• Korean Journal of Adult Nursing
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• v.19 no.1
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• pp.155-165
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• 2007

Purpose: The purpose of this study was to determine the relationships of pain cognition, performance status, and hope with health-related quality of life. Methods: Patients(n=149) with various cancer diagnoses completed the SF-36 standard Korean Version and the Herth Hope Index. The Perceived Meanings of Cancer Pain Inventory was used to measure the cognition dimension of pain, whereas the Brief Pain Inventory Korean version was used to represent the sensory dimension of pain. Results: The patients in the pain group had significant differences in the three dimensions(loss, threat, spiritual awareness) of pain cognition. There were statistically significant negative correlations between the three dimensions(loss, threat, and spiritual awareness) of pain cognitions and SF-36 dimension, and the positive correlations between challenge dimension and SF-36 dimension. Hope had the positive correlation with SF-36 dimensions. Conclusion: Pain has a negative impact on health-related quality of life, especially on physical health. However, patients who ascribed more positive meaning to their pain, tended to have a higher quality of life. Therefore, nursing intervention to reinforce the positive aspects of pain cognition is to empower patients to create a sense of control and assume an active role in pain management and quality of life.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.817-824
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• 2010

Linear Discriminant Analysis (LDA) has been successfully applied for dimension reduction in face recognition. However, LDA requires the transformation of a face image to a one-dimensional vector and this process can cause the correlation information among neighboring pixels to be disregarded. On the other hand, 2D-LDA uses 2D images directly without a transformation process and it has been shown to be superior to the traditional LDA. Nevertheless, there are some problems in 2D-LDA. First, it is difficult to determine the optimal number of feature vectors in a reduced dimensional space. Second, the size of rectangular windows used in 2D-LDA makes strong impacts on classification accuracies but there is no reliable way to determine an optimal window size. In this paper, we propose a new algorithm to overcome those problems in 2D-LDA. We adopt an ensemble approach which combines several classifiers obtained by utilizing various window sizes. And a practical method to determine the number of feature vectors is also presented. Experimental results demonstrate that the proposed method can overcome the difficulties with choosing an optimal window size and the number of feature vectors.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.548-553
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• 2010

This paper presents an effective shape image recognition method using the correlation based on 4-dimensional histogram. The histogram-based correlation is accurately applied to express the similarity by comparing the positions of a corresponding dimension between the images, which is calculated by considering 4 directions of the shape image. The correlation measure by using the normalized cross-correlation is also applied to obtain the robust recognition to the geometrical variations such as shape, position, size, and rotation. The proposed method has been applied to the problem for recognizing the 8 shape images of 64*64 pixels and the 30 shape images of 256*256 pixels. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.226-235
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• 1998

This study proposes the analysis and evaluation of method of time series of ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. The features are extracted from time series data for analysis of weld defects quantitatively. For this purpose, analysis objectives in this study are fractal dimension, Lyapunov exponent, and strange attractor on hyperspace. The Lyapunov exponent is a measure of rate in which phase space diverges nearby trajectories. Chaotic trajectories have at least one positive Lyapunov exponent, and the fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal(correlation) dimensions and Lyapunov exponents show the mean value of 4.663, and 0.093 relatively in case of learning, while the mean value of 4.926, and 0.090 in case of testing in slag inclusion(weld defects) are shown. Therefore, the proposed chaotic feature extraction can be enhancement of precision rate for ultrasonic pattern recognition in defecting signals of weld zone, such as slag inclusion.

• Environmental Engineering Research
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• v.23 no.4
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• pp.442-448
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• 2018

This paper presents the numerical simulation of advection-diffusion mechanism of BOD concentration which was used as an indicator of waste only in one flow-direction of waste stabilization ponds (1-dimension (1-D)). This model was represented in partial differential equation order 2. The purpose of this paper was to determine the simulation of the model 1-D of wastewater transport phenomena based advection-diffusion mechanism and did validate the model. Numerical methods which was used for the solution of this model is finite difference method with Forward Time Central Space scheme. The simulation results which was obtained would be compared with field observation data as a validation model. Collection of field data was carried out in the Wastewater Treatment Plant Sewon, Bantul, D.I. Yogyakarta. The results of numerical simulations were indicate that the advection-diffusion mechanism takes place continuously over time. Then validation of the model was state that there was a difference between the calculation results with the field data, with a correlation value of 0.998.

• The korean journal of orthodontics
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• v.45 no.2
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• pp.59-65
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• 2015

Objective: To investigate skeletal and dental changes after application of a mandibular setback surgery-first orthodontic treatment approach in cases of skeletal Class III malocclusion. Methods: A retrospective study of 34 patients (23 men, 11 women; mean age, $26.2{\pm}6.6years$) with skeletal Class III deformities, who underwent surgery-first orthodontic treatment, was conducted. Skeletal landmarks in the maxilla and mandible at three time points, pre-treatment (T0), immediate-postoperative (T1), and post-treatment (T2), were analyzed using cone-beam computed tomography (CBCT)-generated half-cephalograms. Results: The significant T0 to T1 mandibular changes occurred $-9.24{\pm}3.97mm$ horizontally. From T1 to T2, the mandible tended to move forward $1.22{\pm}2.02mm$, while the condylar position (Cd to Po-perpendicular plane) shifted backward, and the coronoid process (Cp to FH plane) moved vertically. Between T1 and T2, the vertical dimension changed significantly (p < 0.05). Changes in the vertical dimension were significantly correlated to T1 to T2 changes in the Cd to Po-perpendicular plane (r = -0.671, p = 0.034), and in the Cp to FH plane (r = 0.733, p = 0.016), as well as to T0 to T1 changes in the Cp to Po-perpendicular plane (r = 0.758, p = 0.011). Conclusions: Greater alterations in the vertical dimension caused larger post-treatment (T2) stage skeletal changes. Studying the mandibular position in relation to the post-surgical vertical dimension emphasized the integral importance of vertical dimension control and proximal segment management to the success of surgery-first orthodontic treatment.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.24-36
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• 2015

The Geochang granite widely used in construction works is one of the most popular dimension stones in Korea. In order to evaluate the physical properties of rock, a lot of laboratory tests for the Geochang granite were conducted to find unit weight, absorption ratio, P wave velocity, S wave velocity, uniaxial compressive strength, Young's modulus, Poisson's ratio, tensile strength, cohesion, friction angle and point load strength index. The uniaxial compressive strength of the Geochang granite was 19.5 times tensile strength and also 8.6 times cohesion, besides P wave velocity was 1.5 times S wave velocity. Correlation analyses were also conducted to find the correlation among 11 different physical properties, where the uniaxial compressive strength showed Pearson correlation coefficient of more than 0.8 with Poisson's ratio, point load strength index and Young's modulus, respectively. Regression analyses were finally conducted by means of both linear and multiple analysis and the brief results including coefficient of determination of more than 0.7 were presented.

• Journal of the Korean Home Economics Association
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• v.42 no.8
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• pp.123-132
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• 2004

The purpose of this research was to determine the relation between clothing evaluative criteria and personality types. Primary factor analysis was used to classify the clothing evaluative criteria and the continual scores of Myers Briggs Type Indicator (MBTI) were used for classifying the personality types. Correlation analysis and multiple regression analysis were used to determine the relation between the clothing evaluative criteria and the personality types. The data for this research were collected from questionnaires of 309 female university students in Seoul. In the results, the clothing evaluative criteria were grouped into 4 underlying dimensions： practical, situational, appearance producible and symbolic. Partially significant relations between the 4 clothing evaluative criteria and the 4 indicators of MBTI personality types were found through correlation analysis. Multiple regression analysis revealed that the variables explaining the dimension of Sensing and Intuition (SN) were appearance producible and symbolic clothing evaluative criteria; the appearance producible criterion had an inclination toward Intuition while the symbolic criterion had an inclination toward Sensing. The variable explaining the dimension of Judging and Perceiving (JP) was situational clothing evaluative criterion, which had an inclination toward Judging.

• Annals of Clinical Neurophysiology
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• v.4 no.1
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• pp.21-27
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• 2002

Background : Spatial analysis of EEG is a phenomenal assessment and not so informative for phase space and dynamic aspect of EEG data. In contrast, nonlinear EEG analysis attempts to characterize the dynamics of neural networks in the brain. We have analyzed the features of EEG nonlinearly in subjects with white matter change on brain MRI and compared the results with cognitive function in each. Methods : Digital EEG data were taken for 30 seconds in 9 subjects with white matter degeneration and in 5 healthy normal controls without white matter change on MRI. Then we analyzed them nonlinearly to calculate the correlation dimension(D2) using the MATLAB software. The cognitive function was assessed by 3MS(modified mini-mental state examination). The severity of white matter change was assessed by Scheltens scale. Results : The mean D2 value of normal control was greater than that of white matter degeneration group. The D2s of some channels were correlative with 3MS and degree of white matter degeneration significantly. Conclusions : nonlinear analysis of EEG can be used as one of adjuvant functional studies for prediction of cognitive impairment in subjects with white matter degeneration and subcortical white matter change can be influential on cognitive function and correlation dimension of EEG.

• Journal of Integrative Natural Science
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• v.5 no.2
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• pp.120-126
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• 2012

This paper describes the algorithm that lowers the dimension, maintains the gesture recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.