• Journal of the Korea Concrete Institute
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• v.19 no.3
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• pp.359-366
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• 2007

Recently, analysis researches on durability are focused on chloride attack and carbonation due to increased social and engineering significance. Generally, chloride penetration and carbonation occur simultaneously except for in submerged condition and chloride behavior in carbonated concrete is evaluated to be different from that in normal concrete. Furthermore, if unavoidable crack occurs in concrete, it influences not only single attack but also coupled deterioration more severely. This is a study on analysis technique with system dynamics for chloride penetration in concrete structures exposed to coupled chloride attack and carbonation through chloride diffusion, permeation, and carbonation reaction. For the purpose, a modeling for chloride behavior considering diffusion and permeation is performed through previous models for early-aged concrete such as MCHHM (multi component hydration heat model) and MPSFM (micro pore structure formation). Then model for combined deterioration is developed considering changed characteristics such as pore distribution, saturation and dissociation of bound chloride content under carbonation. The developed model is verified through comparison with previous experimental data. Additionally, simulation for combined deterioration in cracked concrete is carried out through utilizing previously developed models for chloride penetration and carbonation in cracked concrete. From the simulated results, CCTZ (chloride-carbonation transition zone) for evaluating combined deterioration is proposed. It is numerically verified that concrete with slag has better resistance to combined deterioration than concrete with OPC in sound and cracked concrete.

• Journal of Gifted/Talented Education
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• v.15 no.1
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• pp.11-36
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• 2005

Cooperative teaching emerged as one of the interesting topics on curriculum administration and teaching-learning method in BSA(Busan Science Academy). The purpose of this study is to do research on social studies learning with respect to cooperative teaching, and to develop the model of cooperative teaching. The results of this study are as follows: First, We surveyed both the concept of cooperative teaching in all aspects and the methodological application on cooperative teaching. Second, We searched all teaching-learning methods in BSA in terms of cooperative teaching. Third, We studied cooperative teaching system on social studies considering current environmental factors. Forth, We performed seminar class which is constructed as one of the cooperative teaching models. The topic of seminar was 'The distortion and falsification of Koguryeo history in China'. The participants of seminar were volunteer students and social studies teachers whose subjects were geography, history, social studies, and ethics. And the participants conducted the research and cooperative learning based on teacher's subjects and subtopics. Fifth, The interactions between teacher and teacher, student and student, and teacher and student in the process of seminar preparation and publication were conducted very excitedly. Especially we found the possibility of cooperative teaching by the interaction between teachers. Finally, students developed the mind-frame to participate in social studies learning actively, and learned the method to research social affairs for themselves, and extended the eyes to approach social affairs with different opinions.

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.1-32
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• 2024

The emissions trading system stands as a pivotal climate policy in Korea, incentivizing abatement equivalent to 87% of total emissions (as of 2021). As the system likely has a far-reaching impact, it is crucial to understand how the real economic activity, energy sector, as well as environment would be influenced by its implementation. Employing a macroeconometric model, this paper is the first study analyzing the effects of the Korean emissions trading policy. It interconnects the Korean Standard Industrial Classification (Economy), Energy Balance (Energy), and National Inventory Report (Environment), enhancing its real-world explanatory power. We find that a 50% increase in emission permit price over four years results in a decrease in greenhouse gas emissions (-0.043%) and downward shifts in key macroeconomic variables, including real GDP (-0.058%), private consumption (-0.003%), and investment (-0.301%). The price increase in emission permit is deemed crucial for achieving greenhouse gas reduction targets. To mitigate transition risk associated with price shocks, revenue recycling using auction could ensure the sustainability of the economy. This study confirms the comparative advantage of expanded current transfers expenditure over corporate tax reduction, particularly from an economic growth perspective.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.14-30
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• 2007

The purpose of this study was to evaluate trophic conditions of various Korean reservoirs using Trophic State Index (TSI) and predict the reservoir conditions by empirical models. The water quality dataset (2000, 2001) used here were obtained from the Ministry of Environment, Korea. The water quality, based on multi-parameters of dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), suspended solid (SS), Secchi depth (SD), chlorophyll-${\alpha}$ (CHL), and conductivity largely varied depending on the sampling watersheds and seasons. In general, trophic conditions declined along the longitudinal axis of headwater-to-the dam and the largest seasonal variations occurred during the summer monsoon of July-August. Major inputs of TP occurred during the monsoon (r=0.656, p=0.002) and this pattern was similar to solid dynamics of SS (r=0.678, p<0.001). Trophic parameters including CHL, TP, SD, and TN were employed to evaluate how the water systems varies with season. Trophic State Index (TSI, Carlson, 1977), based on TSI (CHL), TSI (TP), and TSI (SD), ranged from mesotrophic to eutrophic. However, the trophic state, based on TSI (TN), indicated eutrophic-hypereutrophic conditions in the entire reservoirs, regardless of the seasons, indicating a N-rich system. Overall, nutrient data showed that phosphorus was a primary factor regulating the trophic state. The relationships between CHL (eutrophication index) vs. trophic parameters (TN, TP, and SD) were analysed to develop empirical models which can predict the trophic status. Regression analyses of log-transformed seasonal CHL against TP showed that the value of $R^2$ was 0.31 (p=0.017) in the premonsoon but was 0.69 (p<0.001) during the postmonsoon, indicating a greater algal response to the phosphorus during the postmonsoon. In contrast, SD had reverse relation with TP, CHL during all season. TN had weak relations with CHL during all seasons. Overall, data suggest that TP seems to be a good predictor for algal biomass, estimated by CHL, as shown in the empirical models.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.12
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• pp.1102-1139
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• 2002

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 2000 and 2001 has been done. Focus has been put on current status of research in the aspect of heating, cooling, ventilation, sanitation and building environment. The conclusions are as follows. (1) Most of fundamental studies on fluid flow were related with heat transportation of facilities. Drop formation and rivulet flow on solid surfaces were interesting topics related with condensation augmentation. Research on micro environment considering flow, heat, humidity was also interesting for comfortable living environment. It can be extended considering biological aspects. Development of fans and blowers of high performance and low noise were continuing topics. Well developed CFD technologies were widely applied for developing facilities and their systems. (2) Most of papers related with heat transfer analysis and heat exchanger shows dealt with convection, evaporation, and channel flow for the design application of heat exchanger. The numerical heat transfer simulation studies have been peformed and reported to show heat transfer characteristics. Experimental as well as numerical studies on heat exchanger were reported, while not many papers are available for the system analysis including heat exchanger. (3) A review of the recent studies on heat pump system shows that performance analysis and control of heat pump have been peformed by various simulations and experiments. The research papers on multi-type heat pump system increased significantly. The studies on heat pipe have been examined experimently for change of working characteristics and strut lure. Research on the phase change has been carried out steadily and operation strategies of encapsulated ice storage tank are reported experimentally in several papers. (4) A review of recent studies on refrigeration/air conditioning system have focused on the system performance and efficiency for new alternative refrigerants. Evaporation and condensation heat transfer characteristics are investigated for tube shapes and new alternative refrigerants. Studies on components of refrigeration/air conditioning system are carried to examine efficiency for various compressors and performance of new expansion devices. In addition to thermophysical properties of refrigerant mixtures, studies on new refrigerants are also carried out, however research works on two-phase flow seemed to be insufficient. (5) A review of the recent studies on absorption cooling system indicates that heat and mass transfer phenomena have been investigated to improve absorber performance. Various experimental data have been presented and several simulation models have been proposed. A review of the recent studies on duct and ventilation shows that ventilation indices have been proposed to quantify the ventilation performance in buildings and tunnels. Main efforts have been focused on the applications of ventilation effectiveness in practice, either numerically using computational fluid dynamics or experimentally using tracer gas techniques. (6) Based on a review of recent studies on indoor thermal environment and building service systems, research issues have mainly focused on many innovative ideas such as underfloor air-conditioning system, personal environmental modules, radiant floor cooling and etc. Also, the new approaches for minimizing energy consumption as well as improving indoor environmental conditions through predictive control of HVAC systems, various activities of building energy management and cost-benefit analysis for economic evaluation were highlighted.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.12
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• pp.1175-1183
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• 2013

Even if some CFD software developers and its users think that a state-of-the-art CFD software can be used to reasonably solve at least single-phase nuclear reactor safety problems, there remain limitations and uncertainties in the calculation result. From a regulatory perspective, the Korea Institute of Nuclear Safety (KINS) is presently conducting the performance assessment of commercial CFD software for nuclear reactor safety problems. In this study, to examine the prediction performance of commercial CFD software with the porous model in the analysis of the scale-down APR (Advanced Power Reactor Plus) internal flow, a simulation was conducted with the on-board numerical models in ANSYS CFX R.14 and FLUENT R.14. It was concluded that depending on the CFD software, the internal flow distribution of the scale-down APR was locally somewhat different. Although there was a limitation in estimating the prediction performance of the commercial CFD software owing to the limited amount of measured data, CFX R.14 showed more reasonable prediction results in comparison with FLUENT R.14. Meanwhile, owing to the difference in discretization methodology, FLUENT R.14 required more computational memory than CFX R.14 for the same grid system. Therefore, the CFD software suitable to the available computational resource should be selected for massively parallel computations.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.42 no.3
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• pp.169-178
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• 2006

This research aims at establishing the fundamental characteristics of the kite through the analysis of the flow field around various types of kites. The approach of this study were adopted for the analysis; visualization by CFD(computational fluid dynamics). Also, the lift/drag and PIV(particle image velocimetry) tests of kites had been performed in our previous finding. For this situation, models of canvas kite were designed by solidworks(design program) for the CFD test using the same conditions as in the lift/drag tests. And we utilized FloWorks as a CFD analysis program. The results obtained from the above approach are summarized as follows: According to comparison of the measured and analyzed results from mechanical tests, PIV and CFD test, the results of all test were similar. The numerical results of lift-coefficient and drag-coefficient were 5-20% less than those of the tests when attack angle is $10^{\circ},\;20^{\circ}\;and\;30^{\circ}$. In particular, it showed the 20% discrepancy at $40^{\circ}$. The numerical results of the ratio of drag and lift were 8-13% less than those of the tests at $10^{\circ}$ and 10% less than those of the tests at $20^{\circ},\;30^{\circ}\;and\;40^{\circ}$. Pressure distribution gradually became stable at $10^{\circ}$. In particular, the rectangular and triangular types had the centre of the high pressure field towards the leading edge and the inverted triangular type had it towards the trailing edge. The increase of the attack angle resulted in the eddy in order of the rectangular, triangular and inverted triangular type. The magnitude of the eddy followed the same order. The effect of edge-eddy was biggest in the triangular type followed by the rectangular and then the inverted triangular type. The action point of dynamic pressure as a function of the attack angle was close to the rear area of the model with the small attack angle, and with large attack angle, the action point was close to the front part of the model.

• Journal of the Korean Geographical Society
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• v.46 no.6
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• pp.673-692
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• 2011

Advances in computer technology have enabled us to develop and use numerical landscape evolution models (NLEMs) for exploring the dynamics of geomorphic system from a variety of viewpoints which previously could have not been taken. However, as of yet there have been no trials using or developing NLEMs in Korea. The purpose of this research is to develop a 2 dimensional NLEM on a geological time scale and evaluate its usefulness. The newly developed NLEM (ND-NLEM) treats bedrock weathering as one of the major geomorphic processes and attempts to simulate the thickness of soil. As such it is possible to model the weathering-limited as well as the transport-limited environment on hillslopes. Moreover the ND-NLEM includes not only slow and continuous mass transport like soil creep, but also rapid and discrete mass transport like landslides. Bedrock incision is simulated in the ND-NLEM where fluvial transport capacity is large enough to move all channel bed loads, such that ND-NLEM can model the detachment-limited environment. Furthermore the ND-NLEM adopts the D-infinity algorithm when routing flows in the model domain, so it reduces distortion due to the use of the steepest descent slope flow direction algorithm. In the experiments to evaluate the usefulness of the ND-NLEM, characteristics of the channel network observed from the model results were similar to those of the case study area for comparison, and the hypsometry curve log during the experiment showed rational evidence of landscape evolution. Therefore, the ND-NLEM is shown to be useful for simulating landscape evolution on a geological time scale.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.