• Journal of the Korean Society for Railway
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• v.3 no.4
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• pp.229-236
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• 2000

In this study, the unsteady flow field induced by a high-speed train passing through a tunnel is numerically simulated by using an axi-symmetric Euler Equation. The modified patched grid scheme applied to a structured grid system was used to handle the relative motion of a train. The hybrid-dimensional approach which mixed 1D and axi-symmetric dimension was used to reduce the computation time and memory storage. By employing the hybrid-dimensional approach, a long tunnel as much as 5 km was able to be simulated efficiently. The results show that the maximum pressure rise in the tunnel by the entrance of the train is a function of both train speed and train-tunnel cross-sectional area ratio. The unsteady pressure fluctuation in the tunnel and around the train was also investigated in the real condition; Korean high-speed train on the Seoul-Pusan line.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.83-93
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• 2017

A typical approach to visualizing k (${\geq}2$)-group multidimensional data is to use Fisher's canonical discriminant analysis (CDA). CDA finds the best low-dimensional subspace that accommodates k group centroids in the Mahalanobis space. This paper proposes an alternative visualization procedure functioning in the Euclidean space, which finds the primary dimension with maximum discrimination of k group centroids and the secondary dimension with maximum dispersion of all observational units. This hybrid procedure is especially useful when the number of groups k is two.

• Journal of the Korean Society for Railway
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• v.5 no.4
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• pp.260-266
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• 2002

A numerical simulation has been performed to estimate the transient pressure variation in the tunnel when G7 test train passes through the test tunnel in the Kyoeng-Bu high-speed railway. A modified patched grid scheme is developed to handle the relative motion between a train and a tunnel. Also, a hybrid dimensional approach is proposed to calculate the train-tunnel interaction problem efficiently. An axi-symmetric unsteady Euler solve using the Roe's FDS is used for analyzing a complicated pressure field in tunnel during the test train is passing through the tunnel. Usually, this complex phenomenon depends ell the train speed, train length, tunnel length, blockage ratio between train and tunnel cross-sectional area, relative position between train and tunnel, etc. Therefore, numerical simulation should be done carefully in consideration of these factors. Numerical results in this study would be good guidance to make test plans, test equipments selection and to decide their measuring locations. They will also supply important information to the pressurization equipment for high-speed train.

• Korean Journal of Health Education and Promotion
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• v.20 no.3
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• pp.145-170
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• 2003

The purpose of this study was to clarity the concept of health insensitivity using Hybrid model, which consists of three phases： theoretical, empirical, and analytic. In the theoretical phase, the definitions of health insensitivity were searched in korean dictionary and examples used in the websites because the concept of health insensitivity has never been studied before. Two dimensions of health insensitivity emerged out from this investigation were cognitive and behavioral. And then a working definition of health insensitivity was established. The sub-concepts and related factors of health insensitivity were identified through the extensive reviews of the literature focusing on two dimensions of cognitive and behavioral. In the empirical phase, in order to obtain description of health insensitivity, face-to-face in-depth interviews were conducted with nine persons who are not related to professional health care. Grounded theory approach was applied to analyze these qualitative data. In the final analytic phase, theoretical results and empirical results were analyzed in the integrated way and a theoretical framework of health insensitivity was established. A refined definition of health insensitivity was that decreased health risk perception in cognitive dimension and conduction of the unhealthy behaviors in behavioral dimension. Sub-concepts of decreased health risk perception were optimistic bias and decreased general fear. Sub-concepts of unhealthy behavior were doing health threatening behavior and not doing desirable health behavior. The contact of health information was a causal condition of health insensitivity. Optimistic disposition, health locus of control, and avoidance coping style were intervening conditions of health insensitivity. Three types of health insensitivity were identified： unconcern or ignorance type, optimistic bias type, and cognitive dissonance type. Finally, The implications of these findings for further research and nursing practice are discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.61-68
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• 2012

Recommender Systems have gained much popularity among researchers and is applied in a number of applications. The exponential growth of users and products poses some key challenges for recommender systems. Recommender Systems mostly suffer from scalability and accuracy. The accuracy of Recommender system is somehow inversely proportional to its scalability. In this paper we proposed a Context Aware Hybrid Recommender System using matrix reduction for Hybrid model and clustering technique for predication of item features. In our approach we used user item-feature rating, User Demographic information and context information i.e. specific time and day to improve scalability and accuracy. Our Algorithm produce better results because we reduce the dimension of items features matrix by using different reduction techniques and use user demographic information, construct context aware hybrid user model, cluster the similar user offline, find the nearest neighbors, predict the item features and recommend the Top N- items.

• Journal of Korean Academy of Nursing
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• v.29 no.3
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• pp.467-484
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• 1999

The main objectives of this study were to investigate the concept of family function from the perspective of the contemporary Korean family, and to construct model of change of family function with chronic illness. The hybrid model approach was applied in which three phases(theoretical phase, empirical phase, and analytic phase) of concept development were explored for family functioning. The study was conducted from 1997 to 1998. In empirical phase, two groups of purposive samples were drawn : normal family group composed of six families without ill family member, and ill family group composed of seven families of which wives have rheumatoid arthritis. Only families with child(or children) in primary or secondary schools were included in the study. The results were as follows : In theoretical phase, six dimensions of family concept were emerged : affective, structural, control, cognitive, financial, and reproductive dimension. In order to analyse the Korean normal family function in middle class with middle-aged women, financial and reproductive dimension were not included. In empirical phase, five dimensions(affective, structural, control, cognitive, and external relationship) were found from the normal family data. External relationship dimension is very important factor as a resource of the support, especially when their parents or siblings had no help or support to them. In the affective dimension, Korean family emphasized harmony and balance rather than affective expression between couples and between parents and children. They also showed common goals of the families to solve their problems to control the family members. The priority of the goals was getting into the higher education of their children or helping their unhealthy parents or family members. Six dimensions (affective, structural, control, cognitive, external relationship, and financial) of family functions were emerged from the ill family data. From the analysis of ill family data, types of restructuring house chore after wives illness were developed : (a) negociated, (b) accomodated, and (c) isolated, enduring types. Although the dimensions of family functioning identified in this study are similar to the conceptualizations that exist in the western literature, there were distinct differences in the nature of major themes and subconcepts under these family function dimensions.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.120-130
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• 2021

The spinal cord or CSF surgery is a very complex process. It requires continuous pre and post-surgery evaluation to have a better ability to diagnose the disease. To detect automatically the suspected areas of tumors and symptoms of CSF leakage during the development of the tumor inside of the brain. We propose a new method based on using computer software that generates statistical results through data gathered during surgeries and operations. We performed statistical computation and data collection through the Google Source for the UK National Cancer Database. The purpose of this study is to address the above problems related to the accuracy of missing hybrid KNN values and finding the distance of tumor in terms of brain cancer or CSF images. This research aims to create a framework that can classify the damaged area of cancer or tumors using high-dimensional image segmentation and Laplace transformation method. A high-dimensional image segmentation method is implemented by software modelling techniques with measures the width, percentage, and size of cells within the brain, as well as enhance the efficiency of the hybrid KNN algorithm and Laplace transformation make it deal the non-zero values in terms of missing values form with the using of Frobenius Matrix for deal the space into non-zero values. Our proposed algorithm takes the longest values of KNN (K = 1-100), which is successfully demonstrated in a 4-dimensional modulation method that monitors the lighting field that can be used in the field of light emission. Conclusion: This approach dramatically improves the efficiency of hybrid KNN method and the detection of tumor region using 4-D segmentation method. The simulation results verified the performance of the proposed method is improved by 92% sensitivity of 60% specificity and 70.50% accuracy respectively.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.33 no.4
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• pp.386-390
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• 2007

This is about the case of loss of multiple teeth and alveolar bone caused by trauma, which needed alveolar bone augmentation before implant treatment. Alveolar bone was reconstructed using iliac bone graft, and thereafter first implant surgery was followed by consolidation period of 3 months. Iliac bone resorption was observed at the time of implant placement. And that resorption was more in the horizontal dimension than in the vertical. We conclude that additional treatment planning(e.g. using alveolar distraction osteogenesis or tissue expander) should be considered besides bone graft for vertical alveolar bone augmentation. For both maxilla and mandible, prosthodontic treatment was carried out $4{\sim}5$ months after implant placement. To compensate alveolar bone deficiency, partial hybrid overdenture on maxilla and implant-supported fixed bridge on mandible were fabricated, and the total treatment was finished.

• Current Optics and Photonics
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• v.2 no.2
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• pp.140-146
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• 2018

In this paper, mesoscale optical surface structures are found to possess both geometric and wave optics features. The study reveals that geometric optic analysis cannot correctly predict the experimental results of light transmission or reflection by mesoscale optical structures, and that, for reliable analyses, a hybrid approach incorporating both geometric and wave optic theories should be employed. By analyzing the transmission patterns generated by the mesoscale periodic pyramid prism plates, we show that the wave optic feature is mainly ascribed to the edge diffraction effect and we estimate the relative contributions of the wave optic diffraction effect and the geometric refraction effect to the total scattering field distribution with respect to the relative dimension of the structures.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.9
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• pp.701-709
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• 2011

In semiconductor wafer fabrication, etching is one of the most critical processes, by which a material layer is selectively removed. Because of difficulty to correct a mistake caused by over etching, it is critical that etch should be performed correctly. This paper proposes a new approach for etch endpoint detection of small open area wafers. The traditional endpoint detection technique uses a few manually selected wavelengths, which are adequate for large open areas. As the integrated circuit devices continue to shrink in geometry and increase in device density, detecting the endpoint for small open areas presents a serious challenge to process engineers. In this work, a high-resolution optical emission spectroscopy (OES) sensor is used to provide the necessary sensitivity for detecting subtle endpoint signal. Partial Least Squares (PLS) method is used to analyze the OES data which reduces dimension of the data and increases gap between classes. Support Vector Machine (SVM) is employed to detect endpoint using the data after PLS. SVM classifies normal etching state and after endpoint state. Two data sets from OES are used in training PLS and SVM. The other data sets are used to test the performance of the model. The results show that the trained PLS and SVM hybrid algorithm model detects endpoint accurately.