• KIEAE Journal
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• 제3권1호
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• pp.13-20
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• 2003

It is highly recognized that there is need for protection against indoor air pollution, as we realize environmental pollution is growing, For example, in an indoor environment, a person spends more than 80 percent of their time inside the building. Thus, concern about indoor decoration materials is growing, since they cause pollution in the rooms of an apartment, as well as in offices. As the indoor decoration materials become more diverse and lusurious, so the effect of VOCs(Volatile Organic Compounds) and HCHO(Formaldehy) is growing. The indoor decoration materials cause the Sick Building Syndrome, such as headaches, dizziness, or lack of concentraion, and they in turn cause serious deterioration in people's health. In this study, I probed the status of the indoor air pollution and carried on an investigation and analysis about the prevention technique. In doing so, I performed experimental tests and an assessment of the indoor decoration materials of an apartment. I also examined elements of the emitted and the emission. Finally, I examined the character of emissions, by changing environmental conditions, such as the temperature, humidity, and ventilation. With respect to VOCs tests, I applied the method of solid state adsorption using the adsorptive tube, based on the measurement of the American EPA TO-17, ASTM 5116-97, and the measurement of the Japanese Wall Decoration Industrial Association. The tested sample was analyzed by High Performance Liquid Chromatography, after going through the process of dissolvent extraction. As subjects of the test, Paint were selected. The process of this test is as follows; first, I figured out the character of the emission, by measuring the emitted concentration of VOCs and HOHC from the indoor decoration materials of an apartment. Second, I made a small-scale chamber and the test was processed in the chamber in order to suggest an environment-friendly prediction modlel development.

• Journal of Biosystems Engineering
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• 제43권3호
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• pp.219-228
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• 2018

Purpose: This study evaluated the feasibility of a near-infrared spectroscopy technique for the rancidity prediction of soybean oil. Methods: A near-infrared spectroscopy technique was used to evaluate the rancidity of soybean oils which were artificially deteriorated. A soybean oil sample was collected, and the acid values were measured using titrimetric analysis. In addition, the transmission spectra of the samples were obtained for whole test periods. The prediction model for the acid value was constructed by using a partial least-squares regression (PLSR) technique and the appropriate spectrum preprocessing methods. Furthermore, optimal wavelength selection methods such as variable importance in projection (VIP) and bootstrap of beta coefficients were applied to select the most appropriate variables from the preprocessed spectra. Results: There were significantly different increases in the acid values from the sixth days onwards during the 14-day test period. In addition, it was observed that the NIR spectra that exhibited intense absorption at 1,195 nm and 1,410 nm could indicate the degradation of soybean oil. The PLSR model developed using the Savitzky-Golay $2^{nd}$ order derivative method for preprocessing exhibited the highest performance in predicting the acid value of soybean oil samples. onclusions: The study helped establish the feasibility of predicting the rancidity of the soybean oil (using its acid value) by means of a NIR spectroscopy together with optimal variable selection methods successfully. The experimental results suggested that the wavelengths of 1,150 nm and 1,450 nm, which were highly correlated with the largest absorption by the second and first overtone of the C-H, O-H stretch vibrational transition, were caused by the deterioration of soybean oil.

• 한국안전학회지
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• 제31권3호
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• pp.75-81
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• 2016

Tendon corrosion reliability in KICT-ultra high performance concrete (K-UHPC) bridges is assessed and predicted considering uncertainties in flexural bending capacity and corrosion occurrence. In post-tensioning bridge systems, corrosion is a one of most critical failure mechanisms due to strength reduction by it. During the entire service life, those bridges may experience lifetime corrosion deterioration initiated and propagated in tendons which are embedded not only in normal concrete but also in K-UHPC. For this reason, the time-variant corrosion performance has to be assessed. In the absence of in-depth researches associated with K-UHPC tendon corrosion, a reliability-based prediction model is developed to evaluate lifetime corrosion performance of tendon in K-UHPC bridges. In 2015, KICT built a K-UHPC pilot bridge at 168/5~168/6 milestone on Yangon-Mandalay Expressway in Myanmar, by using locally produced tendons which post-tensioned in longitudinal and lateral ways of K-UHPC girders. For an illustrative purpose, this K-UHPC bridge is used to identify the time-variant corrosion performance.

• 한국지하수토양환경학회지:지하수토양환경
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• 제26권6호
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• pp.165-175
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• 2021

Groundwater is used in many areas in food industry such as food manufacturing, food processing, cooking, and liquor industry etc. in Korea. As groundwater occupies a large portion of food industry, it is necessary to predict deterioration of water quality to ensure the safety of food water since using undrinkable groundwater has a ripple effect that can cause great harm or anxiety to food users. In this study, spatiotemporal data aggregation method was used in order to obtain spatially representative data, which enable prediction of groundwater quality change in a small watershed. In addition, a highly reliable predictive model was developed to estimate long-term changes in groundwater quality by applying a non-parametric segmented regression technique. Two pilot watersheds were selected where a large number of companies use groundwater for food water, and the appropriateness of the model was assessed by comparing the model-produced values with those obtained by actual measurements. The result of this study can contribute to establishing a customized food water management system utilizing big data that respond quickly, accurately, and preemptively to changes in groundwater quality and pollution. It is also expected to contribute to the improvement of food safety management.

• 품질경영학회지
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• 제52권1호
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• 한국인터넷방송통신학회논문지
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• 제9권5호
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• pp.129-132
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• 2009

프레임 손실은 VoIP 망에서의 음질 저하의 주요 원인이다. 본 논문에서는 VoIP 망에서 주로 사용되는 CELP 기반 음성부호화기의 음질 저하를 최소화하기 위해 비선형 회귀분석 기반의 프레임손실은닉 알고리즘을 제안한다. 제안된 기법은 ITU-T G.729 표준 코덱에 적용되었으며, 기존 방법들에 비해 향상된 PESQ 성능을 보였다.

• 대한전기학회논문지
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• 제41권9호
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• pp.1060-1070
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• 1992

In this paper, characteristics of Acoustic Emission in Low Density Polyethylene were studied from tree initiation to breakdown under long-term inhomogeneous alternative electrical field. The voltage levels used were 9, 11 and 14[kV]. Especially, a newly developed automatic measuring system was used to measure time variations of AE average amplitude, AE pulse number, AE pulse distribution patterns due to polarities. The patterns wer specially the variated patterns, when tree propagated. Also, parameters for dielectric breakdown prediction, which were suggested by Okamoto, were calculated. The result was analysed by tree shapes and partial discharge activities in tree due to tree initiation and propagation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.25-28
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• 2004

A fracture was generated by change of clearance and deterioration of material properties on the sheet metal through temperature. This paper describes the results of a prediction about the temperature of the sheet metal during continuous stamping process, because the temperature increase of the sheet metal has a detrimental effect on formability. To analyze the temperature increase of the sheet metal during continuous stamping process, tensile and friction tests were performed from room temperature to 300$^{\circ}C$ at warm condition in this study. As temperature increase, tensile strength, elongation, strain hardening exponent and anisotropy coefficient for each specimens were decreased. On the other hand, friction coefficients were increased. From the FE-simulation results, temperature upward tendency was identified on dies and sheet metal. These observations are rationalized on the basis of the material properties, friction coefficient vs. temperature relationship for the sheet.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 B
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• pp.934-937
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• 1992

The partial discharge signal can be used as the detection signal of the deterioration of the power transformer insulation. Detecting this signal, the insulation failure and the point, in which the partial discharge is generated, could be predicted. In this paper, we study to predict the point, and find that the cross correlation method could predict the point accurately. Also, experimental system and the results are presented here.

• KIEAE Journal
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• 제10권3호
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• pp.103-110
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• 2010

Carbonation is one of the major deterioration factors for concrete. So. lots of researchers have proposed the equations for determining carbonated depth and the initial time of steel corrosion due to carbonation to predict the service life of concrete structures. However, there are large gaps among the equations for predicting carbonation because each researcher has different considering factors to predict carbonation depth. So, in this study, we calculated the deviations of the proposed equations for carbonation, and we calculated each researcher different corrosion initiation time. However, it has a lot of deviation. Therefore, we evaluated the probability of steel corrosion considering each deviation using MCS, an analysis method based on probability theory. In the results, we have proposed much advanced information for determining service life of reinforced concrete structures due to carbonation.