• Design & Manufacturing
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• v.15 no.4
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• pp.14-23
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• 2021

In this study, we have analyzed the access status and the data usage trend of the public Wi-Fi on the bus, which has not been carried out in the previous studies. The analysis period of this study is 5 months from Nov. 2020 to Mar. 2021. When we compared the access status of Seoul metropolitan and the non-metropolitan region against each region's deployment status ratio, the access ratio of the metropolitan region was higher than the non-metropolitan region, of which the gap was 4.53%. The access for each region showed the growing trend, which was 43.5% on average. The data usage also showed the growing trend, 2.7% on average. Weekly data usage showed the growing trend irrespective of weekdays or weekends. The data usage of the weekdays was 695GB higher than weekends. The data usage during commuting hours including school (7:00~9:00 a.m. and 4:00~6:00 p.m.) was higher than 3,000GB. We can conclude that bus public Wi-Fi was used more actively in non-metropolitan region than Seoul metropolitan region by the office workers and students. The secure access also showed the growing trend. And the secure data usage also showed the growing trend.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.705-716
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• 2002

This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.11
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• pp.752-759
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• 2008

This paper is to make up the climograph using standard weather data of the region of Seoul. It is made up by existed standard weather data of which the subjected region is Seoul in order to easily use work. The factors of weather data are outside air temperature and its absolute humidity, total solar radiation, amount of clouds, wind direction, and wind velocity. The standard weather data are verified by comparing with values of the existed degree day method. As the result of their verification, the difference of the data showed less than 3% each other. And, reliability of standard weather data is thought to be same as those of degree day.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.2
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• pp.169-178
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• 2005

A critical component of air pollution modeling is the representation of atmospheric flow fields within a model domain, since an accurate air quality simulation requires an accurate portrayal of the three-dimensional wind fields. The present study investigated data assimilation using surface observational data in the complex coastal regions to simulate a realistic atmospheric flow fields. Surface observational data were categorized into three groups (Near coastal region, Far coastal region 1, Far costal region 2) by the locations where the sites are. Experiments were designed according to the location of observational stations and MM5/CALPUFF was used. The results of numerical simulation of atmospheric flow fields are used as input data for CALPUFF which predicts dispersion fields of air pollutants. The result of this study indicated that data assimilation using data in the far coastal region 2 provided an attractive method for generating realistic meteorological fields and dispersion fields of air pollutants in Gwangyang area because data in the near coastal region are variable and narrow representation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.37-43
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• 2022

In this paper, we calculate the word frequency by date and region using news data related to COVID-19 distributed for about 8 months from December 2019 to July 2020, and visualized the correlation with the current state data of COVID-19 patients using the results. News data was collected from Big Kids, a news big data system operated by the Korea Press Promotion Foundation. The visualization system proposed in this paper shows the news frequency of the selected region compared to the overall region, the key keyword of the selected region, the region of the main keyword, and the date change of the selected region. Through this visualization, the main keywords and trends of COVID-19 confirmed and infected people can be identified for previous events.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.199-205
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• 1996

The purpose of this study, therefore, was to construct the region statistical information to present methods of the data. The results of this paper are as follows: First, the construction of region statistical data is much in need of utilizing the server of regional information center, or the database to the server of public institutions, Second, there are some difficulties to receive the region statistical data because of only depending on the main source of KOSIS provided by national units from National Statistical Office. Third, as there is another problem which is text searching system served by KOSIS, GU system should be established for the user's satisfaction served by easier accessing screen. Fourth, there should be a standard software production to suit for the accessing software of the region statistical data.

• Journal of the Korean earth science society
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• v.33 no.5
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• pp.422-433
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• 2012

The purpose of this study is to investigate the characteristic changes of the Changma season in the 2000s. To accomplish this goal, we have used daily rainfall data collected over nearly 40 years (1971 to 2010). The average summer precipitation data including the Changma season were collected from 16 weather stations that are placed across the three major regions (i.e. central region, southern region, and Jeju region) as Korea Meteorological Administration divided. These precipitation data were analyzed to find out characteristic changes of the Changma season. Results of the precipitation data comparison among the major regions that, monthly average precipitation in the central region was the highest in July; its precipitation tended to increase from May to September. In the southern region, the precipitation amount was lowest in June and tended to increase in May, September, and August. In the Jeju region, the precipitation has been the highest in June and July for the past 30 years, whereas September has been highest month in the last 10 years. The precipitation amount in the Jeju region decreased both in June and July, whereas it tended to grow in May, August and September. A correlation coefficient formula by Karl Pearson has been used to find out correlations between the Changma season and the precipitation of the major regions in 2000s and normal years. It was found that the correlation coefficient has decreased from 0.723 to 0.524 in the 2000s (2001 to 2010) compared to normal years (1971 to 2000).

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.20-21
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• 2014

Recently, activation of related construction projects due to the large traditional gas resource development of frozen soil region of Russia are expected. It is necessary to provide a plan that can be utilized and collectively managed the occurrence data in the engineering & construction stage for continued contracts of the pipe construction. Therefore, this research is aimed to provide a management plan of occurrence data for efficient management in engineering & construction stage of pipeline business in frozen soil region. The data of the engineering & construction(related pipe construction projects) can be accumulated each version and multiply managed. Furthermore, I will be expected to be the foundation of the systematic management of the classifying based on metadata and the optimizing operations using big data method.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.633-645
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• 2004

A critical component of air pollution modeling is the representation of meteorological fields within a model domain, since an accurate air quality simulation requires an accurate portrayal of the three-dimensional wind fields. The present study investigated data assimilation using surface observational data in the complex coastal regions to simulate an accurate meteorological fields. Surface observational data were categorized into three groups(Near coastal region, Far coastal regiln 1, Far costal region 2) by the locations where the data are. Experiments were designed and MM5 was used in each case of regions. Case 1 is an experiment without data assimilation, Case N is executed with data assimilation using observational data by meteorological stations and AWS data located in the near coastal region, within 1 km. Case F1 is also an experiment with data assimilation using observational data by meteorological stations and AWS data located in the far coastal regiln 1, more than 1km and less than 5km from the coastal lines. Case F2 is appled to data assimilation using observational data by meteorological stations and AWS data located in the far coastal region 2, beyond 5km from the coastal lines. The result of this study indicated that data assimilation using data in the far coastal region 1 and 2 provided an attractive method for generating accurate meteorological fields, especially in the complex coastal regions.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.715-718
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• 2009

Time series data is a sequence of data points, measured typically at successive, spaced at time intervals. Many devices for an efficient exploration is developed according as the items of time series data increase. Among these devices, there is a Timebox widget as a representative device of dynamic query for interactive data exploration. Timeboxes are rectangular query region of interest. The users can draw the region of interest using simple mouse manipulation and the query result sets is displayed. But there is a limitation to represent the concrete query region and Timeboxes visualize the query region inconsistent with the mental model of users. To resolve these problems, we propose a new device called DQB(Dynamic Query Band). DQB is a qeury region consisting of user defined polyline with a thickness on time series data. This device is possible to concretely specify the query region. Also, it provides a simple and convenient interface and a good conceptual model.