• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.11a
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• pp.289-297
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• 2000

The determination of surface topography is believed to be extremely important in the areas of contact mechanics, adhesion and friction. In order to describe topography of various frictional surface, the harding test was carried out under different experimental conditions in try friction. And fractal descriptors was applied to frictional surface of laser modified steel with image processing system These descriptors to analyze surface structure are fractal dimension. Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Topography of frictional surface can be effectively obtained by fractal dimensions.

• Computers and Concrete
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• v.26 no.6
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• pp.505-513
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• 2020

Grading of aggregate influences significantly almost all of the concrete performances. The purpose of this paper is to propose practicable equations that express the optimized total aggregate gradation, by weight or by number of particles in a concrete mix. The principle is based on the fractal feature of the grading of combined aggregate in a solid skeleton of concrete. Therefore, equations are derived based on the so-called fractal dimension of the grain size distribution of aggregates. Obtained model was then applied in such a way a correlation between some properties of the dry concrete mix and the fractal dimension of the aggregate gradation has been built. This demonstrates that the parameter fractal dimension is an efficacious tool to establish a unified model to study the solid phase of concrete in order to design aggregate gradation to meet certain requirements or even to predict some characteristics of the dry concrete mixture.

• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.675-685
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• 2020

As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.435-448
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• 2008

3D posture recognition is a solution to overcome the limitation of 2D posture recognition. There are many researches carried out for 3D posture recognition using 3D data. The 3D data consist of massive surface points which are rich of information. However, it is difficult to extract the important features for posture recognition purpose. Meanwhile, it also consumes lots of processing time. In this paper, we introduced a dimension reduction method that transform 3D surface points of an object to 2D data representation in order to overcome the issues of feature extraction and time complexity of 3D posture recognition. For a better feature extraction and matching process, a cylindrical boundary is introduced in meshless parameterization, its offer a fast processing speed of dimension reduction process and the output result is applicable for recognition purpose. The proposed approach is applied to hand and human posture recognition in order to verify the efficiency of the feature extraction.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.305-314
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• 2016

In this study, an analysis is performed for comparing the fractal dimension of Jackson Pollock's art works with that of Korean Infomel art works. In order to test the hypothesis that Jackson Pollock's fractal dimension is different from Korean Informel's, data is collected for the fractal dimensions of 30 Jackson Pollock's and 45 Korean Informel art works. The results show that Korean Informel's fractal dimension is larger than Jackson Pollock's. This might be interpreted that the pattern (in finer scale) of Korean Informel art works is closer to planes, rather than lines or points, compared to that of Jackson Pollock's.

• The Journal of Korean Academy of Prosthodontics
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• v.56 no.1
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• pp.56-63
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• 2018

Severe dental attrition causes pathological changes of the tooth, collapsed occlusion, and functional and aesthetic complications and can also result in a decrease in occlusal vertical dimension. Before increasing the vertical dimension with full-mouth rehabilitation, it is important to determine the amount of vertical dimension through accurate diagnosis. In this case, a 77 year old elderly male patient on anticoagulant medication with generalized attrition and fracture of teeth was treated with full-mouth rehabilitation in order to recover vertical dimension and aesthetics. Accurate clinical and radiographic examination, diagnostic, wax-up, and occlusal vertical dimension evaluation were step by step performed considering pre-medical history and old age. Patient adaptability was evaluated using an occlusal splint and interim restoration. After 3 months of stabilization with interim restoration, definitive prostheses were fabricated. Satisfactory functional and esthetic outcomes are observed after 6 months of follow up.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.4
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• pp.30-37
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• 1999

This study suggested the Fuzzy Lyapunov dimension. The Fuzzy Lyapunov dimension is to evaluate the quantitative variation of the attractor. In this paper the speaker recognition is evaluated by the Fuzzy Lyapunov dimension. It has been proved that the suggested Fuzzy Lyapunov dimension is superior in the discrimination characteristics between standard reference pattern attractors, and in reference to the test pattern attractor, it has been verified that it is the speaker recognition parameter which absorbs the pattern variation. In order to evaluate the Fuzzy Lyapunov dimension as speaker recognition parameter, the mistaken recognition according to discrimination error in each of speaker and standard reference pattern was estimated, and the validity of the speaker recognition parameter was experimental. As the result of the speaker recognition experiment, 97.0[%] of recognition ratio was obtained, and it was confirmed that the Fuzzy Lyapunov dimension was fit for the speaker recognition parameter.

• Journal of Preventive Medicine and Public Health
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• v.15 no.1
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• pp.219-228
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• 1982

This study aimed at assessing the industrial workers' mental health status and identifing the relationship between mental health status and socio-demographic variables. We administered psychiatric self report rating scale (SCL-90)to 622 manual workers and 191 office workers in a textile .industry. The study began on 1 November, 1981 and lasted for 30 days The results were as follow: 1. Scores of symptom dimension were higher in female rather than male, younger than older, lower income group than higher one, lower educated group than higher one, manual workers than office workers and unmarried group than married one respectively. 2. The result of dimension scores of total samples showed that the score of Obsessive-compulsive scale was highest. The rest symptom dimension showed the order as follows: Interpersonal sensitivity, Depression, Hostility, Anxiety, Paranoid ideation, Somatization, Psychoticism and Phobic anxiety. 3. In order to identify the partial contribution of each socio-demographic variables on the mental health, multiple regression method was applied, and the result was as follows. 1) Sex was the most important one to explain the Somatization, Phobic-anxiety and Psychoticism scales among the 7 variables in the multiple regression equation. 2) Economic status was the most important variable to explein the Obsessive-compulsive, Depression and Hostility scales. 3) Marital status was the most important variable to explain the Interpersonal-sensitivity and Paranoid ideation scales.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.409-420
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• 2020

Purpose: The purpose of this study is to develop a measurement scale for evaluating the auditory affect of automobile engine sounds. Methods: In order to collect affective vocabulary, literature review, user tests, and expert interviews were conducted. Affective vocabulary related to automobile engine sounds was selected through three methods. To develop the evaluation scale, open/close card-sorting and expert interview-based survey method was used. Results: The results of this study are as follows; In order to select the main affective vocabulary from the collected vocabulary, 39 vocabularies with a frequency of 5 or higher were selected as vocabulary expressing the main auditory affect of automobile engine sounds. Each affective vocabulary is divided into three di- mensions, it was confirmed that the conceptual model for the auditory affect of automobile engine sounds is composed of three levels: intuitive, descriptive, and evaluative of hierarchical structure. As a result of the study, four indices of intuitive dimension, seven indices of descriptive dimension, and one index of evaluative dimension were derived from the evaluation scale of the auditory affect in an automobile engine sound. Conclusion: The auditory evaluation scale developed in this study can be used to systematically measure and evaluate the auditory affect of automobile engine sounds.