• Atmosphere
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• v.29 no.5
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• pp.639-658
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• 2019

The classification of fog type and the characteristics of fog based on fog events over South Korea were investigated using a 3-year (2015~2017) visibility meter data. One-minute visibility meter data were used to identify fog with present weather codes and surface observation data. The concept of fog events was adopted for the better definition of fog properties and more objective classification through the detailed investigation of life cycle of fog. Decision tree method was used to classify the fog types and the final fog types were radiation fog, advection fog, precipitation fog, cloud base lowering fog and morning evaporation fog. We enhanced objectivity in classifying the types of fog by adding the satellite and the buoy observations to the conventional usage of AWS and ceilometer data. Radiation fog, the most common type in South Korea, frequently occurs in inland during autumn. A considerable number of advection fogs occur in island area in summer, especially in July. Precipitation fog accounts for more than a quarter of the total fog events and frequently occurs in islands and coastal areas. Cloud base lowering fog, classified using ceilometer, occurs occasionally for all areas but the occurrence rate is relatively high in east and west coastal area. Morning evaporation fog type is rarely observed in inland. The occurrence rate of thick fog with visibility less than 100 meters is amount to 21% of total fog events. Although advection fog develops into thick fog frequently, radiation fog shows the minimum visibility, in some cases.

• Atmosphere
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• v.23 no.1
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• pp.103-112
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• 2013

In this study, we developed a fog classification algorithm to classify fog type based on fog generation mechanism. For the analysis period of 1986-2005, 15,748 fog events had been reported from the 40 observational sites in South Korea. Thus, practically, it is almost impossible to individually classify the fog type of the whole fog events occurred in South Korea manually. In this study, the characteristics of fog during the research period were investigated and the fog classification flowchart were developed base on the analysis, and the fog classification algorithm was applied for the classification of fogs occurred at the observational sites. Finally, the classified fog-type and hindcasted fog occurance results obtained from the flowchart were evaluated for verification.

• Atmosphere
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• v.28 no.1
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• pp.69-83
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• 2018

Most of the researches on fog in South Korea have been done based on the naked-eye observation but the number of observation sites is just 22. Considering the localities of fog and various durations, it is essential to utilize more than 250 visibility meters that measure visibility every minute. In this study, the visibility characteristics of visibility meters were compared with that of the naked-eye observation using one year data, 2016, and radiation fog and advection fog cases were analyzed in detail. The concordance rate of the two data set was 0.96~0.97, but discordance rate was 0.19~0.47. In general, visibility meters observed fog more frequently than naked-eye. The correlation between two data sets is clearly dependent on the visibility and geographic locations (fog/thick fog (< 100 m) of inland: 0.86/0.61; fog/thick fog: 0.65/0.73 of island/coastal site). In both fog cases, the fog events observed by naked-eye were consistently detected by visibility meters, and visibility meters clearly well detected very short fog/thick fogs. Formation and dissipation time of fog for the fog cases were similar but fog duration by visibility meters was shorter because of exclusion of temporary dissipated time. In addition, the visibility meters showed a detailed distribution of fog events that occurred simultaneously over South Korea. It would be useful to analyze the spatial and temporal characteristics of, in particular, thick fog using visibility meters. However, more works are needed for the filtering criteria for analyzing fog using visibility meters alone.

• Journal of Auto-vehicle Safety Association
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• v.13 no.3
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• pp.13-19
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• 2021

Fog is a phenomenon caused by condensation of water vapor in the atmosphere, which is when very fine drops of water float in the atmosphere and the distance of visible is less than 1km. Fog dispersion technology is a technology that removing or weakening fog by using artificial methods to reduce damage caused by fog. It is applied differently depending on the temperature of fog generation rather than the cause of fog. This study conducted an experimental study on the fog dispersion mechanism in order to minimize damage caused by fog on the road, and studied two methods of over-cooling dispersion using solid-carbon-dioxide as a dissipated particle and dissipating fog particles through thermal acoustic waves. As a result the two methods proved experimentally that were capable of dissipating fog.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.440-448
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• 2019

The Internet of Things (IoT) is one of the main enablers for situation awareness needed in accomplishing smart cities. IoT devices, especially for monitoring purposes, have stringent timing requirements which may not be met by cloud computing. This deficiency of cloud computing can be overcome by fog computing for which fog nodes are placed close to IoT devices. Because of low capabilities of fog nodes compared to cloud data centers, fog nodes may not be deployed with all the services required by IoT devices. Thus, in this article, we focus on the issue of fog service placement and present the recent research trends in this issue. Most of the literature on fog service placement deals with determining an appropriate fog node satisfying the various requirements like delay from the perspective of one or more service requests. In this article, we aim to effectively place fog services in accordance with the pre-obtained service demands, which may have been collected during the prior time interval, instead of on-demand service placement for one or more service requests. The concept of the logical fog network is newly presented for the sake of the scalability of fog service placement in a large-scale smart city. The logical fog network is formed in a tree topology rooted at the cloud data center. Based on the logical fog network, a service placement approach is proposed so that services can be placed on fog nodes in a resource-effective way.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.183-188
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• 2000

In this paper, we present a development of automatic fog water collector that operates during fog events. This collector consists of fraction collectors, a wind hall and a fog sensor. When a fog event is begin, then the fog sensor would judge whether it is a fog or not. If a fog is detected, the fog would be gathered by air suction fans, At the same time, the wind direction, the wind velocity, the atmospheric temperature and pressure would be measured and record simultaneously. We are also developing a wireless communication system for the remote control and data analysis to collect, store and process data collected in the automatic fog water collector.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.385-385
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• 2000

In this paper, We presents the development of an automatic fog water collector that operates during fog events. This collector consists of fraction collectors, a wind hall and a fog sensor. If a fog event occurred, then the fog sensor wouldjudge whether it is a fog or not. If the fog sensor judged the fug, then the fog in the air would be rucked by suction fans. At the same time, the wind direction, the wind velocity, the atmospheric temperature and the atmospheric pressure would be measured and recorded. We are also developing a wireless communication system for the remote control and the remote data analysis in order to collect, store and process the data collected in the automatic fog water collector.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.1
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• pp.1-10
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• 2017

A heavy foggy event accompanying with complex coastal fog was investigated in this study. This heavy foggy event occurred on FEB 11, 2015. Due to reduced visibility with this foggy event induced more than 100times serial traffic accidents over the Young-jong highway, and Flights from 04:30 AM to 10:00 AM were cancelled on Inchon International Airport. This heavy foggy event was occurred in synoptic and mesoscale environments but dense coastal fog were combined with a combination of sea fog, steam fog, and radiation fog. This kind of coastal fog can predicted by accurate analysis of the direction of the air flow, sea surface temperature(SST), and 925hPa isotherms from numerical weather prediction charts and real time analysis charts.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.51-57
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• 2021

In this paper, we propose a task distribution scheme in fog computing environment considering opportunistic fog computing nodes. As latency is one of the important performance metric for IoT(Internet of Things) applications, there have been lots of researches on the fog computing system. However, since the load can be concentrated to the specific fog computing nodes due to the spatial and temporal IoT characteristics, the load distribution should be considered to prevent the performance degradation. Therefore, this paper proposes a task distribution scheme which considers the static as well as opportunistic fog computing nodes according to their mobility feature. Especially, based on the task requirements, the proposed scheme supports the delay sensitive task processing at the static fog node and delay in-sensitive tasks by means of the opportunistic fog nodes for the task distribution. Based on the performance evaluation, the proposed scheme shows low service response time compared to the conventional schemes.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.117-136
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• 2019

In this study, a hybrid-type of day fog detection algorithm (DFDA) was developed based on the optical and textural characteristics of fog top, using the Himawari-8 /Advanced Himawari Imager data. Supplementary data, such as temperatures of numerical weather prediction model and sea surface temperatures of operational sea surface temperature and sea ice analysis, were used for fog detection. And 10 minutes data from visibility meter from the Korea Meteorological Administration were used for a quantitative verification of the fog detection results. Normalized albedo of fog top was utilized to distinguish between fog and other objects such as clouds, land, and oceans. The normalized local standard deviation of the fog surface and temperature difference between fog top and air temperature were also assessed to separate the fog from low cloud. Initial threshold values (ITVs) for the fog detection elements were selected using hat-shaped threshold values through frequency distribution analysis of fog cases.And the ITVs were optimized through the iteration method in terms of maximization of POD and minimization of FAR. The visual inspection and a quantitative verification using a visibility meter showed that the DFDA successfully detected a wide range of fog. The quantitative verification in both training and verification cases, the average POD (FAR) was 0.75 (0.41) and 0.74 (0.46), respectively. However, sophistication of the threshold values of the detection elements, as well as utilization of other channel data are necessary as the fog detection levels vary for different fog cases(POD: 0.65-0.87, FAR: 0.30-0.53).