• Korea Journal of Hospital Management
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• v.7 no.4
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• pp.24-56
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• 2002

The purpose of this study was to analyze the characteristics of socio-demographic, organizational culture, organizational conflict and organizational commitment, and to examine the interrelation of influential factors in the organizational commitment. The data for this study were collected through a self-administrated survey with a structured questionnaire to 1,027 subjects from several medical doctor staff members, nursing staff members, administration staff members, pharmacist, and technical expert of eleven hospitals. The data were collected by self-reporting questionnaire from July 29 to September 7, 2002. In this analysis frequency test, t-test, ANOVA, multiple regression were used. The main results of this research is as following; 1. According to socio-demographic characteristics the respondents' level of the organizational commitment was higher in a administration staff members than others, for males than females, and for employees aged more than forty, as working for longer time, and as higher level of the working position. 2. According to the organizational culture characteristics the progressive culture, affiliative culture, and task-focused culture among many types of organizational culture were moderately and positively correlated with the level of the organizational commitment while the hierarchical culture was negatively correlated. 3. According to the organizational conflict characteristics as the respondents who got less conflict experience in the organization, their level of the organizational commitment was higher. And, technical conflict experiences were expressed greater than hierarchical conflict experiences. 4. According to the job satisfaction characteristics as his or her satisfaction that is about the promotion, working itself, salary, and fellowship in the organizational was higher, the level of the organizational commitment was higher. The most important factor of the satisfactions was the fellowship among the respondents while the level of job satisfaction for the promotion and salary was average. 5. Overall, according to the result of Multiple Regression as older age and longer working hours, the level of the organizational commitment was higher and as a higher level of the satisfaction for the promotion, working itself, salary, and fellowship in the organization, it caused more effective factors for the organizational commitment. 6. According to the result of Multiple Regression for the doctor staff members in special hospitals rather than general hospitals the hierarchical culture and task focused culture was positively correlated with the satisfaction of working itself while hierarchical conflict factors in the organizational conflict characteristics was negatively correlated with the organizational commitment. For the nursing staff members the affiliative culture and the job satisfaction for the promotion, working itself, salary, and fellowship were positively correlated with the organizational commitment. For the administration staff members as the job satisfaction for the fellowship was positively correlated with the organizational commitment. For medical and pharmacy staff members as more working experience, correlation with the organizational commitment was positive. Besides, as he or she has a high perception of the affiliative culture, it caused statistically more effective factors for the organizational commitment. For the skill and technicians, male worker expressed greater organizational commitment in the organization than female worker. And also older age along with higher education also showed higher organizational commitment. Moreover, the job satisfaction for the fellowship was positively correlated with the organizational commitment. This study identified the major effective factors of the organizational commitment and analyzed the differences among the job category. In that respect, it is significant for the study to be able to provide a reference for managing hospital of industrial accident and organizational development. However, this study has a problem, which is not to identify a valuable model for examining the relationship between organizational factors such as organizational culture, conflict, satisfaction, and commitment. Therefore, further study is needed and strengthened in the field of organizational commitment for hospital for industrial accident.

• Journal of Genetic Medicine
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• v.7 no.1
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• pp.67-77
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• 2010

Purpose: The aims of this study are to evaluate psychological impact and quality of life according to the cancer diagnosis and mutation status in Korean families with BRCA mutations. Materials and Methods: Seventeen affected carriers (AC), 16 unaffected carriers (UC) and 13 healthy non carriers (NC) from 13 BRCA mutation families were included in the study. Outcomes were compared with regard to depression (Beck Depression Inventory), anxiety (State-Trait Anxiety Inventory, STAI), optimism (Reevaluation of the Life Orientation test, LOT-R), knowledge of hereditary ovarian cancer, and quality of life (QoL) (SF-36v2 Health Survey, physical component score [PCS], mental component score [MCS]) among three groups. Result: Level of depression, optimism, and PCS were similar in AC, UC, and NC. Anxiety score was elevated in all three groups. MCS was significantly low in AC than in UC and NC (P=0.009, P=0.017). Knowledge of hereditary breast and ovarian cancer was high in AC than NC (P=0.001). MCS was significantly related to whether patient was affected by cancer (P=0.043) and has occupation (P=0.008) or not in multivariable analysis. Conclusion: From this cross sectional study, psychological adverse effect was not related to the carrier status of BRCA mutation. Elevated anxiety in BRCA family members was observed but, independent to affection and the type of genetic mutation. AC showed low mental QoL. Further effort to understand psychological impact and QoL of genetic testing in BRCA family members is required for follow-up in clinical aspects.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.129-142
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• 2014

Due to the increase of the aged population and population of the disabled today, there is a growing demand for rehabilitation medical instruments. Furthermore, there is a growing demand for evaluation indices for services that should be provided for uses of the rehabilitation medical instruments. In order to evaluate rehabilitation medical instrument designs in this study, the basic index for design evaluations shall be identified to search for assessment plans. Through this, new evaluation indices will be deduced through discussions and analysis of rehabilitation medical experts, biomedical engineers, and designers. The results of this study are summarized as follows. First, the existing design evaluation indices were collected and analyzed to construct 10 rehabilitation medical instrument design evaluation indices and 44 sub-evaluation items. These will be important evaluation standards for designing rehabilitation medical instruments in the future. Second, the design evaluation indices that must be taken into consideration when developing health care rehabilitation medical instruments are the 10 design evaluation indices of usability, cognition, safety, learning, motility, durability, economic feasibility, space, aesthetics and environmental aspects. Third, design evaluation indices of environment, space, cognition, usability, economic feasibility and aesthetics are indices that must be taken into consideration for product design, while learning, safety, motility and durability are factors that must be given special consideration for rehabilitation medical instrument design evaluation indices. Fourth, if existing product design evaluation indices placed importance on environment, space, cognition, usability, economic feasibility and aesthetics of products for design evaluation indices, rehabilitation medical instrument design evaluation indices placed importance on learning, safety, motility and durability on top of usability and economic feasibility, which are the differences between the design evaluation indices of rehabilitation medical instrument and other product designs. The 10 rehabilitation medical device design evaluation indices and 44 sub-evaluation items were carried out in this study. This research is only on the overall rehabilitation medical device design evaluation indices. In future research, the evaluation indices will be applied in the actual rehabilitation medical design device through production of prototypes, while making revisions and supplementations where necessary.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.117-129
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• 2015

As the Internet becomes ubiquitous, a large volume of information is posted on the Internet with exponential growth every day. Accordingly, it is not unusual that investors in stock markets gather and compile firm-specific or market-wide information through online searches. Importantly, it becomes easier for investors to acquire value-relevant information for their investment decision with the help of powerful search tools on the Internet. Our study examines whether or not the Internet helps investors assess a firm's value better by using firm-level data over long periods spanning from January 2004 to December 2013. To this end, we construct weekly-based search volume for information technology (IT) services firms on the Internet. We limit our focus to IT firms since they are often equipped with intangible assets and relatively less recognized to the public which makes them hard-to measure. To obtain the information on those firms, investors are more likely to consult the Internet and use the information to appreciate the firms more accurately and eventually improve their investment decisions. Prior studies have shown that changes in search volumes can reflect the various aspects of the complex human behaviors and forecast near-term values of economic indicators, including automobile sales, unemployment claims, and etc. Moreover, search volume of firm names or stock ticker symbols has been used as a direct proxy of individual investors' attention in financial markets since, different from indirect measures such as turnover and extreme returns, they can reveal and quantify the interest of investors in an objective way. Following this line of research, this study aims to gauge whether the information retrieved from the Internet is value relevant in assessing a firm. We also use search volume for analysis but, distinguished from prior studies, explore its impact on return comovements with market returns. Given that a firm's returns tend to comove with market returns excessively when investors are less informed about the firm, we empirically test the value of information by examining the association between Internet searches and the extent to which a firm's returns comove. Our results show that Internet searches are negatively associated with return comovements as expected. When sample is split by the size of firms, the impact of Internet searches on return comovements is shown to be greater for large firms than small ones. Interestingly, we find a greater impact of Internet searches on return comovements for years from 2009 to 2013 than earlier years possibly due to more aggressive and informative exploit of Internet searches in obtaining financial information. We also complement our analyses by examining the association between return volatility and Internet search volumes. If Internet searches capture investors' attention associated with a change in firm-specific fundamentals such as new product releases, stock splits and so on, a firm's return volatility is likely to increase while search results can provide value-relevant information to investors. Our results suggest that in general, an increase in the volume of Internet searches is not positively associated with return volatility. However, we find a positive association between Internet searches and return volatility when the sample is limited to larger firms. A stronger result from larger firms implies that investors still pay less attention to the information obtained from Internet searches for small firms while the information is value relevant in assessing stock values. However, we do find any systematic differences in the magnitude of Internet searches impact on return volatility by time periods. Taken together, our results shed new light on the value of information searched from the Internet in assessing stock values. Given the informational role of the Internet in stock markets, we believe the results would guide investors to exploit Internet search tools to be better informed, as a result improving their investment decisions.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Preventive Medicine and Public Health
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• v.22 no.3 s.27
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• pp.368-379
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• 1989

The relationship between mercury level of hair and mental retardation was investigated. The 297 subjects with mental retardation were drawn from two schools providing special educational services, one, consisted of children living in an orphan home, another, children with parents. The 117 centre] subjects were drawn from whom had got average or above average academic achivement in a regular elementary school. Hair sample were taken from the nape of the neck and the mercury analysis was carried out on an atomic absorption spectrophotometer(IL 551). There was no relationship between mercury contents and age, and there was a statistically significant difference in mercury contents between male and female in the mentally retarded children living with parents. Children in the retarded group had significantly higher mercury contents compared with control group except the female group with parents. Also, the mercury levels in the retarded group living in an orphan home were significantly higher than that of the retarded group with parents. The concomitant diseases were Down's syndrome, epilepsy, cerebral palsy and autism. There were statistically significant differences in hair mercury levels in the cases of accompanying Down's syndrome and cerebral palsy in male and Down's syndrome and autism in female compared with the control group of the same sex. The most accompanying handicap was speech disturbance(40.7%) and the others were crippled, emotional disturbance etc. The percentages of double handicap were 66.7% among 6 persons exceeding 6ppm of their hair mercury contents. 10.4% among $3{\sim}6$ ppm and 15.7% among the group of 3ppm or less. The findings of this study suggest that the more opportunities of exposure to mercury in mentally retarded children may have occurred, so it can not be excluded the possibility of mercury as a contributing factor to mental retardation. Therefore, the causal relationship between mercury levels and mental retardation should be established through the examinations about their living environments, dietary pattern, eating habit etc.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.1-28
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• 2013

Given that smartphone-based social network services (SNS), such as KakaoStory is now being widely used as a way for people to connect and communicate with each other, this study examines key factors leading to the continued use of SNS. People have been using PC-based SNS, such as Cyworld, for years are now using smartphone-based SNS, such as KakaoStory. KakaoStory developed by KakaoTalk has rapidly grown up as the largest smartphone-based SNS in Korea as smartphone penetration increases. It is more difficult for firms to maintain their current users over time in that alternative SNSs satisfying people's new needs are constantly emerging and evolving. In this sense, one of the most challenging issues for SNS firms is how to retain their current users in the long run. However, there are few empirical studies on this issue. Applying the IS continuance model proposed by Bhattacherjee [2001], this study explores key determinants of users' smartphone-based SNS continuance intention. The model suggests that perceived usefulness and user satisfaction are the key determinants of IS continuance intention. However, the model includes only the utilitarian value that users can obtain through the use of smartphone-based SNS, by considering perceived usefulness. Therefore, the study attempts to extend the IS continuance model by considering hedonic and social values simultaneously. More specifically, we consider subjective norms as social value that are proposed by the theory of reasoned action and the theory of planned behavior. We also consider perceived enjoyment as hedonic value that is emphasized as a key factor influencing users' behavior intention and actual behavior, particularly in the context of hedonic IS use. By considering the three values in our model simultaneously, we could offer a deeper understanding of smartphone-based SNS continuance. That is, this study could offer an explanation of how each value is associated with user satisfaction and SNS continuance intention. The customer value-satisfaction-loyalty model can strengthen the assertion that smartphone-based SNS continuance intention is determined by various different types of customer values, such as utilitarian, hedonic, and social ones. Moreover, the model provides a theoretical basis for the assertion that customer values lead to increased loyalty via customer satisfaction. In this regard, we theorize that SNS continuance intention is influenced by users' various values, namely perceived usefulness, perceived enjoyment, and subjective norms, via user satisfaction. To test the proposed research model and hypotheses, we conducted a partial least squares analysis using a total of 253 data collected on the users of smartphone-based SNS (i.e., KakaoStory). The key findings are as follows: First, it has been found that SNS continuance intention considerably depends on user satisfaction. Second, user satisfaction is determined by confirmation, perceived usefulness, and perceived enjoyment. Third, concerning the effects of the three values on SNS continuance intention, only perceived enjoyment regarded as hedonic value was statistically significant. That is, perceived usefulness considered as utilitarian value and subjective norms considered as social value had no effect on SNS continuance intention. Finally, our results indicate that confirmation increases perceived usefulness, perceived enjoyment, and user satisfaction. The results reconfirm the effectiveness of IS continuance model in predicting smartphone-based SNS continuance intention. Moreover, the results demonstrate that perceived enjoyment reflecting hedonic value is the most important predictor of SNS continuance intention. Therefore, it is imperative for firms to meet SNS users' hedonic value to retain them in the long run. Meanwhile, we could not find any empirical evidence to support the assertion that subjective norms are associated with user satisfaction and SNS continuance intention. The results lead us to conclude that when users have enough direct experience in SNS use, subjective norms have no effect on SNS continuance intention. Discussions and implications of the results are provided.