• 한국수소및신에너지학회논문집
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• 제30권3호
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• pp.237-242
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• 2019

In the hydrogen refueling station (HRS), it is need the pre-cooling system (PCS) to limit the inside temperature ($85^{\circ}C$) of the onboard thank (700 bar) and to charge the hydrogen at short time (within 3 minutes) to fuel cell electric vehicle (FCEV). From those safety reasons, the temperature of hydrogen gas must be controled $-33^{\circ}C$ to $-40^{\circ}C$ in PCS. The cooling test of the gaseous ($N_2$, He, $H_2$) was carried out using heat exchanger (pre-cooler) by indirect cooling and direct cooling method. It was confirmed that the temperature of hydrogen gas had below $-40^{\circ}C$ at below $-75^{\circ}C$ of chiller temperature in direct cooling.

• 한국자동차공학회논문집
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• 제25권2호
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• pp.207-218
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• 2017

Improving fuel consumption, particularly that of commercial vehicles, has become a global concern. The reduction in logistics cost has been a key issue in efforts to improve fuel economy and efficiency of transportation equipment. Typical technologies for reducing reduce fuel usage include air resistance reduction technologies, tire rolling resistance technologies, and idle technologies among others. Air resistance technology is a highly effective method that can be easily applied in a short period. As with air resistance technology, several devices involving side skirt, boat tail and gap fairing have been developed based on an analytical 3-D modeling technique for reducing air resistance attributed to the vehicle configuration. The devices were on a 45 feet tractor-trailer and the emission test was done using PEMS equipment. Fuel economy was evaluated by introducing several devices to reduce outer air resistance. The test was conducted by changing the experimental method of SAE J1321 Joint TMC/SAE Fuel Consumption Test Procedure - Type II test. As a result, air resistance decreased by at least 15 % and fuel economy improved by at least 13 %. This study sought to reduce greenhouse gas and improve fuel economy by applying several devices to a test vehicle to lower air resistance.

• 한국토양비료학회지
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• 제48권5호
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• pp.384-390
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• 2015

Remote sensing can be used to provide information about the monitoring of crop situation. This study was conducted to estimate the amount of nitrogen present in paddy fields by measuring the amount of nitrogen in hairy vetch using an UAV (Unmaned Aerial Vehicle). NDVIs (Normalized Difference Vegetation Index) were calculated using UAV images obtained from paddy fields in Seocheon on May $14^{th}$ 2015. There was strong relationship between UAV NDVI and the amount of nitrogen in hairy vetch ($R^2=0.79$). Spatial distribution maps of green manure nitrogen were generated on each paddy field using the nitrogen-vegetation index relations to help farmers determine the amount of N fertilizers added to their rice fields after the application of green manure such as hairy vetch.

• 기술혁신학회지
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• 제16권2호
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• pp.530-558
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• 2013

새로운 그린카 시대가 도래하면서 자동차 산업에 새로운 전략이 요구되고 있다. 본 논문에서는 그린카 중에서도 전기자동차 산업을 어떻게 효과적으로 발전시킬 수 있는지 살펴보고자 한다. 전기자동차산업의 보다 효과적 분석을 위해서 기존의 자동차산업의 이해관계자를 중심으로 하는 단편적인 관계분석 차원에서 두 고객 그룹 이상을 대상으로 하는 플랫폼차원의 분석으로의 전환이 필요하다. 본 논문에서는 이러한 분석을 위해서 기존의 비즈니스 모델차원의 분석이 아닌 산업플랫폼을 적용한 정책적 분석 프레임워크를 도출하는 것을 목표로 한다. 이를 위해 본 논문에서는 다음의 주요 이슈에 대해 분석하고자 한다. 첫째, 산업플랫폼의 정의는 무엇이고, 필요한 이유는 무엇인가? 둘째, 산업플랫폼의 참여자는 누구이며, 작용요인은 무엇인가? 셋째, 전기자동차 시장에 적용할 수 있는 산업플랫폼의 참여자 및 작용요인은 무엇인가? 넷째, 관련 사례를 기반으로 산업플랫폼의 분석 프레임워크를 도출하고 향후 적용방안에 대해서 논의하고자 한다.

• 한국도로학회논문집
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• 제15권5호
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• pp.111-122
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• 2013

PURPOSES : The purpose of this system (Rear Lighting System) is to provide illumination for the driver to operate the commercial vehicle safely after dark in highway, to increase the conspicuity of the vehicle, and especially be suggesting the finest observable improvement method, depending on color and pattern of rear lighting system of truck for midnight highway traffic. METHODS : Rear lightning system as an improving way for forward commercial vehicles lighting the securing sight from human factors and the surrounding environment in midnight driving. For this one, basic materials were collected from the data analysis about many types of problems, and filed investigation for establishing Driving Simulator. also taking statistic test to human volunteers after finding recognizable distance of them. RESULTS : As a result, color with the highest visuality is amber followed by green-red-blue as in order for all road types. Especially almost no difference is found between red and green, also when the light is turn off, recognizable distances is wide difference compared to turn on the light. One more thing about study per pattern, upper and entire lighting have similar recognizable distances, but under lighting shows short distance with difficulty securing sight from medians. And straight section shows similar recognizable distances. By finding visuality improvement method depending on color and pattern of supplement taillight, it is expected to suggest quantitative judgement standard for introducing regulation and improvement of supplement taillight. CONCLUSIONS : Night time vehicle conspicuity to the rear is provided by rear position lamps. this study is showed that the color of light ramp is not important to be safe driving, most important is to turn on the light, recognizable distances is big different compared to turn off the rear light, so when the drivng dark in highway, have to turn on the light for reducing risk.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.606-612
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• 2011

At the product design and development stage, the main criteria selecting a design alternative were performance aspect as well as cost aspect of a product. Ongoing new paradigm shifts such as low carbon green growth, climate change mitigation, sustainable society development urged considering environmental aspect of a product at the product design and development stage. Up to recently, only cost aspect except performance of a product was considered at the railway vehicle design process. Therefore, it is needed to develop a method that may consider environmental aspect of a product at the railway vehicle design process. Lee (2011) proposed that a method of an integration assessment of environmental aspect and cost aspect based on GHG emission instead of based on monetary value. This study conducted that apply the method of Lee (2011) to design alternative selection process of a railway vehicle. From the integrated view of environmental and cost aspect, the reference product and design alternatives are assessed and compared.

• 한국분말재료학회지
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• 제22권5호
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• pp.362-366
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• 2015

The effect of sublimable vehicle composition in the camphor-naphthalene system on the pore structure of porous Cu-Ni alloy is investigated. The CuO-NiO mixed slurries with hypoeutectic, eutectic and hypereutectic compositions are frozen into a mold at $-25^{\circ}C$. Pores are generated by sublimation of the vehicles at room temperature. After hydrogen reduction at $300^{\circ}C$ and sintering at $850^{\circ}C$ for 1 h, the green body of CuO-NiO is completely converted to porous Cu-Ni alloy with various pore structures. The sintered samples show large pores which are aligned parallel to the sublimable vehicle growth direction. The pore size and porosity decrease with increase in powder content due to the degree of powder rearrangement in slurry. In the hypoeutectic composition slurry, small pores with dendritic morphology are observed in the sintered Cu-Ni, whereas the specimen of hypereutectic composition shows pore structure of plate shape. The change of pore structure is explained by growth behavior of primary camphor and naphthalene crystals during solidification of camphor-naphthalene alloys.

• 한국분무공학회지
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• 제18권2호
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• pp.106-111
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• 2013

Adulterations fuel have been using in the vehicle in these days. Because gasoline, diesel prices are rising every day. so people find more cheap price fuel. Adulterations fuel caused a serious air pollution problems. Adulteration fuel were made from waste engine oil, waste paint. According to Government regulations permit to be used recycle fuel(adulteration fuel) only in industrial boiler. Unburned fuel pollutants are effected to human health. In this paper, the hazardous air pollutants characteristics in the diesel vehicles according to adulterations of vehicle fuels were carried out in the NEDC test mode in chassis dynamometer. It is revealed that the all of the regulation pollutants (THC, NOx, CO and PM) emission in the adulterations of vehicle fuels was increased also the green house gas, $CO_2$ was increased. In the hazardous air pollutants characteristics, the VOCs(Volitile Organic Compounds) BTEX(Benzene, Toluene, Ethylbenzene, Xylene) emissions in the adulterations of vehicle fuels showed higher level than these in the diesel fuels.

• 한국지능시스템학회논문지
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• 제13권1호
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• pp.76-84
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• 2003

요즈음에는 GPS 및 GIS을 기반으로, 운전자에게 최단 경로탐색 및 예상도착시간을 인터넷 및 휴대폰으로 검색할 수 있다. 그러나, 아무리 좋은 자동항법 장치도 평균차량속도가 10- 20 Km 일 때에는 최단경로를 생성할 수 없다. 그러므로 승용차대기시간과 평균차량속도를 개선하기 위해서, 서로 다른 교차로 길이 및 교차로 차선수 일 때에도, 퍼지 적응 규칙을 이용한 최적녹색시간 알고리즘을 제안한다. 본 논문에서는 인터넷을 이용해서 위험한 도로, 공사중인 도로 및 목적지 예상 도착시간 및 최적의 교통상황을 예보하는 기능을 제공할 수 있도록 하였다.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.67-72
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• 2023

In the past decade, Autonomous Vehicle Systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to be a crucial process in many applications, such as in autonomous driving, industrial automation and robotics. Especially in the case of autonomous vehicles, the efficient fusion of data from these two types of sensors is important to enabling the depth of objects as well as the classification of objects at short and long distances. This paper presents classification of objects using CNN based vision and Light Detection and Ranging (LIDAR) fusion in autonomous vehicles in the environment. This method is based on convolutional neural network (CNN) and image up sampling theory. By creating a point cloud of LIDAR data up sampling and converting into pixel-level depth information, depth information is connected with Red Green Blue data and fed into a deep CNN. The proposed method can obtain informative feature representation for object classification in autonomous vehicle environment using the integrated vision and LIDAR data. This method is adopted to guarantee both object classification accuracy and minimal loss. Experimental results show the effectiveness and efficiency of presented approach for objects classification.