• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1185-1196
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• 2007

To enhance competitiveness of game industry and added value, it needs scientific research and bases that suggest satisfaction standard which quantitatively evaluates satisfaction to develop games which have high satisfaction for demanders. Specially, scoring of satisfaction factors and estimation of population distribution are important task. This allows which a game have high or low satisfaction compared to other games. Also we predict improvable factors and technical aspects to promote satisfaction. For it, in this paper we discuss ways to normalization of score distribution for satisfaction factors and estimate its density function using parametric density estimation by simulation.

• Genomics & Informatics
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• v.2 no.3
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• pp.131-133
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• 2004

MediScore is an information retrieval system, which helps to search for the set of genes associated with a specific disease or the set of diseases associated with a specific gene. Despite recent improvement of natural language processing (NLP) and other text mining approaches to search for disease associated genes, many false positive results come out due to diversity of exceptional cases as well as ambiguities in gene names. In order to overcome the weak points of current text mining approaches, MediScore introduces statistical normalization based on binomial to normal distribution approximation which corrects inaccurate scores caused by common words not representing genes and interactive rescoring by the user to remove the false positive results. Interactive rescoring includes individual alias scoring for each gene to remove false gene synonyms, referring MEDLINE abstracts, and cross referencing between OMIM and other related information.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.208-214
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• 2021

Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

• The Journal of Economics, Marketing and Management
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• v.10 no.3
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• pp.21-36
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• 2022

Purpose: The purpose of this study is to compare and analyze the enterprise's score index calculated from atypical data and corrected data. Research design, data, and methodology: In this study, news articles which are non-financial information but qualitative data were collected from 2,432 SMEs that has been extracted "square proportional stratification" out of 18,910 enterprises with fixed data and compared/analyzed each enterprise's score index through text mining analysis methodology. Result: The analysis showed that qualitative data can be quantitatively evaluated by region, industry and period by collecting news from SMEs, and that there are concerns that it could be an element of alternative credit evaluation. Conclusion: News data cannot be collected even if one of the small businesses is self-employed or small businesses has little or no news coverage. Data normalization or standardization should be considered to overcome the difference in scores due to the amount of reference. Furthermore, since keyword sentiment analysis may have different results depending on the researcher's point of view, it is also necessary to consider deep learning sentiment analysis, which is conducted by sentence.

• Phonetics and Speech Sciences
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• v.12 no.3
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• pp.25-32
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• 2020

An analysis of emotional English utterances with 7 emotions (calm, happy, sad, angry, fearful, disgust, surprised) was conducted using the measurement of prosodic distance between 672 emotional and 48 neutral utterances. Applying the technique proposed in the automatic evaluation model of English pronunciation to the present study on emotional utterances, Euclidean distance measurement of 3 prosodic elements such as F0, intensity and duration extracted from emotional and neutral utterances was utilized. This paper, furthermore, extended the analytical methods to include Euclidean distance normalization, z-score and z-score normalization resulting in 4 groups of measurement schemes (sqrF0, sqrINT, sqrDUR; norsqrF0, norsqrINT, norsqrDUR; sqrzF0, sqrzINT, sqrzDUR; norsqrzF0, norsqrzINT, norsqrzDUR). All of the results from perceptual analysis and acoustical analysis of emotional utteances consistently indicated the greater effectiveness of norsqrF0, norsqrINT and norsqrDUR, among 4 groups of measurement schemes, which normalized the Euclidean measurement. The greatest acoustical change of prosodic information influenced by emotion was shown in the values of F0 followed by duration and intensity in descending order according to the effect size based on the estimation of distance between emotional utterances and neutral counterparts. Tukey Post Hoc test revealed 4 homogeneous subsets (calm

• International Journal of Highway Engineering
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• v.16 no.4
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• pp.35-43
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• 2014

PURPOSES: This study provides a methodology for estimating proper number of equipment for ordinary road management works. METHODS: Utilizing a computerized data of record systems (KAMIS) in 18 regional offices, two evaluation indicators were calculated and then normalized for objective comparison. Applied magnifying factor to the outputs, the proper number of equipment can be estimated. RESULTS: As a result, proper number of equipment by regional offices were required 28% more than current conditions. CONCLUSIONS: Using the proposed a methodology, fundamental data for scientific and reasonable strategies can be stored as well as be used for the future plan for budget allocation.

• The Journal of Korean Medicine
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• v.37 no.2
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• pp.119-124
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• 2016

Objectives: To demonstrate a clinical course and feature of a female patient with a severe liver injury (DILI) during antituberculosis treatment for her intestinal tuberculosis, whom traditional Korean medicine completely recovered. Methods: A female patient with diagnosed as DILI by antituberculosis drugs had been treated with herbal drugs; and then the clinical outcome and biochemical parameters had been monitored. Result: A 45-year old female had taken antituberculosis drugs for about 2 months, and complained severe abdominal discomfort and dyspepsia. The RUCAM score was 10, which met the criteria for DILI (AST 584 IU/L, ALT 1212 IU/L, ALP 100 IU/L, and GGT 161 IU/L, total bilirubin 0.9 mg/dL). She had been treated with herbal drugs and acupuncture as inpatient and outpatient, and then her symptoms had been completely recovered with normalization of hepatic enzymes. Conclusion: This report provides a clinical characteristic for a severe hepatotoxicity induced by antituberculosis drugs, and showed an example of TKM-based application.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.35-45
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• 2013

The aim of study is to present how to estimate and use the FRI (Flood Risk Index) for classifying area zones based on regional flooding risk in terms of the integrated flood risk management. To estimate the FRI at a spatial resolution of city/county/town units for the Nakdong River Watershed, the 17 representative flood indexing factors are carefully selected for the three flood indexes, such as PI (Pressure Index), SI (State Index), and RI (Response Index) under the P-S-R (Pressure-State-Response) classification system. Because flood indexing factors are measured at different scales and units, they are transformed into a common domain by the T-Score normalization technique. The entropy weight coefficient method is also applied to calculate the weight of flood indexing factors in order to reduce subjective judgement on the effect of weight coefficients. The three flood indexes of PI, SI, and RI are integrated for an overall value of the FRI to evaluate the flood risk of districts. To examine the practical application of the proposed FRI, the FRI results with/without the weight coefficients are compared with flooding zones of natural disaster risk areas officially announced in 2010. It is expected that the FRI ensured by full verification can make regional protection plans against flooding disasters with respect to causes and characteristics of past floods.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.3-9
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• 1999

This paper presents the study on the rejection capability based on anti-phone modeling for vocabulary independent speech recognition system. The rejection system detects and rejects out-of-vocabulary words which were not included in candidate words which are defined while the speech recognizer is made. The rejection system can be classified into two categories by their implementation methods, keyword spotting method and utterance verification method. The keyword spotting method uses an extra filler model as a candidate word as well as keyword models. The utterance verification method uses the anti-models for each phoneme for the calculation of confidence score after it has constructed the anti-models for all phonemes. We implemented an utterance verification algorithm which can be used for vocabulary independent speech recognizer. We also compared three kinds of means for the calculation of confidence score, and found out that the geometric mean had shown the best result. For the normalization of confidence score, usually Sigmoid function is used. On using it, we compared the effect of the weight constant for Sigmoid function and determined the optimal value. And we compared the effects of the size of cohort set, the results showed that the larger set gave the better results. And finally we found out optimal confidence score threshold value. In case of using the threshold value, the overall recognition rate including rejection errors was about 76%. This results are going to be adapted for stock information system based on speech recognizer which is currently provided as an experimental service by Korea Telecom.

• Investigative Magnetic Resonance Imaging
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• v.19 no.3
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• pp.168-177
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• 2015

Purpose: Brain surface intensity model (BSIM)-based cortical thickness analysis does not require complicated 3D segmentation of brain gray/white matters. Instead, this technique uses the local intensity profile to compute cortical thickness. The aim of the present study was to evaluate intra-rater and inter-rater reliability of BSIM-based cortical thickness analysis using images from elderly participants. Materials and Methods: Fifteen healthy elderly participants (ages, 55-84 years) were included in this study. High-resolution 3D T1-spoiled gradient recalled-echo (SPGR) images were obtained using 3T MRI. BSIM-based processing steps included an inhomogeneity correction, intensity normalization, skull stripping, atlas registration, extraction of intensity profiles, and calculation of cortical thickness. Processing steps were automatic, with the exception of semiautomatic skull stripping. Individual cortical thicknesses were compared to a database indicating mean cortical thickness of healthy adults, in order to produce Z-score thinning maps. Intra-class correlation coefficients (ICCs) were calculated in order to evaluate inter-rater and intra-rater reliabilities. Results: ICCs for intra-rater reliability were excellent, ranging from 0.751-0.940 in brain regions except the right occipital, left anterior cingulate, and left and right cerebellum (ICCs = 0.65-0.741). Although ICCs for inter-rater reliability were fair to excellent in most regions, poor inter-rater correlations were observed for the cingulate and occipital regions. Processing time, including manual skull stripping, was $17.07{\pm}3.43min$. Z-score maps for all participants indicated that cortical thicknesses were not significantly different from those in the comparison databases of healthy adults. Conclusion: BSIM-based cortical thickness measurements provide acceptable intra-rater and inter-rater reliability. We therefore suggest BSIM-based cortical thickness analysis as an adjunct clinical tool to detect cortical atrophy.