• Journal of Ecology and Environment
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• v.38 no.4
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• pp.485-491
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• 2015

This study was conducted to develop stem volume models for the volume estimation of Quercus glauca Thunb. in Jeju Island, Republic of Korea. Furthermore, this study validated the developed stem volume models using an independent dataset. A total of 167 trees were measured for their diameter at breast height (DBH), total height and stem volume using non-destructive sampling methods. Eighty percent of the dataset was used for the initial model development while the remaining 20% was used for model validation. The performance of the different models was evaluated using the following fit statistics: standard error of estimate (SEE), mean bias absolute mean deviation (AMD), coefficient of determination (R²), and root mean square error (RMSE). The AMD of the five models from the different DBH classes were determined using the validation dataset. Model 5 (V = aD^bH^c), which estimates volume using DBH and total height as predicting variables, had the best SEE (0.02745), AMD (0.01538), R² (0.97603) and RMSE (0.02746). Overall, volume models with two independent variables (DBH and total height) performed better than those with only one (DBH) based on the model evaluation and validation. The models developed in this study can provide forest managers with accurate estimations for the stem volumes of Quercus glauca in the subtropical forests of Jeju Island, Korea.

• Toxicological Research
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• v.21 no.1
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• pp.1-14
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• 2005

Transgenic mouse models have been introduced and accepted by regulatory bodies as an alternative to carcinogenicity assay models to predict and evaluate chemical carcinogens. The recent research outcomes in transgenic mouse models have made progressive advances in the understanding of chemical carcinogenesis and the evaluation of potential human carcinogens. However, these models still remain to be insufficient assay systems although the insufficiencies have been recognised and are being resolved. Based on up to date information from literature, this review article intends to understand currently accepted transgenic mouse models, issues arising from study design, interpretation of the study, results of validation project and their cancer prediction rate, and further perspectives of cancer assay models from the regulatory view point.

• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.101-110
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• 2007

This study developed a new model for evaluating activities related to PL(Product Liability), with which our domestic enterprises can more easily assess the actual status of the management of PL than as they could do before. In addition, this model was designed to make the evaluation can be done focusing on the Product safety management cycle, unlike the other PL evaluation models. This model consists of 3 evaluation domains such as evaluations of planning, implementation, and assessment and taking action regarding product safety management. In order to verify that this evaluation model meets its objectives, the researcher directly conducted evaluations of activities related to PL in 3 companies specializing in electric home appliances through visiting them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1113-1135
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• 2018

Existing trust evaluation models for wireless sensor networks can accurately and objectively evaluate trust value of nodes, but the nodes' energy saving problem was ignored. Especially when there are a few malicious nodes in a network, the overall trust value calculation for all nodes would waste lots of energy. Beside that, the network failure caused by nodes death was also not considered. In this paper, we proposed a method for avoiding energy hole which applied trust evaluation models and a trust evaluation method based on information entropy, so as to achieve the purpose of improving nodes utilization. Simulation results show that the proposed method can effectively improve nodes utilization, and it has reasonable detection rate and lower false alert rate compared to other classical methods.

• Geomechanics and Engineering
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• v.13 no.2
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• pp.237-254
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• 2017

Estimation of slope stability is a very important task in geotechnical engineering. However, its estimation using conventional and soft computing methods has several drawbacks. Use of conventional limit equilibrium methods for the evaluation of slope stability is very tedious and time consuming, while the use of soft computing approaches like Artificial Neural Networks and Fuzzy Logic are black box approaches. Multiple Regression (MR) analysis provides an alternative to conventional and soft computing methods, for the evaluation of slope stability. MR models provide a simplified equation, which can be used to calculate critical factor of safety of slopes without adopting any iterative procedure, thereby reducing the time and complexity involved in the evaluation of slope stability. In the present study, a multiple regression model has been developed and tested its accuracy in the estimation of slope stability using real field data. Here, two separate multiple regression models have been developed for dry and wet slopes. Further, the accuracy of these developed models have been compared and validated with respect to conventional limit equilibrium methods in terms of Mean Square Error (MSE) & Coefficient of determination ($R^2$). As the developed MR models here are not based on any region specific data and covers wide range of parametric variations, they can be directly applied to any real slopes.

• Journal of the Korean GEO-environmental Society
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• v.16 no.5
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• pp.13-25
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• 2015

This paper proposes an extended model evaluation method that considers not only the model performance but also the model structure and parameter uncertainties in hydrologic modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250-m, 500-m, and 1-km digital elevation models) were developed and assessed by three evaluative criteria for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. Moreover, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. A number of parameter sets could result in indistinguishable hydrographs. This result indicates that while making hydrologic models complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty.

• KIEAE Journal
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• v.10 no.1
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• pp.65-72
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• 2010

The use of natural light has the potential for improving both the energy efficiency and indoor environmental quality in buildings. A light-pipe system can introduce daylight to spaces that would otherwise not be able to benefit from the advantages of daylight penetration. For the light-pipe system to be widely used in Korea, it is important to quantify its daylighting performance with due consideration regarding the effects imposed by the local climate conditions. This paper presents the evaluation results of existing semi-empirical models to predict daylighting performance of a light-pipe system. The evaluation of the existing models was based on the monitoring data obtained from a underground parking lot in which the light-pipe system was installed. Comparisons were made between the predicted and the monitored data obtained from the study. The results indicated that semi-empirical models which was developed using the experimental data obtained under the Korean climatic conditions had a good prediction performance. We also quantified the effects caused by sky conditions, solar altitudes, room dimensions, and the aspect ratio of a light-pipe system on both the daylighting performance of the light-pipe system and the indoor illuminance distributions of the space using the semi-empirical model. Finally, this paper provides the design guideline of the light-pipe system for its application to an underground parking lot space.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.186-189
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• 2006

Since the columns with flexure-shear failure have lower ductility than those with flexural failure, shear capacity curve models shall be applied as well as flexural capacity curve in order to determine ultimate displacement for seismic design or performance evaluation. In this paper, a proposed modified shear capacity curve model is compared with the other models such as the CALTRANS model, Aschheim et al.'s model, and Priestley et al.'s model. Four shear capacity curve models are applied to the 4 full scale and 7 small scale circular bridge column test results and the accuracy of each model is discussed. It may not be fully adequate to drive a final decision from the application to the limited number of test results, however the proposed model provides the better prediction of failure mode and ultimate displacement than the other models for the selected column test results.

• 한국전산유체공학회:학술대회논문집
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• 2004.10a
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• pp.221-225
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• 2004

Evaluation of turbulence models is performed for a better prediction of thermal stratification in an upper plenum of a liquid metal reactor by applying them to the experiment conducted at JNC. The turbulence models tested in the present study are the two-layer model, the $\kappa-\omega$ model, the v2-f model and the low-Reynolds number differential stress-flux model. When the algebraic flux model or differential flux model are used for treating the turbulent heat flux, there exist little differences between turbulence models in predicting the temporal variation of temperature. However, the v2-f model and the low-Reynolds number differential stress-flux model better predict the steep gradient o( temperature at the interface of thermal stratification, and only the v2-f model predicts properly the oscillation of temperature. The LES Is needed for a better prediction of the amplitude and frequency of the temperature fluctuation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.120-128
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• 1993

In this paper, an implementation of high-speed parallel processing system for neural network design on the multicomputer network is presented. Linear speedup expandability is increased by reducing the synchronization penalty and the communication overhead. Also, we presented the parallel processing models and their performance evaluation models for each of the parallization methods of the neural network. The results of the experiments for the character recognition of the neural network bases on the proposed system show that the proposed approach has the higher linear speedup expandability than the other systems. The proposed parallel processing models and the performance evaluation models could be used effectively for the design and the performance estimation of the neural network on the multicomputer network.