• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.737-744
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• 2000

This paper resorts to rock mass rating and rock mass quality to draw value based on the evaluation of rock and to draw interrelation formula in relation to rock mass quality, A comparative analysis was given of survey values reported in the existing documents. This paper has tried to find out the relationship between RMR and Q System for the sake of choosing rational reinforcing patterns and of the safety of tunnels. The results run as follow: RMR=8.251n(Q)+43.83. This paper has also tried to find out the relationship between RMR and Q System by using Fuzzy Approximate Reasoning Concept. We suggest that those in charge should not depend on a single system only after evaluating the classification of rocks, and compare one result with another for the good of keeping track of the condition of base rocks in a better way.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.187-193
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• 2005

In this paper, we proposes a man-machine interface design for fault diagnosis system with inter-node search method in a Petri net model. First, complicated fault cases are modeled as the Petri net graph expressions. Next, to find out causes of the faults on which we focus, a Petri net model is analyzed using the backward reasoning of transition-invariance in the Petri net. In this step, the inter-node search method algorithm is applied to the Petri net model for reducing the range of sources in faults. Finally, the proposed method is applied to a fault diagnosis of a refrigeration system to confirm the validity of the proposed method.

• International Journal of CAD/CAM
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• v.2 no.1
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• pp.69-75
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• 2002

This paper presents the development of an Intelligent Cavity Layout Design System (ICLDS) for multiple cavity injection moulds. The system is intended to assist mould designers in cavity layout design at concept design stage. The complexities and principles of cavity layout design as well as various dependencies in injection mould design are introduced. The knowledge in cavity layout design is summarized and classified. The functionality, the overall structure and general process of ICLDS are explained. The paper also discusses such issues as knowledge representation and case-based reasoning used in the development of the system. The functionality of the system is illustrated with an example of cavity layout design problem.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.445-454
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• 2001

A workflow model is useful fur business process analysis and has often been implemented for office automation through information technology. Accordingly, the results of workflow modeling need to be systematically managed as information assets. In order to manage the modeling process effectively, it is necessary to enhance the efficiency of their reuse. Therefore, this paper creates a Document-barred Workflow Modeling Support System (DWMSS) using a case-based reasoning (CBR) approach. It proposes a system architecture, and the corresponding modeling process is developed. Furthermore, a repository, which consists of a case base and vocabulary base, is built. A carte study is illustrated to demonstrate the usefulness of th is system.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.84-89
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• 2022

For system maintenance optimization, it is necessary to establish a state information system by CBM+ including CBM and RCM, and sensor selection for CBM+ application requires system process for function model analysis at the early design stage. The study investigated the contents of CBM and CBM+, analyzed the function analysis tasks and procedures of the system, and thus presented a D-FMEA based sensor selection inference methodology at the early stage of design for CBM+ application, and established it as a D-FMEA based sensor selection inference process. The D-FMEA-based sensor inference methodology and procedure in the early design stage were presented for diesel engine sub assembly.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.5
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• pp.942-949
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• 2009

We in this paper propose the method for diagnosis patients through the reasoning based on the diagnosis ontology in oriental medicine. In prior studies, it is simply diagnosed with the information of main symptoms, optional symptoms, and tongue / pulse. In addition, ontology itself has subjective opinions of oriental medical doctors for patients in form of axioms. There is a problem in latter case that it is difficult for other oriental medical doctors to change knowledge within the ontology. In order to solve these problems, we have constructed the diagnosis ontology and the reasoning algorithm as followings: First, in order to raise the diagnosis accuracy, we constructed the diagnosis ontology with pattern identifications, main symptoms, optional symptoms, and tongue / pulse. We also utilize the diagnosis points described in the pathology textbook, which has been studied in all of domestic oriental medical colleges. This information is represented as OWL instances in ontology, not OWL axioms so that it can be easily updated. Second, we suggest the algorithms for diagnosis reasoning and learning method based on the ontology. We have implemented the reasoning and learning system according to the diagnosis algorithm. In future study, we will construct the diagnosis ontology with all of pattern identifications and symptoms within the pathology textbook.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.1-26
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• 2013

Estimating levels of user trust is important for maintaining continuous use of e-commerce systems because trust alleviates user concerns about the invisibility of service providers or their reputation. Conventional trust estimation approaches such as policy-and reputationbased reasoning have focused on the experience of e-commerce systems at an early stage. However, only a few trust reasoning methods have considered the mature stage, which is more related to continuance intention. We propose a trust reasoning method dedicated to the mature stage of using e-commerce systems. In particular, a new method of unobtrusively estimating the degree of user intimacy is developed, because intimacy has been highly associated with trust as well as reputation. Our experiments show that the proposed method is valid and can be used in conjunction with reputation-based trust reasoning.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.907-912
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• 2007

The present level of ubiquitous computing technology have developed to the point where Home-server provides services that user require directly for user in the intelligent space. But it will need intelligent system to provides more active services for user in the near future. In this paper, we define the environment information about situation that user is in as Context, and collect the Context that stereotype as 4W1H form for construct the system that can decision service will be provide from information about a situation that user is in, without user's involvement. Additionally we collect information about user's emotional state, use these informations as nodes of Bayesian network for probabilistic reasoning. From that, we materialize Context Awareness system about it that what kind of situation user is in. And, we propose the Context-based Service reasoning model using Bayesian Network from the result of Context Awareness.

• Journal of KIISE
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• v.43 no.1
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• pp.87-95
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• 2016

Recently, due to the development of the Internet and electronic devices, there has been an enormous increase in the amount of available knowledge and information. As this growth has proceeded, studies on large-scale ontological reasoning have been actively carried out. In general, a machine learning program or knowledge engineer measures and provides a degree of confidence for each triple in a large ontology. Yet, the collected ontology data contains specific uncertainty and reasoning such data can cause vagueness in reasoning results. In order to solve the uncertainty issue, we propose an RDFS reasoning approach that utilizes confidence values indicating degrees of uncertainty in the collected data. Unlike conventional reasoning approaches that have not taken into account data uncertainty, by using the in-memory based cluster computing framework Spark, our approach computes confidence values in the data inferred through RDFS-based reasoning by applying methods for uncertainty estimating. As a result, the computed confidence values represent the uncertainty in the inferred data. To evaluate our approach, ontology reasoning was carried out over the LUBM standard benchmark data set with addition arbitrary confidence values to ontology triples. Experimental results indicated that the proposed system is capable of running over the largest data set LUBM3000 in 1179 seconds inferring 350K triples.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.49-54
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• 2011

Case-based reasoning is an efficient method to find solutions for new problems by using past cases after appropriate changes. It is widely used in everyday life because it resembles the way human acts. In this paper, we propose a military system that generates the most appropriate tactics for CGF (Computer Generated Forces) by utilizing past practices. It indeed applies case-based reasoning at the process of armed conflict. When the CGF squad on a mission, they will be given an action plan to reach the final goal. In the process of executing, tactics for specific action should be organized such as attacks, ambushes, and tactical moves. By using the proposed method, tactics were generated by case-based reasoning. The proposed system successfully receives input through each command and control agent, measures the degree of similarity with the case in case DB, selects the most similar case, modifies, uses, and then stores it for next time.