• 한국식품과학회지
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• 제38권4호
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• pp.589-593
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• 2006

돈육 가공 공정에 대한 QRA에 Monte Carlo simulation이 적용된 바 있는데, 새로운 방법으로 fuzzy 연산을 적용하여 Monte Carlo simulation과 비교 분석하였다. Carcass단계에 대한 오염 예측치인 fuzzy 값과 Monte Carlo simulation 확률분포 값의 기술통계량인 평균값은 각각 -4.393 log $CFU/cm^2$, -4.589 log $CFU/cm^2$ 로 나타났으며, processing 단계에서는 -4.185 log $CFU/cm^2$, -4.466 log $CFU/cm^2$으로 두 가지 접근 방법들이 비슷한 경향을 보였다. Fuzzy 값은 Monte Carlo simulation 확률분포 값을 포함하는 것으로 나타났다. 한편 최근 국내에서는 위해 평가에 대한 연구가 많이 이루어지고 있는데 대부분 데이터 분석은 Monte Carlo simulation에만 의존하고 있고, 다른 접근 방법에 대한 연구는 미진한 실정이다. 따라서 본 연구는 위해 평가를 위한 방법적 도구들을 개발하는데 새로운 접근 방향을 제시하였다 또한 향후 fuzzy 연산법은 데이터가 불충분한 위해 평가의 초기 단계에서 유용하게 사용될 수 있는 방법이 될 것이다.

• 한국CDE학회논문집
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• 제18권1호
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• pp.21-27
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• 2013

Presented in the paper is a log data based modeling method for effective construction of a virtual plant model which can be used for the virtual PLC (Programmable Logic Controller) simulation. For the PLC simulation, the corresponding virtual plant, consisting of virtual devices, is required to interact with the input and output symbols of a PLC. In other words, the behavior of a virtual device should be the same as that of the real device. Conventionally, the DEVS (Discrete Event Systems Specifications) formalism has been used to represent the behavior a virtual device. The modeling using DEVS formalism, however, requires in-depth knowledge in the simulation area, as well as the significant amount of time and efforts. One of the key ideas of the proposed method is to generate a plant model based on the log data obtained from the production system. The proposed method is very intuitive, and it can be used to generate the full behavior model of a virtual device. The proposed approach was applied to an AGV (Automated Guided Vehicle).

• 한국가스학회지
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• 제20권1호
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• pp.13-22
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• 2016

본 연구에서는 다단계 수압파쇄와 수평시추가 적용된 셰일가스정에서 생산자료의 유동형태에 따라 적절한 분석 방법과 궁극가채량을 산출하는 기법을 결정하는 방법을 정리한 흐름도를 제안하였다. 또한 1차 천이유동만이 나타나는 현장자료에 대해 생산천이유동 분석을 수행할 때 고려해야 하는 사항들을 제안하였다. log-log 그래프와 시간제곱근 그래프 분석을 통해 생산자료의 유동 특성을 분류할 수 있고, 이 결과, 1차 천이유동만이 나타나는 생산자료는 이 유동이 종료되는 시점을 정확히 예측하여 이 시점을 기준으로 생산성을 각각 예측하여야 한다. 이 시점은 미세탄성파 탐사자료 해석을 통해 균열자극부피의 면적을 계산함으로써 산출할 수 있다. 공저압력자료나 미세탄성파 탐사자료가 없다면 셰일가스정에 적절한 경험적 방법을 활용하여 생산성을 예측할 수 있다. 생산기간이 짧은 자료는 상대적으로 생산기간이 긴 인접 생산정의 자료를 활용하여 생산기간의 적절성을 평가한 후 필요하다면 생산초기 자료를 제외하고 분석하는 것이 정확도를 향상시킬 수 있다. 또한 미세탄성파 탐사자료 해석에 의해 산출된 SRV는 분석방법이나 분석자의 주관에 의해 과대, 과소 평가될 수 있기 때문에 파쇄 단계, 파쇄유체 주입량, 생산성 분석을 통한 적절성평가를 수행하여 필요한 경우, 저류층 시뮬레이션, 균열모델링, 생산천이분석을 통해 재산정하는 것이 필요하다.

• 한국식품위생안전성학회지
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• 제13권3호
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• pp.278-293
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• 1998

본 연구는 학교급식에서 Cook/chill system으로 생산 가능한 음식으로 삼치구이를 선정하고 모의실험을 통해 급식생산체계를 반복 실시함으로서 식품 위해 분석 중요관리점(HACCP)을 규명하고, 저장기간중의 음식품질 평가를 통해 합리적인 저장기한을 설정하고자 수행되었으며, 그 연구결과는 다음과 같다. 심치 구이의 온도소요시간 측정 결과, 온도상승이 일어난 검수 단계를 제외하면 각 생산단계별 온도-소요 시간 기준이 준수된 양호한 상태 하에 삼치구이가 생산되었음을 알 수 있었다. 삼치구이의 생산단계별 미생물 분석 결과 , 중온성 표준평판 균수의 경우 원재료 ($2.58{\pm}0.12\;Log\;CFU/g$)에서 냉장보관($2.70{\pm}0.42\;Log\;CFU/g$)까지의 품질은 우수하였다. 양념장으로 재우는 과정($3.82{\pm}0.52\;Log\;CFU/g$)에서 반복 실험중 일차에서만 대장균군, 분변성 대장균군이 각각 0.84 Log MPN/g으로 검출되었다. $160^{\circ}C$, 10분의 습열 조리와 $180^{\circ}C$, 3분의 건열 조리를 통해 삼치구이 내부온도는 $76^{\circ}C$로 측정되었는데, 조리 직후 심치구이에서는 중온균 ($1.83{\pm}0.49\;Log\;CFU/g$)만 검출되었고 저온균, 대장균군, 분변성 대장균군은 검출되지 않았다. 급성 냉장과 저장 5일을 거치는 동안 중온균은 거의 검출되지 않았으며 나머지 분석대상 미생물도 검출되지 않았다. 재가열과 배분단계에서도 분석대상 미생물이 전혀 검출되지 않았다. 삼치구이 전 생산단계에 걸쳐 Salmonella 와 Listeria monocytogenes는 검출되지 않았다. 5일의 저장동안 분석된 삼치구이의 pH, 산가, 휘발성 염기질소(TVBN) 함량과 관능 평가 결과, 삼치구이의 저장기한은 4일 이내로 제안되었다. 규명된 CCPs는 삼치의 구입과 검수, 가열 조리, 냉각, 냉장, 재가열 및 배식 단계였다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

• Asian-Australasian Journal of Animal Sciences
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• 제29권8호
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• pp.1188-1196
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• 2016

This study evaluated the risk of Clostridium perfringens (C. perfringens) foodborne illness from natural and processed cheeses. Microbial risk assessment in this study was conducted according to four steps: hazard identification, hazard characterization, exposure assessment, and risk characterization. The hazard identification of C. perfringens on cheese was identified through literature, and dose response models were utilized for hazard characterization of the pathogen. For exposure assessment, the prevalence of C. perfringens, storage temperatures, storage time, and annual amounts of cheese consumption were surveyed. Eventually, a simulation model was developed using the collected data and the simulation result was used to estimate the probability of C. perfringens foodborne illness by cheese consumption with @RISK. C. perfringens was determined to be low risk on cheese based on hazard identification, and the exponential model ($r=1.82{\times}10^{-11}$) was deemed appropriate for hazard characterization. Annual amounts of natural and processed cheese consumption were $12.40{\pm}19.43g$ and $19.46{\pm}14.39g$, respectively. Since the contamination levels of C. perfringens on natural (0.30 Log CFU/g) and processed cheeses (0.45 Log CFU/g) were below the detection limit, the initial contamination levels of natural and processed cheeses were estimated by beta distribution (${\alpha}1=1$, ${\alpha}2=91$; ${\alpha}1=1$, ${\alpha}2=309$)${\times}$uniform distribution (a = 0, b = 2; a = 0, b = 2.8) to be -2.35 and -2.73 Log CFU/g, respectively. Moreover, no growth of C. perfringens was observed for exposure assessment to simulated conditions of distribution and storage. These data were used for risk characterization by a simulation model, and the mean values of the probability of C. perfringens foodborne illness by cheese consumption per person per day for natural and processed cheeses were $9.57{\times}10^{-14}$ and $3.58{\times}10^{-14}$, respectively. These results indicate that probability of C. perfringens foodborne illness by consumption cheese is low, and it can be used to establish microbial criteria for C. perfringens on natural and processed cheeses.

• Geomechanics and Engineering
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• 제15권1호
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• pp.677-686
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• 2018

Aimed at serious casing damage problem during the process of oilfield development by injecting water, based on seepage mechanics, fluid mechanics and the theory of rock mechanics, the multi-physics coupling theory was also taken into account, the mathematical model for production of petroleum with water flooding was established, and the method to solve the coupling model was presented by combination of Abaqus and Eclipse software. The Q9G3 block in Jibei oilfield was taken for instance, the well log data and geological survey data were employed to build the numerical model of Q9G3 block, the method established above was applied to simulate the evolution of seepage and stress. The production data was imported into the model to conduct the history match work of the model, and the fitting accuracy of the model was quite good. The main mechanism of casing damage of the block was analyzed, and some wells with probable casing damage problem were pointed out, the displacement of the well wall matched very well with testing data of the filed. Finally, according to the simulation results, some useful measures for preventing casing damage in Jibei oilfield was proposed.

• Asian-Australasian Journal of Animal Sciences
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• 제18권6호
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• pp.772-779
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• 2005

The objectives of this study were to examine problems with using F$_1$ data by simulation, association of marker loci and QTL from crosses of inbred parental lines and to enumerate the preliminary characterization of genetic superiority within inbred parental lines. In this study, the association between markers for QTL used as covariates and estimates of variance components due to effects of lines was investigated through computer simulation. The effects of size of population to develop inbred lines and initial frequencies and magnitudes of effects of QTL were also considered. Results show that estimates of variance components due to line effects are influenced by including marker information as covariates in the model for analysis. Estimates of line variance were increased by adding marker information into the analysis, because negative covariances between effects associated with the markers and the remaining effects associated with other loci existed. However, the fit of the model as indicated by the log likelihood improved by adding more markers as covariates into the analysis. Marker assisted selection will be beneficial when markers explain unexplained genetic difference during selection procedure. Markers can be used to identify QTLs affecting traits, and to select for favorable QTL alleles. To efficiently use genetic markers, location of markers at the genome must be identified. The estimates of variance due to effects of with and without marker information used as covariates in the analysis were investigated. The estimates of line variances were always increased when markers were included as covariates for the model because a negative covariance were existed.

• 환경영향평가
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• 제9권3호
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• pp.203-214
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• 2000

Health risk assessment is applied to streamlining LCA(Life Cycle Assessment) using Monte carlo simulation for probabilistic/stochastic exposure and risk distribution analysis caused by data variability and uncertainty. A case study was carried out to find benefits of this application. BTC(Benzene, Trichloroethylene, Carbon tetrachloride mixture alias) personal exposure cases were assumed as production worker(in workplace), manager(in office) and business man(outdoor). These cases were different from occupational retention time and exposure concentration for BTC consumption pattern. The result of cancer risk in these 3 scenario cases were estimated as $1.72E-4{\pm}1.2E+0$(production worker; case A), $9.62E-5{\pm}1.44E-5$(manger; case B), $6.90E-5{\pm}1.16E+0$(business man; case C), respectively. Portions of over acceptable risk 1.00E-4(assumed standard) were 99.85%, 38.89% and 0.61%, respectively. Estimated BTC risk was log-normal pattern, but some of distributions did not have any formal patterns. Except first impact factor(BTC emission quantity), sensitivity analysis showed that main effective factor was retention time in their occupational exposure sites. This case study is a good example to cover that LCA with probabilistic risk analysis tool can supply various significant information such as statistical distribution including personal/environmental exposure level, daily time activity pattern and individual susceptibility. Further research is needed for investigating real data of these input variables and personal exposure concentration and application of this study methodology.

• Asian-Australasian Journal of Animal Sciences
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• 제18권12호
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• pp.1675-1683
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• 2005

In the process of crossbreeding, the linkage disequilibria between the quantitative trait loci (QTL) and their linked markers were reduced gradually with increasing generations. To study the potential of QTL mapping using the crossbred population, we presented a mixed effect model that treated the mean allelic value of the different founder populations as the fixed effect and the allelic deviation from the population mean as random effect. It was assumed that there were fifty QTLs having effect on the trait variation, the population mean and variance were divided to each QTL in founder generation in our model. Only the additive effect was considered in this model for simulation. Six schemes (S1-S6) of crossbreeding were studied. The selection index was used to evaluate the synthetic breeding value of two traits of the individual in the scheme of S2, S4 and S6, and the individuals with high selection index were chosen as the parents of the next generation. Random selection was used in the scheme of S1, S3 and S5. In this study, we premised a QTL explained 40% of the genetic variance was located in a region of 20 cM by the linkage analysis previously. The log likelihood ratio (log LR) was calculated to determine the presence of a QTL at the particular chromosomal position in each of the generations from the fourth to twentieth. The profiles of log LR and the number of the highest log LR located in the region of 5, 10 and 20 cM were compared between different generations and schemes. The profiles and the correct number reduced gradually with the generations increasing in the schemes of S2, S4 and S6, but both of them increased in the schemes of S1, S3 and S5. From the results, we concluded that the crossbreeding population undergoing random selection was suitable for improving the resolution of QTL mapping. Even experiencing index selection, there was still enough variation existing within the crossbred population before the fourteenth generation that could be used to refine the location of QTL in the chromosome region.