• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.217-225
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• 2023

2,3-Butanediol (2,3-BDO), which is used in various fields such as cosmetics and fertilizers, is a high value-added substance and the demand for it is gradually increasing. 2,3-BDO produced from the fermentation of microorganisms not only contains by-products of fermentation, but also varies greatly in feed composition depending on fermentation conditions, so it is difficult to efficiently operate the separation process to reach the target purity of the product. Therefore, in this study, through dynamic optimization of the bio-based 2,3-BDO distillation process, the optimal control route was explored to control the 2,3-BDO concentration of the bottom product to 99 wt% or more, when feed concentration changes. Steady and dynamic state process simulation, proportional integral (PI) controller design, and dynamic optimization were sequentially performed. As a result, the error between the 2,3-BDO concentration and the set point of the bottom product was reduced by 75.2%.

• Journal of Korea Trade
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• v.26 no.6
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• pp.1-19
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• 2022

Purpose - This study empirically investigates the effects of Official Development Assistance (ODA) on the economic activities of private actors in recipient countries. As a proxy for the economic activities of private actors, we utilize the job creation activities of foreign subsidiaries in recipient countries. The foreign subsidiaries provide a foundation for economic development by creating paying jobs. That is, if ODA has been successfully transferred to foreign subsidiaries, then these foreign subsidiaries should help economic growth and help create a boom in the local market by providing jobs. These jobs eventually lead to the achievement of the primary aims of foreign aid, including poverty reduction. Thus, this study empirically examines the relationship between ODA and the number of jobs created by foreign subsidiaries in recipient countries. Design/methodology - This is the first study to examine the effects of the ODA on the job creation of foreign subsidiaries because it has been hard to obtain internal information related to the employment status of foreign subsidiaries. Fortunately, we have a unique panel dataset provided by the Export-Import Bank of Korea (KEXIM) for 2006 to 2013. In terms of the empirical specification, we use the generalized least squares (GLS) method. The panel GLS estimator allows us to have an efficient estimation that overcomes the limitations of the panel data. It employs assumptions about the heteroscedasticity between the panels and makes an autocorrelation of the error term within each panel. Findings - We find that ODA influences job creation in foreign subsidiaries. In particular, we found that ODA creates more jobs in sales than in managerial or production positions. This study also shows that the effect of the ODA on the foreign subsidiaries' job creation activities depend on the purpose of the ODA. By examining ODA effects on the foreign subsidiaries' economic activities (e.g., job creation), this study fills a gap in the current literature. Originality/value - Existing studies that focus on the ODA effect have either a macroeconomic point or a microeconomic point of view. However, both approaches do not explain how well foreign aid has influenced private economic actors of recipient countries. In essence, previous researchers found it difficult to obtain the necessary data for internal employment status from foreign subsidiaries. However, thanks to the Korea Export-Import Bank, this study shows that ODA indeed influences the job creation activities of foreign subsidiaries even after controlling for other factors such as FDI, GDP growth rate, employment rate, household expenditure, mother firms' share, etc. By doing so, we can examine how ODA influences the job creation of foreign subsidiaries, which might help economic development and reduce the amount of poverty in recipient countries.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.339-352
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• 2023

Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles and the time interval of paired flow images of the pebble bed. Two types of strategies are put forward: one is adding FC layers to the classic classification CNN models and using regression training, and the other is CNN-based deep expectation (DEX) by regarding the time prediction as a deep classification task followed by softmax expected value refinements. The current dataset is obtained from the discrete element method (DEM) simulations. Results show that the CNN-aided models generally make satisfactory predictions on the remaining time with the determination coefficient larger than 0.99. Among these models, the VGG19+DEX performs the best and its CumScore (proportion of test set with prediction error within 0.5s) can reach 0.939. Besides, the remaining time of additional test sets and new cases can also be well predicted, indicating good generalization ability of the model. In the task of predicting the time interval of image pairs, the VGG19+DEX model has also generated satisfactory results. Particularly, the trained model, with promising generalization ability, has demonstrated great potential in accurately and instantaneously predicting the traits of interest, without the need for additional computational intensive DEM simulations. Nevertheless, the issues of data diversity and model optimization need to be improved to achieve the full potential of the CNN-aided prediction tool.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.701-708
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• 2017

The construction cost is estimated based on the drawings at the design stage and constructor will find efficient construction methods for budgeting and budgeting appropriate to the budget. Accurate quantity estimation and budgeting are critical to determining whether the project is profitable or not. However, since this process is mostly performed depending on manpower or 2D drawings, errors are likely to occur and The BIM(Build Information Modeling) program, which can be automated, is very expensive and difficult to apply in the field. In this study, 3D architectural modeling was performed using SketchUp which is a 3D modeling software and suggest a methodology for Quantity Estimation. As a result, 3D modeling was performed effectively using 2D drawings of buildings. Based on the modeling results, it was possible to calculate the difference of the quantity estimation by 2D drawing and 3D modeling. The research suggests that the 3D modeling using the SketchUp and the calculation of the quantity can prevent the error of the conventional 2D calculation method. If the applicability of the research method is verified through continuous research, it will contribute to increase the efficiency of architectural modeling and quantity Estimation work.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.467-475
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• 2009

Existing studies have suggested Universal Curve only for supplemental damping by damper. Therefore net damping has been determined by means of arithmetic summation between intrinsic, aero-damping of cable and supplemental damping of damper. However linear combination approach by means of the arithmetic summation is not enough theoretical background. So validity of this approach should be verified in order to design adequate cable-damper system by engineers. This study establishes governing differential equation which can consider intrinsic, aero-damping and supplemental damping as well. And also analysis method is solved by combination of muller method and successive iteration method. Consequently, this study succeeds in verification for validity of linear combination approach. As a result of this study, linear combination approach is limitedly effective in case of low stiffness and optimum damping coefficient of damper, short distance from support to damper, lower vibration mode, low aero-damping, and normal windy environment. Whereas this study will be effective in case of opposite conditions, and existing studies or linear combination approach occur to further error. Meaning of this study presents exact solution for net damping of cable-damper system, and verifies linear combination approach by means of the analysis method. In the future, if monitoring of optimum damping coefficient of a damper against aero-damping is feasible on time, algorithm of this study will be available for control of cable and semi-active damper system such as magneto-rheological damper.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.373-379
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• 2009

Cost estimation in the early phase enables government to plan public budgeting more efficiently by providing information about construction cost. However, cost estimation in the early phase is difficult to predict because only a little information can be utilized. The cost estimation method now being used by the government is calculated by length of the road multiplied by unit cost per length and shows high error rate because it cannot reflect the unique characteristics of each project. As the project is being proceeded, level of available information also changed. So, reflecting available information of a project is important. This paper divided early phase into two parts : planning phase and early design phase, and developed cost estimation model considering level of available information of each phase. Total 143 cases are utilized to find influencing variables and develop cost estimation model and model validation is done by adopting required accuracy level. This cost estimation model reflecting level of available information can be applied to public budgeting, feasibility test, and comparison between routes.

• Steel and Composite Structures
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• v.49 no.1
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• pp.81-89
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• 2023

A simplified calculation method of natural vibration characteristics of high-speed railway multi-span bridge-longitudinal ballastless track system is proposed. The rail, track slab, base slab, main beam, bearing, pier, cap and pile foundation are taken into account, and the multi-span longitudinal ballastless track-beam-bearing-pier-cap-pile foundation integrated model (MBTIM) is established. The energy equation of each component of the MBTIM based on Timoshenko beam theory is constructed. Using the improved Fourier series, and the Rayleigh-Ritz method and Hamilton principle are combined to obtain the extremum of the total energy function. The simplified calculation formula of the natural vibration frequency of the MBTIM under the influence of vertical and longitudinal vibration is derived and verified by numerical methods. The influence law of the natural vibration frequency of the MBTIM is analyzed considering and not considering the participation of each component of the MBTIM, the damage of the track interlayer component and the stiffness change of each layer component. The results show that the error between the calculation results of the formula and the numerical method in this paper is less than 3%, which verifies the correctness of the method in this paper. The high-order frequency of the MBTIM is significantly affected considering the track, bridge pier, pile soil and pile cap, while considering the influence of pile cap on the low-order and high-order frequency of the MBTIM is large. The influence of component damage such as void beneath slab, mortar debonding and fastener failure on each order frequency of the MBTIM is basically the same, and the influence of component damage less than 10m on the first fourteen order frequency of the MBTIM is small. The bending stiffness of track slab and rail has no obvious influence on the natural frequency of the MBTIM, and the bending stiffness of main beam has influence on the natural frequency of the MBTIM. The bending stiffness of pier and base slab only has obvious influence on the high-order frequency of the MBTIM. The natural vibration characteristics of the MBTIM play an important guiding role in the safety analysis of high-speed train running, the damage detection of track-bridge structure and the seismic design of railway bridge.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.381-397
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• 2023

The most representative design used in clinical trials is randomization, which is used to accurately estimate the treatment effect. However, comparison between the treatment group and the control group in an observational study without randomization is biased due to various unadjusted differences, such as characteristics between patients. Propensity score weighting is a widely used method to address these problems and to minimize bias by adjusting those confounding and assess treatment effects. Inverse probability weighting, the most popular method, assigns weights that are proportional to the inverse of the conditional probability of receiving a specific treatment assignment, given observed covariates. However, this method is often suffered by extreme propensity scores, resulting in biased estimates and excessive variance. Several alternative methods including trimming, overlap weights, and matching weights have been proposed to mitigate these issues. In this paper, we conduct a simulation study to compare performance of various propensity score weighting methods under diverse situation, such as limited overlap, misspecified propensity score, and treatment contrary to prediction. From the simulation results overlap weights and matching weights consistently outperform inverse probability weighting and trimming in terms of bias, root mean squared error and coverage probability.

• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.281-289
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• 2023

PURPOSE. This study aimed to predict the positional coordinates of incisor points from the scan data of conventional complete dentures and verify their accuracy. MATERIALS AND METHODS. The standard triangulated language (STL) data of the scanned 100 pairs of complete upper and lower dentures were imported into the computer-aided design software from which the position coordinates of the points corresponding to each landmark of the jaw were obtained. The x, y, and z coordinates of the incisor point (X_P, Y_P, and Z_P) were obtained from the maxillary and mandibular landmark coordinates using regression or calculation formulas, and the accuracy was verified to determine the deviation between the measured and predicted coordinate values. Y_P was obtained in two ways using the hamularincisive-papilla plane (HIP) and facial measurements. Multiple regression analysis was used to predict Z_P. The root mean squared error (RMSE) values were used to verify the accuracy of the X_P and Y_P. The RMSE value was obtained after crossvalidation using the remaining 30 cases of denture STL data to verify the accuracy of Z_P. RESULTS. The RMSE was 2.22 for predicting X_P. When predicting Y_P, the RMSE of the method using the HIP plane and facial measurements was 3.18 and 0.73, respectively. Cross-validation revealed the RMSE to be 1.53. CONCLUSION. Y_P and Z_P could be predicted from anatomical landmarks of the maxillary and mandibular edentulous jaw, suggesting that Y_P could be predicted with better accuracy with the addition of the position of the lower border of the upper lip.