• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.129-141
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• 2023

This study analyzes the dynamic characteristics of daily freight rates of dry bulk and tanker shipping markets and their forecasting accuracy by using the error correction models. In order to calculate the error terms from the co-integrated time series, this study uses the common stochastic trend model (CSTM model) and vector error correction model (VECM model). First, the error correction model using the error term from the CSTM model yields more appropriate results of adjustment speed coefficient than one using the error term from the VECM model. Furthermore, according to the adjusted determination coefficients (adjR²), the error correction model of CSTM-model error term shows more model fitness than that of VECM-model error term. Second, according to the criteria of mean absolute error (MAE) and mean absolute scaled error (MASE) which measure the forecasting accuracy, the results show that the error correction model with CSTM-model error term produces more accurate forecasts than that of VECM-model error term in the 12 cases among the total 15 cases. This study proposes the analysis and forecast tasks 1) using both of the CSTM-model and VECM-model error terms at the same time and 2) incorporating additional data of commodity and energy markets, and 3) differentiating the adjustment speed coefficients based the sign of the error term as the future research topics.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1032-1032
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• 2001

Artificial Neural Network (ANN) calibration techniques have been used commercially for agricultural applications since the mid-nineties. Global models, based on transmission data from 850 to 1050 nm, are used routinely to measure protein and moisture in wheat and barley and also moisture in triticale, rye, and oats. These models are currently used commercially in approx. 15 countries throughout the world. Results concerning earlier European ANN models are being published elsewhere. Some of the findings from that study will be discussed here. ANN models have also been developed for coarsely ground samples of compound feed and feed ingredients, again measured in transmission mode from 850 to 1050 nm. The performance of models for pig- and poultry feed will be discussed briefly. These models were developed from a very large data set (more than 20,000 records), and cover a very broad range of finished products. The prediction curves are linear over the entire range for protein, fat moisture, fibre, and starch (measured only on poultry feed), and accuracy is in line with the performance of smaller models based on Partial Least Squares (PLS). A simple bias adjustment is sufficient for calibration transfer across instruments. Recently, we have investigated the possible use of ANN for a different type of NIR spectrometer, based on reflectance data from 1100 to 2500 nm. In one study, based on data for protein, fat, and moisture measured on unground compound feed samples, dedicated ANN models for specific product classes (cattle feed, pig feed, broiler feed, and layers feed) gave moderately better Standard Errors of Prediction (SEP) compared to modified PLS (MPLS). However, if the four product classes were combined into one general calibration model, the performance of the ANN model deteriorated only slightly compared to the class-specific models, while the SEP values for the MPLS predictions doubled. Brix value in molasses is a measure of sugar content. Even with a huge dataset, PLS models were not sufficiently accurate for commercial use. In contrast an ANN model based on the same data improved the accuracy considerably and straightened out non-linearity in the prediction plot. The work of Mr. David Funk (GIPSA, U. S. Department of Agriculture) who has studied the influence of various types of spectral distortions on ANN- and PLS models, thereby providing comparative information on the robustness of these models towards instrument differences, will be discussed. This study was based on data from different classes of North American wheat measured in transmission from 850 to 1050 nm. The distortions studied included the effect of absorbance offset pathlength variation, presence of stray light bandwidth, and wavelength stretch and offset (either individually or combined). It was shown that a global ANN model was much less sensitive to most perturbations than class-specific GIPSA PLS calibrations. It is concluded that ANN models based on large data sets offer substantial advantages over PLS models with respect to accuracy, range of materials that can be handled by a single calibration, stability, transferability, and sensitivity to perturbations.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.61-69
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• 2015

This study compares the forecasting accuracy of five econometric models on domestic total freight volume in South Korea. Applied five models are as follows: Ordinary Least Square model, Partial Adjustment model, Reduced Autoregressive Distributed Lag model, Vector Autoregressive model, Time Varying Parameter model. Estimating models and forecasting are carried out based on annual data of domestic freight volume and an index of industrial production during 1970~2011. 1-year, 3-year, and 5-year ahead forecasting performance of five models was compared using the recursive forecasting method. Additionally, two forecasting periods were set to compare forecasting accuracy according to the size of future volatility. As a result, the Time Varying Parameter model showed the best accuracy for forecasting periods having fluctuations, whereas the Vector Autoregressive model showed better performance for forecasting periods with gradual changes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.523-530
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• 2010

Recently more gravity data is being obtained due to the increased demands from the fields of geodesy, geophysics, and military. In general, the observed gravity values are corrected for the effect of tide, instrument drift, and instrument height to generate the absolute gravity values at a point. Until yet, the models for tide and drift corrections and those procedures are not determined in Korea which led to the inconsistent data processing for different data sets. Therefore, in this study, the models for tide and drift are analyzed to select the appropriate models. Based on the analysis, it was found that there is not much difference between Longman and Tamura tide models for celestial objects. Earth tide, however, should be considered in tide correction procedure. In drift corrections, the difference between the model considering only the common points and that considering all points appears significantly large up to 0.04mGal. In this case, the model with all points should be used as it the correct one according to the adjustment theory and it generates estimates with better precision.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.999-1011
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• 2008

To most of the students studying fashion related major, the graduation fashion show is a big challenge. They have to put together all they learn and show what they can do to their future employers. They design, pattern work, and make up garments for the show all by themselves. Unfortunately. while they make up their garments, they usually don't Dow exactly body measurements of the models. So quite often they have to alter their art works up to the last minute of the fashion show opening. Sometimes such unadequate work process ruins their work. The purpose of this study is to suggest block patterns of Korean fashion models measurements for basic items, such as jacket and pants for male models and torso length block pattern, skirt and pants for female models. 20 male and 20 female professional models were measured. The block patterns were based on their measurements. After the first fitting test, patterns were corrected by their body characteristic. For both male and female models, it was found desirable to fix the shoulder width and make an adjustment to the patterns with a deviation of width and girth items. In case of the resultant patterns the satisfaction was made better. Model sizes proposed in this study are considered closer to the size of average models, since they were based on A-grade models who are currently working in Korea. The resultant patterns can be produced by simply making a slight adjustment to the width of the proposed pattern in this study.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.719-731
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• 2011

Based on the ICE-3G and ICE-5G ice models, we predicted the velocities of crustal uplift caused by Glacial Isostatic Adjustment (GIA) at 39 tide gauge sites operated by Korea Hydrographic and Oceanographic Administration (KHOA). We also divided the Korean peninsula in the ranges of $32-38.5^{\circ}N$ and $124-132^{\circ}E$ in $0.5^{\circ}{\times}0.5^{\circ}$ grids, and computed the GIA velocities at each grid point. We found that the average uplift rates due to GIA in South Korea were 0.33 and 1.21 mm/yr for ICE-3G and ICE-5G, respectively. Because the GIA rates were relatively high at ~1 mm/yr when the updated ice model ICE-5G was used, we concluded that the GIA effect cannot be neglected when we compute the absolute sea level (ASL) rates around the Korean peninsula. In this study, we corrected the ICE-5G GIA velocities from the relative sea level rates provided by KHOA and we computed the ASL rates at 13 tide gauge stations. As a result, we found that the average ASL velocity around the Korean peninsula was 5.04 mm/yr. However, the ASL rates near Jeju island were abnormally higher than the other areas and the average was 8.84 mm/yr.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.217-230
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• 2014

The purpose of this study is to develop the Generalized Depreciation Function (GDF) and Winfrey Depreciation Function (WDF) by reviewing methods for the depreciation accountings. The Depreciation Accounting Models (DAM), including straight-line model, declining-balance model, sum-of-the-year-digit model and sinking fund model presented in this paper, are reclassified into the charging pattern of increasing type, decreasing type and constant type. This paper also discusses the development of the GDFs based on convex type, concave type and constant type according to the demand pattern of product, frequency of plant usage, deterioration of time, relative inadequacy, Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) of the Total Productive Maintenance (TPM). The WDFs presented in this paper depict a sudden degradation of plant performance by measuring the change of TPM activity at the midpoint of useful life of asset. The WDFs are classified into left-modal type, symmetrical type and right-modal type by varying the value of skewness and kurtosis. Moreover, three increasing patterns, such as convex, concave and linear types, are used in this paper to present the distinct identification of WFDs by using Instantaneous Depreciation Rate (IDR) in terms of Performance Depreciation Function (PDF) and Depreciation Density Function (DDF). In order to have better understanding of depreciation models, the numerical examples are used for evaluating the Net Operating Less Adjusted Tax (NOPLAT) and Economic Value Added (EVA). It is concluded that the depreciation models showing a large dispersion of EVA require the adjustment of NOPLAT and Invested Capital (IC) based on the objective cash basis and net operating activity for reducing the variation of EVA.

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1436-1445
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• 2021

To obtain the dynamic characteristics of reactor secondary circuit under transient conditions, the system analysis program was developed in this study, where dynamic models of secondary circuit were established. The heat transfer process and the mechanical energy transfer process are modularized. Models of main equipment were built, including main turbine, condenser, steam pipe and feedwater system. The established models were verified by design value. The simulation of the secondary circuit system was conducted based on the verified models. The system response and characteristics were investigated based on the parameter transients under emergency shutdown and overload. Various operating conditions like turbine emergency shutdown and overspeed, condenser high water level, ejector failures were studied. The secondary circuit system ensures sufficient design margin to withstand the pressure and flow fluctuations. The adjustment of exhaust valve group could maintain the system pressure within a safe range, at the expense of steam quality. The condenser could rapidly take out most heat to avoid overpressure.