• Journal of Microbiology and Biotechnology
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• v.30 no.4
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• pp.533-539
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• 2020

A quantitative real-time polymerase chain reaction (QPCR) was applied to estimate biokinetic coefficients of Clostridium cadaveris and Clostridium sporogenes, which utilize protein as carbon source. Experimental data on changes in peptone concentration and 16S rRNA gene copy numbers of C. cadaveris and C. sporogenes were fitted to model. The fourth-order Runge-Kutta approximation with non-linear least squares analysis was employed to solve the ordinary differential equations to estimate biokinetic coefficients. The maximum specific growth rate (μ_max), half-saturation concentration (K_s), growth yield (Y), and decay coefficient (K_d) of C. cadaveris and C.sporogenes were 0.73 ± 0.05 and 1.35 ± 0.32 h^-1, 6.07 ± 1.52 and 5.67 ± 1.53 g/l, 2.25 ± 0.75 × 10¹⁰ and 7.92 ± 3.71 × 10⁹ copies/g, 0.002 ± 0.003 and 0.002 ± 0.001 h^-1, respectively. The theoretical specific growth rate of C. sporogenes always exceeded that of C. cadaveris at peptone concentration higher than 3.62 g/l. When the influent peptone concentration was 5.0 g/l, the concentration of C.cadaveris gradually decreased to the steady value of 2.9 × 10¹⁰ copies/ml at 4 h Hydraulic retention time (HRT), which indicates a 67.1% reduction of the initial population, but the wash out occurred at HRTs of 1.9 and 3.2 h. The 16S rRNA gene copy numbers of C. sporogenes gradually decreased to steady values ranging from 1.1 × 10¹⁰ to 2.9 × 10¹⁰ copies/ml. C. sporogenes species was predicted to wash out at an HRT of 1.6 h.

• Spatial Information Research
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• v.10 no.2
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• pp.301-316
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• 2002

Soil Loss by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. Also, validity pondage of reservoir or dam is decreased by rivers inflow of eroded soil. Revised Universal Soil Loss Equation(RUSLE) is mainly used to presume soil loss amount of basin using GIS. But, because comparison with survey data is difficult, it is no large meaning that estimate calculated soil loss amount as quantitative. This research used unit sediment deposit survey data of Bo-seong basin for quantitative conclusion of soil loss amount that calculate on RUSLE. Through comparison examination with unit sediment yield that calculate on RUSLE and unit sediment deposit survey data, we can estimate resolution far RUSLE Model. As a result, cell size of 150m was estimated by thing which is most suitable.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.3-5
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• 2008

An increase in oil and gas plants caused by development of process industry have brought into the increase in use of flammable and toxic materials in the complex process under high temperature and pressure. There is always possibility of fire and explosion of dangerous chemicals, which exist as raw materials, intermediates, and finished goods whether used or stored in the industrial plants. Since there is the need of efforts on disaster damage reduction or mitigation process, we have been conducting a research to relate explosion model on the background of real 3D terrain model. By predicting the extent of damage caused by recent disasters, we will be able to improve efficiency of recovery and, sure, to take preventive measure and emergency counterplan in response to unprepared disaster. For disaster damage prediction, it is general to conduct quantitative risk assessment, using engineering model for environmental description of the target area. There are different engineering models, according to type of disaster, to be used for industry disaster such as UVCE (Unconfined Vapour Cloud Explosion), BLEVE (Boiling Liquid Evaporation Vapour Explosion), Fireball and so on, among them, we estimate explosion damage through UVCE model which is used in the event of explosion of high frequency and severe damage. When flammable gas in a tank is released to the air, firing it brings about explosion, then we can assess the effect of explosion. As 3D terrain information data is utilized to predict and estimate the extent of damage for each human and material. 3D terrain data with synthetic environment (SEDRIS) gives us more accurate damage prediction for industrial disaster and this research will show appropriate prediction results.

• Journal of Wetlands Research
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• v.19 no.2
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• pp.240-245
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• 2017

In this study, we developed a method to assess quantitatively the amount and the economic value of water quality regulating service of ecosystem services. Numbers of species and aquatic organisms such as fish increased because of the improved water, but it was due to complex factors such as water quality regulation services of ecosystems, installation of environmental facilities for water quality treatment, and water quality regulation. Therefore we sought ways to quantitatively estimate the value of ecosystem regulation services. In this study, we propose a method to estimate the quantitative value of water quality regulation service of ecosystem by utilizing the total amount of water pollution. In addition, the economic value evaluation method was proposed by multiplying the estimated the quantitative value of water quality regulation service of ecosystem by the unit cost per unit capacity. Finally, the ecosystem water quality regulation service was estimated by using the evaluation method for BOD and T-P in Nakdong river watershed.

• Journal of Energy Engineering
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• v.16 no.3
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• pp.93-102
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• 2007

This paper presents a scenario evaluation model of the AHP (Analytic Hierarchy Process) to evaluate dismantling scenarios considering quantitative and qualitative considerations. And decommissioning information producing modules which can obtain a dismantling schedule, quantify radioactive waste, visualize a radioactive inventory, estimate a decommissioning cost, and estimate a worker's exposure was developed to assess qualitatively decommissioning information. The digital mock-up (DMU) system was developed to verify dismantling processes and find error of scenarios in virtual space. It combines and manages the decommissioning information producing modules, the decommissioning DB, and the dismantling evaluation module synthetically. By using AHP model and DMU system, the thermal column in KRR-1 was evaluated on plasma arc cutting scenario and nibbler cutting scenario using the developed decommissioning DMU system.

• Korean Journal of Veterinary Research
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• v.45 no.2
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• pp.223-231
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• 2005

A quantitative risk assessment tool was used to provide estimates of the probability that foot-and-mouth (FMD) virus-contaminated, smuggled animal products are fed to susceptible swine in Korea. Sensitivity analyses were conducted to attempt to distinguish between parameter uncertainty and variability, using different assumptions on the effect of cooking at home, the effect of the fresh meat, and the effect of heat treatment at garbage processing facility. The median risk estimate was about 20.1% with a mean value of 27.4%. In a scenario regarding all beef and pork were considered as fresh meat the estimated median risk was 3.4%. The risk was greatly dependent on the survival parameters of the FMD virus during the cooking or heat treatment at garbage processing facility. Uncertainty about the proportion of garbage that is likely contaminated with FMD had a major positive influence on the risk, whereas conversion rate representing the size of a load had a major negative effect. This model was very useful in assessing the risk explored. However, the model also requires enhancements, such as the availability of more accurate data to verify the various assumptions considered such as FMD prevalence in a specific country, proportion of garbage which is recycled as feed, proportion of food discarded as garbage. Other factors including the effect of selection of animals for slaughter, ante- and post-mortem inspection, the domestic distribution of the smuggled products, and susceptible animals other than pigs, are need to be taken into account in the future model development.

• Spatial Information Research
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• v.19 no.2
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• pp.29-36
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• 2011

This study performed quantitative assessment of the performance of adjustment models by a-priori analysis of the statistics of the surface parameter estimates against modeling factors. Lidar, airborne imagery, and SAR imagery have been used to acquire the earth surface elevation, where the shape properties of the surface need to be determined through neighboring observations around target location. In this study, parameters which are selected to be estimated are elevation, slope, second order coefficient. In this study, several factors which are needed to be specified to compose adjustment models are classified into three types: mathematical functions, kernel sizes, and weighting types. Accordingly, a-priori standard deviations of the parameters are computed for varying adjustment models. Then their corresponding confidence regions for both the standard deviation of the estimate and the estimate itself are calculated in association with probability distributions. Thereafter, the resulting confidence regions are compared to each other against the factors constituting the adjustment models and the quantitative performance of adjustment models are ascertained.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.274-281
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• 2019

Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

• Journal of Nutrition and Health
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• v.54 no.1
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• pp.95-103
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• 2021

Purpose: High intake of cholesterol leads to cardiovascular disruption. Estimating the actual intake of cholesterol can be beneficial for nutrition intervention. This research aimed to develop Semi-Quantitative Food Frequency Questionnaire (SQ-FFQ) to estimate cholesterol intake and analyze its reliability and validity. Methods: SQ-FFQ was developed by sorting high cholesterol food items in Indonesian food database and food items' availability. A total of 30 older adults were randomly chosen from Public Health Center in Jagir District, Surabaya, Indonesia to test its validity. Reliability test was done by measuring the same developed SQ-FFQ in one-month period, while validity test was done by comparing SQ-FFQ results with 6-days food record. Statistical analysis used for reliability test was paired t-test, the Intra-class Correlation Coefficient (ICC), and Cronbach's α to measure the internal consistency. Meanwhile, validity of developed SQ-FFQ was analyzed using paired t-test and Bland-Altman. Results: Reliability of 2 administered SQ-FFQs showed a good agreement based on paired t-test analysis (p = 0.200), ICC (0.609), and Cronbach's α (0.757). Strong agreement was found in most of food items, but agreements for egg yolk and fried duck were poor. Significant difference was found between those food items (p = 0.001 vs. p < 0.001, respectively) with mean difference were -25.3 mg and 46.2 mg. Validity of developed SQ-FFQ2 compared to 6-days food diary records also found a strong agreement based on paired t-test and the Bland-Altman analysis. Conclusion: This baseline research provides a reasonably valid and repeatable measure of cholesterol intake estimation that can be widely used in nutrition and public health study, especially in Indonesia. No study has been conducted in Indonesia on the development of tools to estimate the cholesterol intake.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.495-506
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• 2021

A Conceptual cost estimate, which is computed in the preliminary step of a project, is important for decision-making by a contractor in terms of the project budget, economic feasibility and validity analysis, and alternative comparisons. Therefore, a high error rate of a prediction model for a conceptual cost estimate can lead to various problems including excessive project expenditures and a delayed break-even point. this study proposed optimal impact factors by configuring quantitative impact factors computable in a preliminary step in various cases(combinations of impact factors). subsequently, the accuracy of different cases was comparatively analyzed by using the cases as input values of a prediction model using regression analysis. when the optimal combination of impact factors proposed in this study and other combination of impact factors were applied to the prediction model, the regression analysis-based prediction model exhibited 0.2-4.7% improvements in accuracy, respectively. the optimal combination of impact factors proposed in this study improved the accuracy of the prediction model of a conceptual cost estimate by removing unnecessary impact factor.