• Genomics & Informatics
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• v.16 no.4
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• pp.32.1-32.7
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• 2018

Ovarian cancer is one of the leading causes of cancer-related deaths in gynecological malignancies. Over 70% of ovarian cancer cases are high-grade serous ovarian cancers and have high death rates due to their resistance to chemotherapy. Despite advances in surgical and pharmaceutical therapies, overall survival rates are not good, and making an accurate prediction of the prognosis is not easy because of the highly heterogeneous nature of ovarian cancer. To improve the patient's prognosis through proper treatment, we present a prognostic prediction model by integrating high-dimensional RNA sequencing data with their clinical data through the following steps: gene filtration, pre-screening, gene marker selection, integrated study of selected gene markers and prediction model building. These steps of the prognostic prediction model can be applied to other types of cancer besides ovarian cancer.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.5
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• pp.832-836
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• 2013

To develop a predictive model for the shelf-life of fish cake, fish cake was stored at 30, 35, or $40^{\circ}C$ and populations of total aerobic bacteria were determined during storage. Gompertz model parameters were determined and their dependence on temperature formulated as a quadratic equation for applications toward shelf-life prediction. The predicted shelf-life values for fish cake used in this study were 6.9, 5.5, and 3.8 days at 0, 4, and $10^{\circ}C$, respectively. The shelf-life prediction equation was appropriate based on statistical analyses that reveal accuracy and bias factors. These results suggest that our prediction model is applicable for estimating the shelf-life of fish cake.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.62-70
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• 2023

We proposed a technique for predicting Stress-Life (S-N) curve or fatigue life using geometric features of a ply-overlap joint structure in which plies of two composite materials are partially or wholly laminated and bonded. Geometric features that could affect fatigue properties of a structure were selected as variables. By analyzing relationships between geometric variables and material constants of the Epaarachchi-Clausen model, a fatigue model for composites, relational expressions of these two factors were proposed. To verify the prediction accuracy of the proposed method, fatigue life of a CFRP/GFRP ply-overlap joint was predicted. Predicted life and life obtained by test data-based model were compared to actual life. High prediction accuracy was confirmed by calculating the coefficient of determination of the predicted S-N curve.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.94-100
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• 2004

A dynamic finite element analysis of a rig test model for truck chassis systems is conducted to establish an appropriate model designed to predict the fatigue life. A reference Belgian road input, which has been obtained from a field test, is imposed on the finite element model in the modal finite element analysis, and the resulting strain history is employed for the prediction of the fatigue life. This is compared with the prediction based upon the strain history measured in the field test. The two agree with each other within the limitation of the field data and the input data to the model. The high frequency responses over 50 Hz are confirmed to be negligible as far as their effect on the fatigue life is concerned.

• Journal of Power System Engineering
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• v.21 no.1
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• pp.43-49
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• 2017

This work aims to investigate on the low cycle fatigue life assessment, which is adopted on the strain-life relationship, or better known as the Coffin-Manson relationship, and also the strain energy density-based model. The low cycle fatigue test results of Alloy 617 weldments under $900^{\circ}C$ have been statistically estimated through the Coffin-Manson relationship according to the provided strain profile. In addition, the strain energy density-based model is proposed to represent the energy dissipated per cycle as fatigue damage parameter. Based on the results, Alloy 617 weldments followed the Coffin-Manson relationship and strain energy density-based model well, and they were compatible with the experimental data. The predicted lives based on these two proposed models were examined with the experimental data to select a proper life prediction parameter.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.6
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• pp.533-542
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• 2014

In this study TBM disc cutter prediction models including Gehring, CSM and NTNU models were investigated and the characteristics of the models were examined. The influence of penetration, uniaxial compressive strength and abrasiveness index on the models was analyzed. The life of disc cutter linearly increases with penetration per revolution and decreases with increasing uniaxial compressive strength of rocks. As the abrasiveness index, CAI, increases, the life of disc cutter in Gehring and CSM model decreases. On the contrary, the life of disc cutter life in NTNU model decreases with increasing CLI. Also, comparisons of predicted disc life were made between models using actual job site data.

• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.19-24
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• 2016

Rubber parts are widely used in many applications such as dampers, shock absorbers, and seals used in railway and automotive industries. Much research has thus far been conducted on property estimation and life prediction of rubber parts. To predict the service life of rubber parts at room temperature, most prior work adopts the well-known Arrhenius model that needs the accelerated life test in high-temperature conditions. However, they may not reflect the actual conditions of use that rubber parts are usually used under a specific strain condition during long period of time. In this context, we propose a method for the life prediction of rubber parts in actual conditions of use. The proposed method is based on the accelerated life test using stress relaxation during which three relatively high elongation percentages (100%, 200%, and 300%) are applied to the rubber specimens. Rubber specimens were prepared in accordance with KS M 6518 standard and three stress relaxation testers were fabricated for actual experiments. Finally, a inverse power model for life prediction was derived from experimental results. The predicted life was compared with the actual test life for validation.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.8
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• pp.71-76
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• 2002

In this study low cycle fatigue (LCF) behavior of 12Cr steel at high temperature are described. Secondly, comparisons between predicted lives and experimental lives are made for the several sample life prediction models. Two minute hold period in either tension or compression reduce the number of cycles to failure by about a factor of two. Twenty minute hold periods in compression lead to shorter lives than 2 minute hold periods in compression. Experiments showed that life predictions from classical phenomenological models have limitations. More LCF experiments should be pursued to gain understanding of the physical damage mechanisms and to allow the development of physically-based models which can enhance the accuracy of the predictions of components. From a design point-of-view, life prediction has been judged acceptable for these particular loading conditions but extrapolations to thermo-mechanical fatigue loading, for example, require more sophisticated models including physical damage mechanisms.

• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.67-72
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• 2000

A dynamic draft model is necessary to analyze mechanics of tillage and to design optimal tillage tools. In order to deal with draft dynamics, a neural network paradigm was applied to develop dynamic draft models. For the development of the models, three kinds of tillage tools were used to measure drafts in the soil bin and a time lagged recurrent neural network was developed. The neural network had a structure to predict dynamic draft, having a function of one-step-ahead prediction. A procedure for network prediction model identification was established. The results show promising modeling of the dynamic drafts with developed neural network.

• Journal of the Korean Home Economics Association
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• v.30 no.4
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• pp.153-165
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• 1992

The objectives of this study were to develop a probabilistic model for both hypotheses testing and mobility prediction. Methodologies being used for the analysis include multivariated analysis for descriptive statistics and logit model for hypotheses testing and prediction. The study used questionaire survey data conducted by Korean Research Institute for Human Settlements (KRIHS) in 1988. There were a total of 1,620 Samples, and both SPSS and Limdep software packages were used for statistical analysis and model testing. The major findings were highlighted as follows; The residential mobility over family life span by the social class were developed with the use of the probability model. Most of households in low class moved downwardly. They had lived the small-owned single detached house in first family life span and moved into the small-rented single detached house in next family life span. Most of households in middle class moved upwardly. They had lived the small-owned apartment in first family life span and moved into the large-owned single detached house in last family life span. Most of households in high class horizontally. They had lived the large-owned single detached house in first family life span and moved into the same one except in last family life span.