• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.141-156
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• 2013

Researchers in welfare services of local government in Korea have rather been on isolated issues as disables, childcare, aging phenomenon, etc. (Kang, 2004; Jung et al., 2009). Lately, local officials, yet, realize that they need more comprehensive welfare services for all residents, not just for above-mentioned focused groups. Still cases dealt with focused group approach have been a main research stream due to various reason(Jung et al., 2009; Lee, 2009; Jang, 2011). Social Security Information System is an information system that comprehensively manages 292 welfare benefits provided by 17 ministries and 40 thousand welfare services provided by 230 local authorities in Korea. The purpose of the system is to improve efficiency of social welfare delivery process. The study of local government expenditure has been on the rise over the last few decades after the restarting the local autonomy, but these studies have limitations on data collection. Measurement of a local government's welfare efforts(spending) has been primarily on expenditures or budget for an individual, set aside for welfare. This practice of using monetary value for an individual as a "proxy value" for welfare effort(spending) is based on the assumption that expenditure is directly linked to welfare efforts(Lee et al., 2007). This expenditure/budget approach commonly uses total welfare amount or percentage figure as dependent variables (Wildavsky, 1985; Lee et al., 2007; Kang, 2000). However, current practice of using actual amount being used or percentage figure as a dependent variable may have some limitation; since budget or expenditure is greatly influenced by the total budget of a local government, relying on such monetary value may create inflate or deflate the true "welfare effort" (Jang, 2012). In addition, government budget usually contain a large amount of administrative cost, i.e., salary, for local officials, which is highly unrelated to the actual welfare expenditure (Jang, 2011). This paper used local government welfare service data from the detailed data sets linked to the Social Security Information System. The purpose of this paper is to analyze the factors that affect social welfare spending of 230 local authorities in 2012. The paper applied multiple regression based model to analyze the pooled financial data from the system. Based on the regression analysis, the following factors affecting self-funded welfare spending were identified. In our research model, we use the welfare budget/total budget(%) of a local government as a true measurement for a local government's welfare effort(spending). Doing so, we exclude central government subsidies or support being used for local welfare service. It is because central government welfare support does not truly reflect the welfare efforts(spending) of a local. The dependent variable of this paper is the volume of the welfare spending and the independent variables of the model are comprised of three categories, in terms of socio-demographic perspectives, the local economy and the financial capacity of local government. This paper categorized local authorities into 3 groups, districts, and cities and suburb areas. The model used a dummy variable as the control variable (local political factor). This paper demonstrated that the volume of the welfare spending for the welfare services is commonly influenced by the ratio of welfare budget to total local budget, the population of infants, self-reliance ratio and the level of unemployment factor. Interestingly, the influential factors are different by the size of local government. Analysis of determinants of local government self-welfare spending, we found a significant effect of local Gov. Finance characteristic in degree of the local government's financial independence, financial independence rate, rate of social welfare budget, and regional economic in opening-to-application ratio, and sociology of population in rate of infants. The result means that local authorities should have differentiated welfare strategies according to their conditions and circumstances. There is a meaning that this paper has successfully proven the significant factors influencing welfare spending of local government in Korea.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

• Journal of Preventive Medicine and Public Health
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• v.28 no.4 s.51
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• pp.809-844
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• 1995

The purposes of this study are to define the scope of occupational health management and to classify occupational management by review of related journals from 1945 to 1994 in Korea. The steps of this study were as follows: (1) Search of secondary reference; (2) Collection and review of primary reference; (3) Survey; and (4) Analysis and discussion. The results were as follows ; 1. Most of the respondents majored in occupational health(71.6%), and were working in university (68.3%), males and over the age 40. Seventy percent of the respondents agreed with the idea that classification of occupational health management is necessary, and 10% disagreed. 2. After integration of the idea of respondents, we reclassified the scope of occupational health management. It was defined 3 parts, that is , occupational health system, occupational health service and others (such as assessment, epidemiology, cost-effectiveness analysis and so on). 3. The number of journals on occupational health management was 510. It was sightly increased from 1986 and abruptly increased after 1991. The kinds of journals related to occupational health management were The Korean Journal of Occupational Medicine(18.2%), Several Kinds of Medical Colloge Journal(17.0%), The Korean Journal Occupational Health(15.1%), The Korean Journal of Preventive Medicine(15.1%) and others(34.6%). As for the contents, the number of journals on occupational health management systems was 33(6.5%) and occupational health services 477(93.5%). Of the journals on occupational health management systems, the number of journals on the occupational health resource system was 15(45.5%), occupational finance system 8(24.2%), occupational health management system 6(18.2%), occupational organization 3(9.1%) and occupational health delivery system 1 (3.0%). Of the journals on occupational health services, the number of journals on disease management was 269(57.2%), health management 116(24.7%), working environmental management 85(18.1%). As for the subjects, the number of journals on general workers was 185(71.1%), followed by women worker, white coiler workers and so on. 4. Respondents made occupational health service(such as health management, working environmental management and health education) the first priority of occupational health management. Tied for the second are quality analysis(such as education, training and job contents of occupational health manager) and occupational health systems(such as the recommendation of systems of occupational and general disease and occupational health organization). 5. Thirty seven respondents suggested 48 ideas about the future research of occupational health management. The results were as follows: (1) Study of occupational health service 40.5%; (2) Study of organization system 27.1%; (3) Study of occupational health system (e.g. information network) 8.3%; (4) Study of working condition 6.2%; and (5) Study of occupational health service analysis 4.2%.

• Journal of Animal Environmental Science
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• v.12 no.3
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• pp.141-150
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• 2006

To optimise the efficient use of nutrients in pig slurry is to cultivate friendly environmental crops. This field survey is to investigate the actual conditions of pig slurry utilization for cultivation of crops in the agricultural farm, based on the survey for 407 selected farms in 9 provinces included 78 counties in Korea. The results obtained in this survey were summarized as follow ; The motive which came to use pig slurry in the agricultural farm were production of friendly environmental crops (29.7%), economy of chemical fertilizer (25.1%), spontaneously (19.2%), inducement of neighboring farmhouse (16.0%), increase of soil fertility (9.3%), and the others (0.7%), respectively. The proportions of pig slurry application land were 56.5% for.ice paddy, 22.6% for dry field, 13.3% for orchard, 4.4% for controlled agriculture and 3.2% for other, respectively. The number of times of pig slurry utilization per year were once (48.9%), twice (31.9%), thrice (14.0%), and the others (5.2%), respectively. The controversial points of pig slurry utilization were malodor (54.1%), insufficiency of spread equipment (22.1%), inconvenience (14.5%), over application (3.4%), over cost (2.9%), heavy metal (1.7%), sanitation (1.0%) and the other (0.2%), respectively. The results indicated that pig slurry could be used as fertilizer source of friendly environmental crops, but further studies are needed to determine the application method and value of the pig slurry for crop cultivation.

• Journal of Distribution Research
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• v.15 no.3
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• pp.1-34
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• 2010

Introduction The purpose of this research is to develop overall model which involves the effect of ongoing support services by franchisor on franchisee's relationship quality(trust, satisfaction, and commitment) and business performance(financial and non-financial performance), and to investigate the relationships among trust, satisfaction, commitment, financial and non-financial performance. This study also suggests franchise business or franchise system should be based on long-term orientation between franchisor and franchisee rather than short-term orientation, or transactional relationship, and proposes the most effective way of providing on-going support services by franchisor with franchisee thru symbiotic relationship among franchisor and franchisee Research Model and Hypothesis The research model as Figure 1 shows the variables on-going support services which affect the relationship quality between franchisor and franchisee such as trust, satisfaction, and commitment, and also analyze the effects of relationship quality on business performance including financial and non-financial performance We established 12 hypotheses to test as follows; Relationship between on-going support services and trust H1: On-going support services factors (product category & price, logistics service, promotion, information providing & problem solving capability, supervisor's support, and education & training support) have positive effect on franchisee's trust. Relationship between on-going support services and satisfaction H2: On-going support services factors (product category & price, logistics service, promotion, information providing & problem solving capability, supervisor's support, and education & training support) have positive effect on franchisee's satisfaction. Relationship between on-going support services and commitment H3: On-going support services factors (product category & price, logistics service, promotion, information providing & problem solving capability, supervisor's support, and education & training support) have positive effect on franchisee's commitment. Relationship among relationship quality: trust, satisfaction, and commitment H4: Franchisee's trust has positive effect on franchisee's satisfaction. H5: Franchisee's trust has positive effect on franchisee's commitment. H6: Franchisee's satisfaction has positive effect on franchisee's commitment. Relationship between relationship quality and business performance H7: Franchisee's trust has positive effect on franchisee's financial performance. H8: Franchisee's trust has positive effect on franchisee's non-financial performance. H9: Franchisee's satisfaction has positive effect on franchisee's financial performance. H10: Franchisee's satisfaction has positive effect on franchisee's non-financial performance. H11: Franchisee's commitment has positive effect on franchisee's financial performance. H12: Franchisee's commitment has positive effect on franchisee's non-financial performance. Method The on-going support services were defined as an organized system of continuous supporting services by franchisor for the purpose of satisfying the expectation of franchisee based on long-term orientation and classified into six constructs such as product category & price, logistics service, promotion, providing information & problem solving capability, supervisor's support, and education & training support. The six constructs were measured agreement using a 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree)as follows. The product category & price was measured by four items: menu variety, price of food material provided by franchisor, and support for developing new menu. The logistics service was measured by six items: distribution system of franchisor, return policy for provided food materials, timeliness, inventory control level of franchisor, accuracy of order, and flexibility of emergency order. The promotion was measured by five items: differentiated promotion activities, brand image of franchisor, promotion effect such as customer increase, long-term plan of promotion, and micro-marketing concept in promotion. The providing information & problem solving capability was measured by information providing of new products, information of competitors, information of cost reduction, and efforts for solving problems in franchisee's operations. The supervisor's support was measured by supervisor operations, frequency of visiting franchisee, support by data analysis, processing the suggestions by franchisee, diagnosis and solutions for the franchisee's operations, and support for increasing sales in franchisee. Finally, the of education & training support was measured by recipe training by specialist, service training for store people, systemized training program, and tax & human resources support services. Analysis and results The data were analyzed using Amos. Figure 2 and Table 1 present the result of the structural equation model. Implications The results of this research are as follows: Firstly, the factors of product category, information providing and problem solving capacity influence only franchisee's satisfaction and commitment. Secondly, logistic services and supervising factors influence only trust and satisfaction. Thirdly, continuing education and training factors influence only franchisee's trust and commitment. Fourthly, sales promotion factor influences all the relationship quality representing trust, satisfaction, and commitment. Fifthly, regarding relationship among relationship quality, trust positively influences satisfaction, however, does not directly influence commitment, but satisfaction positively affects commitment. Therefore, satisfaction plays a mediating role between trust and commitment. Sixthly, trust positively influence only financial performance, and satisfaction and commitment influence positively both financial and non-financial performance.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.191-199
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• 2018

Purpose : In this study, we evaluated the usefulness of colloid gel(slime) as a compensator for irregular patient surfaces in radiation therapy. Materials and Methods : For this study, colloid gel suitable for treatment was made and four experiments were conducted to evaluate the applicability of radiation therapy. Trilogy(Varian) and CT(SOMATOM, Siemens) were used as treatment equipment and CT equipment. First, the homogeneity according to the composition of colloid gel was measured using EBT3 Film(RIT). Second, the Hounsfield Unit(HU) value of colloid gel was measured and confirmed by CRIS phantom, Eclipse RTP(Eclipse 13.1, Varian) and CT. Third, to measure the deformation and degeneration of colloid gel during the treatment period, it was measured 3 times daily for 2 weeks using an ion chamber(PTW-30013, PTW). The fourth experiment was compared the treatment plan and measured dose distributions using bolus, rice, colloid gel and additional, dose profiles in an environment similar to actual treatment using our own acrylic phantom. Result : First experiment, density of the colloid gel cases 1, 2 and 3 was $1.02g/cm^3$, $0.99g/cm^3$ and $0.96g/cm^3$. When the homogeneity was measured at 6 MV and 9 MeV, case 1 was more homogeneous than the other cases, as 1.55 and 1.98. In the second experiment, the HU values of case 1, 2, 3 were 15 and when the treatment plan was compared with the measured doses, the difference was within 1 % at all 9, 12 MeV and a difference of -1.53 % and -1.56 % within the whole 2 % at 6 MV. In the third experiment, the dose change of colloid gel was measured to be about 1 % for 2 weeks. In the fourth experiment, the dose difference between the treatment plan and EBT3 film was similar for both colloid gel and bolus, rice at 6 MV. But colloid gel showed less dose difference than bolus and rice at 9 MeV. Also, dose profile of colloid gel showed a more uniform dose distribution than the bolus and rice. Conclusion : In this study, the density of colloid gel prepared for radiation therapy was $1.02g/cm^3$ similar to the density of water, and alteration or deformation was not observed during the radiotherapy process. Although we pay attention to the density when manufacturing colloid gel, it is sufficient in that it can deliver the dose uniformly through the compensation of the patient's body surface more than the bolus and rice, and can be manufactured at low cost. Further studies and studies for clinical applications are expected to be applicable to radiation therapy.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.75-81
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• 2019

Purpose: Helmet type bolus for 3D printer is being manufactured because of the disadvantages of Bolus materials when photon beam is used for the treatment of scalp malignancy. However, PLA, which is a used material, has a higher density than a tissue equivalent material and inconveniences occur when the patient wears PLA. In this study, we try to treat malignant scalp tumors by using M3 wax helmet with 3D printer. Methods and materials: For the modeling of the helmet type M3 wax, the head phantom was photographed by CT, which was acquired with a DICOM file. The part for helmet on the scalp was made with Helmet contour. The M3 Wax helmet was made by dissolving paraffin wax, mixing magnesium oxide and calcium carbonate, solidifying it in a PLA 3D helmet, and then eliminated PLA 3D Helmet of the surface. The treatment plan was based on Intensity-Modulated Radiation Therapy (IMRT) of 10 Portals, and the therapeutic dose was 200 cGy, using Analytical Anisotropic Algorithm (AAA) of Eclipse. Then, the dose was verified by using EBT3 film and Mosfet (Metal Oxide Semiconductor Field Effect Transistor: USA), and the IMRT plan was measured 3 times in 3 parts by reproducing the phantom of the head human model under the same condition with the CT simulation room. Results: The Hounsfield unit (HU) of the bolus measured by CT was $52{\pm}37.1$. The dose of TPS was 186.6 cGy, 193.2 cGy and 190.6 cGy at the M3 Wax bolus measurement points of A, B and C, and the dose measured three times at Mostet was $179.66{\pm}2.62cGy$, $184.33{\pm}1.24cGy$ and $195.33{\pm}1.69cGy$. And the error rates were -3.71 %, -4.59 %, and 2.48 %. The dose measured with EBT3 film was $182.00{\pm}1.63cGy$, $193.66{\pm}2.05cGy$ and $196{\pm}2.16cGy$. The error rates were -2.46 %, 0.23 % and 2.83 %. Conclusions: The thickness of the M3 wax bolus was 2 cm, which could help the treatment plan to be established by easily lowering the dose of the brain part. The maximum error rate of the scalp surface dose was measured within 5 % and generally within 3 %, even in the A, B, C measurements of dosimeters of EBT3 film and Mosfet in the treatment dose verification. The making period of M3 wax bolus is shorter, cheaper than that of 3D printer, can be reused and is very useful for the treatment of scalp malignancies as human tissue equivalent material. Therefore, we think that the use of casting type M3 wax bolus, which will complement the making period and cost of high capacity Bolus and Compensator in 3D printer, will increase later.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.