• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.570-581
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• 2015

In recent years, many institutions predict that cloud services and big data will be popular IT trends in the near future. A number of leading IT vendors are focusing on practical solutions and services for cloud and big data. In addition, cloud has the advantage of unrestricted in selecting resources for business model based on a variety of internet-based technologies which is the reason that provisioning and virtualization technologies for active resource expansion has been attracting attention as a leading technology above all the other technologies. Big data took data prediction model to another level by providing the base for the analysis of unstructured data that could not have been analyzed in the past. Since what cloud services and big data have in common is the services and analysis based on mass amount of data, efficient operation and designing of mass data has become a critical issue from the early stage of development. Thus, in this paper, I would like to establish data processing architecture based on technological requirements of mass data for cloud and big data services. Particularly, I would like to introduce requirements that must be met in order for distributed file system to engage in cloud computing, and efficient compression technology requirements of mass data for big data and cloud computing in terms of cost-saving, as well as technological requirements of open-source-based system such as Hadoop eco system distributed file system and memory database that are available in cloud computing.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.165-174
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• 1998

The observation of liquid water content(LWC) and the estimation of precipitation enhancement by cloud seeding were made over the Andong in Korea from March 1997 through Feb 1998. A dual-channel microwave radiometer was used to measure the liquid water content and water vapor. It was shown that the 90% of observational period had the amount of less than 0.1 mm in LWC, and that the amount of precipitation was proportionally increased to liquid water content. The amount of LWC has maximum in summer and minimum in winter. The content of liquid cloud water was showed higher value from the time of 12 to the time of 17 except for summer season in which it extremely fluctuated with a large precipitation. The majority of liquid water content over the area occurred with westerly and southwesterly wind which were flowed from the Sobaek mountain. The ratio of horizontal LWC flux and vertical precipitation flux, $P_{en}$ is almost ranked in the interval of 0.0~0.5 with maximum of 0.5 in spring, 0.2 in summer and fall, and 0.1 in winter. Accordingly, it is estimated that the potential enhancement of precipitation over Andong area by cloud seeding has high value in spring with westerly wind.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.1-21
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• 1995

The characteristics of the Asian summer monsoon have been investigated for the periods of 1993/1994, the contrasting years in a view of the summer monsoon precipitation. In order to investigate the monsoon features over the eastern Asian monsoon region, the cloudiness(using the extensive data derived by the geostationary meteorological satellite), the condition of underlying surface including sea-surface temperature, and the summer rainfall are analyzed and some comparisons with 1993 and 1994 are also made and the characteristic differences are discussed. An analysis of the 2-degree latitude-longitude gridded 5-day mean high cloud amount data shows the detailed movement and persistence of the convective activities. In order to describe the spatial and temporal structures of the intraseasonal oscillation for the movement and evolution of the monsoon cloud, the extended empirical orthogonal fnction analysis with the twenty-day window size is used for the each year. Also, in order to find out the periodicity of the equatorial convective cluster, Fourier harmonic analysis is applied to the each year. The most prevailing intraseasonal oscillations of high cloud amount are 61 day mode and 15day mode in the equatorial and the subtropical oceans. However it was found that the most prevailing modes over the equatorial western Pacific and Indian Ocean were different for each year, hence raising the possibillity that the contrasting monsoon presipitation may be more fundamentally related to the interaction of intraseasonal oscillations and seasonal variation of convective activities over the lower latitude ocean.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.35-41
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• 2020

3D laser scanners are an effective way to quickly acquire a large amount of data about an object. Recently, it is used in various fields such as surveying, displacement measurement, 3D data generation of objects, construction of indoor spatial information, and BIM(Building Information Model). In order to utilize the point cloud data acquired through the 3D laser scanner, it is necessary to make the data acquired from many stations through a matching process into one data with a unified coordinate system. However, analytical researches on the accuracy of point cloud data according to the registration method are insufficient. In this study, we tried to analyze the accuracy of registration method of point cloud data acquired through 3D laser scanner. The point cloud data of the study area was acquired by 3D laser scanner, the point cloud data was registered by the ICP(Iterative Closest Point) method and the shape registration method through the data processing, and the accuracy was analyzed by comparing with the total station survey results. As a result of the accuracy evaluation, the ICP and the shape registration method showed 0.002m~0.005m and 0.002m~0.009m difference with the total station performance, respectively, and each registration method showed a deviation of less than 0.01m. Each registration method showed less than 0.01m of variation in the experimental results, which satisfies the 1: 1,000 digital accuracy and it is suggested that the registration of point cloud data using ICP and shape matching can be utilized for constructing spatial information. In the future, matching of point cloud data by shape registration method will contribute to productivity improvement by reducing target installation in the process of building spatial information using 3D laser scanner.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.543-548
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• 2015

Recently top-k query processing has been extremely important along with the explosion of data produced by a variety of applications. Top-k queries return the best k results ordered by a user-provided monotone scoring function. As cloud computing service has been getting more popular than ever, a hot attention has been paid to cloud-based data outsourcing in which clients' data are stored and managed by the cloud. The cloud-based data outsourcing, though, exposes a critical secuity concern of sensitive data, resulting in the misuse of unauthorized users. Hence it is essential to encrypt sensitive data before outsourcing the data to the cloud. However, there has been little attention to efficient top-k processing on the encrypted cloud data. In this paper we propose a novel top-k processing algorithm that can efficiently process a large amount of encrypted data in the cloud. The main idea of the algorithm is to prune unpromising intermediate results at the early phase without decrypting the encrypted data by leveraging an order-preserving encrypted technique. Experiment results show that the proposed top-k processing algorithm significantly reduces the overhead of client systems from 10X to 10000X.

• Atmosphere
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• v.19 no.2
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• pp.155-168
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• 2009

Characteristics of seasonal mean diurnal temperature range (DTR) and their causes over South Korea are investigated using the 60 stations data of Korea Meteorological Administration from 1976 to 2005. In general, the seasonal mean DTR is greatest during spring (in inland area) and least during summer (urban and coastal area). The spatial and seasonal variations of DTR are closely linked with the land surface conditions (especially vegetation activity and soil moisture) and atmospheric conditions (cloud amount, precipitation, local circulation). The seasonal mean DTR shows a decreasing trend at the major urban areas and at the north-eastern part of South Korea. Whereas, it shows an increasing trend at the central area of the southern part. Decreasing and increasing trends of DTR are more significant during summer and fall, and during spring and winter. The decrease (increase) of DTR is mainly caused by the stronger increase of daily minimum (maximum) temperature than daily maximum (minimum) temperature. The negative effects of precipitation and cloud amount on the DTR are greater during spring and at the inland area than during winter and at the coastal area. And the effect of daytime precipitation on the DTR is greater than that of nighttime precipitation.

• Solar Energy
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• v.12 no.2
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• pp.1-8
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• 1992

Identifying characteristics of heating and cooling systems requires estimation of thermal load of specific time interval, especially in cases that its system is operated intermittently, by using thermal storage, of in a partial load condition. Estimating the thermal load, however, needs to forecast hourly weather data variation. Hence, this paper attempts to examine characteristics of hourly ourdoor temperature variation as a preliminary research for the mathematical modeling of the hourly weather variation. Speculating characteristics of daily minimum and maximum temperature occurances, hourly outdoor temperature variation, and daily temperature differences in the increasing range ($07h{\sim}15h$) and decreasing range($15h{\sim}07h$), we were able to analyze changing patterns of daily temperature differences in each range in terms of daily solar amount, cloud ratio, and other weather data. Results from the multiple regression analysis enables us to conclude that daily differences in the increasing range are strongly affected last night temperature itself while the other range's differences are influenced by many weather data, which are solar amount, the variation of cloud, and the maximum temperature of the previous day.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.166-173
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• 2020

Multi-view images, which are widely used for providing free-viewpoint services, can enhance the quality of synthetic views when the number of views increases. However, there needs an efficient representation method because of the tremendous amount of data. In this paper, we propose a method for generating point cloud data for the efficient representation of multi-view color and depth images. The proposed method conducts sequential reconstruction of point clouds at each viewpoint as a method of deleting duplicate data. A 3D point of a point cloud is projected to a frame to be reconstructed, and the color and depth of the 3D point is compared with the pixel where it is projected. When the 3D point and the pixel are similar enough, then the pixel is not used for generating a 3D point. In this way, we can reduce the number of reconstructed 3D points. Experimental results show that the propose method generates a point cloud which can generate multi-view images while minimizing the number of 3D points.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.1-9
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• 2016

To well design the solar energy system, the correlation to calculate and predict solar irradiation is basically needed. So, this study was performed to reveal the relationships between the solar irradiation and four meteorological observation data(dry-bulb temperature, relative humidity, duration of sunshine, and amount of cloud) that didn't show from previous any other researches. And then, we finally proposed the various order non-linear correlation from the measured solar irradiation and four meteorological measurement data using MINITAB. To show the deviation and accuracy of the solar irradiation between measured and calculated, this study compared for the daily total solar insolation. From those results, the calculation error could well predicted about maximum 97% for the daily total solar insolation. But, the coefficients of the proposed correlations didn't show any relationships. So, needs more studies to make the proper one correlation for the country.