• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.57-72
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• 2020

The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• Korea Trade Review
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• v.43 no.3
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• pp.125-145
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• 2018

The Baltic Shipping Exchange is reporting the Baltic Dry Index (BDI) which represents the average charter rate for bulk carriers transporting major cargoes such as iron ore, coal, grain, and so on. And the current BDI index is reflected in the proportion of capesize 40%, panamax 30% and spramax 30%. Like mentioned above, the capesize plays a major role among the various sizes of bulk carriers and this study is to analyze the influence of the factors influencing on charter rate of capesize carriers which transport iron ore and coal as the major cargoes. For this purpose, this study verified causality between variables using Vector Error Correction Model (VECM) and tried to derive a long-run equilibrium model between the dependent variable and independent variables. Regression analysis showed that every six independent variable has a significant effect on the capesize charter rate, even at the 1% level of significance. Charter rate decreases by 0.08% when capesize total fleet increases by 1%, charter rate increases by 0.04% when bunker oil price increases by 1%, and charter rate decreases by 0.01% when Yen/Dollar rate increases by 1%. And charter rate increases by 0.02% when global GDP increases by one unit (1%). In addition, the increase in cargo volume of iron ore and coal which are major transportation items of capesize carriers has also been shown to increase charter rates. Charter rate increases by 0.11% in case of 1% increase in iron ore cargo volume, and 0.09% in case of 1% increase in coal cargo volume. Although there have been some studies to analyze the influence of factors affecting the charterage of bulk carriers in the past, there have been few studies on the analysis of specific size vessels. At present moment when ship size is getting bigger, this study carried out research on capesize vessels, which are biggest among bulk carriers, and whose utilization is continuously increasing. This study is also expected to contribute to the establishment of trade policies for specific cargoes such as iron ore and coal.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.712-722
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• 2007

This study screened three natural ores (iron, mangenase, and zinc), two types of slags, and two elemental metals (elemental iron and zinc) to evaluate transformation characteristics of CAH mixtures [e.g. Carbontetrachloride (CT), 1,1,1-Trichloroethane (1,1,1-TCA), and Perchloroethene (PCE)]. To select an effective metal medium to treat the CAH mixtures, we measured transformation capacities (CAH mass ultimately transformed/mass of metal added) and the degree of dechlorination. We also considered economical efficiency of the metal media by comparing the value, CAH mass ultimately transformed divided by the price of metal medium added. A simplified mathematical model adapting CAH transformation capacity, first-order transformation kinetics, and available mass of metal transforming CAH was developed and used for estimating CAH transformation rate coefficient and longevity of the metal medium. CAH transformation capacity for elemental iron and elemental zinc were 4258~7129 and $4215{\sim}6330{\mu}g\;CAH\;transformed/g$ metal added, respectively, which are a factor of 80~200 higher than slags and natural ores. They also showed a factor of 1.1 to 2.2 greater degree of dechlorination than the others. Among natural ores and slags, Zinc ore showed the highest transformation capacity, $47{\sim}53{\mu}g\;CAH\;transformed/g$ metal added. Although zinc ore have smaller transformation capacity than elemental metals, economical efficiency of zinc ore is a factor of 10~20 greater than elemental metals tested. Consequently, zinc ore would be more economical medium than the others tested in this study. We estimated the pseudo first-order transformation rate of zinc ore was in the order of CT > 1,1,1-TCA > PCE.

• Resources Recycling
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• v.24 no.3
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• pp.34-43
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• 2015

Raw materials in steel industry decide on the productivity, quality and price competitiveness. Utilizing iron-containing by-products as raw materials for steel products can save the cost of cleaning up iron-containing by-products and solve environmental issues. Iron-containing by-products have a small particle size. If they are directly inserted in a steel making process, it cause a problem such as poor heat flow and scattering. To solve these problems and induce the additional reduction, study concern with iron ore-coal mixed briquette technique are conducted by many researchers. In this paper, method of making carbon composite briquette iron(CCBI) using iron-containing by-products was studied. The effect of composition of Fe-containing process wastes, reducing agent, flux and binder on formability of CCBI (carbon composite briquette iron) was measured.

• Korea Trade Review
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• v.47 no.4
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• pp.215-231
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• 2022

Analysis and forecasting of the Baltic Capsize Index (BCI) is important for managing an entity's losses and risks from the uncertainty and volatility of the fast-changing maritime transport market in the future. This study conducted volatility transition analysis through the GARCH model, using BCI which is highly related to steel raw materials. As for the data, 2,385 monthly data were used from March 1999 to March 2021. In this study, after basic statistical analysis, unit root and cointegration test, the GARCH, EGARCH, and DCC-GARCH models were used for volatility transition analysis. As the results of GARCH and EGARCH model, we confirmed that all variables had no autocorrelation between the standardized residuals for error terms and the square of residuals, that the variability of all variables at this time was likely to persist in the future, and that the variability of the time-series error term impact according to Iron ore trade (IoT). In addition, through the EGARCH model, the magnitude convenience of all variables except the Iron ore price (IOP) and Capesize bulk fleet (BCF) variables was greater than the positive value (+). As a result of analyzing the DCC-GARCH (1,1) model, partial linear combinations were confirmed over the entire period. Estimating the effect of variability transition on BCF and C5 with statistically significant linear combinations with BCI confirmed that the impact of BCF on BCI was greater than the impact of BCI itself.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.137-138
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• 2012

Domestic construction materials market was about 65 trillion won and it occupied 45% level of total construction cost by 2007. In addition, due to the recent rapid rise of crude oil and iron ore price, fluctuation of raw material cost has a great influence to the cost of construction industry. This means that smooth performance is closely related to construction materials. And among them, because of high putting rate of metal materials, it can be seen that the fluctuation of metal material prices is an important variables. So in this study, for the pre-study to analyze the impact of metallic material prices to construction cost, the researcher analyzed a causal relationship between metal material prices and construction cost.

• Journal of Korea Port Economic Association
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• v.36 no.4
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• pp.17-30
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• 2020

In the shipping industry, it is essential to engage in the preemptive prediction of freight rate volatility through market monitoring. Considering that freight rates have already started to fall, the loss of shipping companies will soon be uncontrollable. Therefore, in this study, factors affecting the freight rates of bulk carriers, which have relatively large freight rate volatility as compared to container freight rates, were quantified and analyzed. In doing so, we intended to contribute to future shipping market monitoring. We performed an analysis using a vector error correction model and estimated the influence of six independent variables on the charter rates of bulk carriers by Handy Size, Supramax, Panamax, and Cape Size. The six independent variables included the bulk carrier fleet volume, iron ore traffic volume, ribo interest rate, bunker oil price, and Euro-Dollar exchange rate. The dependent variables were handy size (32,000 DWT) spot charter rates, Supramax 6 T/C average charter rates, Pana Max (75,000 DWT) spot charter, and Cape Size (170,000 DWT) spot charter. The study examined charter rates by size of bulk carriers, which was different from studies on existing specific types of ships or fares in oil tankers and chemical carriers other than bulk carriers. Findings revealed that influencing factors differed for each ship size. The Libo interest rate had a significant effect on all four ship types, and the iron ore traffic volume had a significant effect on three ship types. The Ribo rate showed a negative (-) relationship with Handy Size, Supramax, Panamax, and Cape Size. Iron ore traffic influenced three types of linearity, except for Panamax. The size of shipping companies differed depending on their characteristics. These findings are expected to contribute to the establishment of a management strategy for shipping companies by analyzing the factors influencing changes in the freight rates of charterers, which have a profound effect on the management performance of shipping companies.

• Economic and Environmental Geology
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• v.41 no.3
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• pp.287-297
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• 2008

In order to estimate the preliminary development feasibility according to the commodity, the content of 8 strategic metallic commoditites(Pb, Zn, Cu, Fe, Mo, W, Au, U) in 68 ore specimens obtained from 34 metallic mines within the Taebaegsan-Hwanggangri mineralized zone were analyzed. Analytical results are as follows. The ore specimen of Sangdong mine contained 23% copper(cut-off grade=0.7%) and those of Cheongil and Samhwanghak mines contained average 5% zinc(cut-off grade=2.0%). Especially, the detailed investigation on the above-mentioned mines is required. And, in case of molybdenum(cut-off grade=0.02%) content in Yeonhwa No. 2(0.04%) and Hong-cheon mine(0.02%), and lead(cut-off grade=0.58%) content in Wongasa mine(0.70%), and gold(cut-off grade=10ppm) content in Dongmyoung(279ppm) and Samhwanghak mine(251ppm), it is required to elastically carry out the revaluation on reopening of mines in terms of the international metal price. On the other hand, in case of uranium, iron and tungsten, it is thought that there are no mines with the development potential value in this study.

• Economic and Environmental Geology
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• v.43 no.2
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• pp.73-84
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• 2010

Gold and silver deposits within the Eunjeok and Sangeun mines are located in Yeongam district, Cheollanamdo-province. They are composed of vein ore bodies infilling the fractures of Cretaceous rhyolitic tuff. The Eunjeok mine have three gold and silver bearing hydrothermal veins which is infilling the fracture of rhyolitic tuff. Major ore minerals within the Eunjeok and Sangeun mines are arsenopyrite, pyrite, chalcopyrite, sphalerite and galena and minor ores are electrum, native silver and argentite. Sericitization is dominant in alteration zone and chloritization and dickitization is minor. Quartz veins in the Eunjeok and Sangeun mine have the similar paragenesis and vein textures such like breccia, crustiform, comb and vuggy morphology indicating the formation of typical epithermal environment. In order to carry out the preliminary feasibility study of mine according to the commodity and elucidate the occurrence features of mineral resources from Eunjeok and Sangeun mine, common commodity (Pb, Zn, Cu, Fe, Mo, W, Au and U), and industrial commodity (In, Re, Ga, Ge, Se, Te, Y, Eu and Sm) for 17 ore specimen were analyzed. It is tentatively thought that there is no exploitable mine for iron, lead, zinc, copper, tungsten and uranium based on the preliminary result. If the reserves are secured through the detailed prospecting in case of molybdenum and silver, it is tentatively thought that there will be exploitable deposits depending on international metal price. If we assume the vein width from 0.25 m to 2 m including alteration zone with the gold grade of 80g/t, it is inferred that the resources amount of the Eunjeok-Sangeun mines range from 6.5 to 65ton. However, as the vein structure of the Eunjeok and Sangeun mines is developed together with alteration zone, it should be estimated to include potential alteration zone in order to yield the average grade. It is needed to carry out more exploration in the near future because the reserves can be flexibly estimated according to the change of average grade considering the alteration zone.