• 한국가스학회지
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• 제18권4호
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• pp.68-75
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• 2014

독성가스시설에서 대형사고로 인한 손실을 감소시키기 위해서는 인적요소를 제어하고, 평가하는 것이 필요하다. 기존의 안전성 평가는 기계적 결함이나 시스템의 위험이 주로 강조되어 왔으며, 인적오류를 관리하는 평가방법이 부족하여 본 연구에서는 독성가스시설의 사고관리 상황에서 인적오류를 구성하는 수행영향인자 분류체계를 제안하고자 하였다. 이를 위해 주요 수행영향인자 분류체계의 유형을 수집하여 검토와 분석을 한 후 4가지(작업자 특성, 시스템, 직무특성 및 직무환경)로 나누고, 독성가스시설의 상황적 특성과 직무특성 및 작업환경을 고려하여 수행영향인자를 선택하였다. 이로 부터 인적오류의 평가에 사용하기 적절한 수행영향인자 체계를 구축하고, 구축한 수행영향인자 분류체계를 독성가스시설에서 발생하였던 사고 사례분석을 통해 적용성을 검토하였다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.199-202
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• 1996

Although numerous studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective to solve a specific problem. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the prediction performance. This paper proposes the post-model integration method, which means integration is performed after individual techniques produce their own outputs, by finding the best combination of the results of each method. To get the optimal or near optimal combination of different prediction techniques. Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an objective function subject to numerous hard and soft constraints. This study applied three individual classification techniques (Discriminant analysis, Logit and Neural Networks) as base models to the corporate failure prediction context. Results of composite prediction were compared to the individual models. Preliminary results suggests that the use of integrated methods will offer improved performance in business classification problems.

• 한국경영과학회지
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• 제22권3호
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• pp.163-173
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• 1997

Although numerous studies demonstrate that one technique outperforms the others for a given data set, it is hard to tell a priori which of these techniques will be the most effective to solve a specific problem. It has been suggested that the better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the predictive performance. This paper proposes the post-model integration method, which tries to find the best combination of the results provided by individual techniques. To get the optimal or near optimal combination of different prediction techniques, Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an object function subject to numerous hard and soft constraints. This study applies three individual classification techniques (Discriminant analysis, Logit model and Neural Networks) as base models for the corporate failure prediction. The results of composite predictions are compared with the individual models. Preliminary results suggests that the use of integrated methods improve the performance of business classification.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2014년도 추계 학술논문 발표대회
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• pp.214-215
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• 2014

Recently, Russia decided to export an annual 7.5 million tons of natural gas to Korea over 30 years from 2015, as also deal with China, planed to build a pipeline connecting Siberia to Shandong Peninsula about 4000km. Risk management is required depending on the project in extreme cold weather, because it is concerned about the behavior of the seasonal changes in soil temperature and the strain of pipe according to the long-distance pipeline construction. The plan of data management shall be prepared in parallel for a sophisticated risk management, because a data is massive scale and it is generated/accumulated in real time. Therefore, this research is aimed to classify a data items in engineering stage of pipeline by previous studies for managing a generated data depending on the detail works in extreme cold weather. We expect to be provided the foundation of an efficient classification system of a generated data from the pipeline project life cycle.

• Advances in Energy Research
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• 제6권2호
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• pp.103-129
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• 2019

While global demand for energy increases annually, at the same time the demand for carbon-free, sulphur-free and NO_x-free energy sources grows considerably. This state poses a challenge in the research for newer sources like biomass and shale gas as well as renewable energy resources such as solar, wind, geothermal and hydraulic energy. Although wave energy also is a form of renewable energy it has not fully been exploited technically and economically so far. This study tries to explain those reasons in which it is beyond doubt that the demand for wave energy will soon increase as fossil energy resources are depleted and environmental concerns gain more importance. The electrical energy supplied to the grid shall be produced from wave energy whose conversion devices can basically work according to three different systems. i. Systems that exploit the motions or shape deformations of their mechanisms involved, being driven by the energy of passing waves. ii. Systems that exploit the weight of the seawater stored in a reservoir or the changes of water pressure by the oscillations of wave height, iii. Systems that convert the wave motions into air flow. One of the aims of this study is to present the classification deficits of the wave energy converters (WECs) of the "wave developers" prepared by the European Marine Energy Center, which were to be reclassified. Furthermore, a new classification of all WECs listed by the European Marine Energy Center was arranged independently. The other aim of the study is to assess the technological state of the art of these WECs designed and/or produced, to obtain an overview on them.

• 한국식품조리과학회지
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• 제22권3호통권93호
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• pp.299-306
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• 2006

The numerous varieties of coffee beans contain a wide range prices and qualities. While the varieties of green coffee beans can generally be distinguished by their appearance, this visual criterion is impossible after the roasting process. Therefore, we need to develop a classification method or device. In this study, the potential of a new type of electronic nose, fast gas chromatography based on a surface acoustic wave sensor(SAW), was evaluated for the classification of origins and blended commercial brands in roasted coffee beans. Eight blended commercial brands and the origins of four similarly roasted ground coffee beans(with no significant difference of color) were rapidly(90 sec/sample) classified. The reproductive results were easily understandable over the aroma image pattern by $VaporPrint^{TM}$. In conclusion, GC-SAW electronic nose can be applied to the classification of origins and commercial brands in roasted ground coffee beans and to e evaluation of the similarities and differences of volatile pattern between samples.

• 지구물리와물리탐사
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• 제16권4호
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• pp.268-274
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• 2013

마그마 또는 가스가 지하에서 이동함으로써 발생되는 화산지진의 연속적인 관측은 활화산 감시의 가장 중요한 방법 중 하나이다. 이 해설논문에서는 화산지진의 특징에 대해 살펴보았으며, 진원, 지진파형, 주파수, 암상 그리고 메커니즘에 따른 분류를 간단히 설명하였다. 또한 일본, 미국, 이탈리아, 뉴질랜드의 성공적인 분화 경보 사례와 화산지진 감시 실태를 소개하였다.

• 한국추진공학회지
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• 제14권3호
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• pp.79-86
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• 2010

현재 운용중인 UAV 추진기관의 종류 및 각각의 특징과 장단점들을 살펴보았다. 전기추진을 위한 에너지원과 내연기관 추진의 동력원을 상호 비교하였으며, 미래의 UAV에 적합한 추진기관들의 성능 요구 조건을 분석, 제시하였다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1163-1167
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• 2007

Many railway safety measures are carried out after Daegue subway fire accident. Such as replacement of train interior material, fire extinguish and toxic gas evacuation facilities, exercise on emergency response, setting up of national safety management system, and safety technology research. But these safety measures are not considered by system safety due to lack of risk and hazard information. In order to assess fire risk on system level, we proposed hazard events and causes classification for railway fire accident risk analysis.

• 한국산업융합학회 논문집
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• 제25권2_1호
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• pp.169-176
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• 2022

Prognostics and health management (PHM) is recently converging throughout the industry, one of the trending issue is to detect abnormal conditions at decanter centrifuge during water treatment facilities. Wastewater treatment operation produces corrosive gas which results failures on attached sensors. This scenario causes frequent sensor replacement and requires highly qualified manager's visual inspection while replacing important parts such as bearings and screws. In this paper, we propose anomaly detection by measuring the vibration of the decanter centrifuge based on the video camera images. Measuring the vibration of the screw decanter by applying the optical flow technique, the amount of movement change of the corresponding pixel is measured and fed into the LST M model. As a result, it is possible to detect the normal/warning/dangerous state based on LSTM classification. In the future work, we aim to gather more abnormal data in order to increase the further accuracy so that it can be utilized in the field of industry.