• Journal of Microbiology and Biotechnology
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• 제19권7호
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• pp.718-726
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• 2009

The objective of this study was to develop and validate secondary models that can predict growth parameters of L. monocytogenes Scott A as a function of concentrations (0-3%) of a commercial potassium lactate (PL) and sodium diacetate (SDA) mixture, pH (5.5-7.0), and temperature (4-37DC). A total of 120 growth curves were fitted to the Baranyi primary model that directly estimates lag time (LT) and specific growth rate (SGR). The effects of the variables on L. monocytogenes Scott A growth kinetics were modeled by response surface analysis using quadratic and cubic polynomial models of the natural logarithm transformation of both LT and SGR. Model performance was evaluated with dependent data and independent data using the prediction bias ($B_f$) and accuracy factors ($A_f$) as well as the acceptable prediction zone method [percentage of relative errors (%RE)]. Comparison of predicted versus observed values of SGR indicated that the cubic model fits better than the quadratic model, particularly at 4 and $10^{\circ}C$. The $B_f$and $A_f$for independent SGR were 1.00 and 1.08 for the cubic model and 1.08 and 1.16 for the quadratic model, respectively. For cubic and quadratic models, the %REs for the independent SGR data were 92.6 and 85.7, respectively. Both quadratic and cubic polynomial models for SGR and LT provided acceptable predictions of L. monocytogenes Scott A growth in the matrix of conditions described in the present study. Model performance can be more accurately evaluated with $B_f$and $A_f$and % RE together.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• 물과 미래
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• 제18권3호
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• pp.253-264
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• 1985

근본적으로 저수지의 Storage-Yield 관계를 해석하는 데는 두가지 관점이 있다. 가장 보편적인 관점은 필요한 수요량을 공급하기 위하여 저수지의 필요저수용량을 결정하는 것이다. 이런 형태의 문제는 저수지의 계획이나 초기 설계단계에서 보통 생긴다. 두 번째 관점은 주어진 저수용량에 대한 방류량의 결정이며, 이것은 최종 설계나 더 상세한 분석을 위한 현존 저수지의 재평가에서 자주 생긴다. 본 연구의 목적은 저수지의 설계나 운영을 위한 Storage-Yield 관계를 산정하는 현재의 방법론을 개선하는 것이다. 저수지의 Storage-Yield 관계를 해석하느 s가장 적합한 기법을 찾기 위하여 잔차누가곡선기법(Residual mass curve technique), 개선된 저류량기법(Low flow technique)과 TPM 기법(Transition probability matrix technique)이 검토되었다. 저수지의 Storage-Yield 관계를 해석하는데 있어서 홍천댐 건설예정지점의 1917∼1940년 월유입량 자료와 Thomas-Fiering 모델에 의해 모의 발생된 자료를 가지고 위의 세가지 기법을 상세히 검토하였다. 저수지의 Storage-Yield 관계를 폭넓게 검토한 결과, 잔차누가곡선기법과 저류량기법은 예비 설계에 타당하며, TPM 기법은 월별 혹은 계절별 수요변동을 고려할 수 있기 때문에 최종 설계에 타당한 기법임을 알 수 있다.

• Korean Journal of Radiology
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• 제22권6호
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• pp.994-1004
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• 2021

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. Materials and Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. Results: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). Conclusion: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.

• 한국전산구조공학회논문집
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• 제22권5호
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• pp.391-401
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• 2009

하이브리드 구조실험에서는 구조물을 여러 개의 부분구조물로 나누어서 실험과 해석을 하고 이의 결과를 합쳐서 전체적인 구조물의 거동을 파악한다. 이러한 방법은 진동대 실험과 비교하여 구조물의 크기제한의 영향을 받지 않는 유사동적 실험에 효과적이다. 하이브리드 구조실험과정에서 발생된 데이터와 관련 정보를 저장하고 검색할 수 있는 컴퓨터시스템을 만들기 위해서는 하이브리드 구조실험과 관련된 정보를 체계화시켜서 구성하는 작업이 선행되어야 한다. 본 논문은 하이브리드 구조실험에 관련된 정보를 표현하는 데이터 모델을 제시하고 있는데, 이 데이터 모델은 포괄적인 구조실험 정보를 표현하는 데이터 모델의 하나인 리하이 모델에서 하이브리드 실험부분을 개선한 것이다. 하이브리드 구조실험에서의 부분구조물들을 표현하기 위하여 실험모델 클래스와 해석모델 클래스를 정의하였고, 이러한 클래스들의 정보교환을 조정하는 클래스를 정의하였으며, 제한된 범위의 시스템을 구현하여 객체들 간의 연결 상태를 파악할 수 있도록 하였다. 본 논문에서 기술한 데이터 모델은 구조실험자와 연구자들이 사용할 수 있는 하이브리드 구조실험 정보를 저장하는 컴퓨터 시스템을 개발하는데 적용할 수 있을 것으로 사료된다.

• 대한토목학회논문집
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• 제11권4호
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• pp.113-119
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• 1991

본 연구에서는 월 강우량과 월 증발량 자료만 있는 하천유역에 대하여 장기 물수지 분석을 실시하는 방법론을 제시하고져 하였다. 단기간의 월 강우량 자료를 경혐공식에 의해 월 유출량 자료로 변환시킨 후 추계학적 모의발생 모형을 사용하여 이들 단기 유출자료로부터 일군의 장기 유출자료계열을 발생시켰고, 자료계열별로 갈수빈도해석에 의해 최대 갈수기간 및 월 강수량계열을 작성하였다. 계획년도별 각종 용수수요를 표준절차에 의해 추정하였으며 순 물소모량도 계산하였다. 유역내의 기존 저수지를 총괄하는 합성저수지를 통해 Deficit-Supply 방법으로 물 수지분석을 실시한 결과 물 부족량은 갈수재현기간이 커짐에 따라 급격하게 커지는 것으로 나타났다. 이는 하천 유역의 장기 물 수지분석을 통해 신뢰성있는 물 부족량을 계산하기 위해서는 추계학적 모의발생모형에 의한 장기간 유출량의 발생이 필수적이며 수자원 시스템의 적정 갈수재현기간의 선정이 대단히 중요함을 시사해 주는 것이다.

• Journal of Chest Surgery
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• 제20권4호
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• pp.643-654
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• 1987

The effect of prostacyclin[PGI, ] on myocardial preservation during global ischemia was studied in the isolating working rabbit heart model. Forty hearts underwent a 15 minute period of retrograde nonworking perfusion with Krebs-Henseleit buffer solution [37*C] and were switched over to the working mode for 15 minutes. After baseline measurement of heart rate, peak aortic pressure, aortic flow, and coronary flow, all hearts were subjected to 60 minutes of ischemic arrest at 10*C induced with St. Thomas Hospital cardioplegic solution: Group I had single dose cardioplegia, Croup II double dose, Croup III oxygenated double dose, and Group IV single dose with PCI, infusion [10ng/min./gm heart weight]. Hearts were then revived with 15 minute period of nonworking reperfusion at normothermia, followed by 30 minutes of working perfusion. Repeat measurements of cardiac function were obtained and expressed as a percent of the preischemic baseline values. Oxygen content of arterial perfusate and coronary effluent was measured by designed time interval. Leakage of creatine kinase was determined during post-ischemic reperfusion period. Finally wet hearts were weighed and placed in 120*C oven for 36 hours for measurement of dry weight. In the PGI, treated group [IV], heart rate increased consistently throughout the period of reperfusion from 100*5.0% [p<0.001] to 107*6.2% [p<0.001]. The percent recovery of aortic flow showed 95*5.7% [p<0.001] at the first 3 minute and full recovery through the subsequent time. Coronary flow was augmented significantly in the 3 minute [96*6.2%, p<0.001] and then sustained above baseline values. Among the Croup I, II, and III, all hemodynamic values were significantly below preischemic levels. PGI2 relatively increased oxygen delivery [1.22*0.19ml/min, p<0.001] and myocardial oxygen consumption [0.90*0.13ml/min, p<0.001] during reperfusion period. Leakage of creatine kinase in the PGI2 group was 9.3*1.58IU/15min [p<0.001]. This was significantly lower than Group I [33.0*2.68 IU/15min]. The water content of PCI2 treated hearts [81*0.9%, p<0.001] was also lower than the other groups.

• Safety and Health at Work
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• 제11권3호
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• pp.291-300
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• 2020

Background: The study aimed to determine the association of individual cognitive ability in late midlife with labor market participation among older workers. Methods: This prospective cohort study estimates the risk of long-term sickness absence, disability pension, early retirement, and unemployment from scores on the Intelligenz-Struktur-Test 2000R by combining data from 5076 workers from the Copenhagen Aging and Midlife Biobank with a register on social transfer payments. Analyses were stepwise adjusted for age, gender, physical and psychosocial work environment, health behaviors, occupational social class, education, and chronic diseases. Results: In the fully adjusted model, low cognitive ability (≥1 standard deviation below the mean for each gender) and high cognitive ability (≥1 standard deviation above the mean for each gender) were not associated with risk of any of the four labor market outcomes. Conclusion: Individual cognitive ability in late midlife was not associated with risk of long-term sickness absence, disability pension, early retirement, and unemployment in the fully adjusted model. Thus, no direct effect of individual cognitive ability in late midlife was observed on the risk of permanently or temporarily leaving the labor market.

• 물과 미래
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• 제29권2호
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• pp.179-190
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• 1996

한강하류부 수질의 통계학적 해석을 통하여 수질 시계열자료의 기본 통계특성치, 지점별 및 계절별 변동성을 검토하였으며, 유량과 수질인자간의 상관성 분석을 실시하였다. 본류의 주요 6개 지점 및 3개 지류에 대한 통계특성치와 적정분포형을 산정하여 제시하였으며, 시간의존성 및 계절성을 검토하여 제시하였다. 또한, 수질 항목간의 상관성 검토를 통하여 상관성이 높은 수질, 항목간, 그리고 지점간의 상관식을 제시하였다. 추계학적 모의모형의 적용가능성을 확인하였으며, DO 항목은 전 지점간에 높은 상관성을 가지고 있었다. 유량과의 상관관계 검토에 있어서 DO, SS 항목은 유량보다는 수온에 민감하였으며, BOD, COD 항목은 유량이 적은 갈수기에는 유량에 민감한 것으로 나타났다. 수온에 밀접한 영향을 받는 DO 항목외에도 BOD, COD 항목은 계절적인 주기성을 가지고 있었으며, 상호상관 분석결과 DO, BOD, COD 항목 외의 수질 항목들에서도 각 수질 항목들에 내재된 주기성을 찾아볼 수 있었다.

• Steel and Composite Structures
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• 제29권4호
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• pp.545-555
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• 2018

This study aimed to investigate the flexural behavior of precast concrete (PC) wall - steel shoe composite assemblies with various dry connection details at mid-span. Flexural tests were performed for five scenarios. Test parameters included the width of test specimens, arrangement of steel shoe connectors, and use of structural adhesive or waterproof tape at the mid-span joint. The test results showed that the PC wall - steel shoe composite assemblies joined at mid-span showed flexural damage patterns combined with rotational deformation, and the structural performance was satisfactory regardless of the arrangement of steel shoe connectors. Considering the two deformation components (flexural deformation by bending and rotational deformation due to joint opening), a theoretical model was proposed to analyze flexural strength and joint opening, and the simple model gave good predictions with acceptable accuracy.