• Korean Journal of Agricultural Science
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• v.12 no.2
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• pp.206-241
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• 1985

Attempts to search infection period, infection speed in the tissue of neck blast of rice plant, location of inoculum source and effects of several conditions about the leaf sheath of rice plants for neck blast incidence have been made. 1. The most infectious period for neck blast incidence was the booting stage just before heading date, and most of necks have been infected during the booting stage and on heading date. But $Indica{\times}Japonica$ hybrid varieties had shown always high possibility for infection after booting stage. 2. Incubation period for neck blast of rice plants under natural conditions had rather a long period ranging from 10 to 22 days. Under artificial inoculation condition incubation period in the young panicle was shorter than in the old panicle. Panicles that emerged from the sheath of flag leaf had long incubation period, with a low infection rate and they also shown slow infection speed in the tissue. 3. Considering the incubation period of neck blast of rice plant, we assumed that the most effective application periods of chemicals are 5-10 days for immediate effective chemicals and 10-15 days for slow effective chemicals before heading. 4. Infiltration of conidia into the leaf sheath of rice plant carried out by saturation effect with water through the suture of the upper three leaves. The number of conidia observed in the leaf sheath during the booting stage were higher than those in the leaf sheath during other stages. Ligule had protected to infiltrate of conidia into the leaf sheath. 5. When conidia were infiltrated into the leaf sheath, the highest number of attached conidia was observed on the panicle base and panicle axis with hairs and degenerated panicle, which seemed to promote the infection of neck blast. 6. The lowest spore concentration for neck blast incidence was variable with rice varietal groups. $Indica{\times}Japonica$ hybrid varieties were infected easily compared to the Japonica type varieties, especially. The number of spores for neck blast incidence in $Indica{\times}Japonica$ hybrid varieties was less than 100 and disease index was higher also in $Indica{\times}Japonica$ hybrid than in Japonica type varieties. 7. Nitrogen content and silicate content were related with blast incidence in necks of rice plants in the different growing stage changed during growing period. Nitrogen content increased from booting stage to heading date and then decreased gradually as time passes. Silicate content increased from booting stage after heading with time. Change of these content promoted to increase neck blast infection. 8. Conidia moved to rice plant by ascending and desending dispersal and then attached on the rice plant. Conidia transfered horizontally was found very negligible. So we presumed that infection rate of neck blast was very low after emergence of panicle base from the leaf sheath. Also ascending air current by temperature difference between upper and lower side of rice plant seemed to increase the liberation of spores. 9. Conidial number of the blast fungus collected just before and after heading date was closely related with neck blast incidence. Lesions on three leaves from the top were closely related with neck blast incidence, because they had high potential for conidia formation of rice blast fungus and they were direct inoculum sources for neck blast. 10. The condition inside the leaf sheath was very favorable for the incidence of neck blast and the neck blast incidence in the leaf sheath increased as the level of fertilizer applied increased. Therefore, the infection rate of neck blast on the all panicle parts such as panicle base, panicle branches, spikelets, nodes, and internodes inside the leaf sheath didn't show differences due to varietal resistance or fertilizers applied. 11. Except for others among dominant species of fungi in the leaf sheath, only Gerlachia oryzae appeared to promote incidence of neck blast. It was assumed that days for heading of varieties were related with neck blast incidence.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of Preventive Medicine and Public Health
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• v.26 no.1 s.41
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• pp.1-19
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• 1993

Mail questionnaire was administrated to 370 practising physicians and 388 pharmacists in Taegu city selected by systematic sampling to examine utilization states and opinion of pharmacy under medical care insurance programme and the attitude to the functional division between physicians and pharmacists from April to May 1992. Regarding the opinion on the outcome of drug-store under medical insurance, 71.2 percent of practicing physician answered faliure but 13.4 percent of practicing pharmacists answered failure in contrast. Fifty percent of practicing physician asserted introducing functional division between physician and pharmacist while 66.9 percent of practicing pharmacist answered drug-store under medical insurance itself is sucessful programme. Average daily numbers of preparation of medicine was 32.2 case. Percentage of utilization of drug-store under medical issurance to average daily cases of preparing of medicine was 20 percent, percentage of utilization with physician's prescription was 0.7 percent. And 58.7 percent of practicing physician experienced outside the institute prescription. Regarding the opinion on the pros and cons of enforcing functional division between physician and pharmacist, 59.2 percent of practicing physician prefered pros and 17.7 percent cons, but 38 percent of practicing pharmacist prefered pros and 45.5 percent cons. And pharmacist knew better the content of functional division between physician and pharmacist than physician. As a reason for pros of enforcing functional division between physician and pharmacist, practicing physician emphasized to prevent misuse or abuse of medicine but practicing pharmacist emphasized to display physician and pharmacist's professional ability. And as an opinion on implementation style of functional division between physician and pharmacist in pros respondents, practicing physician favored mandatory enforcement (52.3%), while practicing pharmacist favored partial incomplete functional division (81.7%). As the method of prescription if functional division between physician and pharmacist will be enforced, both practicing physician and pharmacist prefered generic name (44.0%, 89%) mostly, but physician prefered brand name (35.3%) secondly. Regarding the reason for not implementing functional division between physician and pharmacist up to date, both physician and pharmacist answered problem of business right between physician and pharmacist, followed by lack of recognition, and interest of people and lack of the govermental willness. Regarding the opinion on prior decision of condition for enforcing functional division between physician and pharmacist, practicing physician and pharmacist named uneven distribution of medical facilities and drug-store between rural and urban, inequality of physician and pharmacist manpower and the problem of manpower demand and supply mostly, and practicing physician pointed out establishing attitude of acceptance on the part of pharmacist and practicing pharmacist favored establishing attitude of acceptance on the part of physician, which was different attitudes between physician and pharmacist. Following conclusion was reached ; 1. Current drug-store under medical insurance program yield insufficient outcome, so we should consider program conversion from drug-store under medical insurance program to functional division between physician and pharmacist. 2. There were problem of business right and conflicts between physician and pharmacist at enforcing functional division between physician and pharmacist, so the goverment should search for formulating plan to resolve the problem and have neutral willness for the protection of the national health.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Sericultural and Entomological Science
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• v.52 no.2
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• pp.110-116
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• 2014

Recently the number of the butterflies, Mellicta ambigua, had been decreasing rapidly, and already disappeared at many habitat. In this studies, we investigated ecological environment of Mellicta ambigua for preparing of primary research data recovering habitat, and studied on bionomical characteristics. Two different habitat, Jindo and Inje, were selected for investigation of ecological environment. We investigated four times during 3-month, from June to August in 2012. In Jindo, we observed more than 100 butterflies and a lot of host plants, Melampyrum roseum var. japonicum. But only 5 butterflies and only a few host plants, Veronicastrum sibiricum were observed in Inje. We could not observe the eggs, the larva and pupa on the host plants at all. For finding of bionomical characteritics, we reared butterflies at natural conditions. Collected 3-female butterflies from Jindo laid 465 eggs on the leaves of 3-host plants, Veronicastrum sibiricum. 120 ~ 186 eggs per each female were laid in the shape of cluster. An egg was globular shape, 0.6 mm diameter and 0.7 mm height. The egg periods were $9.96{\pm}0.4days$ after ovipositioning, and the hatchability was 95.% at natural condition. The larval periods were $4.1{\pm}0.6days$ (1st instar), $2.1{\pm}1.0days$ (2nd), $8.1{\pm}0.7days$ (3rd), $239.2{\pm}10.9days$ (4th), $12.3{\pm}1.3days$ (5th), $17.1{\pm}1.1days$ (6th), $10.5{\pm}1.0days$ (7th) each other. The larva of 4th instar overwintered in the nest that had been made into the leaf of host plant with secreted thread as a group until early March next year. In the early March next year, overwintered larva went around their nest in search of host plants, and went to other host plants, Veronica persica and Plantago asiatica, sometimes. The overwintered larva of Mellicta ambigua could grow up on two other host plants normally. In the following experiment, the butterflies of Mellicta ambigua laid eggs on the leaves of Plantago asiatica, but the 1st instar larva from eggs died all. The headwidth of each developmental larval stage were $0.28{\pm}0.02mm$ (1st), $0.45{\pm}0.02mm$ (2nd), $0.58{\pm}0.02mm$ (3rd), $0.75{\pm}0.03mm$ (4th), $0.89{\pm}0.05mm$ (5th), $1.23{\pm}0.06mm$ (6th), $2.13{\pm}0.11mm$ (7th). The pupal ratio was 92.0%. The pupal period were $9.1{\pm}1.6days$, and the emergence rate was 88.6%. As a result we determined that Mellicta ambigua can rear at natural conditions. But indoor-rearing is considered to be difficult and not useful industrially, because they have long term larval stage and only one life cycle per an year.

• Journal of Preventive Medicine and Public Health
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• v.28 no.4 s.51
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• pp.809-844
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• 1995

The purposes of this study are to define the scope of occupational health management and to classify occupational management by review of related journals from 1945 to 1994 in Korea. The steps of this study were as follows: (1) Search of secondary reference; (2) Collection and review of primary reference; (3) Survey; and (4) Analysis and discussion. The results were as follows ; 1. Most of the respondents majored in occupational health(71.6%), and were working in university (68.3%), males and over the age 40. Seventy percent of the respondents agreed with the idea that classification of occupational health management is necessary, and 10% disagreed. 2. After integration of the idea of respondents, we reclassified the scope of occupational health management. It was defined 3 parts, that is , occupational health system, occupational health service and others (such as assessment, epidemiology, cost-effectiveness analysis and so on). 3. The number of journals on occupational health management was 510. It was sightly increased from 1986 and abruptly increased after 1991. The kinds of journals related to occupational health management were The Korean Journal of Occupational Medicine(18.2%), Several Kinds of Medical Colloge Journal(17.0%), The Korean Journal Occupational Health(15.1%), The Korean Journal of Preventive Medicine(15.1%) and others(34.6%). As for the contents, the number of journals on occupational health management systems was 33(6.5%) and occupational health services 477(93.5%). Of the journals on occupational health management systems, the number of journals on the occupational health resource system was 15(45.5%), occupational finance system 8(24.2%), occupational health management system 6(18.2%), occupational organization 3(9.1%) and occupational health delivery system 1 (3.0%). Of the journals on occupational health services, the number of journals on disease management was 269(57.2%), health management 116(24.7%), working environmental management 85(18.1%). As for the subjects, the number of journals on general workers was 185(71.1%), followed by women worker, white coiler workers and so on. 4. Respondents made occupational health service(such as health management, working environmental management and health education) the first priority of occupational health management. Tied for the second are quality analysis(such as education, training and job contents of occupational health manager) and occupational health systems(such as the recommendation of systems of occupational and general disease and occupational health organization). 5. Thirty seven respondents suggested 48 ideas about the future research of occupational health management. The results were as follows: (1) Study of occupational health service 40.5%; (2) Study of organization system 27.1%; (3) Study of occupational health system (e.g. information network) 8.3%; (4) Study of working condition 6.2%; and (5) Study of occupational health service analysis 4.2%.