• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.124-131
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• 2016

Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, it is an objective and automatic procedure is necessary to select optimal parameter value for baseline correction. Asymmetrically reweighted penalized least squares (arPLS) based on penalized least squares was proposed for baseline correction in our previous study. The method uses a new weighting scheme based on the generalized logistic function. In this study, we present an automatic selection of optimal parameter for baseline correction using arPLS. The method computes fitness and smoothness values of fitted baseline within available range of parameters and then selects optimal parameter when the sum of normalized fitness and smoothness gets minimum. According to the experimental results using simulated data with varying baselines, sloping, curved and doubly curved baseline, and real Raman spectra, we confirmed that the proposed method can be effectively applied to optimal parameter selection for baseline correction using arPLS.

• The Journal of Korean society of community based occupational therapy
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• v.10 no.2
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• pp.63-72
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• 2020

Objective : The purpose of this study is to investigate the effect of intensive one-day training on Movement Assessment Battery for Children-2 screening developmental coordination disorder. Methods : We provided intensive one-day training which combined lecture and practice on MABC-2 assessment tools for 33 trainees. Interrater reliability was calculated by using Intraclass correlation coefficient (ICC) with the raw score of results scored simultaneously by experts and trainees of MABC-2. Results : The 33 female trainees with an average of five years and three months of experience and less experience using motor skill assessment tools scored raw score while watching the performance scenes of normal children. The results of the ICC between experts and training participants in MABC-2 obtained a high confidence 0.95 and above (p<.001). Conclusion : Clinicians who participated in one-day training seems to use MABC-2 effectively. Through this, one-day training seems to be effective in acquiring new motor skill assessment tools.

• Journal of Korean Medical Science
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• v.33 no.51
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• pp.325.1-325.10
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• 2018

Background: To evaluate survival outcomes and prognostic factors for overall survival (OS) in patients with metastatic renal cell carcinoma (mRCC) who received sunitinib (SU) and pazopanib (PZ) as first-line therapy in real-world Korean clinical practice. Methods: Data of 554 patients with mRCC who received SU or PZ at eight institutions between 2012 and 2016 were retrospectively reviewed. Based on the targeted therapy, the patients were divided into SU (n = 293) or PZ (n = 261) groups, and the clinicopathological variables and survival rates of the two groups were compared. A multivariable Cox proportional hazard model was used to determine the prognostic factors for OS. Results: The median follow-up was 16.4 months (interquartile range, 8.3-31.3). Patients in the PZ group were older, and no significant difference was observed in the performance status (PS) between the two groups. In the SU group, the dose reduction rate was higher and the incidence of grade 3 toxicity was more frequent. The objective response rates were comparable between the two groups (SU, 32.1% vs. PZ, 36.4%). OS did not differ significantly between the two groups (SU, 36.5 months vs. PZ, 40.2 months; log-rank, P = 0.955). Body mass index, Eastern Cooperative Oncology Group PS > 2, synchronous metastasis, poor Heng risk criteria, and liver and bone metastases were associated with a shorter OS. Conclusion: Our real-world data of Korean patients with mRCC suggested that SU and PZ had similar efficacies as first-line therapy for mRCC. However, PZ was better tolerated than SU in Korean patients.

• Journal of agriculture & life science
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• v.45 no.4
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• pp.65-72
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• 2011

The objective of this research is to develop biomass allometric equation for Pinus densiflora in central region and Quercus variabilis. To develop the biomass allometric equation by species and tree component, data for Pinus densiflora in central region is collected to 30 plots (70 trees) and for Quercus variabilis is collected to 15 plots (32 trees). This study is used two independent values; (1) one based on diameter beast height, (2) the other, diameter beast height and height. And the equation forms were divided into exponential, logarithmic, and quadratic functions. The validation of biomass allometric equations were fitness index, standard error of estimate, and bias. From these methods, the most appropriate equations in estimating total tree biomass for each species are as follows: $W=aD^b$, $W=aD^bH^c$; fitness index were 0.937, 0.943 for Pinus densiflora in central region stands, and $W=a+bD+cD^2$, $W=aD^bH^c$; fitness index were 0.865, 0.874 for Quercus variabilis stands. in addition, the best performance of biomass allometric equation for Pinus densiflora in central region is $W=aD^b$, and Quercus variabilis is $W=a+bD+cD^2$. The results of this study could be useful to overcome the disadvantage of existing the biomass allometric equation and calculate reliable carbon stocks for Pinus densiflora in central region and Quercus variabilis in Korea.

• Therapeutic Science for Rehabilitation
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• v.8 no.4
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• pp.41-51
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• 2019

Objective : The purpose of this study was to investigate the effects of virtual reality-based activities of daily living (ADL) training on ADL and rehabilitative motivation in patients with traumatic brain injury. Methods : This study was performed using a pre-post design with seven traumatically brain injured patients. Subjects were subjected to virtual reality-based ADL training for 30 minutes a day, 2 to 3 times a week for 4 weeks. Evaluation was conducted before and after the intervention using the Korean Modified Barthel Index (K-MBI), Cognitive Functional Independence Measure (C-FIM), and Volitional Questionnaire (VQ). Changes before and after intervention were analyzed by Wilcoxon signed-rank test, and correlations were analyzed using Spearman's coefficient. Results : After intervention, patients with traumatic brain injury showed significant improvements in K-MBI (p<.05). There was no significant change in total C-FIM score and VQ score (p>.05). Total C-FIM score correlated significantly with VQ score (p<.05, r=.755). The social cognition domain of C-FIM had a significant correlation with VQ score (p<.05, r=826). Conclusions : Virtual reality-based ADL training can improve ADL performance, but further research is needed to determine whether improvements in social cognition and rehabilitative motivation are possible.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.11
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• pp.1705-1714
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• 2019

Objective: Reducing roughage feeding without negatively affecting rumen health is of interest in ruminant nutrition. We investigated the effects of roughage sources and concentrate types on growth performance, ruminal fermentation, and blood metabolite levels in growing cattle. Methods: In this 24-week trial, 24 Hanwoo cattle ($224{\pm}24.7kg$) were fed similar nitrous and energy levels of total mixed ration formulated using two kinds of roughage (timothy hay and ryegrass straw) and two types of concentrate mixes (high starch [HS] and high fiber [HF]). The treatments were arranged in a $2{\times}2$ factorial, consisting of 32% timothy-68% HS, 24% timothy-76% HF, 24% ryegrass-76% HS, and 17% ryegrass-83% HF. Daily feed intakes were measured. Every four weeks, blood were sampled, and body weight was measured before morning feeding. Every eight weeks, rumen fluid was collected using a stomach tube over five consecutive days. Results: The mean dry matter intake (7.33 kg) and average daily gain (1,033 g) did not differ among treatments. However, significant interactions between roughage source and concentrate type were observed for the rumen and blood parameters (p<0.05). Total volatile fatty acid concentration was highest (p<0.05) in timothy-HF-fed calves. With ryegrass as the roughage source, decreasing the roughage inclusion rate increased the molar proportion of propionate and decreased the acetate-to-propionate ratio; the opposite was observed with timothy as the roughage source. Similarly, the effects of concentrate types on plasma total protein, alanine transaminase, Ca, inorganic P, total cholesterol, triglycerides, and creatinine concentrations differed with roughage source (p<0.05). Conclusion: Decreasing the dietary roughage inclusion rate by replacing forage neutral detergent fiber with that from non-roughage fiber source might be a feasible feeding practice in growing cattle. A combination of low-quality roughage with a high fiber concentrate might be economically beneficial.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1836-1843
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• 2019

Objective: Social genetic effects (SGE) are an important genetic component for growth, group productivity, and welfare in pigs. The present study was conducted to evaluate i) the feasibility of the single-step genomic best linear unbiased prediction (ssGBLUP) approach with the inclusion of SGE in the model in pigs, and ii) the changes in the contribution of heritable SGE to the phenotypic variance with different scaling ${\omega}$ constants for genomic relationships. Methods: The dataset included performance tested growth rate records (average daily gain) from 13,166 and 21,762 pigs Landrace (LR) and Yorkshire (YS), respectively. A total of 1,041 (LR) and 964 (YS) pigs were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel. With the BLUPF90 software package, genetic parameters were estimated using a modified animal model for competitive traits. Giving a fixed weight to pedigree relationships (${\tau}:1$), several weights (${\omega}_{xx}$, 0.1 to 1.0; with a 0.1 interval) were scaled with the genomic relationship for best model fit with Akaike information criterion (AIC). Results: The genetic variances and total heritability estimates ($T^2$) were mostly higher with ssGBLUP than in the pedigree-based analysis. The model AIC value increased with any level of ${\omega}$ other than 0.6 and 0.5 in LR and YS, respectively, indicating the worse fit of those models. The theoretical accuracies of direct and social breeding value were increased by decreasing ${\omega}$ in both breeds, indicating the better accuracy of ${\omega}_{0.1}$ models. Therefore, the optimal values of ${\omega}$ to minimize AIC and to increase theoretical accuracy were 0.6 in LR and 0.5 in YS. Conclusion: In conclusion, single-step ssGBLUP model fitting SGE showed significant improvement in accuracy compared with the pedigree-based analysis method; therefore, it could be implemented in a pig population for genomic selection based on SGE, especially in South Korean populations, with appropriate further adjustment of tuning parameters for relationship matrices.

• Journal of Korean Neurosurgical Society
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• v.64 no.6
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• pp.950-956
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• 2021

Objective : Psoas and masseter muscles are known markers of sarcopenia. However, the relative superiority of either muscle as a marker is unclear. Therefore, this study analyzed the two muscles in patients with a prognosis of traumatic brain injury (TBI). Methods : Patients with TBI visiting a regional trauma center between January 2017 and December 2018 were selected, and their medical records were reviewed. TBI patients with an abbreviated injury score (AIS) of 4 or 5 were selected. Patients with an AIS of 4 or 5 at the chest, abdomen, and extremity were excluded. Patients with a hospital stay of 1 to 2 days were excluded. Both muscle areas were measured based on the initial computed tomography. The psoas muscle index (PMI) and the masseter muscle index (MMI) were calculated by dividing both muscle areas by height in meters squared (cm²/m²). These muscle parameters along with other medical information were used to analyze mortality and the Glasgow outcome scale (GOS). Results : A total of 179 patients, including 147 males (82.1%), were analyzed statistically. The mean patient age was 58.0 years. The mortality rate was 16.8% (30 patients). The mean GOS score was 3.7. Analysis was performed to identify the parameters associated with mortality, which was a qualitative study outcome. The psoas muscle area (16.9 vs. 14.4 cm², p=0.028) and PMI (5.9 vs. 5.1 cm²/m², p=0.004) showed statistical differences between the groups. The PMI was also statistically significant as a risk factor for mortality in logistic regression analysis (p=0.023; odds ratio, 0.715; 95% confidence interval, 0.535-0.954). Quantitative analyses were performed with the GOS scores. Bivariate correlation analysis showed a statistically significant correlation between PMI and GOS scores (correlation coefficient, 0.168; p=0.003). PMI (p=0.004, variation inflation factor 1.001) was significant in multiple regression analysis. The masseter muscle area and MMI did not show significance in the study. Conclusion : Larger PMI was associated with statistically significant improved survival and GOS scores, indicating its performance as a superior prognostic marker. Further analyses involving a larger number of patients, additional parameters, and more precise settings would yield a better understanding of sarcopenia and TBI.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1149-1161
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• 2021

With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

• 한국사회정책
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• v.25 no.1
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• pp.259-286
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• 2018

The purpose of this study is to examine which factors decide welfare exit in the hope building account program that targets low-income families. This study used the matched DB of hope ribbon program and hope building account program which is collected by central self-sufficiency foundation. As a result, the significant factors in welfare exit are main income, health(illness), licensed possession of status, education, marital status, employment and entrepreneurship, in-kind support, professional case management service, and social service. In particular, the participants who received proper social services and case management services in the program have more possibility of welfare exit than the participants who did not. It have implications in that the study found the success factors by connecting hope ribbon program and the hope building account program which has been introduced since 2010 and enlarge the scope of the performance analysis of the hope building account program. In addition, this study provides the suggestions to improve anty-poverty policy and system in the direction of providing work incentives and facilitating welfare exit and securing continuity of the hope building account program and the hope ribbon program. Specifically, this paper can be utilized as objective data in establishing a expansion of the hope building account program and suggesting the important issue for the case management in the filed.