• Journal of Korea Trade
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• 제25권4호
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• pp.88-107
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• 2021

Purpose - Using a model that highlights Ricardian comparative advantage and Cournot competition, I derive theoretical predictions on how bilateral measures of trade intensity, specialization, and intra-industry are interrelated, and how Ricardian productivity differences affect these measures. We test the predictions using trade and production data, and confirm them. Design/methodology - A simple two-country general equilibrium model is constructed to derive theory-based bilateral indexes. We then test the relationships among them using panel data for 35 countries and 14 industries between 1996 and 2008. Findings - Bilateral trade intensity is increasing in specialization, as in the classical trade theory, and in intra-industry trade, as in the new trade theory. However, productivity differences positively affect specialization, and negatively affect intra-industry trade. These effects cancel each other; thus productivity differences have little impact on trade intensity. Originality/value - This paper provides a comprehensive conceptual framework for understanding the relationship among trade intensity, specialization, intra-industry trade, and productivity differences. We derive theory-consistent measures of specialization, intra-industry trade, and productivity differences. Moreover, we reevaluate the empirical relevance of these variables for the study of gravity equations. This paper is also an effort to capture oligopolistic competition in a general equilibrium framework, interests in which recently resurged.

• Steel and Composite Structures
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• 제43권3호
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• pp.403-417
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• 2022

Recently, there has been an increasing demand for buildings that allow rapid assembly of construction elements, have ample open space areas and are flexible in their final intended use. Accordingly, researchers have developed new competitive structures in terms of cost and efficiency, such as cold-formed steel and timber composite floors, to satisfy these requirements. Cold-formed steel and timber composite floors are light floors with relatively high stiffness, which allow for longer spans. As a result, they inherently have lower fundamental natural frequency and lower damping. Therefore, they are likely to undergo unwanted vibrations under the action of human activities such as walking. It is also quite expensive and complex to implement vibration control measures on problematic floors. In this study, a finite element model of a composite floor reported in the literature was developed and validated against four-point bending test results. The validated FE model was then utilised to examine the vibration behaviour of the investigated composite floor. Predictions obtained from the numerical model were compared against predictions from analytical formulas reported in the literature. Finally, the influence of various parameters on the vibration behaviour of the composite floor was studied and discussed.

• Geomechanics and Engineering
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• 제31권5호
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• pp.453-460
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• 2022

It is essential for geotechnical engineers to conduct studies and make predictions about the stability of slopes, since collapse of a slope may result in catastrophic events. The Gaussian process regression (GPR) approach was carried out for the purpose of predicting the factor of safety (FOS) of the slopes in the study that was presented here. The model makes use of a total of 327 slope cases from Iran, each of which has a unique combination of geometric and shear strength parameters that were analyzed by PLAXIS software in order to determine their FOS. The K-fold (K = 5) technique of cross-validation (CV) was used in order to conduct an analysis of the accuracy of the models' predictions. In conclusion, the GPR model showed excellent ability in the prediction of FOS of slope stability, with an R² value of 0.8355, RMSE value of 0.1372, and MAPE value of 6.6389%, respectively. According to the results of the sensitivity analysis, the characteristics (friction angle) and (unit weight) are, in descending order, the most effective, the next most effective, and the least effective parameters for determining slope stability.

• ETRI Journal
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• 제45권5호
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• pp.822-835
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• 2023

Recent semantic segmentation frameworks usually combine low-level and high-level context information to achieve improved performance. In addition, postlevel context information is also considered. In this study, we present a Context ReFinement Network (CRFNet) and its training method to improve the semantic predictions of segmentation models of the encoder-decoder structure. Our study is based on postprocessing, which directly considers the relationship between spatially neighboring pixels of a label map, such as Markov and conditional random fields. CRFNet comprises two modules: a refiner and a combiner that, respectively, refine the context information from the output features of the conventional semantic segmentation network model and combine the refined features with the intermediate features from the decoding process of the segmentation model to produce the final output. To train CRFNet to refine the semantic predictions more accurately, we proposed a sequential training scheme. Using various backbone networks (ENet, ERFNet, and HyperSeg), we extensively evaluated our model on three large-scale, real-world datasets to demonstrate the effectiveness of our approach.

• Nuclear Engineering and Technology
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• 제56권9호
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• pp.3826-3834
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• 2024

The main purposes of start-up tests in nuclear power plants (NPPs) are to ensure safe and reliable operation, verify system functionality, comply with regulatory requirements, optimize performance, and establish a foundation for ongoing plant operation and maintenance. However, the start-up tests of NPPs also could be used as a main part of the nuclear code validation procedure for several reasons including: realistic simulation, comprehensive evaluation, detection of code limitations, validation of safety margins and confidence in code predictions. The main purpose of the current study is to define and assess the validation procedure based on actual start-up test data. In this regard, the developed RELAP5 model has been validated against the actual data of VVER-1000 plant during a dynamic start-up test. The results of this full-scale validation show a good agreement between the developed RELAP5 model results and actual plant data. Finally, by defining a step by step validation procedure, it has been recommended to use the start-up phase test data as a more robust validation process which allow for full-scale validation of the nuclear code by comparing its predictions with actual plant measurements and also other advantages which have been demonstrated in the current study.

• Journal of the Korean Wood Science and Technology
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• 제27권3호
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• pp.99-116
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• 1999

목재 hollow core 형태의 프러쉬문은 가구과 목공품 산업에서 주요 제품으로 사용중 틀어짐과 좌굴은 매우 중요한 문제이다. 틀어짐은 도아 표면재 간의 물리적 및 기계적 성질의 차이에 기인된다고 알려져 있다. 본 연구는 수치적 모델덜을 사용해 틀어짐과 좌굴을 예측하는데 그 목적이 있다. 여러 환경조건에서 경질섬유판과 합판으로 만들어진 프러쉬문에 대한 각 모델들과 실측치간의 비교를 하였다. 문의 틀어짐과 좌굴을 예측하기 위해 3가지 연속체 모델, 즉 보, 판상 및 판상-좌굴 모델이 채택되었다. 틀어짐은 고습에서보다 저습에서 현저하게 훨씬 현저하게 발생되었으며, 포아송 비를 고려한 판상 모델은 저습에서 보 모델보다 더 정확하게 틀어짐을 예측할 수 있었다. 그러나 고습에서 좌굴이 문의 표면재에 발생하기 때문에 판상-좌굴 모델 이 모든 시험범위에서 가장 적절하였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1997년도 전력전자학술대회 논문집
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• pp.101-110
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• 1997

The circuit effects due to the transformer primary side series equivalent inductance in the Zero Voltage Switching Pulse Width Modulated Half Bridge DC/DC Converter and its impact on the effective duty are analyzed. The steady state equations and the small signal model of the converter are derived incorporating the effects of the complementary control and the utilization of transformer primary side series equivalent inductance. The open plant dynamics are analyzed on the basis of the model derived. The model predictions are confirmed by experimental measurements.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.445-456
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• 2003

Spatial data are usually obtained at selected locations even though they are potentially available at all locations in a continuous region. Moreover the monitoring locations are clustered in some regions, sparse in other regions. One important goal of spatial data analysis is to predict unknown response values at any location throughout a region of interest. Thus, an appropriate space model should be set up and their estimates and predictions must be accompanied by measures of uncertainty. In this study we see that a space model proposed allows a best interpolation to annual rainfall data in South Korea.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2007년도 International Conference
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• pp.571-575
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• 2007

For better predictions and classifications in customer recommendation, this study proposes an integrative model that efficiently combines the currently-in-use statistical and artificial intelligence models. In particular, by integrating the models such as Association Rule, Connection Frequency Matrix, and Rule Induction, this study suggests an integrative prediction model.

• 한국자동차공학회논문집
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• 제3권1호
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• pp.136-142
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• 1995

An analysis model is proposed for the performance prediction of typical ball and tube type mechanical crash sensors based upon mass-spring-viscous gas damping idealization. Also a construction of mechanical crash pulse generator is suggested as an experimental tool for calibration and verification of model predictions. A sensor tuning procedure for a particular set of crash pulses is suggested based upon the analysis model and the experimental tools.