• The KIPS Transactions:PartA
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• v.12A no.3 s.93
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• pp.253-262
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• 2005

Local accounting system used by UNIX-like operating system provides the accounting information of processes that are in single host. But it is impossible for this local accounting system to record the total resource consumption data of all processes for doing the same job simultaneously. In this paper, we implement accounting system to measure and manage resource usage for MPI(Message Passing Interface) job in the clustering environment. We designed and implemented the accounting system which measure resource usage of each process runs on a cluster node and record the interconnection information of the entire set of processes across network. Also we implemented accounting system which collect the resource usage data of process in the local accounting system and generate the job-level accounting information. Finally, to evaluate the resource consumption data measured by this accounting system we compare with the data collected by local scheduler that widely used in large scale clustering environment.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.367-376
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• 2001

For the electronic map service by wireless, the existing map database cannot be used directly. This is because, the data volume of a map is too big to transfer by wireless and although the map is transferred successfully, the devices to display the map usually don’t have enough resources as the ones for desktop computers. It is also not acceptable to construct map database for the exclusive use of wireless service because of the vast cost. We propose new technique to generate a map for wireless service dynamically, from the existing map database. This technique includes the generalization method to reduce the map data volume and filtering method to guarantee that the data volume don’t exceed the limit of bandwidth. The generalization is performed in 3 steps :ㅁ step of merging the layers, a step of reducing the size of spatial objects, and a step of processing user interface. The filtering is performed by 2 module, counter and selector module. The counter module checks whether the data blume of generated map by generalization, exceeds the bandwidth limit. The selector module eliminates the excess objects and selects the rest, on the basis of distance.

• Atmosphere
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• v.21 no.4
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• pp.405-414
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• 2011

In this study, the influence of a change in land use on the local weather fields is investigated around the Lake Shihwa area using synthetic land cover data and a high-resolution mesoscale model - the Weather Research and Forecasting (WRF). The default land cover data generally used in the WRF is based on the land use category of the United States Geological Survey (USGS), which erroneously presents most land areas of the Korean Peninsula as savannas. To revise such a fault, a multi-temporal land cover data, provided by the Ministry of Environment of Korea, was employed to generate a land cover map of 2005 subject to the land use in Korea at that time. A new land cover map of 1989, before the construction of the Lake Shihwa, was made based on the 2005 map and the Landsat 4-5 TM satellite images of two years. Over the areas where the land use had been changed (e.g., from sea to wetlands, towns, etc.) due to the Lake Shihwa development project, the skin temperature decreased by up to $8^{\circ}C$ in the winter case while increased by as much as $14^{\circ}C$ in the summer case. Changes in the water vapor mixing ratio were mostly affected by advection and topography in both seasons, with considerable increase in the summer case due to continuous sea breeze. Local decrease in water vapor occurred over high land use change areas and/or over downstream of such areas where alteration in wind fields were induced by changes in skin temperature and surface roughness at the areas of land use changes. The albedo increased by about 0.1% in the regions where sea was converted into wetland. In the regions where urban areas were developed, such as Songdo New Town and Incheon International Airport, the albedo increased by up to 0.16%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.345-352
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• 2020

Forest fires generate many types of risk as well as a wide and varied range of damage. Various studies and systems have emerged in response to wildfire disasters. International wildfire disaster safety management systems apply advanced technologies such as utilizing big data, GIS-based systems, and decision-making systems. This study analyzes South Korea's and other countries' forest fire disaster safety management systems, and suggests alternatives for wildfire disaster safety management in Korea. First, a means of integrating information, including field information, obtained by domestic agencies is proposed. Second, a method of applying big data to the disaster response system is proposed. Third, a decision-making system is applied to an existing GIS-based system. When applying the above countermeasures to Korea's existing disaster safety management system, various information and data can be visualized and thus more easily identified, leading to more effective decision-making and reduced fire damage.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.42-53
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• 2020

With the development of social network services, graph structures have been utilized to represent relationships among objects in various applications. Recently, a demand of subgraph matching in real-time graph streams has been increased. Therefore, an efficient approximate Top-k subgraph matching scheme for low latency in real-time graph streams is required. In this paper, we propose an approximate Top-k subgraph matching scheme considering data reuse in graph stream environments. The proposed scheme utilizes the distributed stream processing platform, called Storm to handle a large amount of stream data. We also utilize an existing data reuse scheme to decrease stream processing costs. We propose a distance based summary indexing technique to generate Top-k subgraph matching results. The proposed summary indexing technique costs very low since it only stores distances among vertices that are selected in advance. Finally, we provide k subgraph matching results to users by performing an approximate Top-k matching on the summary indexing. In order to show the superiority of the proposed scheme, we conduct various performance evaluations in diverse real world datasets.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.173-179
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• 2004

Due to the insufficiency of training data in large vocabulary continuous speech recognition, similar context dependent phones can be clustered by decision trees to share the data. When the decision trees are built and used to predict unseen triphones, a phonetic question set is required. The phonetic question set, which contains categories of the phones with similar co-articulation effects, is usually generated by phonetic or linguistic experts. This knowledge-based approach for generating phonetic question set, however, may reduce the homogeneity of the clusters. Moreover, the experts must adjust the question sets whenever the language or the PLU (phone-like unit) of a recognition system is changed. Therefore, we propose a data-driven method to automatically generate phonetic question set. Since the proposed method generates the phone categories using speech data distribution, it is not dependent on the language or the PLU, and may enhance the homogeneity of the clusters. In large vocabulary speech recognition experiments, the proposed algorithm has been found to reduce the error rate by 14.3%.

• Journal of Astronomy and Space Sciences
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• v.25 no.3
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• pp.267-282
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• 2008

The GNSS (Global Navigation Satellite System) signal is delayed by the neutral atmosphere at the troposphere, so that the delay is one of major error sources for GNSS precise positioning. The tropospheric delay is an integrated refractive index along the path of GNSS signal. The refractive index is empirically related to standard meteorological variables, such as pressure, temperature and water vapor partial pressure, therefore the tropospheric delay could be calculated from them. In this paper, it is presented how to generate meteorological data where observation cannot be performed. KASI(Korea Astronomy & Space Science Institute) has operated 9 GPS (Global Positioning System) permanent stations equipped with co-located MET3A, which is a meteorological sensor. Meteorological data are generated from observations of MET3A by Ordinary Kriging. To compensate a blank of observation data, simple models which consider periodic characteristics for meteorological data, are employed.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.183-196
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• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.136-150
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• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• Korean Journal of Occupational Health Nursing
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• v.11 no.1
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• pp.44-51
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• 2002

Purpose: Surgical Site Infection(SSI) is the third most common cause of nosocomial infection, so that it results in serious socioeconomic impact such as extra hospitalization, mortality and health care cost. The aim of this study was to analyses the SSI that based on the degree of wound contamination and patient risk index after general surgery and to generate a reference data for the effective management and reducing SSI. Method: From July, 1999 to June, 2000, 1080 cases which presented with surgical site infection after general surgery at S hospital in chunchon city were included in this study. The data were collected by review of the medical records retrospectively. The collected data, in accordance with the test purpose, is analyzed by SPSS/PC+ program, using real numbers, percentage, $X^2$ test, Pearson's correlation and stepwise logistic regression. Result: The overall wound infection rate was 4.7%(51 cases out of 1,080). The infection rate of clean wounds was 1.4%. Surgical site infection rate for patient risk index scores of 0, 1, 2 and 3 was 1.9%, 8.0%, 13.1% and 20.0%, respectively and increased significantly according to patient risk index(p=.000). Sixteen of the fifty one(31.4%) surgical site infections were found during an outpatient visit after discharge. Multivariate analysis, identified two independent variables : duration of postoperation stay(p=.000), age(p=.037). The most frequent isolated organisms were Pseudomonas aeruginosa(21%) and Staphylococcus aureus(21%). Also Staphylococcus aureus were all MRSA(Methicillin Resistant S. aureus). Conclusion: In this study, SSI was analysed according to the degree of wound contamination and patient risk index after general surgery. The data that obtained from this study is expected that it would be available for surveillance and control of SSI.