Call for Papers The First International Conference on Rough Sets and Knowledge Technology (RSKT2006)

Overview Since the introduction of rough sets in 1982 by Professor Zdzistaw Pawlak. we have witnessed great advances in both theory and appications. There has been a rapid growth inresearch and applications of rough sets in Asia, particulary in China. Rough set theory is closely related to knowledge technology ina variety of forms such as knowledge discovery, approximate reasoning, intelligent and multiagent systems design, knowledgeintensive computations that signal the emergence of a knowledge technology age. The essence of growth in cutting-edge, state-of-the-art and promising knowledge technologies is closely related to learning, pattern recognition, machine intelligence and automation ofacquisition, transformation, communication, exploration and exploitation of knowledge. A principal thrust of such technologies is theutilization of methodologies that facilitate knowledge processing. To present state-of-the-art scientific results, encourage academicand industrial interaction, and promote collaborative reserch and developmental activities, in rough sets and knowledge technologyworldwide, a new intemational confrence named Rough Sets and Knowledge Technology (RSKT) is proposed. It will provide a newforum for researchers in rough sets and knowledge technology.     

基于粗集分类和遗传算法的知识库集成方法

As the base of intelligent system, it is very important to guarantee the consistency and non-redundancy of knowledge in knowledge database. Since the variety of knowledge sources, it is necessary to dispose knowledge with redundancy, inclusion and even contradiction during the integration of knowledge database. This paper researches the integration method based on the multi-knowledge database. Firstly, it finds out the inconsistent knowledge sets between the knowledge databases by rough set classification and presents one method eliminating the inconsistency by test data. Then, it regards consistent knowledge sets as the initial population of genetic calculation and constructs a genetic adaptive function based on accuracy, practicability and spreadability of knowledge representation to carry on the genetic calculation. Lastly, classifying the results of genetic calculation reduces the knowledge redundancy of knowledge database. This paper also presents a frameworkfor knowledge database integration based on the rough set classification and genetic algorithm.     

Editorial

Quantum technology is recognized as one of the most promising directions for our future technologies. By exploiting the unique features of quantum effects, emerging quantum technology is rapidly progressing around the world including quantum computation, quantum communication, quantum metrology and quantum simulation. The development of quantum control plays a grounding role in enabling the preservation and manipulation of quantum states that are used in various quantum technologies. This special issue will focus on new development in relevant topics of estimation and control methods in quantum systems, and provide a forum for idea exchange in this dynamic research area. Particularly, Ian R. Petersen, a key figure in the development of robust and quantum control theory, just turned 60 in the past year. We propose to celebrate this occasion with this special issue on quantum control, one of his main research focuses in the last fifteen years....     

Hybrid Nanoelectronics: Future of Computer Technology

Nanotechnology may well prove to be the 21st century＇s new wave of scientific knowledge that transforms people＇s lives. Nanotechnology research activities are booming around the globe. This article reviews the recent progresses made on nanoelectronic research in US and China, and introduces several novel hybrid solutions specifically useful for future computer technology. These exciting new directions will lead to many future inventions, and have a huge impact to research communities and industries.     

Rough Sets, Their Extensions and Applications

Rough set theory provides a useful mathematical foundation for developing automated computational systems that can help understand and make use of imperfect knowledge.Despite its recency,the theory and its extensions have been widely applied to many problems,including decision analysis,data mining,intelligent control and pattern recognition.This paper presents an outline of the basic concepts of rough sets and their major extensions,covering variable precision,tolerance and fuzzy rough sets.It also shows the diversity of successful applications these theories have entailed,ranging from financial and business,through biological and medicine,to physical,art,and meteorological.     

Technology application in project-based learning

Project-based learning is a student-centered comprehensive instructional approach where students collectively engage themselves in complex learning tasks. Recent advances in educational technologies have made student-centered learning in a technology rich environment both possible and feasible. This paper will report part of a larger study carried out at a school in the United States of America on the use ofconstructivism and technology in project-based learning. Data collection techniques included those typically associated with qualitative field research. In this paper, the technological infrastructure of the school and how technology is used in one of the project-based learning classes will be provided. Based on this study, some suggestions are also provided on how technology can be used in the context of other countries including in Malaysia.     

An Overview of Data Mining and Knowledge Discovery

With massive amounts of data stored in databases,mining information and knowledge in databases has become an important issue in recent research.Researchers in many different fields have shown great interest in date mining and knowledge discovery in databases.Several emerging applications in information providing services,such as data warehousing and on-line services over the Internet,also call for various data mining and knowledge discovery tchniques to understand used behavior better,to improve the service provided,and to increase the business opportunities.In response to such a demand,this article is to provide a comprehensive survey on the data mining and knowledge discorvery techniques developed recently,and introduce some real application systems as well.In conclusion,this article also lists some problems and challenges for further research.     

Recent Progress on Selected Topics in Database Research ——-A Report by Nine Young Chinese Researchers Working in the United States

The study on database technologies, or more generally, the technologies of data and information management, is an important and active research field. Recently, many exciting results have been reported. In this fast growing field, Chinese researchers play more and more active roles. Research papers from Chinese scholars, both in China and abroad,appear in prestigious academic forums.In this paper,we, nine young Chinese researchers working in the United States, present concise surveys and report our recent progress on the selected fields that we are working on.Although the paper covers only a small number of topics and the selection of the topics is far from balanced, we hope that such an effort would attract more and more researchers,especially those in China,to enter the frontiers of database research and promote collaborations. For the obvious reason, the authors are listed alphabetically, while the sections are arranged in the order of the author list.     

The Global Crisis and Academic Communication： The Challenge of Social Networks in Research

The global economic crisis is seriously affecting academic research. The situation is provoking some big changes and an urgent need to seek alternatives to traditional models. It is as if the academic community was reinventing itself; and this reinvention is happening online. Faced with a lack of funding, researchers have determined to help each other develop their projects and they are doing so on social knowledge networks that they have created for this mission. The purpose of this paper is to analyze different social networks designed for academic online research. To this end, we have made a selection of these networks and established the parameters for their study in order to determine what they consist of, what tools they make use of, what advantages they offer and the degree to which they are bringing about a revolution in how research is carried out. This analysis is conducted from both a qualitative and a quantitative perspective, allowing us to identify the percentage of these networks that approach what would be the ideal social knowledge network. As we will be able to confirm, the closer they are to this ideal, the more effective they will be and the better future they will have, which will also depend on the commitment of users to participation and the quality of their contributions.     

Function S-rough sets and law identification

By introducing element equivalence class that proposes dynamic characteristic into Pawlak Z rough sets theory, the first author of this paper improved Pawlak Z rough sets and put forward S-rough sets （singular rough sets）. S-rough sets are defined by element equivalence class that proposes dynamic characteristic. S-rough sets have dynamic characteristic. By introducing the function equivalence class （law equivalence class） that proposes dynamic characteristic into S-rough sets, the first author improved S-rough sets and put forward function S-rough sets （function singular rough sets）. Function S-rough sets have dynamic characteristic and law characteristic, and a function is a law. By using function S-rough sets, this paper presents law identification, law identification theorem, and law identification criterion and applications. Function S-rough sets are a new research direction of rough sets theory, and it is also a new tool to the research of system law identification.     

Autonomous clustering using rough set theory

This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease. The results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency.     

Rough集之间的相似度量

Applications of rough set theory in incomplete information systems are a key of putting rough set into real applications. In this paper, after analyzing some basic concepts of classical rough set theory and extended rough set theory, the measure of similarity is developed between two rough sets in the classical rough set theory based on indiscernibility relation and between two rough sets in the extended rough set theory based on limited tolerance relation. Then,some properties of these two methods for measuring similarity are developed respectively. At last,these two measure methods of rough set theory are compared.     

Development of a viable 3D integrated circuit technology

Three-dimensional integrated circuit technology with transistors stacked on top of one an-other in multi-layer silicon film has always been a vision in the future technology direction. While the idea is simple, the technique to obtain high performance multi-layer transistors is extraordinarily diffi-cult. Not until recently does such technology become feasible. In this paper, the background and vari-ous techniques to form three-dimensional circuits will be reviewed. Recent development of a simple and promising technology to achieve three-dimensional integration using Metal-Induced-Lateral-Crystalliza-tion will be described. Preliminary results of 3D inverters will also be provided to demonstrate the viabil-ity for 3D integration.     

The Future of Computer Science

Computer science is undergoing a fundamental change and is reshaping our understanding of the world. An important aspect of this change is the theory and applications dealing with the gathering and analyzing of large real-world data sets. In this paper, we introduce four research projects in which processing and interpreting large data sets is a central focus. Innovative ways of analyzing such data sets allow us to extract useful information that we would never have obtained from small or synthetic data sets, thus providing us with new insights into the real world.     

一种基于决策表的分类规则挖掘新算法

The mining of classification rules is an important field in Data Mining. Decision table of rough sets theory is an efficient tool for mining classification rules. The elementary concepts corresponding to decision table of Rough Sets Theory are introduced in this paper. A new algorithm for mining classification rules based on Decision Table is presented, along with a discernable function in reduction of attribute values, and a new principle for accuracy of rules. An example of its application to the car‘s classification problem is included, and the accuracy of rules discovered is analyzed. The potential fields for its application in data mining are also discussed.     

An Overview of Calibration Technology of Industrial Robots

With the continuous improvement of automation,industrial robots have become an indispensable part of automated production lines.They widely used in a number of industrial production activities,such as spraying,welding,handling,etc.,and have a great role in these sectors.Recently,the robotic technology is developing towards high precision,high intelligence.Robot calibration technology has a great significance to improve the accuracy of robot.However,it has much work to be done in the identification of robot parameters.The parameter identification work of existing serial and parallel robots is introduced.On the one hand,it summarizes the methods for parameter calibration and discusses their advantages and disadvantages.On the other hand,the application of parameter identification is introduced.This overview has a great reference value for robot manufacturers to choose proper identification method,points further research areas for researchers.Finally,this paper analyzes the existing problems in robot calibration,which may be worth researching in the future.     

Research on Next-Generation Internet Architecture

The primary problem during the evolvement of next-generation Internet is the contradiction between growing requirements for Internet and the insufficient development of network theory and technology. As the fundamental principles to guide the developing direction of Internet, the study of Internet architecture is always a focus in the research community. To address the core issue of network scalability, we propose multi-dimension scalable architecture of next-generation Internet, the main idea of which is to extend the single-dimension scalability of traditional Internet on interconnection to multi-dimension scalability of next-generation Internet. The multi-dimension scalability is composed of scale-scalability, performance-scalability, security-scalability, function-scalability, and service-scalability. We suggest five elements, namely, IPv6, authentic IPv6 addressing, scalable processing capacity of routers, end-to-end connectionless Quality-of-Service control, and 4over6 mechanism to realize the multi-dimension scalability. The current research results show that the multi-dimension scalable architecture composed of these five elements will bring great influence on next-generation Internet.     

e-LITE： A Concurrent Engineering Method Dedicated to E-learning Training Development for the Enhancement of Research Project Results

Scientific research projects aim to produce new knowledge generally in domains of high specialization.Some of these projects have goals of improving the performance of companies.In this case,the issues of the capitalization and transfer of scientific knowledge and its rapid transformation into professional skills are directly addressed.However,there is no method to derive e-learning teaching material from project results.So,this paper presents the e-LITE Method and its application to the ISTA3 project to support the process of developing a e-learning training.This application has allowed us to highlight the contributions of the method that promotes better knowledge sharing between partners of a research project and the development and transfer of research results to the professional world.So,after the presentation of the method,an application to the ISTA3 project will be presented.     

Optimizing radial basis function neural network based on rough sets and affinity propagation clustering algorithm

A novel method based on rough sets (RS) and the affinity propagation (AP) clustering algorithm is developed to optimize a radial basis function neural network (RBFNN). First, attribute reduction (AR) based on RS theory, as a preprocessor of RBFNN, is presented to eliminate noise and redundant attributes of datasets while determining the number of neurons in the input layer of RBFNN. Second, an AP clustering algorithm is proposed to search for the centers and their widths without a priori knowledge about the number of clusters. These parameters are transferred to the RBF units of RBFNN as the centers and widths of the RBF function. Then the weights connecting the hidden layer and output layer are evaluated and adjusted using the least square method (LSM) according to the output of the RBF units and desired output. Experimental results show that the proposed method has a more powerful generalization capability than conventional methods for an RBFNN.     

机电一体化培训和教育中的电子移动学习课件开发(英文)

Knowledge is essential for the competitiveness of individuals as well as organizations.Thus the application of the latest methodologies and technologies are utilized to support knowledge acquisition,warehousing,distribution,and transfer.Means and methods of web 2.0 are useful to support this procedure.Especially,highly complex and very dynamic knowledge domains have to be accessible and applicable in the framework of learning network communities,including the stakeholders of training and education.Mechatronics for example is such an interdisciplinary,dynamic field of research and application.Based on intelligence,software,and hardware it is requiring special approaches for developing a courseware based learning and knowledge transfer environment.After defining the specifics of mechatronics education and postgraduate training in the context of e-education,the concepts of the development and utilization of mechatronic courseware can be deduced from e-learning 2.0 and mobile learning facilities,possibilities,and abilities.Mechatronic courseware will be developed by using authoring software and embedding the material into learning management systems with respect to general methods and rules of modern system and software development.As an example,the courseware is used for vocational training and further education especially in cooperation networks of educational institutions and SME.