• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.39-47
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• 2017

Nowadays, there have been an increasing number of illegal use cases where people try to fabricate the working hours by using fake fingerprints. So, the fingerprint liveness detection techniques have been actively studied and widely demanded in various applications. This paper proposes a new method to detect fake fingerprints using CNN (Convolutional Neural Ntworks) based on the patches of fingerprint images. Fingerprint image is divided into small square sized patches and each patch is classified as live, fake, or background by the CNN. Finally, the fingerprint image is classified into either live or fake based on the voting result between the numbers of fake and live patches. The proposed method does not need preprocessing steps such as segmentation because it includes the background class in the patch classification. This method shows promising results of 3.06% average classification errors on LivDet2011, LivDet2013 and LivDet2015 dataset.

• Korean journal of communication and information
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• v.17
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• pp.37-60
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• 2001

This study attempted to demonstrate the interaction effects between attitudinal frames of nine daily newspapers and community structure in the 1994s Michigan gubernatorial election. It was theoretically guided by framing research and the self-presentation theory of social-cognition perspective and empirically tested with archival data. For the purpose of this study, content analysis of nine statewide daily newspapers was employed in order to provide data on news framing. Data on voting rates for John Engler, winner of the 1994 Michigan Gubernatorial election, in each county of Michigan were used for vote choice while Michigan census data were used for constructing an Index of community structural differentiation. The results indicated that majority compliance frames were slightly more related with vote choice in homogeneous com-unities rather than were majority compliance frames in heterogeneous communities while social identification frames tended to have an influence on vote choice in heterogeneous communities more than did social identification frames in homogeneous communities.

• Survey Research
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• v.8 no.1
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• pp.55-79
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• 2007

This article attempts to provide an overview of the exit polls for the 2006 local elections in Korea. The sampling method, sampling error, non-response rate, and prediction error of the exit polls are reviewed. Also, we explore the fact that the propensity to vote varies according to age and gender of voters. In terms of age and gender, the representativeness of the sample is investigated by comparing to the data released by the National Election Commission. Through this empirical research, we show that the exit poll samples are unbalanced in terms of age and this unbalance may be one of the causes of bias occurred in the prediction of the 2006 local election results. The design effects of the sample design implemented for the exit polls are also examined.

• Journal of the Korean Society of Costume
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• v.64 no.4
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• pp.21-36
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• 2014

The purpose of this study is to suggest an effective fashion design process using social network services(SNS) as a method to develop designs. Fashion design process was systemized through literature study. The characteristics of social network, and element and method of network formation were investigated, and then design processes using SNS were suggested through survey study. This was done by applying formation of network and its method in SNS with contents of fashion to stage of process to develop fashion design. The study results are as follows. First, Fashion design process using SNS is composed of 5 stages. Second, SNS types with contents of fashion were classified to five types: blog, community, connection of fashion web service and SNS, fashion SNS, and fashion SNS game. Among them, types where development of fashion design and product distribution was done by formation of network are connected type of fashion web service and SNS, fashion SNS type. Fashion design development can be done by compiling, having contests, and cooperative work. A method that can be used for making assessments and decision is voting and predicting the market. Third, Fashion design process using SNS is composed of the stages such as planning, compiling, analysis, decision, implementation, and formation of network. It was analyzed that by connecting stages of collection and evaluation of information through participation of users, new contents were produced and there was a structure that was cycled continuously.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.319-324
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• 2005

An integrated approach for prostate cancer detection using proteomic data is presented. Due to the high-dimensional feature of proteomic data, the discrete wavelet transform (DWT) is used in the first-stage for data reduction as well as noise removal. After the process of DWT, the dimensionality is reduced from 43,556 to 1,599. Thus, each sample of proteomic data can be represented by 1599 wavelet coefficients. In the second stage, a voting method is used to select a common set of wavelet coefficients for all samples together. This produces a 987-dimension subspace of wavelet coefficients. In the third stage, the Autoassociator algorithm reduces the dimensionality from 987 to 400. Finally, the artificial neural network (ANN) is applied on the 400-dimension space for prostate cancer detection. The integrated approach is examined on 9 categories of 2-class experiments, and also 3- and 4-class experiments. All of the experiments were run 10 times of ten-fold cross-validation (i. e. 10 partitions with 100 runs). For 9 categories of 2-class experiments, the average testing accuracies are between 81% and 96%, and the average testing accuracies of 3- and 4-way classifications are 85% and 84%, respectively. The integrated approach achieves exciting results for the early detection and diagnosis of prostate cancer.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.1-8
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• 2011

In modern society, the amount of information has been significantly increased according to the development of Internet and IT convergence technology and that leads to develop information obtaining and searching technologies from lots of data. Although the system integration for medicare has been largely established and that accumulates large amounts of information, there is a lack of providing and supporting information for nursing activities using such established database. In particular, the judgement for the intervention of pains depends on the experience of individual nurses and that leads to make subjective decisions in usual. In this paper, a pain nursing supporting method that uses the existing medical data and performs collaborative filtering is proposed. The proposed collaborative filtering is a method that extracts some items, which represent a high relativeness level, based on similar preferences. A preference estimation method using a user based collaborative filtering method calculates user similarities through Pearson correlation coefficients in which a neighbor selection method is used based on the user preference.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.915-925
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• 1996

In this paper, in order to find effective features which can handle variations in off-line handwritten numerals, we performed a comparative study on various sets of features. Results of experimental performance comparison shows that 4- directional features using contours and features which combined cross distance, cross, mesh and projection features are very effective for off-line handwritten numerals recognition in terms of recognition rates and recognition time. And in order to surmount limitation of recognition rate by a single neural network. we proposed a modularized neural network using majority voting and reliability factor with complex feature that mix effective features together. In order to verify the performance of the proposed method, the handwritten numeral databases of Concordia University of Canada and Dong-A University of Korea are used in the experiments. With the database of Concordia University, the recognition rate of 97.1%, the rejection rate of 1.5%, the error rate of 1.4% and the reliability of 98.5% are obtained ; and with the database of Dong-A University, there cognition rate of 98%, the rejection rate of 1.2%, the error rate of 0.8%, the reliability o99.1% are obtained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.4
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• pp.559-573
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• 1998

Recently Standards Developments Organizations (SDO$\_S$) in the field of Information and Communication recognize that "More new and more complex standards should be developed in shorter time". To cope with this challenge they try to construct Standards Information Cooperation Network (SICN) or Electronic Document Handling (EDH) systems for efficient standards development process. This paper presents the design and implementation of an Extranet based Web system dedicated to effective on-line standards making environments. The system, which is called SICN (Standards Information Cooperation Network), is a workflow-based network application created with a view to fostering faster standards development with functionalities such as an electronic signature mechanism, electronic voting, comment gathering and dynamic links for ready retrieval of standards information stored in a database. This paper also describes the concept of a VSDO (Virtual Standards Development Organization) that supports all the features needed by the relevant standards making bodies to carry out their activities in dynamic on-line environments.ironments.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.34-43
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• 2000

Replicated data that is used for fault tolerant distributed system requires replica control protocol to maintain data consistency. The one of replica control protocols is quorum consensus method which accesses replicated data by getting majority approval. If site failure or communication link failure occurs and any one can't get quorum consensus, it degrades the availability of data managed by quorum consensus protocol. So it needs for ghost to replace the failed site. Because ghost is not full replica but process which has state information using meta data, it is important to simplify meta data. In order to maintain availability and simplify meta data, we propose a method to use cohort set as ghost's meta data. The proposed method makes it possible to organize meta data in 2N+logN bits and to have higher availability than quorum consensus only with cohort set and dynamic linear voting protocol. Using Markov model we calculate proposed method's availability to analyze availability and compare it with existing protocols.