• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1163-1169
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• 2004

An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.344-351
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• 1999

Stress analysis of bogie frame by using the finite element method has been performed for the various loading conditions according to the UIC (International Union of Railways) Code 615-4. Multiaxial fatigue damage models such as signed von Mises method and typical critical plane theories were reviewed, and multiaxial fatigue analysis program (MUFAP) has been developed. Fatigue analysis of bogie frame under multiaxial loading was performed by using MUFAP and finite element analysis results. The procedure developed in this study is considered to be useful for the life prediction in preliminary design stage of railway components under multiaxial loading conditions. 3-dimensional surface modeling, mesh generation and finite element analysis were performed by Pro-Engineer, MSC/PATRAN and MSC/NASTRAN, respectively, which were installed in engineering workstation.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1048-1064
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• 2005

Detection of specific compounds influencing food flavor quality is not easy. Electronic nose, comprised of electronic chemical sensors with partial specificity and appropriate pattern recognition system, is capable of recognizing simple and complex volatiles. It provides fast analysis with simple and straightforward results and is best suited for quality control and process monitoring of flavor in food industry. This review examines application of electronic nose in food analysis with brief explanation of its principle. Characteristics of different sensors and sensor drift. and solutions to related problems are reviewed. Applications of electronic nose in food industry include monitoring of fermentation process and lipid oxidation, prediction of shelf life, identification of irradiated volatile compounds, discrimination of food material origin, and quality control of food and processing by principal component analysis and neural network analysis. Electronic nose could be useful for quality control in food industry when correlating analytical instrumental data with sensory evaluation results.

• International Journal of Fluid Machinery and Systems
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• v.5 no.4
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• pp.143-151
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• 2012

Predicting the future condition of machine and assessing the remaining useful life are the center of prognostics. This paper contributes a new prognostic method based on grey model and survival probability. The first step of the method is building a normal condition model then determining the error indicator. In the second step, the survival probability value is obtained based on the error indicator. Finally, grey model coupled with one-step-ahead forecasting technique are employed in the last step. This work has developed a modified grey model in order to improve the accuracy of prediction. For evaluating the proposed method, real trending data of low methane compressor acquired from condition monitoring routine were employed.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.130-132
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• 2020

배터리 시스템은 어플리케이션의 대영화에 따른 데이터 저장공간 문제 및 연속적인 배터리 신뢰성 문제 해결을 위한 건전성 예측 및 관리기술 접목에 관한 문제에 직면해 있으며, 이러한 문제 해결을 위해서는 배터리 시스템 신호를 통해 추출 가능한 건전성 지표 수립이 중요하다. 본 논문은 건전성 지표를 물리적, 간접적 지표로써 정의하고, 사이클 노화 데이터를 통해 건전성 지표로써의 성능을 검증하였다.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1519-1519
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• 2001

The aim of this work was to test the feasibility of NIRS in analysing textural characteristics of “Pasta Filata” cheese during the shelf-life. For this purpose, 128 samples of “Pasta Filata” cheese, subdivided into two sets on the basis of the wax used to avoid mechanical damages (paraffin, biodegradable wax), were analysed by using an InfraAlyzer 500 (Bran+Luebbe). Analyses were performed at room temperature. Samples were cut into small cylinders (D=3.2 cm, height = 1 cm), in agreement with literature information. Data were processed by using Sesame Software (Bran+Luebbe). Samples were analysed, during the shelf-life, at 90 and 120 days. In parallel, textural characteristics were detected carrying out a compression method by using an Universal Testing Machine Instron model 4301 (Instron Corporation, Canton, Massachusetts). As compression probe was used a cylinder (D = 5.8 cm, height = 3.7 cm) and a speed rate of 20mm/min was applied. The load at 20 mm of compression was recorded on sample cylinders of 1.7 cm (D) by 2 cm (height). Qualitative analysis of full spectra showed the possibility to gather samples on the basis of the days of shelf-life. The textural characteristics of cheese during the shelf-life was evaluated by comparing NIRS data with rheological results. The best correlation was obtained applying MLR to the first derivative of normalized absorbance values at seven wavelengths. Load values were plotted against the NIR prediction values based on first derivatives. NIRS proved to be an useful tool in classifying samples on the basis of the shelf-life period as well as in predicting their textural characteristics ($R^2$= 0.916, SEC = 0.192, SEP = 0.248, SEV = 0.345).

• Bulletin of the Korean Chemical Society
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• v.32 no.6
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• pp.2008-2014
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• 2011

Serotonin or 5-hydroxytryptamine subtype 2C ($5-HT_{2C}$) receptor belongs to class A amine subfamily of G-protein-coupled receptor (GPCR) super family and its ligands has therapeutic promise as anti-depressant and -obesity agents. So far, bovine rhodopsin from class A opsin subfamily was the mostly used X-ray crystal template to model this receptor. Here, we explained homology model using beta 2 adrenergic receptor (${\beta}$2AR), the model was energetically minimized and validated by flexible ligand docking with known agonists and antagonists. In the active site Asp134, Ser138 of transmembrane 3 (TM3), Arg195 of extracellular loop 2 (ECL2) and Tyr358 of TM7 were found as important residues to interact with agonists. In addition to these, V208 of ECL2 and N351 of TM7 was found to interact with antagonists. Several conserved residues including Trp324, Phe327 and Phe328 were also found to contribute hydrophobic interaction. The predicted ligand binding mode is in good agreement with published mutagenesis and homology model data. This new template derived homology model can be useful for further virtual screening based lead identification.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.214-221
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• 1999

Spot welding is very important and useful technology in fabriaction of the thin sheet structure such as the automobile, train and air craft, Because fatigue strength of the spot welding point is however considerably lower than base metal due to stress concentration at the nugget edge, reasonable fatigue strength evaluation of spot welded lap joint is very important to estimate the reliability and durability of th spot welded structure and to establish a criterion of ling life fatigue design. For reasonalbe fatigue strength evaluation, it is necessary to estimate the fatigue strength of spot welded lap joints, systematically. So far, many investigators have numerically and experimentally studied on the systematic fatigue strength estimation for various spot welded lap joints, and the methods suggested has been considerably accumulated. By the way, for applying them in practical fatigue design of the thin sheet structure fabricated by spot welding ,it is also necessary to verify their efficiency and reliability on the predicted results, Therefore, in this study, a statistical fatigue strength estimation method for spot welded lap joints was developed by using the Weibull probability distribution function. From the result, it was found that fatigue strength and fatigue life of the spot welded lap joints having various dimension were able to be statically predicted . And also, a reliable criterion for long life fatigue design of the spot welded lap joint could be established.

• Journal of Ginseng Research
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• v.39 no.2
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• pp.141-147
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• 2015

Background: Adipocytes, which are the main cellular component of adipose tissue, are the building blocks of obesity. The nuclear hormone receptor $PPAR{\gamma}$ is a major regulator of adipocyte differentiation and development. Obesity, which is one of the most dangerous yet silent diseases of all time, is fast becoming a critical area of research focus. Methods: In this study, we initially aimed to investigate whether the ginsenoside Rf, a compound that is only present in Panax ginseng Meyer, interacts with $PPAR{\gamma}$ by molecular docking simulations. After we performed the docking simulation the result has been analyzed with several different software programs, including Discovery Studio, Pymol, Chimera, Ligplus, and Pose View. All of the programs identified the same mechanism of interaction between $PPAR{\gamma}$ and Rf, at the same active site. To determine the drug-like and biological activities of Rf, we calculate its absorption, distribution, metabolism, excretion, and toxic (ADMET) and prediction of activity spectra for substances (PASS) properties. Considering the results obtained from the computational investigations, the focus was on the in vitro experiments. Results: Because the docking simulations predicted the formation of structural bonds between Rf and $PPAR{\gamma}$, we also investigated whether any evidence for these bonds could be observed at the cellular level. These experiments revealed that Rf treatment of 3T3-L1 adipocytes downregulated the expression levels of $PPAR{\gamma}$ and perilipin, and also decreased the amount of lipid accumulated at different doses. Conclusion: The ginsenoside Rf appears to be promising compound that could prove useful in antiobesity treatments.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1481-1489
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• 2021

Objective: To construct a CT-based Fagotti scoring system by analyzing the correlations between laparoscopic findings and CT features in patients with advanced ovarian cancer. Materials and Methods: This retrospective cohort study included patients diagnosed with stage III/IV ovarian cancer who underwent diagnostic laparoscopy and debulking surgery between January 2010 and June 2018. Two radiologists independently reviewed preoperative CT scans and assessed ten CT features known as predictors of suboptimal cytoreduction. Correlation analysis between ten CT features and seven laparoscopic parameters based on the Fagotti scoring system was performed using Spearman's correlation. Variable selection and model construction were performed by logistic regression with the least absolute shrinkage and selection operator method using a predictive index value (PIV) ≥ 8 as an indicator of suboptimal cytoreduction. The final CT-based scoring system was internally validated using 5-fold cross-validation. Results: A total of 157 patients (median age, 56 years; range, 27-79 years) were evaluated. Among 120 (76.4%) patients with a PIV ≥ 8, 105 patients received neoadjuvant chemotherapy followed by interval debulking surgery, and the optimal cytoreduction rate was 90.5% (95 of 105). Among 37 (23.6%) patients with PIV < 8, 29 patients underwent primary debulking surgery, and the optimal cytoreduction rate was 93.1% (27 of 29). CT features showing significant correlations with PIV ≥ 8 were mesenteric involvement, gastro-transverse mesocolon-splenic space involvement, diaphragmatic involvement, and para-aortic lymphadenopathy. The area under the receiver operating curve of the final model for prediction of PIV ≥ 8 was 0.72 (95% confidence interval: 0.62-0.82). Conclusion: Central tumor burden and upper abdominal spread features on preoperative CT were identified as distinct predictive factors for high PIV on diagnostic laparoscopy. The CT-based PIV prediction model might be useful for patient stratification before cytoreduction surgery for advanced ovarian cancer.