• International Journal of Highway Engineering
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• v.14 no.4
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• pp.93-101
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• 2012

PURPOSES : Adverse weather conditions such as heavy rain, heavy snowfall, and thick fog and so on have highly affect on the change in traffic conditions on the road. In particular, heavy snowfall causes capacity reduction as well as crash occurrence. This study investigated the effects of snowfall on speed on a freeway. METHODS : Vehicle detection systems data were matched with corresponding weather station data by regression analysis. RESULTS : The results show that the travel speed is reduced by 6.7% under little snowfall and by 12.8% under heavy snowfall. Regarding the speed variation, 8.7% and 114.7% increases are observed under little snowfall and heavy snowfall, respectively. It is also found that 1 cm increase in snowfall leads to 0.4% decrease in travel speed. In addition, the travel speed increases by 0.4% when the temperature increases by $1^{\circ}C$. CONCLUSIONS : It is expected that the outcome of this study will be useful in establishing more effective strategies for winter operations and road maintenance in practice.

• Journal of radiological science and technology
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• v.6 no.1
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• pp.43-67
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• 1983

In order to increase the sensitivity of the photographic emulsion, one of the chemical sensitizers hydroxymethane sulfonic acid sodium salt(HMS) was applied through the chemical ripening process and following four types of emulsion were prepared. Their grain sizes were determined through the electron microscope. The ranges of average grain sizes were $0.05-0.40{\mu}m$ for silver chlorobromide emulsion of low sensitivity $0.10-0.45{\mu}m$ for the silver chlorobromide emulsion of medium sensitivity, $0.60-1.05{\mu}m$ for the silver iodobromide emulsion of high sensitivity, and $0.90-1.55{\mu}m$ for the ammonical silver iodobromide emulsion of high sensitivity. Through the reduction sensitization with HMS, they showed significant sensitivity enhancement by the increment of HMS concentration above pH 5.5 and pBr 3.0. Required sensitivity was obtained above pH 6.2 and pBr 3.3 when sulfur and gold sensitization were applied. Fog formed along the reduction sensitization was successfully prevented by the addition of 5.5-dimethylhydantion.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.715-724
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• 2012

In this study, we simulated water temperature in the downstream according to withdrawal types of dam using EFDC model. Three scenarios were assumed as water was released from the surface layer, the middle layer, and the bottom layer at intervals of 10m depth. In case of the surface layer withdrawal, the water temperature rose from March and lowered gradually after it reached a peak in August. The middle and the bottom layers effluence temperatures were lower than the surface layer temperature by maximum $15.9^{\circ}C$(in July), but after September, temperature inversion appeared. It was advantageous for the surface layer withdrawal to decrease cold damage and fog in downstream area and was possible to the middle and the bottom layers withdrawal from August to September. However, the reliability of model should be improved by accumulating the real-time information of water temperature.

• Journal of Korean Society for Atmospheric Environment
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• v.8 no.1
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• pp.1-6
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• 1992

Using data measured in 1989, a study on variations of visibility and air pollution observed in Seoul, Chongju and Choopoongryong is carried out. Analysis includes on low visibility (< 10km) and smog occurring in the Metropolitan Seoul. It was observed that number of days of visibility less than 10km during 1989 was 56.7% (207 days) for Seoul, 45.7%(167 days) for Chongju and 5.8% (21 days) for Choopoongryong. Chongju is a medium size city (population : a half million) and Choopoongryong is a rural site. In the urban are as, however, the number of low visibility days was relatively large during the winter but with little seasonal variations. In each month these cities recorded more than 10 days of low visibility. The visibility reduction due to mist, fog and haze been occurred with air pollution. In particular, the reduction in a cold season related with an increase in high concentrations of $SO_x$ and aerosols. This type of low visibility occurring in Seoul is a similar type that is occurring in London, U.K. On the other hand, the visibility reduction during in a warm season is related with high concentrations of NOx and other photochemical precursors. The visibility reduction in Seoul during summer is the same type occurring in Los Angeles, U.S.A.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.839-842
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• 2009

It is used to differential image for moving object detection in general. But it is difficult to detect the accurate detection which uses differential image between frames. In this paper, the proposed method overcome the noise that is generated by camera, grabber card, or weather condition. It extract to moving big object such as human or vehicle. The proposed method process morphological filtering and binary for the image with noise, reduce error. We are expect to apply to a real-time moving object detection system at fog condition, pass the limit of the object detection method using the differential image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.90-97
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• 2017

The Internet of Things(IoT) market is expected to grow from 15.5billion to 75.4 billion by 2015-2025. As the number of IoT devices increases, the amount of data that is sent to the cloud is increasing. Today's Cloud Computing models are not suited to handle the vast amount of data generated by IoT devices. In this paper, we propose a Cooperation Coordinator System that reduces server load and improved real-time processing capability under specific circumstances by using Band-Cloud. The cooperation coordinator system dynamically forms the cloud when cooperation is needed between mobile devices located near. It is called Band-Cloud. Band-Cloud provides services entrusted by Central Cloud. This paper describes the proposed system and shows the cooperation process using the Android-based mobile devices and Wi-Fi Direct technology. Such a system can be applied to cases where real-time processing is required in a narrow area such as a hospital ward or a school classroom.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.376-380
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• 2015

This paper proposes new recognition method of road lanes misty day. The method enables autonomous-driving of cars and the safety of the drivers while driving with bad visibility in foggy roads. The proposed method, firstly, determines whether the foggy or not according to pixel number distributions and starting point of the fog period from input images. If it is foggy then the median filter's size of the Retinex algorithm is set to 1000 or more and it performs histogram equalization and normalization. The computer simulation results show that the proposed method can recognize better long distances and fine detection than earlier methods.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.29-29
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• 2010

Engineering plastics have excellent electrical properties, mechanical strength and various characteristic which include chemical resistance, environmental resistance, weatherability at a wide temperature range. It has good characteristic(light weight, good productivity) as compare with epoxy or porcelain insulators. However, engineering plastics not suited to outdoor insulator because it isn't hydrophobic. Therefore, to over come these critical problems, we improve the surface insulation characteristics of engineering plastic by coating micro-, nano- size inorganic fillers added to RTV-SIR(Room temperature vulcanized-silicone rubber) at this plastic surface. The effect is analyzed through salt-fog test, tracking test. In conclusion, the engineering plastic coated RTV with micro-$Al_2O_3$20[phr], nano-Al(OH)3 1 ~ 3[phr] improved much better than the others.