• Progress in Medical Physics
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• v.11 no.1
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• pp.49-57
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• 2000

New method about the dose optimization problem in radiation treatment was researched. Since all conditions are more complex and there are more relevant variables, the solution of three-dimensional treatment planning is much more complicate than that of current two-dimensional one. There(ore, in this study, as a method to solve three-dimensional dose optimization problem, the considered variables was minized and researched by reducing the domain that solutions can exist and pre-determining the important beam parameters. First, the dangerous beam range that passes critical organ was found by coordinate transformation between linear accelerator coordinate and patient coordinate. And the beam size and rotation angle for rectangular collimator that conform tumor at arbitrary beam position was also determined. As a result, the available beam position could be reduced and the dependency on beam size and rotation angle, that is very important parameter in treatment planning, totally removed. Therefore, the resultant combinations of relevant variables could be greatly reduced and the dose optimization by objective function can be done with minimum variables. From the above results, the dose optimization problem was solved for the two-dimensional radiation treatment planning useful in clinic. The objective function was made by combination of dose gradient, critical organ dose and dose homogeniety. And the optimum variables were determined by applying step search method to objective function. From the dose distributions by optimum variables, the merit of new dose optimization method was verified and it can be implemented on commercial radiation treatment planning system with further research.

• Journal of Food Hygiene and Safety
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• v.29 no.1
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• pp.16-20
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• 2014

The prevalence of Bacillus cereus was determined in salad and Kimbab obtained from commercial retailers. Among the 100 salad samples analyzed, 54 samples were negative for B. cereus, whereas the bacterial count was < 10 colony forming units (CFU)/g in 8 samples, < 100 CFU/g in 25 samples, < 1,000 CFU/g in 11 samples, and > 1,000 CFU/g in 2 samples. The mean (standard deviation) was 1.18 log CFU/g (${\pm}0.71$ log CFU/g). In Kimbab, B. cereus was isolated from 20 samples; the mean bacterial count was 1.01 log CFU/g (${\pm}0.71$ log CFU/g). On the basis of the monitoring data, a statistical sampling plan was determined with the NEW sampleplan program (ICMSF), which was used as an analytical tool. To identify the most suitable sampling plan, the microbial limits (m, M) and the maximum allowable number of sample units yielding unsatisfactory test results (c) were varied, but the number of samples units, n = 5, was fixed. Sampling plans showing an acceptable probability (Pa) over 0.95 were considered suitable. Two plans (A and B) were finally suggested. Parameters for plan A are n = 5, c = 0, m = 1,000, and M = 10,000 and for plan B are n = 5, c = 2, m = 100, and M = 1,000. Interestingly, the latter plan was identical to the microbial sampling plan used in New Zealand. Thus, it was concluded that the suggested plan can be used as a sampling plan that is in line with international standards.

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.5
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• pp.615-623
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• 2001

A study of mammary function in relation to glucose metabolism of first lactation Bali cows on grass-legume diets was carried out using 12 primiparous cows (initial BW $263.79{\pm}21.66kg$) for 16 weeks starting immediately post calving. The animals were randomly allocated into 4 dietary treatment groups R1, R2, R3 and R4, receiving from the last 2 months of pregnancy onwards, rations based on a mixture of locally available grass and legume feed ad libitum. On a DM basis R1 contained 70% elephant grass (PP, Penicetum purpureum) plus 30% Gliricidia sepia leaves (GS), R2 was 30% PP plus 25% GS supplemented with 55% Hibiscus tilliacius leaves (HT, defaunating effect), R3 and R4 were 22.5% PP+41.25% GS+11.25% HT+25% concentrate, with R4 supplemented with zinc-diacetate. TDN, CP and zinc contents of the diets were 58.2%, 12.05% and 18.3 mg/kg respectively for R1, 65.05%, 16.9% and 25.6 mg/kg respectively for R2, 66.03%, 16.71% and 29.02 mg/kg respectively for R3 and 66.03%, 16.71% and 60.47 mg/kg respectively for R4. Milk production and body weights were monitored, an energy and protein balance trial conducted, overall glucose kinetics parameters assessed, mammary blood flow (MBF) and metabolite arteriovenous differences (${\Delta}AVs$) measured to get uptake data and mammary performance relationships. Parameters of glucose kinetics at peak lactation or during dry condition were not affected by ration quality. Glucose pool size, space of distribution and flux increased by 61.77, 62.26 and 82.08%, respectively, during lactation compared to the dry period. Mean glucose flux of lactating Bali cows was $5.52mg/min.kgBW^{0.807}$ which resembles the range of values of temperate dairy cows. Calculation showed that glucose requirements for maintenance, milk lactose and fat-glycerol synthesis, and the formation of NADPH reached 461.69 g for a yield of 1 kg/d or equal to 320.62 mg/min, which was less than the average glucose flux of lactating Bali cows of 481.35 mg/min. Mammary blood flow (MBF) values ranged from 56 to 83 l/h for the different treatments and the ratio MBF per kg milk produced improved from av. 1540 l/kg for R1 to av. 967 l/kg for R4 treated cows. Mammary glucose uptake ranged from 6.27 to 12.03 g/h or 120 to 140 g/kg milk. Glucose uptake was mass-wise 2 to 4 times the amount secreted as lactose, which indicated values less than the calculated mammary glucose needs and that little lactose was synthesized. The excess glucose taken-up was used for other metabolic processes. Linear relationships between metabolite ${\Delta}AVs$ and arterial blood plasma concentration [A] showed that in Bali cows triglycerides (TG), phenylalanine (Phe) and tyrosine (Tyr) have high coefficients of determination, i.e. 0.77, 0.81 and 0.69, respectively. For glucose, the relationship is quadratic with an $R^2$ value of 0.49. It was concluded that lactose synthesis was inadequate, which led to a speculation that milk yield could be improved by increased lactose synthesis.

• Journal of the Korean earth science society
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• v.26 no.6
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• pp.524-540
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• 2005

This study has focused on the amount of evaporites and geochemical characteritics of evaporites from the acid mine drainage and on the variation of constituents in acid mine drainage during evaporation. The various colors of evaporites are frequently observed at the rock surfaces contacting acid mine drainage. In order to produce evaporites in the laboratory, acid mine drainages were sampled from the abandoned mine areas (GTa, GTb, GH and GB) and air-dried at room temperature. During the evaporation of acid mine drainages, TDS, EC values and the concentrations of major and minor ions increased, whereas ER and DO values decreased with time. The concentration of Fe increased gradually with evaporation time in the GTb and GB, whereas GH founded in one day but rapidly not detected in the other day after due to removal of Fe by formation-precipitation of amorphous Fe hydroxide. The amounts of the evaporites were produced in amounts of 4 g (GTa), 5 g (GB), 15 g (GH), and 24 g (GTb) from 4 liter of acid mine drainage after 80 days of the evaporation, respectively. In linear analysis from the products with the parameters which are the EC, TDS, salinity, ER, DO and pH contents in field, the determination coefficients were 0.98, 0.99, 0.98, 0.88, 0.89, and 0.25 respectively. If we measure the parameters in field, it would be easy to estimate the amount of evaporites in acid mine drainage. Gypsum and epsomite were identified in all of the evaporites by x-ray powder diffraction studies. Evaporite (GTb) was heated at 52, 65, 70, 95, 150, 250, and 350oC for one hour in electrical furnaces. Gypsum, $CaSO_4\cdot1/2H_2O$ and kieserite were identified in the heated evaporite by XRD. With increased heating temperature, the intensity of the peak at $7.66/AA$ (diagnostic peak of gypsum), the peak at 5.59A ($CaSO_4{\cdot}1/2H_2O)$ and the peak at $4.83{\AA}$ (kieserite) decreased in x-ray diffraction due to dehydration. In the SEM and EDS analysis for the evaporite, gypsum of well-crystallized, radiating cluster of fibrous, acicular, and columnar shapes were observed in all samples. Ca was not detected in the EDS analysis of the flower structures of GTb. Because of that, the evaporite with flower structures is thought to be eposmite.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.363-371
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• 2023

To construct a ship, blocks of various sizes must be moved and erected . In this process, lugs are used such that they match the block fastening method and various functions suitable for the characteristics of each shipyard facility. The sizes and shapes of the lugs vary depending on the weight and shape of the block structures. The structure is reinforced by welding the doubling pads to compensate for insufficient rigidity around the holes where the shackle is fastened. As for the method of designing lugs according to lifting loading conditions, a simple calculation based on the beam theory and structural analysis using numerical modeling are performed. In the case of the analytical method, a standardized evaluation method must be established because results may differ depending on the type of element and modeling method. The application of this ambiguous methodology may cause serious safety problems during the process of moving and turning-over blocks. In this study , the effects of various parameters are compared and analyzed through numerical structural analysis to determine the modeling conditions and evaluation method that can evaluate the actual structural response of the lug. The modeling technique that represents the plate part and weld bead around the lug hole provides the most realistic behavior results. The modeling results with the same conditions as those of the actual lug where only the weld bead is connected to the main body of the lug, showed a lower ulimated strength compared with the results obtained by applying the MPC load. The two-dimensional shell element is applied to reduce the modeling and analysis time, and a safety working load was verified to be predicted by reducing the thickness of the doubling pad by 85%. The results of the effects of various parameters reviewed in the study are expected to be used as good reference data for the lug design and safe working load prediction.

• Korean Journal of Environmental Agriculture
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• v.23 no.2
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• pp.85-91
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• 2004

The objective of this study is to determine the optimum conditions of operational parameters using factorial design for phenol degradation in photocatalytic oxidation reactors. Factorial design is widely used to select the dominant factors and their ranges in experiments involving several factors where it is necessary to study the effect of factors on a response. The effects of initial concentration of phenol, intensity of UV light and surface area of catalyst on phenol degradation were investigated. Two levels were considered in this study so that the experiment was a $2^3$ factorial design with three replicates. The experimental results show that an increase in initial concentration of phenol from 5 to 50 mg/L intensity of UV light from 5,000 to $20,000\;{\mu}W/cm^2$, and surface area of catalyst from 740 to $2,105\;cm^2$ enhanced the phenol degradation rate by an average of 1.86, 1.79, and 2.10 mg/L hr, respectively. Interaction effects do not appear to be as large on the phenol degradation rate as the main effects of single factors. The optimum working condition for photocatalytic oxidation reactors, despite the higher three factors the better removal rate, is the highest surface area or catalyst.

• Korean Journal of Soil Science and Fertilizer
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• v.17 no.4
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• pp.363-370
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• 1984

In order to predict the possible fertilizer requirement from the K supplying capacity of soil, the relative K activity ratio, Kas/Kai and Gapon coefficients, KG. were determined for the soil samples before flooding and at heading stage of rice in pot experiment. These parameters assumed as the K supplying capacity of soils were discussed through correlation with other factors such as grain yields or the amounts of $K_2O$ uptake by the rice plant. The results may be summarized as follows: 1. The KGo values in soils before flooding were 7.8, 6.6, and 7.1, whereas the Kas/Kai values were 1.37, 1.26 and 2.11, respectively, in clay, loam and sandy loam soils. 2. The significant yield responses to the application of potassium fertilizer were observed whenever the KG values in soils at heading stage become larger to the original KG values, regardless of any levels of fertilizer application. 3. The linear correlations between the exchangeable cation ratios [Kex./(Ca+Mg) ex.:me/100g] in soils and the potassium activity ratios ($[K^+]/\sqrt{[Ca^{{+}{+}}+Mg^{{+}{+}}]}$: mole/l) in equilibrium solutions were observed with different linear gradients according to the soil properties. 4. The Kas/Kai in the soils, estimated prior to the experiment, showed high correlations with the grain yields or the amounts of $K_2O$ uptake in the all treatments, while the Kas/Kai and the KGo in the soils at heading stage showed high correlations with the grain yields or the amounts of $K_2O$ uptake in only N 15 Kg/10a treatments. 5. The Kas/Kai and the KGo values determined in the soil at heading stage of rice showed high negative correlation each other and they could be used as soil factors for predicting potassium fertilizer requirement.

• Food Science and Preservation
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• v.23 no.2
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• pp.211-217
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• 2016

This study was carried out to determine the shelf-life of cricket powder and investigate the changes in its quality during storage. To determine the shelf-life, cricket powder was stored at temperatures of 25, 35, and $40^{\circ}C$ for 6 months. The changes in quality parameters of the cricket powder, such as moisture content, color, acid value, volatile base nitrogen (VBN), fatty acid, growth of microorganisms, and sensory appeal were investigated. The moisture content of the cricket powder increased during storage but did not show any significant difference at 6 months of storage. L value was increased at $25^{\circ}C$ storage but decreased at 35 and $40^{\circ}C$. However, there were no significant different in a and b values. The acid value decreased more rapidly at higher temperatures, while the VBN content was not changed. The major composition of fatty acids of cricket powder were palmitic acid, oleic acid, and linoleic acid. Their content was not changed at various the storage temperatures. No aerobic and coliform bacteria grew in the powder during the whole storage period. Cricket powder stored at $25^{\circ}C$ and $35^{\circ}C$ showed similar scores in sensory evaluation, but it storaged at $40^{\circ}C$ showed the significant difference (p<0.05). Moisture content, acid value, oleic acid, and flavor were selected as the criteria for shelf-life establishment of cricket powder. Based on these parameters, especially the moisture content, the shelf life of cricket powder was likely to be 18 months when stored at $25^{\circ}C$.

• Korean journal of applied entomology
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• v.53 no.4
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• pp.375-380
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• 2014

The sweetpotato whitefly (SPW), Bemisia tabaci Gennadius, is a major pest in tomato greenhouses on Jeju Island because they transmit viral diseases. To develop practical sampling methods for adult SPWs, yellow-color sticky traps were used in commercial tomato greenhouses throughout the western part of Jeju Island in 2011 and 2012. On the basis of the size and growing conditions in the tomato greenhouses, 20 to 30 traps were installed in each greenhouse for developing a sampling plan. Adult SPWs were more attracted to horizontal traps placed 60 cm above the ground than to vertical trap placed 10 cm above the plant canopy. The spatial patterns of the adult SPWs were evaluated using Taylor's power law (TPL) and Iwao's patchiness regression (IPR). The results showed that adult SPWs were aggregated in each surveyed greenhouse. In this study, TPL showed better performance because of the coefficient of determination ($r^2$). On the basis of the fixed-precision level sampling plan using TPL parameters, more traps were required for higher precision in lower SPW densities per trap. A sequential sampling stop line was constructed using TPL parameters. If the treatment threshold was greater than 10 maximum adult SPWs on a trap, the required traps numbered 15 at a fixed-precision level of 0.25. In estimating the mean density per trap, the proportion of traps with two or more adult SPWs was more efficient than whole counting: ${\ln}(m)=1.19+0.90{\ln}(-{\ln}(1-p_T))$. The results of this study could be used to prevent the dissemination of SPW as a viral disease vector by using accurate control decision in SPW management programs.