• Journal of the Korean Institute of Navigation
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• v.19 no.1
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• pp.33-48
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• 1995

In the process of containerization, the problem of regional maldistribution of container management plan arises seriously due to several factors like a number of unbalances of containers between loading and discharging ports. This study focus on the minimizing cost. This study is composed of two models which in effective management decision making show decision of the number of containers and transfer of empty containers. One is decision of the number of containers which carriers should possess by appropriate forecasting and the other is effective management decision making which includes the transfer of empty containers on calling ports. This study has suggested as follows, First, the Time Series analysis method, especially the "Exponential Smooting with Trend Adjustment" was used to forecast the trade volumes for the designated traffic route. Second, the Time Series analysis method in deciding the optimal number of owned container at the unbalances trade situation between East Bound and West Bound service, most important variables were found such as total traffic volume, the calling interval at a port, the number of days of voyage and the length of stay on shore of container for the optimal number of owned container. Third, effective management decision making model, which makes it possible to analyze the impacts of change in important matters such as lease and positioning policy, and actually influence decision making.on making.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.273-280
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• 2019

Many studies have shown that job performance and leadership are important in our society. In addition, to improve the quality of work or to improve the work efficiency is still a lot of challenges for each leader. In Vietnam, there are few specific studies on the impact of leadership styles on employee engagement such as: transformational leadership styles, business leadership styles and leadership styles. In the field of higher education, the fewer studies on these issues. A study is conducted to test the impact of leadership styles on the engagement of cadres, lecturers and staff at public universities in Vietnam. Using adjustment techniques, inspecting the scales and theoretical models representing the relationship among the influential factors. The research is based on a sample of 309 cadres, lecturers and staff currently working in universities in Vietnam and used Structural Equation Modeling (SEM) to test the relationships among the variables. The study results show that the scales of the variables: transformational leadership, transactional leadership, laissez faire leadership, job satisfaction and organizational engagement attain the validity and reliability in the research. The study results also show transformational leadership, transactional leadership and laissez faire leadership are directly and indirectly affected by job satisfaction and organizational commitment.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.255-261
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• 2003

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• Korea Real Estate Review
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• v.27 no.1
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• pp.33-44
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• 2017

The continuously rising housing prices in major Chinese cities have raised question about whether inflation is the main reason to drive up housing price to skyrocket in recent years. Based on the provincial panel dataset of China from 2006-2014, this paper investigates the impact of inflation on Chinese housing markets within the frameworks of both static and dynamic panel data models. Our empirical results show evidence that inflation has indeed been a main force of accumulating housing bubbles in these housing markets, especially in eastern region of China. We also find an interesting phenomenon in which Chinese housing bubble is, to a certain extent, affected by market self-adjustment mechanism.

• Journal of Physiology & Pathology in Korean Medicine
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• v.34 no.4
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• pp.209-214
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• 2020

The association of cold-heat (CH) pattern and anthropometry/body composition has been suggested in that they are related to thermoregulation. We aimed to study the association of CH pattern and anthropometry/body composition. A total of 1479 individuals aged 50-80 years were included in the study, and their CH pattern were evaluated by a self-administered questionnaire. After adjustment for age and sex, the CH score were significantly correlated with weight, BMI (body mass index), body surface area, waist-hip ratio, fat free mass, body fat mass, body cell mass, intracellular water, extracellular water, and basal metabolic rate; however, the correlation coefficients were mostly low (0.15-0.24). The selected variables for predicting CH score were various according to the methods used for variable selection; however, the adjusted R-squared of the final models were all around 0.12. Thus the most parsimonious model could be the one that includes sex and BMI. In conclusion, various anthropometry and body composition indices were associated with CH pattern. Future studies are necessary to improve the performance of the prediction model.

• Safety and Health at Work
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• v.12 no.1
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• pp.10-19
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• 2021

Background: Traditional safety concept, which is called Safety-I, and its relevant methods and models have much contributed toward enhancing the safety of industrial systems. However, they have proved insufficient to be applied to complex socio-technical systems. As an alternative, Safety-II and resilience engineering have emerged and gained much attention for the last two decades. However, it seems that safety professionals have still difficulty understanding their fundamental concepts and methods. Accordingly, it is necessary to offer an introductory guide to them that helps safety professionals grasp them correctly in consideration of their current practices. Methods: This article firstly explains the limitations of Safety-I and how Safety-II can resolve them from the four points of view. Next, the core concepts of resilience engineering and Functional Resonance Analysis Method are described. Results: Workers' performance adjustment and performance variability due to it should be the basis for understanding human-related accidents in socio-technical systems. It should be acknowledged that successful and failed work performance have the same causes. However, they are not well considered in the traditional safety concept; in contrast, Safety-II and resilience engineering have conceptual bases and practical approaches to reflect them systematically. Conclusion: It is necessary to move from a find-and-fix and reactive approach to a proactive approach to safety management. Safety-II and resilience engineering give a set of useful concepts and methods for proactive safety management. However, if necessary, Safety-I methods need to be properly used for situations where they can still be useful as well.

• The Journal of Korean Medicine
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• v.42 no.4
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• pp.185-196
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• 2021

Objectives: Many symptoms of cold and heat patterns are related to the thermoregulation of the body. Thus, we aimed to study the association of cold and heat patterns with anthropometry/body composition. Methods: The cold and heat patterns of 2000 individuals aged 30-55 years were evaluated using a self-administered questionnaire. Results: Among the anthropometric and body composition variables, body mass index (-0.37, 0.39) and fat mass index (-0.35, 0.38) had the highest correlation coefficients with the cold and heat pattern scores after adjustment for age and sex in the cold-heat group, while the correlation coefficients were relatively lower in the non-cold-heat group. In the cold-heat group, the most parsimonious model for the cold pattern with the variables selected by the best subset method and Lasso included sex, body mass index, waist-hip ratio, and extracellular water/total body water (adjusted R² = 0.324), and the model for heat pattern additionally included age (adjusted R² = 0.292). Conclusions: The variables related to obesity and water balance were the most useful for predicting cold and heat patterns. Further studies are required to improve the performance of prediction models.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.23-32
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• 2022

Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.373-373
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• 2021

Rainfall forecasting is an important issue that is applied in many areas, such as agriculture, flood warning, and water resources management. In this context, this study proposed a statistical and machine learning-based forecasting model for monthly rainfall. The Bayesian Gaussian process was chosen to optimize the hyperparameters of the Stacked Long Short-term memory (SLSTM) model. The proposed SLSTM model was applied for predicting monthly precipitation of Seoul station, South Korea. Data were retrieved from the Korea Meteorological Administration (KMA) in the period between 1960 and 2019. Four schemes were examined in this study: (i) prediction with only rainfall; (ii) with deseasonalized rainfall; (iii) with rainfall and minimum temperature; (iv) with deseasonalized rainfall and minimum temperature. The error of predicted rainfall based on the root mean squared error (RMSE), 16-17 mm, is relatively small compared with the average monthly rainfall at Seoul station is 117mm. The results showed scheme (iv) gives the best prediction result. Therefore, this approach is more straightforward than the hydrological and hydraulic models, which request much more input data. The result indicated that a deep learning network could be applied successfully in the hydrology field. Overall, the proposed method is promising, given a good solution for rainfall prediction.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.204-204
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• 2021

Terrestrial water storage (TWS) includes all components of water (e.g., surface water, groundwater, snow and ice) over the land. So accurately predicting and estimating TWS is important in water resource management. Although many land surface models are used to predict the TWS, model output has errors and biases in comparison to the observation data due to the model deficiencies in the model structure, atmospheric forcing datasets, and parameters. In this study, Gravity Recovery And Climate Experiment (GRACE) satelite TWS data is assimilated in the Community Land Model version 5 with a biogeochemistry module (CLM5.0-BGC) over East Asia from 2003 to 2010 by employing the Ensemble Adjustment Kalman Filter (EAKF). Results showed that TWS over East Asia continued to decrease during the study period, and the ability to simulate the surface water storage, which is the component of the CLM derived TWS, was greatly improved. We further investigated the impact of assimilated TWS on the vegetated and carbon related variables, including the leaf area index and primary products of ecosystem. We also evaluated the simulated total ecosystem carbon and calculated its correlation with TWS. This study shows that how the better simulated TWS plays a role in capturing not only water but also carbon fluxes and states.