2. Special Session on Advances in Bio-inspired Computing: Theories and Applications

Organizers:
Dr.  Niu Ben (Associate Professor)
College of Management, Shenzhen University, Shenzhen, China
E-mail: drniuben@gmail.com

Dr. Liang Jing (Associate Professor)
School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
Email: liangjing@zzu.edu.cn

Dr. Liu Yan Min (Professor)
Department of Math, Zunyi Normal College, Zunyi，China
E-mail: yanmin7813@gmail.com

Dr. Chen Hanning (Associate Professor)
Laboratory of Information Service and Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences Shenyang, China 
Email: chenhanning@sia.cn

Scope：
Bio-inspired computing is the field of research works with computational techniques inspired by biological behavior or phenomena. In the last decades, many new biological inspired computing approaches have been proposed such as particle swarm optimization, ant colony system, bee colony algorithm, bacterial foraging algorithm etc. This special session is soliciting papers on all aspects of bio-inspired algorithms and their applications. This special issue provides an opportunity to present and discuss the latest theoretical advances and real-world applications in this research field. The topics of interest include but are not limited to:

3. Special Session on Data Mining Techniques in Epidemiological/Biological Sciences

Organizer:
Dr. Wilbert Sibanda (PhD)
School of Information Technology
North-West University
South Africa
Email: Wilbert.sibanda@nwu.ac.za

Scope:
Epidemiology is a branch of science that deals with finding and explaining health and disease trends in human, animal and plant populations. The study aims to determine patterns, aetiology, and effects of diseases in populations. Data mining is a computational process that involves finding algorithms to describe inherent trends in large data sets. Data mining can assist in understanding the hidden disease dynamics, resulting in simpler interpretation of the data set.
The purpose of this session is to bring together researchers in the fields of data mining in epidemiological and biological sciences to address the challenges in the field and exchange cutting edge research results and methodologies.
Topics of interest include the following:

4. Special Session on Time Series Forecasting and Analysis Using Artificial Neural Networks

Organizers:
Dr. Abir Hussain (Senior Lecturer)
School of Computing and Mathematical Sciences, Liverpool John Moores University, UK
E-mail: a.hussain@ljmu.ac.uk

Dr. Dhiya Al-Jumeily (Principal Lecturer)
School of Computing and Mathematical Sciences, Liverpool John Moores University, UK
E-mail: d.aljumeily@ljmu.ac.uk

Dr. Hissam Tawfik (Associate Professor)
Department of Computer Science, Liverpool Hope University, UK
Email: tawfikh@hope.ac.uk

Dr. David Reid (Senior Lecturer)
Department of Computer Science, Liverpool Hope University, UK
Email: reidd@hope.ac.uk

Scope：
Time series generally refers to a sequence of data points, of any data series measured typically at successive times, spaced at time intervals. In practice, it is a collection of historical data of one system, such as a stock price, traffic data, and the pollution rates.
Time series analysis comprises methods that attempt to understand the behaviour of such time series, often either to understand the underlying theory of the data points, or to make forecasts. Time series forecasting is the use of a model to predict future events or future data points based on known past events. It is a process that produces a set of outputs based on a given set of historical variables. Forecasting assumes that future occurrences are based on present or past events, in which some aspects of the past patterns will continue into the future. Past relationship can then be discovered through study and observation. Hence, time series forecasting can be considered to refer to the discovery of relationships between present, past and future observations.
The scientific community continues to be interested in understanding how and to what extent novel neural network architectures can be efficiently applied for time series forecasting.
The aim of this session is to report on a variety of neural computing techniques for time series and forecasting.

Various types of time series to consider can include, but are not limited to:

5. Special Session on Computer Human Interaction using Multiple Visual Cues and Intelligent Computing

Organizer:
Dr.  Prashan Premaratne
School of Electrical, Computer and Telecommunications Engineering,
Faculty of Engineering and Information Sciences,
University of Wollongong, Australia
E-mail: prashan@uow.edu.au

Dr. Hanning Zhou
Vice President of Research
Zhigu Technology, Beijing
Email: zhouhn@zhigu.com

Scope:
Human computer interaction (HCI) has prominently featured in most of the consumer electronics control systems over the past decade. Every new consumer electronic ‘gadget’ is reviewed by numerous parties to highlight their user friendliness in day-to-day operations. Remote controllers are seen as ‘the’ mode of interaction with these apparatus however, many are looking forward to a flexible and natural way to communicate with these devices. Now a new trend is emerging in Intelligent Computer arena where hand gestures, head movements and eye and face movements can be accepted as a mode of communication when interacting with machines. Research developments in this area have inspired gaming devices such as Microsoft Kinect that would accept face and gaze tracking and hand gestures. This session will highlight latest research carried out in the area of human computer interaction and their potential applications in gaming industry, other modes of entertainment and communicating with disabled persons. This special issue provides an opportunity to present and discuss the latest theoretical advances and practical applications in this research field. The topics of interest include but are not limited to:

6. Special Session on Computer Aided Detection and Pattern Recognition in Real Life and Medicine.

Organizer:
Ph.D. Vitoantonio Bevilacqua
Tenured Assistant Professor of Human Computer Interaction
Department of Electrical and Information Engineering
Polytechnic of Bari - Italy
E-mail: bevilacqua@poliba.it

Scope：
Real Life Scenarios and Medical Applications can take advantages from specific algorithms and frameworks designed and tested by multidisciplinary team involving Engineers, Computer Scientists, Physicians but also bioinformaticians, psychologists and architects. In particular, the main potentialities in this field concern with several results obtained by using computers to detect and recognize patterns and features useful to support decisions in innovative and complex scenarios. The goal of this special issue is the discussion of the latest theoretical advances and practical applications in this research field with particular aspect to Real Life and Medicine. The topics of interest include but are not limited to:

7. Special Session on Protein and Gene Bioinformatics: Analysis, Algorithms and Applications

Organizers:
Michael Gromiha PhD
Associate Professor, Department of Biotechnology, Indian Institute of Technology Madras Chennai 600 036, India
Email: gromiha@iitm.ac.in
URL: http://www.biotech.iitm.ac.in/Gromiha

Y-h. Taguchi Ph.D.
Professor, Department of Physics, Chuo University, Tokyo 112-8551,Japan
E-mail：tag@granular.com
URL: http://www.granular.com/tag/index-j.htm

Scope：
The advanced developments in Biotechnology provide a wealth of data on genomes, proteomes, metabolomes and transcriptomes. This has been evidenced with the growth of data in gene expression profiles, amino acid sequences, protein three-dimensional structures and protein-protein interaction networks. The availability of data pave way to several analyses in biological and medical research, such as high-throughput protein structure prediction, genome-wide protein-protein interaction prediction, binding sites and interface structures in protein complexes, identification of post-transcription modification sites, single nucleotide polymorphism (SNP) prediction, gene expression profile data analysis and so on. The comprehensive analysis, development of efficient algorithms, software and tools for data integration and visualization are necessary in these cutting-edge research fields. 
This special session provides a forum for researchers to present and discuss their latest research results to timely identify and address related problems and challenges. We invite the submission of high-quality, original and unpublished papers in this area. Computational methods for protein and gene bioinformatics includes but are not limited to:

8. Special Session on Biometric System and Security for Intelligent Computing

Organizers:
Saiful Islam, Assistant Professor
Department of Computer Engineering
Aligarh Muslim University
Aligarh, India
email: saifulislam@zhcet.ac.in

Vandana Dixit Kaushik, Assistant Professor
Department of Computer Science & Engineering
Harcourt Butler Technological Institute
Kanpur, India
e-mail: vandanadixitkaushik@yaghoo.com

Phalguni Gupta
Professor
Department of Computer Science and Engineering
Indian Institute of Technology Kanpur
Kanpur, India
email: pg@iitk.ac.in

Scope:
Biometrics is generally used as a form of identification and access control. It extracts physiological and behavioral characteristics of an individual and used as a descriptor and identifier of an individual. Biometrics is considered to be the most reliable means to secure data that has to be transferred digitally. The collection of biometric data raises privacy concerns about the ultimate use of this information. With the increase in the size and complexity of biometric data the problem becomes much more acute. It still it suffers from various challenges which need careful attention before the mass scale deployment. The public acceptance of biometrics is greatly dependent upon its ease of use, social status, performance, and feasibility of spoofing. There is a strong need to study security of biometric template and technologies. This motivates the research in the area of biometrics security with a path forward. he topics of interest include but are not limited to:

9: Special Session on Learning from Imbalanced Data

Organizers
Jair Cervantes Canales, Ph.D
Department of Computer Sciences
Autonomous University of Mexico State (UAEMEX-Texcoco)
Email: jcervantesc@uaemex.mx

Farid Garcia Lamont
Department of Computer Sciences
Autonomous University of Mexico State (UAEMEX-Texcoco)
Email: fgarcial@uaemex.mx

Asdrúbal Lopez Chau
Department of Computer Sciences
Autonomous University of Mexico State (UAEMEX-Zumpango)
Email: asdrubalchau@gmail.com

Scope:
Machine learning techniques have shown tremendous progress in recent years, which has allowed it become commonly used in the real world. Many techniques have been introduced to discover different representations of knowledge from data in numerous fields. It is in this context that the importance of certain problems that some researchers were beginning to glimpse is of paramount importance. One of such problem is the imbalanced data, where one class contains much smaller number of examples than the remaining classes. The imbalanced distribution of classes constitutes a difficulty for standard learning algorithms and calls for specialized approaches. This problem is extensive in many real-world applications: fraud detection, risk management, face recognition, text classification, and many others. The aim of this special session is to provide a forum for international researchers and practitioners to present and share their original works addressing the new challenges, research issues and novel solutions in imbalanced data.

Topics of interest

10: Special Session on Advanced Modeling, Control and Optimization Techniques for Complex Engineering Systems

Organizers:
Kang Li, Professor & PhD
Queen's University of Belfast, UK
Email: k.li@qub.ac.uk

Ning Li, Professor & PhD
Shanghai Jiaotong University,China
Email: ning_li@sjtu.edu.cn

Dajun Du, PhD
Shanghai University, China
Email: ddj@shu.edu.cn

Jing Deng
Queen’s University Belfast, UK
Email: dengjing101@gmail.com

Scope:
The main focus of this special session will be on the new theories and their applications in modeling, control and optimization for complex engineering systems, especially in industry applications. The special session enables researchers worldwide to report their most recent developments and ideas in the field, with a special emphasis on the technical advances proposed within the last five years. The topics to be covered include, but not limited to:

11: Special Session on Complex Networks and Their Applications

Organizer:
Dr. Yunxia Liu (Associate Professor)
College of Information Science and Technology
Zhengzhou Normal University, Zhengzhou, China
Email: liuyunxia0110@hust.edu.cn

Scope
Real-world entities often interconnect with each other through explicit or implicit relationships to form a complex network. Complex networks describe a wide range of systems in nature and society, much quoted examples including biological systems, engineering systems, economic systems, the Internet, and so on. Complex Networks and their Applications aims at bringing together researchers and practitioners from different science communities working on areas related to complex networks, which can cover everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications in ecological, informational, engineering, technological and other systems.
Authors are encouraged to submit both theoretical and applied papers on their research in complex networks. Topics for this session include, but are not limited to: