• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.347-357
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• 2022

The aim of the study is to model demand for full-time Bachelor's Degree Programs in Hospitality and Catering, taking into account the influence of the main determinants in the COVID-19 pandemic. The research used methods of algorithms, correlation and regression analysis, ANOVA, graphical method, deduction and induction, abstraction, etc. It was found that the demand for full-time Bachelor's Degree Programs in Hospitality and Catering is price elastic. It has been argued that it is useful to consider both price and non-price determinants when modelling demand for full-time Bachelor's Degree Programs in Hospitality and Catering. It is proved that the main determinants of demand for full-time Bachelor's Degree Programs in Hospitality and Catering are full-time tuition fee, maximum government order, license volume and Consolidated Ranking of a higher education institution (HEI). In this case, the applicant decides to enrol in a full-time Bachelor's Degree Program in Hospitality and Catering, guided by the optimal ratio of tuition fee and the prestige of the HEI.

• The Journal of Bigdata
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• v.6 no.2
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• pp.85-98
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• 2021

The pandemic of COVID-19 further promoted the imbalance in the volume of imports and exports among countries using containers, which worsened the shortage of empty containers. Since it is important to secure as many empty containers as the appropriate demand for stable and efficient port operation, measures to predict demand for empty containers using various techniques have been studied so far. However, it was based on long-term forecasts on a monthly or annual basis rather than demand forecasts that could be used directly by ports and shipping companies. In this study, a daily and weekly prediction method using an actual artificial neural network is presented. In details, the demand forecasting model has been developed using multi-layer perceptron and multiple linear regression model. In order to overcome the limitation from the lack of data, it was manipulated considering the business process between the loaded container and empty container, which the fully-loaded container is converted to the empty container. From the result of numerical experiment, it has been developed the practically applicable forecasting model, even though it could not show the perfect accuracy.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.199-209
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• 2008

This paper is described the concepts and limitations for the traditional directional design hour volume estimation. The main objective of this paper is to establish an estimation method of probabilistic directional design hour volume in order to improve the limitation for the traditional approach method. To express the traffic congestion of specific road segment, this paper proposed the link travel time as the probability that the road capacity can accommodate a certain traffic demand at desired service level. Also, the link travel time threshold was derived from chance-constrained stochastic model. Such successive probabilistic process could determine optimal ranked design hour volume and directional design hour volume. Therefore, the probabilistic directional design hour volume can consider the traffic congestion and economic aspect in road planning and design stage. It is hoped that this study will provide a better understanding of various issues involved in the short term prediction of directional design hourly volume on different types of roads.

• The Korea Journal of Herbology
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• v.31 no.4
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• pp.93-100
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• 2016

Objectives : The internet is the most common method to investigate information. It is showed that 75.2% of Internet users of 20s had health information search experience. So this study is aim to understanding of interest of public about the herbal medicine using internet search query volume data.Methods : The Naver that is the top internet portal web service of the Republic of Korea has provided an Internet search query volume data from January 2007 to the current through the Naver data lab (http://datalab.naver.com) service. We have collected search query volume data which was provided by the Naver in 606 herbal medicine names and sorted the data by peak and total search volume.Results : The most frequently searched herbal medicines which has less bias and sorted by peak search volume is 'wasong (와송)'. And the most frequently searched herbal medicines which has less bias and sorted by total search volume is 'hasuo (하수오)'.Conclustions : This study is showed that the rank of interest of public about herbal medicines. Among the above herbal medicines, some herbal medicines had supply issue. And there are some other herbal medicines that had very little demand in Korean medicine market, but highly interested public. So it is necessary to monitor for these herbal medicines which is highly interested of the public. Furthermore if the reliability of the data obtained on the basis of these studies, it is possible to be utilizing herbal medicine monitoring service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6084-6091
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• 2014

This paper presents the GJR GARCH model (Glosten et. al, 1993) to analyze the influences of volume volatilities on price volatilities in the fishery market. For the analysis, this study used the monthly price and volume data of aquacultural flatfish in Jeju. As a result, empirical analysis suggested volatility clustering. The persistency parameter(${\lambda}$) was estimated to be approximately 1 in aquacultural flatfish. The results showed that there is a significant negative relationship between the conditional variance of supply and that of price for aquacultural flatfish. This means that the general law of supply is valid. Finally, the empirical analysis was that an asymmetric coefficient (${\gamma}$) of GJR GARCH model was negative (-). This means that the higher volatility of volume leads to lower price volatility. That is, it is useful to make government policies that can adjust the volume (stockpiling, stabilizing supply and demand).

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.155-161
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• 2023

97.5% of our country's exports and 87.2% of imports are transported by sea, making ports an important component of the Korean economy. To efficiently operate these ports, it is necessary to improve the short-term prediction of port water volume through scientific research methods. Previous research has mainly focused on long-term prediction for large-scale infrastructure investment and has largely concentrated on container port water volume. In this study, short-term predictions for petroleum and liquefied gas cargo water volume were performed for Ulsan Port, one of the representative petroleum ports in Korea, and the prediction performance was confirmed using the deep learning model LSTM (Long Short Term Memory). The results of this study are expected to provide evidence for improving the efficiency of port operations by increasing the accuracy of demand predictions for petroleum and liquefied gas cargo water volume. Additionally, the possibility of using LSTM for predicting not only container port water volume but also petroleum and liquefied gas cargo water volume was confirmed, and it is expected to be applicable to future generalized studies through further research.

• Journal of computational fluids engineering
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• v.17 no.2
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• pp.65-70
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• 2012

The droplet ejection behavior from drop-on-demand printhead are investigated numerically in terms of the non-dimensional parameters. The numerical simulation is performed using a volume-of-fluid model. It is important to eject droplet within the printability range, where the droplet is ejected in stable manner without satellite droplets. Generally, the printability range has been determined by Z number, which is the inverse of Oh number. However, it is found that the ejection of droplets with same Z number can exhibit different behavior depending on the value of Ca and We number. Therefore, it is insufficient to determine the printability range only with Z number. Instead, other non-dimensional parameters, such as Ca and We number, should be considered comprehensively.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.495-498
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• 2003

In order to analyze water supply capacity in estuary barrage dam, a system was developed in which base model was consisted of daily water balance model and daily inflow model. Agricultural water demand to paddy fields and domestic and industrial water demand were considered in this daily water balance model. Also outflow volume through sluice gate and inside water level at time to start outflow was conditioned initially to simulate reservoir storage. The DAWAST model was selected to simulate daily reservoir inflow in which return flows from agricultural, domestic and industrial water were included to simulate runoff. Using this developed system, water supply capacity in the Keum river estuary reservoir was analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.97.2-97
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• 2001

This work is concerned with the improvement of the productivity and the product quality in the polymerization reactors by using model-on-demand predictive control(MoDPC). This technique is applied to a continuous styrene polymerization reactor and a semibatch methyl methacrylate (MMA)/vinyl acetate(VAc) copolymerization reactor. The regress is constructed with the most influential variables the conversion and the jacket inlet temperature for the styrene polymerization reactor, and the free volume and the reactor temperature for the MMA/VAc copolymerization reactor through open loop operations. From the simulation results for setpoint tracking and disturbance rejection problems, it is demonstrated that the MoDPC shows ...

• Fashion, Industry and Education
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• v.14 no.2
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• pp.24-34
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• 2016

This research examined two decades of the U.S. used clothing exports to the world. All countries (209) were classified into four groups based on the level of economic development. Between 1996 and 2012, U.S. used clothing exports shifted away from low-income economies to high-income economies. For the first time, our research demonstrated that the majority of used clothing discarded by American consumers is exported to high-income economies instead of poorest nations of the world. Next, used clothing exports and imports by volume and value in seven high-income countries were analyzed. The high-income countries not only exported but also imported significant amount of used clothing, which indicates a growing demand for worn apparel in developed nations. The demand might be at least partially attributed to the popular vintage clothing trend and increasing consumer environmentalism. Implications regarding development and implementation of a new classification system of worn clothing and recommendations for future research are presented.