• 한국콘텐츠학회논문지
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• 제15권1호
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• pp.264-275
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• 2015

지역보건의료사업의 효과성과 효율성을 개선하기 위해 지역사회 요구에 기반한 우선순위과제가 선정되어 추진되고 있으나, 선정방법의 체계적인 사용이 이루어지지 못하고 있다. 본 연구는 우선순위선정 방법의 개선방안을 제시하고자 수행되었다. 81개의 지역보건의료계획에서 사용된 우선순위선정에 대해 방법 및 기준의 빈도를 파악하고, 각 방법이 제시한 내용을 바탕으로 실제 사용의 적절성을 분석하였다. 우선순위선정을 위한 분석대상으로 건강문제가 아닌 사업 자체를 하고 있는 경우가 많았다. 가장 많이 사용된 우선순위선정 방법은 Basic priority rating 이었으며 다음은 우선순위화 매트릭스이었다. 우선순위기준 중 문제의 크기를 보면, 만성질환에서는 유병률, 건강행위에서는 주로 건강문제를 가진 사람의 비율이 지표로 사용되고 있었다. 문제의 크기를 비롯하여 심각성, 중재 효과 등의 우선순위선정 기준이 객관적 자료 없이 평가되고 있었으며, 점수화기준도 명확하지 않았다. 우선순위선정의 분석대상을 건강문제로 한정하고, 건강문제 영역별로 점수화 기준을 제시해 줄 필요가 있다.

• 한국콘텐츠학회논문지
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• 제12권3호
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• pp.34-43
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• 2012

두 문자열 간의 유사도를 계산하는 문제는 정보 검색, 오타 교정, 스팸 필터링 등 다양한 분야에 응용될 수 있다. 동적 계획법 기반의 유사도 계산 방법을 통하여 한글 문자열의 유사도 계산을 위해서는 우선 음소간의 유사도에 대한 정의가 필요하다. 그러나 기존의 방법들은 수동적 설정에 의한 유사도 점수를 사용하고 있다는 한계점이 있다. 본 논문에서는 PAM(Point Accepted Mutation) 행렬과 유사한 확률 모델을 이용하여 변형 단어 집합으로부터 음소 간의 유사도를 자동적으로 계산하는 기법을 제안한다. 제안 기법은 주어진 변형 단어의 집합 내 유사한 단어 쌍을 찾아 문자열 정렬(Text Alignment)을 수행함으로써 음소 변형 규칙을 도출하고, 이로부터 각 음소 쌍의 상호 변형 빈도에 따른 유사도 점수를 계산한다. 실험 결과 특이도(Specificity) 77.2~80.4% 수준에서 불일치 여부에 따른 단순 점수 부여 방식에 비해서는 10.4~14.1%, 수동으로 음소 간 유사도를 직접 설정하는 방식에 비해서는 8.1~11.8%의 민감도(Sensitivity) 향상이 있음을 확인하였다.

• Journal of Computing Science and Engineering
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• 제8권2호
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• pp.94-106
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• 2014

Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2005년도 추계학술발표대회 및 정기총회
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• pp.15-18
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• 2005

A ribonucleic acid (RNA) is one of the two types of nucleic acids found in living organisms. An RNA molecule represents a long chain of monomers called nucleotides. The sequence of nucleotides of an RNA molecule constitutes its primary structure, and the pattern of pairing between nucleotides determines the secondary structure of an RNA. Non-coding RNA genes produce transcripts that exert their function without ever producing proteins. Predicting the secondary structure of non-coding RNAs is very important for understanding their functions. We focus on Nussinov's algorithm as useful techniques for predicting RNA secondary structures. We introduce a new traceback matrix and scoring table to improve above algorithm. And the improved prediction algorithm provides better levels of performance than the originals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• 시스템엔지니어링학술지
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• 제18권1호
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• pp.46-57
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• 2022

In this paper, we proposed the DFMEA Implementation Method for safety design of Weapon System. First, we presented the process for DFMEA. And then, the case analysis of OOO missile was performed in accordance with the process presented. After defining the system requirements of OOO missile, failure definition scoring criteria was set. In order to clarify the definition of failure, the failure was classified into safety, reliability, maintainability and others. After performing the function analysis, the relationship matrix analysis was performed to identify the failure mode according to the function without omission. After clarifying the failure classification, mode of failure, cause of failure and effect were analyzed to calculate the severity, occurrence and detection values. After the action priority was judged, the recommended action according to the failure classification was identified for the determined action priority. The results of this study can be used as a relevant basis for the design reflection and resource re-allocation of stakeholders.

• 융합신호처리학회논문지
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• 제23권3호
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• pp.143-149
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• 2022

This excerpt delineates a quantitative measure of relationship between a research title and its respective abstract extracted from different journal articles documented through a Korean Citation Index (KCI) database published through various journals. In this paper, we propose a machine learning-based similarity metric that does not assume normality on dataset, realizes the imbalanced dataset problem, and zero-variance problem that affects most of the rule-based algorithms. The advantage of using this algorithm is that, it eliminates the limitations experienced by Pearson correlation coefficient (r) and additionally, it solves imbalanced dataset problem. A total of 107 journal articles collected from the database were used to develop a corpus with authors, year of publication, title, and an abstract per each. Based on the experimental results, the proposed algorithm achieved high correlation coefficient values compared to others which are cosine similarity, euclidean, and pearson correlation coefficients by scoring a maximum correlation of 1, whereas others had obtained non-a-number value to some experiments. With these results, we found that an effective title must have high correlation coefficient with the respective abstract.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.635-637
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• 2021

사이버 보안성 평가란 위협 및 취약성 분석을 통해 시스템의 위험 수준을 평가하여 적절한 보안조치를 취하기 위한 과정이다. 최근 증가하고 있는 사이버 공격과 지속적으로 개발되는 지능형 보안 위협에 대비하기 위해 정확한 보안 평가 모델이 필요하다. 따라서 보안 장비와 구간, 취약점마다 가중치를 할당하여 점수화하는 매트릭 기반 보안 평가 모델 분석을 통해 위험도 평가 모델을 제시한다. 사이버 보안성 평가 시 필요한 요소들을 간략화하고 기업 환경에 맞춰 평가가 가능하다. 보안 장비별 평가를 통하여 기업 환경에 더 적합한 평가를 시행하여 추후 사이버 보안 평가 연구에 도움이 될 것으로 기대된다.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.809-817
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• 2008

Program plagiarism is widespread due to intelligent software and the global Internet environment. Consequently the detection of plagiarized source code and software is becoming important especially in academic field. Though numerous studies have been reported for detecting plagiarized pairs of codes, we cannot find any profound work on understanding the underlying mechanisms of plagiarism. In this paper, we study the evolutionary process of source codes regarding that the plagiarism procedure can be considered as evolutionary steps of source codes. The final goal of our paper is to reconstruct a tree depicting the evolution process in the source code. To this end, we extend the well-known bioinformatics approach, a local alignment approach, to detect a region of similar code with an adaptive scoring matrix. The asymmetric code similarity based on the local alignment can be considered as one of the main contribution of this paper. The phylogenetic tree or evolution tree of source codes can be reconstructed using this asymmetric measure. To show the effectiveness and efficiency of the phylogeny construction algorithm, we conducted experiments with more than 100 real source codes which were obtained from East-Asia ICPC(International Collegiate Programming Contest). Our experiments showed that the proposed algorithm is quite successful in reconstructing the evolutionary direction, which enables us to identify plagiarized codes more accurately and reliably. Also, the phylogeny construction algorithm is successfully implemented on top of the plagiarism detection system of an automatic program evaluation system.

• 한국환경보건학회지
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• 제41권2호
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• pp.133-145
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• 2015

Objectives: Food safety has become one of the major public-concerning issues in Korea. In order to set guidelines to create manuals for the response to a food safety crisis by food industry, this paper classified food safety crises and suggested techniques to determine crisis level. Methods: This study clarified common terminologies and definitions including in food safety crises. It reviewed various food safety crises and described characteristics, types, and states of crises. Results: The results of this study suggested that a food safety crisis implied a situation in which hazards/risk spreading in the food supply chain was widely described, causing strong public concern followed by a socioeconomic impact, and therefore, requiring the implementation of a prompt and full response regarding the situation. In terms of seeking response plans, food safety crises might be classified according to the penalties resulting from violations of laws and regulations, causative substances, stages of the food supply chain, and first contact point for incidents. The crisis level for a food safety crisis could be classified according to its severity parameters. The guideline matrix was divided into four major stages: Blue/guarded, Yellow/elevated, Orange/high, and Red/severe. This study also suggested several methods for determining the crisis level, such as the simple judgement method, scoring methods using a check-list and a weighted check-list. Conclusion: The severity of related parameters might be of great importance in understanding a crisis and determining response options/challenges for crisis levels.