• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.93-124
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• 2003

This paper studies the financial analyst's forecasting activities on the firm's operating performance during the period from 1999 to 2003. In this study, financial analyst's forecasting activities are focused on the sales, operating income and net income and financial analyst's forecasting accuracy, forecasting revising patterns and forecasting activities to the unexpected firm's operating performance are studied. Some empirical findings in this study are as follows. First, standard estimate error on the sales, operating income and net income are all significantly negative value and so financial analyst's forecast on the firm's operating performance are upwardly biased. Second, domestic financial analyst's forecasting activities is relatively more accuracy than foreign financial analyst's forecasting activities. Third, forecasting time is more close to the end of the operating performance announcement day, forecasting activities are more accuracy. Fourth, comparing with individual financial analyst's forecast, consensus forecast is more accuracy. Fifth, in the comparative forecasting activities study according to the prior firm's operating performance, financial analyst's forecasting revision activities are found to be upward or downward. Sixth, financial analysts overreact in the sales forecast and underreact in the operating income and net income forecast. Seventh, in the empirical analysis on the Easterwood-Nutt's test model(1999) which the firm's performance change are divided into the expected performance change and the unexpected performance change, it is found that financial analyst's forecasting activities on the firm's operating performance are systematically optimistic.

• Korean Chemical Engineering Research
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• v.48 no.6
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• pp.717-724
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• 2010

The flash point is one of the most important physical properties used to determine the potential for fire and explosion hazards of flammable liquids. Despite the needs of the experimental flash point data for the design and construction of chemical plants, there is often a significant gap between the demands for the data and their availability. This study have built and compared two models of partial least squares(PLS) and support vector machine(SVM) to predict the experimental flash points of 893 organic compounds out of DIPPR 801. As the independent variables of the models, 65 functional groups were chosen based on the group contribution method that was oriented from the assumption that each fragment of a molecule contributes a certain amount to the value of its physical property, and the logarithm of molecular weight was added. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, an optimization technique should be used to get three parameters of SVM model. This work adopted particle swarm optimization that is one of heuristic optimization methods. As the selection of training data can affect the prediction performance, 100 data sets of randomly selected data were generated and tested. The PLS and SVM results of the average absolute errors for the whole data range from 13.86 K to 14.55 K and 7.44 K to 10.26 K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.561-572
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• 2014

The backwater effect at a tributary junction increases the risk of flood damage such as inundation and levee overflow. In particular, the rapid increase in water level may cause injury to persons. The purpose of this research is the development of the real-time flood forecasting technique as a part of the non-structural flood damage reduction measures. To this end, the factors causing a water level rising at a junction were examined, and the empirical formula for predicting flood level at a junction was developed using the calculated discharge and water level data from the well-constructed hydraulic model. The water level predictions show that average absolute error is about 0.2~0.3m with the maximum error of 1.0m and peak time can be captured prior to 0~5 hr. From the results of this study, the real-time flood forecasting system of a tributary junction can be easily constructed, and this system is expected to be utilized for reduction of flood inundation damage.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.169-187
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• 2023

Aggregates from 84 cities and counties in Korea were tested for quality to allow analysis of the physical characteristics of aggregates from river, land, and forest environments. River and land aggregates were analyzed for 18 test items, and forest aggregates for 12 test items. They were classified according to watershed and geology, respectively. The observed physical characteristics of the river aggregates by basin were as follows: aggregates from the Geum River basin passed through 2.5, 1.2, 0.6, 0.3, 0.15, and 0.08 mm sieves; clay lumps constituted the Nakdong River basin material; aggregates from the Seomjin River basin passed through 10, 5, and 2.5 mm sieves; those from the Youngsang River basin passed through 1.2, 0.6, 0.3, 0.15, and 0.08 mm sieves; and aggregates from the Han River basin passed through 10, 5, 2.5, 1.2, 0.6, 0.3, and 0.08 mm sieves, Stability; Standard errors were analyzed for the average amount passing through 10, 0.6, and 0.08 mm silver sieves, and performance rate showed different distribution patterns from other physical characteristics. Analysis of variance found that 16 of the 18 items, excluding the absorption rate and the performance rate, had statistically significant differences in their averages by region. Considering land aggregates by basin, those from the Nakdong River basin excluding the Geum River basin had clay lumps, those from the Seomjin River basin had 10 and 5 mm sieve passage, aggregates from the Youngsang River basin had 0.08 mm sieve passage, and those from the Han River basin had 10, 0.6, and 0.08 mm sieve passage. The standard error of the mean of the quantity showed a different distribution pattern from the other physical characteristics. Analysis of variance found a statistically significant difference in the average of all 18 items by region. Analyzing forest aggregates by geology showed distributions of porosity patterns different from those of other physical characteristics in metamorphic rocks (but not igneous rocks), and distributions of wear rate and porosity were different from those of sedimentary rocks. There were statistically significant differences in the average volume mass, water absorption rate, wear rate, and Sc/Rc items by lipid.

• Journal of the Korean Society of Radiology
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• v.17 no.4
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• pp.541-549
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• 2023

The aim of this study wasto conduct a quantitative analysis of CT image quality according to an algorithm designed to reduce metal artifacts induced by metal components. Ten baseline images were obtained with the standard filtered back-projection algorithm using spectral detector-based CT and CT ACR 464 phantom, and ten images were also obtained on the identical phantom with the standard filtered back-projection algorithm after inducing metal artifacts. After applying the to raw data from images with metal artifacts, ten additional images for each were obtained by applying the virtual monoenergetic algorithm. Regions of interest were set for polyethylene, bone, acrylic, air, and water located in the CT ACR 464 phantom module 1 to conduct compare the Hounsfield units for each algorithm. The algorithms were individually analyzed using root mean square error, mean absolute error, signal-to-noise ratio, peak signal-to-noise ratio, and structural similarity index to assess the overall image quality. When the Hounsfield units of each algorithm were compared, a significant difference was found between the images with different algorithms (p < .05), and large changes were observed in images using the virtual monoenergetic algorithm in all regions of interest except acrylic. Image quality analysis indices revealed that images with the metal artifact reduction algorithm had the highest resolution, but the structural similarity index was highest for images with the metal artifact reduction algorithm followed by an additional virtual monoenergetic algorithm. In terms of CT images, the metal artifact reduction algorithm was shown to be more effective than the monoenergetic algorithm at reducing metal artifacts, but to obtain quality CT images, it will be important to ascertain the advantages and differences in image qualities of the algorithms, and to apply them effectively.

• Korean Journal of Ecology and Environment
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• v.39 no.1 s.115
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• pp.13-20
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• 2006

The changing patterns of water temperature and turbidity in streams entering Imha Reservoir were studied. The turbidity variation near the intake tower in Imha Reservoir was investigated in relation with the variation of water temperature and turbidity in streams. Water temperature was estimated using multi-regression method with air temperature and dew point as independent variables. Peak turbidity was also estimated using non-linear regression method with rainfall intensity as an independent variable. Although more independent variables representing watershed characteristics seem to be needed to increase estimation accuracies, the methodology used in this study can be applied to estimate water temperature and peak turbidity in other streams.

• Journal of Korea Port Economic Association
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• v.28 no.2
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• pp.75-93
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• 2012

The steel cargoes as the core raw materials for the manufacturing industry have important roles for increasing the handling volume of the port. In particular, steel cargoes are fundamental to vitalize Port of Incheon because they have recognized as the primary key cargo items among the bulk cargoes. In this respect, the IPA(Incheon Port Authority) ambitiously developed the port complex facilities including dedicated terminals and its hinterland in northern part of Incheon. However, these complex area has suffered from low cargo handling records and has faced operational difficulties due to decreased net profits. In general, the import and export steel cargo volumes are sensitively fluctuated followed by internal and external economy index. There is a scant of research for forecasting the steel cargo volume in Incheon port which used in various economy index. To fill the research gap, the aim of this research is to predict the steel cargoes of Port of Incheon using the well established methodology i.e. System Dynamics. As a result, steel cargoes volume dealt with in Incheon port is forecasted from about 8 million tons to about 10 million tons during simulation duration (2011-2020). The Mean Absolute Percentage Error (MAPE) is measured as 0.0013 which verifies the model's accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• The Journal of Korean Academy of Prosthodontics
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• v.48 no.1
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• pp.1-7
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• 2010

Purpose: The purpose of this study was to evaluate the fit of zirconia core using MAD/MAM system comparing to that of conventional metal-ceramic and CAD/CAM system. Materials and methods: Duplicating the prepared resin tooth, 50 improved stone dies were fabricated. These dies are classified as a group of 5 to create the core. The groups were composed of metal-ceramic, $Cercon^{(R)}$, $Ceramill^{(R)}$, $Rainbow^{TM}$, and $Zirkonzhan^{(R)}$. Each core was cemented to stone die, and then, absolute marginal discrepancy was measured with microscope at a magnification of ${\times}50$. Statistical analysis was done with one-way ANOVA test and Tukey's HSD test. Results: The mean absolute marginal discrepancy for metal-ceramic was $51.97{\pm}23.38{\mu}m$, for $Cercon^{(R)}$ was $62.16{\pm}25.88{\mu}m$, for $Ceramill^{(R)}$ was $67.64{\pm}40.38{\mu}m$, for $Rainbow^{TM}$ was $125.07{\pm}42.19{\mu}m$, and for $Zirkonzhan^{(R)}$ was $105{\pm}44.61{\mu}m$. Conclusion: 1. Fit of margin was identified as in the order of metal-ceramic, $Cercon^{(R)}$, $Ceramill^{(R)}$, $Zirkonzhan^{(R)}$, and $Rainbow^{TM}$. 2. Absolute marginal discrepancy of the zirconia core that designed by MAD/MAM system had significant differences in order of $Ceramill^{(R)}$, $Zirkonzhan^{(R)}$, and $Rainbow^{TM}$. 3. The mean absolute marginal discrepancy between $Cercon^{(R)}$ and $Ceramill^{(R)}$ did not show significant differences.