• Korean Journal of Environmental Biology
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• v.27 no.2
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• pp.191-197
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• 2009

In order to characterize the ecological traits of Q. mongolica, we treated the seedlings of this species with three environmental factors, light, moisture and nutrient gradients from March to October 2007, and measured morphological and ecological 17 characters. Lastly calculated ecological niche breadth and niche overlap between Q. mongolica-Q. acutissima and Q. mongolica-Q. variabilis, and analysed them with a special reference to ecological distribution pattern and their competition relationship in Korea. The ecological niche breadth of Q. mongolica showed the lowest in nutrient treatment, but the highest in soil moisture treatment. The ecological niche value under light was intermediate. On comparison of the ecological niche breadth of three oak species, Q. mongolica showed the highest in light environment, which might be a reason for the dominant distribution in the forest plant community, Korea. The ecological niche overlap of Q. mongolica-Q. acutissima and Q. mongolica-Q. varabilis was the widest in moisture treatment, but the narrowest in nutrient treatment and the intermediate in light one. These results means that these three oak species be most competitive in moisture environment than light or nutrient one, and that there are least differentiated among oak species for soil moisture condition. Cluster and PCA ordination showed that Q. mongolica and Q. acutissima were more closely arranged than Q. mongolica and Q. variabilis. From these results, it can be explained that Q. mongolica have more similar ecological niche with Q. acutissima than with Q. variabilis, consequently competition between Q. mongolica and Q. acutissima is intensive than Q. mongolica and Q. variabilis for environment condition, especially in soil moisture.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.12a
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• pp.411-419
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• 1999

EBPP는 소비자, 사업자간에 고지서 발송, 접수 및 지불을 네트워크를 통하여 전자적으로 처리하는데 필요한 환경을 의미하며, 인터넷을 기반으로 하여 전자우편 혹은 웹 페이지를 통하여 고지서를 처리한다 EBPP 시스템은 크게 소비자, 사업자 그리고 은행간의 거래로 이루어 지지만 컴퓨터 및 인터넷의 보급의 한계 등의 문제로 현재로서 모든 고지서를 전자적으로 처리하는 것은 무리가 따른다. 그럼에도 불구하고 EBPP 시스템은 1) 경쟁력 확보를 위해 기업/금융 기관들이 인터넷을 통한 고품질 서비스 개발에 주력하는 추세이고, 2) 고객과의 보다 긴밀한 관계 유지를 위한 수단 제공하며, 3) 인터넷 등 온라인 통신 인구가 급격한 증가(2701년에 전체 인구의 약 50%가 활용할 것으로 전망)하고 있으며,4) 소비자를게 보다 편리한 지불방법 제시해주며, 5) 또 다른 마케팅 매체로 활용 가능하므로 앞으로의 전망이 매우 밝다. EBPP시스템은 크게 금융기관, 기업, 소비자 부분으로 구성되며, 소비자와 접촉 방법으로는 대표적으로 Web과 전자우편을 생각할 수 있으며, EBPP 시스템을 구축하기 위해서는 기본적으로 상접 혹은 기업에서 청구에 필요한 정보를 등록시키는 통합 청구서버(Bill consolidation server), 소비자에게 청구 가능한 정보를 갖고있는 청구 제시서버 (Bill presentment server), 소비자의 지불요청에 따라 은행으로부터 지불을 요구하는 지불서버(Payment gateway) 등이 필요하며, 이들 각각의 서버들의 구성 요소들은 제공하는 서비스에 따라 달라질 수 있다. 통합 청구서버에서 청구 제시서버로 전송되는 청구 건은 통상적으로 실시간 처리되는 것이 아니라 통합 청구서버에 존재하는 Spool DB에 저장되어 그 양이 일정한도를 넘어서면 자동 전송되도록 하여, 망의 할용도를 높이는 역할을 수행한다. 청구 제시서버의 DB에 등록된 청구 건은 인터넷을 통해 소비자에게 청구되며, 소비자에게 전송 되는 청구서는 사용자DB를 참조하여 사용자가 미리 정의한 원하는 형태로 변환되어 전달되며, 필요시 암호화 과정을 거치는 것이 가능해야 한다. 전송된 청구서는 전자우편의 경우, 암호해독이 가능한 전용 브라우저를 통해 열람 되며, 이는 다시 전용 브라우저를 통해 지불인증이 승인되어 청구 제시서버에게 전송된다. EBPP 시스템의 제어 흐름은 크게 기업이 청구 정보를 소비자에게 제시하는 흐름과 소비자의 지불 승인으로 인해 기업이 은행에 지불을 요구하는 흐름으로 구분할 수 있다. 본 논문에서는 통합 청구서버 및 정구 제시서버의 역할 및 구성 요소들에 대해 서술하고, EBPP 시스템과 연동하여야 하는 메일 서버와의 상호 작용에 대해 서술할 것이다. 본 시스템을 아직 구현이 되지 않은 관계로 시스템의 성능 등의 수치적 결과를 제시할 수 없는 상태다.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.7-14
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• 2008

The main objective of sewer rehabilitation is to improve its function while eliminating inflow/infiltration (I/I). If we can identify the amount of I/I for an individual pipe, it is possible to estimate the I/Is of sub-areas clearly. However, in real, the amount of I/I for an individual pipe is almost impossible to be obtained due to the limitation of cost and time. In this study, I/I occurrence of each sewer pipe is estimated using AHP (Analytic Hierarch Process) and RPDM (Rehabilitation Priority Decision Model for sewer system) was developed using the estimated I/I of each pipe to perform the efficient sewer rehabilitation. Based on the determined amount of I/I for an individual pipe, the RPDM determines the optimal rehabilitation priority (ORP) using a genetic algorithm for sub-areas in term of minimizing the amount of I/I occurring while the rehabilitation process is performed. The benefit obtained by implementing the ORP for rehabilitation of sub-areas is estimated by the only waste water treatment cost (WWTC) of I/I which occurs during the sewer rehabilitation period. The results of the ORP were compared with those of a numerical weighting method (NWM) which is the decision method for the rehabilitation priority in the general sewer rehabilitation practices and the worst order which are other methods to determine the rehabilitation order of sub-areas in field. The ORP reduced the WWTC by 22% compared to the NWM and by 40% compared to the worst order.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.279-290
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• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.38-46
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• 2004

Image segmentation is the task which partitions the image into meaningful regions and considered to be one of the most important steps in computer vision and image processing. Image segmentation is also widely used in object-based video compression such as MPEG-4 to extract out the object regions from the given frame. Watershed algorithm is frequently used to obtain the more accurate region boundaries. But, it is well known that the watershed algorithm is extremely sensitive to gradient noise and usually results in oversegmentation. To solve such a problem, we propose an image segmentation method which is robust to noise by using stabilized inverse diffusion equation (SIDE) and is more efficient in segmentation by employing multiresolution approach. In this paper, we apply both the region projection method using labels of adjacent regions and the region merging method based on region adjacency graph (RAG). Experimental results on noisy image show that the oversegmenation is reduced and segmentation efficiency is increased.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.27-37
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• 2020

In this paper, we propose the methodology based on data-driven approach using Natural Language Processing and Machine Learning for classifying requirements into functional requirements and non-functional requirements. Through the analysis of the results of the requirements classification, we have learned that the trained models derived from requirements classification with data-preprocessing and classification algorithm based on the characteristics and information of existing requirements that used term weights based on TF and IDF outperformed the results that used stemming and stop words to classify the requirements into functional and non-functional requirements. This observation also shows that the term weight calculated without removal of the stemming and stop words influenced the results positively. Furthermore, we investigate an optimized method for the study of classifying software requirements into functional and non-functional requirements.

• Asia Marketing Journal
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• v.13 no.4
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• pp.29-54
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• 2012

Recently, as film has been admitted as the artistic merit and higher value-added business, the past studies on film have been lively carried on various fields. Especially, the film business is thought to be value-added business and has explored the causes of influencing spectators. However, there are no researches enough to explain what induces the choice and diffusion of the film. The film is not only hedonic products but also typical example of experiential products. So how to process film formation plays important roles in explaining the procedures of forming preference on the film and the movies spread more widely. But the great part of study of films has been concentrated on exploring hedonic factors of influencing spectator's choice. Until now there is not enough study for the relationship between experiential information processing and film preference. To explain film's preference, our study focuses on preference fluency and processing fluency that can provide an insight for our question about the relationship. In this article, to explain the procedures of processing experiential information and forming preference on the film, our study focuses on finding the relationship between film's processing fluency and film's preference fluency and explores the factors that affect film's processing fluency. To achieve the goal of this study, we distinguish factors of film's conceptual fluency from factors of film's perceptual fluency and explore the paths from the factors to film's preference fluency. The factors which have effects on perceptual fluency are hypothesized to be distinction of image expression, distinction of sound expression, correspondence between actors' image and their role. The factors which have effect on conceptual fluency are supposed to be well-organized story, suitability of lines expression. The experiments in which students were sampled at 'C' university were conducted in 2010 (december). Data collection was proceeded through questionnaires. We test the hypothesized model by using structural equation modeling(Amos 17.0). The fit indices for the model are as follows : x²=416.266(df=213, p=0.00), GFI=0.855, AGFI=0.812, RMSEA =0.069, IFI=O.925, CFI=0.920, TLI=0.905. According to the guidelines, there is evidence that our measurement model fits data. The results of empirical study are as follows. The path from film's perceptual fluency to film's preference fluency is supported(estimate: 0.223, C.R: 2.641). The path from film's conceptual fluency to film's preference fluency is supported(estimate: 0.397, C.R: 4.863). The path from distinction of image expression to film's perceptual fluency is not supported(estimate: 0.113, C.R: 1.665). The path from distinction of sound expression to film's perceptual fluency is supported (estimate: 0.190, C.R: 2.042). The path from correspondence between actors' image and their role to film's perceptual fluency is supported(estimate: 0.686, C.R: 5.566). The path from well-organized story to film's conceptual fluency is supported(estimate: 0.396, C.R: 4.023). The path from suitability of lines expression to film's conceptual fluency is supported(estimate: 0.536, C.R: 5.441). Concludingly, our study explored the influencing factors of film's processing fluency inducing film's Preference fluency. First, film's perceptual fluency and film's conceptual fluency have positive effects on film's preference fluency. Second, distinction of image expression is not significant on film's perceptual fluency, but distinction of sound expression and image's correspondence of actors' image and their role have positive effects on film's perceptual fluency. Lastly, well-organized story and suitability of lines expression have positive effects on film's conceptual fluency.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.265-269
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• 2006

차세대 웹의 중심기술인 시맨틱 웹을 구현하기 위해서는 컴퓨터가 지식을 추론하고 처리할 수 있게 하기 위한 지식표현방법인 온톨로지가 필수적으로 요구된다. 이러한 온톨로지 생성의 중요성이 점차 커져 가는 실정에 따라, 생성된 온톨로지들의 재사용을 위한 방법이 관련 연구들 사이에 중요한 과제로 떠오르기 시작되었다. 본 논문에서는 온톨로지의 재사용을 효율적으로 하기 위한 방법을 제안한다. 우리가 제안하는 방법은 온툴로지를 사용자가 이해하기 쉽고 편집이 용이한 그래프 형태로 표현하는 방법으로 온톨로지를 UML로 변환하여 UML을 통한 온툴로지 재사용 방안을 제안한다. 우리가 제안하는 방법은 다음과 같다. OMG의 MDA 개념을 기반으로 기존에 생성된 온톨로지를 XML 파서를 이용하는 방법을 통하여 XMI로 변환한다. XMI로 변환된 온툴로지는 UML 도구를 사용하여 재사용 할 수 있다. UML로 변환된 온톨로지는 위 과정을 역으로 다시 수행함으로써 온톨로지로 변환된다. 이렇게 UML로 변환된 온톨로지는 UML의 장점을 그대로 가지게 된다. 이미 널리 사용되고 가독성과 편집력 그리고 상호 운용성이 높은 UML을 이용하여 온톨로지의 재 사용성을 높이고자 하는데 있다. 즉 사용자가 직관적으로 온톨로지의 전체 구조와 의미를 파악하는데 도움을 주며 편집 또한 용이하다. 이러한 방법을 바탕으로 UML을 통해 온톨로지를 쉽게 사용자의 온톨로지에 대한 이해와 수정을 도와 온톨로지의 재 사용성을 높이고 사용자간의 공유를 용이하게 만들 수 있다.

• Journal of The Korean Association of Information Education
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• v.7 no.2
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• pp.219-226
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• 2003

It takes a lot of time to classify official documents in schools and educational institutions. In order to reduce the overhead, we propose an automatic document classification method using word information of the titles of documents in this paper. At first, meaningful words are extracted from titles of existing documents and Inverse Document Frequency(IDF) weights of words are calculated against each category. Then we build a word weight dictionary. Documents are automatically classified into the appropriate category of which the sum of weights of words of the title is the highest by using the word weight dictionary. We also evaluate the performance of the proposed method using a real dataset of a middle school.

• The Journal of Information Technology
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• v.1 no.1
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• pp.13-26
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• 1998

In general Information retrieval systems, improper keywords are often extracted and different search results are offered comparing to user's aim bacause the systems use only term frequency informations for selecting keywords and don't consider their meanings. It represents that improving precision is limited without considering semantics of keywords because recall ratio and precision have inverse proportion relation. In this paper, a system which is able to improve precision without decreasing recall ratio is designed and implemented, as client user module is introduced which can send feedbacks to server with user's intention. For this purpose, keywords are selected using relative term frequency and inverse document frequency and co-occurrence words are extracted from original documents. Then, the keywords are clustered by their semantics using calculated mutual informations. In this paper, the system can reject inappropriate documents using segmented semantic informations according to feedbacks from client user module. Consequently precision of the system is improved without decreasing recall ratio.