ICIC 2016 Special Session

2016 International Conference on Intelligent Computation
August 2-5,2016
Lanzhou,China
( http://www.ic-icc.cn/2016/index.htm )

The ICIC 2016 Program Committee is inviting proposals for special sessions to be held during the conference (http://www.ic-icc.cn/2016/index.htm), taking place on August 2-5 2016, in Lanzhou,China.

Each special session proposal should be well motivated and should consist of 8 to 12 papers. Each paper must have the title, authors with e-mails/web sites, and as detailed an abstract as possible. The special session organizer(s) contact information should also be included. All special session organizers must obtain firm commitments from their special session presenters and authors to submit papers in a timely fashion (if the special session is accepted) and, particularly, present them at the ICIC 2016. Each special session organizer will be session chair for their own special sessions at ICIC 2016 accordingly. All planned papers for special sessions will undergo the same review process as the ones in regular sessions. All accepted papers for special sessions will also be published by Springer's Lecture Notes in Computer Sciences (LNCS)/ Lecture Notes in Artificial Intelligence (LNAI)/ Lecture Notes in Bioinformatics (LNBI)/ Communications in Computer and Information Science (CCIS).

All the authors for each special session must follow the guidelines in CALL FOR PAPERS to prepare your submitted papers.

Proposals for special sessions should be submitted in ELECTRONIC FORMAT to Workshop/Special Session Chairs:

Ling Wang
Tsinghua University, China
wangling@mail.tsinghua.edu.cn


SS1 on Intelligent Computing in Scheduling(Danyu Bai, et. al, China)
SS2 on Advances in Swarm Intelligence: Algorithms and Applications (Ben Niu, et. al, China)
SS3 on Advances in Swarm Intelligence Algorithm(Yongquan Zhou, et. al, China)
SS4 on Learning from Imbalanced Data(Jair Cervantes Canales, et. al, Mexico)
SS5 on Advances in Particle Swarm Optimization(Fei Han, et. al, China)
SS6 on Complex Diseases Informatics(Shulin Wang, et. al, China)
SS7 on Computer Human Interaction using Multiple Visual Cues and Intelligent Computing(Prashan Premaratne, et. al, Australia)
SS8 on Machine Learning and Data Analysis for Medicaland Engineering Applications(Abir Hussain, et. al, UK)
SS9 on Emerging Behavior of Machines with Humans and other Machines(Vitoantonio Bevilacqua, et. al, Italy)
SS10 on Special Session on Information Security

1. Special Session on Intelligent Computing in Scheduling

Danyu Bai
School of Economics & Management, Shenyang University of Chemical Technology, Shenyang 110142, P.R.China
Email: mikebdy@163.com

Ling Wang
Tsinghua University, China
wangling@mail.tsinghua.edu.cn

Scope:

This special session intends to give the state-of-the-art of scheduling research that satisfies the needs of modern manufacturing and planning systems. Interdisciplinary methodologies may be given based on the advanced intelligent computing and scheduling techniques to provide effective and efficient solution procedures for complex scheduling problems. The aim of this special session is to reflect the most recent developments of metaheuristics, evolutionary algorithms, swarm intelligence and other intelligent computing techniques used for scheduling in a variety of manufacturing and planning systems. The topics include but are not limited to:

  • Intelligent computing in production scheduling
  • Intelligent computing in project scheduling
  • Intelligent computing in transportation scheduling
  • Intelligent computing in timetabling
  • Intelligent computing in nursing scheduling
  • Intelligent computing in other scheduling problems
  • Intelligent computing in multi-objective scheduling
  • Intelligent computing in dynamic/uncertain/fuzzy scheduling
  • Intelligent scheduling in practical systems
  • Related topics

    2. Special Session on Advances in Swarm Intelligence: Algorithms and Applications

    Dr. Ben Niu (Professor)
    College of Management, Shenzhen University, Shenzhen, China
    Email: drniuben@gmail.com

    Dr. X.H. Chu (Assistant Professor)
    College of Management, Shenzhen University, Shenzhen, China
    xianghua.chu@gmail.com

    Dr. Bing Xue(Assistant Professor)
    School of Engineering and Computer Science, Victoria University of Wellington, New Zealand.?
    bing.xue@ecs.vuw.ac.nz

    Ms. Ying Bi
    College of Management, Shenzhen University, Shenzhen, China
    yingbi.szu@gmail.com

    Scope:

    Swarm intelligence is a dynamic system that deals with natural and artificial systems which consist of many simple individuals with decentralized control and self-organization. As a multidisciplinary study inspired by nature, this field typically focuses on collective behaviors deriving from a population of simple agents interacting with one another and with environment. These behaviors include bees colonies, birds flocking, bacteria foraging, and so on. Over the last few decades, there has been a remarkable growth in this field that encompasses the interests and efforts of researchers ranging from social science and ethology to computer science and engineering. Swarm intelligence has been successfully applied to various real-world problems such as discrete optimization, dynamic decision and computational system.

    This special issue is devoted to publishing original and high-quality articles that advance the state-of-the-art algorithms and applications of swarm intelligence with discrete and dynamic characteristics.

    Topics of interest include but not limited to:

  • Particle swarm optimization
  • Ant colony optimization
  • Bee colony optimization
  • Bacterial foraging optimization
  • Artificial fish search algorithm
  • Krill herd algorithm
  • Other algorithms inspired by swarm intelligence
  • Operations research
  • Decision making
  • Management optimization
  • Information systems
  • Power and energy systems
  • Other management and engineering problems

    3. Special Session on Advances in Swarm Intelligence Algorithm

    Yongquan Zhou, Professor, Ph.D
    College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006,China
    Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence, Nanning 530006, China
    Email: yongquanzhou@126.com

    Yunfei Yi, Ph.D & Associate professor
    College of Computer and Information Engineering, Hechi University, Yizhou, 546300
    Email: gxyiyf@163.com

    Scope:

    Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. Swarm Intelligence-based techniques can be used in a number of applications. This special session will highlight the latest development in this rapidly growing research area of new swarm intelligence algorithm, such as, Glowworm Swarm Optimization(GSO),Bat Algorithm(BA),Cuckoo Algorithm (CA), Grey Wolf Optimization Algorithm(GWOA),Krill Herd Algorithm(KHA),et.al and its applications. Authors are invited to submit heir original work in the areas including (but not limited to) the following:

  • New swarm intelligent algorithms convergence analysis and parameter choice method
  • Multi-stage swarm intelligence algorithms with applications
  • Hybrid swarm intelligence algorithms with applications
  • Hyper-swarm intelligence algorithms with applications
  • Various improved version swarm intelligence algorithms with applications.

    4. Special Session on Learning from Imbalanced Data

    Jair Cervantes Canales
    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

    Asdr篓虏bal 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. Manytechniques 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 algorithmsand 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 newchallenges, research issues and novel solutions in imbalanced data.

    Topics of interest include but not limited to:

  • Sampling techniques for imbalanced data
  • High dimensional and class-imbalanced data.
  • Ensembles for imbalanced data.
  • Pre-processing, structuring and organizing complex data
  • Imbalanced classes in noisy environments.
  • Skewed data and difficult classes.
  • Imbalanced data for regression.
  • Imbalanced data and semi-supervised learning.
  • Imbalanced in multi-class problems.
  • Performance evaluation of classifiers in imbalanced domains.
  • Handling class imbalance by modifying inductive bias and post-processing of learned models
  • Theoretical aspects of constructing combined imbalanced learning systems
  • Imbalanced learning in changing environments
  • Incremental online learning algorithms
  • Cost-sensitive learning.
  • Real applications.

    5. Special Session on Advances in Particle Swarm Optimization

    Shou-Bao Su, Professor
    School of Computers Engineering, Jinling Institute of Technology,Nanjing, Jiangsu, China
    Email: showbo@jit.edu.cn

    Fei Han, Professor, Ph.D
    School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
    Email: hanfei@mail.ujs.edu.cn

    Scope:

    Particle swarm optimization (PSO), one of the pillars of Swarm Intelligence, is a population-based stochastic optimization technique. Compared with other optimization methods, PSO has no complicated evolutionary operators and adjusts less parameter in the course of training. These merits make it easy to implement, apply, extend and hybridise. Many attempts have been made to improve the performance of the original PSO in past several years. This special session will highlight the latest development in this rapidly growing research area of new PSO and its applications. Authors are invited to submit their original work in the areas including (but not limited to) the following:

  • Convergence analysis and parameter choice of PSO
  • Empirical and theoretical analyses of the dynamics of PSO particles and populations
  • Multiple population cooperative PSO
  • Advanced bare-bones and distribution-based PSOs
  • PSOs for stochastic, dynamic, multi-objective and combinatorial optimization problems
  • Novel combinations of PSO algorithms with other techniques
  • Novel applications in bioinformatics, image and signal processing, and computational intelligence.

    6. Special Session on Complex Diseases Informatics

    Prof. Shulin Wang
    College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China.
    Email: smartforesting@gmail.com

    Prof. Jiawei Luo
    College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
    Email: luojiawei@hnu.edu.cn

    Dr. Jianwen Fang
    Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20850, USA.
    Email: Jianwen.fang@nih.gov

    Scope:

    Complex diseases result from a combination of genetic and environmental factors, many of which are not understood. These diseases include various cancers, Parkinson's disease, neurodegenerative diseases, psychiatric, autoimmune disorders, etc.The purpose of this special session on complex diseases informaticsincluding models, methods and algorithms is to bring together researchers and practitioners interested in the application of information technologies to the field of molecular biology, including for example the use of statistics and algorithms to understanding the process of complex diseases, e.g. cancer evolution progression, with a focus on new developments in the analysis methods of biologically big data obtained by high-throughput technologies such as next-generation sequencing that are helping drive a revolution in complex diseases genomics. Theresulteddiscoveries have the potential to lead to how complex diseases will be diagnosed and treated as well as life-changing improvements for patients and their loved ones.This special session encourages authors to submit papers to one of the main topicsas follows.

  • Sequence analysis
  • Various omics data analysis such as computational genomics
  • Protein-protein interactions network
  • Gene regulatory network
  • MicroRNA regulatory network
  • Cancer-related gene selection
  • Biostatistics
  • Biologically big data mining
  • Diseases classification and cluster with machine learning
  • Computationally evolutionary biology

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

    Dr. Prashan Premaratne (ICIC 2016 International Liaison Chair)
    School of Electrical, Computer and Telecommunications Engineering,
    Faculty of Engineering and Information Sciences,
    University of Wollongong, North Wollongong, NSW, 2522, Australia.
    Email: prashan@uow.edu.au

    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:

  • Computer Human Interaction
  • Gesture Recognition and Classification
  • Skin Segmentation
  • Face and Gaze Detection and Recognition
  • Eye Tracking
  • Stereoscopy
  • Technological developments in sign language
  • Emotion recognition by machine
  • Computer Vision Applications

    8. Special Session on Machine Learning and Data Analysis for Medicaland Engineering Applications

    Dr. Abir Hussain
    Liverpool John Moores University, UK
    Email: a.hussain@ljmu.ac.uk

    Dr. Dhiya Al-Jumeily
    Liverpool John Moores University, UK
    Email: d.aljumeily@ljmu.ac.uk

    Dr. Paul Fergus
    Liverpool John Moores University, UK
    Email: p.fergus@ljmu.ac.uk

    Prof. Hani Hamdan
    CentraleSup篓娄lec, L2S UMR CNRS, France
    Email: Hani.Hamdan@centralesupelec.fr

    Scope:

    Machine Learning and Data Analysis (MLDA) techniques have become important tools for the decision making and the development of medical and engineering applications. They can play an important role in the decision making process, as well as the method on which various types of data are collected, treated, processed and presented; most importantly making intelligent decisions about simulate new scenarios and devices. Despite the fact that in the past, healthcare and engineering professionals were septic regarding the use of these technologies as tools for decision making, these worries have been eliminated due to the huge development of MLDA techniques and their roles as examples in personalized health, accuracy of diagnosis, and engineering decision making. This special session will cover the following topics but is not limited to:

  • The use of MLDA in decision making
  • The use of MLDA in prediction
  • Data analysis using machine learning
  • knowledge engineering
  • Computational intelligence in bio- and clinical medicine
  • Information systems and medical data analysis
  • Intelligent devices based on MLDA and instruments

    Original Artificial Intelligence contributions can also be involved which include but are not limited to:

  • Fuzzy logic
  • Decision tree
  • Support vector machine
  • Nonlinear systems
  • Feedforward neural networks
  • Recurrent Neural Networks
  • Supervised and unsupervised learning models

    9. Special Session on Emerging Behavior of Machines with Humans and other Machines

    Vitoantonio Bevilacqua, PhD, Tenured Professor
    Human Machine Interaction
    Dipartimento di Ingegneria Elettrica e dell 'Informazione - Politecnico di Bari, Italy
    Email: vitoantonio.bevilacqua@poliba.it

    Scope:

    Nowadays, evolution and organisation of natural and artificial cognitive systems are emerging with their adaptive behavior and cognitive models. These methods could help technicians and psychologists to investigate the potentialities of new solutions and applications in several fields where biologically-inspired cognitive systems and robots could interact to each other or with humans to perform original tasks and collaborating goals. Topics for this session include but are not limited to:

  • Cognitive and neural modelling
  • Brain Imaging and Signals
  • Language and Image Understanding
  • Emotion Recognition
  • Adaptive Behavior
  • Information visualization and communications in adaptive agents

    10. Special Session on Information Security

    Yunxia Liu, PhD & Professor
    College of Information Science and Technology
    Zhengzhou Normal University, Zhengzhou, China
    Email: liuyunxia0110@hust.edu.cn

    Scope:

    Information security has become a crucial need for almost all information transaction applications due to the large diversity of the hackers and attacks, Traditional techniques such as cryptography, watermarking, and data hiding are basic notions and play an important role in developing information security algorithms and solutions. In spite of the large development in the information security techniques, there are still several challenges that need to be addressed in terms of time, accuracy and reliability. The special session targets the information security research area with respect to trends, advanced techniques and applications, which attracts researchers and practitioners from academia and industry, and provides a discussion environment in order to share their experiences in information security. Authors are encouraged to submit both theoretical and applied papers on their research in information security. Topics of interest include, but are not limited to:

  • applied cryptography
  • data protection
  • formal methods in security
  • information dissemination control
  • information hiding and watermarking
  • network security
  • privacy
  • secure group communications
  • security in social networks
  • embedded security