• 한국의류학회지
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• 제44권3호
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• pp.556-571
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• 2020

This study predicts consumer preference for social clothing at work, excluding uniforms using the self-product congruence theory that also establishes a model to predict the preference for recommended products that match the consumer's own image. A total of 490 Korean male office workers participated in this study. Participants' self-image and the product images of 20 apparel items were measured using nine adjective semantic scales (namely elegant, stable, sincere, refined, intense, luxury, bold, conspicuous, and polite). A model was then constructed to predict the consumer preferences using a neural network with Python and TensorFlow. The resulting Predict Preference Model using Product Image (PPMPI) was trained using product image and the preference of each product. Current research confirms that product preference can be predicted by the self-image instead of by entering the product image. The prediction accuracy rate of the PPMPI was over 80%. We used 490 items of test data consisting of self-images to predict the consumer preferences for using the PPMPI. The test of the PPMPI showed that the prediction rate differed depending on product attributes. The prediction rate of work apparel with normative images was over 70% and higher than for other forms of apparel.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 가을 학술논문 발표대회
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• pp.133-134
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• 2022

Recently, the criteria for assessing industrial accidents have been replaced by the mortality rate. It was found that the number of deaths from excavation work was the highest among construction machinery. The risk assessment is being conducted, however the industrial accident mortality rate has not decreased. Accordingly, this study aims to provide the basic for the create of a risk assessment model specialized in construction work at excavator. It provides absolute value from the risk model which is capable of delivery the probability of a disaster. In addition, we provide a relative risk model that compares the risk through scores between detailed works. The relative risk model is combined by likelihood and severity; the likelihood indicates the frequency of accidents and the severity indicates seriousness of fatal accidents. A variable that reflects the conditions of the construction site was added to the risk assessment model based on past disaster cases. And using the concepts of probability and average, the risk assessment process was quantified and used as an objective indicator. Therefore, the model is expected to reduce disasters by raising the awareness of disasters.

• 한국도로학회논문집
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• 제13권3호
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• pp.195-202
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• 2011

본 연구의 목적은 차종별 교통류 모형을 이용한 편도 2차로 고속도로 공사구간의 용량 값을 산정하는 것이다. 공사구간의 교통류 모형은 공사구간의 유입부 및 유출부를 대상으로 차종별 모형과 승용차 환산계수를 적용한 전체 차량에 대한 모형으로 도출하였다. 차종별 모형에서 산정된 최대교통류율은 승용차환산계수 및 중차량 비율을 적용하여 공사구간의 용량 값으로 전환하였다. 차종별 모형의 유입부 및 유출부 최대교통류율 값은 각각 1,845pcphpl과 1,884pcphpl로 산정되었으며 차량 전체를 대상으로 한 모형의 최대교통류율은 차종별 결과보다 높게 분석되었다. 모형의 비교 검증을 위하여 최대밀도에 따른 거리 차두간격을 적용하였다. 공사구간의 용량은 공사구간의 흐름이 안정된 유출부 용량보다 공사구간 진입을 위한 차선 변경 등으로 교통흐름이 원활하지 못한 유입부 용량에 좌우되므로 유입부 교통류 모형의 최대교통류율 값인 1,800pcphpl을 편도 2차로 고속도로 공사구간 용량 값으로 산정하였다.

• 한국분무공학회지
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• 제25권1호
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• pp.8-14
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• 2020

Recently, 1-D model-based engine development using virtual engine system is getting more attention than experimental-based engine development due to the advantages in time and cost. Injection rate profile is the one of the main parameters that determine the start and end of combustion. Therefore, it is essential to set up a sophisticated model to accurately predict the injection rate as starting point of virtual engine system. In this research, procedure of 1-D model setup based on AMESim is introduced to predict the dynamic behavior and injection rate of diesel injector. As a first step, detailed 3D cross-sectional drawing of the injector was achieved, which can be done with help of precision measurement system. Then an approximate AMESim model was provided based on the 3D drawing, which is composed of three part such as solenoid part, control chamber part and needle and nozzle orifice part. However, validation results in terms of total injection quantity showed some errors over the acceptable level. Therefore, experimental work including needle movement visualization, solenoid part analysis and flow characteristics of injector part was performed together to provide more accuracy of 1-D model. Finally, 1-D model with the accuracy of less than 10% of error compared with experimental result in terms of injection quantity and injection rate shape under normal temperature and single injection condition was established. Further work considering fuel temperature and multiple injection will be performed.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.33-40
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• 2013

Purpose: The goal of this study was to build an accurate digital factory that evaluates the performance of a factory using computer simulation. To achieve this goal, we evaluated the effect of worker-related variables on production in a simulation model using comparative analysis of two cases. Methods: The overall work process and worker-related variables were determined and used to build a simulation model. Siemens PLM Software's Plant Simulation was used to build a simulation model. Also, two simulation models were built, where the only difference was the use of the worker-related variable, and the total daily production analyzed and compared in terms of the individual process. Additionally, worker efficiency was evaluated based on worker analysis. Results: When the daily production of the two models were compared, a 0.16% error rate was observed for the model where the worker-related variables were applied and error rate was approximately 5.35% for the model where the worker-related variables were not applied. In addition, the production in the individual processes showed lower error rate in the model that included the worker-related variables than the model where the worker-related variables were not used. Also, among the total of 22 workers, only three workers satisfied the IFRS (International Financial Reporting Standards) suggested worker capacity rate (90%). Conclusions: In the daily total production and individual process production, the model that included the worker-related variables produced results that were closer to the real production values. This result indicates the importance of worker elements as input variables, in regards to building accurate simulation models. Also, as suggested in this study, the model that included the worker-related variables can be utilized to analyze in more detail actual production. The results from this study are expected to be utilized to improve the work process and worker efficiency.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1995년도 추계학술대회 논문집
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• pp.60-63
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• 1995

The behavior of the work materials in the chip-tool interface in extremely high strain rates and temperatures is more that of viscous liquids than that of normal solid metals. In these circumstances the principles of fluid mechanics can be invoked to describe the metal flow in the neighborhood of the cutting edge. In the present paper an Eulerian finite element model is presented that simulates metal flow in the vicinity of the cutting edge when machining a low carbon steel with carbide cutting tool. The work material is assumed to obey visco-plastic (Bingham solid) constitutive law and Von Mises criterion. Heat generation is included in the model, assuming adiabatic conditions within each element. the mechanical and thermal properties of the work material are accepted to vary with the temperature. The model is based on the virtual work-stream function formulation, emphasis is given on analyzing the formation of the stagnant metal zone ahead of the cutting edge. The model predicts flow field characteristics such as material velocity effective stress and strain-rate distributions as well as built-up layer configuration

• 한국산학기술학회논문지
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• 제12권10호
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• pp.4618-4625
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• 2011

본 연구는 자동차 모듈조립 작업장에서 RFID 방식을 통하여 MES 서버와 POP 단말기 간의 상호작용과 인터페이스를 효율적으로 향상시킬 수 있는 특정 모형을 제시한다. MES 서버, RFID, PLC 및 POP 단말기 간의 실험결과, RFID에 의한 인터페이스 방식의 경우 기존의 근접센서에 의한 방식에 비하여 이동대차당 작업처리시간이 평균 10분에서 1분으로 대폭 감소하였고, 불량률도 평균 20%에서 1%로 대폭 줄어들었다.

• 음성과학
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• 제14권1호
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• pp.151-162
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• 2007

This study focuses on the classification of pathological voice using GMM (Gaussian Mixture Model) and compares the results to the previous work which was done by ANN (Artificial Neural Network). Speech data from normal people and patients were collected, then diagnosed and classified into two different categories. Six characteristic parameters (Jitter, Shimmer, NHR, SPI, APQ and RAP) were chosen. Then the classification method based on the artificial neural network and Gaussian mixture method was employed to discriminate the data into normal and pathological speech. The GMM method attained 98.4% average correct classification rate with training data and 95.2% average correct classification rate with test data. The different mixture number (3 to 15) of GMM was used in order to obtain an optimal condition for classification. We also compared the average classification rate based on GMM, ANN and HMM. The proper number of mixtures on Gaussian model needs to be investigated in our future work.

• 한국건설관리학회논문집
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• 제21권3호
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• pp.48-56
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• 2020

기획단계에서의 공사비 예측은 타당성 분석, 예산 책정, 계획수립 등을 위한 기초정보를 제공한다는 점에서 성공적인 프로젝트 수행을 위한 중요한 요소이다. 본 연구에서는 초기 기획단계의 신한옥 공사비 예측 정확도 향상을 목적으로 전체 공사비 중 가장 많은 비중을 차지하는 목공사는 다양한 조건(구조형식, 지붕형태, 평면형태 등)에 의해 개략 물량을 자동 산출하여 공사비를 예측하고, 이외의 공종은 단위단가식을 적용해 공사비를 예측하는 모델을 제시하였다. 2개의 사례를 대상으로 개략 견적 모델로써의 활용성 및 타당성을 검증하였으며, 총공사비의 오차율은 각각 -4%(사례 1), -6%(사례2)로 나타났다. 이러한 결과값은 초기 기획단계에서 실무활용 가능한 범위에서의 오차를 보였다.

• 대한기계학회논문집
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• 제14권5호
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• pp.1043-1058
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• 1990

본 연구에서는 전자기 성형법에 의한 원통형상의 가공재의 자유 확관성형 가 공에 대해서 유한요소해석법을 이용한 변형 및 응력해석을 수행하였다. 탄소성 재료 모형을 확장하여 변형 경화율이 변형률 및 변형률 속도의 지배를 받는 변형률 속도 종 속 탄소성 재료 모형을 도입하였고, 1차 제하 이후까지 포함하여 고속 성형시 변형률 속도 효과에 의해 발생하는 현상들에 대해서 연구하였다.결과의 비교 및 논의를 위 하여, 해석대상과 성형조건, 그리고 가공재에 작용하는 자기압력은 Suzuki의 것과 동 일한 것을 사용하였다.