• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.564-566
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• 2003

There are no immutable phenomena in reality. A lot of applications are dealing with data characterized by spatial and temporal and/or uncertain features. Currently, there has no any data model accommodating enough those three elements of spatial objects to directly use in application systems. For such reasons, we introduce a fuzzy spatio -temporal data model (FSTDM) and a method of integrating temporal and fuzzy spatial operators in a unified manner to create fuzzy spatio -temporal (FST) operators. With these operators, complex query expression will become concise. Our research is feasible to apply to the management systems and query processor of natural resource data, weather information, graphic information, and so on.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.827-836
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• 2002

Moving object management systems manage spatiotemporal data, which change their location over tine such as people, animals, and cars. These moving object management systems can be applied to vehicle location tracking, digital battlefield, location-based service, and so on. The existing moving object management systems only manage past or future location of the moving objects separately. Therefore, they cannot suggest estimation method of uncertain past or future location of the moving objects. In this paper, we propose a moving object management system, which not only manages historical data of the moving objects, but also predicts past and future location of the moving objects using historical data stored in database. We define the moving objects for vehicle location tracking and propose a moving object database structure. Finally, we suggest an execution model of the proposed system and apply the execution model to a virtual scenario for vehicle tracking.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.173-181
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• 1997

In oriental medicine, it is required that correct medical knowledge should be maintained for medical expert system which analyzes and diagnoses patients symptoms. Typical medical expert system has a knowledge base as its core, and the knowledge base contains a domain specific knowledge about patients records. However, oriental medicine diagnostic knowledge is formed mostly as qualitative data, knowledge could be ambiguous and uncertain. In this paper, we looked at quantification methods and propose a method for quantifying the oriental medicine diagnostic knowledge, which is improving the knowledge base of an oriental medicine expert system.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.06a
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• pp.1-25
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• 1995

This paper deals with the development of an intelligent CAD system for specifying the operation sequence in cold forging. Cold forging technology is facing with various new design requirements. Therefore, it is very important to develop a decision method for the operation sequence, with comparatively high adaptability to the new requirements. An intelligent CAD system which is the uncertain factors in human knowledge into consideration by applying fuzzy theory is established. Various actual design data about were organized, and these organized data were applied to the system as the case base. The system automatically generates the design data of operation sequence such as the forming method and the geometric data of products in each operation stage by the reasoning method applied the fuzzy pattern matching. By comparing the design results in the above system with the actual design data of a human expert, this paper presents that our method is useful for practical application.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.85-110
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• 2008

Ground investigation data to be used as a basis for geotechnical analysis and foundation design are usually troubled with large uncertainty, due to natural variability and limited number of data. Statistical methods can be a rational tool for handling such uncertain ground data, in particular with a view to the selection of characteristic values for estimating ground design parameters used in design. The characteristic values of soil properties for use in geotechnical design have oftenly based on not only a subjective judgment but also engineer's past acumulated experience. This paper discussed some statistical methods which can handle such intrinsic ground uncertainty data with a case design in a rational manner.

• Journal of the Korean Society of Safety
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• v.11 no.4
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• pp.42-48
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• 1996

Since the fatigue phenomenon is characterized as a probability feature and test data cannot be easily collected number its small sample data are uncertain. Therefore, statistical evaluation methods should necessarily be introduced into data evaluation. With such a basic concept in mind, this study attempted to apply conventional statistical processing methods to the fatigue data and thereby present a new evaluation method in consideration of the fact that the fatigue test is usually performed within a limited number. That is a package evaluation method was adopted which co-realtes parameters between different levels of capacity in E-N or S-N level. So far fatigue limits have been found by means of stiarcase method. But it was also disclosed that this new method has its own disadvantage because limited frequencies are not duely considered.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.25-32
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• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• Journal of Distribution Science
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• v.16 no.6
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• pp.25-35
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• 2018

Purpose - Although marketing networks are crucial competitive advantage in terms of firm's new information and resource acquisition ability, their impact on new product development performance remains vague, especially under environmental uncertainty. The principal objective of this research is to provide a better understanding of effects of technological uncertainty and volume uncertainty on first tier supplier's perceived performance of new product development under conditions reflecting varying levels of structural holes. Specifically, this research examines the moderating effect of structural holes on the relationship between environmental uncertainty and new product development performance. Research design, data, and methodology - To test the hypotheses, a questionnaire survey was conducted with a Korean engineering firm's major first-tier suppliers in the context of internal network entities, manufacturer-supplier-subsupplier relationships, and to verify the proposed hypotheses, structural equation modeling was established. Construct measures were based on existing measures and previous research. Results - The survey results indicate that technological uncertainty and volume uncertainty differentially affect NPD performance under conditions of high and low structural holes. Conclusions - This study offer some theoretical and practical implications among distribution channel members, especially, this study suggests that interfirm networks have critical competitive advantage in uncertain environments. The distinctiveness of engineering industry might limit the generalizability of the results. Thus, future research should consider a wider range of industries.