• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.39 no.2
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• pp.71-76
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• 2013

Objectives: In three-dimensional computed tomography (3D-CT), the cant is evaluated by measuring the distance between the reference plane (or line) and the tooth. The purpose of this study was to determine the horizontal skeletal reference plane that showed the greatest correlation with clinical evaluation. Materials and Methods: The subjects were 15 patients who closed their eyes during the CT image taking process. The menton points of all patients deviated by more than 3 mm. In the first evaluation, clinical cant was measured. The distance from the inner canthus to the ipsilateral canine tip and the distance from the eyelid to the ipsilateral first molar were obtained. The distance between the left and right sides was also measured. In the second evaluation, skeletal cant was measured. Six reference planes and one line were used for the evaluation of occlusal cant: 1) FH plane R: Or.R - Or.L - Po.R; 2) FH plane L: Or.R - Or.L - Po.L; 3) F. Ovale plane R: Rt.F.Ovale - Lt.F.Ovale - Or.R; 4) F. Ovale plane L: Rt.F.Ovale - Lt.F.Ovale - Or.L; 5) FZS plane R: Rt.FZS - Lt.FZS - Po.R; 6) FZS plane R: Rt.FZS - Lt.FZS - Po.L, and; 7) FZS line: Rt.FZS - Lt.FZS. Results: The clinical and skeletal cants were compared using linear regression analysis. The FH plane R, FH plane L, and FZS line showed the highest correlation (P<0.05). Conclusion: The FH plane R and FH plane L are the most appropriate horizontal reference plane in evaluation of occlusal cant on 3D-CT.

• Journal of Korean Society of Rural Planning
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• v.9 no.1 s.18
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• pp.65-75
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• 2003

As a pre-step research to make land-use planning in the region level, this study aims to analyze some probability pattern representing transition probabilities from farmland to others using the sequential detailed digital land-use maps. Kinki and Chubu regions of Japan, which have Osaka and Nagoya cities as their center places respectively, were selected as test regions in this study. The 10m grid land-use maps for four time series at every 5 year from 1977 to 1992 were used. In this study, the regions were divided into three sub-areas 10km, 20km, and 30km according to distance from center cities, respectively. The correlation coefficient (CC) between sub-areas with same distance in the two regions was calculated to analyze whether or not the two regions have common points in the pattern of land-use conversion probability from farmland to other types. The probability distribution of the converted areas which were moved to the urbanized area (residential, commercial, industrial, road, park and public facility areas) was about $40{\sim}70%$ for both all periods and sub-areas. According to distance from city centers, the probability moved to the urbanized area was about 60% at 10km area, and 40% at the 30km area, which means that the values we decreased gradually, while in the case moved to the forest and the etc areas, the values were increased slightly. The CC analysis from the paddy field and the dry field to the others separately showed that there is high correlation in the probability pattern between the two regions.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.939-948
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• 2004

In this paper. we Propose a robust and fast image registration technique for motion correction in brain CT-CT angiography obtained from same patient to be taken at different time. First, the feature points of two images are respectively extracted by 3D edge detection technique, and they are converted to locally weighted 3D distance map in reference image. Second, we search the optimal location whore the cross-correlation of two edges is maximized while floating image is transformed rigidly to reference image. This optimal location is determined when the maximum value of cross-correlation does't change any more and iterates over constant number. Finally, two images are registered at optimal location by transforming floating image. In the experiment, we evaluate an accuracy and robustness using artificial image and give a visual inspection using clinical brain CT-CT angiography dataset. Our proposed method shows that two images can be registered at optimal location without converging at local maximum location robustly and rapidly by using locally weighted 3D distance map, even though we use a few number of feature points in those images.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.967-973
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• 2021

In 2011, an earthquake and subsequent tsunami hit the Fukushima Daiichi Nuclear Power Plant, causing simultaneous accidents in several reactors. This accident shows us that if there are several reactors on site, the seismic risk to multiple units is important to consider, in addition to that to single units in isolation. When a seismic event occurs, a seismic-failure correlation exists between the nuclear power plant's structures, systems, and components (SSCs) due to their seismic-response and seismic-capacity correlations. Therefore, it is necessary to evaluate the multi-unit seismic risk by considering the SSCs' seismic-failure-correlation effect. In this study, a methodology is proposed to obtain the seismic-response-correlation coefficient between SSCs to calculate the risk to multi-unit facilities. This coefficient is calculated from a probabilistic multi-unit seismic-response analysis. The seismic-response and seismic-failure-correlation coefficients of the emergency diesel generators installed within the units are successfully derived via the proposed method. In addition, the distribution of the seismic-response-correlation coefficient was observed as a function of the distance between SSCs of various dynamic characteristics. It is demonstrated that the proposed methodology can reasonably derive the seismic-response-correlation coefficient between SSCs, which is the input data for multi-unit seismic probabilistic safety assessment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.318-321
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• 2007

Since human listening is very sensitive to sound, a subjective index of a sound quality is required. Therefore, in the analysis for each situation, the sound evaluation is composed with sound quality factor. Many researchers spends their effort to make a more reliable and more accurate of sound in term of sound quality index for various system noise. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are so depended on jury test very much that they result in many difficulties. So, to reduce jury test weight, we suggested a new method using Mahalanobis distance for SQ evaluation. Threrefore, in this study Mahalanobis distance for the vehicle interior noise was derived using the objective SQ except jury test. Finnaly, the results of the SQ evaluation was analyzed discrimination between reference and abnormal group.

• Journal of Environmental Impact Assessment
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• v.21 no.2
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• pp.289-296
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• 2012

The shock vibration such as machine vibration, blasting vibration etc. has effect on nearby structure as well as human body. The purpose of this study is to predict allowable limit distance of vibration about human body. First of all, vibration velocity such as PPV, PVS was measured by shock vibration experiment, and vibration level was calculated by conversion formula of vibration velocity. And then, allowable limit distance was analyzed by converted vibration level. The results are as follows : Firstly, the correlation coefficient of converted vibration level was over R=0.94, and vibration level caused by PVS was usually represented to high curve line. Secondly, the cross point of vibration level between ground and concrete condition was represented to 66.68dB(V), and allowable limit distance was represented to difference over three times when vibration regulation was raised from 65dB(V) to 80dB(V).

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.1
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• pp.57-60
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• 2008

Since human listening is very sensitive to sound, for evaluating of a sound quality is required. Therefore, in the analysis for each situation, the sound evaluation is composed with sound quality factor. My researchers spends their effort to make a more reliable and more accurate of sound in term of sound quality index for various system noise. The previous methods to evaluation of the SQ about vehicle interior noise are linear regression analysis of subjective SQ metrics by statistics and the estimation of the subjective SQ values by neural network. But these are highly dependent on jury test and have many difficulties due to various environmental factors. So, to reduce jury test weight. we suggested a new method using Mahalanobis distance for SQ evaluation. Threrefore, in this study Mahalanobis distance for the vehicle interior noise was derived using the objective SQ except jury test. Finnaly, the results of the SQ evaluation was analyzed discrimination between reference and abnormal group.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.250-255
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• 2012

Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.219-230
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• 2021

International seismic codes stipulate that adjacent buildings should be separated by a specified minimum distance, otherwise the pounding effect should be considered in the design. Recent researches proposed an alternative method (Double Difference Combination Rule) to estimate seismic gap between structures, as this method considers the cross relation of adjacent buildings behavior during earthquakes. Four different criteria were used to calculate the minimum separation distance using this method and results are compared to the international codes for five separation cases. These cases used four case study buildings classified by different heights, lateral load resisting systems and fundamental periods of vibrations to assess the consistency in results for the alternative methods. Non-linear analysis was performed to calculate the inelastic displacements of the four buildings, and the results were used to evaluate the relation between elastic and inelastic displacements due to the ductility of structural elements resisting seismic loads. A verification analysis was conducted to guarantee that the separation distance calculated is sufficient to avoid pounding. Results shows that the use of two out of the four studied methods yields separation distances smaller than that calculated by the code specified equations without under-estimating the minimum separation distance required to avoid pounding.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.369-380
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• 2004

Clustering algorithms with different similarity measures are commonly used to find an optimal clustering or close to original clustering. The recovery level of using Euclidean distance and distances transformed from correlation coefficients is evaluated and compared using Rand's (1971) C statistic. The C values present how the resultant clustering is close to the original clustering. In simulation study, the recovery level is improved by applying the correlation coefficients between objects. Using the data set from Spellman et al. (1998), the recovery levels with different similarity measures are also presented. In general, the recovery level of true clusters was increased by using the correlation coefficients.