• 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 Astronomy and Space Sciences
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• v.22 no.1
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• pp.1-12
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• 2005

The Korean VLBI Network (KVN) will open a new field of research in astronomy, geodesy and earth science using the newest three Elm radio telescopes. This will expand our ability to look at the Universe in the millimeter regime. Imaging capability of radio interferometry is highly dependent upon the antenna configuration, source size, declination and the shape of target. In this paper, imaging simulations are carried out with the KVN system configuration. Five test images were used which were a point source, multi-point sources, a uniform sphere with two different sizes compared to the synthesis beam of the KVN and a Very Large Array (VLA) image of Cygnus A. The declination for the full time simulation was set as +60 degrees and the observation time range was -6 to +6 hours around transit. Simulations have been done at 22GHz, one of the KVN observation frequency. All these simulations and data reductions have been run with the Astronomical Image Processing System (AIPS) software package. As the KVN array has a resolution of about 6 mas (milli arcsecond) at 220Hz, in case of model source being approximately the beam size or smaller, the ratio of peak intensity over RMS shows about 10000:1 and 5000:1. The other case in which model source is larger than the beam size, this ratio shows very low range of about 115:1 and 34:1. This is due to the lack of short baselines and the small number of antenna. We compare the coordinates of the model images with those of the cleaned images. The result shows mostly perfect correspondence except in the case of the 12mas uniform sphere. Therefore, the main astronomical targets for the KVN will be the compact sources and the KVN will have an excellent performance in the astrometry for these sources.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1690-1698
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• 2012

As alcohol use is one of the most important risk factors for injuries, this study was intended to clarify and evaluate any relationship between drinking patterns and the incidence rates/specific characteristics of injuries in adult populations, using a widely accepted tool, the Alcohol Use Disorders Identification Test (chronic alcohol drinking behaviors measurement, hereinafter the AUDIT) developed by the World Health Organization to help to assess the behaviors in a more accurate and reliable manner. This study used the data collected from the 2009 Korea National Health and Nutrition Examination Survey (KNHANES), in which 7,511 of 7,893 adult participants aged ${\geq}19$ years answered the questions about injuries, and excluding 104 non-respondents, 6,258 of participants in the questionnaire survey of drinking patterns were finally analyzed. The incidence rates and specific characteristics of injuries as classified by the AUDIT categories (i.e., body regions, types and mechanisms) were assessed and estimated in terms of their relative risk using t-test, ANOVA, and logistic regression. SPSS 19.0 statistical package software was employed for statistical analyses. These analyses indicate that the incidence rates of overall injuries were significantly higher in male respondents than in female respondents. The risks of alcohol use related injuries were 8.3 times higher in male respondents than in female ones. Regarding educational background, high school graduates showed the highest rates in the AUDIT with significant difference from the other groups. The married group and the group of respondents having monthly income estimated at KRW 2.01 to 3 million also showed the highest rates in the AUDIT compared to the other groups, indicating statistically significant difference. Significantly increased in problematic drinkers and those with alcohol dependence, the incidence rate of injuries body regions was 0.0371 in the head/neck, and with respect to the AUDIT and the mechanisms of external causes of injuries, transport accidents ranked first, followed by slippage, others, crash and fall. In regard to the classified types of injuries, it was statistically significant in others (e.g., laceration, contusion, addiction, or penetrating wound). In conclusion, the mechanisms of external causes of injuries as well as injuries attributed to alcohol use are very important, and a strategy is required to reduce such the injuries in the manner of decreasing the frequency of drinking after motivation by professional counsellors.

• Journal of radiological science and technology
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• v.26 no.2
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• pp.57-61
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• 2003

The purpose of this study is to compare both 1.5T and 4.7T in Praietal White matter material Phantom using the same methodology at both field strengths. Data at both field strengths are compared in terms of $T_2$ relaxation times, line widths and SNRs MR imaging and $^1H$ MR spectroscopy were performed on GE 1.5T SIGNA system and Broker Biospec 4.7T/30 MRI/MRS system. After phantom axial scan $^1H$ MRS was obtained from T2 weighted image by 3-dimensional localization technique(PRESS : Point RE solved spectroscopy Sequence) this phantom is composed of an aqueous solution 36.7 mmol/L of NAA, 25.0 mmol/L of Cr, 6.3 mmol/L of choline chloride, 30.0 mmol/L or Glu, and 22.5 mmol/L of MI(adjusted to a pH of 7,15 in a phosphate buffet). Data processed using software developed inhouse. At 1.5T, T2 relaxation times for Cho, Cr, and NAA were $0.41{\pm}0.07,\;0.26{\pm}0.04,\;0.46{\pm}0.07$ while at 4.7T they were $0.17{\pm}0.03,\;0.14{\pm}0.05,\;0.20{\pm}0.03$ respectively. At 1.5T, line widths for water, Cho, Cr and NAA were $2.9{\pm}0.7,\;1.6{\pm}0.7,\;1.7{\pm}0.8,\;2.2{\pm}0.02Hz$ while at 4.7T they were $5.2{\pm}1.1,\;4.6{\pm}1.9,\;4.01{\pm}1.8,\;4.8{\pm}1.9Hz$ respectively. It can be seen that $T_2$ relaxation times were significantly shorter at 4.7 compared to 1.5T and that the line widths were also broader. The average SNRs for NAA for subjects at short and long TEs were $23.5{\pm}11.3$ at TE=20 msec ; $15.4{\pm}7.7$ at TE=272 msec at 1.5T and $40{\pm}8.3$ and $17{\pm}3.5$ respectively at 4.7T higher field strength is superior because of improved sensitivity and chemical shift dispersion. However these improvements are partially offset by increased line widths and decrease $T_2$ relaxation times, which act to reduce both sensitivity and resolution. In our experiments with the equipment available to us, 4.7T proton spectra at short TEs exhibit moderately improved sensitivity compared to 1.5T.

• Journal of Gifted/Talented Education
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• v.14 no.4
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• pp.125-149
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• 2004

The purpose of this study is to provide basic information on the current status of elementary school teachers' perception of gifted education. For this purpose, this study wi1l analyze elementary school teachers' perception of the gifted education (i.e., general perception of gifted education, characteristics of gifted children, identification of gifted children, programs for gifted education, and teachers of gifted education). A questionnaire survey was used for the purpose and research questions of this study. The questionnaire used in this study was constructed by taking into account the results of surveys conducted in previous studies and the literature on gifted education. Before conducting the research, a preliminary inquiry was made to identify problems that may occur while the subjects were participating in the survey, as well as to determine the appropriateness of the questionnaire and the amount of time needed. The preliminary inquiry was conducted with ten randomly selected elementary school teachers who did not participate as subjects in the actual research. The results were later used as initial data for the actual research. The subjects of this study were teachers who were teaching in8 elementary schools under each office of education in Seoul. This process was conducted for 180 elementary school teachers from April to May 2004. The results were analyzed using SPSS (Statistical Package for Social Science) Ver. 10.1, a software program for statistical research. After the data were analyzed, the following conclusions were arrived at: 1. The result of the genera1 perception of gifted education by elementary school teachers were positive and reasonably high. The level of their perception of detailed information or knowledge, however, was relatively low. 2. As for their perceptions of the emotional characteristics of gifted children, t11e results showed a low level of understanding of the characteristics of gifted children. 3. As for their perceptions of identification of gifted children, the results showed a high level of understanding of the appropriate time to provide special education to gifted children and of the methods to identify such. On the other hand, their understanding of the identification of gifted children in an actual class was poor. 4. The respondents' level of perceptions of programs for gifted education was very low since many subjects did not have any experiences with such programs. 5. The results showed a very positive response to receiving training on gifted education, though they were very reluctant to be assigned as teachers of gifted education because of the excessive work that is associated with such and their lack of capability in handling gifted children.

• Journal of the korean academy of Pediatric Dentistry
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• v.31 no.2
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• pp.228-235
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• 2004

The development and proliferation of the mandibular condyle can be altered by changes in the biomechanical environment of the temporomandibular joint. The biomechanical loads were varied by feeding diets of different consistencies. The purpose of the present study was to determine whether changes of masticatory forces by feeding a soft diet can alter the trabecular bone morphology of the growing mouse mandibular condyle, by means of micro-computed tomography. Thirty-six female, 21 days old, C57BL/6 mice were randomly divided into two groups. Mice in the hard-diet control group were fed standard hard rodent pellets for 8 weeks. The soft-diet group mice were given soft ground diets for 8 weeks and their lower incisors were shortened by cutting with a wire cutter twice a week to reduce incision. After 8 weeks all animals were killed after they were weighed. Following sacrifice, the right mandibular condyle was removed. High spatial resolution tomography was done with a Skyscan Micro-CT 1072. Cross-sections were scanned and three-dimensional images were reconstructed from 2D sections. Morphometric and nonmetric parameters such as bone volume(BV), bone surface(BS), total volume(TV), bone volume fraction(BV/TV), surface to volume ratio(BS/BV), trabecular thickness(Tb. Th.), structure model index(SMI) and degree of anisotropy(DA) were directly determined by means of the software package at the micro-CT system. From directly determined indices the trabecular number(Tb. N.) and trabecular separation(Tb. Sp.) were calculated according to parallel plate model of Parfitt et al.. After micro-tomographic imaging, the samples were decalcified, dehydrated, embedded and sectioned for histological observation. The results were as follow: 1. The bone volume fraction, trabecular thickness(Tb. Th.) and trabecular number(Tb. N.) were significantly decreased in the soft-diet group compared with that of the control group (p<0.05). 2. The trabecular separation(Tb. Sp.) was significantly increased in the soft-diet group(p<0.05). 3. There was no significant differences in the surface to volume ratio(BS/BV), structure model index(SMI) and degree of anisotropy(DA) between the soft-diet group and hard-diet control group (p>0.05). 4. Histological sections showed that the thickness of the proliferative layer and total cartilage thickness were significantly reduced in the soft-diet group.

• Management & Information Systems Review
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• v.33 no.1
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• pp.191-217
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• 2014

The Purpose of this study is to find the effect factors of R&D investment in SMEs which plays an important role in the national economy, and the differences of the effect factors by the type of SMEs. The subject of this study is about 3,400 SMEs mentioned in "The survey of technical statistics on SMEs in 2007" by Korea Federation of Small and Medium Business. The effect factors are related with the size of business, the infrastructure of R&D and the activities of R&D which have been studied by many researchers. The methods of analysis are regression analysis, moderating effect analysis and the software package used is SPSS 12.0. The results of the study are as fallow. First, it was found that unlike in previous studies which show the effect of the elements of business's size, research infrastructure, research activities on R&D investment, one element alone can't be considered for meaningful result but the various elements have effect on R&D investment at the same time. In other words, the number of employees and the sales as the elements of business's size, the ratio of researchers, the technical ability, the ratio of equipment possession and the intellectual properties as the elements of R&D infrastructure, the activity of ideas and joint research as the elements of R&D activities have positive(+) effect, whereas the participation of CEO in the activity of R&D as the elements of R&D activities activity has negative(-) one. The number of employees, the ratio of researchers, and the sales had relatively high influence whereas equipment possession, technical ability, intellectual properties, the participation of CEO in the research, the activity of idea, joint research had relatively low influence. Next, it was also found that there are differences of the effect factors over the types of SMEs. SMEs were classified into 19 types by eight criteria such as start-ups and existing business by business age; small business and medium business by size; manufacturing business and service business by product type;independent business and subcontractor business by dealing type; businesses in the entering, growing, maturing and restructuring stage by growth stage; businesses with low, medium and high technology by technological level; pioneering business and non-pioneering business by industrial type; and businesses with state-of-the-art technology and non-advanced business by the level of business activities. The meaning of this study lies in the fact that it found the various effect factors should be considered at the same time when conducting study on SMEs' R&D investment, and the differences by the type should be acknowledged. This study surpassed the limitations of the previous studies which focused on a couple of factors and types. This study result can also be considered for other studies on achievement, organization, marketing and others. Moreover, it shows that a differential policy by business type is needed when formulating SME policy.

• Korean Journal of Poultry Science
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• v.43 no.4
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• pp.273-279
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• 2016

Recently, it was reported that certain polymorphisms in the growth hormone secretagogue receptor gene (GHSR) are associated with the growth of chickens. However, the correlation between GHSR polymorphisms and economic traits has not been investigated in Korean native chickens (KNCs). Therefore, the objective of this study was to confirm the suitability of the GHSR gene as a candidate for genomic selection and identify a genetic marker for KNCs. A total of 220 KNCs from six breeds raised at the National Institute of Animal Science were genotyped for the c.739+726 SNP in the GHSR gene using polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), and the sequence for a subset of 30 birds was analyzed using direct sequencing. The association between the SNP genotypes and the economic traits of the KNCs was analyzed using the statistical package for the social science (SPSS) software program. The association analysis between the c.739+726T>C SNP and economic traits revealed that the SNP was significantly associated with body weight at 150 and 270 days (BW150 and BW270, respectively) in all KNCs (p<0.01), BW150 in KNC (Gary) (p<0.05), and egg production number in KNC (White, p<0.05). In addition, the SNPs discovered using direct sequencing (513A>G, 517A>T) had a significant effect on the body weight and egg production traits (p<0.05). In conclusion, these results might be useful as a basis for studies on the improvement of KNC breeds. Furthermore, these results suggest that the SNPs (c.739+726T>C, 513A>G, and 517A>T) located in the GHSR gene could be useful molecular genetic markers for KNCs.

• Journal of Korean Society of Forest Science
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• v.108 no.4
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• pp.469-483
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• 2019

North Korea has experienced floods and sediment-related disasters annually since the 1970s due to deforestation. It is of paramount importance that technologies and trends related to forest restoration and soil erosion control engineering be properly understood in a bid to reduce damage from sediment-related disasters in North Korea, and to effect national territorial management following unification. This paper presents a literature review and bibliometric analysis including 146 related articles published in North Korea. First, we analyzed the textual characteristics of the articles. We then employed the VOSviewer software package to classify the research topic and analyzed this topic based on the time change. The results showed that articles on the topic have consistently increased since the 1990s. In addition, research related to soil erosion control engineering has been classified into four subjects in North Korea: (i) assessment of hazard area on soil erosion and soil loss, sediment related-disasters; (ii) hydraulic and hydrologic understanding of forests; (iii) reasonable construction of soil erosion control structures; and (iv) effects and management plan of soil erosion control works. The proportion of research related to the (ii) hydraulic and hydrologic understanding of forests had been significant during the reign of Kim Ilsung. However, the proportion of research related to the (i) assessment of hazard area on soil erosion and soil loss, sediment-related disasters, increased during the reign of Kim Jongil and Kim Jongun. Using these results, our analysis indicated that an interest in and need for soil erosion control engineering in North Korea has continually increased. The results of this study are expected to serve as a basis for preparing forestry cooperation between North and South Korea, and to serve as essential data for better understanding soil erosion control engineering in North Korea.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.