• Journal of applied mathematics & informatics
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• v.39 no.1_2
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• pp.105-116
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• 2021

Information systems and decision rules with imprecision and uncertainty in data analysis are studied in complete residuated lattices. In this paper, we introduce the notions of distance spaces, Alexandrov pretopology (precotopology) and join-meet (meet-join) operators in complete co-residuated lattices. We investigate their relations and properties. Moreover, we give their examples.

• The Pure and Applied Mathematics
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• v.29 no.1
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• pp.19-29
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• 2022

Information systems and decision rules with imprecision and uncertainty in data analysis are studied in complete residuated lattices. In this paper, we introduce the notions of Alexandrov pretopology (precotopology) and join-meet (meet-join) operators in complete co-residuated lattices. Moreover, their properties and examples are investigated.

• Ocean Systems Engineering
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• v.8 no.1
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• pp.41-55
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• 2018

Accidental oil and gas leak is a critical concern for the offshore industry because it can lead to severe consequences and as a result, it is imperative to evaluate the probabilities of occurrence of the consequences of the leakage in order to assess the risk. Event Tree Analysis (ETA) is a technique to identify the consequences that can result from the occurrence of a hazardous event. The probability of occurrence of the consequences is evaluated by the ETA, based on the failure probabilities of the sequential events. Conventional ETA deals with events with crisp failure probabilities. In offshore applications, it is often difficult to arrive at a single probability measure due to lack of data or imprecision in data. In such a scenario, fuzzy set theory can be applied to handle imprecision and data uncertainty. This paper presents fuzzy ETA (FETA) methodology to compute the probability of the outcomes initiated due to oil/gas leak in an actual offshore-onshore installation. Post FETA, sensitivity analysis by Fuzzy Weighted Index (FWI) method is performed to find the event that has the maximum contribution to the severe sequences. It is found that events of 'ignition', spreading of fire to 'equipment' and 'other areas' are the highest contributors to the severe consequences, followed by failure of 'leak detection' and 'fire detection' and 'fire water not being effective'. It is also found that the frequency of severe consequences that are catastrophic in nature obtained by ETA is one order less than that obtained by FETA, thereby implying that in ETA, the uncertainty does not propagate through the event tree. The ranking of severe sequences based on their probability, however, are identical in both ETA and FETA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.117-131
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• 2015

Conventional data envelopment analysis (DEA) models require that inputs and outputs are given as crisp values. Very often, however, some of inputs and outputs are given as imprecise data where they are only known to lie within bounded intervals. While a typical approach to addressing this situation for optimization models such as DEA is to conduct sensitivity analysis, it provides only a limited ex-post measure against the data imprecision. Robust optimization provides a more effective ex-ante measure where the data imprecision is directly incorporated into the model. This study aims to apply robust optimization approach to DEA models with imprecise data. Based upon a recently developed robust optimization framework which allows a flexible adjustment of the level of conservatism, we propose two robust optimization DEA model formulations with imprecise data; multiplier and envelopment models. We demonstrate that the two models consider different risks regarding imprecise efficiency scores, and that the existing DEA models with imprecise data are special cases of the proposed models. We show that the robust optimization for the multiplier DEA model considers the risk that estimated efficiency scores exceed true values, while the one for the envelopment DEA model deals with the risk that estimated efficiency scores fall short of true values. We also show that efficiency scores stratified in terms of probabilistic bounds of constraint violations can be obtained from the proposed models. We finally illustrate the proposed approach using a sample data set and show how the results can be used for ranking DMUs.

• Journal of Bone Metabolism
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• v.25 no.4
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• pp.235-241
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• 2018

Background: Procollagen type I N-terminal propeptide (PINP) is one of the most clinically useful bone formation biomarkers. Therefore, the purpose of this study was to independently evaluate the performance of automated total PINP assay and established age- and gender- specific reference intervals for PINP in healthy Korean population. Methods: The imprecision, linearity, and detection capability of Elecsys total PINP assay was determined and reference interval was established using 599 serums from Korean population with normal bone mineral densities based on bone densitometry. Age groups were divided into 20s, 30s, 40s, 50s, 60s and over. Results: Elecsys total PINP had excellent performance in imprecision, linearity, and detection capability. When partitioning age groups in Korean male and female populations, there was significant difference in total PINP between different age groups. In male populations, PINP level was decreased with increasing age, then it remained steady after middle-age. In female populations, there was a decreasing tendency similar to that in the male population with a sharp increase in the 50 to 59 age group. Conclusions: Elecsys total PINP assay showed precise and reliable performance in our study. We established age-related PINP reference intervals for Korean male and female population with normal bone mineral densities.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.706-708
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• 2002

Vibration, giving rise to acoustical noise, is an important index of motor performance. The unbalance force due to rotor eccentricity caused by manufacturing imprecision or bearing defects is one possible source of excitation to vibration. With the advent of new high-energy magnetic material together with high precision motor applications, magnetic sources of vibration are becoming more serious. This paper introduces two types of high-speed slotless permanent magnet (PM) machine for electro-mechanical battery and investigates unbalance force due to static eccentricity with finite element method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.231-242
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• 1997

This paper describe an approximation method for solving the minimum makespan problem of job shop scheduling with fuzzy processing time. We consider the multi-part production scheduling problem in a job shop scheduling. The job shop scheduling problem is a complex system and a NP-hard problem. The problem is more complex if the processing time is imprecision. The Fuzzy set theory can be useful in modeling and solving scheduling problems with uncertain processing times. Lee-Li fuzzy number comparison method will be used to compare processing times that evaluated under fuzziness. This study propose heuristic algorithm solving the job shop scheduling problem under fuzzy environment. In This study the proposed algorithm is designed to treat opinions of experts, also can be used to solve a job shop environment under the existence of alternate operations. On the basis of the proposed method, an example is presented.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.8
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• pp.65-72
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• 2004

For the burrs formed in machining are irregular and very sharp in shape, it is usually very difficult to measure burr accurately. It was proved that micro burr geometry can be measured imprecision by the Conoprobe sensor using conoscopic holography method. We developed 3D burr measurement system using this sensor. The system is composed of Conoprobe sensor, XY table, controller and 3D measurement program. Some measurements using the developed system are conducted for the burrs formed in micro drilling and piercing. Specific software fur burr measurement includes several function, calculation of burr volume, average burr height. Burs formed on a curved surface were compensated and measured successfully using the basic surface compensation function.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.90-102
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• 1996

Process incapability index which is intended to evaluate the process capability by measuring process incapability provides more detailed information by dividing information about the process mean and variance. But when the target value is not consistent with the center of specification, it is very difficult to evaluate the process capability accurately. Thus it is necessary to improve the existing process incapability index. The improved process incapability index can identify the variation of the process faster than other process capability indices when applied firstly, to the precision process which can be affected sensitively by the change of the process, secondly, to the ordinary process where cost difference from the change of process is noticeable. By using subindices such as inaccuracy index and imprecision index, it is easier for quality manager to find where the cause of the variation of process is, and to take necessary action in advance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1072-1077
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• 1992

In ths paper a new active assembly algorithm for chamferless precision parts mating, is considered. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly mehtod alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as imperfect knowledge of the parts being assembled as well as the limitation of the devices performing the assebled as well as the limitation of the devices performing the assembly. To cope with these problems, a self-learning rule-based assembly algorithm is proposed by intergaring fuzzy set theory and neural network. In this algortihm, fuzzy set theory copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly schemen so as to learn fuzzy rules form experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly algorithm is evaluated through a series of experiments. The results show that the self-learning fuzzy assembly scheme can be effecitively applied to chamferless precision parts mating.