• The Journal of Korean Academy of Prosthodontics
• /
• v.46 no.2
• /
• pp.169-174
• /
• 2008

Statement of problem: Changes of the marginal bone around dental implants have significance not only for the functional maintenance but also for the esthetic success of the implant. It was proposed that bone-retention elements such as microthreads at the coronal part of implant might help maintain the marginal bone level. Purpose: This study was designed to evaluate the effect of microthread configuration within the marginal coronal portion of the implant fixture at the marginal bone changes after loading around two different external hex implants. Material and methods: Twenty-four patients were included and randomly assigned to treatment with $Br{{\aa}}nemark$ system implants (Group 1, rough-surfaced implants, n=20) and Oneplant system implants (Group 2, rough-surfaced neck with microthreads, n=20). Clinical and radiographic examinations were conducted at baseline (implant loading) and 1 year postloading. Data analysis was performed by the SAS statistical package version 9.1.3 (SAS Institute, Cary, NC, USA) and the final model was calculated by the MIXED procedure (three-level ANCOVA) for marginal bone change of each test group at baseline and 1 year follow-up. Results: Comparing to baseline, significant differences were noted in marginal bone level changes for the 2 groups at 1 year follow-up (P<0.05). Group 1 had a mean crestal bone level changes of $0.83{\pm}0.31mm$; Group 2 had a mean crestal bone level changes of $0.44{\pm}0.36mm$. Rough-surfaced with microthreads implants showed significantly less marginal bone loss than rough surfaced neck without microthread implants. Conclusion: A rough surface with microthreads at the implant was beneficial design to maintain the marginal bone level against functional loading.

• Food Science and Preservation
• /
• v.15 no.1
• /
• pp.15-20
• /
• 2008

By considering the storage temperatures of agricultural products, three types of PCMs $(K_1$, $K_2$, $K_3$) were developed to be used in temperature ranges of $0{\sim}5^{\circ}C$, $5{\sim}10^{\circ}C$ and $10{\sim}15^{\circ}C$, $K_1$ PCM for $0{\sim}5^{\circ}C$ was developed by mixture of $C_{14}H_{30}$ and soduim polyacrylate, and $K_2$ PCM for $5{\sim}10^{\circ}C$ and $K_3$ PCM for $10{\sim}15^{\circ}C$ were mixture of $C_{14}H_{30}$, $C_{18}H_{38}$ and soduim polyacrylate with different composition ratio. 'The target temperatures of cold chain system were set at $7^{\circ}C$, $13^{\circ}C$, and $17^{\circ}C$ with $K_{1-3}$, $K_{2-3}$ and $K_{3-1}$ PCMs, respectively. The times to reach the target temperatures in the storage chamber were 21 hours, 18 hours, and 61 hours with $K_1$, $K_2$, and $K_3$ PCMs, respectively. The performances of natural convection type and forced convection of the temperature controlled portable container were analyzed Apples were stored in the portable container of $5^{\circ}C$, and temperatures at surface and center were measured. The initial temperature of the apple was $25^{\circ}C$. The temperatures of apple at the surface and the center were $15^{\circ}C$ and $16^{\circ}C$, respectively, after 5 hours with natural convection type. However, the temperatures at the surface and the center were already reached to $7^{\circ}C$ within 1 hour with forced convection type. The forced convection type showed the better performance and the temperatures of portable container were maintained more than 15 hours.

• Korean Journal of Food Science and Technology
• /
• v.11 no.1
• /
• pp.42-49
• /
• 1979

In order to evaluate the utility of the anthocyanins of Amaranthys tricolor L. as an edible pigment, the present study was undertaken to investigate the effects of pH. temperature, ascorbic acid, sugars and their degradation products, quercetin, thiourea, sodium pyrophosphate and metal ions on the stability of the anthocyanins in the model systems. The results obtained from this study were as follows. 1. The degradation of total anthocyanins was retarded as the pH levels decreased from 8.0 to 1.0. At pH 1.0, however. the initial degradation reaction proceeded faster than at pH 2.0 to 3.0 2. On heating in buffered aqueous solution at $80^{\circ}C$, the total anthocyanin content was higher at pH 2.0 than other pH levels. Increasing the storage temperature accelerated greatly the pigment degradation. In darkness at $40^{\circ}C$, after 10 days, only 19% of the original amount was left, while at $2^{\circ}C$, under the same conditions of storage, approximately 90% of the pigment was retained. The half-life of the pigment, 63.0 days at $2^{\circ}C$, shortened to 1. 7 days at $40^{\circ}C$. 3. An increase in ascorbic arid concentration from 0. 15 to 0.50 mg/ml lowered the anthocyanin retention. 4. There was no significant difference between glucose and fructose in anthocyanin degradation effect. Furfural was more effective than other sugar degradation products, formic acid or levulinic acid in accelerating anthocyanin breakdown. 5. Neither quercetin nor sodium pyrophosphate had a protective effect on the anthocyanins in the presence of ascorbic acid, while, in the systems 0.5 or 1 mg/ml of thiourea with $150{\;}{\mu}g/ml$ of ascorbic acid, the loss of anthocyanins was significantly reduced. 6. Both mercuric and cupric ions in 30 ppm greatly accelerated anthocyanin degradation.

• Journal of the Korea Computer Graphics Society
• /
• v.6 no.4
• /
• pp.1-7
• /
• 2000

Traditionally, three dimension model s have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity. it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined. traversed, and rendered together. In fact, as suggested by Shade et al. [1]. these different representations can be used as different LOD's for a given object. For in stance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range. and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform : designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection. handling their transition s. implementing appropriate interaction schemes. and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit. to accommodate new node types for environment maps. billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also. during interaction, regardless of the viewing distance. a 3D representation would be used, if it exists. Finally. we carried out experiments to verify the theoretical derivation of the switching rule and obtained positive results.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.8 no.6
• /
• pp.1572-1578
• /
• 2007

The specified wastes consist of waste acid, waste alkali, waste oil, waste organic solvent, waste resin, dust, sludge, infectious waste, and others. Among these specified wastes, a great portion is liquid phase wastes. The purpose of this study is to develop the high temperature and high pressure (HTHP) treatment system for decomposition of the liquid phase specified waste (LPSW). For this, we analyzed the physical and chemical properties of the LPSW such as density, proximate analysis, ultimate analysis, heating values, and designed 0.3 ton/day HTHP treatment system. The LPSW tested in this experiment were prepared by adding TCE(trichloroethylene) and toluene to liquid phase waste which was brought into the commercial waste treatment company. The average density of waste oil (25 samples), waste resin (5 samples), and waste solvent (12 samples) was 0.99 g/mL, 0.91 g/mL, and 0.93 g/mL, respectively. And the average lower heating value of waste oil, waste resin, and waste solvent was 8,294 kcal/kg, 5,809 kcal/kg, and 7,462 kcal/kg, respectively. The DRE (Destruction & Removal Efficiency) of TCE and toluene were 99.95% and 99.73% at atmospheric pressure conditions and that were 99.99% and 99.82% at pressurized conditions, respectively. These results showed that TCE/toluene mixtures were properly decomposed over about 99.73% of DRE by the HTHP treatment system and pressurized conditions were more effective to destroy those pollutants than atmospheric pressure conditions. Also these systems could be directly applied to industries which try to treat the liquid phase specified waste within the regulation limit.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.133-148
• /
• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Korean Journal of Environmental Biology
• /
• v.32 no.1
• /
• pp.58-67
• /
• 2014

The outdoor mass cultivation is not possible for microalgae in Korea all year round, due to cold winter season. It is not easy to maintain proper level of productivity of microalgae even in winter. To prevent a drastic decrease of temperature in a greenhouse, two layers were covered additionally, inside the original plastic layer of the greenhouse. The middle layer was made up of plastic and the inner layer, of non-woven fabric. Acrylic transparent bioreactors were constructed to get more sunlight, not only from the upper side but also from the lateral and bottom directions. In winter at freezing temperatures, six different culture conditions were compared in the triply covered, insulated greenhouse. Wastewater after anaerobic digestion was used for the cultivation of microalgae to minimize the production cost. Water temperature in the bioreactors remained above $10^{\circ}C$ on average, even without any external heating system, proving that the triple-layered greenhouse is effective in keeping heat. Algal biomass reached to 0.37g $L^{-1}$ with the highest temperature, in the experimental group of light-reflection board at the bottom, with nitrogen and phosphorus removal rate of 92% and 99%, respectively. When fatty acid composition was analyzed using gas-chromatography, linoleate (C18 : 3n3) occupied the highest proportion up to 61%, in the all experiment groups. Chemical oxygen demand (COD), however, did not decrease during the cultivation, but rather increased. Although the algal biomass productivity was not comparable to warm seasons, it was possible to maintain water temperature for algae cultivation even in the coldest season, at the minimum cost.

• Journal of the Korean Applied Science and Technology
• /
• v.34 no.4
• /
• pp.962-973
• /
• 2017

Concerns about an air pollution are gradually increasing at home and abroad. The automotive and fuel researchers are trying to reduce emissions and greenhouse gases of vehicles through a research on new engine designs and innovative after-treatment systems using clean fuels (eco-alternative fuel) and fuel quality improvements. In this paper, we stduy the emission characteristics of greenhouse gases on seven vehicles using gasoline, diesel, and LPG by legal test mode in domestic and abroad.(Urban mode, Highway mode, rapidly acceleration and deceleration, using air conditioner, low temperature condition) Regardless of fuels, most of the greenhouse gases tend to show the worst results in cold FTP-75 mode. In the case of A vehicles (2.0 MPI) and B vehicles (2.4 GDI) using a gasoline fuel, the factors that increase greenhouse gases are in order of a rapidly acceleration and deceleration, using air conditioner, low temperature condition. But G vehicles(LPLi) have different emission characteristics from another vehicles. In the case of A vehicles (2.0 w/o DPF) and B vehicles (2.2 with DPF) using a diesel fuel, the factors that increase greenhouse gases are in order of a rapidly acceleration and deceleration, using air conditioner, low temperature condition. However, the factor of F vehicles are in order of low temperature condition, using air conditioner, rapidly acceleration and deceleration. In conclusion, it will be an effective method to apply different technologies of emission reduction for each fuel.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.33-56
• /
• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Journal of dental hygiene science
• /
• v.12 no.6
• /
• pp.644-651
• /
• 2012

This study purports to measure the level of work friendship in dental clinic and examines the friendship's effect on the organizational effectiveness. Data were collected from workers who worked in dental clinic located in Seoul and Gyeonggi areas by self-administered questionnaires from early in October till lately in September, 2009 through direct interview and e-mail. Among 250 questionnaires, 240 responses were returned, and 17 copies with an inaccurate answer were excluded. Finally 223 responses were analyzed through SPSS program. The study revealed that the work friendship in dental clinic has enormous influence on job satisfaction, occupational commitment, intent to leave, stress etc. The results imply that the managers of the dental clinics need to create an organizational climate which emphasizes on a good relationship among members and have them take part in various committees or informal activities.