• Journal of Biomedical Engineering Research
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• v.26 no.3
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• pp.171-176
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• 2005

This paper proposes an automatic liver segmentation method using improved partial histogram threshold (PHT) algorithms. This method removes neighboring abdominal organs regardless of random pixel variation of contrast enhanced CT images. Adaptive multi-modal threshold is first performed to extract a region of interest (ROI). A left PHT (LPHT) algorithm is processed to remove the pancreas, spleen, and left kidney. Then a right PHT (RPHT) algorithm is performed for eliminating the right kidney from the ROI. Finally, binary morphological filtering is processed for removing of unnecessary objects and smoothing of the ROI boundary. Ten CT slices of six patients (60 slices) were selected to evaluate the proposed method. As evaluation measures, an average normalized area and area error rate were used. From the experimental results, the proposed automatic liver segmentation method has strong similarity performance as the MSM by medical Doctor.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.4
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• pp.178-198
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• 2003

Mutual information as an association measure, has been used for various purposes as well as for calculating term similarity. There we, however, some limits in mutual information. It tends to emphasize low frequency terms extremely because the marginal value of mutual information changes inversely to frequency of terms. To compensate for this limit this study suggests relative mutual information(RMI) coefficients which normalize mutual information, and examines their characteristics in some details. The RMI coefficients also improve effectiveness of global query expansion when they are adapted to three different collections.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.430-460
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• 2004

This study presented a personalization system that adopted a methodology which is applicable for digital content recommendation and executed by the Internet service providers. The system made a recommendation to the users on the basis of their preferences, while most techniques for recommending digital content have focused on considering the similarity of content. In addition, it developed a method of evaluation to determine the priority of recommendations and adopted measures when selecting a set of recommendations. To experiment the feasibility and effectiveness of the presented methodology, a prototype system was developed and was applied to an English newspaper on the Internet.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.2
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• pp.139-155
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• 2003

The aim of this study is to identify the data traffic capacity of 3G mobile communication networks, especially of cdma2000-1X networks. Three-layered ON/OFF traffic model is used to describe the dynamics of data traffics and the process of data transmission such as packet scheduling. We construct a simulator fully incorporating packet handling process of cdma2000-lX data network as well as three-layered ON/OFF traffic model describing the behavior of source data traffics. To get influence of traffic parameters on performance measures, the extensive simulations were performed for several data sets which are obtained from real trace data or previous studies. The experimental results show that the engineered throughput satisfying QoS criteria is approximately 25% of total capacity. Finally, some proposals to improve the system capacity are followed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.31-36
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• 2010

Many clustering algorithms have been used in diverse fields. When we need to group given data set into clusters, many clustering algorithms based on similarity or distance measures are considered. Most clustering works have been based on hierarchical and non-hierarchical clustering algorithms. Generally, for the clustering works, researchers have used clustering algorithms case by case from these algorithms. Also they have to determine proper clustering methods subjectively by their prior knowledge. In this paper, to solve the subjective problem of clustering we make empirical comparisons of popular clustering algorithms which are hierarchical and non hierarchical techniques using Silhouette measure. We use silhouette information to evaluate the clustering results such as the number of clusters and cluster variance. We verify our comparison study by experimental results using data sets from UCI machine learning repository. Therefore we are able to use efficient and objective clustering algorithms.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.177-191
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• 2013

Social network has been expected to increase the value of social capital through online user interactions which remove geographical boundary. However, online users in social networks face challenges of assessing whether the anonymous user and his/her providing information are reliable or not because of limited experiences with a small number of users. Therefore. it is vital to provide a successful trust model which builds and maintains a web of trust. This study aims to propose a prediction method for the interpersonal trust which measures the level of trust about information provider in Facebook. To develop the prediction method. we first investigated behavioral research for trust in social science and extracted 5 antecedents of trust : lenience, ability, steadiness, intimacy, and similarity. Then we measured the antecedents from the history of interactive behavior and built prediction models using the two decision trees and a computational model. We also applied the proposed method to predict interpersonal trust between Facebook users and evaluated the prediction accuracy. The predicted trust metric has dynamic feature which can be adjusted over time according to the interaction between two users.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.474-477
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• 1999

In this paper, a new method of measuring of distance between digital images, the 2D Integra-Normalizer, is proposed and compared with the grey block distance (GBD) to show its superiority of images. The 2D Integra-Normalizer removes a restriction that the image to be compared is {{{{ { 2}^{n } }}}} dimension where n is a positive integer, which means that any dimensional image can be applied to the 2D Integra-Normalizer for measuring distance of images. In addition, the 2D Integra-Normalizer measures the distance of images more in detail than the GBD with a better interpretation that is more close to human's intuitive understanding.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.526-528
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• 2003

공기빈도를 이용한 전역적 질의확장 검색에서 공기유사도를 판정하는데 이용되는 유사계수의 특성에 따른 질의확장 성능을 비교해보았다. 먼저 각 유사계수의 통계적인 특성을 말뭉치와 검색실험 문서집단을 대상으로 살펴본 결과 코사인 계수, 자카드 계수는 고빈도어 선호경향을 보이고 상호정보량과 율의 Y는 저빈도어 선호경향을 보이는 것으로 나타났다. 질의확장 검색실험에서는 고빈도어 선호경향을 가진 유사계수에 비해서 저빈도어 선호경향을 가진 유사계수률 이용할 때 더 종은 성능이 나타났다. 특히 율의 Y는 질의어의 DF가 1에 가깝게 매우 낮을 때 다른 유사계수와 달리 고빈도어를 선호함으로써 항상 저빈도어를 선호하는 상호정보량에 비해서 질의확장 검색에 유리함을 알 수가 있었다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.253-260
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• 2001

Understanding and adapting to changes of customer behavior is an important aspect for a company to survive in continuously changing environment. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different time snapshots. For this purpose, we first define three types of changes as emerging pattern, unexpected change and the added / perished rule. Then we develop similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is evaluated to detect significantly changed rules. Our proposed methodology can evaluate degree of changes as well as detect all kinds of change automatically from different time snapshot data. A case study for evaluation and practical business implications for this methodology are also provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4160-4176
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• 2015

Data compression like image and video compression has come a long way since the introduction of Compressive Sensing (CS) which compresses sparse signals such as images, videos etc. to very few samples i.e. M < N measurements. At the receiver end, a robust and efficient recovery algorithm estimates the original image or video. Many prominent algorithms solve least squares problem (LSP) iteratively in order to reconstruct the signal hence consuming more processing time. In this paper non-iterative threshold based recovery algorithm (NITRA) is proposed for the recovery of images and videos without solving LSP, claiming reduced complexity and better reconstruction quality. The elapsed time for images and videos using NITRA is in ㎲ range which is 100 times less than other existing algorithms. The peak signal to noise ratio (PSNR) is above 30 dB, structural similarity (SSIM) and structural content (SC) are of 99%.