• 한국임상수의학회지
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• 제20권1호
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• pp.7-11
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• 2003

감염된 환축을 찾는 진단과정에 완벽하지 못한 진단검사를 사용하는 경우 진단검사 결과는 흔히 왜곡되어 나타난다. 본 연구에서 저자는 Helicobacter pylori 감염을 진단하는데 사용되는 urease 검사, PCR 검사 및 조직학적인 검사법을 단독으로 사용하는 경우와 병행하여 사용하는 상황으로 구분하여 각각 진단적 특성을 평가하였다. 비선형 회귀모형 분석결과 민감도, 특이도, 양성우도비 및 음성우도비는 urease 검사법의 경우 99.9%, 99.9%, 99.9%, 99.6%, PCR 검사의 경우 88.6%, 99.9%, 99.9%, 70.5%, 조직검사법의 경우 78.3%, 97%, 78.3%, 97%fh 나타났다. 예측도는 유병율의 변화에 따라 다양한 값을 보였으며 Helicobacter pylori 감염의 유병율이 35% 이상일 때 조직 검사상 양성결과는 90% 이상의 일치도를 보였고, 유병율이 25% 미만일 때 조직 검사상 음성결과는 90% 이상의 일치도를 보였다. 본 연구결과 임상에서 감염된 개체를 스크리닝하는 목적으로 세가지 진단검사를 병행하는 것은 실질적인 이익이 없으며 단독검사로서 urease 검사와 PCR 검사가 가장 적합한 것으로 나타났다.

• 대한토목학회논문집
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• 제32권3A호
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• pp.139-148
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• 2012

원형 콘크리트 충전 강관 (CFT)은 강관과 콘크리트 내부채움재로 이루어진 합성구조로 급속 시공이 가능하고 치수 대비 강도의 효율성이 좋아 교량의 교각이나 건축물의 기둥으로 사용되고 있다. CFT에 대한 실험적 연구는 지난 수년간 꾸준히 연구되어 왔지만 이러한 실험 연구만으로 CFT의 거동을 파악하기는 충분하지 않다. 따라서, CFT의 실험 연구를 보완하고 보다 다양한 제원 및 하중 조건을 고려하여 CFT의 구조 거동을 파악하기 위해서는 수치해석 모델이 필요하다. 본 연구는 CFT의 비선형 유한 요소 해석 기법을 개발하는데 목표가 있다. 개발된 CFT의 유한 요소 해석 모델 기법은 다양한 하중이 작용하는 실험 결과들과 비교하여 그 타당성을 입증하였으며, 제안된 유한 요소 해석 모델은 CFT의 구속 효과 및 CFT의 구조 거동을 잘 모사할 수 있었다.

• Genomics & Informatics
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• 제11권4호
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• pp.263-271
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• 2013

We investigated the contribution of genetic variations of KLF5 to basal metabolic rate (BMR) and resting metabolic rate (RMR) and the inhibition of obesity in Korean children. A variation of KLF5 (rs3782933) was genotyped in 62 Korean children. Using multiple linear regression analysis, we developed a model to predict BMR in children. We divided them into several groups; normal versus overweight by body mass index (BMI) and low BMR versus high BMR by BMR. There were no differences in the distributions of alleles and genotypes between each group. The genetic variation of KLF5 gene showed a significant correlation with several clinical factors, such as BMR, muscle, low-density lipoprotein cholesterol, and insulin. Children with the TT had significantly higher BMR than those with CC (p=0.030). The highest muscle was observed in the children with TT compared with CC (p=0.032). The insulin and C-peptide values were higher in children with TT than those with CC (p=0.029 vs. p=0.004, respectively). In linear regression analysis, BMI and muscle mass were correlated with BMR, whereas insulin and C-peptide were not associated with BMR. In the high-BMR group, we observed that higher muscle, fat mass, and C-peptide affect the increase of BMR in children with TT (p < 0.001, p < 0.001, and p=0.018, respectively), while Rohrer's index could explain the usual decrease in BMR (adjust $r^2$=1.000, p < 0.001, respectively). We identified a novel association between TT of KLF5 rs3782933 and BMR in Korean children. We could make better use of the variation within KLF5 in a future clinical intervention study of obesity.

• 한국의류학회지
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• 제42권3호
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• pp.503-515
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• 2018

In this research, the three-dimensional structural and colorimetrical modeling of yarn-dyed woven fabrics was conducted based on the Kubelka-Munk theory (K-M theory) for their accurate color predictions. In the K-M theory for textile color formulation, the absorption and scattering coefficients, denoted K and S, respectively, of a colored fabric are represented using those of the individual colorants or color components used. One-hundred forty woven fabric samples were produced in a wide range of structures and colors using red, yellow, green, and blue yarns. Through the optimization of previous two-dimensional color prediction models by considering the key three-dimensional structural parameters of woven fabrics, three three-dimensional K/S-based color prediction models, that is, linear K/S, linear log K/S, and exponential K/S models, were developed. To evaluate the performance of the three-dimensional color prediction models, the color differences, ${\Delta}L^*$, ${\Delta}C^*$, ${\Delta}h^{\circ}$, and ${\Delta}E_{CMC(2:1)}$, between the predicted and the measured colors of the samples were calculated as error values and then compared with those of previous two-dimensional models. As a result, three-dimensional models have proved to be of substantially higher predictive accuracy than two-dimensional models in all lightness, chroma, and hue predictions with much lower ${\Delta}L^*$, ${\Delta}C^*$, ${\Delta}h^{\circ}$, and the resultant ${\Delta}E_{CMC(2:1)}$ values.

• Korean Journal of Radiology
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• 제19권6호
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• pp.1021-1030
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• 2018

Objective: We evaluated the effect of various patient characteristics and time-density curve (TDC)-factors on the test bolus-affected vessel enhancement on coronary computed tomography angiography (CCTA). We also assessed the value of generalized linear regression models (GLMs) for predicting enhancement on CCTA. Materials and Methods: We performed univariate and multivariate regression analysis to evaluate the effect of patient characteristics and to compare contrast enhancement per gram of iodine on test bolus (${\Delta}HUTEST$) and CCTA (${\Delta}HUCCTA$). We developed GLMs to predict ${\Delta}HUCCTA$. GLMs including independent variables were validated with 6-fold cross-validation using the correlation coefficient and Bland-Altman analysis. Results: In multivariate analysis, only total body weight (TBW) and ${\Delta}HUTEST$ maintained their independent predictive value (p < 0.001). In validation analysis, the highest correlation coefficient between ${\Delta}HUCCTA$ and the prediction values was seen in the GLM (r = 0.75), followed by TDC (r = 0.69) and TBW (r = 0.62). The lowest Bland-Altman limit of agreement was observed with GLM-3 (mean difference, $-0.0{\pm}5.1$ Hounsfield units/grams of iodine [HU/gI]; 95% confidence interval [CI], -10.1, 10.1), followed by ${\Delta}HUCCTA$ ($-0.0{\pm}5.9HU/gI$; 95% CI, -11.9, 11.9) and TBW ($1.1{\pm}6.2HU/gI$; 95% CI, -11.2, 13.4). Conclusion: We demonstrated that the patient's TBW and ${\Delta}HUTEST$ significantly affected contrast enhancement on CCTA images and that the combined use of clinical information and test bolus results is useful for predicting aortic enhancement.

• 사물인터넷융복합논문지
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• 제7권2호
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• pp.31-40
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• 2021

본 연구는 간호대학생의 임상실습중 경험하는 언어폭력, 감정반응, 간호전문직관, 임상실습 스트레스 정도를 파악하고 임상실습 스트레스에 영향을 미치는 요인들을 확인하기 위하여 시도되었다. 연구 대상은 4년제 간호대학 4학년에 재학중인 간호대학생 106명이였으며 측정 도구는 언어폭력, 감정반응, 간호전문직관, 임상실습스트레스에 관한 문항으로 구성되었다. 언어폭력, 감정반응, 간호전문직관, 임상실습스트레스 정도는 기술통계로 분석하였고 언어폭력, 감정반응, 간호전문직관, 임상실습스트레스간의 상관관계는 Pearson correlation coefficients, 임상실습스트레스에 영향을 미치는 요인은 다중 선형 회귀분석(Multiple linear regression)을 적용하였다. 임상실습스트레스는 언어폭력, 감정반응과 유의한 정적상관성이 있는 것으로 나타났다(r=.683, r=.573). 유의미한 영향요인으로 언어폭력(𝛽=.487), 감정반응(𝛽=.240)순으로 임상실습스트레스의 49%를 설명하였다. 본 연구의 결과를 토대로 간호대학생들이 임상실습중 언어폭력에 대처하고 임상실습스트레스를 관리하기 위한 전략개발에 기초자료를 제공하고자 한다.

• Animal Bioscience
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• 제36권7호
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• pp.1003-1009
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• 2023

Objective: The objective was to compare (pedigree-based) best linear unbiased prediction (BLUP), genomic BLUP (GBLUP), and single-step GBLUP (ssGBLUP) methods for genomic evaluation of growth traits in a Mexican Braunvieh cattle population. Methods: Birth (BW), weaning (WW), and yearling weight (YW) data of a Mexican Braunvieh cattle population were analyzed with BLUP, GBLUP, and ssGBLUP methods. These methods are differentiated by the additive genetic relationship matrix included in the model and the animals under evaluation. The predictive ability of the model was evaluated using random partitions of the data in training and testing sets, consistently predicting about 20% of genotyped animals on all occasions. For each partition, the Pearson correlation coefficient between adjusted phenotypes for fixed effects and non-genetic random effects and the estimated breeding values (EBV) were computed. Results: The random contemporary group (CG) effect explained about 50%, 45%, and 35% of the phenotypic variance in BW, WW, and YW, respectively. For the three methods, the CG effect explained the highest proportion of the phenotypic variances (except for YW-GBLUP). The heritability estimate obtained with GBLUP was the lowest for BW, while the highest heritability was obtained with BLUP. For WW, the highest heritability estimate was obtained with BLUP, the estimates obtained with GBLUP and ssGBLUP were similar. For YW, the heritability estimates obtained with GBLUP and BLUP were similar, and the lowest heritability was obtained with ssGBLUP. Pearson correlation coefficients between adjusted phenotypes for non-genetic effects and EBVs were the highest for BLUP, followed by ssBLUP and GBLUP. Conclusion: The successful implementation of genetic evaluations that include genotyped and non-genotyped animals in our study indicate a promising method for use in genetic improvement programs of Braunvieh cattle. Our findings showed that simultaneous evaluation of genotyped and non-genotyped animals improved prediction accuracy for growth traits even with a limited number of genotyped animals.

• 한국지형학회지
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• 제26권3호
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• 한국지반환경공학회 논문집
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• 제25권7호
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• pp.5-19
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• 2024

During the blasting process, a fracture zone is formed in the vicinity of the blast hole. Any damage that extends beyond the excavation boundary line necessitates the implementation of an additional support system to assure safety. Typically, fracture zone radius is estimated from blast hole pressure using theoretical methods due to its simplicity. However, linear charge concentration (kg/m) is used for tunnel blasting. This paper compiles Swedish experimental datasets to estimate the radius of fracture zones based on linear charge concentration. Further numerical analyses are performed in LS-DYNA for coupled single-hole blasting. The Riedel-Hiermaier-Thoma (RHT) model has been selected as the constitutive model for this investigation. The numerical model is validated against small-scale laboratory tests. Parametric studies are conducted to predict fracture zones in granite and sandstone rocks using two kinds of explosives, PETN and AFNO. The analyses evaluate ten types of blast hole sizes, ranging from 17 to 100 mm. The results indicate that granite has a larger fracture zone than sandstone, and the PETN explosive predicts more damage than ANFO. Smaller blast holes exhibit smaller fracture zones in comparison to larger blast holes. Wave propagation is more rapidly attenuated in granite than in sandstone. Subsequently, the predicted fracture zone outcomes are compared with the empirical dataset. Fracture zones of medium blast hole diameter align well with the experimental data set. A predictive equation is derived from the data set, which may be used to evaluate blast design to manage fracture zones beyond the excavation line.

• The Journal of the Acoustical Society of Korea
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• 제17권2E호
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• pp.31-37
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• 1998

This paper proposes a feature extraction method using wavelet transform for speech recognition. Speech recognition system generally carries out the recognition task based on speech features which are usually obtained via time-frequency representations such as Short-Time Fourier Transform (STFT) and Linear Predictive Coding(LPC). In some respects these methods may not be suitable for representing highly complex speech characteristics. They map the speech features with same may not frequency resolutions at all frequencies. Wavelet transform overcomes some of these limitations. Wavelet transform captures signal with fine time resolutions at high frequencies and fine frequency resolutions at low frequencies, which may present a significant advantage when analyzing highly localized speech events. Based on this motivation, this paper investigates the effectiveness of wavelet transform for feature extraction of wavelet transform for feature extraction focused on enhancing speech recognition. The proposed method is implemented using Sampled Continuous Wavelet Transform (SCWT) and its performance is tested on a speaker-independent isolated word recognizer that discerns 50 Korean words. In particular, the effect of mother wavelet employed and number of voices per octave on the performance of proposed method is investigated. Also the influence on the size of mother wavelet on the performance of proposed method is discussed. Throughout the experiments, the performance of proposed method is discussed. Throughout the experiments, the performance of proposed method is compared with the most prevalent conventional method, MFCC (Mel0frequency Cepstral Coefficient). The experiments show that the recognition performance of the proposed method is better than that of MFCC. But the improvement is marginal while, due to the dimensionality increase, the computational loads of proposed method is substantially greater than that of MFCC.