• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.31-50
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• 2018

This study implemented an empirical analysis of education and training for dangerous goods and hazardous materials handlers on the Busan New Port terminals and hinterland logistics centers using a Structural Equation Modeling (SEM) in combination with the formative model and reflective model, from the viewpoint of the supply chain. An effect size analysis was also conducted. The results of the empirical analysis show that Training Environment and the Atmosphere of Education have a positive influence on the Educational Expectation of hazardous material handlers, and the Educational Expectation has a positive influence on the Education and Training Program and Transfer of Education Training. Likewise, the Education and Training Program has a positive influence on the Transfer of Education Training and Result of Education and Training. Furthermore, the Transfer of Education Training has a positive influence on the Result of Education and Training. The Result of Education and Training has a positive influence on the Present State of hazardous material management. According to the results of the effect size analysis, the following parameters represented a great effect: the Atmosphere of Education to the Education Expectation, the Education Expectation to the Education and Training Program, the Transfer of Education Training to the Result of Education and Training, and the Result of Education and Training to the Present State of Dangerous Goods Management. The results of this study provided various suggestions for related practices.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.95-102
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• 2010

As the electric power industry is evolving into competitive market scheme, a new paradigm is required for the operation of market. Traditional dispatch algorithm was built based on the optimization model with an objective function and multiple constraints. Commercial market simulator followed the concept of the microeconomic model used in the dispatch algorithm, which is called as analytic method. On analytic method it is prerequisite to procure the exact data for the simulation. It is not easy anymore for each market participant to access to other participants' financial information while it used to be easy for monopoly decision maker to know all the information needed for the optimal operation. Considering the changing situation, it is required to introduce a new method for estimating the market price. This paper proposes an empirical method based on stochastic processes expected to build a capacity planning and long term contracts.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.395-395
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• 2000

Optimization of existing processes becomes more important than the past as environmental problems and concerns about energy savings stand out. When we can model a process mathematically, we can easily optimize it by using the model as constraints. However, modeling is very difficult for most chemical processes as they include numerous units together with their correlation and we can hardly obtain parameters. Therefore, optimization that is based on the process models is, in turn, hard to perform. Especially, f3r unknown processes, such as bioprocess or microelectronics materials process, optimization using mathematical model (first principle model) is nearly impossible, as we cannot understand the inside mechanism. Consequently, we propose a few optimization method using empirical model evolutionarily instead of mathematical model. In this method, firstly, designing experiments is executed fur removing unecessary experiments. D-optimal DOE is the most developed one among DOEs. It calculates design points so as to minimize the parameters variances of empirical model. Experiments must be performed in order to see the causation between input variables and output variables as only correlation structure can be detected in historical data. And then, using data generated by experiments, empirical model, i.e. response surface is built by PLS or MLR. Now, as process model is constructed, it is used as objective function for optimization. As the optimum point is a local one. above procedures are repeated while moving to a new experiment region fur finding the global optimum point. As a result of application to the pulp digester benchmark model, kappa number that is an indication fur impurity contents decreased to very low value, 3.0394 from 29.7091. From the result, we can see that the proposed methodology has sufficient good performance fur optimization, and is also applicable to real processes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.6
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• pp.520-529
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• 2016

The main purpose of this study was to analyze the performance of a medium-altitude long endurance unmanned aerial vehicle through reverse-engineering method. The external configuration data of the RQ-1 Predator was reverse-engineered from related photos and specification data available on public domains, which also were used to generate the CATIA modeling and weigh distribution data of the UAV. The aerodynamic characteristics of RQ-1 Predator were mainly predicted the vortex lattice method and an empirical method, which the propeller performance was analyzed by the empirical method proposed by Howe. The rate of climb, service ceiling, range, and the loiter endurance of the UAV was analyzed, which showed good agreement with the reference data.

• Journal of Navigation and Port Research
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• v.42 no.1
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• pp.39-46
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• 2018

Strategic partnerships of alliances and large shipping companies have been steadily launched in shipping market. Converting these alliances into customers and maintaining them important hub port status. The cases of container terminals to establish a political strategy based on. On the other hand, bulk terminals are relatively unexplored container terminal and bulk terminal are included in the same category of port empirical research from the overall perspective. Therefore, analysis of structural equations was utilized in this study. Analysis of the entire measurement model showed that all items except "Results - Intention of renewal" on bulk terminals were significant. This study is expected to contribute to promotion of empirical studies in various levels by compare container terminals and bulk terminals.

• Journal of Astronomy and Space Sciences
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• v.39 no.1
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• pp.11-22
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• 2022

It is suggested that magnetosonic waves (also known as equatorial noise) can scatter radiation belt electrons in the Earth's magnetosphere. Therefore, it is important to understand the global distribution of these waves between the proton cyclotron frequency and the lower hybrid resonance frequency. In this study, we developed an empirical model for estimating the global distribution of magnetosonic wave amplitudes and wave normal angles. The model is based on the entire mission period (approximately 2012-2019) of observations of Van Allen Probes A and B as a function of the distance from the Earth (denoted by L^*), magnetic local time (MLT), magnetic latitude (λ), and geomagnetic activity (denoted by the Kp index). In previous studies the wave distribution inside and outside the plasmasphere were separately investigated and modeled. Our model, on the other hand, identifies the wave distribution along with the ambient plasma environment-defined by the ratio of the plasma frequency (f_pe) to the electron cyclotron frequency (f_ce)-without separately determining the wave distribution according to the plasmapause location. The model results show that, as Kp increases, the dayside wave amplitude in the equatorial region intensifies. It thereby propagates the intense region towards the wider MLT and inward to L^* < 4. In contrast, the f_pe/f_ce ratio decreases with increasing Kp for all regions. Nevertheless, the decreasing aspect differs between regions above and below L^* = 4. This finding implies that the particle energy and pitch angle that magnetosonic waves can effectively scatter vary depending on the locations and geomagnetic activity. Our model agrees with the statistically observed wave distribution and ambient plasma environment with a coefficient of determination of > 0.9. The model is valid in all MLTs, 2 ≤ L^* < 6, |λ| < 20°, and Kp ≤ 6.

• School Mathematics
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• v.16 no.2
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• pp.387-407
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• 2014

Gender differences have been given major attention in mathematics education in the context of pursuing gender equity in instructional and learning environment. It had been traditional belief that male students would outperform female students in mathematics, especially in the areas as geometry. This belief has been given doubts by cumulated empirical evidences that gender differences are gradually diminishing or even reversing its direction as time goes on. In this study, gender differences in geometry were explored using TIMSS 8th grade mathematics data administered in TIMSS 2003, 2007, and 2011, based on a cognitive diagnostic modeling(CDM) approach. Among various CDM models, the Fusion model was employed. The Fusion model has advantages over other CDM models in that it provides more detailed information about gender differences at the attribute level as well as item level and more mathematically tractable. The findings of this study show that Attribute 3(Three-dimensional Geometric Shapes) revealed statistically significant gender differences favoring male students in TIMSS 2003 and 2007, but did not show significant differences in TIMSS 2011, which provides an additional empirical evidence supporting the recent observation that gender gap is narrowing. In addition to the general trends in gender differences in geometry, this study also provided affluent information such as gender differences in attribute mastery profiles and gender differences in relative contributions of each attribute in solving a particular item. Based on the findings of the CDM approach exploring gender differences, instructional implications in geometry education are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2606-2611
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• 2003

Comprehensive study on the control system design for a RTP process has been conducted. The purpose of the control system is to maintain maximum temperature uniformity across the silicon wafer achieving precise tracking for various reference trajectories. The study has been carried out in two stages: thermal balance modeling on the basis of a semi-empirical radiation model, and optimal iterative learning controller design on the basis of a linear state space model. First, we found through steady state radiation modeling that the fourth power of wafer temperatures, lamp powers, and the fourth power of chamber wall temperature are related by an emissivity-independent linear equation. Next, for control of the MIMO system, a state space modeland LQG-based two-stage batch control technique was derived and employed to reduce the heavy computational demand in the original two-stage batch control technique. By accommodating the first result, a linear state space model for the controller design was identified between the lamp powers and the fourth power of wafer temperatures as inputs and outputs, respectively. The control system was applied to an experimental RTP equipment. As a consequence, great uniformity improvement could be attained over the entire time horizon compared to the original multi-loop PID control. In addition, controller implementation was standardized and facilitated by completely eliminating the tedious and lengthy control tuning trial.

• Geomechanics and Engineering
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• v.13 no.4
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• pp.671-683
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• 2017

Groundwater control is a significant issue in most underground construction. An estimate of the inflow rate is required to size the pumping system, and treatment plant facilities for construction planning and cost assessment. An estimate of the excavation-induced drawdown of the initial groundwater level is required to evaluate potential environmental impacts. Analytical and empirical methods used in current engineering practice do not adequately account for the effect of the jointed-rock-mass anisotropy and heterogeneity. The impact of geostructural anisotropy of fractured rocks on tunnel inflows is addressed and the limitations of analytical solutions assuming isotropic hydraulic conductivity are discussed. In this paper the unexcavated Zagros tunnel route has been classified from groundwater flow point of view based on the combination of observed water inflow and numerical modeling results. Results show that, in this hard rock tunnel, flow usually concentrates in some areas, and much of the tunnel is dry. So the remaining unexcavated Zagros tunnel route has been categorized into three categories including high Risk, moderately risk and low risk. Results show that around 60 m of tunnel (3%) length can conduit the large amount of water into tunnel and categorized into high risk zone and about 45% of tunnel route has moderately risk. The reason is that, in this tunnel, most of the water flows in rock fractures and fractures typically occur in a clustered pattern rather than in a regular or random pattern.

• Computers and Concrete
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• v.14 no.4
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• pp.445-462
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• 2014

To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. There have been many packages that can be employed to analyze reinforced concrete plane frames. However, because most structural analysis packages suffer from closeness of systems, it is very difficult to integrate them with optimization packages. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrates Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build the models Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables. The RC frame optimization problem was examined to evaluate the DAMDO approach, and the empirical results showed that it can be solved by the approach.