• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.231-250
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• 2014

Due to the recent development of Information and Communication Technologies (ICT), the amount of research publications has increased exponentially. In response to this rapid growth, the demand of automated text processing methods has risen to deal with massive amount of text data. Biomedical text mining discovering hidden biological meanings and treatments from biomedical literatures becomes a pivotal methodology and it helps medical disciplines reduce the time and cost. Many researchers have conducted literature-based discovery studies to generate new hypotheses. However, existing approaches either require intensive manual process of during the procedures or a semi-automatic procedure to find and select biomedical entities. In addition, they had limitations of showing one dimension that is, the cause-and-effect relationship between two concepts. Thus;this study proposed a novel approach to discover various relationships among source and target concepts and their intermediate concepts by expanding intermediate concepts to multi-levels. This study provided distinct perspectives for literature-based discovery by not only discovering the meaningful relationship among concepts in biomedical literature through graph-based path interference but also being able to generate feasible new hypotheses.

• Science of Emotion and Sensibility
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• v.8 no.4
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• pp.385-391
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• 2005

A frictional coefficients of in-vivo skin characteristic is the most important factor of the cutaneous mechanical properties ant the method of evaluating skin care in the fields of cosmetics products. In-vivo skin characteristic varies in many different ways depends on what is applied to the skin, loading condition, shape, surface roughness, and material of the probe. In this research, we designed a system which can be measured frictional coefficients of a human skin on real time. It consists of multi-components load-cell, actuator, linear motor and arm fixator. This measurement system was automatically controlled by computer. We measured frictional coefficients between probe an4 skin using this system ant inquired adjectives for subjective evaluation while rubbing cosmetic product on skin. Lastly, we analyzed correlation between two factors by calculating Pearson Correlation Coefficient. As a result, we could know that frictional coefficients varied from 0.17-1.2 according to cosmetic products, normal forte, materials and surface conditions of probe. We also confirmed sensual feelings of cosmetic products have close correlation with frictional coefficients.

• Journal of Radiation Protection and Research
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• v.31 no.3
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• pp.135-140
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• 2006

Intakes of radionuclides through both inhalation and ingestion pathways may occur particularly in an incident involving unsealed radionuclides. If one assume only one intake path in this case, which is usual in routine monitoring, a significant error in the evaluated committed effective dose($E_{50}$) may result. In order to demonstrate the potential errors, variations of the resulting committed effective doses were analyzed for different fractions of the inhaled activities to the total intake of $^{241}Am$. Simulated bioassav measurements for the lungs, urine and feces were generated based on the biokinetic model and data of the radionuclide, 5 ${\mu}m$ AMAD and absorption type M for inhalation, for various inhalation fractions. The potential errors in $E_{50}$ due to the assumption of one intake path were in the range from -100% to as large as +34,000% when the bioassays were made 3 days after the intakes. Larger errors are expected when only the feces assay is applied while inhalation intake exists. A strategy which employs two types of bioassay was proposed to reduce the error caused by a misjudgement of the intake path.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.492-503
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• 2008

With the recent development and increasing importance of personal identification systems, biometric technologies with less risk of loss or unauthorized use are being popularized rapidly. In particular, because of their high identification rate and convenience, fingerprint identification systems are being used much more commonly than other biometric systems such as iris recognition, face recognition and vein pattern recognition. However, a fingerprint identification system has the problem that artificially forged finger-prints can be used as input data. Thus, in order to solve this problem, the present study proposed a method for detecting forged fingerprints by measuring the degree of attenuation when the light from an optical fingerprint sensor passes through the finger and analyzing changes in the transmission of light over stages at fixed intervals. In order to prove improvement in the performance of the proposed system, we conducted an experiment that compared the system with an existing multi-sensor recognition system that measures also the temperature of fingerprint. According to the results of the experiment, the proposed system improved the forged fingerprint detection rate by around 32.6% and this suggests the possibility of solving the security problem in fingerprint identification systems.

• Journal of Food Hygiene and Safety
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• v.38 no.5
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• pp.338-346
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• 2023

The demand for probiotic products has been steadily increasing, and Lactobacillus strains are widely used and are currently the most popular probiotics. Optimizing culture conditions for Lactobacillus production for use as probiotics will enhance their profitability by reducing production costs and time. Statistical analysis using response surface methodology revealed the following optimal sets of independent variables: 22.55 h (cultivation time), 25℃ (cultivation temperature), and 3.41% (w/w, prebiotics concentration) for Lactobacillus acidophilus; 24 h, 30.86℃, and 2% (w/w) for Lactiplantibacillus plantarum; 66.67 h, 35℃, and 3.41% (w/w) for Lacticaseibacillus rhamnosus. Actual outcomes using predicted optimal conditions for Lactobacillus strains have been confirmed to closely match predicted results. This study will provide valuable guidelines for high yield Lactobacillus production.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.89-99
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• 2015

The World Economic Forum and the Korean Ministry of Knowledge Economy have selected big data as one of the top 10 in core information technology. The key of big data is to analyze effectively the properties that do have data. Clustering analysis method of big data techniques is a method of assigning a set of objects into the clusters so that the objects in the same cluster are more similar to each other clusters. Similarity measures being used in the cluster analysis may be classified into various types depending on the nature of the data. In this paper, we studied upper and lower bounds for binary similarity measures with negative matches such as Russel and Rao measure, simple matching measure by Sokal and Michener, Rogers and Tanimoto measure, Sokal and Sneath measure, Hamann measure, and Baroni-Urbani and Buser mesures I, II. And the comparative studies with these measures were shown by real data and simulated experiment.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.289-305
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• 2011

To efficiently analyze complex and voluminous data, OLAP systems increasingly provide functionalities for visual exploration of the data allowing end-users to navigate the desired view of the data cube. This paper only deals with data cubes whose schemas represented like the exclusive symmetric hierarchy which is not addressed by current OLAP implementations. This paper presents a conceptual classification of abstraction hierarchies, and an approach to navigating data cubes with a hierarchical visualization technique. The hierarchical visualization technique is developed by using the transitive closure of a binary relation. The approach is exemplified using a real-world study from the domain of national license administration.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.135-142
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• 2006

The flow-density relations represent equilibrium relations between flow and density in the stationary state. Using individual vehicle data this paper proposed a method to 131ter traffic data in the stationary state and showed flow-density relations produced by the traffic data in the stationary state. The Proposed method is based on the idea that free flow and congested flow show totally different traffic behaviors and time series of the traffic data observed at detection stations. The traffic data collected from the stationary state in the free flow using this filtering method consist in the left branch of the flow-density relation and the traffic data collected from the stationary state in the congested flow consist in the right branch of the flow-density relation. The traffic data in the stationary state skew reproducible flow-density relation in the almost whole range of the traffic flow.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.24-29
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• 2019

AIS is one of the most critical systems in any organization. Data quality plays a critical role in a knowledge-based economy. The objective of this study is to identify the most important factors for accounting information quality and their impact on AIS data quality outcomes. This study includes an extensive literature review to identify a set of CSF for data quality. The study uses empirical data to test the research hypothesis and resluts show that the top three most important factors that affect AIS's data quality are toop management commitmentm the nature of the AIS and input controls. The study further uses regression analysis to test the effect of those factors on AIS data quality, finding that there is a significant positive relationship between the perceived performance of the three factors and AIS data quality putcomes. To be develop to AIS data quality further study for CSF's control methodology is necessary.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.289-307
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• 2016

Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.