• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.295-303
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• 2022

This study investigates the impact of globalization, coal consumption, and economic growth on CO₂ emissions in Malaysia by applying the Kuznets Environmental Curve model. The study employed the Autoregressive Distributed Lag modeling technique on time series data over the period of 1970-2018 to determine the short and long-run relationship between CO₂ emissions and a number of variables, including globalization, coal consumption, and economic growth. The results show that globalization increase CO₂ emissions in both the short and long run in Malaysia. Furthermore, the results reveal that economic growth and coal consumption degrade the environmental quality by accelerating the CO₂ emissions in the short-run and long run. As a result, the findings validate the Kuznets Environmental Curve hypothesis of an inverted U-shaped relationship between economic growth and CO₂ emissions in the long run for Malaysia. The findings of this study suggest that higher globalization levels and usage of coal consumption degrade the environmental quality in Malaysia. The findings also indicate the effect of economic growth on environmental degradation is positive at the initial stage but improves after the economy achieves a threshold level of income per capita in the economic development process with an inverted U-shaped pattern in the long run.

• Nuclear Engineering and Technology
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• v.41 no.8
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• pp.1073-1078
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• 2009

A kinetic model for the oxidation of a $UO_2$ pellet to $U_3O_8$ powder has been suggested by considering the mass transfer and the diffusion of oxygen molecules. The kinetic parameters were estimated by a fitting of the experimental data. The activation energies for the chemical reaction and the product layer diffusion were calculated from the kinetic model. The oxidation conversion of a $UO_2$ pellet was simulated at various operating conditions. The suggested model explains the oxidation behavior of $UO_2$ well.

• Journal of Energy Engineering
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• v.28 no.4
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• pp.13-18
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• 2019

The high energy penalty in amine-based post-combustion CO₂ capture process is hampering its industrial scale application. An advanced process is designed by intensive heat integration within the conventional process to reduce the stripper duty. The study presents the technical feasibility for stripper duty reduction by intensive heat integration in CO₂ capture process. A rigorous rate-based model has been used in Aspen Plus® to simulate conventional and advanced process for a 300 MW coal-based power plant. Several design and operational parameters like split ratio, stripper inter-heater location and flowrate were studied to find the optimum values. The results show that advanced configuration with heat integration can reduces the stripper heat by 14%.

• Transactions of the Korean hydrogen and new energy society
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• v.35 no.2
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• pp.115-120
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• 2024

In this study, the extent of water removal in the high-moisture coal was measured. The simplified adsorption model was developed to predict the extent of water removal. The water removal was observed to increase up to 25% at saturation condition of 25℃. The modeling work shows that adsorption contributes the water removal only by 3%, whereas other factors such as CO₂ solubility and wettability would be responsible for the water removal.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.229-232
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• 2001

4H-SIC(silicon carbide) MESFET large signal model was studied using modified Materka-Kacprzak large signal MESFET model. 4H-SiC MESFET device simulation have been conducted by Silvaco's 2D device simulator, ATLAS. The result is modeled using modified Materka large signal model. simulation and modeling results are -8V pinch off voltage, under $V_{GS=0V}$, $V_{DS=25V}$ conditions, $I_{DSS=270㎃}$mm, $G_{m=45㎳}$mm were obtained. Through the power simulation 2GHz, at the bias of $V_{GS=-4V}$ and $V_{DS=25V}$, 10dB Gain, 34dBm(1dB compression point)output power, 7.6W/mm power density, 37% PAE(power added efficiency) were obtained.d.d.d.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.592-610
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• 2020

In South Korea, the concept of water environment was expanded to include aquatic ecosystems with the Integrated Water Management implementation. Watershed-scale modeling is typically performed for hydrologic component analysis, however, there is a need to expand to include ecosystem variability such that the modeling corresponds to the social and political issues around the water environment. For this to be viable, the modeling must account for several distinct features in South Korean watersheds. The modeling must provide reasonable estimations for peak flow rate and apply to paddy areas as they represent 11% of land use area and greatly influence groundwater levels during irrigation. These facts indicate that the modeling time intervals should be sub-daily and the hydrologic model must have sufficient power to process surface flow, subsurface flow, and baseflow. Thus, the features required for watershed-scale modeling are suggested in this study by way of review of frequently used hydrologic models including: Agricultural Policy/Environmental eXtender(APEX), Catchment hydrologic cycle analysis tool(CAT), Hydrological Simulation Program-FORTRAN(HSPF), Spatio-Temporal River-basin Ecohydrology Analysis Model(STREAM), and Soil and Water Assessment Tool(SWAT).

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.17-33
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• 2022

An experimental study is carried out to investigate the performance of the cutting tool regarding the insert wear, surface roughness, cutting forces, cutting power and material removal rate of three coated carbides GC2015 (TiCN-Al₂O₃-TiN), GC4215 (Al₂O₃-Ti(C,N)) and GC1015 (TiN) during the dry turning of AISI4140 steel. For this purpose, a Taguchi design (L₉) was adopted for the planning of the experiments, the effects of cutting parameters on the surface roughness (R_a), tangential cutting force (F_z), the cutting power (P_c) and the material removal rate (MRR) were studied using analysis of variance (ANOVA), the response surface methodology (RSM) was used for mathematical modeling, with which linear mathematical models were developed for forecasting of R_a, F_z, P_c and MRR as a function of cutting parameters (V_c, f, and a_p). Then, Multi-Objective Ant Lion Optimizer (MOALO) has been implemented for multi-objective optimization which allows manufacturers to enhance the production performances of the machined parts. Furthermore, in order to characterize and quantify the flank wear of the tested tools, some machining experiments were performed for 5 minutes of turning under a depth of 0.5 mm, a feed rate of 0.08 mm/rev, and a cutting speed of 350 m/min. The wear results led to a ratio (V_B-GC4215/V_B-GC2015) of 2.03 and (V_B-GC1015/V_B-GC2015) of 4.43, thus demonstrating the efficiency of the cutting insert GC2015. Moreover, SEM analysis shows the main wear mechanisms represented by abrasion, adhesion and chipping.

• Journal of Mechanical Science and Technology
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• v.17 no.9
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• pp.1268-1275
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• 2003

In this paper, a compact 3-DOF mobile microrobot with sub-micron resolution is presented. It has many outstanding features : it is as small as a coin ; its precision is of sub-micrometer resolution on the plane ; it has an unlimited travel range ; and it has simple and compact mechanisms and structures which can be realized at low cost. With the impact actuating mechanism, this system enable both fast coarse motion and highly precise fine motion with a pulse wave input voltage controlled. The 1 -DOF impact actuating mechanism is modeled by taking into consideration the friction between the piezoelectric actuator and base. This modeling technique is extended to simulate the motion of the 3-DOF mobile robot. In addition, experiments are conducted to verify that the simulations accurately represent the real system. The modeling and simulation results will be used to design the model-based controller for the target system. The developed system can be used as a robotic positioning device in the micromanipulation system that determines the position of micro-sized components or particles in a small space, or assemble them in the meso-scale structure.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.2
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• pp.108-113
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• 2016

The real-world problems usually show nonlinear and multi-variate characteristics, so it is difficult to establish concrete mathematical models for them. Thus, it is common to practice data-driven modeling techniques in these cases. Among them, most widely adopted techniques are regression model and intelligent model such as neural networks. Regression model has drawback showing lower performance when much non-linearity exists between input and output data. Intelligent model has been shown its superiority to the linear model due to ability capable of effectively estimate desired output in cases of both linear and nonlinear problem. This paper proposes modeling method of daily photovoltaic power systems using ELM(Extreme Learning Machine) based modular networks. The proposed method uses sub-model by fuzzy clustering rather than using a single model. Each sub-model is implemented by ELM. To show the effectiveness of the proposed method, we performed various experiments by dataset acquired during 2014 in real-plant.

• Environmental Engineering Research
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• v.14 no.2
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• pp.111-119
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• 2009

A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.