• Restorative Dentistry and Endodontics
• /
• v.27 no.2
• /
• pp.142-149
• /
• 2002

Low-viscosity composite resins may produce better sealed margins than stiffer compositions (KempScholte and Davidson, 1988: Crim, 1989). Plowable composites have been recommended for use in Class V cavities but it is also controversial because of its high rates of shrinkage. On the other hand, in the study comparing elastic moduli and leakage, the microfill had the least leakage (Rundle et at. 1997) Furthermore, in the 1996 survey of the Reality Editorial Team, microfills were the clear choice for abfraction lesions. The purpose of this study was to evaluate the microleakage of 6 compostite resins (2 hybrids, 2 microfills, and 2 flowable composites) with and without load cycling. Notch-shaped Class V cavities were prepared on buccal surface of 180 extracted human upper premolars on cementum margin. The teeth were randomly divided into non-load cycling group (group 1) and load cycling group (group 2) of 90 teeth each. The experimental teeth of each group were randomly divided into 6 subgroups of 15 samples. All preparations were etched, and Single bond was applied. Preparations were restored with the following materials (n=15) : hybrid composite resin [Z250(3M Dental Products Inc. St. Paul, USA), Denfil(Vericom, Ahnyang, Korea)], microfill [Heliomolar RO(Vivadent, Schaan, Liechtenstein), Micronew(Bisco Inc. Schaumburg, IL, USA)], and flowable composite［AeliteFlo(Bisco Inc. Schaumburg, IL, USA), Revolution(Kerr Corp. Orange, CA, USA)]. Teeth of group 2 were subjected to occlusal load (100N for 50,000 cycles) using chewing simulator(MTS 858 Mini Bionix II system, MTS Systems Corp. Minn. USA). All samples were coated with nail polish 1mm short of the restoration, placed in 2％ methylene blue for 24 hours, and sectioned with a diamond wheel. Enamel and dentin/cementum margins were analyzed for microleakage on a sclale of 0 (no leakage) to 3 (3/3 of wall). Results were statistically analyzed by Kruscal-Wallis One way analysis, Mann-Whitney U-test, and Student-Newmann-Keuls method. (p = 0.05) Results : 1. There was significantly less microleage in enamel margins than dentinal margins of all groups (p＜0.05) 2. There was no significant between six composite resin in enamel margin of group 1. 3. In dentin margin of group 1, flowable composite had more microleakage than others but not of significant differences. 4. there was no significant difference between six composite resin in enamel margin of group 2. 5. In dentin margin of group 2, the microleakage were R＞A =H=M＞D＞Z. But there was no significant differences. 6. In enamel margins, load cycling did not affect the marginal microleakage in significant degree. 7. In enamel margins, load cycling did affect the marginal microleakage only in Revolution. (p＜0.05).

• Journal of Intelligence and Information Systems
• /
• v.21 no.3
• /
• pp.79-99
• /
• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.34 no.3
• /
• pp.189-200
• /
• 2008

In this study, the antioxidative effects, inhibitory effects on elastase, and components of Quercus glauca extracts were investigated. The free radical (1,1-diphenyl-2-picrylhydrazyl, DPPH) scavenging activity $(FSC_{50})$ of extract I fractions of Quercus glauca leaf was in the order: 50% ethanol extract $(12.45{\mu}g/mL)$ < ethyl acetate fraction $(10.47{\mu}g/mL)$ < deglycosylated flavonoid aglycone fraction $(8.57{\mu}g/mL)$. Reactive oxygen species (ROS) scavenging activities $(OSC_{50})$ of some Quercus glauca leaf extracts on ROS generated in $Fe^{3+}-EDTA/H_2O_2$ system were investigated using the luminol-dependent chemiluminescence assay. The order of ROS scavenging activity was 50% ethanol extract $(OSC_{50},\;4.2{\mu}g/mL)$ < deglycosylated flavonoid aglycone fraction $(1.58{\mu}ug/mL)$ < ethyl acetate fraction $(0.66{\mu}g/mL)$. Ethyl acetate fraction showed the most prominent scavenging activity. The protective effects of extract / fractions of Quercus glauca leaf on the rose-bengal sensitized photohemolysis of human erythrocytes were investigated. The Quercus glauca leaf extracts suppressed photohemolysis in a dose dependent manner, particularly deglycosylated flavonoid aglycone fraction exhibited the most prominent celluar protective effect $({\tau}_{50}$, 398.67 min at $50{\mu}g/mL$). Aglycone fractions obtained from the deglycosylation reaction of ethyl acetate fraction among the Quercus glauca leaf extracts, showed 2 bands in TLC and 2 peaks in HPLC experiments (360 nm) as well. Two components were identified as quercetin (55.77%), and kaempferol (44.23 %). TLC chromatogram of ethyl acetate fraction of Quercus glauca leaf extracts revealed 6 bands $(QG1{\sim}QG6)$, Among them, isoquercitrin (QG3), hyperin (QG4), and rutin (QG6) were identified. The inhibitory effect of aglycone fraction on tyrosinase $(IC_{50},\;73.5{\mu}g/mL)$ and elastase $(IC_{50},\;16.2{\mu}g/mL)$ was high. These results indicate that extract / fractions of Quercus glauca can function as antioxidants in biological systems, particularly skin exposed to UV radiation by scavenging $^1O_2$ and other ROS, and protect cellular membranes against ROS. And component analysis of Quercus glauca leaf extract and inhibitory activity on tyeisinase and elastase of the aglycone fraction could be applicable to new functional cosmetics.

• Journal of the Korean Geographical Society
• /
• v.40 no.1 s.106
• /
• pp.126-152
• /
• 2005

In recent years, there are some confusions related to the definition and existence of mountain ranges, which have been described in current geography text books. We contend that these confusions came from the lack of understanding on the geomorphological processes that form the mountain system in Korea. This research attempts to clarify the definition of mountain ranges and offer geological and geomorphological explanations about the formation of them. Based on the analyses of the social and cultural causes underlying the recent debates on the existence of mountain ranges, we tried to identify the relationships among the definition of mountain ranges, geological structure of Korea, and the forming processes of mountain ranges. The current and past mountain range maps were compared with geological structures, geological maps, surface curvature, and hill shade maps. The latter two maps were derived from a Digital Elevation Model of the Korean Peninsular. The results show that we are able to prove the existence of most mountain ranges, which provides a useful framework to understand the geological evolution of Korean peninsular and formation of mountainous landscape of Korea. In terms of their morphological continuity and genesis, however, we identified five different categories of mountain ranges: 1) Uplift mountain ranges(Hamkyeong Sanmaek, Nangrim Sanmaek, Taebaek Sanmaek), which were formed by the uplift processes of the Korean Peninsular during the Tertiary; 2) Falut mountain ranges(Macheonryeong Sanmaek, Sobaek Sanmaek, Buksubaek Sanmaek), whirh were directly related to the uplift processes of the Korean Peninsular during the Tertiary; 3) Trust mountain ranges(Jekyouryeong Sanmaek, Kwangju Sanmaek, Charyeong Sanmaek, Noryeong Sanmaek), which were formed by the intrusion of granite and consequent orogenic processes during the Mesozoic era; 4) Drainage divide type mountain ranges, which were formed by the erosion processes after the uplift of Korean Peninsular; 5) Cross-drainage basin type mountain ranges (Kangnam Sanmaek, Eunjin Sanmaek, Myelak sanmaek), which were also formed by the erosion processes, but the mountain ranges cross several drainage basins as connecting mountains laterally We believe that the current social confusions related to the existence of mountain ranges has partly been caused by the vague definition of mountain ranges and the diversity of the forming processes. In order to overcome theses confusions, it is necessary to characterize the types of them according the genesis, the purpose of usages and also the scale of maps which will explains the mountain systems. It is also necessary to provide appropriate educational materials to increase the general public's awareness and understanding of geomorphological processes.

• Clinical and Experimental Pediatrics
• /
• v.52 no.10
• /
• pp.1153-1160
• /
• 2009

Purpose:To evaluate the risk factors for mortality and prognostic factors in pediatric hemato-oncology patients admitted to the pediatric intensive care unit (PICU). Methods:We retrospectively reviewed the medical records of pediatric hemato-oncology patients admitted at the PICU of the Asan Medical Center between September 2005 and July 2008. Patients admitted at the PICU for perioperative or terminal care were excluded. Results:Total 88 patients were analyzed. Overall ICU mortality rate was 34.1%. Mean age at PICU admission was $7.0{\pm}5.7$ years and mean duration of PICU stay was $18.1{\pm}22.2$ days. Hematologic diseases contributed to 77.3% of all the primary diagnoses, and the primary cause of admission was respiratory failure (39.8%). The factors related to increased mortality were C-reactive protein level (P<0.01), ventilation or dialysis requirement (P<0.01), and hematopoietic stem cell transplantation (P<0.05). In all, 3 scoring systems were investigated [Number of Organ System Failures (OSF number), the Pediatric Risk of Mortality III (PRISM III) score, and the Sequential Organ Failure Assessment (SOFA) score]; higher score correlated with worse outcome (P<0.01). The Oncological Pediatric Risk of Mortality (O-PRISM) scores of the 21 patients who had received hematopoietic stem cell transplantation were higher among the non-survivors, but not statistically significant (P=0.203). Conclusion:The PRISM III and SOFA scores obtained within 24 hours of PICU admission were found to be useful as early mortality predictors. The highest OSF number during the PICU stay was closely related to poor outcome.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.109-130
• /
• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.53-74
• /
• 2018

Since South Korea has an economic structure that has a characteristic which market-dependent on overseas, the tourism industry is considered as a very important industry for the national economy, such as improving the country's balance of payments or providing income and employment increases. Accordingly, the necessity of more accurate forecasting on the demand in the tourism industry has been raised to promote its industry. In the related research, economic variables such as exchange rate and income have been used as variables influencing tourism demand. As information technology has been widely used, some researchers have also analyzed the effect of media on tourism demand. It has shown that the media has a considerable influence on traveler's decision making, such as choosing an outbound destination. Furthermore, with the recent availability of online information searches to obtain the latest information and two-way communication in social media, it is possible to obtain up-to-date information on travel more quickly than before. The information in online media such as blogs can naturally create the Word-of-Mouth effect by sharing useful information, which is called eWOM. Like all other service industries, the tourism industry is characterized by difficulty in evaluating its values before it is experienced directly. And furthermore, most of the travelers tend to search for more information in advance from various sources to reduce the perceived risk to the destination, so they can also be influenced by online media such as online news. In this study, we suggested that the number of online media posting, which causes the effects of Word-of-Mouth, may have an effect on the number of outbound travelers. We divided online media into public media and private media according to their characteristics and selected online news as public media and blog as private media, one of the most popular social media in tourist information. Based on the previous studies about the eWOM effects on online news and blog, we analyzed a relationship between the volume of eWOM and the outbound tourism demand through the panel model. To this end, we collected data on the number of national outbound travelers from 2007 to 2015 provided by the Korea Tourism Organization. According to statistics, the highest number of outbound tourism demand in Korea are China, Japan, Thailand, Hong Kong and the Philippines, which are selected as a dependent variable in this study. In order to measure the volume of eWOM, we collected online news and blog postings for the same period as the number of outbound travelers in Naver, which is the largest portal site in South Korea. In this study, a panel model was established to analyze the effect of online media on the demand of Korean outbound travelers and to identify that there was a significant difference in the influence of online media by each time and countries. The results of this study can be summarized as follows. First, the impact of the online news and blog eWOM on the number of outbound travelers was significant. We found that the number of online news and blog posting have an influence on the number of outbound travelers, especially the experimental result suggests that both the month that includes the departure date and the three months before the departure were found to have an effect. It is shown that online news and blog are online media that have a significant influence on outbound tourism demand. Next, we found that the increased volume of eWOM in online news has a negative effect on departure, while the increase in a blog has a positive effect. The result with the country-specific models would be the same. This paper shows that online media can be used as a new variable in tourism demand by examining the influence of the eWOM effect of the online media. Also, we found that both social media and news media have an important role in predicting and managing the Korean tourism demand and that the influence of those two media appears different depending on the country.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.33 no.3
• /
• pp.145-152
• /
• 2007

In this study, the antioxidative effects of Sueada asparagoides and Salicornia herbacea extracts were investigated. The free radical(1,1-diphenyl-2-picrylhydrazyl, DPPH) scavenging activity($FSC_{50}$) of extract/fractions of Sueada asparagoides was in the order: 100 % ethanol extract(329.33 ${\mu}g/mL$) < 50 % ethanol extract(40.73) < ethylacetate fraction(13.87) < deglycosylated aglycone fraction (7.80). In case of Salicornia herbacea, the free radical scavenging activities of ethylacetate fraction and aglycone fraction were 13.87 and 7.80 ${\mu}g/mL$, respectively. Reactive oxygen species(ROS) scavenging activities($OSC_{50}$) of Sueada asparagoides and Solicornia herbacea extracts on ROS generated in $Fe^{3+}-EDTA/H_2O_2$ system were investigated using the luminol-dependent chemiluminescence assay. The order of ROS scavenging activity of Sueada asparagoides extracts was 50 % ethanol extract($OSC_{50}$, $0.99{\mu}g/mL$) < ethylacetate fraction (0.05) < aglycone fraction (0.03). Aglycone fraction showed the most prominent scavenging activity. In case of Salicornia herbacea, the ROS scavenging activities of ethylacetate fraction and aglycone fraction were 0.10 and 0.20 ${\mu}g/mL$, respectively. The protective effects of extract/fractions of Sueada asparagoides and Salicornia herbacea on the rose-bengal sensitized photohemolysis of human erythrocytes were investigated. The ethanol extract(100%) of Sueada asparagoides diminished photohemolysis in a concentration dependent manner($1{\sim}100{\mu}g/mL$). Particularly deglycosylated aglycone fraction exhibited the most prominent celluar protective effect($\tau_{50}$, 310 min at 50 ${\mu}g/mL$). In case of Salicornia herbacea, ethylacetate fraction exhibited more potent protective effect. These results indicate that extract/fractions of Sueada asparagoides can function as antioxidants in biological systems, particularly skin exposed to UV radiation by scavenging $^1O_2$ and other ROS, and protect cellular membranes against ROS.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.41 no.2
• /
• pp.11-26
• /
• 2013

Designing large parks such as Yongsan Park requires the open-ended process-oriented design approach in complex layers rather than the conventional self-completed master plan method. This study aims to examine the characteristics of process-oriented design in the eight invited entries of "International Competition for the Master Plan of the Yongsan Park, Korea"(2012). For this purpose, it analyzed each entry according to three criteria: objects of process-oriented approach, time factor and its features of phasing plan, and presentation method of the process. This analysis can not only critically review the current level of the process-centered design methodology but also suggest strategic future directions for Yongsan Park. The objects of process-oriented design in the eight works were order of physical space development, restoration process of ecosystem, recovering process of publicity, and economic operation and management. Main considerations in the objects were connections to adjacent urban fabrics, links to regional green and water system, reuse of existing buildings and infrastructures in the site. The temporal criteria of the phasing plan had two aspects. One was planning a certain time and period, and the other was just establishing an order of phases. Most of the presentation method of process was the phasing plan, but some of the entries suggested a scenario plan. The eight works of "International Competition for the Master Plan of Yongsan Park" did not attempt process-oriented designs entirely and completely. Rather, they tried to introduce the phasing plan as part of a process-centered design. Also, they took an eclectic approach between master plan and process-oriented design instead of rejecting the conventional master plan approach.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.61-83
• /
• 2012

A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.