• Journal of Korea Soil Environment Society
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• v.1 no.1
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• pp.47-54
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• 1996

Soil pollution indices (SPI) were designed for estimating quality of soil polluted with arsenic and heavy metals. Applying the quality reference value of soil based on its multifunctional purpose was a key step. For considereing multifunctions of soil, soil was classified into 4 groups-agricultural land, residential area, recreational area, factorial site. Then, each concentration of arsenic and each of five heavy metals (Cd, Cu, Hg, Pb, Zn) in soils grouped was transformed to a mathematical value based on the soil quality reference value which may stand for ecological impact. Soil pollution score (SPS) was the addition of the 6 values transformed, and the range of the SPS was divided into 4 Soil Pollution Classes (SPC). The SPC 1, 2, 3, and 4 were SPS <100, SPS 100-200, SPS >200-300, and SPS >300, repectively. SPS and SPC were evaluated with the results of the data from employing the Soil Network of 1994. Based on the soil quality reference values, SPS and SPC of the Soil Network's data were transformed and classified, respectively. Then, SPS and SPC were compared with arsenic and the 5 heavy metal contents of their reference values resulted from the Soil Network's. From this method, soil quality of most of the Soil Network area was estimated to be healthy. However, ca. 3.0~4.0% of the Soil Network area was determined in a range of slightly and heavily polluted. As the mean value of SPS of the Soil Network's was 66.2 which indicates most of soil evaluated was healthy. When the SPSs of the data were divided into 4 groups of SPC, Class 1 (Good quality of soil), Class 2 (Need to be checked area 1), Class 3 (Need to be checked area 2) and Class 4 (Polluted area) were 87.0, 9.4, 2.4, 1.2%, respectively. Using SPI were comparable to those of heavy metal contents in soils, and would be comprehenve to determine the status of soil qulity. Methodology of the developing SPI would be applicable to the other soil pollutants such as organic and inorganics than arsenic and 5 heavy metals used here.

• KSBB Journal
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• v.14 no.3
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• pp.328-336
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• 1999

A green microalga, Chlorella vulgaris UTX 259, was cultivated in a bench-scale raceway pond. During the culture, 15%(v/v) $CO_2$ was supplied and industrial wastewater discharged from a steel-making plant was used as a culture medium. In a small scale culture bottle, the microalga grew up to 1.8 g $dm^{-3}$ of cell concentration and ammonia was completely removed from the wastewater with an yield coefficient of 25.7 g dry cell weight $g^{-1}\;NH_3-N$. During the bottle-culture, microalga was dominant over heterotrophic microorganisms in the culture medium. Therefore, the amount of carbon dioxide fixation could be estimated from the change of dry cell weight. In a semi-continuous operation of raceway pond with intermittent lighting (12 h light and 12 h dark), increase of dilution rate resulted in increase of the ammonia removal rate as well as the $CO_2$ fixation rate but the ammonia removal efficiency decreased. Ammonia was not completely removed from the medium (wastewater) of raceway pond which was operated in a batch mode under a light intensity up to 20 klux. The incomplete removal of ammonia was believed due to insufficient light supply. A mathematical model, capable of predicting experimental data, was developed in order to simulate the performance of the raceway pond under the light intensity of sun during a bright daytime. Simulation results showed that the rates of $CO_2$ fixation and ammonia removal could be enhanced by increasing light intensity. According to the simulation, 80 mg $dm^{-3}$ of ammonia in the medium could be completely removed if the light intensity was over 60 klux with a continuous lighting. Under the optimal operating condition determined by the simulation, the rates of carbon dioxide fixation and ammonia removal in the outdoor operation of raceway pond were estimated as high as $24.7 g m^{-2} day^{-1}$ and $0.52 g NH_3-N m^{-2} day^{-1}$, respectively.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Progress in Medical Physics
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• v.16 no.2
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• pp.89-96
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• 2005

In this study, we investigated the effect of time gating threshold on the delivered dose at a organ with internal motion by respiration. Generally, the internal organs have minimum motion at exhalation during normal breathing. Therefore to compare the dose distribution time gating threshold, in this paper, was determined as the moving region of target during 1 sec at the initial position of exhalation. The irradiated fields were then delivered under three conditions; 1) non-moving target 2) existence of the moving target in the region of threshold (1sec), 3) existence of the moving target region out of threshold (1.4 sec, 2 sec). And each of conditions was described by the moving phantom system. It was compared with the dose distributions of three conditions using film dosimetry. Although the treatment time increased when the dose distributions was obtained by the internal motion to consider the TGT, it could be obtained more exact dose distribution than in the treatment field that didn't consider the internal motion. And it could be reduced the unnecessary dose at the penumbra region. When we set up 1.4 sec of threshold, to reduce the treatment time, it could not be obtained less effective dose distribution than 1 sec of threshold. Namely, although the treatment time reduce, the much dose was distributed out of the treatment region. Actually when it is treated the moving organ, it would rather measure internal motion and external motion of the moving organ than mathematical method. If it could be analyzed the correlation of the internal and external motion, the treatment scores would be improved.

• Progress in Medical Physics
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• v.9 no.4
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• pp.227-245
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• 1998

A most appropriate model of 3-D conformal radiotherapy has been induced by clinical evaluation and animal study, and therapeutic gains were evaluated by numerical equation of tumor control probability(TCP) and normal tissue complication probability (NTCP). The radiation dose to the tumor and the adjacent normal organs was accurately evaluated and compared using the dose volume histogram(DVH). The TCP and NTCP was derived from the distribution of given dosage and irradiated volume, and these numbers were used as the biological index for the assessment of the treatment effects. Ten patients with liver disease have been evaluated and 3 dogs were sacrificed for this study. Based on the 3-D images of the tumor and adjacent organs, the optimum radiation dose and the projection direction which could maximize the radiation effect while minimizing the effects to the adjacent organs could be decided. 3). The most effective collimation for the normal adjacent organs was made through the beams eye view with the use of multileaf collimator. When the dose was increased from 50Gy to 70Gy, the TCP for the conventional 2-port radiation and the 5-port multidimensional therapy was 0.982 and 0.995 respectively, while the NTCP was 0.725 and 0.142 respectively, suggesting that the 3-D conformal radiotherapy might be the appropriate therapy to apply sufficient radiation dose to the tumor while minimizing the damages to the normal areas of the liver. Positive correlation was observed between the NTCP and the actual complication of the normal liver in the animal study. The present study suggest that the use of 3-D conformal radiotherapy and the application of the mathematical models of TCP and NTCP may provide the improvements in the treatment of hepatoma with enhanced results.

• Journal of Wetlands Research
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• v.22 no.3
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• pp.194-199
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• 2020

Unlike in the past, the world is facing water shortages due to climate change and difficulties in simultaneously managing the risks of flooding. The Four Major Rivers project was carried out with the aim of realizing a powerful nation of water by managing water resources and fostering the water industry, and the construction period was relatively short compared to the unprecedented scale. Therefore, the prediction and analysis of how the river environment changes after the Four Major Rivers Project is insufficient. Currently, part of the construction section of the Four Major Rivers Project is caused by repeated erosion and sedimentation due to the effects of sandification caused by large dredging and flood-time reservoirs, and the head erosion of the tributaries occurs. In order to solve these problems, the riverbed maintenance work was installed, but it resulted in erosion of both sides of the river and the development of new approaches and techniques to keep the river bed stable, such as erosion and excessive sedimentation, is required. The water agent plays a role of securing a certain depth of water for the main stream by concentrating the flow so much in the center and preventing levee erosion by controlling the flow direction and flow velocity. In addition, Groyne products provide various ecological environments by forming a natural form of riverbeds by inducing local erosion and deposition in addition to the protection functions of the river bank and embankment. Therefore, after reviewing the method of determining the shape of the Groyne structure currently in use by utilizing the mobile limit flow rate and marginal reflux force, a new Critical Movement Velocity(${\bar{U}}_d$) and a new resistance coefficient formula considering the mathematical factors applicable to the actual domestic stream were developed and the measures applicable to Groyne installation were proposed.

• Childhood Kidney Diseases
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• v.4 no.2
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• pp.144-153
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• 2000

Purpose : Effects to predict tile progression of chronic renal failure (CRF) in children, using mathematical models based on transformations of serum creatinine (Scr) concentration, have failed. Error may be introduced by age-related variations in creatinine production rate. Height (Ht) is a reliable reference for creatinine production in children. Thus, Scr, factored for Ht, could provide a more accurate predictive model. We examined this hypothesis. Methods : The progression of of was detected in 63 children who proceeded to end-stage renal disease. Derivatives of Scr, including 1/Scr, log Scr & Ht/Scr, were defined fir the period Scr was between 2 and 5 mg/dl. Regression equation were used to predict the time, in months, to Scr > 10 mg/dl. The prediction error (PE) was defined as the predicted time minus actual time for each Scr transformation. Result : The PE for Ht/Scr was lower than the PE for either 1/Scr or log Scr (median: -0.01, -2.0 & +10.6 mos respectively; P<0.0001). For children with congenital renal diseases, the PE for Ht/Scr was also lower than for the other two transformations (median: -1.2, -3.2 & +8.2 mos respectively; P<0.0001). However, the PEs for children with glomerular diseases was not as clearly different (median: +0.9, +0.5 & +9.9 respectively). In children < 13 yrs, PE for Ht/Scr was tile lowest, while in older children, 1/Scr provided the lowest PE but not significantly different from that for Ht/Scr. The logarithmic transformation tended to predict a slower progression of CRF than actually occurred. Conclusion : Scr, floored for Ht, appears to be a useful model to predict the rate of progression of CRF, particularly in the prepubertal child with congenital renal disease.

• Journal of Educational Research in Mathematics
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• v.21 no.4
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• pp.327-344
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• 2011

This study is the first step for us toward improving high school students' capability of statistical inferences, such as obtaining and interpreting the confidence interval on the population mean that is currently learned in high school. We suggest 5 underlying concepts of 'discretion of contingency and inevitability', 'discretion of induction and deduction', 'likelihood principle', 'variability of a statistic' and 'statistical model', those are necessary to appreciate statistical inferences as a reliable arguing tools in spite of its occasional erroneous conclusions. We assume those 5 concepts above are to be gradually developing in their school periods and Korean mathematics textbooks of grades 1-12 were analyzed. Followings were found. For the right choice of solving methodology of the given problem, no elementary textbook but a few high school textbooks describe its difference between the contingent circumstance and the inevitable one. Formal definitions of population and sample are not introduced until high school grades, so that the developments of critical thoughts on the reliability of inductive reasoning could not be observed. On the contrary of it, strong emphasis lies on the calculation stuff of the sample data without any inference on the population prospective based upon the sample. Instead of the representative properties of a random sample, more emphasis lies on how to get a random sample. As a result of it, the fact that 'the random variability of the value of a statistic which is calculated from the sample ought to be inherited from the randomness of the sample' could neither be noticed nor be explained as well. No comparative descriptions on the statistical inferences against the mathematical(deductive) reasoning were found. Few explanations on the likelihood principle and its probabilistic applications in accordance with students' cognitive developmental growth were found. It was hard to find the explanation of a random variability of statistics and on the existence of its sampling distribution. It is worthwhile to explain it because, nevertheless obtaining the sampling distribution of a particular statistic, like a sample mean, is a very difficult job, mere noticing its existence may cause a drastic change of understanding in a statistical inference.

• Korean Journal of Environmental Agriculture
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• v.30 no.2
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• pp.169-178
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• 2011

BACKGROUND: This study aimed to estimate the measurement uncertainty associated with determination of cadmium and lead from tomato paste by ICP/MS. The sources of measurement uncertainty (i.e. sample weight, final volume, standard weight, purity, molecular weight, working standard solution, calibration curve, recovery and repeatability) in associated with the analysis of cadmium and lead were evaluated. METHODS AND RESULTS: The guide to the expression of uncertainty was used for the GUM (Guide to the expression of Uncertainty in Measurement) and Draft EURACHEM/CITAC (EURACHEM: A network of organization for analytical chemistry in Europe/Co-Operation on International Traceability in Analytical Chemistry) Guide with mathematical calculation and statistical analysis. The uncertainty components were evaluated by either Type A or Type B methods and the combined standard uncertainty were calculated by statistical analysis using several factors. Expected uncertainty of cadmium and lead was $0.106{\pm}0.015$ mg/kg (k=2.09) and $0.302{\pm}0.029$ mg/kg (k=2.16), on basis of 95% confidence of Certified Reference Material (CRM) which was within certification range of $0.112{\pm}0.007$ mg/kg for cadmium (k=2.03) and $0.316{\pm}0.021$ mg/kg for lead (k=2.01), respectively. CONCLUSION(s): The most influential components in the uncertainty of heavy metals analysis were confirmed as recovery, standard calibration curve and standard solution were identified as the most influential components causing uncertainty of heavy metal analysis. Therefore, more careful consideration is required in these steps to reduce uncertainty of heavy metals analysis in tomato paste.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.403-414
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• 2004

In the accompanying paper, we proposed a real. time volumetric imaging method using a cross array based on receive dynamic focusing and synthetic aperture focusing along lateral and elevational directions, respetively. But synthetic aperture methods using spherical waves are subject to beam spreading with increasing depth due to the wave diffraction phenomenon. Moreover, since the proposed method uses only one element for each transmission, it has a limited transmit power. To overcome these limitations, we propose a new real. time volumetric imaging method using cross arrays based on synthetic aperture technique with linear wave fronts. In the proposed method, linear wave fronts having different angles on the horizontal plane is transmitted successively from all transmit array elements. On receive, by employing the conventional dynamic focusing and synthetic aperture methods along lateral and elevational directions, respectively, ultrasound waves can be focused effectively at all imaging points. Mathematical analysis and computer simulation results show that the proposed method can provide uniform elevational resolution over a large depth of field. Especially, since the new method can construct a volume image with a limited number of transmit receive events using a full transmit aperture, it is suitable for real-time 3D imaging with high transmit power and volume rate.