• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1276-1276
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• 2001

Polycyclic aromatic hydrocarbons(PAHs) are widely distributed in the environment and are often implicated as potential carcinogens. The chromatographic methods of detection and quantitative determination of PAHs in environmental samples are costly, time consuming, and do not account for all kinds of PAHs. This work describes a quantitative spectroscopic method for the analysis of mixtures of eight PAHs using multivariate calibration models for Fourier transform near infrared(FT-NIR) spectral data. The NIR spectra of mixtures of PAHs (anthracene, pyrene, 1,2-benzanthracene, perylene, chrysene, benzo(a)pyrene, 1-methylanthracene and benzo(ghi)perylene) were measured in the wavelength range from 1100 nm to 2500 nm. The spectral data were processed using a partial least squares regression. We have studied the spectral characteristics of NIR spectra of mixtures of PAHs. It was possible to determine each PAM used in this study at the environmental level(mg L-1) in the laboratory samples. Further development may lead to the rapid determination of more PAHs in typical environmental samples.

• Particle and aerosol research
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• v.18 no.4
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• pp.109-127
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• 2022

Recently, low-cost particulate matter (PM) sensors have been widely used in monitoring mass concentration. Maintaining the accuracy of the sensors is important and requires rigorous performance evaluation and calibration. In this study, two commercial low-cost PM sensors(LCS), Plantower PMS3003 and Plantower PMS7003, were evaluated in the laboratory and field with a reference-grade PM monitor (GRIMM 11-D). Laboratory evaluation was conducted with single/mixed particles of PSL (Poly Styrene Latex) in an acrylic chamber at 20℃ and relative humidity of 20%. Field evaluation was conducted inside a building of Yonsei University (Shinchon) from February 12 to March 31, 2022. In both evaluations, LCS measured values became different from reference measured values when the relative humidity was high or the outdoor air PM10/PM2.5 ratio was high. Based on the field evaluation, the LCS measured values were corrected through four different regression analysis models. As a result, the multivariate polynomial regression analysis model showed highest matching with the reference PM monitor (PM2.5 >0.9, PM10 >0.85). In this model, the PM10/PM2.5 ratio and relative humidity were chosen as independent variables.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.393-401
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• 2007

Affective aspects of design attributes such as color, Pattern, and texture are important to the overall impression and the success of interior products. Among all the interior materials, wallpapers and flooring materials take up largest construction area and they are main components in creating affective impression for customers. This study aims to investigate the relationship between luxuriousness and related affective variables and design elements of wallpapers and flooring materials. The approach consists of 3 steps: (1) selecting related affective features and product design attributes through a literature survey, opinion of expert panel, and focus group interview, (2) conducting evaluation experiments, and (3) developing Kansei models using multivariate statistical analysis and analyzing critical attributes. Evaluation experiment was conducted using a questionnaire made up of 7-point scale and 100-point scale and 30 housewives and 20 interior designers participated in the evaluation experiment. The result of evaluation was analyzed through principal component regression and quantification I analysis. As a result of analyzing the survey data, the relationship between luxuriousness and related affective features and product design attributes was identified, moreover a optimal combination of the design component was identified. Consequently, it is expected that the results of the study would be a basis of the concept of emotion-based design by giving insights about how customers perceive the luxuriousness and suggesting the optimal combination, and providing specific quantitative design guidelines.

• Journal of Chest Surgery
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• v.26 no.1
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• pp.24-31
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• 1993

The long term clinical results following valve replacement with Hancock and Carpentier-Edwards bioprostheses were compared between tow valve models and between tow groups totaling 249 patients who were discharged after valve replacement from 1976 to 1986. The two groups of patients were treated with nonrandomized fashion. Follow-up was 87% complete. Cummulative duration of follow-up was 1909 patient-years, with maximum follow-up duration of 15 years. The actuarial survival for 122 patients with Hancock valves was 95.2%[\ulcornerstandard deviation] and 84.4% after 5 and 10 years of follow-up, respectively. Comparable figures for 127 patients undergoing valve replacement with Carpentier-Edwards valves were 87.3% and 76.4%, respectively[p=NS]. The probability of freedom from structural valve deterioration after 5 and 10 years of follow-up was 97.2% and 60.6%, respectively, with Hancock valves and 97.2% and 55.7%, respectively, with Carpentier-Edwards valves[p=NS]. Considering all 249 patients, multivariate [Cox model] regression revealed that ejection fraction was only significant predictor of structural valve deterioration. The probability of freedom from thromboembolism after 5 and 10 years of follow-up was 91.3% and 86.4%, respectively, with Hancock valves and 94.2% and 82.5%, respectively, with Carpentier-Edwards valves[p=NS]. Hence more strict control of anticoagulation should be done on patients with left atrial factors. In summary, there were no significant differences in actuarial survival rate and major valve related complications between tow valve models. These results suggests that its use should be confined to older patients or patients with a contraindication of anticoagulation.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.27-39
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• 2022

The exchange rate is an important macroeconomic variable that influences internal and external balances. Nepal follows a dual exchange rate such that the Nepali rupee (NPR) is pegged with the Indian rupee (INR) but floats with the United States dollar (USD) and all other currencies. There have been very few studies on the exchange rate of Nepal, of which the majority focus on the bivariate relationship between exchange rate and another variable. However, this paper analyses the multivariate relationship between the USD-NPR exchange rate and major macroeconomic variables. Determinants of Nepal's exchange rate have been derived with multiple regression using the ordinary least square (OLS) approach. Since the explanatory variables could not significantly capture the movement of the dependent variable, a long-run relationship between Nepal and India's exchange rate has been analyzed using Engle-Granger cointegration to establish a relationship as suggested by a graphical representation. This explains that Nepal's exchange rate long run is determined by India's exchange rate than its own fundamentals. In addition, the macro-linkages of Nepal's macroeconomic variables have been analyzed using Standard Vector Autoregressive models followed by impulse response analysis which is useful for policy decisions. Some policy implications indicating the sustainability of Nepal's pegged regime have been drawn based on the empirical analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1481-1488
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• 2014

Background: To avoid performing axillary lymph node dissection (ALND) for non-sentinel lymph node (SLN)-negative patients with-SLN positive axilla, nomograms for predicting the status have been developed in many centers. We created a new nomogram predicting non-SLN metastasis in SLN-positive patients with invasive breast cancer and evaluated 14 existing breast cancer models in our patient group. Materials and Methods: Two hundred and thirty seven invasive breast cancer patients with SLN metastases who underwent ALND were included in the study. Based on independent predictive factors for non-SLN metastasis identified by logistic regression analysis, we developed a new nomogram. Receiver operating characteristics (ROC) curves for the models were created and the areas under the curves (AUC) were computed. Results: In a multivariate analysis, tumor size, presence of lymphovascular invasion, extranodal extension of SLN, large size of metastatic SLN, the number of negative SLNs, and multifocality were found to be independent predictive factors for non-SLN metastasis. The AUC was found to be 0.87, and calibration was good for the present Ondokuz Mayis nomogram. Among the 14 validated models, the MSKCC, Stanford, Turkish, MD Anderson, MOU (Masaryk), Ljubljana, and DEU models yielded excellent AUC values of > 0.80. Conclusions: We present a new model to predict the likelihood of non-SLN metastasis. Each clinic should determine and use the most suitable nomogram or should create their own nomograms for the prediction of non- SLN metastasis.

• Journal of Preventive Medicine and Public Health
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• v.49 no.1
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• pp.45-52
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• 2016

Objectives: Previous large-scale cohort studies conducted in Korea have found a positive association between diabetes mellitus (DM) and colorectal cancer (CRC) in men only, in contrast to studies of other populations that have found significant associations in both men and women. Methods: A total of 1070 CRC cases and 2775 controls were recruited from the National Cancer Center, Korea between August 2010 and June 2013. Self-reported DM history and the duration of DM were compared between cases and controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by binary and polytomous logistic regression models. Results: DM was associated with an elevated risk of CRC in both men (OR, 1.47; 95% CI, 1.13 to 1.90) and women (OR, 1.92; 95% CI, 1.24 to 2.98). This association remained when we controlled for age, body mass index, alcohol consumption, and physical activity level. In sub-site analyses, DM was associated with distal colon cancer risk in both men (multivariate OR, 2.04; 95% CI, 1.39 to 3.00) and women (multivariate ORs, 1.99; 95% CI, 1.05 to 3.79), while DM was only associated with rectal cancer risk in women (multivariate OR, 2.05; 95% CI, 1.10 to 3.82). No significant association was found between DM and proximal colon cancer risk in either men (multivariate OR, 1.45; 95% CI, 0.88 to 2.41) or women (multivariate OR, 1.79; 95% CI, 0.78 to 4.08). Conclusions: Overall, DM was associated with an increased risk of CRC in Koreans. However, potential over-estimation of the ORs should be considered due to potential biases from the case-control design.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.383-401
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• 2016

In this paper, we described the statistical modeling of crop yields using satellite images, climatic datasets, soil property maps, and fertilizer data for the Midwestern United States during 2001-2012. Satellite images were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic datasets were provided by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group. Soil property maps were derived from the Harmonized World Soil Database (HWSD). Our multivariate regression models produced quite good prediction accuracies, with differences of approximately 8-15% from the governmental statistics of corn and soybean yields. The unfavorable conditions of climate and vegetation in 2012 could have resulted in a decrease in yields according to the regression models, but the actual yields were greater than predicted. It can be interpreted that factors other than climate, vegetation, soil, and fertilizer may be involved in the negative biases. Also, we found that soybean yield was more affected by minimum temperature conditions while corn yield was more associated with photosynthetic activities. These two crops can have different potential impacts regarding climate change, and it is important to quantify the degree of the crop sensitivities to climatic variations to help adaptation by humans. Considering the yield decreases during the drought event, we can assume that climatic effect may be stronger than human adaptive capacity. Thus, further studies are demanded particularly by enhancing the data regarding human activities such as tillage, fertilization, irrigation, and comprehensive agricultural technologies.

• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.717-726
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• 2009

Multivariate models were developed for the simultaneous spectrophotometric determination of copper (II), nickel (II) and zinc (II) in water with 1-(2-thiazolylazo)-2-naphthol as chromogenic reagent in the presence of Triton X-100. To overcome the drawback of spectral interferences, principal component regression (PCR) and partial least square (PLS) multivariate calibration approaches were applied. Performances were validated with several test sets, and their results were then compared. In general, no significant difference in analytical performance between PLS and PCR models. The root mean square error of prediction (RMSEP) using three components for $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ were 0.018, 0.010, 0.011 ppm, respectively. Figures of merit such as sensitivity, analytical sensitivity, limit of detection (LOD) were also estimated. High reliability was achieved when the proposed procedure was applied to simultaneous determination of $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ in synthetic mixture and tap water.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.415-424
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• 2021

Objective: To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH). Materials and Methods: We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power. Results: The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively. Conclusion: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.