systems.
There are abundant situations where one can meet uncertainity in data in the wireless sensor network context. These situations can be shortly stated as node deployment, node clustering, data classification, optimization problems, and so on. The existing uncertainity in data may either result from the use of linguistic variables for data modeling, or may be the result of insufficient or untrusted data. Fuzzy sets and logic enable us to efficiently and flexibly handle uncertainities occuring in this sense. Moreover, the use of fuzzy logic in WSNs bridges the gap between simulations and real-world implementations the simulations are targeting.
We invite interested authors to submit their original and unpublished work to this special session. The main topics of this special session include, but are not limited to, the following:
Dr. Murat KARAKAYA received the B.S.E.E. degree in 1991 from the Turkish Military Academy (KHO), Ankara, Turkey, and the M.S. and Ph. D. degrees in Computer Engineering from the Bilkent University, Ankara, Turkey in 2000 and 2008, respectively. From 1992 to 2000, he worked as an engineer at different units in the Turkish Land Forces (KKK), Ankara, Turkey. From 2000 to 2005, he worked as an instructor and software engineer at the Turkish Military Academy (KHO), Ankara, Turkey. Then, during 2005-2008 he worked as IT Project Manager in the North Atlantic Treaty Organization (NATO) Brussels, Belgium. From 2008 to 2012, he worked as an instructor and software engineer at the Turkish Military School of Electronics, Communications and Information Systems (MEBS) and Turkish Military Academy (KHO), Ankara, Turkey. He joined the faculty of Atilim University in 2012 and is currently an Asstant Professor in the department of Computer Engineering, Ankara, Turkey. His research interests are natural computing methods and applications, sensor networks, peer-to-peer networks, and communications protocol design. He is currently an Editorial Board Member of the Journal of Telecommunications System & Management, a Scientific Committee Member of the International Symposium on Engineering, Artificial Intelligence and Applications (ISEAIA), an Organizing Committee Member of the International Conference and Business Expo on Wireless Communication, and a Technical Committee Member of the International Conference on Computer and Software Modeling. He has authored over 25 publications in international and national scientific Journals, book chapters and peer-reviewed conferences.
Muhsin CIVELEK (Computer Engineering Dept., Turkish Military Academy) (Short Bio Provided)
Muhsin Civelek is a lecturer and head of computer engineering department in Turkish Military Academy. His Phd. topic is Automated object classification in WMSN (Wireless Multimedia Sensor Network). He also participated in Fuzzy Object Oriented Multimedia Database Project which is administrated by Prof.Dr. Adnan YAZICI.
Seyyit Alper SERT (Computer Engineering Dept., Middle East Technical University)
Seyyit Alper SERT received the B.S.E.E. degree in 2004 from the Turkish Military Academy, Ankara, Turkey, and the M.S. degree in Computer Engineering from the Middle East Technical University, Ankara, Turkey in 2014. Starting from 2004, he has worked as an engineer at different units in the Turkish Land Forces Command, Ankara, Turkey. His PhD topic is the Design and Implementation of a Fuzzy Fusion-based framework for Surveillance Applications in WMSNs. Currently, he works as an engineer in the Turkish Land Forces command and also a part-time lecturer in the department of Computer Engineering, Middle East Technical University.
Dept. of Computer Engineering,
Atilim University, Ankara, Turkey
Tel : +90 312 586 8361
Fax : +90 312 586 8091
E-mail: murat.karakaya@atilim.edu.tr
There are abundant situations where one can meet uncertainity in data in the wireless sensor network context. These situations can be shortly stated as node deployment, node clustering, data classification, optimization problems, and so on. The existing uncertainity in data may either result from the use of linguistic variables for data modeling, or may be the result of insufficient or untrusted data. Fuzzy sets and logic enable us to efficiently and flexibly handle uncertainities occuring in this sense. Moreover, the use of fuzzy logic in WSNs bridges the gap between simulations and real-world implementations the simulations are targeting.
Objectives and topics:
This special session aims to offer a systematic overview of fuzzy data processing techniques and provides innovative approaches to handle various uncertainty issues in data processing and analysis in wireless sensor networks by applying fuzzy sets, fuzzy logic, fuzzy systems and other computationally intelligent techniques.We invite interested authors to submit their original and unpublished work to this special session. The main topics of this special session include, but are not limited to, the following:
- Fuzzy node clustering in wireless sensor networks,
- Fuzzy data classification in wireless sensor networks,
- Data uncertainity handling in wireless sensor networks,
- Tools and techniques for fuzzy data modeling in WNSs,
- Application of Genetic Fuzzy Systems for wireless sensor networks,
- Applying fuzzy logic for decision-making on WSNs,
- Fuzzy event detection in WSNs,
- Energy efficient fuzzy logic-based Intelligent WSNs,
- Uncertain issues in WSNs,
- Fuzzy decision-making in wireless sensor networks.
Short biography of the organizer(s) and contact information:
Asst.Prof. Dr. K. Murat Karakaya (Computer Engineering Dept., Atilim University)Dr. Murat KARAKAYA received the B.S.E.E. degree in 1991 from the Turkish Military Academy (KHO), Ankara, Turkey, and the M.S. and Ph. D. degrees in Computer Engineering from the Bilkent University, Ankara, Turkey in 2000 and 2008, respectively. From 1992 to 2000, he worked as an engineer at different units in the Turkish Land Forces (KKK), Ankara, Turkey. From 2000 to 2005, he worked as an instructor and software engineer at the Turkish Military Academy (KHO), Ankara, Turkey. Then, during 2005-2008 he worked as IT Project Manager in the North Atlantic Treaty Organization (NATO) Brussels, Belgium. From 2008 to 2012, he worked as an instructor and software engineer at the Turkish Military School of Electronics, Communications and Information Systems (MEBS) and Turkish Military Academy (KHO), Ankara, Turkey. He joined the faculty of Atilim University in 2012 and is currently an Asstant Professor in the department of Computer Engineering, Ankara, Turkey. His research interests are natural computing methods and applications, sensor networks, peer-to-peer networks, and communications protocol design. He is currently an Editorial Board Member of the Journal of Telecommunications System & Management, a Scientific Committee Member of the International Symposium on Engineering, Artificial Intelligence and Applications (ISEAIA), an Organizing Committee Member of the International Conference and Business Expo on Wireless Communication, and a Technical Committee Member of the International Conference on Computer and Software Modeling. He has authored over 25 publications in international and national scientific Journals, book chapters and peer-reviewed conferences.
Muhsin CIVELEK (Computer Engineering Dept., Turkish Military Academy) (Short Bio Provided)
Muhsin Civelek is a lecturer and head of computer engineering department in Turkish Military Academy. His Phd. topic is Automated object classification in WMSN (Wireless Multimedia Sensor Network). He also participated in Fuzzy Object Oriented Multimedia Database Project which is administrated by Prof.Dr. Adnan YAZICI.
Seyyit Alper SERT (Computer Engineering Dept., Middle East Technical University)
Seyyit Alper SERT received the B.S.E.E. degree in 2004 from the Turkish Military Academy, Ankara, Turkey, and the M.S. degree in Computer Engineering from the Middle East Technical University, Ankara, Turkey in 2014. Starting from 2004, he has worked as an engineer at different units in the Turkish Land Forces Command, Ankara, Turkey. His PhD topic is the Design and Implementation of a Fuzzy Fusion-based framework for Surveillance Applications in WMSNs. Currently, he works as an engineer in the Turkish Land Forces command and also a part-time lecturer in the department of Computer Engineering, Middle East Technical University.
Organizers Contact Information
Asst.Prof.Dr K. Murat KarakayaDept. of Computer Engineering,
Atilim University, Ankara, Turkey
Tel : +90 312 586 8361
Fax : +90 312 586 8091
E-mail: murat.karakaya@atilim.edu.tr
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy Consensus Measures & Analytics in Social Media: Risk and Uncertainty in Human Computer Interaction"
Introduction
Since last two decade substantial social interactions have witnessed a rapid surge of interest in Social Networks and media as strong computational vista to attract mass active users and also demonstrated significant impact in several breakthroughs in the form of political and techno-social events contemporary to either in Tunisia or Egypt and almost in most countries of the Middle East through Facebook, Twitter, and YouTube. Apart from social networks; social media such as YouTube and Flickr, social news like Twitter, or social bookmarking as Delicious have been significantly occupied voluminous positions and thus enhanced human computer interactions considerably. The scale of consensus measurement from social and political blog also has become a significant research agenda encompassing different business intelligence domain. Thus it has been observed that the ranges of social networking applications (starting from web 2.0 as the precursor) and recommender systems are providing relevant co-relational social information and their computational analysis reveals important socio-industrial breakthroughs. The arguments still continues that how dependable and trust-worthy resolutions are associated with such co relational analysis? As extendable uncertainty of expressing opinion under social network has been found and also situation awareness improvises human-computer interactions across social network as well.The culture of social networks create the necessity of different Wired and Wireless/mobile devices which are capable of creating; storing, processing, forwarding and sharing content that are socially connected in a new radical network architecture harnessing the social behaviour and mobility of the users. More and more human like intelligence usually captures the motif of social media application to raise the awareness of web users towards different technical temporal events. It has been also seen that social awareness through social network and media even could influence business users to have inferences on specific context. We may argue the actual scope of fuzzy logic to measure the effective social awareness propagated through social media and also could mark up that how far human –computer interaction could amalgamate the emerging social media and trend analysis towards fuzzy analytics. Thus, the pervasive and ubiquitous flavour of computation presents Social computing paradigms to encourage the cross-disciplinary research integration of different sciences such as computer science, engineering, biology, physics, anthropology, social sciences, been experienced under social computational paradigm and trend of generalized recommendation system that entails an ensemble of machine learning algorithms to generate an advice based on the partial knowledge garnered from Social Networks by tracking the reactions and opinions of crowd are emerged from WWW community. The motivation arises primarily from a need to stimulate and support the emergence of innovative ICT based platforms for grassroots Social Innovation, in effect providing socially, environmentally and economically sustainable approaches and solutions to tackle societal challenges. The session will also provide an excellent opportunity for scientists and engineers to present and discuss their latest scientific achievements and engineering approaches for both academic and industrial areas. The main goal of this special session is to improvise cross-disciplinary research discussions that are of relevance to new and novel fuzzy computing ideas, applications and experimental results in the area of all forms of social media and networks.
Topics of interest include (but are not limited to) the following:
- Social networks analysis using Fuzzy artifacts
- Social information retrieval and consensus
- Knowledge discovery from large social networks
- Fuzzy modeling in pervasive social network
- Social-inspired content creation and Computational intelligence
- Fuzzy behaviroal informatics and
- Business awareness modeling and new product launching in social network
- Human –Computer Interaction model using Fuzzy as a tool under social network
- Cognition under Social Media
- Opinion Mining and brand analysis
- Social networks analysis under temporal events
Deadline:
Paper submission deadline: February 8, 2015Notification of paper acceptance: March 23, 2
Camera-ready submission: April 21, 2015
Please submit your papers for this special session to both the organizers and
submission system (http://fuzzieee2015.org/)
If you have any question, please do not hesitate to contact the organizers:
Prof. Valentina E. Balas
“AUREL VLAICU”
UNIVERSITY OF ARAD,
ROMANIA
balas@drbalas.ro
Assoc. Prof. Soumya
Banerjee
Department of Computer
Science
Technology,
Campus, Jharkhand,
dr.soumya@ieee.org
Prof. Lachmi C. Jain
PhD, ME, BE(Hons),
Fellow Engineers
Lakhmi.jain@unisa.edu.au
Call for Papers FUZZ-IEEE Special Session "Adaptive fuzzy control for nonlinear & time-delay systems"
The aim of this special session is to present the state-of-the-art results in the area of adaptive, intelligent control theories and applications for researchers to get together in these areas. Adaptive control is a technique of applying some methods to obtain a model of the process and using this model to design a controller. Especially, fuzzy adaptive control has been an important area of active research. Significant developments have been seen, including theoretical success and practical design. One of the reasons for the rapid growth of fuzzy adaptive control is its ability to control plants with uncertainties during its operation.
The authors submitting papers to this special session can report about the recent and use of advanced techniques as well as algorithms of adaptive control. These include various robust techniques, performance enhancement techniques, techniques with less a-priori knowledge and nonlinear intelligent adaptive control techniques. To make this session more interesting stability and adaptive/intelligent control of nonlinear time-delay systems using fuzzy T-S methods and other advanced fuzzy computational techniques have been included to broaden the scope of the session. This special session aims to provide an opportunity for international researchers to share and review recent advances in the foundations, integration architectures and applications of hybrid and adaptive systems.
Topics of interest include, but are not limited to:
The authors submitting papers to this special session can report about the recent and use of advanced techniques as well as algorithms of adaptive control. These include various robust techniques, performance enhancement techniques, techniques with less a-priori knowledge and nonlinear intelligent adaptive control techniques. To make this session more interesting stability and adaptive/intelligent control of nonlinear time-delay systems using fuzzy T-S methods and other advanced fuzzy computational techniques have been included to broaden the scope of the session. This special session aims to provide an opportunity for international researchers to share and review recent advances in the foundations, integration architectures and applications of hybrid and adaptive systems.
Topics of interest include, but are not limited to:
- Fuzzy Self-Organizing Controllers
- Adaptive Fuzzy Control Design
- Fuzzy Applications• Fuzzy Modeling and Simulation
- Fuzzy Model Reference Learning Controller
- Hybrid adaptive fuzzy control• Robust adaptive fuzzy control
- Adaptive fuzzy sliding-mode control• Time-Delay Nonlinear Systems• Adaptive and learning control theory
- Adaptive control of processes
- Data based auto-tuning of the controller
- Estimation and identification and its application to control design
- Cooperative Control
- Hybrid Intelligent Control• Modeling and Simulation
- Knowledge based control systems• Nonlinear Systems
- Controller designs using LMIs.
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy Logic in Biometrics"
The SCOPE
The aim of this special session is to present interdisciplinary state-of-the-art results in the fields of Biometrics and Fuzzy Logic and to get together researchers that are active in these two areas.The PERSPECTIVE
In short, since the partitioning of comparisons space in genuine, imposter (and eventually undecidable pairs) is f-granular, giving a biometric decision using today’s state-of-the-art biometric systems means, in fact, giving a fuzzy biometric decision. In a simplified view, the cumulatives of the imposter and genuine score distributions are the fuzzy indicators of the two (or three) f-granules, whereas the point of equal error define a defuzzification in which the security risks (expressed as False Accept Rate) and user comfort risks (expressed as False Reject Rate) are balanced. When speed-precision balance is at stake, regardless the biometric traits used in today’s state-of-the-art biometric systems, analyzing biometric decision with fuzzy instruments and processing the biometric data with illustrates the direct connection and causality between imprecision and speed in defining digital identity – on the one hand, and the security or comfort risks assumed in these systems – on the other. From this perspective, the special session aims to provide an opportunity for international researchers in the field of Biometrics and Fuzzy Logic to share their original work or/and review the recent advances in better defining the fuzzy biometric digital identity toward minimizing the security risks and comfort risks Submissions reflecting both new theoretical advances and new highly experimental works using the largest publicly available biometric databases are especially encouraged.The TOPICS
Suggested topics of FLB special session include but are not limited to- Fuzzy techniques for iris / palm / face / eye / ear / fingerprint / behavioral:
- detection;
- segmentation;
- understanding (essential features detection / definition);
- encoding;
- template matching;
- template classification;
- Fuzzy scoring schemes for
- multi-sample based biometric systems;
- multi-classifier fusion in biometrics;
- multi-biometrics fusion;
- Crisp/Fuzzy Biometric Theory and Practice:
- Aging,
- Verification,
- Identification,
- Fusion,
- Fuzzy Extractors,
- Fuzzy Vaults,
Short biography of the organizer(s) and contact information:
For any questions, please contact Nicolaie Popescu-Bodorin (bodorin@ieee.org) & Valentina E. Balas (balas@drbalas.ro).Valentina E. Balas, PhD. Eng. in Automation,
IEEE Senior Member,
Professor of Engineering, Head of Intelligent Systems
Laboratory, University Aurel Vlaicu of Arad, ROMANIA,
Member of BISC, AMS, ACM, IEEE, EUSFLAT, IFSA
Member of EUSFLAT Board, Vice-President of IFSA (Awards)
http://ro.linkedin.com/pub/valentina-emilia-balas/
+0040-740-059151
http://drbalas.ro/
Nicolaie Popescu-Bodorin, PhD in Comp. Sci.,
IEEE Senior Member,
Technical Expert (Research & Development, Computer Science &
Engineering), Head of Applied Computer Science Testing
Laboratory, University of S-E Europe LUMINA, Bucharest,
ROMANIA, Member of BISC, AMS, ACM, IEEE and
IEEE Biometrics Council
http://ro.linkedin.com/in/bodorin/
+ 40 722882471 ,
http://lmrec.org/bodorin/
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Call for Papers FUZZ-IEEE Special Session "Fuzzy Systems for Physiological and Affective Computing"
Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions” (R. Picard, MIT Media Lab). AC seeks to facilitate research through the recognition and modelling of human affective states (e.g., happiness, sadness, etc.), cognition (e.g., frustration, boredom, etc.) and motivation, as represented by speech, facial expressions, physiological signals, and neurocognitive performance. Physiological Computing (PC) relates to more generic computational systems that incorporates and utilizes physiological information (e.g., as in computer-human interaction). Practical applications of AC and PC based systems seek to achieve a positive impact on our everyday lives by monitoring, recognising and acting on our physiological signals, speech, facial expressions and gestures. Integrating these sensing modalities into intelligent and pervasive computing systems will reveal a far richer picture of how our fleeting emotional responses, changing moods, feelings and sensations, such as pain, touch, tastes and smells, are a reaction to or influence how we implicitly or explicitly interact with the environment and increasingly the connected computing artefacts within.
The integration and use of AC and PC raise new challenges for signal processing, machine learning and Computational Intelligence (CI). Fuzzy systems provide a useful methodology for addressing research challenges in AC/PC, where data sources such as: body signals (e.g. heart rate, brain waves, skin conductance and respiration), facial features, speech and human kinematics are inherently noisy and uncertain. Fuzzy systems are well suited to model and represent vague and ambiguous linguistic notions of perceptions, impulses, feelings, desires and human cognitive states which can be both subject and context dependent. As we develop better ways of integrating affective and physiological data pervasively and in context of diverse data sources, it will create highly complex, dynamic and uncertain information rich scenarios. Here the use of hybrid fuzzy approaches combining other CI approaches such as evolutionary algorithms and neural computing techniques can be used to create novel self-learning affective computing systems that are able to more naturally interact and empathize with people, understand their physical and emotive states and automatically respond in beneficial and useful ways.
The Fuzzy Systems for Physiological and Affective Computing special session aims to bring together researchers to discuss how fuzzy logic approaches can be used to help solve challenging AC/PC problems, and develop ways of modelling and using physiological and affect (emotion) information to inspire new approaches and applications. We encourage high quality publications related to both academic and commercial research where topics of interest can include but are not limited to:
Faculty of Engineering and Computing
Coventry University
Priory Street, Coventry
CV1 5FB, UK
Email: faiyaz.doctor@coventry.ac.uk
http://www.coventry.ac.uk/research-bank/experts-directory/ec-staff/faiyaz-doctor/
Dr. Faiyaz Doctor is a Senior Lecturer in the Faculty of Engineering and Computing at Coventry University. He has previously worked jointly in industry and academia to develop novel artificial intelligence solutions for addressing real world problems related to smart environments, energy optimization, predictive analytics and decision support. His work has resulted in high profile innovation awards (Best KTP Regional Finalist 2011, Load Stafford Award for Innovation) and an international patent on improved approaches for data analysis and decision-making using hybrid neuro-fuzzy and type-2 fuzzy systems: WO/2009/141631. He has previously been a co-investigator on a Technology Strategy Board funded project on developing driver prediction models using artificial intelligence approaches in collaboration with Jaguar Land Rover Ltd. His research interests are in the area of computational intelligence with an emphasis on fuzzy logic, type-2 fuzzy logic and hybrid systems where his research has been applied to ambient intelligence, pervasive and affective computing, industrial automation and biomedical systems. Dr. Doctor has published over 30 papers in peer reviewed international journals, conferences and workshops. He currently chairs the IEEE Computational Intelligence Society’s Emergent Technologies ‘Affective Computing’ Task Force and has been co-organizer of the special session on Computational Intelligence for Physiological and Affective Computing (CIPAC) and co-chair at the special session on Brain and Physiological Computation for Affective Computing at the 2014 IEEE World Congress on Computational Intelligence. He has been a guest editor for the Journal of Ambient Intelligence and Smart Environments (JAISE), Thematic Issue on Affect Aware Ubiquitous Computing and serves as co-organiser of the International Workshop on Applications of Affective Computing in Intelligent Environments (ACIE) in conjunction with the International Conference on Intelligent Environments. He is also and member of the IEEE and IEEE Computational Intelligence Society.
School of Computer Science
University of Nottingham, UK
Email: christian.wagner@nottingham.ac.uk
http://ima.ac.uk/wagner
Christian Wagner is Transitional Fellow in Computer Science at the Horizon Digital Economy Research Institute and the School of Computer Science at the University of Nottingham, UK. He received his MSc in Robotics and Embedded Systems and his PhD in Computer Science at the University of Essex in 2006 and 2009 respectively. His main research interests are type-2 fuzzy logic, uncertainty handling and computational intelligence in general. He is specifically interested in the theoretical and practical aspects of general type-2 fuzzy logic and the application of fuzzy logic for approximate reasoning and the modeling of humans and human concepts such as emotions and language. The application of his research has been mainly focused on applications in robotics, ambient intelligence and most recently on digital economy and affective computing applications. He has published more than 40 papers and articles in international journals and at international conferences as well as three book chapters. In 2012 shared the Fuzz-IEEE best paper award. He also won the 2012 IEEE Transactions on Fuzzy Systems Outstanding paper award for the best paper published in 2010. He is chair of the IEEE CIS Task Force on Affective Computing. He has been a special session co-organizer and chair at the International Conference on Fuzzy Systems from 2009-2013. He has been an invited panelist in the “Future of type-2 fuzzy logic” panel held in London in 2010 and the publication chair of the UK Workshop on Computational Intelligence 2010. He has been a programme committee member of several international conferences and a reviewer for several international conferences and journals such as the IEEE Transactions on Fuzzy Systems and International Journal of Robotics and Automation. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the IEEE Computational Intelligence Society. Over several years, he has held placements with several companies, including SES (Astra), Sun Microsystems and GE Fanuc Automation.
GE Global Research, Niskayuna, NY, USA
Email: drwu09@gmail.com
https://sites.google.com/site/drwu09/
Dongrui Wu has been a Research Engineer in the Machine Learning Lab, GE Global Research, Niskayuna, NY, since 2010. He received a B.E in Automatic Control from the University of Science and Technology of China (USTC), Hefei, Anhui, China, in 2003, an M.Eng in Electrical and Computer Engineering from the National University of Singapore (NUS), Singapore, in 2005, and a PhD in Electrical Engineering from the University of Southern California (USC), Los Angeles, CA, in 2009. He was a Research Associate in the USC Institute for Creative Technologies and Signal Analysis and Interpretation Laboratory.
Dongrui Wu's research interests include affective computing, brain-computer interaction, computational intelligence, intelligent control, machine learning, optimization, and speech and physiological signal processing. Dongrui Wu has over 70 publications, including a book “Perceptual Computing” (with J.M. Mendel, Wiley-IEEE, 2010). He received IEEE International Conference on Fuzzy Systems Best Student Paper Award in 2005, IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award in 2012, IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, and North American Fuzzy Information Processing Society (NAFIPS) Early Career Award in 2014. He was one of 200 selected young researchers worldwide to attend the 1st Heidelberg (Abel/Fields/Turing) Laureate Forum in 2013, and is one of 30 selected U.S. engineers to attend the National Academy of Engineering 2015 German-American Frontiers of Engineering Symposia.
Dongrui Wu has worked on a broad range of projects from GE Capital, Healthcare, Transportation, Power and Water, and Oil and Gas. Two of his projects won the prestigious CIO 100 Awards in 2012 (TrueSense for GE Water) and 2014 (Fleet Optimizer for GE Capital), respectively. Additionally, he has received nine Above and Beyond Awards for outstanding performance. He is now Principal Investigator of a U.S. Army Research Lab funded project on machine learning for EEG based brain-computer interface, and a major contributor in GE Capital's stress testing team.
Dongrui Wu is an Associate Editor of IEEE Transactions on Fuzzy Systems and IEEE Transactions on Human-Machine Systems, and an Editorial Board member of PeerJ Computer Science and Journal of Applied Computer Science. He was a Guest Editor of the IEEE Computational Intelligence Magazine Special Issue on Computational Intelligence and Affective Computing. He is a Senior Member of IEEE, an Executive Committee member of the Association for the Advancement of Affective Computing (AAAC), and a member of IEEE Systems, Man and Cybernetics Society Brain-Machine Interface Systems Technical Committee, IEEE CIS Fuzzy Systems Technical Committee, Emergent Technologies Technical Committee, and Intelligent Systems Applications Technical Committee. He was Chair of the IEEE CIS Affective Computing Task Force in 2012, and has been a Vice Chair since 2013.
The integration and use of AC and PC raise new challenges for signal processing, machine learning and Computational Intelligence (CI). Fuzzy systems provide a useful methodology for addressing research challenges in AC/PC, where data sources such as: body signals (e.g. heart rate, brain waves, skin conductance and respiration), facial features, speech and human kinematics are inherently noisy and uncertain. Fuzzy systems are well suited to model and represent vague and ambiguous linguistic notions of perceptions, impulses, feelings, desires and human cognitive states which can be both subject and context dependent. As we develop better ways of integrating affective and physiological data pervasively and in context of diverse data sources, it will create highly complex, dynamic and uncertain information rich scenarios. Here the use of hybrid fuzzy approaches combining other CI approaches such as evolutionary algorithms and neural computing techniques can be used to create novel self-learning affective computing systems that are able to more naturally interact and empathize with people, understand their physical and emotive states and automatically respond in beneficial and useful ways.
The Fuzzy Systems for Physiological and Affective Computing special session aims to bring together researchers to discuss how fuzzy logic approaches can be used to help solve challenging AC/PC problems, and develop ways of modelling and using physiological and affect (emotion) information to inspire new approaches and applications. We encourage high quality publications related to both academic and commercial research where topics of interest can include but are not limited to:
- Models of emotion and physiological information
- Classifiers for physiological information
- Applications based on/around physiological information
- Fuzzy set and system based architectures for processing emotions and other affective states
- Automatic emotion recognition & synthesis from physiological signals, facial expressions, body language, speech, or neurocognitive performance
- Multimodal sensor fusion for emotional recognition
- Emotion mining from texts, images, or videos
- Affective interaction with virtual agents and robots based on fuzzy systems
- Physiological and emotion driven control.
- Applications of affective computing in interactive learning, affective gaming, personalized robotics, virtual reality, social networking, smart environments, healthcare and behavioral informatics, etc.
Keywords:
Affective computing, physiological computing, classification of physiological signals, affective interaction, emotion modeling, emotion recognition/synthesis, emotion mining, fuzzy systems, computational intelligenceShort biography of the organizer(s) and contact information:
The organizers have a track record at organizing and chairing special sessions at a number of previous IEEE conferences, including WCCI 2014, Fuzz-IEEE 2013, WCCI 2012, FUZZ-IEEE 2011, WCCI 2010 and FUZZ-IEEE 2009.Dr Faiyaz Doctor
Senior Lecturer in ComputingFaculty of Engineering and Computing
Coventry University
Priory Street, Coventry
CV1 5FB, UK
Email: faiyaz.doctor@coventry.ac.uk
http://www.coventry.ac.uk/research-bank/experts-directory/ec-staff/faiyaz-doctor/
Dr. Faiyaz Doctor is a Senior Lecturer in the Faculty of Engineering and Computing at Coventry University. He has previously worked jointly in industry and academia to develop novel artificial intelligence solutions for addressing real world problems related to smart environments, energy optimization, predictive analytics and decision support. His work has resulted in high profile innovation awards (Best KTP Regional Finalist 2011, Load Stafford Award for Innovation) and an international patent on improved approaches for data analysis and decision-making using hybrid neuro-fuzzy and type-2 fuzzy systems: WO/2009/141631. He has previously been a co-investigator on a Technology Strategy Board funded project on developing driver prediction models using artificial intelligence approaches in collaboration with Jaguar Land Rover Ltd. His research interests are in the area of computational intelligence with an emphasis on fuzzy logic, type-2 fuzzy logic and hybrid systems where his research has been applied to ambient intelligence, pervasive and affective computing, industrial automation and biomedical systems. Dr. Doctor has published over 30 papers in peer reviewed international journals, conferences and workshops. He currently chairs the IEEE Computational Intelligence Society’s Emergent Technologies ‘Affective Computing’ Task Force and has been co-organizer of the special session on Computational Intelligence for Physiological and Affective Computing (CIPAC) and co-chair at the special session on Brain and Physiological Computation for Affective Computing at the 2014 IEEE World Congress on Computational Intelligence. He has been a guest editor for the Journal of Ambient Intelligence and Smart Environments (JAISE), Thematic Issue on Affect Aware Ubiquitous Computing and serves as co-organiser of the International Workshop on Applications of Affective Computing in Intelligent Environments (ACIE) in conjunction with the International Conference on Intelligent Environments. He is also and member of the IEEE and IEEE Computational Intelligence Society.
Dr Christian Wagner
Horizon Digital Economy Institute & Intelligent Modeling and Analysis GroupSchool of Computer Science
University of Nottingham, UK
Email: christian.wagner@nottingham.ac.uk
http://ima.ac.uk/wagner
Christian Wagner is Transitional Fellow in Computer Science at the Horizon Digital Economy Research Institute and the School of Computer Science at the University of Nottingham, UK. He received his MSc in Robotics and Embedded Systems and his PhD in Computer Science at the University of Essex in 2006 and 2009 respectively. His main research interests are type-2 fuzzy logic, uncertainty handling and computational intelligence in general. He is specifically interested in the theoretical and practical aspects of general type-2 fuzzy logic and the application of fuzzy logic for approximate reasoning and the modeling of humans and human concepts such as emotions and language. The application of his research has been mainly focused on applications in robotics, ambient intelligence and most recently on digital economy and affective computing applications. He has published more than 40 papers and articles in international journals and at international conferences as well as three book chapters. In 2012 shared the Fuzz-IEEE best paper award. He also won the 2012 IEEE Transactions on Fuzzy Systems Outstanding paper award for the best paper published in 2010. He is chair of the IEEE CIS Task Force on Affective Computing. He has been a special session co-organizer and chair at the International Conference on Fuzzy Systems from 2009-2013. He has been an invited panelist in the “Future of type-2 fuzzy logic” panel held in London in 2010 and the publication chair of the UK Workshop on Computational Intelligence 2010. He has been a programme committee member of several international conferences and a reviewer for several international conferences and journals such as the IEEE Transactions on Fuzzy Systems and International Journal of Robotics and Automation. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the IEEE Computational Intelligence Society. Over several years, he has held placements with several companies, including SES (Astra), Sun Microsystems and GE Fanuc Automation.
Dr Dongrui Wu
Machine Learning LabGE Global Research, Niskayuna, NY, USA
Email: drwu09@gmail.com
https://sites.google.com/site/drwu09/
Dongrui Wu has been a Research Engineer in the Machine Learning Lab, GE Global Research, Niskayuna, NY, since 2010. He received a B.E in Automatic Control from the University of Science and Technology of China (USTC), Hefei, Anhui, China, in 2003, an M.Eng in Electrical and Computer Engineering from the National University of Singapore (NUS), Singapore, in 2005, and a PhD in Electrical Engineering from the University of Southern California (USC), Los Angeles, CA, in 2009. He was a Research Associate in the USC Institute for Creative Technologies and Signal Analysis and Interpretation Laboratory.
Dongrui Wu's research interests include affective computing, brain-computer interaction, computational intelligence, intelligent control, machine learning, optimization, and speech and physiological signal processing. Dongrui Wu has over 70 publications, including a book “Perceptual Computing” (with J.M. Mendel, Wiley-IEEE, 2010). He received IEEE International Conference on Fuzzy Systems Best Student Paper Award in 2005, IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award in 2012, IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, and North American Fuzzy Information Processing Society (NAFIPS) Early Career Award in 2014. He was one of 200 selected young researchers worldwide to attend the 1st Heidelberg (Abel/Fields/Turing) Laureate Forum in 2013, and is one of 30 selected U.S. engineers to attend the National Academy of Engineering 2015 German-American Frontiers of Engineering Symposia.
Dongrui Wu has worked on a broad range of projects from GE Capital, Healthcare, Transportation, Power and Water, and Oil and Gas. Two of his projects won the prestigious CIO 100 Awards in 2012 (TrueSense for GE Water) and 2014 (Fleet Optimizer for GE Capital), respectively. Additionally, he has received nine Above and Beyond Awards for outstanding performance. He is now Principal Investigator of a U.S. Army Research Lab funded project on machine learning for EEG based brain-computer interface, and a major contributor in GE Capital's stress testing team.
Dongrui Wu is an Associate Editor of IEEE Transactions on Fuzzy Systems and IEEE Transactions on Human-Machine Systems, and an Editorial Board member of PeerJ Computer Science and Journal of Applied Computer Science. He was a Guest Editor of the IEEE Computational Intelligence Magazine Special Issue on Computational Intelligence and Affective Computing. He is a Senior Member of IEEE, an Executive Committee member of the Association for the Advancement of Affective Computing (AAAC), and a member of IEEE Systems, Man and Cybernetics Society Brain-Machine Interface Systems Technical Committee, IEEE CIS Fuzzy Systems Technical Committee, Emergent Technologies Technical Committee, and Intelligent Systems Applications Technical Committee. He was Chair of the IEEE CIS Affective Computing Task Force in 2012, and has been a Vice Chair since 2013.
Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.Tuesday, 2 December 2014
Call for Papers FUZZ-IEEE Special Session "Handling Uncertainties in Big Data by Fuzzy Systems"
Description
The volume, variety, velocity, veracity and value of data and data communication are increasing exponentially. The “Five Vs” are the key features of big data, and also the causes of inherent uncertainties in the representation, processing, and analysis of big data. Big data, by its nature, contains bias, noise and abnormality, which may not be a correct characterisation of the actual system that it is meant to represent. Big data also contains a significant amount of unstructured, uncertain and imprecise data. For example, social media data is inherently uncertain.Fuzzy sets, logic and systems enable us to efficiently and flexibly handle uncertainties in big data, thus enabling it to better satisfy the needs of real world big data applications and improve the quality of organizational data-based decisions. Successful developments in this area have appeared in many different aspects, such as fuzzy data analysis technique and fuzzy data inference methods. In particular, the linguistic representation and processing power of fuzzy logic is a unique tool for bridging symbolic intelligence and numerical intelligence gracefully. Hence, fuzzy logic can help to extend transfer learning in big data from the numerical data level to the knowledge rule level. It is therefore instructive and vital to gather current trends and provide a high quality forum for the theoretical research results and practical development of fuzzy logic and systems in handling uncertainties in big data.
The volume, variety, velocity, veracity and value of data and data communication are increasing exponentially. The “Five Vs” are the key features of big data, and also the causes of inherent uncertainties in the representation, processing, and analysis of big data. Big data, by its nature, contains bias, noise and abnormality, which may not be a correct characterisation of the actual system that it is meant to represent. Big data also contains a significant amount of unstructured, uncertain and imprecise data. For example, social media data is inherently uncertain.
Fuzzy sets, logic and systems enable us to efficiently and flexibly handle uncertainties in big data, thus enabling it to better satisfy the needs of real world big data applications and improve the quality of organizational data-based decisions. Successful developments in this area have appeared in many different aspects, such as fuzzy data analysis technique and fuzzy data inference methods. In particular, the linguistic representation and processing power of fuzzy logic is a unique tool for bridging symbolic intelligence and numerical intelligence gracefully. Hence, fuzzy logic can help to extend transfer learning in big data from the numerical data level to the knowledge rule level. It is therefore instructive and vital to gather current trends and provide a high quality forum for the theoretical research results and practical development of fuzzy logic and systems in handling uncertainties in big data.
Objective and topics
This special session aims to offer a systematic overview of this new field and provides innovative approaches to handle various uncertainty issues in big data presentation, processing and analysing by applying fuzzy sets, fuzzy logic, fuzzy systems and other computational intelligent techniques.We invite interested authors to submit their original and unpublished work to this special session. The main topics of this special session include, but are not limited to, the following:
- Fuzzy rule-based knowledge representation in big data processing
- Information uncertainty handling in big data processing
- Unstructured big data visualization
- Uncertain information and knowledge modeling in big data sets
- Tools and techniques for big data analytics in uncertain environments
- Context-aware big data processing
- Fuzzy systems for big data analytics
- Uncertain data presentation in big data systems
- Uncertain issues in data-driven decision support systems
- Uncertain issues in recommender systems in big data environments
- Uncertain issues in cloud computing
- Uncertain issues in social network and web services
Short biography of the organizer(s) and contact information:
Dr. Jie Lu is currently the Associate Dean (Research) in the Faculty of Engineering & IT, and the Director of the Decision Systems and e-Service Intelligence (DeSI) Research Laboratory in the Centre for Quantum Computation & Intelligent Systems at the University of Technology, Sydney (UTS). Prior to this, she served as the Head of the School of Software at UTS. Her main research interests lie in the area of decision support systems, fuzzy information processing, recommender systems and e-Service intelligence. She has published five research books and 350 papers in refereed journals and conference proceedings. She has won six Australian Research Council (ARC) discovery grants, and 10 other research grants. She received the first UTS Research Excellence Medal for Teaching and Research Integration in 2010. She is the Editor-In-Chief for Knowledge-Based Systems (Elsevier), Editor-In-Chief of International Journal on Computational Intelligence Systems (Atlantis), Associate Editor for IEEE Transactions on Fuzzy Systems, Editor for a book series on Intelligent Information Systems (World Scientific), and has served as a guest editor of seven special issues for international journals, as well as having delivered numerous keynote speeches at international conferences.Dr Chin-Teng Lin is the Provost, Chair Professor of Electrical and Computer Engineering, and Director of Brain Research Center, National Chiao Tung University. Dr. Lin was elevated to be an IEEE Fellow and IFSA Fellow for his contributions to biologically inspired information systems in 2005 and 2013, respectively. He served on the Board of Governors at IEEE Circuits and Systems (CAS) Society in 2005-2008, IEEE Systems, Man, Cybernetics (SMC) Society in 2003-2005, IEEE Computational Intelligence Society in 2008-2010, Chair of IEEE Taipei Section in 2009-2010. Dr. Lin was the Distinguished Lecturer of IEEE CAS Society from 2003 to 2005. He served as the Deputy Editor-in-Chief of IEEE Transactions on Circuits and Systems-II in 2006-2008 and serve as the Editor-in-Chief of IEEE Transactions on Fuzzy Systems in 2011-2016. Dr. Lin was the General Chair of FUZZ-IEEE2011, Program Chair of IEEE International Conference on Systems, Man, and Cybernetics in 2005. Dr. Lin is the coauthor of Neural Fuzzy Systems (Prentice-Hall), and the author of Neural Fuzzy Control Systems with Structure and Parameter Learning (World Scientific). He has published over 170 journal papers in the areas of neural networks, fuzzy systems, multimedia hardware/software, and cognitive neuro-engineering, including approximately 85 IEEE journal papers. Dr. Lin is a member of Tau Beta Pi, Eta Kappa Nu, and Phi Kappa Phi honorary societies. He has been the member of Board of Government (BoG) of Asia Pacific Neural Network Assembly (APNNA) since 2000; and the Council member of International Fuzzy System Association (IFSA) since 2000. Dr. Lin was the President of APNNA for 2004-2005. He has won the Outstanding Research Award granted by National Science Council (NSC), Taiwan, since 1997 to present, the Outstanding Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE) in 1997, the Outstanding Engineering Professor Award granted by the Chinese Institute of Engineering in 2000, and the 2002 Taiwan Outstanding Information-Technology Expert Award. Dr. Lin was also elected to be one of the 38th Ten Outstanding Rising Stars in Taiwan (2000). The main axis in Dr. Lin’s research career is to pursue for the biological-inspired intelligent systems, including algorithm development and system design. The research interests cover the basic circuitry level, to signal and information level, and to the system level, either from the biological or engineering point of views. The short-term target system is brain machine interface and the long-term goal is on brain-like intelligent system.
Dr. Farookh Hussain is a Senior Lecturer at the School of Software in the Faculty of Engineering and Information Technology. Additionally he is a member of the Decision Systems and e-Service Intelligence Research Laboratory in the Centre for Quantum Computation & Intelligent Systems at the University of Technology, Sydney (UTS). He received his PhD from Curtin University of Technology, Australia, in 2007. His main research interests lie in the area of engineering intelligent Cloud Services, trust and reputation management and modeling for web-based services. He is particularly interested in the making use of Soft Computing techniques such as Fuzzy Logic and Neural Network for engineering intelligent Cloud Services. He has published four research books and over 100 papers in refereed journals and conference proceedings, including IEEE Intelligent Systems, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, and The Computer Journal. He has delivered two keynote speeches at international conferences.
Dr. Vahid Behbood is Lecturer at the School of Software in the Faculty of Engineering and Information Technology. Additionally he is a member of the Decision Systems and e-Service Intelligence Research Laboratory in the Centre for Quantum Computation & Intelligent Systems at the University of Technology, Sydney (UTS). He received the Ph.D. degree in software engineering from the University of Technology Sydney, Sydney, Australia. His research interests include machine learning, fuzzy sets and systems, warning systems, and big data analytics. He has published over 20 papers in journals and conferences.
Dr. Guangquan Zhang is an associate professor at the Centre for Quantum Computation and Intelligent Systems (QCIS), Faculty of Engineering and Information Technology at the University of Technology, Sydney (UTS), Australia. He has a PhD in Applied Mathematics from Curtin University of Technology, Australia. He was with the Department of Mathematics, Hebei University, China, from 1979 to 1997, as a Lecturer, Associate Professor and Professor. His main research interests lie in the area of prediction modelling, multi-objective, bilevel and group decision making, decision support system tools, fuzzy measure, fuzzy optimization and uncertain information processing. He has published four monographs, four reference books and over 350 papers in refereed journals and conference proceedings including IEEE Transactions on Fuzzy Systems, IEEE Transactions on Industrial Informatics and Artificial Intelligence. He has won five Australian Research Council (ARC) discovery grants and many other research grants.
Contact Information
Dr Jie Lu Professor Head, School of Software Director of Decision Systems & e-Service Intelligence Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology, University of Technology, Sydney P.O. Box 123, Broadway, NSW 2007, Australia Phone: +61-2-95141838 Fax: +61-2-95144535 Email: jielu@it.uts.edu.au http://www-staff.it.uts.edu.au/~jielu/ http://decide.it.uts.edu.au/Important Dates
- Paper submission February 8, 2015
- Notification of acceptance for papers March 23, 2015
- Camera-ready paper submission April 21, 2015
- Early registration deadline April 23, 2015
- Conference August 2-5, 2015
Submission of the papers
Please submit your papers for this special session to both the organizers and conference online submission system (http://fuzzieee2015.org/) by indicating the title of the special session.
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