• The korean journal of orthodontics
• /
• v.22 no.1
• /
• pp.253-271
• /
• 1992

The purpose of this study was to investigate the difference of EMG activity of the Orbicularis oris and Mentalis muscle between normal occlusion and class III malocclusion group during various lip position and to find out whether any correlations exist between the muscular activity and craniofacial morphology. In this study, 50 subjects with a mean age of 22.9 Years (range 20.0-26.0) were investigated (25 subjects were normal occlusion, and 25 subjects were class III malocclusion). EMG data were recorded from the Orbicularis oris and Mentalis muscle during rest lip posture, lip position at maximum biting, lip position at maximum sealing effort, lip position at chewing, swallowing and phonation with the Medelec MS-25 electromyographic machine. Lateral cephalometric radiographs was taken with the mandible in intercuspal position on all subjects. All data were recorded and statistically processed. The findings of this study can be summerized as follows: 1. In normal occlusion, the maximal mean amplitude of upper lip during the lip position at chewing was lower than that of lower lip and mentalis muscle. But the maximal mean amplitude of orbicularis oris and mentalis muscle during the other lip position was not statistically different. 2. In Class III malocclusion, the maximal mean amplitude of upper lip during the lip position at chewing, swallowing and phonation was lower than that of lower lip and mentalis muscle. But the maximal mean amplitude of orbicularis oris and mentalis muscle during the other lip position was not statistically different. 3. Compare to normal occlusion, the Class III malocclusion was showed low maximal mean amplitude of upper lip during rest lip posture and the lip position at swallowing of saliva, and showed great maximal mean amplitude of lower lip and meantalis muscle during the lip position at chewing and phonation. 4. In normal occlusion, the maximal mean amplitude of upper lip during various lip position was not correlated with the length and thickness of upper lip, but the maximal mean amplitude of lower lip during the lip position at chewing and swallowing was positively correlated with the thickness of lower lip. 5. In Class III malocclusion, the maximal mean amplitude of upper lip during rest lip posture was negatively correlated with the thickness of upper lip, and the maximal mean amplitude of lower lip and mentalis muscle during the lip position at chewing and swallowing was positively correlated with the thickness of lower lip and mentalis muscle. But the maximal mean amplitude of orbicularis oris and mentalis muscle during the other lip position was not correlated with the cephalometric measurements of soft tissue. 6. The correlation between the maximal mean amplitude of orbicularis oris and mentalis muscle and cephalometric measurements of incisors was not nearly present. 7. In normal occlusion, the maximal mean amplitude of lower lip and mentalis muscle during the lip position at maximum biting was negatively correlated with the angle between palatal plane and mandibular plane. In Class III malocclusion, the maximal mean amplitude of upper lip, lower lip and mentalis muscle during function was negatively correlated with the length of maxilla, the maximal mean amplitude of upper lip and lower lip during function was negatively correlated with the SNA and SNPo, and the maximal mean amplitude of lower lip during the lip position at chewing was negatively correlated with the ANB.

• Journal of Soil and Groundwater Environment
• /
• v.11 no.6
• /
• pp.69-75
• /
• 2006

Improper disposal of petroleum and spills from underground storage tanks have created large areas with highly toxic contamination of the soil and groundwater. Methyl tert-butyl ether (MTBE) is widely used as a fuel additive because of its advantageous properties of increasing the octane value and reducing carbon monoxide and hydrocarbon exhausts. However, MTBE is categorized as a possible human carcinogen. This research investigated the Modified Photo-Fenton system which is based on the Modified Fenton reaction and UV light irradiation. The Modified Fenton reaction is effective for MTBE degradation near a neutral pH, using the ferric ion complex composed of a ferric ion and environmentally friendly organic chelating agents. This research was intended to treat high concentrations of MTBE; thus, 1,000 mg/L MTBE was chosen. The objectives of this research are to find the optimal reaction conditions and to elucidate the kinetic and mechanism of MTBE degradation by the Modified Photo-Fenton reaction. Based on the results of experiments, citrate was chosen among eight chelating agents as the candidate for the Modified Photo-Fenton reaction because it has a relatively higher final pH and MTBE removal efficiency than the others, and it has a relatively low toxicity and is rapidly biodegradable. MTBE degradation was found to follow pseudo-first-order kinetics. Under the optimum conditions, [$Fe^{3+}$] : [Citrate] = 1 mM: 4 mM, 3% $H_2O_2$, 17.4 kWh/L UV dose, and initial pH 6.0, the 1000 ppm MTBE was degraded by 86.75% within 6 hours and 99.99% within 16 hours. The final pH value was 6.02. The degradation mechanism of MTBE by the Modified Photo-Fenton Reaction included two diverse pathways and tert-butyl formate (TBF) was identified to be the major degradation intermediate. Attributed to the high solubility, stability, and reactivity of the ferric-citrate complexes in the near neutral condition, this Modified Photo-Fenton reaction is a promising treatment process for high concentrations of MTBE under or near a neutral pH.

• The Journal of the Korean Society for Microbiology
• /
• v.21 no.4
• /
• pp.503-513
• /
• 1986

Previous studies have developed the technique of topical application of tetracycline(TC) into the periodontal pockets and examined the change of clinical parameters and subgingival microbial morphotypes. The purpose of this study was to longitudinally examine the clinical and microbiological effects of topically applied TC in a double-blind and split-mouth design. Thirteen patients with moderate periodontitis, who were treated with or without TC application and scaling treatment, were examined. TC gel(3%) was used to apply into the selected periodontal pockets twice a week for 2 weeks. During the experiment, clinical parameters and subgingival microbial morphotypes were examined, and for isolation of black-pigmented Bacteroides(BPB) and streptococci, an anaerobic sample culturing was done at week 0, 2, and 7. In clinical observation the TC-scaled group exhibited a significant decrease of Gingival Inflammatory Index, Plaque Index, Sulcus Bleeding Index, pocket depth, and gingival crevicular fluid when compared to the TC-unsealed, placebo-scaled, and placebo-unsealed groups. The result of microbial morphotype observation showed a significant increase of coccal form and a decrease of spirochetes in the TC-scaled, TC-unscaled, and placebo-scaled groups. The culture study of streptococci revealed that TC with scaling treatment resulted in a significant increase of S. sanguis I at week 2, but its proportion had returned to the base line level. The anaerobic culture study showed that BPB was significantly reduced in the TC-scaled and TC-unsealed groups at week 7. Among BPB species, B. intermedius declined significantly with time treatment(week 2 and 7) in the TC-scaled and TC-unsealed groups. These results suggest that the settled pathogenic microflora can be succeeded by nonpathogenic microflora in periodontal pockets after TC treatment.

• Tuberculosis and Respiratory Diseases
• /
• v.55 no.5
• /
• pp.499-505
• /
• 2003

Background : The brain is a common site of a metastasis in lung cancer patients. If left untreated, the patients succumb to progressive neurological deterioration with a lower survival rate than with other metastases sites. Contrast-enhanced MR imaging in the absence of symptoms or clinical signs is not recommended for identifying a cerebral metastasis in lung cancer patients because of management effectiveness. This pilot study was performed to estimate whether or not limited brain MR imaging, which has a lower cost, could be used to replace conventional brain MR imaging. Method : Between April 1999 and March 2001, 43 patients with a primary lung cancer and the others (breast cancer, stomach cancer, colon cancer, malignant melanoma etc), who had neurological symptoms and signs, were examined using conventional brain MR imaging to examine brain metastases. The control group involved four patients who had no evidence of brain metastases the sensitivity, specificity and correlation of limited brain MR imaging were compared with conventional brain MR imaging. Results : All the 43 patients who were examined with conventional brain MR imaging showed evidence of brain metastases, whereas limited brain MR imaging indicated that 42 patients had brain metastases(sensitivity=97.67%). One patient in whom limited brain MR imaging showed no brain metastasis had a metastasis in the cerebellum, as shown by the contrast-enhanced T1 weighted axial view using conventional brain MR imaging. The conventional brain MR imaging and the limited brain MI imaging of the 4 control patients both indicated no brain metastases (specificity=100 %). The Pearson Correlation of the two groups was 0.884(Confidence Interval : 99%) observed. Conclusion : Limited brain MR imaging can detect a brain metastasis with the same accuracy. In addition, it is cost-effective (229,000 won, 180$) compared to conventional brain MR imaging(529,000 won, 480$) when patients had neurological symptoms and signs or staging.

• Korean Journal of Materials Research
• /
• v.11 no.5
• /
• pp.427-430
• /
• 2001

We prepared 10cm-diameter Si(100)/500 $\AA$-Si$_3$N$_4$/Si(100) wafer Pairs adopting 500 $\AA$ -thick Si$_3$N$_4$layer as insulating layer between single crystal Si wafers. Si3N, is superior to conventional SiO$_2$ in insulating. We premated a p-type(100) Si wafer and 500 $\AA$ -thick LPCVD Si$_3$N$_4$∥Si (100) wafer in a class 100 clean room. The cremated wafers are separated in two groups. One group is treated to have hydrophobic surface and the other to have hydrophilic. We employed a FLA(fast linear annealing) bonder to enhance the bond strength of cremated wafers at the scan velocity of 0.1mm/sec with varying the heat input at the range of 400~1125W. We measured bonded area using a infrared camera and bonding strength by the razor blade crack opening method. We used high resolution transmission electron microscopy(HRTEM) to probe cross sectional view of bonded wafers. The bonded area of two groups was about 75%. The bonding strength of samples which have hydrophobic surface increased with heat input up to 1577mJ/$m^2$ However, bonding strength of samples which have hydrophilic surface was above 2000mJ/$m^2$regardless of heat input. The HRTEM results showed that the hydrophilic samples have about 25 $\AA$ -thick SiO layer between Si and Si$_3$N$_4$/Si and that maybe lead to increase of bonding strength.

• Restorative Dentistry and Endodontics
• /
• v.32 no.6
• /
• pp.550-558
• /
• 2007

The purpose of this study was to evaluate the insertion depth of several brands of master gutta percha cones after shaping by various Ni-Ti rotary files in simulated canals. Fifty resin simulated J-shape canals were instrumented with ProFile, ProTaper and HEROShaper. Simulated canals were prepared with ProFile .04 taper #25(n=10), .06 taper #25(n=10), ProTaper F2(n=10), HEROShaper .04 taper #25(n=10) and .06 taper #25(n=10). Size #25 gutta percha cones with a .04 & .06 taper from three different brands were used: DiaDent; META; Sure-endo. The gutta percha cones were selected and inserted into the prepared simulated canals. The distance from the apex of the prepared canal to the gutta percha cone tip was measured by image analysis program. Within limited data of this study, the results were as follows 1. When the simulated root canals were prepared with HEROShaper, gutta-percha cones were closely adapted to the root canal. 2. All brands of gutta percha cones fail to go to the prepared length in canal which was instrumented with ProFile, the cones extend beyond the prepared length in canal which was prepared with ProTaper. 3. In canal which was instrumented with HEROShaper .04 taper #25, Sure-endo .04 taper master gutta percha cone was well fitted(p < 0.05). 4. In canal which was instrumented with HEROShaper .06 taper #25, META .06 taper master gutta percha cone was well fitted(p < 0.05). As a result, we concluded that the insertion depth of all brands of master gutta percha cone do not match the rotary instrument, even though it was prepared by crown-down technique, as recommended by the manufacturer. Therefore, the master cone should be carefully selected to match the depth of the prepared canal for adequate obturation.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.159-172
• /
• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Tuberculosis and Respiratory Diseases
• /
• v.61 no.5
• /
• pp.433-439
• /
• 2006

Background: Although airway hyper-responsiveness is one of the characteristics of asthma. bronchial hyper-responsiveness has also been observed to some degree in patients with chronic obstructive pulmonary disease (COPD). Moreover, several reports have demonstrated that a number of patients have both COPD and asthma. The methacholine bronchial challenge test (MCT) is a widely used method for the detecting and quantifying the airway hyper- responsiveness, and is one of the diagnostic tools in asthma. However, the significance of MCT in differentiating asthma or COPD combined with asthma from pure COPD has not been defined. The aim of this study was to determine the role of MCT in differentiating asthma from pure COPD. Method: This study was performed prospectively and was composed of one hundred eleven patients who had undergone MCT at Chonbuk National University Hospital. Sixty-five asthma patients and 23 COPD patients were enrolled and their MCT data were analyzed and compared with the results of a control group. Result: The positive rates of MCT were 65%, 30%, and 9% in the asthma, COPD, and control groups, respectively. The mean $PC_{20}$ values of the asthma, COPD, and control groups were $8.1{\pm}1.16mg/mL$, $16.9{\pm}2.21mg/mL$, and $22.0{\pm}1.47mg/mL$, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of MCT for diagnosing asthma were 65%, 84%, 81%, and 69%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of MCT (ed note: please check this as I believe that these values correspond to the one $PC_{20}$ value. Please check my changes.) at the new cut-off points of$PC_{20}{\leq}16mg/ml$, were 80%, 75%, 78%, and 78%, respectively. Conclusion: MCT using the new cut-off point can be used as a more precise and useful diagnostic tool for distinguishing asthma from pure COPD.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.99-122
• /
• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Korean Journal of Environmental Biology
• /
• v.36 no.3
• /
• pp.400-411
• /
• 2018

This study was a survey of the Wonju stream in Wonju city from May 2015 to September 2016. A total of three sites were selected from the upstream area Gwanseol-dong to the downstream area Hojeo-myeon. Physicochemical analysis, aquatic insect changes, cluster analysis, functional group analysis, rarefaction curve, and statistical analysis were compared between 2004 and 2016. A total of 19 species (38.78%) in 2004 and 22 species (36.67%) in 2016 were analyzed, with the largest number belonging to ephemeroptera. The individual ratio ranged from 27,759.2 (ind. $m^{-2}$, 84.30%) in 2004 to 4,573.2 (ind. $m^{-2}$, 41.64%) in 2016, with the highest number involving diptera. As a result of the community analysis, significant differences were detected in the indices of dominance, diversity, evenness, and richness in 2004 and 2016 (p<0.05). Burrowers of the habitat orientation groups showed the greatest variation with an average of -68.00% (${\pm}2.15$) and the collector-gatherers of the functional feeding groups showed the highest variation of -40.12% (${\pm}1.77$). The rarefaction curve analysis suggested that the species was the poorest in the midstream regions in 2004 and 2016. Physical factors and water quality showed a significant correlation with diversity index, evenness index, and the number of individuals. MDS analysis of the similarity of upstream and downstream regions was high in 2004, and low in 2016. The differences were attributed to physicochemical changes such as increase in flow velocity due to improvement of small dams and changes in bottom structure.