• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.523-531
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• 2016

This paper studies the empirical relationship between various privacy protection measures and personal information invasion experience of firms and individuals using rich and heterogeneous survey data. By analyzing PSM models. we get the following results: first, the treatment group which have more technical measures and/or IS investment tends to experience more privacy invasion than the control group which have less of them. second, the reverse causality, that is firms and individuals with more experience of privacy invasion tends to take more measure for personal information protection, is found to exist. From these result, we discuss proper privacy policies implications in respects of attackers benefits and individual irrationality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2609-2618
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• 2011

Under the knowledge-based economy in 21C, the convergence and complexity in science and technology are being more active. Interoperability between heterogeneous domains is a very important point considered in the field of scholarly information service as well information standardization. Thus we suggest the systematic solution method to flexibly extend classification scheme in order for content management and service organizations. Especially, This paper shows that automatic method for interoperability between heterogeneous scholarly classification code structures will be effective in enhancing the information service system.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.111-131
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• 2004

Software change is an essential operation for software evolution. To maintain the system competently, managers as well as developers must be able to understand the structure of the system but the structure of software is hidden to the developers and managers who need to change it. In this paper, we present a system (OntCIA) for supporting change impact analysis for rating and billing domain based on the semantic web technology. The basic idea of OntCIA is to build a domain knowledge base using an OWL ontology and RDF to implement change impact analysis system that would support the managers and software developers in finding out information about structure of large software system. OntCIA allows users to incrementally build an ontology in rating and billing domain and provides useful information in response to user queries concerning the code, such as, for example 'Find the modules which have a role for confirming new subscription'. The strengths of OntCIA are its architecture for easy maintenance as well as semantic indexing by automatic reasoning.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.711-716
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• 2014

With the gradual increase of interest in plagiarism and intelligent file content search, the demand for similarity measuring between two sentences is increasing. There is a lot of researches for sentence similarity measurement methods in various directions such as n-gram, edit-distance and LSA. However, these methods have their own advantages and disadvantages. In this paper, we propose a new sentence similarity measurement method approaching from another direction. The proposed method uses the set-based POI data search that improves search performance compared to the existing hard matching method when data includes the inverse, omission, insertion and revision of characters. Using this method, we are able to measure the similarity between two sentences more accurately and more quickly. We modified the data loading and text search algorithm of the set-based POI data search. We also added a word operation algorithm and a similarity measure between two sentences expressed as a percentage. From the experimental results, we observe that our sentence similarity measurement method shows better performance than n-gram and the set-based POI data search.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.453-462
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• 2018

This study was conducted to investigate whether the parental sodium intake and the sodium intake of adolescents are consistent with each other, to identify factors affecting sodium intake of adolescent children, and to measure sodium intake at home. For this study, 405 subjects in the National Health and Nutrition Survey of 2015 whose sodium intake was measured among nutritional intake were selected, excluding elementary school students, middle school students and high school students aged 7 to 18 years. The data were then matched with the father ID and the mother ID in the youth ID. The results of this study were as follows: ${\beta}=-0.187$ for male adolescents, ${\beta}=0.192$ for older adolescents, ${\beta}=0.153$ for higher adolescents, and sodium intake for adolescents. This is because the mother usually prepares meals in Korea. On the other hand, it is predicted that parents will not be able to consider the quality of their children due to the increased number of dual-income couples.

• Journal of KIISE
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• v.44 no.8
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• pp.760-766
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• 2017

Repetitive strings have been studied in diverse fields such as data compression, bioinformatics and so on. Recently, two problems of approximate periods of strings over integer alphabets were introduced, finding minimum ${\delta}-approximate$ periods and finding minimum ${\gamma}-approximate$ periods. Both problems can be solved in $O(n^2)$ time when n is the length of the string. In this paper, we present two parallel algorithms for solving the above two problems in O(n) time using $O(n^2)$ threads, respectively. The experimental results show that our parallel algorithms for finding minimum ${\delta}-approximate$ (resp. ${\gamma}-approximate$) periods run approximately 19.7 (resp. 40.08) times faster than the sequential algorithms when n = 10,000.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.548-558
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• 2007

This paper presents a method of location sensing of mobile objects using RF devices. By analyzing signal strengths between a certain number of fixed RF devices and a moving RF device, we can recognize the location of a moving object in real time. Firstly, signal strength values between RF devices are gathered, and then the values are normalized and constructed as a model feature vector for specific location. A number of model patterns are acquired and registered for all of the location which we want to recognize. For location sensing, signal strength information for an arbitrary moving RF device is acquired and compared with model feature vectors registered previously. In this case, distance value is calculated and the moving RF device is classified as one of the known model patterns. Experimental results show that our methods have performed the location sensing successfully with 100% rate of recognition when the number of fixed RF devices is 10 or more than 12. In terms of cost and applicability, experimental results seem to be very encouraging.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1398-1406
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• 2007

Providing natural and efficient access to the fast growing multimedia information is a critical aspect for content-based information system. Query by humming system allows the user to find a song by humming part of the tune form music database. Conventional music information retrieval systems use a high precision pitch extraction method. However, it is very difficult to extract true pitch perfectly. So, In this paper, we propose to use YIN parameter with applying the reliability to reduce the pitch extraction errors. And we describes developed music information retrieval method based on a query by humming system which uses reliable feature extraction. Developed system is based on a continuous dynamic programming algorithm with features including pitch, duration and energy along with their confidence measures. The experiment showed that the proposed method could reduce the errors of the top-10 7.2% and the top-1 9.1% compared with the cepsturm based multiple pitch candidate. The overall retrieval system achieved 92.8% correct retrieval in the top-10 rank list on a database of 155 songs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.203-207
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• 1999

In this paper we propose the automated generation algorithm of penetration scenario using association mining technique. Until now known intrusion detections are classified into anomaly detection and misuse detection. The former uses statistical method, features selection, neural network method in order to decide intrusion, the latter uses conditional probability, expert system, state transition analysis, pattern matching for deciding intrusion. In proposed many intrusion detection algorithms unknown penetrations are created and updated by security experts. Our algorithm automatically generates penetration scenarios applying association mining technique to state transition technique. Association mining technique discovers efficient and useful unknown information in existing data. In this paper the algorithm we propose can automatically generate penetration scenarios to have been produced by security experts and is easy to cope with intrusions when it is compared to existing intrusion algorithms. Also It has advantage that maintenance cost is not high.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.348-355
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• 2011

In this paper, we propose an automatic prostate segmentation method from dynamic magnetic resonance (MR) images. Our method detects contrast-enhanced images among the dynamic MR images using an average intensity analysis. Then, the candidate regions of prostate are detected by the B-spline non-rigid registration and subtraction between the pre-contrast and contrast-enhanced MR images. Finally, the prostate is segmented by performing a dilation operation outward, and sequential shape propagation inward. Our method was validated by ten data sets and the results were compared with the manually segmented results. The average volumetric overlap error was 6.8%, and average absolute volumetric measurement error was 2.5%. Our method could be used for the computer-aided prostate diagnosis, which requires an accurate prostate segmentation.