• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.264-275
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• 2015

While the method of prioritization has been practicing in the community needs-based programs to improve the effectiveness and efficiency of community health planning, it has not been systematically used. This study aims to suggest more sophisticated method of prioritizing. Based on the analysis of 81 community health plans which adopt prioritizing method, this study tried to examine their methods and criteria and evaluate their adequacy. In the prioritization process, projects themselves, rather than health problems, were commonly adopted for the subject of the analysis. The most used was the Basic priority rating, followed by the Prioritization matrix. Looking at the size of health problem among the prioritization criteria, the prevalence for chronic diseases and the proportion of people with health problems for health behaviors, mainly were used as indicators. Along with the size of health problem, other factors such as the degree of seriousness of health problem, and the effectiveness of intervention have been used as the criteria of prioritizing, not fully supported by objective data base and the clear standard of scoring. In the prioritization, the analysis need to be limited only to health problems, and the scoring criteria for each health problem area be presented.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.34-43
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• 2012

Determining the similarity between two strings can be applied various area such as information retrieval, spell checker and spam filtering. Similarity calculation between Korean strings based on dynamic programming methods firstly requires a definition of the similarity between phonemes. However, existing methods have a limitation that they use manually set similarity scores. In this paper, we propose a method to automatically calculate inter-phoneme similarity from a given set of variant words using a PAM-like probabilistic model. Our proposed method first finds the pairs of similar words from a given word set, and derives derivation rules from text alignment results among the similar word pairs. Then, similarity scores are calculated from the frequencies of variations between different phonemes. As an experimental result, we show an improvement of 10.1%~14.1% and 8.1%~11.8% in terms of sensitivity compared with the simple match-mismatch scoring scheme and the manually set inter-phoneme similarity scheme, respectively, with a specificity of 77.2%~80.4%.

• Journal of Computing Science and Engineering
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• v.8 no.2
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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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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• v.15 no.7
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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.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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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.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.635-637
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• 2021

Cybersecurity assessment is the process of assessing the risk level of a system through threat and vulnerability analysis to take appropriate security measures. Accurate security evaluation models are needed to prepare for the recent increase in cyberattacks and the ever-developing intelligent security threats. Therefore, we present a risk assessment model through a matrix-based security assessment model analysis that scores by assigning weights across security equipment, intervals, and vulnerabilities. The factors necessary for cybersecurity evaluation can be simplified and evaluated according to the corporate environment. It is expected that the evaluation will be more appropriate for the enterprise environment through evaluation by security equipment, which will help the cyber security evaluation research in the future.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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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.

• Journal of Environmental Health Sciences
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• v.41 no.2
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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.