• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.12
• /
• pp.1687-1696
• /
• 1995

An integrated fault diagnosis system for heterogeneous manufacturing environments is developed. This system has a contrast with existing diagnosis systems in the respect that they are mostly for diagnosing faults on individual machines. In addition to the usual (e.g., audio, electrical) diagnostic signals, the characteristics of products from the machines are considered as the unifying diagnostic parameters among heterogeneous machines in the diagnosis. The system is composed of a knowledge representation scheme and a diagnostic query processing mechanism. Its knowledge representation scheme allows the diagnostic knowledges from heterogeneous unit diagnostic systems to be uniformly expressed in terms of the causal relations among relevant data items. It is flexible in the sense that causes for one relation can be effects for another may be reflected on our knowledge representation scheme. The diagnosis mechanism is based on a probabilistic inferencing method. This probablistic diagnosis mechanism provides more general diagnosis than existing ones in that it accommodates multiple causes and takes complication among causes into account. These scheme and mechanism are applied to a typical example to demonstrate how our system works.

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.5
• /
• pp.622-629
• /
• 1999

This paper presents the development of an interactive knowledge-based CAM system for design-ing and manufacturing the mold. The system is composed of two functional parts. One is the geo-metric modeller that uses the feature-based models. The models include base plate step, hole, pocket, boss and slot, These are designed by interactive user interface. The other is the expert sys-tem module with inference engine and knowledge database of workpiece material tools manufac-turing machines process an working conditions. With two parts the final mold shape is generated with manufacturing information for effective production.

• Journal of KIISE
• /
• v.43 no.9
• /
• pp.963-973
• /
• 2016

Providing a semantic knowledge system using media ontologies requires not only conventional axiom reasoning but also knowledge extension based on various types of reasoning. In particular, spatio-temporal information can be used in a variety of artificial intelligence applications and the importance of spatio-temporal reasoning and expression is continuously increasing. In this paper, we append the LOD data related to the public address system to large-scale media ontologies in order to utilize spatial inference in reasoning. We propose an RDFS/Spatial inference system by utilizing distributed memory-based framework for reasoning about large-scale ontologies annotated with spatial information. In addition, we describe a distributed spatio-temporal SPARQL parallel query processing method designed for large scale ontology data annotated with spatio-temporal information. In order to evaluate the performance of our system, we conducted experiments using LUBM and BSBM data sets for ontology reasoning and query processing benchmark.

• Journal of Internet Computing and Services
• /
• v.15 no.6
• /
• pp.99-106
• /
• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• The KIPS Transactions:PartB
• /
• v.13B no.4 s.107
• /
• pp.421-428
• /
• 2006

Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.3-8
• /
• 2001

Regarding current rapid innovations and applications of information and telecommunication technologies as well as economical requirements, modeling and simulation (M&S) plays an increasingly important role for the planning, development and operation of high-tech products and systems. M&S has to seen as a key technology for multi-facetted analysis of complex systems during their life-cycles. For reasons as accuracy, credibility and cost-effectiveness, the selection of adequate and effective M&S techniques and tools is of significant importance. Regarding these aspects, this paper summarizes the basic methodological modeling approach for effective product and system modeling. In addition, besides a classification of different basic architectures and taxonomies combining knowledge-processing and simulation techniques, the paper describes some practical implementations and experiences.

• The Journal of the Korea Contents Association
• /
• v.5 no.5
• /
• pp.10-16
• /
• 2005

Information producing and sharing methods are modified into digital forms. All kinds of documents are also converted into electronic forms so they become very useful and besides, they are increasing in quantity. Thus effective contents management system is requisite. Until now CMS(Contents Management System) has problems including composite contents management, processing delay and deterioration of contents because of deficiency of consistent contents storing methods and policies. In this paper an ECM(Efficient Contents Management) system is proposed for efficient processing of multimedia data and ubiquitous KM(Knowledge Management).

• The KIPS Transactions:PartB
• /
• v.10B no.6
• /
• pp.593-598
• /
• 2003

Machine learning organizes knowledge for efficient and accurate reuse. This paper is concerned with methods of concept learning from examples, which glean knowledge from a training set of preclassified ‘objects’. Ideally, training facilitates classification of novel, previously unseen objects. However, every learning system relies on processing and representation assumptions that may be detrimental under certain circumstances. We explore the biases of a well-known learning system, ID3, review improvements, and introduce some improvements of our own, each designed to yield accurate and pedagogically sound classification.

• English Language & Literature Teaching
• /
• v.10 no.1
• /
• pp.1-22
• /
• 2004

The primary purpose of this study is to investigate the applicability of content and formal schemata for processing the scientific texts which encompass the human knowledge of the physical world. In general, schema theory is based on the culture-oriented background of a text. From this point of view, the problem as to whether both content and formal schemata are applicable to the comprehension of a scientific text deserves a focal attention in terms of information processing modes. The results of empirical study indicate that whereas the universality of general knowledge content about the natural world attenuates the tenets of schema theory, the rhetorical organization of scientific texts encourages the application of the schema-based approach; the reader's familiarity with the structural patterns of a text facilitates his reading comprehension.

• Journal of Information Processing Systems
• /
• v.14 no.2
• /
• pp.523-538
• /
• 2018

Keystroke dynamics user authentication is a behavior-based authentication method which analyzes patterns in how a user enters passwords and PINs to authenticate the user. Even if a password or PIN is revealed to another user, it analyzes the input pattern to authenticate the user; hence, it can compensate for the drawbacks of knowledge-based (what you know) authentication. However, users' input patterns are not always fixed, and each user's touch method is different. Therefore, there are limitations to extracting the same features for all users to create a user's pattern and perform authentication. In this study, we perform experiments to examine the changes in user authentication performance when using feature vectors customized for each user versus using all features. User customized features show a mean improvement of over 6% in error equal rate, as compared to when all features are used.