• Korean Journal of Psychosomatic Medicine
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• v.17 no.2
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• pp.52-61
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• 2009

Objectives : The aim of this study was to assess health-related quality of life and evaluate the risk factors affecting severity of menopausal symptoms in early and late postmenopausal women based on the stages of reproductive aging workshop(STRAW) paradigm. Methods : This cross-sectional study examined 497 Korean postmenopausal women aged 41-59 years in Seoul and Gyeonggi province. We divided subjects into early postmenopause group and late postmenopause group. Menopause Rating Scale(MRS) was used to measure the quality of life. MRS scores, sociodemographic variables, smoking, alcohol use, age at menopause, and risk factors such as attitude to menopause, depression, history of premenstrual dysphoric disorder were compared between early and late postmenopause groups. Multiple regression analysis was performed in each group to assess the independent contribution of several variables. Results : Early postmenopause group showed significantly higher MRS scores, more negative attitude toward menopause, higher scores of depressive symptoms than late postmenopause group. Moderate to very severe hot flush group showed significantly, more negative attitude toward menopause, higher score of depressive symptoms, and higher MRS scores than none to mild hot flush groups. Depressive symptoms and attitude toward menopause contributed to the severity of menopausal symptom in both early and late postmenopause groups. Chronological age, age at menopause, history of PMDD contributed to severity of menopausal symptoms in early postmenopause group while marital status and occupation contributed in late postmenopause group. Conclusion : Health-related quality of life in postmenopause women was significantly lower in early postmenopause group than the late. Attitude toward menopause and depressive symptoms contributed significantly to quality of life in both early and late postmenopause groups but other variables contributed differently in each group. Further studies on clinical samples of postmenopausal women in order to confirm quality of life and its risk factor are needed to be done.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.293-299
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• 2007

Intelligent pipeline inspection gauges (PIGs) are inspection vehicles that move along within a (gas or oil) pipeline and acquire signals (also called sensor data) from their surrounding rings of sensors. By analyzing the signals captured in intelligent PIGs, we can detect pipeline defects, such as holes and curvatures and other potential causes of gas explosions. There are two major data access patterns apparent when an analyzer accesses the pipeline signal data. The first is a sequential pattern where an analyst reads the sensor data one time only in a sequential fashion. The second is the repetitive pattern where an analyzer repeatedly reads the signal data within a fixed range; this is the dominant pattern in analyzing the signal data. The existing PIG software reads signal data directly from the server at every user#s request, requiring network transfer and disk access cost. It works well only for the sequential pattern, but not for the more dominant repetitive pattern. This problem becomes very serious in a client/server environment where several analysts analyze the signal data concurrently. To tackle this problem, we devise a fast in-memory cache manager, called T-Cache, by considering pipeline sensor data as multiple time-series data and by efficiently caching the time-series data at T-Cache. To the best of the authors# knowledge, this is the first research on caching pipeline signals on the client-side. We propose a new concept of the signal cache line as a caching unit, which is a set of time-series signal data for a fixed distance. We also provide the various data structures including smart cursors and algorithms used in T-Cache. Experimental results show that T-Cache performs much better for the repetitive pattern in terms of disk I/Os and the elapsed time. Even with the sequential pattern, T-Cache shows almost the same performance as a system that does not use any caching, indicating the caching overhead in T-Cache is negligible.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.344-350
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• 2003

In this paper, we propose a novel sharing method ordering the events occurring between users collaborated with the common telecomputing environment. We realize the sharing method with multimedia data to improve the coworking effect using teleprocessing network. This sharing method advances the efficiency of communicating projects such as remote education, tele-conference, and co-authoring of multimedia contents by offering conveniences of presentation, group authoring, common management, and transient event productions of the users. As for the conventional sharing white board system, all the multimedia contents segments should be authored by the exclusive program, and we cannot use any existing contents or program. Moreover we suffer from the problem that ordering error occurs in the teleprocessing operation because we do not have any line-up technology for the input ordering of commands. Therefore we develop a method of retrieving input and output events from the windows system and the message hooking technology which transmits between programs in the operating system In addition, we realize the allocation technology of the processing results for all sharing users of the distributed computing environment without any error. Our sharing technology should contribute to improve the face-to-face coworking efficiency for multimedia contents authoring, common blackboard system in the area of remote educations, and presentation display in visual conference.

• Journal of Distribution Science
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• v.9 no.2
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• pp.131-140
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• 2011

On 1 July 2000, as the over-65 year-old population numbered 3,371,000 and accounted for over 7.1% of Korea's total population, an aging society was revealed. The over-65 percentage climbed to 11.0% by late 2010. A truly aged society is expected soon, by 2019. This aging society requires marketing research concerning the consumer behaviour and well-being of the elderly, because the 'silver generation' is emerging as a large part of the consumer market. The purpose of this study is to empirically analyse one effect among several satisfaction factors in the consuming cycle of various health functional products on consumer's well-being and the effect of product knowledge on the relationship between product satisfaction and well-being. To achieve this purpose, we established a research model after reviewing previous studies on product satisfaction, product knowledge, and consumer's well-being. The following hypotheses were developed from the research model. Hypothesis 1: When elderly consumers' satisfaction with health functional products increases, their well-being will increase. Hypothesis 2: The effect of their satisfaction with health functional products on their well-being will be strengthened according to the level of their knowledge of the products. Those hypotheses were tested by multiple and moderated regressions to the empirical data through a questionnaire survey. As a result, Hypothesis 1 was totally adopted, and Hypothesis 2 was only partially adopted. The study has many practical implications for well-being marketing. First, in order to heighten the elderly consumer's well-being, the level of his or her satisfaction with the health functional products has to be raised in every stage: during the acquisition, preparation, use, maintenance, and disposition of the consumption cycle. Moreover, promoting positive emotional experiences while diminishing negative ones requires effort because a consumer's well-being is made up of various needs. Second, the marketing of health functional products should be invigorated in order to raise the level of elderly consumers' knowledge of them. In other words, it is important to give them an expertise in the health functional products through different channels. A statistical analysis showed, however, that their knowledge has a decisive effect on only two satisfaction stages, preparation and maintenance. Nevertheless, this merely confirmed the intuitive assumption that the knowledge of health functional products is most relevant to their preparation and maintenance. In conclusion, this study is timely because few empirical studies exist on the relationships between silver consumer behaviour and well-being marketing. It contributes to our understanding of this subject by revealing the causality between the silver consumer's satisfaction and his or her well-being in the consumption cycle and by discovering the moderating influence of knowledge in that process.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.1-22
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• 2007

Customer satisfaction is important in an increasingly competitive and global marketplace. This implies that customer service is a critical factor for many organizations. In service encounter context, customer satisfaction is affected by employees' attitudes and behaviors. Accordingly, service firms have been focusing on selecting high quality of service employees, which resulted the ability to identify and select quality service- or customer- oriented employees to become critical for an organization's success. It was suggested that customer service orientation links to performance and subsequent organizational revenue. Moreover, it was found that service encounter failures were among the major reasons for customers' service switch. Therefore, the selection of customer service oriented employees is a key factor in establishing customer service - a potential source of sustained competitive advantage. However, the measurement of employee service orientation is more confusing than that of definitive answers. The difficulty of measuring service orientation is attributed to the use of broad versus narrow measures of personality. Advocates for the broad perspective prefer using basic personality constructs, such as the Big Five personality traits. On the contrary, the latter prefer a construct-oriented approach of personality research that provides a better measure of job performance because it requires the specification of the relationship of the personality traits with multiple dimensions of job performance. The customer service orientation was defined as "a set of basic individual predispositions and an inclination to provide service, to be courteous and to be helpful in dealing with customers and associates." Similarly, it is a fact that the Big five personality traits are predictors of customer orientation, and employee's self- and supervisor performance. They propose that basic personality traits may be too far removed from focal service behaviors to be able to predict specific service behaviors (customer orientation) and service worker performance. Also, customer orientation is defined as "an employee's tendency or predisposition to meet customer needs in an on-the-job context." This means that people who have job-relevant personality traits such as concern, empathy, and conscientiousness will be more adept at customer service than people who do not possess these traits. However, little attention has been given to the exploration of the service orientation of customer-contact employees who play a key role in creating satisfactory service encounters in the hospitality industry except for Kim, McCahon, & Miller (2003)'s study, especially in family restaurants context. Thus, the purposes of this study are to examine and validate the customer service orientation of customer-contact employees using the instrument developed by Donavan (1999) in Korean family restaurants, because the scale was developed to measure the personality traits related job behaviors. And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). For these purposes the author developed several hypotheses as follows: H1: Employee's service orientation is associated with service performance. H2: Employee's service orientation is positively associated with job satisfaction. H3: Employee's service orientation is positively associated with organizational commitment. H4: Service performance is positively associated with job satisfaction. H5: Service performance is positively associated with organizational commitment. H6: Job satisfaction is negatively associated with organizational commitment. The data were collected from 278 employees in 5 deluxe hotels located in Pusan, Korea. The researcher contacted the manager of the restaurants, and managers consented to administer surveys to their employees. The survey was executed during one month period in the October of 2007. The data were analyzed with structural equation modeling with LISREL 8.7 W. The result of the overall model analysis appeared as follows: $X^2$=122.638 (p = 0.00), df=59, GFI=.936, AGFI=.901, NFI=.948, CFI=.971, RMSEA=.0625. Since the result of the overall model analysis demonstrated a good fit, we could further analyze our data. The findings can be summarized as follows: First, the greater the employee service orientation, the greater the service performance. Second, the greater the employee service orientation, the greater the job satisfaction. Third, the greater the employee service orientation, the greater the organizational commitment. Fourth, the greater the service performance, the greater the job satisfaction. Fifth, the greater the service performance, the greater the organizational commitment. Finally, the greater the job satisfaction, the greater the organizational commitment. Seventh, the greater the customer satisfaction, the greater the customer loyalty.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• Journal of Chest Surgery
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• v.32 no.6
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• pp.536-542
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• 1999

Background: The purpose of this study is to improve the quality of the diagnostic procedures in the preoperative evaluation so as to reduce the unnecessary thoracotomy and to ensure resectability in non-small cell lung cancer. Material and Method: Of 616 patients who underwent thoracotomy for primary lung cancer from January 1990 to December 1996, 59 patients(9.6%) turned out to have inoperable lesions after the thoracotomy. We reprospectively reviewed the bronchoscopic findings, methods of tissue diagnosis, CT scans, pulmonary function test and lung perfusion scan, reasons for nonresectability, and adjuvant therapy, and then followed up on the survival rate after exploratory thoracotomy. Result: The cell types were squamous cell carcinoma in 38, adenocarcinoma in 15, large cell carcinoma in 3 and others in 3. Primary loci were RUL in 20, RML in 6, RLL in 8, LUL in 13, LLL in 4 and others in 8. The reasons for non-resectability were various; direct tumor invaison to mediastinal structures(n=41), seeding on pleural cavity(n=8), poor pulmonary function(n=2), invasions to extranodal mediastinal lymph node(n=2), technical non- resectability due to extensive chest wall invasion (n=3), small cell carcinoma (n=1), malignant lymphoma(n=1), and multiple rib metastases(n=1). In the follow-up of 58 patients, 1-year survival rate was 55.2% and 2-year survival rate was 17.2% and the mean survival time was 14 months. When compared according to cell types or postoperative adjuvant therapeutic modalities, no significant difference in the survival rates were found. The squamous cell carcinoma was frequently accompanied by local extension to contiguous structures and was the main cause of non-resectability. In adenocarcinoma, pleural seeding with malignant effusion was frequently encountered, and was the major reason for non-resectability. Conclusion: These data revealed that if appropriate preoperative diagnostic tools had been available, many unnecessary thoracotomies could have been avoided. Both the use of thoracoscopy in selected cases of adenocarcinoma and the more aggressive surgical approach to the locally advanced tumor could reduce the incidence of unnecessary thoracotomies for non-small cell lung cancers.

• Journal of Korean Home Economics Education Association
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• v.17 no.2
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• pp.197-219
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• 2005

This study attempted, in accordance with the National Educational Curriculum, to develop achievement assessment standards for a course within the field of home economics which has been widely adopted by Korean vocational high schools, namely, the food and nutrition subject. Focus was also placed on strengthening the management of the curriculum for this food and nutrition course, as well as on establishing proper assessment standards by developing model assessment tools which can be used to assess the subject. The results of this study can be summarized as follows : First, based on an analysis of the related literature and materials. the desired notion of the achievement and assessment standards was established, and their significance ascertained the achievement and assessment standards for the food and nutrition course were set and the type of model assessment tool which should be developed, as well as the method in which it should be applied. was established Second. by analyzing the curriculums and the contents of the textbooks used in the food and nutrition subject, the researcher was able to compile the 70 factors which could to be used to develop the achievement and assessments standards, and then classify these into 6 main categories and 32 sub-categories. Based on the characteristics of these factors and learners' academic performance levels the number of factors was expanded to 89 in order to establish the achievement standards. In turn, these achievement standards were used, in accordance with the learners' achievement and teaming activity levels, to develop three different levels of assessment standards. namely, upper, middle, and lower ones. Third. a model assessment tool was developed which could be used by individual school units as a reference in terms of achievement and assessment standards, and that could be modified to meet each school's circumstances. In order to create the model assessment tool a 100-question questionnaire was formulated that contained various types of questions, such as essay, report, theoretical and practical, portfolio, as well as multiple choice-type questions. Lastly, the researcher introduced measures to effectively use the achievement and assessment standards developed for the food and nutrition course, as well as the model assessment tool in school units.

• Korean Journal of Occupational Health Nursing
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• v.11 no.1
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• pp.13-30
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• 2002

Industrial shift workers feels suffer mental stresses which are caused by unfamiliar day sleep, noisy environment, sleeping disorder by bright light, unusual contacts with family, difficulty in meeting with friends or having formal social meetings and other social limitations such as the use of transportation. Such stresses influence health of the workers negatively. Thus the health promotion policy for shift workers should be made considering the workers' ways of living and shift work specially. This study attempted to provide basic information for development of the health promotion program for industrial shift workers by examining predictive factors influencing health promotion behaviors of those workers. In designing the study, three power generation plants located in Pusan and south Kyungsang province were randomly selected and therefrom 280 workers at central control, boiler and turbine rooms and environmental chemistry parts whose processes require shift works were sampled as subjects of the study. Data were collected two times from September 17 to October 8, 1999 using questionnaires with helps of safety and health managers of the plants. The questionnaires were distributed through mails or direct visits. Means for the study included the measurement tool of health promotion behavior provided by Park(1995), the tool of self-efficacy measurement by Suh(1995), the tool of internal locus of control measurement by Oh(1987), the measurement tool of perceived health state by Park(1995) and the tool of social support measurement by Paek(1995). The collected data were analyzed using SPSS program. Controlling factors of the subjects were evaluated in terms of frequency and percentage ratio Perceived factors and health promotion behaviors of the subjects were done so in terms of mean and standard deviation, and average mark and standard deviation, respectively. Relations between controlling and perceived factors were analyzed using t-test and ANOVA and those between perceived factors and the performance of health promotion behaviors, using Pearson's Correlation Coefficient. The performance of health promotion behaviors was tested using t-test, ANOVA and post multi-comparison (Scheffe test). Predictive factors of health promotion behavior were examined through the Stepwise Multiple Regression Analysis. Results of the study are summarized as follows. 1. The performance of health promotion behaviors by the subjects was evaluated as having the value of mean, $161.27{\pm}26.73$ points(min.:60, max.:240) and average mark, $2.68{\pm}0.44$ points(min.:1, max.:4). When the performance was analyzed according to related aspects, it showed the highest level in harmonious relation with average mark, $3.15{\pm}.56$ points, followed by hygienic life($3.03{\pm}.55$), self-realization ($2.84{\pm}.55$), emotional support($2.73{\pm}.61$), regular meals($2.71{\pm}.76$), self-control($2.62{\pm}.63$), health diet($2.62{\pm}.56$), rest and sleep($2.60{\pm}.59$), exercise and activity($2.53{\pm}.57$), diet control($2.52{\pm}.56$) and special health management($2.06{\pm}.65$). 2. In relations between perceived factors of the subjects(self-efficacy, internal locus of control, perceived health state) and the performance of health promotion behaviors, the performance was found having significantly pure relations with self-efficacy (r=.524, P=.000), internal locus of control (r=.225, P=.000) and perceived health state(r=.244, P=.000). The higher each evaluated point of the three factors was, the higher the performance was in level. 3. When relations between the controlling factors(demography-based social, health-related, job-related and human relations characteristics) and the performance of health promotion behaviors were analyzed, the performance showed significant differences according to marital status (t=2.09, P= .03), religion(F=3.93, P= .00) and participation in religious activities (F=8.10, P= .00) out of demography-based characteristics, medical examination results (F=7.20, P= .00) and methods of the collection of health knowledge and information(F=3.41, P= .01) and methods of desired health education(F=3.41, P= .01) out of health-related characteristics, detrimental factors perception(F=4.49, P= .01) and job satisfaction(F=8.41, P= .00) out of job-related characteristics and social support(F=14.69, P= .00) out of human relations characteristics. 4. The factor which is a variable predicting best the performance of health promotion behaviors by the subjects was the self-efficacy accounting for 27.4% of the prediction, followed by participation in religious activities, social support, job satisfaction, received health state and internal locus of control in order all of which totally account for 41.0%. In conclusion, the predictive factor which most influence the performance of health promotion behaviors by shift workers was self-efficacy. To promote the sense, therefore, it is necessary to develop the nursing intervention program considering predictive factors as variables identified in this study. Further industrial nurses should play their roles actively to help shift workers increase their capability of self-management of health.