• Restorative Dentistry and Endodontics
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• v.32 no.5
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• pp.469-475
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• 2007

The purpose of this study was to evaluate the effect of a new resin monomer on the microleakage of composite resin restorations. By adding new methoxylated Bis-GMA (Bis-M-GMA, 2,2-bis[4-(2-methoxy-3-methacryloyloxy propoxy) phenyl] propane) having low viscosity, the content of TEGDMA which has adverse effects on polymerization shrinkage might be decreased. As a result, microleakage might be improved. $2\;mm\;{\times}\;2\;mm\;{\times}\;2\;mm$ cavities with occlusal margins in enamel and gingival margins in dentin were prepared on buccal and lingual surfaces of 40 extracted human premolars. Prepared teeth were randomly divided into four groups and restored with Clearfil SE bond (Kuraray, Japan) and one of experimental composite resins; EX1, Experimental composite resin1 (Bis-M-GMA/TEGDMA = 95/5 wt%, 40 mm nanofillers); EX2, Experimental composite resin2 (Bis-M-GMA/TEGDMA = 95/5 wt%, 20 mm nanofillers); EX3, Experimental composite resin3 (Bis-GMA/TEGDMA = 70/30 wt%, 40 nm nanofillers); and Filtek Z250 (3M ESPE, USA) was filed as a control group. The restored teeth were thermocycled, and immersed in 2% methylene blue solution for 24 hours. The teeth were sectioned buccolingually with a low speed diamond saw and evaluated for microleakage under stereomicroscope. The data were statistically analyzed by Pearson Chi-Square test and Fisher Exact test (p = 0.05). The microleakage scores seen at the enamel margin were significantly lower than those of dentin margin (p = 0.007). There were no significant differences among the composite resins in the microleakage scores within each margin (p > 0.05). Bis-M-GMA, a new resin monomer having low viscosity, might in part replace high viscous Bis-CMA and might improve the quality of composite resin.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.301-310
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• 2016

This is a nonequivalent control group non-synchronized experiment research to verify the effect of moxibustion therapy on efficient management of daily living disabilities and sleep patterns in elderly women with chronic low back pain. Total 12 sessions of moxibustion therapy were applied to elderly women(30 subjects in an experimental group and 30 subjects in a control group) in G City once a week for 12 weeks from March 15th to May $31^{st}$ 2015. Then the follow-up study was conducted 2 weeks after the post survey. For moxibustion, was applied to Shen-shu, Ashi point, Ta chang shu, Yang kuan and Yosu. 5 sheets of moxibustion were applied to 7 acupuncture points of Mugeukboyang moxibustion; Zu san li & Chu chi, Chung wan, Chung chi & Shui tao, Fei shu, Kao hung and Tien shu, Wijung respectively and experimental treatment was conducted. For assessing the degree of back pain, Visual Analog Scale(VAS) developed by Scott & Huskisson(1979) was used and for measuring the degree of daily living disability, Oswestry Disability Index, which was developed by Fairbank et al(1980) and translated and revised by Yim, Hyeon-sul et al.(1998), was used. For measuring sleep patterns, the sleep pattern measurement tool developed by Oh, Jin-su, Song, Mi-soon and Kim, Sin-mi(1998) was used. For data analysis, SPSS/WIN 18.0 was employed and Chi-square test, t-test and repeated measures ANOVA were performed. There were significant differences in pain score(F=2510.32, p<.001), daily living disability score(F=1937.82, p<.001) and sleep pattern score((F=15.54, p<.001) of elderly women that were provided with moxibustion therapy, compared to the control group. Therefore, it was found that moxibustion therapy made a positive contribution to reduction in pain and daily living disabilities and improvement in sleep quality. Based on this study finding, there is a need to apply moxibustion therapy to elderly people with chronic low back pain as a nursing intervention in future.

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

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

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.6
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• pp.16-24
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• 2015

This study quantified storage and annual uptake of carbon for riparian greenspaces established in watersheds of four major rivers in South Korea and explored desirable strategies to improve carbon reduction effects of riparian greenspaces. Greenspace structure and planting technique in the 40 study sites sampled were represented by single-layered planting of small trees in low density, with stem diameter at breast height of $6.9{\pm}0.2cm$ and planting density of $10.4{\pm}0.8trees/100m^2$ on average. Storage and annual uptake of carbon per unit area by planted trees averaged $8.2{\pm}0.5t/ha$ and $1.7{\pm}0.1t/ha/yr$, respectively, increasing as planting density got higher. Mean organic matter and carbon storage in soils were $1.4{\pm}0.1%$ and $26.4{\pm}1.5t/ha$, respectively. Planted trees and soils per ha stored the amount of carbon emitted from gasoline consumption of about 61 kL, and the trees per ha annually offset carbon emissions from gasoline use of about 3 kL. These carbon reduction effects are associated with tree growth over five years to fewer than 10 years after planting, and predicted to become much greater as the planted trees grow. This study simulated changes in annual carbon uptake by tree growth over future 30 years for typical planting models selected as different from the planting technique in the study sites. The simulation revealed that cumulative annual carbon uptake for a multilayered and grouped ecological planting model with both larger tree size and higher planting density was approximately 1.9 times greater 10 years after planting and 1.5 times greater 30 years after than that in the study sites. Strategies to improve carbon reduction effects of riparian greenspaces suggest multilayered and grouped planting mixed with relatively large trees, middle/high density planting of native species mixed with fast-growing trees, and securing the soil environment favorable for normal growth of planting tree species. The research findings are expected to be useful as practical guidelines to improve the role of a carbon uptake source, in addition to water quality conservation and wildlife inhabitation, in implementing riparian greenspace projects under the beginning stage.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.7
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• pp.656-664
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• 2010

We investigated the levels and distribution patterns of 16 priority polycyclic aromatic hydrocarbons (PAHs), 12 Coplanar polychlorinated biphenyls (Co-PCBs) and organochlorine pesticides (OCPs) in the surface sediments from the Nakdong river basin, Korea. The levels of 16 PAHs and 12 Co-PCBs in the river sediment samples ranged from not detected (N.D.)~969.3 ng/g-dry, 4.2~7716.5 pg/g-dry (0.0~10.1 pg-TEQ/g-dry), respectively. Also, the levels of 16 PAHs were from 5.8~2987.2 ng/g-dry and 4.3~461.1 pg/g-dry (0.0~0.6 pg-TEQ/g-dry) for 12 Co-PCBs in the lake sediment samples. Only dichloro-diphenyl-trichloroethane (DDT) were detected among target OCPs and the concentration ranged from N.D.~1.5 ng/g-dry in the river sediment samples. These contamination levels were far below the guideline values suggested for environmental quality assessment. Low molecular weight PAHs were dominant in the river sediment samples, while middle and high molecular weight PAHs were dominant among 16 PAHs in the lake sediment samples. PCB-118 and PCB-105 were predominant congeners in the sediment, which were similar to the results obtained from previous studies. With these results, the assessment of potential sources of PAHs and Co-PCBs contamination in the sediments of the Nakdong river basin was performed. The pyrogenic-PAHs originated from combustion of fossil fuel and biomass were related with the PAHs contribution in most of the sediment samples, and Co-PCBs in the sediment samples were related with commercial PCB products.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.351-360
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• 2018

The LWR (Locally Weighted Regression) model, which is traditionally a lazy learning model, is designed to obtain the solution of the prediction according to the input variable, the query point, and it is a kind of the regression equation in the short interval obtained as a result of the learning that gives a higher weight value closer to the query point. We study on an incremental ensemble learning approach for LWR, a form of lazy learning and memory-based learning. The proposed incremental ensemble learning method of LWR is to sequentially generate and integrate LWR models over time using a genetic algorithm to obtain a solution of a specific query point. The weaknesses of existing LWR models are that multiple LWR models can be generated based on the indicator function and data sample selection, and the quality of the predictions can also vary depending on this model. However, no research has been conducted to solve the problem of selection or combination of multiple LWR models. In this study, after generating the initial LWR model according to the indicator function and the sample data set, we iterate evolution learning process to obtain the proper indicator function and assess the LWR models applied to the other sample data sets to overcome the data set bias. We adopt Eager learning method to generate and store LWR model gradually when data is generated for all sections. In order to obtain a prediction solution at a specific point in time, an LWR model is generated based on newly generated data within a predetermined interval and then combined with existing LWR models in a section using a genetic algorithm. The proposed method shows better results than the method of selecting multiple LWR models using the simple average method. The results of this study are compared with the predicted results using multiple regression analysis by applying the real data such as the amount of traffic per hour in a specific area and hourly sales of a resting place of the highway, etc.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.6
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• pp.1408-1418
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• 2013

To investigate the quality properties of functional anchovy fish sauce added with raw sea tangle, 2%, 5%, and 10% (w/w) of sea tangle was added to 25% (w/w) salted anchovy and then fermented at $20^{\circ}C$. During fermentation period, the amino nitrogen contents were increased at all groups and the highest contents were at 450 days of fermentation with $11.99{\pm}0.08$, $12.51{\pm}0.08$, and $11.95{\pm}0.08mg/mL$ at 2%, 5%, and 10% addition of raw sea tangle, respectively. After later, the contents were keeping at a similar level. VBN contents were continuously increased until 270 days of fermentation with $208.10{\pm}3.50$, $210.00{\pm}4.10$, $215.15{\pm}1.50mg/100ml$ at 2%, 5%, 10% addition of raw sea tangle, respectively. Alginic acid recovery was gradually increased in fermentation duration, showed the highest concentration at 540 days of fermentation with 67.00, 67.25, 67.90% at 2%, 5% and 10% addition of raw sea tangle, respectively. Dietary fiber recovery was rapidly increased at the beginning of fermentation and then decreased slowly as the fermentation is progressed. The highest recovery was at 30 days with 18.7, 18.6, and 17.9%, and the lowest was at 360 days with 8.7 and 11.1% at 2 and 10% addition of raw sea tangle, respectively, and 450 days with 11.4% at 5% sea tangle. The lowest fucoidan contents were exhibited at 30 days of fermentation with 0.07% at both of 2% and 5% addition, and 90 days with 0.10% at 10% addtion of sea tangle. The highest fucoidan contents were 270 days showing 0.24, 0.25, and 0.23% at 2, 5, and 10% addition, respectively. All groups adding different sea tangle concentration were not significantly different at all properties. However, the newly developed products were sufficient to the standard guideline of Korea Food Drug Adminstration. The best processing process of functional anchovy fish sauce in addition with raw sea tangle is 2% addition of raw sea tangle and fermented more than 450 days. The results obtained in this study indicated that the fish sauce added with sea tangle is superior in taste, functions to traditional fish sauce and could be competitive fishery fermented food.

• Korean Security Journal
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• no.12
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• pp.89-116
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• 2006

As the society changes, the Private Security has developed highly in a short time. However, it has brought about various problems. The best urgent problem of those problems is the wage problem. This study is examining into the difference with the wage satisfaction and devotion to organization, and analyzing influence that wage satisfaction has on devotion to organization. According to this research, the first, women appeared higher numerical value than men in satisfaction with a wage level, wage disparity, wage system and the welfare system and the highest age group is over 26 year-old. While the college graduates appeared high satisfaction with a wage level and wage disparity, the university graduates is high satisfaction with wage system and the welfare. This shows that as the scholarship is high, they think they must be getting wages higher and higher as their work result or produce. The second, in devotion to his(her) organization, the men is higher than the women. The third, the men show the high emotional devotion because the men devote to his work on his own initiative while the women show the high continuos service devotion because they are passively. The fourth, over the 26-year old group appeared high level in devotion to his(her) organization, the university graduate group appeared high level both the emotional devotion and the continuous service devotion. The long-term employed person showed the satisfaction with job position, pay grade, and career and also appeared high in devotion to his(her) organization. The fifth, as the scholarship is low, they were concerned about a wage level and wage disparity but, as the scholarship is high, they were concerned about the wage system and the welfare. The wage satisfaction has influence on the scholarship, job position and career therefore, the long-term employed persons showed high wage satisfaction and devotion to his(her) organization. In conclusion, for the development of Private Security and high devotion to organization, the wage level of private security guards must be systematize and the quality of the welfare must be improved. And the many factors about the wage and welfare must be studied and analyzed to occupy as one of the skill lists through the educational-industrial collaboration.