• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.142-147
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• 2005

A numerical study of evaluation of turbulence models for thermal striping phenomenon is performed. The turbulence models chosen in the present study are the two-layer model, the shear stress transport (SST) model and the V2-f model. These three models are applied to the analysis of the triple jet flow with the same velocity but different temperature. The unsteady Reynolds-averaged Navier-Stokes (URANS) equation method is used together with the SIMPLE algorithm. The results of the present study show that the temporal oscillation of temperature is predicted only by the V2-f model, and the accuracy of the mean velocity, the turbulent shear stress and the mean temperature is a little dependent on the turbulence model used. The the two-layer model and the SST model shows nearly the same capability of predicting the thermal striping and the amplitude of the temperature fluctuation is predicted best by the V2-f model.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.3
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• pp.230-234
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• 2009

As concrete ages, the surrounding environment is expected to have growing influences on the concrete. As all the impacts of the environment cannot be considered in the strength-estimating model of a nondestructive concrete test, the increase in concrete age leads to growing uncertainty in the strength-estimating model. Therefore, the variation of the model error increases. It is necessary to include those impacts in the probability model of concrete strength attained from the nondestructive tests so as to build a more accurate reliability model for structural performance evaluation. This paper reviews and categorizes the existing strength-estimating statistical models of nondestructive concrete test, and suggests a new form of the strength-estimating statistical models to properly reflect the model uncertainty due to aging of the concrete. This new form of the statistical models will lay foundation for more accurate structural performance evaluation.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.226-235
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• 1999

The purpose of this study is to present models for evaluation and selection of Electronic Commerce systems suppliers. The Major concern of management is that almost all decision problems have multiple, usually conflicting, criteria. The fuzzified multi-objective programming models are given to accommodate the aspiration level and satisfaction level of decision makers. The proposed models are classified into three types, that is, min-operator. additive and pre-emptive priority. Numerical Examples illustrating each type of model are presented and the implications of these models are discussed.

• Journal of the Korea Safety Management & Science
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• v.9 no.1
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• pp.145-156
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• 2007

This paper is to propose model classification and evaluation of measurement uncertainty. In order to obtain type A and B uncertainty, variety of measurement mathematical models are illustrated by example. The four steps to evaluate expanded uncertainty are indicated as following; First, to get type A standard uncertainty, measurement mathematical models of single, double, multiple, design of experiment and serial autocorrelation are shown. Second, to solve type B standard uncertainty measurement mathematical models of empirical probability distributions and multivariate are presented. Third, type A and B combined uncertainty, considering sensitivity coefficient, linearity and correlation are discussed. Lastly, expanded uncertainty, considering degree of freedom for type A, B uncertainty and coverage factor are presented with uncertainty budget. SPC control chart to control expanded uncertainty is shown.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.114-121
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• 2019

This paper presents a new benchmark system for visual odometry (VO) and monocular depth estimation (MDE). As deep learning has become a key technology in computer vision, many researchers are trying to apply deep learning to VO and MDE. Just a couple of years ago, they were independently studied in a supervised way, but now they are coupled and trained together in an unsupervised way. However, before designing fancy models and losses, we have to customize datasets to use them for training and testing. After training, the model has to be compared with the existing models, which is also a huge burden. The benchmark provides input dataset ready-to-use for VO and MDE research in 'tfrecords' format and output dataset that includes model checkpoints and inference results of the existing models. It also provides various tools for data formatting, training, and evaluation. In the experiments, the exsiting models were evaluated to verify their performances presented in the corresponding papers and we found that the evaluation result is inferior to the presented performances.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.82-89
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• 2023

Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.364-378
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• 2008

Data Envelopment Analysis(DEA) models can be used for performance evaluation on governmental funding projects for IT small and medium-sized enterprises associated with multiple-outputs/multiple-inputs. In order to enhance the accuracy of DEA efficiency scores, DEA models with exogenously fixed variables are required where the corporate competency is taken into account. Additionally, it is necessary to use multiple DEA basic as well as extended models so as to relax the restriction on the performance evaluation to relying on a single DEA model. In this study; 1)a DEA data structure is designed including exogenously fixed variables representing corporate asset, revenue and the number of employees at the point in time that the governmental funding project concerned is initiated; 2)DEA basic as well as extended models are established according to the DEA data structure presented abovementioned; and 3)a case study is illustrated with an empirical testbed dataset. As for the DEA basic models, CCR, BCC, Super-efficiency model are adopted. The DEA extended models are developed based on the models associated with noncontrollable and nondiscretionary variables. In the case study, it is explained a comparison of DEA models and also major numerical outcomes such as efficiency scores, ranks derived from each DEA model are integrated using Analytic Hierarchy Process(AHP) weights. Performance significance with DEA efficiency scores between technical categories are tested based not only on parametric but also nonparametric single-factor analysis of variance method.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.57-65
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• 2016

Threat evaluation is a process to estimate the threat score which enemy aerial threat poses to defended assets. The objective of threat evaluation is concerned with making an engagement priority list for optimal weapon allocation. Traditionally, the threat evaluation of massive air threats has been carried out by air defence experts, but the human decision making is less effective in real aerial attack situations with massive enemy fighters. Therefore, automation to enhance the speed and efficiency of the human operation is required. The automatic threat evaluation by air defense experts who will perform multi-variable judgment needs formal models to accurately quantify their linguistic evaluation of threat level. In this paper we propose a threat evaluation model by using a fuzzy rule-based inference method. Fuzzy inference is an appropriate method for quantifying threat level and integrating various threat attribute information. The performance of the model has been tested with a simulation that reflected real air threat situation and it has been verified that the proposed model was better than two conventional threat evaluation models.

• International Journal of Contents
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• v.8 no.2
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• pp.67-74
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• 2012

Technological substitution is the process by which a radical technology replaces the dominant technology in an industry. The processes of diffusion and substitution have been modeled extensively (Technology & innovation, 2010). However, the formulation of classical quantitative models encompasses only part of the theoretical space. These models impose many simplified constraints to the achievement of analytical resolution. The interior design organization needs to establish a set of technical system requirements by describing the scope of the accessibility needs of the organization against current technology use. Because of complicated design resources and ongoing advances in design technologies, design systems face the challenge of prioritizing new technologies for supporting. The problem is small design organization administration often displays a lack of concern toward the evaluation of technology integration. In this paper, I will identify the influence of a design organization's technology, and predict how future technology will inform, support, and potentially hinder productivity, culture, and work satisfaction within a design organization in the industry. In addition, I will use current design organizational behavior and leadership models to support my predictions. Finally, I will examine a proven approach to assist designers with evaluating technology integration in interior design organization. The goal is to develop a high quality, professional development scorecards for the evaluation. I will conduct both the evaluation of technology integration and CRM performance evaluation is recommended to assess the effectiveness of technology integration. Therefore, the evaluation of integration technologies oriented design hold the promise of solving the organization application integration challenge. The evaluation of integration technology is a significant pattern for processing such a vision. The careful selection of an integration technology for this purpose is crucial in contributing toward the success of such an interior design organization endeavor.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.113-132
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• 2021

This study is a new evaluation using the Arrhenius equation, which is known as the chemical reaction rate estimation equation, to evaluate the intrinsic and extrinsic value elements of patents as a model. The performance of the evaluation model was superior to the SVM, Logistic reg. and ANN models that were used as patent evaluation models in prior studies. In addition, there was a strong correlation between the predicted lifespan of the patent and the actual lifespan of the patent. These evaluation models may be used for evaluation purposes only, or if an evaluation is required, including a commercialization entity or technical characteristics.