• Journal of the Korea Society of Computer and Information
• /
• v.6 no.1
• /
• pp.60-66
• /
• 2001

We designed a role-based access control model that can resolve the complicated tasks of control requirements. The designed access control model can control permissions efficiently use of a role-based access control. It guarantees the confidentiality integrity and availa information making use of identity-based and rule-based access controls. It can also centre information flow. Our access control model protects resources from unauthorized accesses b multi-level security policies such as role, security level, integrity level and ownership.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.189-192
• /
• 2007

This study proposes a Natural Language Query Framework (NLQF) on the semantic web to support the intelligent deduction at semantic level. A large number of former researches are focused on the knowledge representation on the semantic web. However, to revitalize the intelligent agent (IA)-based automated e-business contract with human customers, there is a need for semantic level approach to the web information. To enable accessing web information at semantic level, this paper discusses the pattern of complex natural language processing at first, and then the semantic web-based natural language inference in e-business environment. The NL-based approach could help the IAs on the web to communicate with customers and other IAs with more natural interface than traditional HTML-based web information. Therefore, our proposed NLQF will be used in semantic web-based intelligent e-business contracts between customers and IAs.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2337-2341
• /
• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• Korean Journal of Computational Design and Engineering
• /
• v.11 no.2
• /
• pp.88-96
• /
• 2006

This paper introduces an approach to ontology-based framework for knowledge management in a product development domain. The participants in a product life cycle want to share the product knowledge without any heterogeneity. However, previous knowledge management systems do not have any conceptual specifications of their knowledge. We suggest the three levels of knowledge framework. First level is an axiom, which specifies the semantics of concepts and relations. Second level is a product development knowledge map. It defines the common domain knowledge which domain experts agree with. Third level is a specialized knowledge for domain, which includes three knowledge types; expert knowledge, engineering function and data-analysis-based knowledge. We propose an ontology-based knowledge framework based on the three levels of knowledge. The framework has a uniform representation; first order logic to increase integrity of the framework. We implement the framework using prolog and test example queries to show the effectiveness of the framework.

• Steel and Composite Structures
• /
• v.21 no.6
• /
• pp.1389-1410
• /
• 2016

This paper proposes a hybrid of topological derivative-based level set method (LSM) and isogeometric analysis (IGA) for structural topology optimization. In topology optimization a significant drawback of the conventional LSM is that it cannot create new holes in the design domain. In this study, the topological derivative approach is used to create new holes in appropriate places of the design domain, and alleviate the strong dependency of the optimal topology on the initial design. Furthermore, the values of the gradient vector in Hamilton-Jacobi equation in the conventional LSM are replaced with a Delta function. In the topology optimization procedure IGA based on Non-Uniform Rational B-Spline (NURBS) functions is utilized to overcome the drawbacks in the conventional finite element method (FEM) based topology optimization approaches. Several numerical examples are provided to confirm the computational efficiency and robustness of the proposed method in comparison with derivative-based LSM and FEM.

• ETRI Journal
• /
• v.34 no.4
• /
• pp.602-612
• /
• 2012

It is becoming increasingly difficult to identify promising technologies due to the influx of new technologies and the high level of complexity involved in many of these technologies. Identifying promising information and communications technology (ICT)-based converging technologies holds the key to finding new sources of economic growth and forward momentum. The goal of this study is to identify cutting-edge ICT-based converging technologies by examining the latest trends in the US patent market. Analyzing the US patent market, the most competitive of such markets in the world, can yield certain clues about which of the ICT-based converging technologies may be the next revolutionary technologies. For a classification of these technologies, this study follows the International Patent Classification system. As for ICT, there are 58 related fields at the subclass level and 831 fields at the main-group level. For emerging and converging technologies, there are 75 at the main-group level. From these technologies, a final selection for cutting-edge ICT-based converging technologies is made using a composite index reflecting the converging coefficient, emerging coefficient, and technology impact index.

• Environmental Engineering Research
• /
• v.14 no.2
• /
• pp.111-119
• /
• 2009

A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.129-143
• /
• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.1
• /
• pp.38-46
• /
• 2009

With the rapid increase in the number of Web documents, the problem of information overload is growing more serious in Internet search. In order to ease the problem, researchers are paying attention to personalization, which creates Web environment fittingly for users' preference, but most of search engines produce results focused on users' queries. Thus, the present study examined the method of producing search results personalized based on a user's understanding level. A characteristic that differentiates this study from previous researches is that it considers users' understanding level and searches documents of difficulty fit for the level first. The difficulty level of a document is adjusted based on the understanding level of users who access the document, and a user's understanding level is updated periodically based on the difficulty of documents accessed by the user. A Web search system based on the results of this study is expected to bring very useful results to Web users of various age groups.

• Journal of Digital Convergence
• /
• v.4 no.2
• /
• pp.51-65
• /
• 2006

This study is to evaluate the morality of teenagers with regard to features of justice. On the basis of the findings, an online morality level test system is designed and implemented to help students understand themselves better and to increase moral maturity through this self-test method based on Kohlberg's Morality Development Level. The main purpose of this study is to help students test and evaluate their morality, and it will be contributed to slough off egocentrism and to orient a relationship based on a mutual respect by using the embodied system. If this system can be applied successfully, an effective improvement on students' further education guidance may be gained because the test and its results are made in the system simultaneously. Also this easy and fast test system can attain much more economical effects than a written test.