Wednesday, 13 December 2017

CFP: WCCI Special Session On Spiking Neural Networks (SNN)

IJCNN-09 Spiking Neural Networks (SNN)

Spiking Neural Networks (SNN) are a rapidly emerging means of neural information processing, drawing inspiration from the 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.

Scope and Topics

The aim of this special session is to bring together research works of contemporary areas of SNN, including theoretical, computational, application-oriented, experimental studies, and emerging technologies such as neuromorphic hardware. This special session invites researchers to present state-of-the-art approaches, recent advances and the potential of SNN.

The topics relevant to this special session include, but are not limited to, the following:

  • Theory of SNN
  • Learning algorithms for SNN, including Deep Learning
  • Computation with and within SNN
  • Theory or practice in biologically-plausible 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 encoding for SNN
  • SNN applications in neuroinformatics, bioinformatics, medicine and ecology.
  • SNN in BCI
  • SNN in neuro-robotic
  • Any other topics relating to SNN, their theory, or applications.

Important dates:

Paper Submission Deadline: January 15, 2018
Paper acceptance notification date: March 15, 2018
Final paper submission deadline: May 1, 2018
Conference: July 08-13, 2018

Submission Guidelines

Please follow the regular submission guidelines of WCCI 2018. Please notify the chairs of your submission by sending an email to:
Professor Nikola Kasabov (nkasabov@aut.ac.nz), Dr Elisa Capecci (ecapecci@aut.ac.nz), Maryam Doborjeh (mgholami@aut.ac.nz).

SNN Special Session page: WCCI 2018 Special Session On Spiking Neural Networks (SNN)
Conference page: http://www.ecomp.poli.br/~wcci2018/

Best Regards,
On behalf of the organizers
Professor Nikola Kasabov nkasabov@aut.ac.nz
Dr Elisa Capecci ecapecci     ecapecci@aut.ac.nz
Maryam Doborjeh mgholami@aut.ac.nz
Zohreh Gholami zgholami@aut.ac.nz


CFP: WCCI Special Session on Computational Intelligence for Cognitive-Cyber-Physical Autonomous Systems (CI-C2PAS)


IEEE WCCI 2018,
Rio de Janeiro, Brazil - July, 8-13 2018

Special Session Web Site: http://www.husseinabbass.net/C2PAS-2018.htm


Aim and Scope

Computational Intelligence Techniques have been very successful at the interaction of cognitive-cyber-physical autonomous systems. CI techniques have been used for technologies sitting at the human-machine interface to analyse the interaction between the cognitive and cyber domain. Equally, CI has been successful for cyber security and physical robotics such as autonomous vehicles and unmanned aerial systems. The aim of this special session is to bring together success stories in theory and applications of CI techniques in the C2P domain and to showcase recent advances in these fast emerging research areas.


Research Topics

CI for Human-Machine Autonomous Systems:
- Adaptive Automation
- Adaptive Interfaces and Interface Design
- Brain Computing
- Cognitive-Cyber Symbiosis
- Human-Autonomy Teaming
- Human-Brain Interface
- Human-Robot Interaction
- Workload and Mental load Modelling
- CI for Cyber-Physical Autonomous Systems

Autonomic Systems:
- Cognitive Computing
- Cognitive fault detection and diagnosis systems
- Cyber Robots
- Ground Vehicles
- Ethics of C2PAS
- Intelligent sensor networks
- Surface Water Vehicles
- Swarm Systems
- Unmanned Aerial Vehicles
- Underwater Vehicles
- Cognitive fault-diagnosis systems
- Smart objects and Internet of Things

Applications of C2PAS:
- Applications in Agriculture
- Applications in Bioinformatics
- Applications in Critical-Infrastructure Monitoring
- Applications in Defence
- Application in Education
- Applications in Entertainment
- Applications in Health
- Applications in Psychology and Cognitive Science
- Applications in Social Media
- Applications in Security
- Applications in Smart home/building

Trusted Autonomy for C2PAS:
- Trust Detection
- Trust Evaluation
- Trusted Machine Learning
- Trust Modelling
- Trust Monitoring
- Trusted Optimisation
- Trusted Simulation Environments
- Trusted Systems


IMPORTANT DATES

Paper submission: 15th January 2018

Paper Decision notification: 15th March 2018

Camera-ready submission: 1st May 2018

Conference Dates: July, 8-13 2018


Submission

Papers submitted to this hybrid special session will appear in the IJCNN proceedings.
Please submit your paper to IJCNN and follow the instructions at WCCI Paper Instructions:
http://www.ecomp.poli.br/~wcci2018/submissions/#papersubmission


Organisers

Hussein A. Abbass, University of New South Wales, Canberra, Australia
Jianhua Ma, Hosei University, Japan
Manuel Roveri, Politecnico di Milano, Italy
Christian Wagner, Nottingham, UK


CFP: CEC Special Session on Evolutionary Computation for Complex Optimization in the Energy Domain


IEEE World Congress on Computational Intelligence 2018
(Congress on Evolutionary Computation – CEC 2018)
João Soares, Fernando Lezama, Zita Vale
Task force: IEEE CIS Task Force on 'Computational Intelligence in the Energy Domain, IEEE CIS Intelligent Systems Applications TC (http://ci4energy.uni-paderborn.de/committee/)

Aim and scope:

Increasing energy demand and limited world resources call for sustainability, which is critical to keep up the world at the current pace. Efficiency is very relevant to contribute to this sustainability, and adequate methods of energy production and consumption are highly relevant. Optimization approaches are a crucial part of the planning, operation, and control of energy systems. However, many optimization problems in the energy domain are complex by nature since they are highly constrained and face issues related to high-dimensionality, lack of information, noisy and corrupted data as well as real-time requirements. Under these conditions, it becomes difficult to find a solution in an adequate amount of time. Even the most sophisticated exact solutions require workarounds that often lead to unsatisfactory performance and applicability of the algorithms.

Due to the difficulties of traditional algorithms to find feasible solutions for those complex problems in real-world conditions, Evolutionary Computation (EC) has emerged and demonstrated satisfactory performance in a wide variety of applications in the energy domain.

This special session welcomes research work concerning real-world applications of EC in the energy domain. The problems can be focused in different parts of the energy chain (e.g., heating, cooling, and electricity supply) and different consumer targets (e.g., residential or industrial level). Problems dealing with uncertainty, dynamic environments, and large-scale search spaces are a plus to the aim of this special session. This special session aims at bringing together the latest applications of EC to optimization problems in the energy domain.


Topics must be related to EC in the energy domain including:

-        Electric and plug-in hybrid vehicles
-        Electricity markets
-        Energy scheduling
-        Heat and electricity joint optimization problems
-        Hydrogen economy problems
-        Multi-objective problems in the energy domain
-        Natural gas optimization problems
-        Optimal power flow in distribution and transmission
-        Residential, industrial and district cooling/heating problems
-        Smart grid and micro-grid problems
-        Solar and wind power integration and forecast
-        Super grids problems (continental and trans-continental transmission system)
-        Transportation & energy joint problems

Important Dates:
Paper Submission Deadline: January 15, 2018
Paper Acceptance Notification Date: March 15, 2018
Final Paper Submission & Early Registration Deadline: May 1st, 2018
IEEE WCCI 2018: July 08-13, 2018

Special Session Organizers:
Joao Soares, GECAD, Polytechnic of Porto
(joaps@isep.ipp.pt)
Fernando Lezama, GECAD, Polytechnic of Porto
(flzcl@isep.ipp.pt)
Zita Vale, GECAD, Polytechnic of Porto
(zav@isep.ipp.pt)

Short biographies:

João Soares has a BSc in computer science and a master in Electrical Engineering from Polytechnic of Porto in 2011. He attained his Ph.D. degree in Electrical and Computer Engineering at UTAD university in 2017. He is a senior researcher at GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development. His research interests include optimization in transport and energy systems, including heuristic, hybrid and classical optimization. He published over 80 scientific articles in renowned journals and international conferences.

Fernando Lezama received an M.Sc. degree (with Honors) in Electronic Engineering - Telecommunication (2011), and a Ph.D. in Information Technologies and Communications (2014) both from the Monterrey Institute of Technology and Higher Education (ITESM), Mexico. He was a research visitor at the UNIBO (2013) and Scuola Superiore Sant'Anna (2015), Italy, where he worked with topics related to optical networks and 5G. He was a postdoctoral researcher at INAOE, Mexico, where he worked in the development of intelligent systems for in complex optimization problems. He is also part of the National System of Researchers (C-Level) of Mexico since January 2016. Currently, he is a researcher at GECAD (Portugal). His research interests include computational intelligence, evolutionary computation, network planning, and optimization of smart grids and optical networks.

Zita Vale is a senior researcher at the Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) and a full professor at the Polytechnic of Porto. She received her diploma in Electrical Engineering in 1986 and her Ph.D. in 1993, both from University of Porto. Zita Vale works in the area of Power and Energy Systems, with a special interest in the application of Artificial Intelligence techniques. She has been involved in more than 50 funded projects related to the development and use of Knowledge-Based systems, Multi-Agent systems, Genetic Algorithms, Neural networks, Particle Swarm Intelligence, Constraint Logic Programming and Data Mining. She published over 600 scientific articles in top-level SCI journals and international conferences.

Potential contributors:

-        BISITE, University of Salamanca, Salamanca, Spain (Juan Corchado)

-        Centrum Wiskunde & Informatica, Amsterdam, Netherlands (Michael Kaisers)

-        Computational Intelligence Research Group, CIRG, Pernambuco University, Recife, Brazil (Fernando Buarque)

-        Department of Electrical Sustainable Energy, Delft University of Technology, Delft, Netherlands. (Jose Rueda)

-     Engineering faculty Deparment, São Paulo State University (UNESP), Ilha Solteira, Sao Paulo, Brazil (Ruben Romero)

-        GESE, Federal Institute of Santa Catarina (IFSC), Florianopolis, Brazil (Piara Fernandes)

-      Laboratory for Advanced Studies in Electric Power and Integration of Renewable Energy Systems (L-ASPIRES), The University of Texas At Austin, USA (Surya Santoso)

-        Luxembourg Institute of Science and Technology (LIST), Luxembourg (Ivan S. Razo-Zapata)

-        National Institute of Astrophysics, Optics and Electronics, Puebla, Mexico (Enrique Munoz de Cote)

Real-Time Power and Intelligent Systems (RTPIS), Clemson University, SC, USA (G. Kumar Venayagamoorthy)







Sunday, 10 December 2017

CFP: IJCNN 2018 special cross-disciplinary session on “Interactive/Multiple Clustering using Evolutionary Computation, Fuzzy, Machine Learning and/or Neural Networks”


             2018 IJCNN/IEEE World Congress on Computational Intelligence

         08-13 July 2018, Windsor Convention Centre, Rio de Janeiro, BRAZIL

                                    http://www.ecomp.poli.br/~wcci2018/



Organized by Marcilio de Souto (University of Orleans, France), Andre
de Carvalho (University of São Paulo, Brazil), Christel Vrain
(University of Orleans, France), and Guillaume Cleuziou (University of
Orleans, France)

Clustering is a well-studied domain. Currently, more and more data are
collected from multiple sources or represented by multiple views
(e.g., text, video, images, biological data, among others). Also, for
the same data there might exist several different structures
(clusterings) which are meaningful for the user. In this context,
clustering techniques are often required to be able to provide several
possibilities for analyzing the data. As a consequence, in recent
years, the interdisciplinary research topic on multiple clusterings
has drawn significant attention of the data mining community.

Another topic of recent interest in clustering is interactive
clustering. For instance, usually clustering is studied in the
unsupervised learning framework. However, as pointed out in some
studies, in several real-world problems, such as personalized
recommendations, it is not possible to reach the “optimal” clustering
(the solution that meets the requirements of the user) without
interacting with the end user. In order to approach this problem,
recently frameworks for interactive clustering with human in the loop
have been proposed. These algorithms can interact with the human in
steps and receive feedback to improve.

The aim of this special session is to bring together researchers from
Machine Learning and Data Mining which are actively working in the
fields of multiple clusterings and interactive clustering. The idea is
to cover a wide spectrum of topics, ranging from multi-view
clustering, the interaction with human supervisors to constraint-based
clustering, and stimulate cross-fertilization. In this context, as it
is a cross-disciplinary session, we welcome papers in which techniques
such machine learning, neural networks, fuzzy systems and evolutionary
computing are used in the context of Interactive/Multiple Clustering.

In particular, we welcome contributions that address aspects
including, but not limited to:

·      Cluster ensemble and   Multi-view clustering:

·       How to combine/merge different clustering, how to
control/force the disagreement/diversity between distinct clusterings,
how to choose a solution among too many possible ones, how to
represent/visualize a set of solutions.

·      Multi-objective clustering.

·      Multiple clustering solutions from very high dimensional and
complex databases.

·      Constraint-based clustering and applications as, for instance,
alternative clustering.

·      New approaches to interactive clustering.

·      Methodologies for the evaluation of interactive clustering, and
comparative studies.

Submission: information about the special session and submission
process can be found in the link:
https://sites.google.com/site/interactivemultipleclustering/home





IMPORTANT DATES:

· Paper submission: 15th January 2018

· Paper acceptance: 15th March 2018

· Final paper submission: 1st May 2018

· Early registration: 1st May 2018

· IEEE WCCI 2018 conference: 8-13 July 2018

Monday, 4 December 2017

CFP: WCCI Special session on Computational Intelligence for Bioinformatics and Computational Biology


2018 IEEE World Congress on Computational Intelligence (WCCI 2018)

Rio de Janeiro, BRAZIL, 08-13 July 2018 - http://www.ecomp.poli.br/~wcci2018/


Abstract & Topics

Bioinformatics and Computational Biology deal with a wide range of problems and applications which, in recent years, have been successfully solved by means of Computational Intelligence and Machine Learning techniques. Moreover, due to technological progress, huge amounts of data concerning biological organisms are  gathered and collected (e.g. genes transcript, protein structures and the like), thereby demanding the use of parallel and distributed computing for facing Big Datasets and/or high-throughput application requirements. Further, in such fields, data usually encodes complex information, which is natively represented by structured records, such as sequences, graphs and images, most of which lie in so-called “non-metric spaces”, i.e. input spaces for which a meaningful (dis)similarity measure might not be metric, making the problem more challenging since ad-hoc (dis)similarity measures or embedding functions need to be defined.

This Special Session aims at collecting the latest research in Computational Intelligence applications for Bioinformatics and Computational Biology, with emphasis on parallel/distributed computing and non-metric spaces analysis, by means of different (or hybridization of) Computational Intelligence techniques, from evolutionary meta-heuristics to neural computation, from pattern recognition to fuzzy systems.

Topics of interest include (but are not limited to):
-       Protein function prediction
-       Protein folding prediction
-       Generative models for protein contact networks
-       String kernel methods for sequence classification
-       Mining metabolic pathways
-       Gene finding and prediction
-       Exact/inexact motifs and pattern matching
-       Network and Systems Biology
-       Granular computing approaches for non-metric spaces analysis
-       Large-scale data mining and pattern recognition
-       Distributed and parallel computing systems for machine learning and data mining
-       Clinical Diagnostic Systems
-       Medical image analysis

Organizers
       Prof. Antonello Rizzi, University of Rome “La Sapienza”, Rome, antonello.rizzi@uniroma1.it
       Dr. Alessandro Giuliani, Istituto Superiore di Sanità, Rome, alessandro.giuliani@iss.it

Antonello Rizzi
Antonello Rizzi received the Ph.D. in Information and Communication Engineering in 2000, from the University of Rome “La Sapienza”. In September 2000, he joined the INFO-COM Dpt., as an Assistant Professor. Since July 2010 he joined the “Information Engineering, Electronics and Telecommunications” Dpt. (DIET), in the same University. His major research interests are in the area of Soft Computing, Pattern Recognition and Computational Intelligence, including supervised and unsupervised data driven modeling techniques, neural networks, fuzzy systems and evolutionary algorithms. His research activity concerns the design of automatic modeling systems, focusing on classification, clustering, function approximation and prediction problems. Currently, he is working on different research topics and projects, such as Granular Computing, Data Mining and Knowledge Discovery, Content Based Retrieval Systems, classification and clustering systems for structured patterns, graph and sequence matching, agent-based clustering, smart grids and micro-grids modeling and control, intelligent systems for sustainable mobility, battery management systems. Since 2008, he serves as the scientific coordinator and technical director of the R&D activities in the "Intelligent Systems Laboratory" within the Research and Technology Transfer Center for Sustainable Mobility of Lazio Region. He is the scientific coordinator of the "Computational Intelligence and Pervasive Systems" Lab at DIET. Dr. Rizzi (co-)authored more than 140 international journal/conference papers and book chapters. He is a member of IEEE.

Alessandro Giuliani
Alessandro Giuliani was born in Roma, on February 14, 1959. He took his Laurea in Biological Sciences at  University of Rome "La Sapienza" score 110/110 cum laude (Academic Year ‘81/’82) with a specialization in Statistics. He serves as Senior Scientist at Environment and Health Dept., Istituto Superiore di Sanità, Rome, Italy (1997 - ). He is Professor (on contract basis) at Pontifical Urbaniana University, Rome.

Dr. Alessandro Giuliani is involved since more than thirty years in the generation and testing of soft physical and statistical models for life sciences. He puts a special emphasis on the elucidation of mesoscopic complex systems like protein sequence/structure prediction, complex network approaches, QSAR, Systems Biology. He contributed (together with Prof. Zbilut and Prof. Webber) to the development of Recurrence Quantification Analysis (RQA) data analysis technique. He is the author of about 300 publications on peer-review journals with an H-index = 38.


Authors’ Information
Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of WCCI 2018.
Authors who submit papers to this session are invited to mention it in the form during the submission.
Submissions to Regular and Special Sessions follow identical format, instructions, deadlines and procedures of the other papers.

More information can be found at
-        Official WCCI 2018 Call for Papers:         http://www.ecomp.poli.br/~wcci2018/call-for-papers/
-        Official WCCI 2018 Guidelines:    http://www.ecomp.poli.br/~wcci2018/submissions/#guidelines
-        The Special Session website:        https://sites.google.com/a/uniroma1.it/wcci2018-ci4bcb/

Important Dates
Paper Submission Deadline:       15 January 2018
Notification of Acceptance:        15 March 2018
Early Registration:                      1 May 2018
WCCI 2018 Conference:             8 – 13 July 2018