• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.9-15
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• 2013

In this study, texture feature analysis (TFA) algorithm to automatic recognition of liver disease suggests by utilizing computed tomography (CT), by applying the algorithm computer-aided diagnosis (CAD) of hepatocellular carcinoma (HCC) design. Proposed the performance of each algorithm was to comparison and evaluation. In the HCC image, set up region of analysis (ROA, window size was $40{\times}40$ pixels) and by calculating the figures for TFA algorithm of the six parameters (average gray level, average contrast, measure of smoothness, skewness, measure of uniformity, entropy) HCC recognition rate were calculated. As a result, TFA was found to be significant as a measure of HCC recognition rate. Measure of uniformity was the most recognition. Average contrast, measure of smoothness, and skewness were relatively high, and average gray level, entropy showed a relatively low recognition rate of the parameters. In this regard, showed high recognition algorithms (a maximum of 97.14%, a minimum of 82.86%) use the determining HCC imaging lesions and assist early diagnosis of clinic. If this use to therapy, the diagnostic efficiency of clinical early diagnosis better than before. Later, after add the effective and quantitative analysis, criteria research for generalized of disease recognition is needed to be considered.

• Journal of Biomedical Engineering Research
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• v.43 no.1
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• pp.52-60
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• 2022

Purpose: For now, cognitive load is assessed based on survey-based methods, which can be difficult to track the amount of cognitive load in real-time. In this study, we investigated the difference in electrophysiological activation due to different levels of cognitive load not only at sensor-level but also at source-level using electroencephalogram that might be potentially used for quantitative cognitive load evaluation. Materials and Methods: In this study, ten healthy subjects (mean age 24.3 ± 2.1, three female) participated the experiment. All participants performed 4 sessions of n-back task in different difficulties: 0-, 1-, 2-, and 3-back during electroencephalogram recording. For sensor-level analysis, we calculated the event-related potential and event-related spectral perturbation while low resolution brain electromagnetic tomography (LORETA) to estimate the source activation. Each result was compared between different workload conditions using statistical analysis. Results: Statistical results revealed that the accuracy of the task performance was significantly different between different cognitive loads (p = 0.018). The post-hoc analysis confirmed that the accuracy of the 3-back task was significantly decreased compared to 1-back condition (p = 0.018), but not with 2-back condition (p = 0.180). ERP results showed that P300 target amplitude between 1-back and 3-back had a marginal difference in Cz (p = 0.059) and Pz(p = 0.093). A significant inhibition in Cz high-beta activation (p = 0.017) and decrease in source activation of right parahippocampal gyrus was found in 3-back condition compared to 1-back condition (p < 0.05). Conclusion: In this study, we compared the sensor- and source-level differences in electroencephalogram between different levels of cognitive load, that were found to be in line with the previous reports related to cognitive load evaluation. We expect that the outcome of the current study can be used as a feature to establish a quantitative cognitive load assessment system.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1653-1662
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• 2018

Inspired by the increasing popularity of cosmetic-related mobile application as a tool for instant beautification, the present study examined colors of virtual makeup templates and makeup looks. A survey study was performed by thirty-six respondents to determine the top three desirable virtual makeup templates among nineteen templates. The templates of 'Bella', 'Hilary' and 'Cara' were then analyzed by makeup specialists and color experts for the evaluation of their makeup design and colors. Each color feature of three makeup templates were also evaluated through statistical analysis of ANOVA on the measure of $L^*a^*b^*$ crossed with five types of face elements on three types of virtual makeup images. Overall results indicate that Korean female users in their 20s and 30s preferred a similar makeup concept appeared in makeup template and key worlds. They also preferred a pale skin tone with higher lightness and a slightly higher saturated lip color as an emphasis than other features.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.235-245
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• 2012

Logistic discrimination is an useful statistical technique for quantitative analysis of financial service industry. Especially it is not only easy to be implemented, but also has good classification rate. Generalized additive model is useful for credit scoring since it has the same advantages of logistic discrimination as well as accounting ability for the nonlinear effects of the explanatory variables. It may, however, need too many additive terms in the model when the number of explanatory variables is very large and there may exist dependencies among the variables. Mixtures of factor analyzers can be used for dimension reduction of high-dimensional feature. This study proposes to use the low-dimensional factor scores of mixtures of factor analyzers as the new features in the generalized additive model. Its application is demonstrated in the classification of some real credit scoring data. The comparison of correct classification rates of competing techniques shows the superiority of the generalized additive model using factor scores.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.60-74
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• 2007

For quantitative analysis of spatio-temporal distribution pattern on marine environment, spatial autocorrelation statistics on the both global and local aspects was applied to the observed data obtained from Gwangyang Bay in South Sea of Korea. Global indexes such as Moran's I and General G were used for understanding environmental distribution pattern in the whole study area. LISAs (local indicators of spatial association) such as Moran's I ($I_i$) and $G_i{^*}$ were considered to find similarity between a target feature and its neighborhood features and to detect hot spot and/or cold spot. Additionally, the significance test on clustered patterns by Z-scores was carried out. Statistical results showed variations of spatial patterns quantitatively in the whole year. Then all of general water quality, nutrients, chlorophyll-a and phytoplankton had strong clustered pattern in summer. When global indexes showed strong clustered pattern, the front region with a negative $I_i$ which means a strong spatial variation was observed. Also, when global indexes showed random pattern, hot spot and/or cold spot were/was found in the small local region with a local index $G_i{^*}$. Therefore, global indexes were useful for observing the strength and time series variations of clustered patterns in the whole study area, and local indexes were useful for tracing the location of hot spot and/or cold spot. Quantification of both spatial distribution pattern and clustering characteristics may play an important role to understand marine environment in depth and to find the reasons for spatial pattern.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.392-397
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• 2015

Society has been developed through analogue, digital, and smart era. Every technology is going through consistent changes and rapid developments. In this competitive society, R&D strategy establishment is significantly useful and helpful for improving technology competitiveness. A patent document includes technical and legal rights information such as title, abstract, description, claim, and patent classification code. From the patent document, a lot of people can understand and collect legal and technical information. This unique feature of patent can be quantitatively applied for technology analysis. This research paper proposes a methodology for extracting core technology and patents based on quantitative methods. Statistical analysis and social network analysis are applied to IPC codes in order to extract core technologies with active R&D and high centralities. Then, core patents are also extracted by analyzing citation and family information.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.1
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• pp.44-48
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• 2008

Purpose: In FDG-PET/CT of breast cancer, a sensitivity was 80~96% and a specificity was 75~95% commonly. It was valuable to identify a cancer in early stage been difficult in Mammography. Most of the PET/CT scans have been examined on supine position, so, the image of breast has been acquired by reconstructed whole body scan image. However, using prone position with a compensator, a shape of breast was reassembly shown to be real by gravity. Therefore, the purpose of this study was to evaluate diagnostic value of prone position in FDG PET-CT of breast cancer. Materials and Methods: 30 female patients with doubtful or positive breast cancer were examined. The PET-CT whole body scan was acquired at 60 minutes after $^{18}F$-FDG injection on Supine position. Then, regional breast spot scan was progressed on prone position using a compensator. Each image was evaluated by physicians blinded to patient's data, and statistical analysis did through SUVs measured in PET-CT images. Results: In 27 of 30 patients, prone position was shown accurate discrimination and diagnostic value, but in another 3 patients had a lesion 1cm below, PET-CT couldn't detect it, unlike MRI. Consequently, prone position distinguished a lesion better than Supine position, because of low degree of metamorphosis by gravity. The SUVs analysis of each position was significant (p value=0.004). Conclusion: In PET-CT of breast cancer, prone position could detect micrometastasis as well as primary lesion, better than supine position. Therefore, this study proposes that any technical change considered morphological feature like prone position can offer adequate and useful diagnostic information, together with complementary quantitative analysis.

• The Korean Journal of Pesticide Science
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• v.8 no.3
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• pp.151-161
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• 2004

Three dimensional quantitative structure-activity relationships (3D-QSAR) studies for the protox inhibition activities against root and shoot of rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli) by a series of new A=3,4,5,6-tetrahydrophthalimino, B=3-chloro-4,5,6,7-tetrahydro-2H-indazolyl and C=3,4-dimethylmaleimino group, and R-group substituted on the phenyl ring in 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2chloro-4-fluorobenzene derivatives were performed using comparative molecular field analyses (CoMFA) methodology with Gasteiger-Huckel charge. Four CoMFA models for the protox inhibition activities against root and shoot of the two plants were generated using 46 molecules as training set and the predictive ability of the each models was evaluated against a test set of 8 molecules. And the statistical results of these models with combination (SIH) of standard field, indicator field and H-bond field showed the best predictability of the protox inhibition activities based on the cross-validated value $r^2_{cv.}$ $(q^2=0.635\sim0.924)$, conventional coefficient $(r^2_{ncv.}=0.928\sim0.977)$ and PRESS value $(0.091\sim0.156)$, respectively. The activities exhibited a strong correlation with steric $(74.3\sim87.4%)$, electrostatic $(10.10\sim18.5%)$ and hydrophobic $(1.10\sim8.30%)$ factors of the molecules. The steric feature of molecule may be an important factor for the activities. We founded that an novel selective and higher protox inhibitors between the two plants may be designed by modification of X-subsitutents for barnyardgrass based upon the results obtained from CoMFA analyses.