• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.26 no.3
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• pp.254-264
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• 1990

Using the meteorological data, surface weather map, and oceanographic data for 5 years(1984-1988). I investigated the characteristics of the fog occurrence and the role of the inshore in Pusan about the fog occurrence. And the meteorological data and sea surface temperature(SST), which were observed in July, 1989 in Suyoung Bay, were compared with those in Pusan. The fogs in Pusan concentrate in May, June and July. And at fog occurrence time the principal wind directions are Southwest(SW) winds, which easily supply with water vapor, and a series of Northeast(NE) wind. At the fog days pressure patterns are pattern 7 in spring time (March, April, and May) and pattern 10 and pattern 13 in summer time (June, July, and August). Also the advection fog(sea fog) is closely related with the relationship between warm and cold advection in 850~700mb and cold and warm SST rather than the increase of the instability of atmosphere in 850~500mb. The fogs in Taegu, which is the inland region, mainly occur at dawn in fall time due to the strong night radiation fog. On the other hand in Pusan the coastal region, the fogs occur from late spring time to summer time (May, June, and July). Because there is the abundant supply of the water vapor from the ocean owing to a series of South(S) wind at this time. Then the atmosphere, which has high relative humidity, reaches easily the supersaturation by the radiation cooling. In Suyoung Bay and Pusan the meteorological observation data, SST and fog days are almost similar. And I think that the mechanism of the fog occurrence nearly accords with both regions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.7
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• pp.449-455
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• 2016

Fog causes economic losses in transportation. It also results in health problems when it is combined with air pollutants. Considerable research efforts have focused on developing fog removal systems. However, most systems operate themselves after monitoring the fog. Additionally, continuous energy supply and maintenance are required to retain the fog-removal efficiency of the system. This study included the demonstration of a moss filter (a polyolefin mesh interlaced with moss) as a fog-removal method overcoming the limitations of the fog removal system. Three types of mosses with different surface structures were investigated to elucidate the relation between the moisture absorption rate and the structures. Among the different moss types, Hypopterygium japinicum showed the highest efficiency based on the smallest pore diameter and the largest total pore area. The visibilities with the moss filter and the polyolefin mesh were compared to perform the fog removal tests. The moss filter could provide a cost-effective and eco-friendly fog removal system with sustainability.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1317-1328
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• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.250-255
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• 2020

For the resolution of the latency problem of the cloud center-based cloud computing, fog computing was proposed that allows end devices to offload computations to nearby fog nodes. In the fog computing, virtualized service images are placed on fog nodes and, if service images are placed close to end devices, the duplicate service image placement problem may occur. Therefore, in this paper, we propose a service image placement mechanism based on the logical fog network that reduces duplicate service images by considering the pattern of collected service requests. For the performance evaluation of the proposed mechanism, through simulations, we compare ours with the on-demand mechanism placing a service image upon the receipt of a service request. We consider the performance factors like the number of service images, the number of non-accommodated service requests, and the network cost.

• Journal of KIISE
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• v.43 no.12
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• pp.1420-1427
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• 2016

This paper proposes a method taking advantage of Fog computing and SDN in the connected vehicle environment which is having an unstable communication channel and a dynamic topology. For this purpose, the controller should understand the current state of the overall network by maintaining recent network topology, especially, the mobility information of mobile nodes. These are managed by the controller, and are important in unstable conditions in the mobile environment. The mobility levels are divided into 3 categories. We can efficiently exploit that information. By utilizing network state information, we suggest two outcomes. First, we reduce the control message overhead by adjusting the period of beacon messages. Second, we propose a recovery process to prepare the communication failure. We can efficiently recover connection failure through mobility information. Furthermore, we suggest a path recovery by decoupling the cloud level and the fog level in accordance with application data types. The simulation results show that the control message overhead and the connection failure time are decreased by approximately 55% and 5%, respectively in comparison to the existing method.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.669-676
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• 2018

The Geostationary Ocean Color Imager(: GOCI) detects the sea fog at a high horizontal resolution of $500m{\times}500m$ using the Rayleigh corrected reflectance of 8 bands. The visible and the near infrared waves strongly reflect the characteristics of the earth surface, causing errors in cloud and fog detection. A threshold of the Band7 reflectance was set to detect the sea fog entering the land. When the region on which Band4 reflectance is larger than Band8 is determinated as cloud, the error over-estimated as sea fog is corrected by comparing the average reflectance with the surrounding region. The improved algorithm has been verified by comparing the fog images of the Cheollian satellite (COMS: Communication, Ocean, and Meteorological Satellite) as well as the visibility data from the Korea Meteorological Administration.

• Journal of Environmental Science International
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• v.29 no.6
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• pp.683-689
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• 2020

According to a NASA Goddard Institute for Space Studies report, temperatures have risen by approximately 1℃ so far, based on temperatures recorded in 1880. The 2003 heatwave in Europe affected approximately 35,000 people across Europe. In this study, a cooling fog, which is used in smart cities, was designed to efficiently reduce the temperature during a heatwave and its pilot test results were interpreted. A model experiment of the cooling fog was conducted using a chamber, in which nano mist spray instruments and spray nozzles were installed. The designed cooling fog chamber model showed a temperature reduction of up to 13.8℃ for artificial pavement and up to 8.0℃ for green surfaces. However, this model was limited by constant wind speed in the experiment. Moreover, if the cooling fog is used when the wind speed is more than 3m/s in the active green zone, the temperature reduction felt by humans is expected to be even greater. As a second study, the effect of cooling fog on temperature reduction was analyzed by installing a pilot test inside the Land Housing Institute (LHI). The data gathered in this research can be useful for the study of heat reduction techniques in urban areas.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.3
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• pp.343-355
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• 2005

Cloud/fog water was collected at Daegwallyeong, a typical clean environmental area, by using an active fog sampler during the foggy period in 2002, The pH ranged from 3,7 to 6,5 with a mean of 5,0, but the pH calculated from average concentrations of $H^+$ was 4.4. $SO_4^{2-},\;NO_3^-\;and\;NH_4^+$ were predominant ions with average concentrations of 473,3, 463,3 and $576,0\;{\mu}eq/L$, respectively, This showed that cloud/fog water was slightly acidified, but the concentrations of major pollutants were as high as those for polluted area, suggesting effect from long range transported pollutants, Samples were categorized into four groups (E, W, S, N) by applying 48-h back trajectory analysis using the Hybrid Single-Particle Largrangian Integrated Trajectory (HYSPLIT) model. Concentrations of seasalt $(Na^+\;and\;Cl^-)$ were the highest for group E, indicating large input of seasalts by air masses transported from the East Sea. The concentrations of $SO_4^{2-}$ were slightly higher in group W but the difference was not significant. However, the concentrations of $NO_3^-$ were significantly higher in group W than those in other three groups, The median values of cloud/fog water pH for group N and W were below 4,5, which is significantly lower than median values in group E and group S, This suggests that the acidifying pollutants were transported from the Asia continents and Seoul metropolitan area cause acidification of the cloud/fog water in Daegwallyeong.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.294-297
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• 2007

Steam and advection fogs are frequently observed in the Yellow Sea located between Korea and China during the periods of March-April and June-July respectively. This study uses the remote sensing (RS) data for monitoring sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided an informative synopsis for the occurrence of steam and advection fogs through a ground truth. The RS data used in this study was GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and near-IR channel of GOES-9 and MTSAT-1R satellites was applied to estimate the extension of the sea fog. For the days examined, it was found that not only the DCD but also the texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind is used to provide a weak wind area less than threshold under stable condition of the surface wind around a fog event. The Laplacian computation for a measurement of the homogeneity was designed. A new combined method of DCD, QuikSCAT wind speed and Laplacian was applied in the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and Laplacian are -2.0 K, 8 m $s^{-1}$ and 0.1, respectively. The validation methods such as Heidke skill score, probability of detection, probability of false detection, true skill score and odds ratio show that the new combined method improves the detection of sea fog rather than DCD method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2310-2345
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• 2017

With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.