Wednesday, 21 June 2017

Deadline extension -- Special Issue on Spiking Neural Networks for Cognitive and Developmental Systems, IEEE TCDS

It is my honor to cordially invite you to submit papers to the Special Issue on Spiking Neural Networks for Cognitive and Developmental Systems in IEEE Transactions on Cognitive and Developmental Systems journal.

The deadline for submission of papers has been extended to 10th of August 2017. The reviewing process takes about 3-4 weeks. Accepted papers will be published by the end of 2017.

The new schedule for this special issue is as follows:

10 August 2017 Deadline for manuscript submission
10 September 2017 Notification of authors
10 October 2017 Deadline for submission of revised manuscripts
31 October 2017 Final decisions
End of 2017 – Special Issue Publication in IEEE TCDS

Please refer to: http://cis.ieee.org/ieee-transactions-on-cognitive-and-developmental-systems.html for further information about the TCDS journal.

Link to special issue of SNN: http://bit.ly/2sQlc1Y

SUBMISSION

Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://goo.gl/0eMHUd and submissions should be made through the IEEE TCDS Manuscript center at https://mc.manuscriptcentral.com/tcds-ieee selecting the category “SI: Spiking Neural Networks”.

AIM AND SCOPE

Spiking Neural Networks (SNN) are a rapidly emerging means of neural information processing, drawing inspiration from brain processes. They have the potential to advance technologies and techniques in fields as diverse as medicine, finance, computing, and indeed any field that involves complex temporal or spatiotemporal data. SNN, as the third generation of neural networks, can operate on noisy data, in changing environments at low power and with high effectiveness. Due to their basis in biological neural networks, SNN research is strongly positioned to benefit from advances made in the fields of molecular, evolutionary and cognitive neuroscience.
There is presently considerable interest in this topic. We believe that this area is quickly establishing itself as an effective alternative to traditional machine learning technologies, and the interest in this area of research is growing rapidly.

This special issue aims to bring together research works of contemporary areas of SNN, including theoretical, computational, application-oriented, experimental studies, and emerging technologies such as neuromorphic hardware.
THEMES

Topics relevant to this special issue include, but are not limited to:
·         Theory of SNN
·         Learning algorithms for SNN, including Deep Learning
·         Computation with and within SNN
·         Theory or practice in biologically realistic neural simulation or biomimetic models
·         Big data and stream data processing in SNN
·         Multiple sensor networks data processing in SNN
·         Neuromorphic hardware systems and applications
·         Optimization of SNN
·         SNN models of cognitive development
·         Information coding for SNN
·         SNN applications in neuroinformatics, bioinformatics, medicine and ecology
·         SNN in BCI
·         SNN in neuro-robotic
·         Any other topics relating to Spiking Neural Networks, their theory, or applications
Thus, the special issue reports state-of-the-art approaches, recent advances and the potential of SNN.
Editors

Professor Nikola Kasabov, Knowledge Engineering & Discovery Research Institute (KEDRI), Auckland University of Technology, New Zealand (nkasabov@aut.ac.nz).
N. Kasabov received MSc degree in Electrical Eng., spec. Computer Science, in 1971 and Ph.D. degree in Mathematical Sciences in 1975 from the Technical University in Sofia. He has published over 550 works in the areas of intelligent systems, neural networks, connectionist and hybrid connectionist systems, fuzzy systems, expert systems, bioinformatics, neuroinformatics. He is a Fellow of IEEE, Fellow of the Royal Society of New Zealand and a Distinguished Visiting Fellow of the RAE UK. He is a Past President of the International Neural Network Society (INNS) and the Asia Pacific Neural Network Assembly (APNNA) and currently - a member of the INNS and APNNA Governing Boards. Kasabov is the Director of the Knowledge Engineering and Discovery Research Institute (www.kedri.aut.ac.nz) and Personal Chair of Knowledge Engineering in Auckland University of Technology, New Zealand.

Dr Josafath I Espinosa-Ramos, Knowledge Engineering & Discovery Research Institute (KEDRI), Auckland University of Technology, New Zealand (josafath.ramos@aut.ac.nz)
Dr. Josafath Israel Espinosa Ramos holds a MSc in cybernetics from La Salle University, Mexico City, and a PhD in computer science at the Centre for Computing Research of the National Polytechnic Institute, Mexico City. His main research interests are in the areas of computational neuroscience, evolutionary algorithms and machine learning. Currently, he is working as a research officer at the Knowledge Engineering and Discovery Research Institute (KEDRI) in the Auckland University of Technology, New Zealand, applying spiking neural networks to model multisensory and multivariate streaming data. The aim of this research is analyzing the spatial and temporal relationships among the variables that describe the dynamics of a sensor network.

ASSOC Prof André Grüning, Department of Computing, University of Surrey, Guildford, Surrey (a.gruning@surrey.ac.uk).
Dr. Andre Grüning is a senior lecturer (associate professor) in the Department of Computer Science at the University of Surrey. His research focuses on learning algorithms for Spiking Neural Networks. He currently leads the Task “Functional plasticity for multi-compartment neurons” within the Human Brain Project.  Previously he held research positions in Computational Neuroscience Group at SISSA, Italy, in cognitive psychology at the University of Warwick and in Complex Systems at the Max-Planck-Institute for Mathematics in Sciences. He is a board member of the ENNS. Andre strongly believes that research into Spiking Neural Networks will both boost our understand of how the brain works and help us build more powerful computational devices.

Maryam Doborjeh, Knowledge Engineering & Discovery Research Institute (KEDRI), Auckland University of Technology, New Zealand (mgholami@aut.ac.nz)
M. G. Doborjeh obtained her MSc degree in Computer Science from Easter Mediterranean University, North Cyprus in 2012.  She is currently a PhD student and research assistant at the Knowledge Engineering and Discovery Research Institute (KEDRI) in the Auckland University of Technology, New Zealand. Her main research area is developing methods for the analysis of dynamic patterns in spatiotemporal data (such as EEG and fMRI data) using spiking neural network architecture.

Dr Joseph Chrol-Cannon, UK. (Joseph.Chrol-Cannon@surrey.ac.uk)
Dr. Joseph Chrol-Cannon received a PhD degree in Computer Science from the University of Surrey in 2016. The topic of his thesis was the application and analysis of synaptic plasticity in spiking networks for machine learning pattern recognition tasks. Since 2015, as a research fellow, he has been investigating spiking neuron encoding. Currently, he is working at the Surrey Technology Center, applying neural network learning in the area of finance.

Tuesday, 20 June 2017

Call for Nominations / Applications for the position of Editor-in-Chief of the IEEE Transactions on Games


The IEEE Transactions on Computational Intelligence and AI in Games (TCIAIG) will be renamed the IEEE Transactions on Games (TG) in January 2018.  It will have a very succinct scope: The IEEE Transactions on Games publishes original high-quality articles covering scientific, technical, and engineering aspects of games.   TG is a publication of the IEEE Computational Intelligence Society (CIS) with financial co-sponsorship from the IEEE Sensors Council and the IEEE Consumer Electronics Society. It was first published as TCIAIG in 2009. Details about the current state of this publication can be found at: http://cis.ieee.org/ieee-transactions-on-computational-intelligence-and-ai-in-games.html.

As a result of the name and scope changes, a new Editor-in-Chief needs to be appointed. The IEEE CIS Executive Committee has formed an Adhoc Search Committee to seek suitable candidates to serve as the next EiC of TG. The Search Committee solicits nominations/applications for this position. Nominees/applicants should be dedicated volunteers with outstanding research profiles and extensive editorial experience. The nomination/application package should include complete CV along with  a separate description (max 300 words/topic) on each of the following items: Vision Statement; Editorial Experience; Summary of publishing experience in IEEE journals/magazines; IEEE Volunteer Experience; Institutional Support; Current service and administrative commitments; Networking with the Community; Challenges, if any, faced by the publication, and how to deal with them (an itemized list of issues and possible solutions); Why does the candidate consider himself/herself fit for this position? 

The nomination/application package should be emailed as a single PDF to kellerj@missouri.edu by August 15, 2017.   


Jim Keller, Chair of the Search Committee
Nik Pal, CIS
Simon Lucas, CIS
Sanaz Mostaghim, CIS
Ricardo Gutierrez-Osuna, Sensors Council
John Vig, Sensors Council
Samad Ahmadi, Consumer Electronics Society


Wednesday, 14 June 2017

CFP: 16th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2017)


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Cancun, Mexico
Dec 18 – 21, 2017
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ICMLA 2017 aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning (ML).
The conference provides a leading international forum for the dissemination of original research in ML, with emphasis on applications as well as novel algorithms and systems. Following the success of previous ICMLA conferences, the conference aims to attract researchers and application developers from a wide range of ML related areas, and the recent emergence of Big Data processing brings an urgent need for machine learning to address these new challenges. The conference will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, are especially encouraged. The technical program will consist of, but is not limited to, the following topics of interest:

Statistical learning; Neural network learning; Learning through fuzzy logic; Learning through evolution; Reinforcement learning; Multi-strategy learning; Cooperative learning; Planning and learning; Multi-agent learning; Online and incremental learning; Scalability of learning algorithms; Inductive learning; Inductive logic programming; Bayesian networks; Support vector machines; Case-based reasoning; Grammatical inference; Knowledge acquisition and learning; Knowledge discovery in databases; Knowledge intensive learning; Knowledge representation and reasoning  ; Machine learning for information retrieval; Learning through mobile data mining; Machine learning for web navigation & mining; Text and multimedia mining; Feature extraction and classification; Distributed and parallel learning algorithms and applications; Computational learning theory; Theories and models for plausible reasoning; Cognitive modeling; Hybrid learning algorithms; Multi-lingual knowledge acquisition and representation

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Applications of machine learning in:

Medicine and health informatics; Bioinformatics and systems biology; Industrial and engineering applications; Security; Smart cities; Game playing and problem solving; Intelligent virtual environments; Economics; business and forecasting.

The conference will include a number of interesting keynote plenary talks, which will be announced on the conference web site as arrangements are finalized. Previous invited speakers included numerous fellows of IEEE, AMIA, AAAS, AAAI, etc. Prospective authors are invited to submit eight pages manuscript describing original work. The manuscript has to be written in English and in PDF format. Please visit the conference website for details: http://www.icmla-conference.org/icmla17/

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Key dates:

Paper Submission Deadline: Main Conference:   July 6, 2017
Special Sessions/Workshops/Challenges:        August 6, 2017
Notification of Acceptance:                         September 9, 2017
Camera-ready Papers:                                        October 1, 2017

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Organizing Committee:

General Chair:
Bill Chen (Wayne State University)

Conference Chair:
Bo Luo (The University of Kansas)

Program Co-Chairs:
Vasile Palade (Conventry University)
Feng Luo (Clemson University)

Workshop and Special Session Chair:
Yanjie Fu (Missouri University of Science and Technology)

Publicity Chair:
Roozbeh Razavi-Far (University of Windsor)
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Thursday, 8 June 2017

IEEE Transactions on Fuzzy System, Volume 25, Issue 3, June 2017

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=91#

1. A Profit Maximizing Solid Transportation Model Under a Rough Interval Approach
Author(s): A. Das, U. Kumar Bera and M. Maiti
Page(s): 485-498
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7456282&isnumber=7936677

2. Design of State Feedback Adaptive Fuzzy Controllers for Second-Order Systems Using a Frequency Stability Criterion
Author(s): K. Wiktorowicz
Page(s): 499-510
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468497&isnumber=7936677

3. Dynamic Output-Feedback Dissipative Control for T–S Fuzzy Systems With Time-Varying Input Delay and Output Constraints
Author(s): H. D. Choi, C. K. Ahn, P. Shi, L. Wu and M. T. Lim
Page(s): 511-526
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468469&isnumber=7936677

4. Adaptive Predefined Performance Control for MIMO Systems With Unknown Direction via Generalized Fuzzy Hyperbolic Model
Author(s): L. Liu, Z. Wang, Z. Huang and H. Zhang
Page(s): 527-542
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468492&isnumber=7936677

5. Revisiting Fuzzy Set and Fuzzy Arithmetic Operators and Constructing New Operators in the Land of Probabilistic Linguistic Computing
Author(s): S. C. Ngan
Page(s): 543-555
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468457&isnumber=7936677

6. Asymptotic Fuzzy Tracking Control for a Class of Stochastic Strict-Feedback Systems
Author(s): C. Chen, Z. Liu, Y. Zhang, C. L. P. Chen and S. Xie
Page(s): 556-568
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468488&isnumber=7936677

7. Approaches to T–S Fuzzy-Affine-Model-Based Reliable Output Feedback Control for Nonlinear Itô Stochastic Systems
Author(s): Y. Wei, J. Qiu, H. K. Lam and L. Wu
Page(s): 569-583
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468467&isnumber=7936677

8. Pixel Modeling Using Histograms Based on Fuzzy Partitions for Dynamic Background Subtraction
Author(s): Z. Zeng, J. Jia, D. Yu, Y. Chen and Z. Zhu
Page(s): 584-593
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468482&isnumber=7936677

9. Varying Spread Fuzzy Regression for Affective Quality Estimation
Author(s): K. Y. Chan and U. Engelke
Page(s): 594-613
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468477&isnumber=7936677

10. Ranking of Multidimensional Uncertain Information Based on Metrics on the Fuzzy Ellipsoid Number Space
Author(s): G. Wang and Y. Li
Page(s): 614-626
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468496&isnumber=7936677

11. The Spatial Disaggregation Problem: Simulating Reasoning Using a Fuzzy Inference System
Author(s): J. Verstraete
Page(s): 627-641
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7469335&isnumber=7936677

12. Adaptive Fuzzy Backstepping Tracking Control for Strict-Feedback Systems With Input Delay
Author(s): H. Li, L. Wang, H. Du and A. Boulkroune
Page(s): 642-652
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7469360&isnumber=7936677

13. Dynamic Output Feedback-Predictive Control of a Takagi–Sugeno Model With Bounded Disturbance
Author(s): B. Ding and H. Pan
Page(s): 653-667
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7482722&isnumber=7936677

14. Command-Filtered-Based Fuzzy Adaptive Control Design for MIMO-Switched Nonstrict-Feedback Nonlinear Systems
Author(s): Y. Li and S. Tong
Page(s): 668-681
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7482820&isnumber=7936677

15. Type-2 Fuzzy Alpha-Cuts
Author(s): H. Hamrawi, S. Coupland and R. John
Page(s): 682-692
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7482819&isnumber=7936677

16. A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems
Author(s): L. X. Wang
Page(s): 693-706
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7436787&isnumber=7936677

17. LMI-Based Stability Analysis for Piecewise Multi-affine Systems
Author(s): A. T. Nguyen, M. Sugeno, V. Campos and M. Dambrine
Page(s): 707-714
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7468468&isnumber=7936677

18. An Extended Type-Reduction Method for General Type-2 Fuzzy Sets
Author(s): B. K. Xie and S. J. Lee
Page(s): 715-724
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7469349&isnumber=7936677

19. Critique of “A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems"
Author(s): J. M. Mendel and D. Wu
Page(s): 725-727
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7820064&isnumber=7936677

Wednesday, 7 June 2017

Call for Tutorials -- IEEE World Congress on Computational Intelligence, Rio de Janeiro, 08 - 13 July 2018



The IEEE WCCI 2018 solicits proposals for tutorials aimed at researchers, students and practicing professionals. Tutorials will be held on 8th July 2018. Traditionally, tutorials attract a broad range of audiences, including professionals, researchers from academia, students, and practitioners, who wish to enhance their knowledge in the selected tutorial topic. Tutorials offer a unique opportunity to disseminate in-depth information on specific topics in computational intelligence.

Tutorials will cover fundamental areas in:
  • Evolutionary computation,
  • Neural networks and learning systems,
  • Fuzzy systems, soft computing, and related areas
  • Advanced topics and applications in computational intelligence.

Tutorials will be organized by scientists or professionals who have significant expertise in the selected topic and whose recent work has had a significant impact in their field. The format of each tutorial will be up to the organizer(s), but the focus should be on well-organized, systematic presentations of didactic value. Tutorial organizers should prepare various materials including handouts or electronic resources that will be made available for distribution before or during the tutorial. Setting up specific web pages for tutorials by tutorial organizers is highly encouraged. Tutorials will be typically of 1.5 hours duration; proposals for 3 hours, or full-day tutorial will be considered, if the justification deems sufficient for the extended presence. The audience size of an average tutorial is expected to be around 25-50. Organizers of successful tutorials may receive some minor compensation, the details of which will be communicated later.

If you are interested in proposing a tutorial, would like to recommend someone who might be interested, or have questions about tutorials, please contact the Tutorials Co-Chair most appropriate to your topic (with a copy to the other Tutorials Co-Chairs):

Dr Andre Carvalho (Neural Networks and Learning Systems)
o   email: andre@icmc.usp.br

Dr Carmelo Bastos-Filho  (Evolutionary Computation)
o   email: carmelofilho@ieee.org

Dr Keeley Crockett    (Fuzzy Logic and Systems)
o    email: K.Crockett@mmu.ac.uk

For Advanced topics and applications in computational intelligence
o   Please email  proposals to all three tutorial chairs.

Tutorial proposals must be submitted electronically by 15th December 2018.

Notification of successful tutorials will be on the 2nd March 2018.

Early submission is encouraged.

The proposal should be brief and structured as follows:
  • Title of Tutorial
  • Organisers names, email addresses and links to their webpages
  • Description of the goal of the proposed tutorial (max. 4000 characters)
  • Plan of the session with brief detail of the proposed format (max. 4000 characters)
  • Outline of the covered material (max. 4000 characters)
  • Justification, which should include the potential audience and the timeliness of the given tutorial, proposed duration, as well as the qualifications of the proposer(s).


IEEE Transactions on Emerging Topics in Computational Intelligence, Volume. 1, Issue 3, June 2017


http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7433297

***Special Issue on Computational Intelligence for Software Engineering and Services Computing***

WebAPIRec: Recommending Web APIs to Software Projects via Personalized Ranking
Authors: F. Thung, R. J. Oentaryo, D. Lo and Y. Tian
Page(s): 145-156
http://ieeexplore.ieee.org/document/7935481/

Context-Aware, Adaptive, and Scalable Android Malware Detection Through Online Learning
Authors: A. Narayanan, M. Chandramohan, L. Chen and Y. Liu
Page(s): 157-175
http://ieeexplore.ieee.org/document/7935482/

A Model-Driven Approach to Enable Adaptive QoS in DDS-Based Middleware
Authors: J. F. Inglés-Romero, A. Romero-Garcés, C. Vicente-Chicote and J. Martínez
Page(s): 176-187
http://ieeexplore.ieee.org/document/7857781/

Search-Based Energy Optimization of Some Ubiquitous Algorithms
Authors: A. E. I. Brownlee, N. Burles and J. Swan
Page(s): 188-201
http://ieeexplore.ieee.org/document/7935484/

Dynamic Selection of Classifiers in Bug Prediction: An Adaptive Method
Authors: D. Di Nucci, F. Palomba, R. Oliveto and A. De Lucia
Page(s): 202-212
http://ieeexplore.ieee.org/document/7935483/

Epistasis Based ACO for Regression Test Case Prioritization
Authors: Y. Bian, Z. Li, R. Zhao and D. Gong
Page(s): 213-223
http://ieeexplore.ieee.org/document/7935487/

A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare
Authors: E. Mezghani, E. Exposito and K. Drira
Page(s): 224-234
http://ieeexplore.ieee.org/document/7935485/

Saturday, 3 June 2017

IEEE CIS Distinguished Lecture Program: Call For Nominations


The CIS Distinguished Lecturer Program (DLP) supports local CIS Chapters and CIS members by helping them to invite leading researchers in their respective fields. DLP speakers act as ambassadors of the society during their visit to local chapters and foster professional activities in the area. The IEEE CIS DLP committee invites all Society's Technical Committees Chairs, Chapter Chairs, EiCs, and AdCom/ExCom members to nominate Distinguished Lecturers. Up to eight exceptionally outstanding IEEE CIS members will be selected among the nominees to serve as the DLs for the three year term of 2018-2020. The nominations should be received by no later than August 30, 2017.

The nomination form, procedure, policies and criteria for the Selection of DL Lecturers are available at the following URL: http://cis.ieee.org/distinguished-lecturers-program.html