• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.13-21
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• 2004

The thermal-hydraulic model ARTS which was based on the RETRAN-3D code adopted in the domestic full-scope power plant simulator which was provided in 1998 by KEPRI. Since ARTS is a generalized code to model the components with control volumes, the smaller time-step size should be used even if converged solution could not get in a single volume. Therefore, dedicated models which do not force to reduce the time-step size are sometimes more suitable in terms of a real-time calculation and robustness. In the case of PRT(Pressurizer Relief Tank) model, it is consist of subcooled water in bottom and non-condensable gas in top. The sparger merged under subcooled water enhances condensation. The complicated thermal-hydraulic phenomena such as condensation, phase separation with existence of non-condensable gas makes difficult to simulate. Therefore, the PRT volume can limit the time-step size if we model it with a general control volume. To prevent the time-step size reduction due to convergence failure for simulating this component, we developed a dedicated model for PRT. The dedicated model was expected to provide substantially more accurate predictions in the analysis of the system transients. The results were resonable in terms of accuracy, real-time simulation, robustness and education of operators, complying with the ANSI/ANS-3.5-1998 simulator software performance criteria and RETRAN-3D results.

• Transactions of Materials Processing
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• v.22 no.7
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• pp.394-400
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• 2013

Microforming is a very efficient and economical technology to fabricate very small metallic parts in various applications. In order to extend the use of this forming technology for the production of microparts, the size effect, which occurs with the reduction of part size and affects the forming process significantly, must be thoroughly investigated. In this study, the tribological size effect in microforming was studied using modeling and scaled ring compression experiments. A micro-scale friction approach based on the slip-line field theory and lubricant pocket model was used to understand the friction mechanism and explain the tribological size effect. Ring compression tests were performed to analyze the interfacial friction condition from the deformation characteristics of the ring specimens. In addition, finite element analysis results were utilized to quantitatively determine the size-dependent frictional behavior of materials in various process conditions. By comparing theoretical results and experimental measurements for different size factors, the accuracy and reliability of the model were verified.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.45-60
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• 2017

The study suggests a contract model of application operation through case study of A bank's IT outsourcing application contract based on workload. The IT outsourcing order form has a problem in that the scope of work is ambiguous due to the integration of operation and maintenance. In this study, application operation and maintenance were separated by referring to application operation history provided in ISO/IEC15504-5 standard. The scope of the IT outsourcing service was clarified by organizing the definition and detail activities of the application operation business. Application operation contract method has generally applied estimation method by the number of input manpower and period by agreement between buyer and client. As there is no activity to calculate the number of input manpower based on the operational work history and based on the standard workload per activity. In this case is not guaranteed due to the simple agreement between the contractors. In this paper, we propose an application operating cost estimation model that measures the size of the operating software using function point analysis that is the basis of application operation tasks. In order to verify the validity of the application operation cost model, we verified the correlation between the application size and the labor cost through regression analysis using SPSS.

• Journal of the Korean Society of Safety
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• v.18 no.1
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• pp.64-70
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• 2003

For the unconfined vapor cloud explosion(UVCE) accident by the continuous release of gas-liquid flow of various saturated liquids in a vessel at ground level, overpressures were estimated by TNT equivalency model with two estimation methods, such as UVCE I model based on a constant release time and UVCEII model based on a real travel time of vapor by dispersion and analyzed with various release conditions. As a simulation result the simple, easy, and correct method of evaluation of consequences of the UVCE accident was proposed by using consequences of UVCE I model and correlation equations for differences of overpressures between UVCE models, so that this evaluation method could be used easily in the small and medium size enterprises without using the dispersion model.

• Fashion & Textile Research Journal
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• v.13 no.2
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• pp.205-214
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• 2011

The purpose of this study is to develop a size information providing model which is easy recognition and utilization for customer. This study also implemented web page to apply the size-informational model. Web page implemented using Apache Web Server and JAVA client-side scripting. Research result on the actual condition of fashion electronic commerce, most of the firms are used the old named same with period of 1980. On the same named-code, they are used different sizing systems by firms or items. Size interval is used 2~5 cm, different by firms. In the size information, is provided only named-code(55, 66 etc.) or garment size, and is confusing whether the marked is body size or garment size. Many of the marked size information were wrong. The sizing system of KS K5001(2009) is not used well. These problems are increased a lose customer and firm by return, exchange, mending-cost, stock, etc. Therefore, the problems should be improved by providing correct and detailed information of size and garment, as well as standardization of sizing systems based on KS K5001.

• IE interfaces
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• v.17 no.1
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• pp.1-12
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• 2004

In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2960-2967
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• 2021

In this work, a new hardening model is proposed for the depth-dependent hardness of ion-irradiated polycrystals with obvious grain size effect. Dominant hardening mechanisms are addressed in the model, including the contribution of dislocations, irradiation-induced defects and grain boundaries. Two versions of the hardening model are compared, including the linear and square superposition models. A succinct parameter calibration method is modified to parametrize the models based on experimentally obtained hardness vs. indentation depth curves. It is noticed that both models can well characterize the experimental data of unirradiated polycrystals; whereas, the square superposition model performs better for ion-irradiated materials, therefore, the square superposition model is recommended. In addition, the new model separates the grain size effect from the dislocation hardening contribution, which makes the physical meaning of fitted parameters more rational when compared with existing hardness analysis models.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• International Journal of Ocean System Engineering
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• v.2 no.3
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• pp.170-175
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• 2012

Currently, most logistics use containers. The construction of new port and high speed medium size container ship for the transportation of merchandise have become very important. The problem of ship stability is also important because of its direct influence on the loss of human life, ships, and merchandise. The stability of a container ship during its operation is not a large problem because it is well considered in the design process. However, the assessment of ship stability during container loading/unloading in port still depends on the expertise of experienced personnel. In this paper, a model based simulation system is introduced, which is able to assess ship stability during container loading/unloading, using ENVISION, a general purpose simulation system.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.184-196
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• 2021

This paper proposes statistics adaptive linear regression-based object size prediction method for object detection. YOLOv2 and YOLOv3, which are typical deep learning-based object detection algorithms, designed the last layer of a network using statistics adaptive exponential regression model to predict the size of objects. However, an exponential regression model can propagate a high derivative of a loss function into all parameters in a network because of the property of an exponential function. We propose statistics adaptive linear regression layer to ease the gradient exploding problem of the exponential regression model. The proposed statistics adaptive linear regression model is used in the last layer of the network to predict the size of objects with statistics estimated from training dataset. We newly designed the network based on the YOLOv3tiny and it shows the higher performance compared to YOLOv3 tiny on the UFPR-ALPR dataset.