• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.277-284
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly-simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests for different sets of classifications were performed and demonstrated the seasonal effects of clouds and sun glint to be robust.

• Journal of Institute of Convergence Technology
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• v.9 no.1
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• pp.31-36
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• 2019

After 30 years of KKP model analysis and extended 30 years of accuracy analysis, the unique correlation and various problems between measured horizontal surface insolation and measured weather data are found in this paper. The KKP model's 10yrs daily total horizontal surface insolation forecasting was averaged about 97.7% on average, and the forecasting accuracy at peak times per day was about 92.1%, which is highly applicable regardless of location and weather conditions nationwide. The daily total solar radiation forecasting accuracy of the modified KKP cloud model was 98.9%, similar to the KKP model, and 93.0% of the forecasting accuracy at the peak time per day. And the results of evaluating the accuracy of calculation for 30 years of KKP model were cloud model 107.6% and cloud model 95.1%. During the accuracy analysis evaluation, this study found that inaccuracies in measurement data of cloud cover should be clearly assessed by the Meteorological Administration.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.235-244
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• 2004

This study focuses on the assessment for proposed algorithm to discriminate cloudy pixels from snowy pixels through use of visible, near infrared, and short wave infrared channel data in VEGETATION-1 sensor embarked on SPOT-4 satellite. Traditional threshold algorithms for cloud and snow masks did not show very good accuracy. Instead of these independent masking procedures, K-Means clustering scheme is employed for cloud/snow discrimination in this study. The pixels used in clustering were selected through an integration of two threshold algorithms, which group ensemble the snow and cloud pixels. This may give a opportunity to simplify the clustering procedure and to improve the accuracy as compared with full image clustering. This paper also compared the results with threshold methods of snow cover and clouds, and assesses discrimination capability in VEGETATION channels. The quality of the cloud and snow mask even more improved when present algorithm is implemented. The discrimination errors were considerably reduced by 19.4% and 9.7% for cloud mask and snow mask as compared with traditional methods, respectively.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.229-237
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• 2021

Cloud of things (CoTs) is a newer idea which combines cloud computing (CC) with the Internet of Things (IoT). IoT capable of comprehensively producing data, and cloud computing can be presented pathways that allow for the progression towards specific destinations. Integrating these technologies leads to the formation of a separate element referred to as the Cloud of Things (CoTs). It helps implement ideas that make businesses more efficient. This technology is useful for monitoring a device or a machine and managing or connecting them. Since there are a substantial amount of machines that can run the IoT, there is now more data available from the IoT that would have to be stored on a local basis for a provisional period, and this is impossible. CoTs is used to help manage and analyze data to additionally create usable information by permitting and applying the development of advanced technology. However, combining these elements has a few drawbacks in terms of how secure the process is. This investigation aims to recent study literature from the past 3 years that talk about how secure the technology is in terms of protecting by authentication, reliability, availability, confidentiality, and access control. Additionally, this investigation includes a discussion regarding some kinds of potential attacks when using Cloud of Things. It will also cover what the various authors recommend and conclude with as well as how the situation can be approached to prevent an attack.

• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.29-40
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• 2011

In this study, the effects of an urban thermal environment on air quality were investigated using hourly surface weather observation data and air quality data over six summers from 2000 to 2005 in two cities on the Korean Peninsula. One, the city of Daegu, is representative of basin topography and the other, the city of Busan, represents a coastal area. It is known that the characteristics of an urban thermal environment are represented as an "urban heat island". Here, we focus on the nighttime urban thermal environment, which is called a "tropical night", during the summer. On tropical nights in Busan, the temperature and cloud cover levels were higher than on non-tropical nights. Wind speed did not appear to make a difference even on a tropical night. However, the frequency of southwestern winds from the sea was higher during tropical nights. The prevailing southwest winds in all areas meant an inflow of air from the sea. So at most of the air quality stations, the ozone concentration during tropical nights was lower than during non-tropical nights. In Daegu, the tropical nights had higher temperatures and cloud covers. Despite these higher temperatures, the ozone concentration during the tropical nights was lower than that on non-tropical nights at most of the air quality stations. This feature was caused by low irradiance, which in turn caused an increased cloud cover. Wind speed was stronger during the tropical nights and dispersed the air pollutants. These meteorological characteristics of the tropical nights reduced ozone concentrations in the Daegu Basin.

• Journal of Navigation and Port Research
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• v.35 no.5
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• pp.387-392
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• 2011

The value of Photovoltaic as an independent power supply is small, but the city's carbon emissions reduction and for the reduction of fossil fuel use distributed power is the power source to a very high value. However, according to the weather conditions for solar power generation by power fluctuations because of the size distribution to be effective, the big swing for effectively controlling real-time monitoring should be made. But that depends on solar power generation solar radiation forecasts from the National Weather Service does not need to predict it, and this study, the diffuse sky radiation in the history of the solar radiation in the darkness of the clouds, thick and weather forecasts can be inferred from the atmospheric transmittance to announce this value is calculated to represent each weather forecast solar radiation and solar radiation predicted by substituting the expression And the measured solar radiation and CRM (Cloud Cover Radiation Model) technique with an expression of Kasten and Czeplak irradiation when compared to the calculated predictions were verified.

• Journal of Korean Society of Forest Science
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• v.83 no.4
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• pp.441-449
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• 1994

The two reflective channels(red and near infrared spectrum) of advanced very high resolution radiometer(AVHRR) data were used to classify primary vegetation cover types in the Korean Peninsula. From the NOAA-11 satellite data archive of 1991, 27 daytime scenes of relatively minimum cloud coverage were obtained. After the initial radiometric calibration, normalized difference vegetation index(NDVI) was calculated for each of the 27 data sets. Four or five daily NDVI data were then overlaid for each of the six months starting from February to November and the maximum value of NDVI was retained for every pixel location to make a monthly composite. The six bands of monthly NDVI composite were nearly cloud free and used for the computer classification of vegetation cover. Based on the temporal signatures of different vegetation cover types, which were generated by an unsupervised block clustering algorithm, every pixel was classified into one of the six cover type categories. The classification result was evaluated by both qualitative interpretation and quantitative comparison with existing forest statistics. Considering frequent data acquisition, low data cost and volume, and large area coverage, it is believed that AVHRR data are effective for vegetation cover type mapping at regional scale.

• Korean Journal of Heritage: History & Science
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• v.52 no.4
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• pp.18-37
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• 2019

This study derived a method for establishing the chronology of cloud patterns by examining the arrangement of the treasure motifs in the cloud pattern used in the relevant pattern-decorated book covers of 89 Oegyujanggak Uigwe books, which are currently housed in the National Museum of Korea. The cloud pattern with a treasure motif was used in the covers of a total of 89 books from King Hyojong Gukjangdogam Uigwe (1659) to Sadoseja Garyedogam Uigwe (1744), spanning 86 years. First, to analyze the cloud pattern, it should be broken down into smaller parts to the extent that the different shapes of treasure motifs can be recognized. Secondly, the method of decoding the pattern is as follows: First, check whether the pattern is arranged in one or two directions from the vertex of the cloud's head, and determine the direction of the cloud tail. Then, decode the treasure motif's arrangement starting from the vertex of the cloud's head toward the direction the tail of manja is headed. Record the findings of this decoding process by categorizing them. Thirdly, as a result of the analysis, a total of 28 types of cloud patterns with treasure motifs were identified in 89 books. There were 45 types of treasure motifs used in such patterns. Finally, we have concluded that applying the method of decoding the treasure motif in the cloud pattern to portraits, excavated costumes, and various relics can be useful to establish the chronology of cloud patterns in the late Joseon period. The method suggested in this study is called 'The Reading Method of Chronology in Cloud Pattern with Treasure Motifs' (also 'Jeung-ha Cloud Pattern Reading Method').

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.19-27
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• 2010

Sky cover method can be used to determine sky condition by cloud amount of the Korea Meteorological Administration. And, HCI (Hourly Clearness Index) method is another method determined by measured horizontal global radiation data. The results of the HCI methods of Erbs et al. (1982), Orgill and Hollands (1977) seem to be not good enough because of the air pollution such as smog phenomenon or yellow sand phenomenon and so on. Therefore, HCI should be corrected. The aim of this study is to improve HCI. Therefore, this study is to analyze and compare on the sky conditions from Sky cover method and HCI, and then presents hourly correction factor based on Sky 채팩 method. The results of corrected HCI improved.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.75-85
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• 2006

This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer's approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of several land-cover types and the other is that the incompleteness of each sensor data due to cloud-cover can be modeled for the fusion process. The image classification based on the Dempster-Shafer theory usually assumes that each sensor is represented by a single channel. The evidential approach to image classification, which utilizes a mass function obtained under the assumption of class-independent beta distribution, has been discussed for the multiple sets of mutichannel data acquired from different sensors. The proposed method has applied to the KOMPSAT-1 EOC panchromatic imagery and LANDSAT ETM+ data, which were acquired over Yongin/Nuengpyung area of Korean peninsula. The experiment has shown that it is greatly effective on the applications in which it is hard to find homogeneous regions represented by a single land-cover type in training process.