• Journal of Korea Port Economic Association
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• v.25 no.1
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• pp.1-14
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• 2009

This study predicted Port trade volume by considering Korea's export to China and import Com China separately using ARIMA model (Multiplicative Seasonal ARIMA Model). We predicted monthly Port trade volumes for 27 months from October 2008 to December 2010 using monthly data from September 2008 to January 2001 using monthly data. As a result of prediction, we found that the export volume decreased in January, February, August and September while the import volume decreased in February, March, August and September. As the decrease period was clearly differentiated, it was possible to predict export and import volumes. Therefore, it is believed that the results of this study will generate useful basic data for policy makers or those working for export and import enterprises when they set up policies and management plans. And to improve competitive power of Port trade, this study suggests privatization of Port, improvement of information capability, improvement of competitive power of Port management companies, support for Port distribution companies, plans for active encouragement of transshipment, and management of added value creation policy.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.97-105
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• 2006

The autogenous shrinkage of high-performance concrete is important in that it can lead the early cracks in concrete structures. The purpose of the present study is to explore the autogenous shrinkage of high-performance concrete with admixture and to derive a realistic equation to estimate the autogenous shrinkage model of that. For this purpose, comprehensive experimental program has been set up to observe the autogenous shrinkage for various test series. Major test variables were the type and contents of admixture and water-cement ratio is fixed with 30%. The autogenous shrinkage of HPC with fly ash slightly decreased than that of OPC concrete, but the use of blast furnace slag increased the autogenous shrinkage. Also, the autogenous shrinkage of HPC is found to decrease with increasing shrinkage reduction agent and expansive additive. A prediction equation to estimate the autogenous shrinkage of HPC with admixture was derived and proposed in this study. The proposed equation show reasonably good correlation with test data on autogenous shrinkage of HPC with mineral and chemical admixture.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.65-84
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• 2019

This study attempted to predict citizens' emotions regarding mortgage rates using machine learning algorithms. To accomplish the research purpose, I reviewed the related literature and then set up two research questions. To find the answers to the research questions, I classified emotions according to Akman's classification and then predicted citizens' emotions on mortgage rates using six machine learning algorithms. The results showed that AdaBoost was the best classifier in all evaluation categories. However, the performance level of Naive Bayes was found to be lower than those of other classifiers. Also, this study conducted a ROC analysis to identify which classifier predicts each emotion category well. The results demonstrated that AdaBoost was the best predictor of the residents' emotions on home mortgage rates in all emotion categories. However, in the sadness class, the performance levels of the six algorithms used in this study were much lower than those in the other emotion categories.

• Journal of the Korean earth science society
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• v.44 no.2
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• pp.105-118
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• 2023

In this study, we predicted the presence of fog with a one-hour delay using the XGBoost DART machine learning algorithm for Andong, which had the highest occurrence of fog among inland stations from 2016 to 2020. We used six datasets: meteorological data, agricultural observation data, additional derived data, and their expanded data. The weather phenomenon numbers obtained through naked-eye observations and the visibility distances measured by visibility meters were classified as fog [1] or no-fog [0]. We set up twelve machine learning modeling experiments and used data from 2021 for model validation. We mainly evaluated model performance using recall and AUC-ROC, considering the harmful effects of fog on society and local communities. The combination of oversampled meteorological data features and the target induced by weather phenomenon numbers showed the best performance. This result highlights the importance of naked-eye observations in predicting fog using machine learning algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.317-328
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• 2010

The method to evaluate the flexural capacity of steel fiber-reinforced ultra high strength concrete beams was proposed in this study. An experimental program was set up and fourteen beams have been tested. Test results were compared with predictions by design code and by the proposed method, respectively. It was found that predictions by using ACI 544 Committee recommendations considerably underestimate the flexural capacity. Underestimation of flexural capacity resulted from that of tensile stress block. Three-point bending test data of notched prism specimens and their inverse analysis results were incorporated into modeling of tension stress block. The ratio of the predicted to the experimental flexural capacity was in the range of 0.98 to 1.14. The present study represents that the proposed method allows more realistic prediction of flexural capacity of steel fiber-reinforced ultra high strength concrete beams.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.997-1000
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• 2005

Dynamic job shop environment requires not only more flexible capabilities of a CAPP system but higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations to be performed by predicting the machine loads. The developed algorithm is based on the multiple objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as Pareto-optimal solutions). The objective shows a combination of the minimization of part movement and the maximization of machine utility balance. The algorithm is characterized by a new and efficient method for nondominated sorting, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II.

• Korean Journal of Food Science and Technology
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• v.15 no.4
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• pp.392-398
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• 1983

A pilot single-screw food extruder was constructed, and its mechanical properties and product characteristics were investigated by using corn grits. The screw rotational speed was varied and the changes in temperature profile of the barrel for the start-up period of operation were measured. The rate of heat generation for the start-up period was affected by the screw speed and feed rate. The screw speed resulted in a great influence on the estimated dough viscosity. The changes in the dough viscosity could indicate the on-set of termoplastic reaction in the barrel. The expansion ratio during the start-up period mainly depended on the barrel temperature and the degree of thermoplastic reaction in the barrel. The barrel temperatures for the gelatinization and burning of corn grits depended on the screw speed as well as the feed rate.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1025-1034
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• 2004

This paper proposes an adaptive motion estimation algorithm using the temporal continuity of motion. We set up a squared global search region (GSR), which basically corresponds to the search region of FSA, and non-squared adaptive local search regions (LSRs), the positions for which are predicted by the motion vectors of the temporal neighbor blocks, are constructed in the GSR. The previous frame blocks that possibly have effects on the current block are to be the temporal neighbor blocks. Because motion estimation is only performed in the areas made by LSRs, we can estimate motion more correctly and reduce processing time. Experimental results show that the proposed method can enhance visual qualities with significant reductions of complexity by reducing search regions, when compared to the conventional methods.

• Food Science and Preservation
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• v.9 no.2
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• pp.179-183
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• 2002

This study was carried out to set up alcohol fermentation condition for uncooked corn. Response surface methodology(RSM) was applied to optimize and monitor the alcohol fermentation condition with uncooked corn. The optimal yeast strain for fermentation of uncooked corn was Saccharomyces cerevisiae GRJ. The polynomial equation for alcohol contents, brix, pH and total acidity showed 0.8852, 0.9202, 0.8806 and 0.9940 of R$^2$, respectively. The optimal rendition for maximum alcohol contents were 0.18%(w/w) of enzyme concentration and 180%(v/w) of added water content. Predicted values at optimum alcohol fermentation condition agreed with experimental value.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.4
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• pp.91-98
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• 2018

A numerical investigation of stage separation behavior of a two-body vehicle focusing on its flow characteristics is carried out. For this simulation, the separation of a booster from a vehicle is modeled using a chimera grid system and calculated with commercial code, $CFD-FASTRAN^{TM}$. Consideration of spring force, gravity and relative acceleration of a booster is the essential factor of a realistic simulation. In this study, it is validated that the booster separation time decreases with an increase in flight Mach number and angle of attack. In view of results thus far achieved, it is expected that the dynamics modeling and boundary condition set-up applied in this study will be useful for estimating safe stage separation and event sequencing of flight tests.