• Journal of Korean Academy of Fundamentals of Nursing
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• v.21 no.1
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• pp.18-28
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• 2014

Purpose: This study was done to apply Andersen's behavioral model to identify factors that determine oral health-related quality of life in elderly persons. Methods: Participants were 257 people ages 65 years or older. Data were analyzed using frequency, percentage, mean and hierarchical multiple regression. Results: The variables in the behavioral model, predisposing factors, enabling factors and need factors, explained 31% (F=12.7, p<.001) of variance in oral health-related quality of life. The predisposing factors, enabling factors, need factors and health behavior collectively explained 35% (F=9.22, p<.001) of variance in oral health-related quality of life. Factors influencing oral health-related quality of life in older adults were ADL and IADL, self-reported oral health status, xerostomia and dental care in last 12 months. Conclusions: The analysis results showed that the need factor had the highest level of relative importance of the three factors. The model used for this study can be used to predict oral health-related quality of life.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1729-1734
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• 2011

Urban transit administers need to introduce the intelligent system to know the situations in the urban transit service area automatically. It is one of the important elements to detect of intrusion in operation room or electric rooms, etc. In this paper, we describe the definition for detection of intrusion in urban transit area, and propose the context-awareness model detect of intrusion. We expect that the definition is helpful to extract the elements that are need to construct the intrusion detecting system. The proposed model that is based on an image analysis model and a rule-based model is also helpful to design intelligent surveillance model.

• Journal of Ship and Ocean Technology
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• v.5 no.4
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• pp.44-50
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• 2001

Large container carriers are suffering from lack of knowledge on reliable correlation allowances between model tests and full-scale trials, especially at fully loaded condition, Careful full-scale sea trial with a full loading of containers both in holds and on decks was carried out to clarify it. Model test results were analyzed by different methods but with the same measuring data to figure out appropriated correlations factors for each analysis methods, Even if it is no doubt that model test technique is one of the most reliable tool to predict full scale powering performance, its assumptions and simplifications which have been applied on the course of data manipulation and analysis need a feedback from sea trial data for a fine tuning, so called correlation factor. It can be stated that the best correlation allowances at fully loaded condition for both 2-dimensional and 3-dimensional analysis methods are fecund through the careful sea trial results and relevant study on the large size container carriers.

• Journal of the korean academy of Pediatric Dentistry
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• v.24 no.1
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• pp.195-203
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• 1997

The purpose of this study is to provide framework for understanding women's preventive dental utilization. In this paper Andersen-Newman's model is applied to the use of dental visits. This model consists of predisposing, enabling, and need components that describe a person's decision to use preventive health services. The sample consisted of 1907 women living Iksan city. Models are operationalized using stepwise multiple regression analysis and path analysis. The number of independent variables used in the analysis was 27 in total, i.e. 20 predisposing components, 6 enabling components, and 1 need component. Preventive dental utilization was measured based on the number of visits. The data collected by means of a questionnaire survey. In this study, the amount of variance by the model was 11 percent. Number of restricted activity days caused by oral disease, perceived threat of dental disease, having a regular dental care, and income were found to have significant major effects on preventive dental utilization of women. Number of restricted activity days caused by oral disease was the most important variable affecting preventive dental utilization of women.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.395-408
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• 2003

Common Channel Signaling(CCS) networks need special controls to avoid overload of signaling networks and degradation of call process-ing rate, since they play an important role of controlling communication transfer networks. Congestion control and flow control mechanisms are well described in ITU-T recommendation on Signaling System No.7(SS7). For the practical provisions, however, we need an analysis on the relation among service objects, system requirements and implementation of congestion control algorithms. SS7 provides several options for controlling link congestion in CCS networks. In this paper we give a general queueing model of congestion control algorithm which covers both the international and national options. From the queuing model, we obtain the performance parameters such as throughput, message loss rate and mean delay for the international option. To show the performance of the algorithm, some numerical results are also given.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.252-255
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• 1997

In this paper, we will propose the methodology of data analysis using the fuzzy property set model. In real world, the data can be represented with the object. $\theta$. and the property, $\pi$, and its has-property relation, P. Then, the conceptual space can be defined with the chosen properties. Each object has a unique location in the conceptual space. In Fuzzy mode, the fuzzy property, and fuzzy conceptual space can be redefined. To analyze data using the fuzzy property set model, the rough set need to be defined in the fuzzy conceptual space.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.117-144
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• 2008

Lots of virtual communities and online businesses presently derive their primary sources of revenues through advertising, but nevertheless are plagued with marginal profitability though they might possess a significant user base. In the light of the need for an efficacious business model, there have been recent insights of an online community in particular reaping profits through an innovative and lucrative revenue generation method that earns by selling digital items. There have been some obvious evidences (e.g., Cyworld, SecondLife, Habo Hotel, etc.) that online communities can be profitable through their unique business model of selling digital items. However, there is lack of understanding about the motivation of purchasing digital items. This study tries to identify the main motivators of digital item purchases based on social/individual identity theory and self-presentation theory. "Digital items", otherwise known as "virtual assets", may include online avatars, accessories for the avatars, decorative ornaments like furniture, digital wallpapers, skins, background music and virtual weapons used for Internet games. These digital items are employed by users for representation and articulation in the online space, especially to create and enhance their online profiles in web pages and games. Prices for digital items typically range from a few cents to a few dollars each. Based on the theoretical framework like social identity theory and self-presentation theory, we developed the research model and proposed seven hypotheses. An analysis of 225 members of Cyworld found that digital item purchase intention in virtual world is affected by both members' need for self-presentation and need for affiliation. We also found that the need for self-presentation is significantly increased by innovativeness of members, community group norm, and community involvement. We concluded that the need for self-presentation could be a key variable for profitable business model in online community service industry. However, neither individual self-efficacy nor the need for affiliation significantly influenced the need for self-presentation which triggers purchase intention of digital items. In term of the theoretical and practical contribution, this study can be a pioneering empirical research that investigates the purchase intention of digital items based on social identity theory and self-presentation theory in the online context. Also, the findings of our study are valuable and practical for practitioners in the market who wish to adopt or improve the business model of selling digital items in an online community. From the findings, it can be seen that innovativeness of users, community group norm, and community involvement are three significant factors that influence need for self-presentation of users which ultimately leads to their intentions to buy digital items. These findings put forth that virtual community providers and online businesses selling digital items should prioritize their efforts and focus on these three factors if they want to increase the sales of these digital items and generate greater revenues. This study provides important implications for academic researchers and practitioners to understand why the community members pay money for their digital items in virtual world and how the practitioners can increase the sales of digital items in an online community. A couple of limitations of the study and future research directions are also discussed.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.823-829
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• 2001

Even though a rapid development of modem medical science, paralysis disease is a highly dangerous and murderous disease. Shin et al. (1978) constructed the diagnosis expert system which identify a type of the paralysis disease from symptoms of a paralysis disease patients by using the canonical discriminant analysis. The decision tree-based analysis, however, has advantages over the method used in Shin et al. (1998), such as it does not need assumptions - linearity and normality, and suggest appropriate diagnosis procedure which is easily explained. In this paper, we applied the decision tree to construct the model which Identify a type of the paralysis disease.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.

• Journal of Embryo Transfer
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• v.31 no.1
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• pp.97-107
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• 2016

Although many diseases could be treated by the development of modern medicine, there are some incurable diseases including brain cancer, Alzheimer disease, etc. To study human brain cancer, various animal models were reported. Among these animal models, mouse models are valuable tools for understanding brain cancer characteristics. In spite of many mouse brain cancer models, it has been difficult to find a new target molecule for the treatment of brain cancer. One of the reasons is absence of large animal model which makes conducting preclinical trials. In this article, we review a recent study of molecular characteristics of human brain cancer, their genetic mutation and comparative analysis of the mouse brain cancer model. Finally, we suggest the need for development of large animal models using somatic cell nuclear transfer in translational research.