• Journal of Service Research and Studies
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• v.9 no.4
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• pp.41-62
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• 2019

In this intangible good-oriented, modern service economy era, we have to first understand the characteristics of the healthcare service in order to enhance the competitiveness of the healthcare industry and achieve continuous growth. In addition, service nature and characteristics should be reinforced so that connections can be made to the organizational job performance. To achieve the aforementioned results, this study analyzes the direct effects service nature and characteristics have on job performance in the healthcare industry and investigates the indirect effects with individual personality as the moderating effect. While conducting this study, a total of 340 healthcare workers were surveyed. Survey data from a total of 315 workers were used for analysis during empirical investigation of the research hypothesis. According to the analysis, it was proven that interactivity and horizontality among service nature and characteristics have a positive (+) effect on job effectiveness. This means that customer needs can be identified at customer touchpoints to quickly and accurately provide customers with the products and services they want, while horizontality among service nature and characteristics have a positive (+) effect on job effectiveness. This means that customer needs can be identified at customer touchpoints to quickly and accurately provide customers with the products and services they want, while horizontal communication enhance from department to department and from colleague to colleague within the organization can be linked to job performance. Also, with regards to the relationship shared between the customer or the patient, the job performance of healthcare workers may also improve if they provide customers with their desired service as an expert at the same level. In a rapidly changing healthcare environment, if the healthcare service nature and characteristics are put into practical use, it will be possible to propel the growth of hospitals and sustain it while investigating the moderating effects of individual personality, a partial moderating effect was observed for self-esteem and growth desire. As the study on service nature and characteristics came about only just recently, there is a needs for futher research. The study focuses on the healthcare service industry and hopefully, it will serve as a base study that can be applied to different service industries as well.

• Journal of Korea Technology Innovation Society
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• v.10 no.4
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• pp.654-686
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• 2007

To estimate and analyze an interested science and technology level in any case requires three basic informations: (1) relative positions of our technology level, (2) other relevant technology level of the world best country holding the state of the art technology, and (3) its theoretical or practical maximum level within a certain period of time. Further, additional information from analyzing its respective rate of technology changes is necessary. It seems that most previous empirical or case studies on technology level have not considered third and fourth informations seriously, and thus critically have missed important findings from a dynamic point of view on the matter. A dynamic approach considering types of development processes and paths as well as current position needs an application of a concept of technology development stages and respective growth curves. This paper proposes a new method of approach and application by implementing relatively simple types of the growth curve(S-curve) such as logistic and Comports curves and applying estimation results of these curves to ten core technologies of the growth engines for the next future generation in Korea. The study implies that Korean science and technology level in general clearly gets higher as it approaches to a recent time of period, but relative technology gap from the world best in terms of catching-up period does not get better or narrower in case of at least part of the concerned technologies such as bio new drugs and human organs, and intelligence robots. The possibility does exist that some of our concerned technologies shooting for the next future generation may not come to the world highest level in the near future. The purpose of this study is to propose possibilities of catching-up, if any, by estimating its relevant type of growth pattern by way of measuring and analyzing technology level and by analyzing the technology development process through a position analysis. At this stage this study tries to introduce a new theoretical approach of estimating technology level and its application to existing case study results(data) from Korea Institute of Science and Technology Planning and Evaluation(KISTEP) and Korea Institute of Industrial Technology Evaluation and Planing(ITEP), for years of 2004 and 2006 respectively. The study has some limitations in terms of accuracy of measuring(estimating) a relevant growth curve to a particular technology, feasibility of applying estimated results, accessing and analyzing panel experts opinions. Hence, it is recommended that further study would follow soon enough to verify practical applicability and possible expansion of the study results.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.482-488
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• 2014

This paper aims to analyze user's emotion automatically by analyzing Twitter, a representative social network service (SNS). In order to create sentiment analysis models by using machine learning techniques, sentiment labels that represent positive/negative emotions are required. However it is very expensive to obtain sentiment labels of tweets. So, in this paper, we propose a sentiment analysis model by using self-training technique in order to utilize "data without sentiment labels" as well as "data with sentiment labels". Self-training technique is that labels of "data without sentiment labels" is determined by utilizing "data with sentiment labels", and then updates models using together with "data with sentiment labels" and newly labeled data. This technique improves the sentiment analysis performance gradually. However, it has a problem that misclassifications of unlabeled data in an early stage affect the model updating through the whole learning process because labels of unlabeled data never changes once those are determined. Thus, labels of "data without sentiment labels" needs to be carefully determined. In this paper, in order to get high performance using self-training technique, we propose 3 policies for updating "data with sentiment labels" and conduct a comparative analysis. The first policy is to select data of which confidence is higher than a given threshold among newly labeled data. The second policy is to choose the same number of the positive and negative data in the newly labeled data in order to avoid the imbalanced class learning problem. The third policy is to choose newly labeled data less than a given maximum number in order to avoid the updates of large amount of data at a time for gradual model updates. Experiments are conducted using Stanford data set and the data set is classified into positive and negative. As a result, the learned model has a high performance than the learned models by using "data with sentiment labels" only and the self-training with a regular model update policy.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.203-212
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• 2017

This research analyzed the factors that have the influences on the intentions to use the consumer dispute settlement system for the small- and medium-sized corporations. The consumer dispute settlement system is a general Internet information portal service which enables the small- and medium-sized corporations and the small businesses receive the support for the accurate damage handling method and the legal service through the Internet in their disputes with the black consumers or the consumers. With the small- and medium-sized corporation users who use the consumer dispute settlement system as the subjects, the research took a lot at what influences the consumer dispute settlement system has on the quality of the information, the quality of the system, the ease-of-use regarding which the environmental factors are perceived, and the ease that was perceived and, finally, what influences it has on the intention of the use. The accuracy, the convenience, and the costs of the consumer dispute settlement system had the positive influences on the ease-of-use that was perceived and the accuracy and the convenience, also had the positive influences on the usefulness that was perceived. Also, it was verified that the ease-of-use of the consumer dispute settlement system that was perceived and the usefulness of use of the consumer dispute settlement system that was perceived finally had the positive influence relationships with the intention of the use. It is highly expected that if, based on the results of this research, the quality of the consumer dispute settlement system is maintained and supplemented to fit the priority order, there will be the maintenance of, and the development toward, a system that is even more improved than the previously existent system.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.12
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• pp.1929-1936
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• 2014

This study investigated purchasing behaviors of processed foods in high school students (male 94 and female 85) in the Yongin region. Frequency of eating processed foods was generally once (36.9%) or twice (32.4%) a day. Frequency according to processed food items was in the following order: confectionary (31.3%)> beverages (17.3%)> breads (12.3%)> instant noodles (11.7%) and milk or dairy products (11.7%)> frozen desserts (10.6%). The places for purchasing were a big mart (30.7%), convenience store (28.5%), and school cafeteria (26.8%). The reasons for purchasing were 'tasty' at 43.6% and 'hungry' at 35.2%. Main factors affecting purchasing were 'taste' at 70.9%, followed by price (16.2%)> quantity (5.6%)> nutrition (4.5%). The most important parts of food and nutrition labels were 'shelf-life' (67.0%) and 'calories' (57.5%). Degrees of confirmation of food and nutrition labeling were 'always' (12.3%), 'rarely' (28.5%), and 'sometimes' (59.2%). The reasons for not reading labels were 'unconcerned' (27.9%), 'too tiny lettering' (28.5%), 'hard to understand' (16.2%), and 'habitually' (15.1%). These results reflect low attention of high school students towards healthy food choices using food and nutrition labeling during purchasing. In conclusion, a specific education program for providing accurate product information as well as leading healthy purchasing behaviors should be required.

• Advances in pediatric surgery
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• v.16 no.1
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• pp.1-10
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• 2010

The members of the Korean Association of Pediatric Surgeons conducted a retrospective study of two hundred and twenty-two cases of intestinal atresia for the period from January 1, 2007 to December 31, 2009. Seventeen hospitals were involved. There were 76 duodenal, 65 jejunal, and 81 ileal atresias (3 colonic). The male to female ratio was 0.85:1 in DA and 1.34:1 in JIA. Ninety-four patients(43.3 %) were premature babies (DA 40.3 %, JA 64.6 %, IA 28.8 %), and 70 babies (32.0 %) had low birth weight (DA 38.7 %, JA 44.4 %, IA 16.0 %). Antenatal diagnosis was made in 153 cases (68.9 %). However, 27 infants (17.6 %) with antenatal diagnosis were transferred to the pediatric surgeon's hospitals after delivery. Maternal polyhydramnios was observed in 81 cases (36.59 %) and most frequent with proximal obstruction. In forty-four cases (19.8 %), only simple abdominal film was taken for diagnostic study. The associated malformations were more frequently observed in DA - 61.8 % in DA and 22.6 % in JIA. Meconium peritonitis, small bowel volvulus and intussusception were more frequently associated with ileal atresia. The overall mortality rate was 3.6 %. (Abbreviations: DA;duodenal atersia, JA;jejunal atresia, JIA;jejunoileal atresia, IA;ileal atrsia).

• Journal of The Korean Association For Science Education
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• v.18 no.4
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• pp.601-615
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• 1998

Establishing and evaluating science education policies and revising and monitoring the effectiveness of science curriculum should be based upon the results of systematic and scientific research studies. Advanced nations have already been administering and developing national level science assessments for these purposes. The science assessments administered in Korea have been reported having many limitations and problems, and not succeeded in providing data for science education policy making and curriculum reform. The major purpose of the study is developing national level science knowledge assessment system in order to identify longitudinal trends of elementary and secondary school students science knowledge achievements. The research team consisted of science education experts and teachers from various school levels, decided the directions and major elements of national level science knowledge assessment with the consultation of educational evaluation experts. Item developing ability of the researchers was improved by seminars? and workshops on national assessment in advanced nations and developing skills of writing science items. Nearly 500 items were developed and revised. Pilot test was administered with 958 students at various school levels. 380 items were selected and tested with 8766 students, and the characteristics were analyzed in terms of item response theory. The target populations for national level science knowledge assessment are 5th-grade of elementary school, 2nd-grade of middle school, 1st and 2nd-grade of high school students. The proper period for the assessment is February every year. Multi-stage clustered sampling method is desirable and rotated forms are recommendable for the test format. Bridge items should be introduced to compare the results of multiple tests, and various grades. Anchor items should also be used for longitudinal interpretations of the results. The items for elementary school require low to medium abilities, for middle school and first grade of high school require medium to high abilities and for 2nd-grade of high school high abilities. The discrimination ability of the items developed is high.

• Tuberculosis and Respiratory Diseases
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• v.47 no.6
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• pp.747-756
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• 1999

Background: Acid-fast stain and cultures for diagnosis of pulmonary tuberculosis are primary and essential method, but have their limitation : low sensitivity and time consuming. The objective of this study is comparison of amplified Mycobacterium tuberculosis direct test(MTD) by the conventional AFB smears and cultures in the detection of Mycobacterium tuberculosis in respiratory specimens. Methods: During the period between November, 1997 and May, 1998 a total of 267 respiratory specimens (sputum 173, bronchial washing 94) from 187 patients suspected pulmonary tuberculosis were subjected to AFB smears, cultures and MID test. MID is based on nucleic acid amplification. We compared the MID with 3% Ogawa culture method. In positive AFB smear and negative MID specimen, positive culture identification between nontuberculous mycobacterium and M.tuberculosis was assesed by using Accuprobe M.tuberculosis complex probe. In negative AFB smear and negative AFB culture, MTD results are assessed by clinical follow-up. Results : 1) Compared with culture in sputum and bronchial fluid specimens, sensitivity and specificity of MTD in positive AFB smear is 79.7% and 20.0%, sensitivity and specificity of MTD in negative AFB smear specimens is 75.0% and 79.7%. 2) Discrepant analysis is assessed by clinical follow-up and other specimen results beyond study. Culture negative but MTD positive specimens were proved to be true positive and gave MTD sensitivity 79.2%, specificity of 84.4%, positive predictive value 80.5% and negative predictive value 83.2%. 3) 14 out of 31 specimens in negative AFB smear, negative AFB culture and positive MTD showed pulmonary tuberculosis diagnosed on clinical follow-up and sensitivity is 45.2%. 4) 2 out of 13 specimens in positive AFB smear, positive AFB culture and negative MID diagnosed as non tuberculous mycobacterium by Accuprobe culture. Conclusion: This study suggested that MID in respiratory specimens is simple and rapid diagnostic method, but considered adjuvant method rather than replace the conventional AFB smear and culture.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.8
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• pp.1164-1171
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• 2011

The purpose of this study was to compare service quality between local and global coffee brand shops and to investigate improvement. Of 350 questionnaires distributed to customers of six brand coffee shops (three local brands, three global brands) located in Daejeon, 330 complete questionnaires (94.3%) were analyzed. The questionnaire included a seven-point multiple-item scale for measuring service quality. The 21 items measuring service quality were grouped into four factors, and the mean scores for the levels of "representativeness", "coffee sensory and beverage features", "employee attitude" and "physical environment" were 5.42, 4.77, 4.74, and 4.13, respectively. The levels of "coffee sensory and beverage features" and "employee attitude" of the high income customers were significantly lower than those of the low income customers. The results showed that the levels of "employee attitude" of local coffee brand shops was significantly higher (p=0.050) than that of global coffee brand shops. Whereas, the levels of "representativeness" of global coffee brand shops was significantly higher (p=0.003) than that of local coffee brand shops. Based on the results, the global coffee brand shops should pay attention to internal marketing and the local coffee brand shops must strive to improve service quality through strategies such as improving brand awareness and developing representative beverages and foods.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.