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International Conference on Computers, Communications and Control

Băile Felix, Oradea, România, May 8-12, 2012

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Acad. Florin-Gheorghe Filip
The Romanian Academy,
Chair of the Information Science
and Technology" Section,
Calea Victoriei 125,
RO  010071 Bucharest,
Romania, ffilip@acad.ro

The goal of this workshop is to bring together researchers interested in Intelligent Computing, Knowledge Discovery in Databases, Decision Support Systems for Crisis Management, in order to exchange ideas, problems, solutions, and to work together in a friendly environment. After this interaction meeting we intend make some teams for design of intelligent decision support systems for management of crisis: economic, financial, energy, food, healthcare, military, manufacturing etc.

SECTION 1: Intelligent Computing

Chair: Prof. Rãzvan Andonie
Central Washington University,
400 East University Way, Ellensburg, WA 98926, USA,
andonie@cwu.edu, http://www.cwu.edu/~andonie/

SECTION SCOPE
Conflict and management involves implementing strategies to limit the negative aspects of conflict and to increase the positive aspects of conflict. It is not concerned with eliminating all conflict or avoiding conflict. Conflict can be valuable when managed properly. In order to manage a conflict effectively and to minimize the anticipated adverse impacts, imminent decisions must be made on the necessary actions and on the most effective use of the available resources in different managerial levels.
The main topic of this section is machine intelligence and intelligent computing applied to conflict management. All areas of conflict management are considered: risk management, military and political conflicts, crises management, conflict resolution, conflict prediction, early warning, etc.
In this perspective, Artificial and Computational Intelligence provide the background for the development of intelligent conflict management systems. Today, such intelligent systems take many forms, encompass a variety of approaches and include many design challenges.

TOPICS
We seek original and high-quality contributions on the general theme of Intelligent Systems for Conflict Management. The following is a non-exhaustive list with topics of special interest:

• Artificial and computational intelligence methods in conflict management
• Conflict resolution in multi - agent based intelligent environments
• Data fusion for resolving data conflicts
• Decision making using computer-supported conflict management methodology
• Conflict detection algorithms
• Data mining in terrorism informatics
• Web mining and social network analysis applied to conflict early warning
• Mobile and P2P technologies in conflict management
• Adaptive management approaches for conflict resolution
• Self-organizing conflict prevention / resolution techniques
• Decision making with missing and/or uncertain data
• Machine learning for intelligent support of conflict resolution
• Computational intelligence techniques for crisis prediction
• Risk assessment and evaluation of predictions

SECTION 2: Knowledge Discovery in Databases

Chair: Prof. Gang Kou
University of Electronic Science and Technology of China,
School of Management and Economics, Chengdu,
P. R. China, 610054,  kougang@uestc.edu.cn

SECTION SCOPE
Today’s crisis management involves heterogeneous types of information that are stored in different computer systems, platforms, data types, and so on. How to integrate incident data sources and help decision makers make immediate and effective responses under pressure and uncertainties is an essential issue that requires cross-disciplinary collaboration.
Data mining and knowledge discovery (DMKD), which develops methods, algorithms, and techniques to extract useful information from huge amounts of data, emerged in 1990s and grew rapidly since then. Data mining techniques, such as classification, association, and clustering, can be used to analyze different types of data to assist substantially in crisis management.
Data mining for crisis management has been an active research area in the past decade. Many data mining methods, techniques, and tools have been developed to support various aspects of crisis management. Although there are successful cases, the complexity in building efficient crisis management system requires specialized data mining methods and techniques.

TOPICS

• Data mining and knowledge discovery in crisis management
• Analyzing and evaluating of critical decision elements under different crisis situations (e.g., earthquake, terrorist attacks, hurricane)
• Modeling different types of emergency problems using the data mining algorithms and tools
• Developing data mining-based hazard planning and emergency management systems
• Applying the data mining methods and techniques in developing crisis response plans or policies

SECTION 3: Decision Support Systems

Chair: Prof. Yong Shi
Research Center on Fictitious Economy & Data Science
Chinese Academy of Sciences
Beijing 100190, China, yshi@gucas.ac.cn
and
College of Information Science & Technology
University of Nebraska at Omaha Omaha, USA,
NE 68182, USA, yshi@unomaha.edu

SECTION SCOPE
Decision support system (DSS) generally refers to a computer-based information systems which supports business decision making activities. DSSs utilizes organizational database to serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance. The current extensions of DSS related organizational systems are data warehousing (DW), data mining (DM) and business intelligence (BI). In many situations, DW, DM and DSS focus on structured data, BI incorporates both structured and unstructured data as inputs. Research on interactions of DSS with DW, DM and BI can speed up the development of technologies to effectively transform data into information, and then into knowledge. Extended DSS can allow the decision analysts combine the results of DM based a DW with human knowledge to produce intelligent knowledge to enhance the power of BI. This section encourages various research topics that address DSS as well as the extensions of DSS, such as DW, DM and BI.

TOPICS
All original and high-quality research papers related to, but not limited to the following are welcome:

• Decision support system
• Data warehousing
• Data mining or knowledge discovery from large-scale databases
• Business intelligence

SECTION 4: Crisis Management

Chair: Prof. Mișu-Jan Manolescu
Agora University, Romania
Piata Tineretului, 8, 410526 Oradea, Romania,
rectorat@univagora.ro

SECTION SCOPE
To present and discuss latest research on ideas, problems, solutions and methods for management of crisis and conflicts: economic, financial, energy, food, healthcare, military, manufacturing etc.

TOPICS

• Emergency management
• Knowledge management in crisis and conflicts
• Managing IT e-commerce
• Supply chain management systems modeling
• Semantic web applications in conflict management 
• Conflict preventing
• Crisis management

Deadline

March 15, 2012: Extended abstracts submission (1-2 pages A4 about idea, proposal etc.).
March 30, 2012: Notification of acceptance/rejection of extended abstracts.
April 15, 2012: Ready camera paper submission & Registration fee transfer (200 EUR, include all workshop materials, Welcome dinner, Friendly dinner, and refreshments).

Submission:

•  Online System OpenConf
  

Program at a Glance

1. May 8, Tuesday: Arrival of participants
2. May 9, Wednesday: Official opening, Invited talks, Provocative presentations, Welcome dinner.
3. May 10, Thursday: Parallel sessions, Joint meeting, Friendly dinner
4. May 11, Friday: Excursion
5. May 12, Saturday: Departure of participants

Publication

The accepted extended abstracts will be published in Abstracts of ICCCC, ISSN 1844-4334.
Selected papers will be published in IJCCC, ISSN 1841-9836 (ISI WoS/WoK, Impact factor in JCR2010: 0.650).

Contact

• E-mail: icccc@univagora.ro, Tel. +40359101032