• Korea journal of population studies
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• v.26 no.2
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• pp.175-195
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• 2003

This paper investigates spatial distribution of the knowledge-information occupations by utilizing Geographical Information System(GIS). The knowledge-information occupations, comprised mainly of professionals, engineers and managers, have played a key role in the knowledge-based information society. The uneven development of bureaucratization and informatization among regions have resulted in unequal spatial distribution of the knowledge-information occupations. Analysis of 1995 and 2000 Census shows that these occupations tend to concentrate in some major metropolitan areas, while the other areas show rather traditional occupational structure. This spatial unequality has been also found in the occupational distribution within Seoul. This tendency of spatial concentration in the occupational distribution inherited from the industrial society and is not going to diminish in the knowledge-information society. More aggressive policies to make the most of decentralizing impacts of information and communication technologies should be implemented to counter-balance this tendency.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.189-208
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• 2021

Public library usage is closely related to the accessibility to library facilities. Therefore, public library planning and development authorities should consider the policies for improving the library accessibility of community, for releasing disparities of the spatial accessibility and for increasing location efficiency of public libraries. In this regard, this study strives to analyze the spatial distribution of public libraries in Busan and to derive the regions that lack public libraries by identifying main characteristics using geographical information systems (GIS): identify the blind spot for public library service, analyze the hot and cold spot for the supply of libraries, and identify the vulnerable areas of library based on population density. The result of the study will contribute to understand the spatial distribution of public libraries in Busan and to prioritize sites where public library should be constructed in order to improve the accessibility to public library services.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.395-410
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• 2024

Text data is usually made up of a wide variety of unique words. Even in standard text data, it is common to find tens of thousands of different words. In text data analysis, usually, each unique word is treated as a variable. Thus, text data can be regarded as a dataset with a large number of variables. On the other hand, in text data classification, we often encounter class label imbalance problems. In the cases of substantial imbalances, the performance of conventional classification models can be severely degraded. To improve the classification performance of support vector machines (SVM) for imbalanced data, algorithms such as the Synthetic Minority Over-sampling Technique (SMOTE) can be used. The SMOTE algorithm synthetically generates new observations for the minority class based on the k-Nearest Neighbors (kNN) algorithm. However, in datasets with a large number of variables, such as text data, errors may accumulate. This can potentially impact the performance of the kNN algorithm. In this study, we propose a method for enhancing prediction performance for the minority class of imbalanced text data. Our approach involves employing variable selection to generate new synthetic observations in a reduced space, thereby improving the overall classification performance of SVM.

• Journal of KIISE
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• v.44 no.11
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• pp.1209-1218
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• 2017

A variety of sensors is widely used these days, and it has become much easier to acquire spatial big data streams from various sources. Since spatial data streams have inherently skewed and dynamically changing distributions, the system must effectively distribute the load among workers. Previous studies to solve this load imbalance problem are not directly applicable to processing spatial data. In this research, we propose Adaptive Spatial Key Grouping (ASKG). The main idea of ASKG is, by utilizing the previous distribution of the data streams, to adaptively suggest a new grouping scheme that evenly distributes the future load among workers. We evaluate the validity of the proposed algorithm in various environments, by conducting an experiment with real datasets while varying the number of workers, input rate, and processing overhead. Compared to two other alternative algorithms, ASKG improves the system performance in terms of load imbalance, throughput, and latency.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.161-173
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• 2020

This study analyzed local imbalances in the supply and demand of emergency medical services in Busan using the 119 emergency activity reports of the Busan Fire & Disaster Headquarters. The data for EMS activity reports in 2017 was converted into Jimgyegu units. The spatial distribution of the indicators representing the local imbalance of emergency demand and supply (number of reports, number of reports relative to the population, average coefficient of variation and outlier of on-site arrival time, and number of dispatches outside the jurisdiction) was analyzed using Hotspot analysis of GIS spatial statistics analysis. As a result of the analysis, the hot spot area and the cold spot area where both supply and demand of emergency services are concentrated were clearly distinguished. This means that the supply and demand of emergency services in Busan are locally unbalanced. In particular, there was a difference in the demand and supply of emergency services in the original downtown and its surrounding areas, and in the outskirts of Busan.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.373-381
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• 2011

This paper discusses how to get the sums of squares due to treatment factors when Type I Analysis is used by projections for the analysis of data under the assumption of a two-way ANOVA model. The suggested method does not need to calculate the residual sums of squares for the calculation of sums of squares. There-fore, the calculation is easier and faster than classical ANOVA methods. It also discusses how eigenvectors and eigenvalues of the projection matrices can be used to get the calculation of sums of squares. An example is given to illustrate the calculation procedure by projections for unbalanced data.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.121-125
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• 2009

The Public Noticed Land Price system was developed in order to establish a practical and consistent land price information system, where land prices are appraised and publicly noticed according to the Law Governing the Public Notice of Real Estate Prices and Appraisals.The appraisal process for evaluating and appraising the public noticed land price in conducted in phases, where the nation's land is divided into human and spatial portions according to administrative districts. Depending on the subjective judgement of the appraiser, it is therefore possible for discrepancies to occur in land prices for lots near the boundaries of administrative districts. There is the computerized support system to maintain the public noticed land prices balance between the boundaries of cities, counties, and districts (the units in which evaluation and appraisal are conducted to determine public noticed land prices). But, due to that system is divided into attribute and spatial data information, it is possible for discrepancies to occur in land prices for lots near the boundaries of administrative districts. The purpose of this study to suggest the reasonable methods on discrepancies in public noticed land prices through spatial analysis using GIS.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.519-532
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• 2024

Anomaly detection for the penetration rate of tunnel boring machines (TBMs) is crucial for effective risk management in TBM tunnel projects. However, previous machine learning models for predicting the penetration rate have struggled with imbalanced data between normal and abnormal penetration rates. This study aims to enhance the performance of machine learning-based anomaly detection for the penetration rate by utilizing a data augmentation technique to address this data imbalance. Initially, six input features were selected through correlation analysis. The lowest and highest 10% of the penetration rates were designated as abnormal classes, while the remaining penetration rates were categorized as a normal class. Two prediction models were developed, each trained on an original training set and an oversampled training set constructed using SMOTE (synthetic minority oversampling technique): an XGB (extreme gradient boosting) model and an XGB-SMOTE model. The prediction results showed that the XGB model performed poorly for the abnormal classes, despite performing well for the normal class. In contrast, the XGB-SMOTE model consistently exhibited superior performance across all classes. These findings can be attributed to the data augmentation for the abnormal penetration rates using SMOTE, which enhances the model's ability to learn patterns between geological and operational factors that contribute to abnormal penetration rates. Consequently, this study demonstrates the effectiveness of employing data augmentation to manage imbalanced data in anomaly detection for TBM penetration rates.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.119-144
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• 2003

This study attempts to figure out the impact of Information and communication technologies (ICTs) on spatial structure and to speculate on spatial strategies in the electronic economy from a geographical perspective. The unprecedented development of ICTs based on the explosive use of the Internet was enough to lead to the expectation that physical distance would not be a significant barrier in business activities. In fact, however, at least at a current stage, the development of ICTs has not automatically removed the inequality in spatial structure. The accessibility to electronic space is different by economic and social status within a country as well as between countries. The importance of place, locality, and place-specific assets has been strengthened in the global economy. Physical proximity is still of great importance because it helps to minimize transaction costs, to exploit place-specific social networks, and to accumulate credibility for successful businesses. Likewise, the development of electronic commerce such as B2B and B2C EC also does not necessarily result in the ignorance of place and locality. Rather, the recognition of the importance of spatial strategies is extremely important for the success in online businesses. As a conclusion, the spatial dimension becomes more important in the digital era for successful businesses and balanced regional developments than ever before. The need for the improvement of ICT infrastructures, the development of human resources, and the establishment of regional innovation systems in peripheral areas cannot be overemphasized even in the digital era.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.10-15
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• 1998

주문형 비디오 시스템에서 저장되는 영화들의 다중 액세스를 지원하기 위해 영화들은 비디오 서버의 다수의 디스크에 걸쳐 스트라이프되고, 비디오 서버의 디스크 배열들간의 부하 불균형을 피할 뿐만 아니라 저장 공간과 장치 대역폭을 최대로 이용하기 위하여 영화의 블록들은 디스크 배열에 신중히 배치되어야 한다. 본 논문에서는 영화의 인기도를 고려한 동적 디스크 스트라이핑에 기초하는 그룹교대 라운드로빈이라는 영화 배치 방법을 제안하고, 그것의 성능을 시뮬레이션을 통하여 평가한다.