• Research in Plant Disease
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• v.18 no.4
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• pp.317-323
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• 2012

The study aims to identify the pathogenicity of Phytophthora. capsici isolates in major pepper-producing areas in Korea and the inherit genetic pattern of phytophthora blight resistance by inocula. With five kinds of testing materials including 'Kataguma (Sakata Korea)' peppers, a disease-susceptible material, '#308', a phytophthora blight resistance material, 'CM334', and their $F_1$ and $F_2$, respective isolates of P. capsici obtained from Icheon, Eumseong, Buan, Imsil and Yeongyang regions together with six kinds of peppers' inoculum including PA-159 (KACC No.40482) received from Korean Agricultural Culture Collection were used for inoculation. The disease-susceptible material '#308', the resistant material 'CM334' and the non-segregating generation of $F_1$ represented 4.94-5.00, 1.00-1.07, and 1.01-1.08 phytophthora blight incidence respectively in the group comparison by isolate. This result means that the phytophthora blight resistance was clearly distinguished among testing materials in the group comparison by P. capsici isolate. Moreover, $F_2$ segregating generation showed 1.79-2.31 phytophthora blight incidence which turned out to be identical in the group comparison by the six isolates of P. capsici isolate and with similarity between both the resistant and susceptible materials. Thus, the result proved that using the six isolates of P. capsici tested as inocula was suitable to investigate the phytophthora blight resistance. When it comes to group comparison of $F_2$ segregation generation, however, isolates were divided with PA-159 isolate being the center: a group consisting of isolates from Icheon, Buan, and Imsil and a group consisting of Yeongyang and Eumseong isolates with higher pathogenicity. The expected segregation ratio of the phytophthora blight resistance in $F_2$ generation by isolate was analyzed. PA-159 isolate showed 3:1 or 9:3:3:1, indicating that one to two genes were involved. On the other hand, results also proved that there is an interaction of genes since both Eumseong and Yeongyang isolates showed a segregation ratio of 11:5 while the Icheon isolate represented 12:3:1.

• Korean Journal of Environmental Biology
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• v.29 no.4
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• pp.251-257
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• 2011

Cobalt is a naturally occurring element found in rocks, soil, water and/or is among the harmful pollutants as generated by industrialized. In the environment, cobalt has two oxidation states, cobalt (II) (Co (II)) and cobalt (III) (Co (III)). If coastal water is contaminated by cobalt, it through the food chain can have an impact on marine ecosystems. Therefore, we examined the gametotoxic and embryotoxic effects of Co (II) at various concentrations (10, 100, 500, 1000, 2500 ppb) in the sea urchin $Hemicentrotus$ $pulcherrimus$. Spawning was induced by injecting 1 mL of 0.5 M KCl into coelomic cavity. Males released white or cream-colored sperms and females released yellow or orange-colored eggs. Experiment was begun within 30 min the collection of both gametes. The fertilization and embryo development rates test were performed for 10 min and 64 h after fertilization, respectively. The fertilization rates in the control condition (not including Co (II)) and experimental group were not significantly changed. The embryo development rates in the control condition were greater than 90% and were significantly decreased with concentration dependent manner. The normal embryogenesis rate was significantly inhibited in exposed to cobalt (II) ($EC_{50}$=71.84 ppb, 95% Cl=16.71-203.36 ppb). The NOEC and LOEC of normal embryogenesis rate were <10 ppb and 10 ppb, respectively. These results suggest that the early embryo stages of $H.$ $pulcherrimus$ have toxic effect at greater than 10 ppb of Co (II) concentration.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.2
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• pp.151-161
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• 2014

Sesame lignan, including sesamin and sesamolin has been reported to have various content according to accessions and environmental factors. The objective of this study were to analyze the lignan variation of 143 sesame accessions from core collection in Korea and to test the effects of growing years and locations on lignan and lipid content of Korea sesame elite lines. The results showed that the core sesame germplasm in Korea has broad variation of lignan content from 2.33 to 12.17 mg/g with an average 8.18 mg/g. Among tested sesame accessions, the IT184615 had the highest lignan content of as 12.17 mg/g. So this accession will be a good genetic resource for developing a high lignan sesame variety. The sesamin and sesamolin content for sesame accessions across origin had significant difference. The average lignan content of accessions collected from Russia (10.0 mg/g) and Nepal (9.08 mg/g) were relatively higher than other countries. The sesamin and sesamolin content for sesame accessions across seed coat color had significant difference. The average lignan content of sesame with white, brown and black seed coat color was 8.61, 7.51, and 5.49 mg/g, respectively. The variation of lignan and lipid content was significantly different across elite lines, locations and growing years. Therefore, it is important to find sesame accessions having high lignan content with environmental stability.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• Journal of Korean Public Health Nursing
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• v.12 no.1
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• pp.116-131
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• 1998

This study was undertaken to obtain the menstrual patterns and menstrual discomforts in women university students. For the data collection, self-administered questionnaire survey was made from December 10, 1996 to January 20, 1997 among the 180 women university students in Seoul. The resultant data were processed by SAS program for frequency, proportion, and chi-square test. The results of this study are as follows ; 1) The mean age of the subjects was 20.6 years old. The mean height was 162cm and weight was 52.3Kg. $26.9\%$ of the subjects responded that they had experienced the unbalanced diet, $56\%$ the irregular meal, $39.6\%$intermittent dizziness, and $63.4\%$ the premenstrual syndrome. $53.7\%$ had feeling that skin temperature of their four extremities was 'a little lower than others'. The mean BMI(Body Mass Index) was 19.8, 'normal level' was $41.8\%$. $18.7\%$ responded that their characters were 'introspective ones'. The mean age of menache was 13.8 years old. The subjects responded that the mean number of pads they used per day during menstrual periods was 4.6 sheets. The mean duration of menstruation was 5.4 days, $10.4\%$ responded that their menstrual cycles were 'extremely regular', $44.8\%$ was 'regular', $36.6\%$ was 'a little irregular', and $8.2\%$ was 'extremely irregular'. Out of them who had experienced the dysmenorrhea, $21.3\%$ had family history of dysmenorrhea in connection with their mother and $35.0\%$ in their sisters. The mean of the first time that they experienced dysmenorrhea was 15 years old. $94\%$ of the subjects responded that they had experienced the dysmeorrhea. $47.6\%$ of the subjects responded that they experienced the dysmenorrhea 'monthly' and $52.4\%$ 'intermittently'. $53.0\%$ of them who had experienced dysmenorrhea responded that dysmenorrhea was the severest 'on the first menstrual day' and $22.4\%$ 'on the second day'. $48.8\%$ of them who had experienced dysmenorrhea responded that the most painful region was 'low abdomen'. $40\%$ of them who had experienced dysmenorrhea responded that they used 'analgesics' to soothe dysmenorrhea, $24.8\%$ used nothing, $18.4\%$ lay in their beds or slept, and $12\%$ made their 'low abdomen' warm. $70.3\%$ who had used analgesics because of dysmenorrhea took analgesics 'one or two times per month', $25.7\%$ 'intermittently', and $4.0\%$ more than 3 times per month. The analgesics which they used were 'geworin$(33.8\%)$,' 'penzal$(32.4\%)$', 'tyrenol$(18.9\%)$', and 'aspirin$(4.2\%)$'. $(47.9\%)$ of them who took analgesics because of dysmenorrhea responded that the duration of analgesics effect was '4 to 8 hours'. $15.1\%$ of them who experienced dysmenorrhea responded that they had visited the hospital. 2) The incidence of premenstrual syndrome was no significant difference according to the BMI, unbalanced diet, pattern of meal, skin temperature of four extremites, and characters. 3) The incidence of dysmenorrhea was significant difference according to the BMI, unbalanced diet, pattern of meal, skin temperature of four extremites, and characters. 4) The incidence of analgesics usage was significant difference according to the BMI, subjects with low BMI took more analgesics than those with normal BMI (p<.05). The incidence of analgesics usage was significant difference in accordance with pattern of meal. The women who had a meal regularly took more analgesics than those who had a meal irregularly(p<.05). But the incidence of analgesics usage was no significant difference in accordance with the unbalanced diet, characters, the incidence of dizziness, skin temperature of four extremities, the incidence of premenstrual syndrome.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.253-259
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• 2004

in this study, we developed a Monte Carlo imaging simulation code written by the visual C$\^$++/ programing language for design optimization of a digital X-ray imaging system. As a digital X-ray imaging system, we considered a Gd$_2$O$_2$S(Tb) scintillator and a photosensor array, and included a 2D parallel grid to simulate general test renditions. The interactions between X-ray beams and the system structure, the behavior of lights generated in the scintillator, and their collection in the photosensor array were simulated by using the Monte Carlo method. The scintillator thickness and the photosensor array pitch were assumed to 66$\mu\textrm{m}$ and 48$\mu\textrm{m}$, respertively, and the pixel format was set to 256 x 256. Using the code, we obtained X-ray images under various simulation conditions, and evaluated their image qualities through the calculations of SNR (signal-to-noise ratio), MTF (modulation transfer function), NPS (noise power spectrum), DQE (detective quantum efficiency). The image simulation code developed in this study can be applied effectively for a variety of digital X-ray imaging systems for their design optimization on various design parameters.

• Clinical and Experimental Pediatrics
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• v.48 no.5
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• pp.500-505
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• 2005

Purpose : This study was designed to estimate the prevalence of Mycoplasma pneumoniae infection during an epidemic period by means of examining the antibody conversion rate and to investigate the association of the antibody conversion with age, initial antibody titer, and atopy. Methods : We chose 191 children whose antibody titer to M. pneumoniae was negative, 1 : 40, or 1 : 80 during the first half of 2003. After the second half of 2003 when the M. pneumoniae epidemic occurred, follow-up collection of sera was performed during the first half of 2004. M. pneumoniae antibody titer was measured by Serodia-Myco II particle agglutination test. Results : Of 191 children, antibody conversion was detected in 83 children(43.5 percent). No significant difference was found between the conversion and non-conversion group with respect to age, sex and atopy. Dividing the subjects into four groups by age, results on the antibody conversion rate revealed no significant differences between the groups. Assessed by initial antibody titer, a diminished trend of conversion rate was observed in children with 1 : 80 titer but the difference was not significant. There was no significant difference in the antibody conversion rate between atopic and non-atopic children. Conclusion : Based on the antibody conversion rate in this study, the prevalence of M. pneumoniae infection during an epidemic period was estimated to be 43.5 percent. This high infection rate suggests that during an epidemic, we should bear in mind M. pneumoniae as an important etiologic agent for respiratory infection in children.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Child Health Nursing Research
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• v.8 no.1
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• pp.32-43
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• 2002

The purpose of this study was to provide basic data on elementary school children's lifestyle and to contribute to developing on the health education program in elementary schools. The subjects were 1,412 children in 4 elementary schools in Gangwon-Do and Chonrabuk-Do area. Data collection was done from September to November 2001 by questionnaire and school health documents. The questionnaire corrected for the purpose of this study which had been developed by Bronson School of Nursing(1991), 'Lifestyle Questionnaire for School-age Children'. The questionnaire consists of 3 categories; 'Activities that promote health', 'Injury prevention', 'Feeling'. Cronbach coefficient alpha for the 29 items was .68. The data analyzed to obtain frequency, mean, percentage, t-test, ANOVA and Pearson correlation coefficient by SPSS Win program. The results of this study were as follows. 1. Females(50.2%) of gender, 6th grade(24.2%) of grade, nuclear family(82.0%) of family type, beyond college graduate(54.5%) of father's school career, under high school graduate(58.1%) of mother's school career, first of birth order(47.1%) were majority. Mean of father's age was 41.2 and mother's age was 38.1. 2. The mean of lifestyle was 66.4, feeling was 73.3, activities that promote health was 60.3 and injury prevention was 64.0. The highest degree of activities that promote health was 「I eat fruits」and injury prevention was 「I look both ways when crossing streets」and feeling was 「I enjoy my family」. The lowest degree of activities that promote health was 「I visit the dentist every tear」 and injury prevention was 「I wear a helmet when I go on bike trips」 and feeling was 「I think it is okay to cry」. 3. There were significant differences in lifestyle of gender(t=4.309, p=.000), grade(F=6.299, p=.000), father's age(t=2.534, p=.011), father's education(t=-4.933, p=.000), mother's education(t=-3.360, p=.001), birth order (t=5.363, p=.000). There were significant differences in activities that promote health of gender(t=-2.462, P=.014), grade(F=4.893, p=.000), father's education(t=-4.480, p=.000), birth order(t=4.343, p=.000), in injury prevention of gender(t=-4.452, p=.000), grade(F=8.636, p=.000), father's age(t=3.386, p=.001), mother's age(t=2.059, p=.040), father's education(t=-6.051, p=.000), mother's education(t=-5.173, p=.000), birth order(t=4.417, p=.000) and in feeling of gender (t=-3.285, p=.001), grade(F=7.526, p=.000), mother's age(t=-3.268, p=.001). 4. Activities that promote health was positively correlated with injury prevention(r=.432, p=.000), feeling(r=.210, p=.000), lifestyle (r=.785, p=.000). Injury prevention was positively correlated with feeling(r=.256, p=.000), lifestyle(r=.854, p=.000) also feeling was positively correlated with lifestyle(r=.504, p=.000). These findings suggest the need to develop nursing strategy to promote elementary school children's health. Because helmet use score in injury prevention marked the lowest score, it is necessary to encourage helmet use when planning injury prevention and health promotion.