• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1123-1125
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• 2006

As Kyoto protocol has been effective in 2005, the reduction of $CO_2$ emission is a global urgent problem. In Korea, the $CO_2$ emission of transportation increases continuously, which can be solved partially by the use of railroad. Therefore, it is necessary to calculate exactly the $CO_2$ emission of railroad through life cycle approach. In this study, the $CO_2$ emission of electric motor unit (EMU) was evaluated with its carboy material using life cycle inventory analysis (LCIA). Among the life cycles of EMU, $CO_2$ emission was the highest in the running phase. As the total weight of EMU was lowered, $CO_2$ emission was reduced. In conclusion, the light-weighting of EMU can reduce $CO_2$ emission efficiently.

• Journal of Multimedia Information System
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• 제5권2호
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• pp.87-90
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• 2018

Various approaches have been proposed to convert low dynamic range (LDR) to high dynamic range (HDR). Of these approaches, the Multi Scale Fusion (MSF) algorithm based on Laplacian pyramid decomposition is used in many applications and demonstrates its usefulness. However, the pyramid fusion technique has no means for controlling the luminance component because the total number of pixels decreases as the pyramid rises to the upper layer. In this paper, we extract the reflection light of the image based on the Retinex theory and generate the weight map by adjusting the reflection component. This weighting map is applied to achieve an MSF-like effect during image fusion and provides an opportunity to control the brightness components. Experimental results show that the proposed method maintains the total number of pixels and exhibits similar effects to the conventional method.

• Design & Manufacturing
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• 제13권3호
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• pp.24-28
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• 2019

In this study, a study was carried out that could effectively produce a heat dissipation effect on plastic materials. Using carbon nanotube (CNT), aluminum powder and plastic, the material properties were tested in 2 cases of compounding ratio. The test sample mold was designed and constructed prior to the experiment. The experiments include tensile strength, elongation rate, flexural strength, flexural elasticity rate, eye-jaw impact strength, gravity and thermal conductivity. Results from 60% and 70% mixture of aluminium to plastic were tested, and a 10% less combined result was a relatively good property. For research purposes, the heat dissipation effect and light weighting obtained a good measure when the combined amount of Al was 60%.

• Design & Manufacturing
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• 제13권3호
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• pp.6-10
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• 2019

In this study, a study was carried out that could effectively produce a heat dissipation effect on plastic materials. Using carbon nanotube (CNT), aluminum powder and plastic, the material properties were tested in 2 cases of compounding ratio. The test sample mold was designed and constructed prior to the experiment. The experiments include tensile strength, elongation rate, flexural strength, flexural elasticity rate, eye-jaw impact strength, gravity and thermal conductivity. Results from 60% and 70% mixture of aluminium to plastic were tested, and a 10% less combined result was a relatively good property. For research purposes, the heat dissipation effect and light weighting obtained a good measure when the combined amount of Al was 60%.

• 반도체디스플레이기술학회지
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• 제23권1호
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• pp.110-116
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• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• 대한임베디드공학회논문지
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• 제17권1호
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• pp.9-17
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• 2022

As the COVID-19 pandemic situation worsens, the time spent indoors increases, and the exposure to indoor environmental pollution such as indoor air pollution and noise also increases, causing problems such as deterioration of human health, stress, and discord between neighbors. This paper designs and implements a system that measures and monitors indoor air quality and noise, which are representative evaluation criteria of the indoor environment. The system proposed in this paper consists of a particulate matter measurement subsystem that measures and corrects the concentration of particulate matters to monitor indoor air quality, and a noise measurement subsystem that detects changes in sound and converts it to a sound pressure level. The concentration of indoor particulate matters is measured using a laser-based light scattering method, and an error caused by temperature and humidity is compensated in this paper. For indoor noise measurement, the voltage measured through a microphone is basically measured, Fourier transform is performed to classify it by frequency, and then A-weighting is performed to correct loudness equality. Then, the RMS value is obtained, high-frequency noise is removed by performing time-weighting, and then SPL is obtained. Finally, the equivalent noise level for 1 minute and 5 minutes are calculated to show the indoor noise level. In order to classify noise into direct impact sound and air transmission noise, a piezo vibration sensors is mounted to determine the presence or absence of direct impact transmitted through the wall. For performance evaluation, the error of particulate matter measurement is analyzed through TSI's AM510 instrument. and compare the noise error with CEM's noise measurement system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.334-334
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• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• 한국산학기술학회논문지
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• 제19권8호
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• pp.25-31
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• 2018

본 연구에서는 카울 모듈의 성형 시 최적 설계 공정을 유한요소해석을 통해 도출하는 방안을 제시하였다. 소재 인장시험 및 성형성 평가와 같은 기계적 물성 평가를 통해 성형 해석의 주름 및 크랙 발생을 사전에 파악하고 이를 개선하기 위한 공정 설계 변경을 통해 최적 설계 방안을 도출하였다. 또한 제진성 향상이 필요한 카울 로워 패널에 패치워크를 적용을 통해 카울 모듈의 강성 증대 및 제진 특성 향상을 고유진동수 측정 시험과 해석을 통해 확인하였다. 해석 결과, 실러 패치워크 기술 적용에 따른 1차 고유진동수가 향상됨을 알 수 있었고, 이는 강성 및 제진특성 증대와 관련있다고 볼 수 있다. 실러 패치워크 적용 시 공정수 감소를 위해 성형 전 로워 패널 블랭크에 패치워크 블랭크를 점용접으로 접합시켜 성형하므로, 성형 후 패치워크 패널의 위치가 점용접 조건에 따라 달라진다. 이를 위해 점용접 위치에 따른 성형 해석을 실시하여 결과를 바탕으로 최적 공정 설계를 도출하였다. 스탬핑 공법을 이용한 타부품의 적용을 위해 성형 해석 기법을 구축하여 다양한 제품 설계에 도움이 될 것으로 판단된다.

• 한국전산구조공학회논문집
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• 제30권5호
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• pp.445-452
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• 2017

본 연구에서의 날개 앞전은 날개의 공기역학적인 기능뿐만 아니라 조류 등의 외부의 손상을 줄 수 있는 것으로부터 날개 내부 구성요소를 보호하고 안전한 항공기 운항을 위한 반드시 필요한 구조 요소이다. 복합재 무인기의 날개 경량화를 위한 최적의 제작 모델을 비교 검토하였다. MSC. Patran/Nastran을 이용한 유한요소해석을 통하여 비틀림 하중의 변위 형상을 비교 확인하였으며, 각 모델들의 비틀림 강도 실험을 통하여 적층 유형, 두께 변화 및 형상 적용에 따른 경량화 성능 개선을 확인하므로써 소형 복합재 무인기 최적의 경량화 날개 앞전스킨의 형태를 제시하였다.

• 한국잠사곤충학회지
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• 제28권1호
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• pp.72-78
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• 1986

견에 대한 오배자탄닌과 합성탄닌의 처리조임이 견의 탄닌증량율에 미치는 영향과 탄닌증량견의 염색조건 및 실용적 특성을 구명하기 위하여 시험결과 1. 견의 증량율을 기안한 합리적인 탄닌처리 농도는 오배자 30g/l, 합성탄닌산 15g/l이었고, 처리온도 및 시간은 8$0^{\circ}C$에서 60분 내외 처리용액의 산도는 pH 2-3이었다. 2. 탄닌처리 견의 염색조건에 있어서 부착된 탄닌의 탈락을 적게하며 염착농도(K/S)를 향상시킬 수 있는 OrangeII에 의한 합리적 염색온도 및 시간은 6$0^{\circ}C$, 90분이었다. 3. 탄닌염색 가공견포의 Soaping에 의한 색착($\Delta$E)는 미가공 견포에 비하여 현저히 감소됨으로서 세탁견도가 2급이나 향상되었다. 4. 탄닌 염색가공 견포의 자외선 조사에 의한 dyeloss율은 무처리염색견포의 1/6정도로 감소됨으로서 탄니처리 견포의 내광성이 현저히 개선되었다. 5. 탄닌 염색가공 견포의 마찰견도와 발수성은 미가공 견포와 같은 수준이었으나 Drape계수는 감소됨으로서 의복의 착용감이 향상되었다.