• Fashion & Textile Research Journal
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• v.20 no.6
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• pp.722-732
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• 2018

This study was to develop a dress form that is highly representative of the body shapes of senior men in their 50s and 60s. And this research was compared the measurements and forms of three different dress forms available in the market, in order to analyze the body type and suitability and provide a standard for developing and utilizing the dress forms. After extracting the body shapes of the senior men's 3D shape, the body type that is curvature on the back prevalent among senior men, was chosen. The dress form was created as follows: 3D modeling and rendering, printing with a FDM-type 3D printer. The dress forms were 3D-scanned and the 3D data was analyzed - classification drop value, area deviation, compared horizontal section and vertical section. The results were as follows: This suggested that the area deviation amount at the chest and hip circumference levels was larger in the commercial products than in the dress form in this study, while that at the waist circumference level was larger in the dress form in this study. The vertical length of the lateral shoulder point-waist circumference was smaller, the side shape showed severe curvature on the back, and the waist circumference was larger in the senior men dress form than the commercial products. The dress form developed in this study reflected the body type of senior men and, therefore, were suitable for fitting when creating clothes for senior men.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.11
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• pp.95-104
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• 2018

Healthcare technology has been growing and fostering cooperation between industry, university and hospitals as growth engines in korea. So, the medibio research institutes in hospital have been constructed to promote research and industrialization centering on healthcare technology. The purpose of this study is to investigate the cases of research institutes in hospitals, and search the characteristics of building organization of medibio research laboratory facilities. Case study is investigated by floor plan, homepage and site visits about five research institutes selected in research-driven hospitals. The facility title and size of research laboratory is originated from site area and research building location. The building function include not only the research lab and business office reflecting on the development platform, and but assembly and meeting room in the ground level. Laboratory floor plans have three types, rectangular, rectangular+linear and linear type, one is traditional and efficient, the others are people and friendly. And building core types are correlated with lab space unit modules, single and double side core are shown in rectangular type. All the laboratories are open lab, composed with laboratory bench and research note writing desk facing the lab service and enclosed lab-support area. And they have communication space looking as warm and cozy common area for the innovation, convergence and collaboration. As the high risk of contamination and high standard for safety and security, equipment and facilities are well managed with biological environment including BSC, fume hood, PCR classification, eye washing and emergency shower.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.593-601
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• 2022

We call "fruad" the cases that are not frequently occurring but cause significant losses. Fraud detection is commonly encountered in various applications, including wafer production in the semiconductor industry. It is not trivial to directly extend the standard binary classification methods to the fraud detection context because the misclassification cost is much higher than the normal class. In this article, we propose the functional fraud detection support vector machine (F²DSVM) that extends the fraud detection support vector machine (FDSVM) to handle functional covariates. The proposed method seeks a classifier for a function predictor that achieves optimal performance while achieving the desired sensitivity level. F²DSVM, like the conventional SVM, has piece-wise linear solution paths, allowing us to develop an efficient algorithm to recover entire solution paths, resulting in significantly improved computational efficiency. Finally, we apply the proposed F²DSVM to the defective wafer detection problem and assess its potential applicability.

• Food Science of Animal Resources
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• v.42 no.2
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• pp.313-320
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• 2022

Brazil is considered as a great broiler feet exporter, especially for the Chinese trade. Contact lesions at the tibiotarsal region are responsible for economic losses and there is no model for its classification, thereby this study presents a fast and practical grade system to be used in the poultry industry and proposes these lesion characterizations into three different grades. For this, correlation was made between macroscopic, histological findings and microbiological quantification (Escherichia coli, Staphylococcus spp., Streptococcus spp. and sulphite-reducing clostridia) from contact lesions in the tibiotarsal region of 112 broiler carcasses, divided in four groups (n=28), accordingly to the lesion's intensity. There were no significant differences in microbiological quantification among the groups (p>0.05) except for the grade 3 group, as grade 1 and 2 lesions were in the early stages and histopathological changes such as ulceration were not observed. In grade 3 lesion group, it was observed bacterial cocci grume and ulceration at the articular region and significantly higher microbiological count (p<0.05) for E. coli and Staphylococcus spp. In conclusion, the visual standard proposed in this work, correlated and confirmed by the histopathologic, and microbiologic characterization, allows to precise and fast ascertainment of the contact lesion grade in the tibiotarsal regions of broiler carcasses. Moreover, it should be highlighted that grades 1 and 2 alterations are not caused by an inflammatory process caused by pathogenic agents and should not be considered a public health risk.

• 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.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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• pp.445-453
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• 2012

The aim of this paper was to prove that if the risk level in combined tasks was improved through evaluation of postural load of liquid weight measurement process, the workload level and ratio of exposure time would be changed, and the time of process would be seen concurrently. Background: According to results of epidemiological studies conducted by Korea Occupational Safety & Health Agency, 122 musculoskeletal disorders occurred during 1992 to 2008, in which manufacturing industry covers 96(78.7%) of total. However, this is an insufficient level and only occupies 39% based on the South Korea's manufacturing standard industrial classification(246 industries). Method: Firstly, the number of batches weighed on one day(460min) was investigated based on the work performed and Weight measured weekly. VCR recording was taken based on the level of liquid ingredients prescribed for 1batch using the Camcorder. After dividing a 356 sec video into 1 sec using the screen capture function in Gom player, the job classification was performed by analyzing the change of working postures, which revealed 148 working postures. Time measurement was decided by time of the postures was being maintained. Then, the REBA analysis was performed for the working postures. The ratio of Exposure time was calculated based on the measurement time and REBA Score. In addition, the recommendations were designed and implementation was carried out for the working postures with REBA Score higher than 3. Finally, after the intervention, REBA measurement, time measurement, and ratio of exposure time were calculated for the comparison of works before and after improvement. Results: The number of work elements was decreased by 30.4% from 148 to 103 after improvement. The results of time measurement showed that the time was reduced by 46.3% from 356 sec to 191 sec. And the ratio of exposure time was also improved by 52.1% from 0% to 52.1% after improvement. Conclusion: The reduction of time was found to improve the productivity of management. Furthermore, because the reduction of ratio of exposure time and the improvement of workload level are the improvement of discomfort, it would contribute to the improvement of the worker's psychological working posture. Application: These results would contribute to musculoskeletal disease prevention and management performance. Further studies for other industries would be needed based on this case study.

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.511-544
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• 2016

Standards boost technological innovation by promoting information sharing, compatibility, stability and quality. Identifying groups of companies that particularly benefit from these functions of standards in their technological innovation and commercialization helps to customize planning and implementation of standards-related policies for demand groups. For this purpose, this study engages in profiling of SMEs whose R&D objective is to respond to standards as well as those who need to implement standards system for technological commercialization. Then it suggests a prediction model that can distinguish such companies from others. To this end, decision tree analysis is conducted for profiling of characteristics of subject SMEs through data mining. Subject SMEs include (1) those that engage in R&D to respond to standards (Group1) or (2) those in need of product standard or technological certification policies for commercialization purposes (Group 2). Then the study proposes a prediction model that can distinguish Groups 1 and 2 from others based on several variables by adopting discriminant analysis. The practicality of discriminant formula is statistically verified. The study suggests that Group 1 companies are distinguished in variables such as time spent on R&D planning, KoreanStandardIndustryClassification (KSIC) category, number of employees and novelty of technologies. Profiling result of Group 2 companies suggests that they are differentiated in variables such as KSIC category, major clients of the companies, time spent on R&D and ability to test and verify their technologies. The prediction model proposed herein is designed based on the outcomes of profiling and discriminant analysis. Its purpose is to serve in the planning or implementation processes of standards-related policies through providing objective information on companies in need of relevant support and thereby to enhance overall success rate of standards-related projects.

• Journal of Korea Technology Innovation Society
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• v.17 no.3
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• pp.467-489
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• 2014

The purpose of this study is to explore the suitable creative class in korea as the core capital of creative urban growth under creative economy era. We are test to find it for two types of creative class. One is Richard Florida(2002)'s creative class, the other is Mcgranahan & Wojan(2007)'s recasting creative class. Data on 2010 for this paper are generated from Statistics Korea. As a result, we find that the economic geography of creative class is highly concentrated. Furthermore, the geography of creative class is strongly associated with innovation index and high-technology industry location. And Mcgranahan & Wojan(2007)'s creative class is more strong relationship between all dependent variables than Florida's. We also find that it has better power of explanation than Florida's with all of them in regression analysis. According to the results, this study suggests some solutions. First, this study can be provided to government and local policy makers as basis data and practical policy guide to attract creative class. Second, this paper presents standard about a diversity of definitions for creative class in Korea. Third, this research also facilitates follow-up studies about regional economic growth and creative climates.

• International Commerce and Information Review
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• v.14 no.3
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• pp.159-183
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• 2012

Promoted in places like Korea, the central government and the local governments that can provide information on which to base investment policy to attract foreign direct mutation-specific gravity model (Shift-Share Model) In this study, the decrease of foreign direct investment performance using factors looked up in the industry. The sample period of 2009, 2010, 2011 nationwide (metropolitan and non-metropolitan separated) of foreign direct investment performance for Industry Standard Industrial Classification (Division) was conducted. Factors to look at the results of the National Growth Effect(NS), the industrial structure effect (IM), local allocation effect(RS) to decrease foreign direct investment in 2010 and 2011 non-metropolitan, metropolitan national growth effect(RS) is negative(-) has a value. Because it appears to be the aftermath of the global recession, the impact on the domestic economy Metropolitan area and the Industrial Mix Effect(IM) to the development of education, culture, business, and transportation, etc. in the development of service industries than in non-metropolitan valid environment. In the sector of services (food accommodation, business services, entertainment), We did it, was able to find the function. However, the Regional Share Effect(RS) be competitive in the manufacturing sector in metropolitan areas in the metal and chemical sectors have been identified. These results seems to enhance the competitiveness of the region, such as the metropolitan area's excellent workforce. Shift-Share analysis technique based on competitive factors of the region, to find the failure has limitations.

• Journal of Technology Innovation
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• v.22 no.3
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• pp.1-35
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• 2014

This study analyzed convergence status among input technologies used in technology development with Technology I-O analysis. It was another version of industry input-output analysis which is used in technology planning. This case is an analysis of association between technology an product. The subjects of analysis were 401 tasks that applied to '2012 Convergence Technology Development Project for Small and Medium Businesses' promoted by Korea Technology & Information Promotion Agency for Small and Medium Enterprises. The process of analysis is as followed. First step, we made a matrix table as an input of technology input-output analysis. Input was defined by technology and output was defined by the product. Input technology was defined in a 3-digit code under National Science Technology Classification and output products were defined in a 5-digit under National Standard Industry Code. Second, the Spillover ratio among technologies were calculated and was used to make a picture of technology linkage. As a result of analysis, technology spillover of embedded S/W was the highest in IT convergence, mold product in ET convergence, and functional cosmetics development technology in BT convergence. In general, IT convergence had many element technologies with high technology spillover, and ET had a small number of element technologies with high technology spillover. Therefore, investment effect of element technology is expected to be large if investment on element technologies with high technology spillover is important for vitalizing convergence.