• KDI Journal of Economic Policy
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• v.35 no.1
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• pp.63-101
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• 2013

'Venture firms' in Korea are the firms who are certified as 'venture', whose certification types are defined by a law ('Special Law for the Support of Venture Firms'), and therefore encompass not only the venture capital-financed companies, which are usually regarded as ventures in USA and European countries, but also other types of firms such as R&D-intensive firms and the firms with financial guarantee or loans through technology evaluation ('technology finance or loan firms'). This paper examines the differences in the Korean venture firms' growth between the venture certification types. For the empirical analysis, this paper uses the lists of venture-certified firms from 1998 to 2010 which are then linked with their financial data in Korea Enterprises Database (KED). According to the results of empirical analyses, the companies in the 'venture capital-financed firms' type show greater growth rate in sales and the number of regular employees 3 and 5 years after first venture certification than the firms in type of 'technology finance/loan firms'. Moreover, the newly certified companies in 'R&D-intensive firms' type are also showing faster growth than the 'technology finance/loan firms' since 2003 where the venture industry has undergone a consolidation phase after the blast of so-called 'IT venture bubble' in 2001~2002. These results imply that the so-called 'venture firms' in Korea are composed with heterogeneous firm groups with different characteristics and that the companies selected through market mechanism ('venture capital-financed firms') outperforms the companies selected on the basis of policy interests ('technology finance/loan firms') in terms of the growth in sales and employment. On the basis of these findings, this paper suggests that the current venture-support policy should consider the different policy demands of firms across the type of venture certification more actively and that should refocus the objective of policies on facilitating venture capital market rather than emphasizing the nominal increase in the number of venture-certified firms.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.96-107
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• 2015

Brownfield sites are beginning to be considered as potentially useful areas for landscape design and planning, with post-industrial areas such as water treatment facilities and military training bases being converted into useful landscapes such as parks and recreation areas. These redevelopments bring broad benefits through revitalizing communities and increasing property values, thus, increasing the demand for comprehensive management and planning policies. This study examines changes in U.S. brownfield policies and programs and, identifies their periodic characteristics over the thirty years since the Superfund program was introduced in 1980. A descriptive and interpretive approach was utilized, focusing specifically on a time sequential analysis of the data gathered from the overview of the Environmental Protection Agency's web-based documents and related literature. The primary changes in and characteristics of programs and policies were analyzed and divided into three periods : environmental protection, remediation and reuse, and comprehensive planning. Four major features were identified: relaxation and readjustment of regulation, diversification of support programs, a mix of top-down and bottom-up approaches, and database system building. The study examines how common brownfield problems such as site identification difficulties and assessment and remediation cost have been dealt with in the regulatory context and has implications for future policies and programs for effective brownfield planning and management in Korea.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.2
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• pp.65-76
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• 2014

Green Infrastructure(GI) is suggested to recover urban water circulation system as a newly conceptual alternative methodology by Korean landscape field in recent years. In this context, the study considers the essential meaning of GI. The methodology of this study is literature review with 47 published papers which were peer-reviewed in international journals in the recent 5 years. These papers were collected from online database and academic archives. The main analysis targets are definition sentences about GI. The each sentences were interpreted by semantic structure between verbs and objects in the definition sentences. As the results, it figured out 5 aims('Provide', 'Improve', 'Produce', 'Conserve', 'Reduce'), 4 objects('Humanistic', 'Environmental', 'Ecological', 'Hydrological') and 3 spaces('Object space', 'Technically available spaces', 'Object or technically available spaces'). The '5 aims' connected with the elements of '4 objects' based on the '3 spaces'. The elements was connected to the '5 aims' via single form or 2~3 forms of the essential meaning networks of GI. The study provides 83 meaning networks to use landscape architecture planning and urban planning.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.467-477
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• 2004

While recommender systems were used by a few E-commerce sites former days, they are now becoming serious business tools that are re-shaping the world of I-commerce. And collaborative filtering has been a very successful recommendation technique in both research and practice. But there are two problems in personalized recommender systems, it is First-Rating problem and Sparsity problem. In this paper, we solve these problems using the associative relation clustering and “Lift” of association rules. We produce “Lift” between items using user's rating data. And we apply Threshold by -cut to the association between items. To make an efficiency of associative relation cluster higher, we use not only the existing Hypergraph Clique Clustering algorithm but also the suggested Split Cluster method. If the cluster is completed, we calculate a similarity iten in each inner cluster. And the index is saved in the database for the fast access. We apply the creating index to predict the preference for new items. To estimate the Performance, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.1-8
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• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1221-1230
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• 2004

In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

• Ecology and Resilient Infrastructure
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• v.2 no.2
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• pp.185-190
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• 2015

Greenhouse gas (GHG) emission from agricultural lands is recognized as one of important factors of global warming. The objective of this short communication was to evaluate the applicability of different soil GHG emission prediction models on agricultural systems in Korea. Four models, namely, DNDC, DAYCENT, EXPERT-N and COUP, were selected and the basic structure (e.g., components and sub-model), input variables, and output variables were compared. In particular, the availability and compilation of essential input variables were assessed. Major input variables needed for operating these predictive models were found to be available through database systems established by national organizations such as the Korea Meteorological Administration, the Korean Soil Information System, and the Rural Development Administration. However, in order to apply these models in Korea, it was necessary to calibrate and validate each of the models for the domestic landscape settings and climate conditions. In addition, field data of long-term monitoring of GHG emission from agricultural lands are limited and therefore should be measured.

• Journal of the Society of Disaster Information
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• v.13 no.3
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• pp.296-304
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• 2017

In order to predict about forest fire behavior we constructed a database for combustion characteristic of forest fuels in Samcheok, Gangwon-do and prepared fire risk map and fire risk rating using GIS method in this study. For the mapping autoignition temperature, ignition time, flame duration time, total heat release and total smoke release are selected as the standardized parameters and the overall risk rating was made up of the ignition risk parameters(autoignition temperature, ignition time) and the spread risk parameters(flame duration time, total heat release, total smoke release). Forest fire risk was classified into 5 grades and lower grade of fire risk rating mean to correspond to more dangerous forest fire. As a result, the overall risk rating of Samcheok was classified into three grades from 1 to 3 and Nogok-myeon and Miro-myeon were turned out the most dangerous areas for forest fire. Because of the colony of pine and oak trees and the higher fire loads, the flame propagation will be carried out quickly in these areas.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.397-409
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• 2014

According to the Personal Information Protection Act(PIPA) which is legislated in March 2011, the individual or company that handles personal information, called Personal information processor, should encrypt some kinds of personal information kept in his Database. For convenience sake we call it DB Encryption in this paper. Law enforcement and the implementation agency accordingly are being strengthen the supervision that the status of DB Encryption is being properly applied and implemented as the PIPA. However, the process of DB Encryption is very complicate and difficult as well as there are many factors to consider in reality. For example, there are so many considerations and requirements in the process of DB Encryption like pre-analysis and design, real application and test, etc.. And also there are surely points to be considered in related system components, business process and time and costs. Like this, although there are plenty of factors significantly associated with DB Encryption, yet more concrete and realistic validation entry seems somewhat lacking. In this paper, we propose a realistic DB Encryption Assurance Framework that it is acceptable and resonable in the performance of the PIPA duty (the aspect of the individual or company) and standard direction of inspection and verification of DB Encryption (the aspect of law enforcement).