• 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 Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.42-48
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• 2008

The house of quality (HOQ) involves subjective and ambiguous information typically through a likert scale, It isimportant to validate consistency of such input in the HOQ before rating the fmal importance of technicalrequirements, Previously, a methodology was developed to test the consistency of relationship strengths in theHOQ between roof matrix and relationship matrix. We described disadvantages of the previous method andpropose a new approach based on the permutation test. Advantages of the proposed method are illustrated withan example.

• The Korean Journal of Emergency Medical Services
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• v.9 no.1
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• pp.43-53
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• 2005

The purpose of this study was to survey a perception of frequency & importance level of job performance, from 249 paramedics who were working at fire station. The job related activities of 4 duties, 18 tasks and 145 task elements were checked by 4 rating scale. The data were analyzed using a SPSS program for descriptive statistics. The results of the study were as follows ; 1. Some of the most frequent tasks were medical tx, managing people & organization, trauma care, pt assessment, general coping skill 2. Some of the most frequent task elements were preparation of written reports, operation of pt lifting supplies, transportation of patients on stretchers, administration of cervical collar and utilization of scoop stretcher. 3. Some of the highest level of importance in task were resuscitation of circulation, surgical tx, safety & infection control, environmental emergency care, trauma care. 4. Some of the highest level of importance in task elements were administration of cervical collar, adult CPR, infant CPR, child CPR, and AED. 5. The highest level of task elements in perception of frequency & importance were administration of cervical collar, infection control after pt care, utilization of long back board, disinfection of ambulance after ride a long, care of chest pain pt, care of unconscious pt, tx of asthma. 6. A difference between frequent & importance score were due to lack of supplies(41%), structural problems(30%) and medical control system(16%), lack of skills(10%), Suggestion; 1. This paper would be more reliable and confirm through wilder range of survey. 2. It would be necessary of more depth survey through dacom study from paramedic. 3. Development of field oriented protocol & curriculum that based on task elements which have high score of both frequency & importance level is required.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.2
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• pp.138-151
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• 2012

This study determines a consumer retail store choice by applying the Analytic Hierarchy Process (AHP) method for multi-criteria decision-making in the fashion retail industry. The study provides detailed and relevant information for management, marketers of fashion retail stores, and to improve competition between suppliers. Data was collected in February 2011 from questionnaires completed by 319 university students in Busan, South Korea. One of the major findings of this study was that consumer store preference was affected by the following factors in order of importance: product, image, service quality, and purchase facilitation. Brand image was assessed to be the most important of the evaluation elements, followed by individuality, style, and price. The results of rating the relative importance and priority of fashion retailers showed that department stores ranked most highly, followed by outlet malls, Internet shopping malls, brand malls, and discount stores.

• Fashion & Textile Research Journal
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• v.19 no.2
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• pp.230-239
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• 2017

In the clothes industry, there are lack of experts including technical designers who can analyze the fit of clothes. This study is to provide practical data available for fit analysis education by distinguishing the differences in standards and aspects of garment fit between experts and novices, through the eye-tracking technology to quantify the sense of fit. For this study, two groups were organized; one composed of 7 experts with over 15 year-experience including technical designers and patternmakers, and the other composed of 7 novices who are students majoring in clothing. Wearing the goggle type eye-tracker Tobii Pro Glasses 2, the participants in the experiments were required to conduct fit analyses for a pair of pants on a live model. After those experiments, they were required to check the items for fit analysis and assess the importance level of them on a questionnaire. The differences between the two groups in the ratios of total visit count and total visit duration by each AIO(Area of Interest) of clothes were analyzed through non-parametric statistical test. The results of eye tracking experiments showed that experts focused on center front and back line, crotch area, and side seam, while novice's fixation points were dispersed around the pants. The survey results showed that the experts put importance on the center line position and its verticality, front-back proportion of side seam line, and front-back proportion of waist line, 71.4~100% of whom checked them, while 14.3% of the novices checked them.

• Journal of Distribution Research
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• v.4 no.3
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• pp.65-86
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• 2000

From the perspective of relationship marketing, salespeople acts important role by creating values and developing, establishing long-term relationship with customers. This study is designed to suggest validated measure of evaluating retail salespeople in department store setting in an effort to facilitate active future studies. For this purpose, this study investigated attributes of retail salespeople based on series of personal interviews and literature reviews, and validated its measurement via exploratory and confirmatory factor analysis. In addition, this study explored consumers' rating of the importance of attributes related to some selected consumer variables (consumer knowledge, product involvement, and demographic variables). The findings of this study revealed five dimensions of retail salespeople attributes: Service Mind, Sales Efforts, Product Knowledge, Comfortable Impression and Sale Inducing Skill. Customers of department stores put importance of salespeople attributes in this order. Some dimensions of consumer knowledge and product involvement do affect consumers' rating of retail salespeople attributes. Theoretical and managerial implications were suggested based on empirical results.

• Korean journal of applied entomology
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• v.52 no.4
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• pp.327-333
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• 2013

Plant parasitic nematodes were isolated from 274 soil samples collected from soybean fields in Korea. Nematode importance rating in soybean is proposed based on this study and by reviewing other reports. Soybean cyst nematode, Heterodera glycines is the most important nematode species and rated as $1^{st}$ because it detected from 38%(range 25-51%) of soil samples with high density except Jeju province. Root-knot nematode, Meloidogyne spp. is rated $2^{nd}$ and is more widely distributed in southern provinces, Gyeongnam, Jeonnam, and Jeju province (detection rate ranged 16-44%). Pratylenchus is rated $3^{rd}$ and is more frequently detected from northern provinces such as Gyeonggi and Gangwon (detection rate ranged 10-13%). Helicotylenchus is rated $4^{th}$ and is particularly important in Jeju province (detection rate is 62% and numbers averaged 571 nematodes/$300cm^3$ soil), which is the main production area for sprouting soybean in Korea. Tylenchorhynchus, Paratylenchus, Criconema, Criconemoide, Mesocriconema, Ogma, Xiphinema, Paratrichodorus, and Trichodorus occur in low frequency and density, thus they are rated to $5^{th}$. We propose to delete following nematode genus from the list of soybean parasitic nematode in Korea because their parasitism on soybean is unconfirmed or negligible; Tylenchus, Aphelenchus, Aphelenchoides, Ditylenchus, Hirschmanniella immamuri, Basiria graminophila, Psilenchus, and Pseudhalenchus. Therefore, we revised 30 species in 16 genera as soybean parasitic nematodes in Korea. Importance rating is $1^{st}$ Heterodera glycines, $2^{nd}$ Meloidogyne spp., $3^{rd}$ Pratylenchus spp. and $4^{th}$ Helicotylenchus spp. especially in Jeju province.

• Journal of the Korean Dietetic Association
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• v.2 no.2
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• pp.123-140
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• 1996

The purpose of this study was to examine financial management practices in elementary school foodservices. Respondents were asked to provide information on demographics, operational characteristics, financial management activities(responsibility, importance and time demand). Data were collected from 106 elementary school foodservice using the mail questionnaire. The results were as follows 1. Time demand of 14 financial management activities was examined. The results of time-demand showed that most financial activities were performed about once per month. Reporting, inventory checking and production cost accounting were performed several times per week. 2. Major financial management activities performed by school dietitians were inventory checking, record keeping, production cost accounting, and foodservice operation planning. 3. Results of the importance rating of 14 financial management activities showed that the production cost accounting, budgeting, controlling meal costs, reporting the national treasury accounts, and inventory checking were rated as very important(4.00-4.49). Factor analysis was conducted on the importance ratings. Five activities were differentiated such as budgeting, record keeping, cost controlling, cost accounting, and reporting. The cost controlling task was identified at the most important one among them. 4. Important ratings for reporting were found to be significantly different by age, and years of experience. The younger and the less experienced were responded with higher scores on reporting. Analysis of variance for the importance scales by meal costs per one person, food cost percentage, labor cost percentage was conducted, but significant differences were not founded.

• Korean Journal of Psychosomatic Medicine
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• v.19 no.1
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• pp.3-14
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• 2011

Delirium is a common psychiatric disorder and occurs in many hospitalized older patients and has serious consequences including increased mortality rate. Despite its importance, health care clinicians often fail to recognize delirium or misdiagnosed as other psychiatric illness. Awareness of the etiologies and risk factors of delirium should enable clinicians to focus on patients at risk and to recognize delirium symptoms early. To improve early recognition of delirium, emphasis should be given to terminology, psychopathology and knowledge regarding clinical rating scale for delirium in the specific medical and surgical clinical settings. In this study, authors introduce rating scales for delirium and knowledge of clinical diagnostic process for delirium and give rise to appropriate assessment of delirium in the clinical situation.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4339-4347
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• 2014

Purpose: This study aimed at exploring treatment delay (TD) among cancer patients in China with an attempt to develop a practical methodology facilitating frontline Chinese clinicians in promoting earlier cancer diagnosis and treatment. Materials and Methods: The study comprised framework development, qualitative interviews and paired factor rating. Framework development utilized systematic literature review, soft systems thinking and consensus groups. Qualitative interviews employed a checklist of open questions soliciting information about all the domains included the framework from cancer patients drawn via stratified randomized sampling of inpatients at 10 hospitals in Hefei, China. Paired factor rating used a self-developed computer aid and the interviewed patients as referring cases to weigh the relative importance of the factors listed in the framework in terms of their contributions to specific components of total delay (TD). Results: a) A conceptual framework was proposed consisting of a 6-step path to TD and 36 category determinants. b) A total of 227 patients were interviewed; their TD was 267.3 mean or 108 median days ranging from 0 to 2475 days; average appraisal, illness, behavioral, preparation and treatment delay accounted for 52.1%, 9.4%, 0.30%, 8.8% and 29.4% of the TD respectively. Individual side factors were rated substantially more important than environmental side factors (60% vs. 40%); most influential TD factors included cancer symptoms, overall health, family relations and knowledge about cancer and health. Conclusions: The framework proposed together with the interviewing and rating approaches used provide a potential new methodology for understanding cancer patients' TD and promoting earlier cancer treatment.