• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.263-274
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• 2004

High resolution spectroscopic observations of BX And using the BOBS (Bohyunsan Optical Echelle Spectrograph) of Bohyunsan Optical Astronomical Observatory (BOAO) were performod during 26-27, Feb. 2003. From the observations, we obtained 38 line spectra of BX And which cover all phases except the phase interval between $0.^p1$ and $0.^p3$. Both methods of the CCF (Cross-Correlation Function) and BF (Broadening Function) were used to get the radial velocities of primary and secondary components. Both velocities of the primary and secondary stars were calculated with the BF method while only primary velocities were determined with the CCF. Using new radial velocity curves, the maximum radial velocities of the primary and secondary stars were obtained as $K_1=90.1km/s\;and\;K_2=196.6km/s$, respectively. New absolute dimension of BX And was deduced with the combination of our spectroscopic solution with the photometric one of Bell et al. (1990).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.271-278
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• 2004

In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital sign processing approach. From the 20 seconds query audio file, the audio signal is segmented into 23ms frame with non-overlapped hamming window and 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS(Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we can verify the superior performance of the proposed method that provides near 90% success rate for the genre classification which means 10%∼20% improvements over the previous methods. For the case of actual user system environment, feature vector is extracted from the random interval of the query audio and it shows overall 80% success rate except extreme cases of beginning and ending portion of the query audio file.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5522-5536
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• 2017

In this paper, a video based smoke detection method using dynamic texture feature extraction with volume local binary patterns is studied. Block based method was used to distinguish smoke frames in high definition videos obtained by experiments firstly. Then we propose a method that directly extracts dynamic texture features based on irregular motion regions to reduce adverse impacts of block size and motion area ratio threshold. Several general volume local binary patterns were used to extract dynamic texture, including LBPTOP, VLBP, CLBPTOP and CVLBP, to study the effect of the number of sample points, frame interval and modes of the operator on smoke detection. Support vector machine was used as the classifier for dynamic texture features. The results show that dynamic texture is a reliable clue for video based smoke detection. It is generally conducive to reducing the false alarm rate by increasing the dimension of the feature vector. However, it does not always contribute to the improvement of the detection rate. Additionally, it is found that the feature computing time is not directly related to the vector dimension in our experiments, which is important for the realization of real-time detection.

• Korean Journal of Computational Design and Engineering
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• v.13 no.6
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• pp.403-411
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• 2008

The alignment of facial images is crucial for 2D face recognition. This is the same to facial meshes for 3D face recognition. Most of the 3D face recognition methods refer to 3D alignment but do not describe their approaches in details. In this paper, we focus on describing an automatic 3D alignment in viewpoint of quantitative analysis. This paper presents a framework of 3D face alignment and normalization based on feature points obtained by Active Shape Models (ASMs). The positions of eyes and mouth can give possibility of aligning the 3D face exactly in three-dimension space. The rotational transform on each axis is defined with respect to the reference position. In aligning process, the rotational transform converts an input 3D faces with large pose variations to the reference frontal view. The part of face is flopped from the aligned face using the sphere region centered at the nose tip of 3D face. The cropped face is shifted and brought into the frame with specified size for normalizing. Subsequently, the interpolation is carried to the face for sampling at equal interval and filling holes. The color interpolation is also carried at the same interval. The outputs are normalized 2D and 3D face which can be used for face recognition. Finally, we carry two sets of experiments to measure aligning errors and evaluate the performance of suggested process.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1011-1020
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• 2004

A lot of work has been done to improve the I/O performance of such a system that store and manage a massive amount of data by distributing them across multiple disks and access them in parallel. Most of the previous work has focused on an efficient mapping from a grid ceil, which is determined bY the interval number of each dimension, to a disk number on the assumption that each dimension is split into disjoint intervals such that entire data space is GRID-like partitioned. However, they have ignored the effects of a GRID partitioning scheme on declustering performance. In this paper, we enhance the performance of mapping function based declustering algorithms by applying a good GRID par-titioning method. For this, we propose an estimation model to count the number of grid cells intersected by a range query and apply a GRID partitioning scheme which minimizes query result size among the possible schemes. While it is common to do binary partition for high-dimensional data, we choose less number of dimensions than needed for binary partition and split several times along that dimensions so that we can reduce the number of grid cells touched by a query. Several experimental results show that the proposed estimation model gives accuracy within 0.5% error ratio regardless of query size and dimension. We can also improve the performance of declustering algorithm based on mapping function, called Kronecker Sequence, which has been known to be the best among the mapping functions for high-dimensional data, up to 23 times by applying an efficient GRID partitioning scheme.

• Journal of dental hygiene science
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• v.15 no.4
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• pp.480-487
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• 2015

The purpose of this study was to examine the association between oral health status and health related quality of life (HRQoL). The study used a nationally representative sample of Koreans (2013 Korea National Health and Nutrition Examination Survey) aged 19~64 years (n=3,252). Dependent variable was HRQoL, which was assessed with each component of EuroQol-5 dimension (EQ5D). Independent variable was oral health status (oral pain, chewing problem, speaking problem, and perceived oral health). After adjustment for confounders (socio-demographic factors, oral health behaviors, health behaviors, and physical conditions), the risk of having poor HRQoL was greater in adults with poor oral health status. The odds ratio (OR) of having pain/discomfort were 1.50 (95% confidence interval [CI], 1.22~1.86) for respondents with oral pain, 1.72 (95% CI, 1.33~ 2.22) for respondents with chewing problem, 1.79 (95% CI, 1.22~2.62) for respondents with speaking problem, and 1.36 (95% CI, 1.09~1.70) for respondents with poor perceived oral health. The OR of having anxiety/depression were 1.74 (95% CI, 1.28~2.38) when having a chewing problem, 1.72 (95% CI, 1.12~2.64) when having a speaking problem, and 1.54 (95% CI, 1.14~2.08) when rating his/her oral health poor. Among Korean adults, two of the EQ5D components were associated with oral health status. Future study is needed to examine the detailed causal relations between oral health status and HRQoL longitudinally.

• Journal of Preventive Medicine and Public Health
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• v.56 no.5
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• pp.467-474
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• 2023

Objectives: Diabetes mellitus (DM) is a serious public health issue that places a heavy financial, social, and health-related burden on individuals, families, and healthcare systems. Self-reported health-related quality of life (HRQoL) is extensively used for monitoring the general population's health conditions and measuring the effectiveness of interventions. Therefore, this study investigated HRQoL and associated factors among patients with type 2 DM at a primary healthcare center in Indonesia. Methods: A cross-sectional study was conducted in Klaten District, Central Java, Indonesia, from May 2019 to July 2019. In total, 260 patients with DM registered with National Health Insurance were interviewed. HRQoL was measured with the EuroQol Group's validated Bahasa Indonesia version of the EuroQoL 5-Dimension 5-Level (EQ-5D-5L) with the Indonesian value set. Multivariate regression models were used to identify factors influencing HRQoL. Results: Data from 24 patients were excluded due to incomplete information. Most participants were men (60.6%), were aged above 50 years (91.5%), had less than a senior high school education (75.0%), and were unemployed (85.6%). The most frequent health problems were reported for the pain/discomfort dimension (64.0%) followed by anxiety (28.4%), mobility (17.8%), usual activities (10.6%), and self-care (6.8%). The average EuroQoL 5-Dimension (EQ-5D) index score was 0.86 (95% confidence interval [CI], 0.83 to 0.88). In the multivariate ordinal regression model, a higher education level (coefficient, 0.08; 95% CI, 0.02 to 0.14) was a significant predictor of the EQ-5D-5L utility score. Conclusions: Patients with diabetes had poorer EQ-5D-5L utility values than the general population. DM patients experienced pain/discomfort and anxiety. There was a substantial positive relationship between education level and HRQoL.

• Journal of the Ergonomics Society of Korea
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• v.20 no.1
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• pp.15-29
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• 2001

This study was conducted to develop a prototype of adjustable desk and chair for students from elementary to high school. The development process started with identifying the problems of existing adjustable desks and chairs that are currently available in the market. The following fundamental design criteria were established and then applied to develop the prototype. The criterion of minimization of production cost yielding lower the market selling price was the most critically considered in view of the school furniture buyers' price-consciousness. Other design criteria used in this development were designing for stable and solid structure, requiring few motions and no tools to adjust, requiring the use of only one hand to adjust, unrestricting the adjustable interval, providing extra space for foot and knee area, reducing weight to move easily, and requiring not to move around for cleaning up floor. To evaluate the performance of the prototype, the adjustability of prototype was specifically compared with both dimensions suggested by KS G 2010(Korean Standards for desks and chairs for students) and current anthropometric dimension in terms of the flexible range of accommodation. Results of this study illustrate that the prototype developed in this study could be accommodated for the both dimensions. As a concluding mark, appropriate adjustable range for various grades and age groups were presented.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.13-20
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• 2014

In this paper, we implemented the object scanning with nxtOSEK which is an open source platform. nxtOSEK consists of device driver of leJOS NXJ C/Assembly source code, TOPPERS/ATK(Automotive real time Kernel) and TOPPERS/JSP Real-Time Operating System source code that includes ARM7 specific porting part, and glue code make them work together. nxtOSEK can provide ANSI C by using GCC tool chain and C API and apply for real-time multi tasking features. We experimented the 3D scanning with ultra sonic and laser sensor which are made directly by laser module diode and experimented the measurement of scanning the object by knowing x, y, and z coordinates for every points that it scans. In this paper, the laser module is the dimension of $6{\times}10[mm]$ requiring 5volts/5[mW], and used the laser light of wavelength in the 650[nm] range. For detecting the object, we used the beacon detection algorithm and as the laser light swept the objects, the photodiode monitored the ambient light at interval of 10[ms] which is called a real time. We communicated the 3D scanning platform via bluetooth protocol with host platform and the results are displayed via DPlot graphic tool. And therefore we enhanced the functionality of the 3D scanner for identifying the image scanning with laser sensor modules compared to ultra sonic sensor.