• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.518-523
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• 2001

This paper proposes the new method which is adopted in extracting character features and recognizing characters using fractal dimension of the Chaos theory which highly recolonizes a minute difference with strange attractor created from Henon system. This paper implements a high precision character recognition system. firstly, it gets features of mesh, projection and cross distance feature from character images. And their feature is converted into data of time series. Then using modified Henon system suggested in this paper, each characters attractor about standard Korean Character, KSC 5601 is reconstructed. Secondly, in order to analyze the Chaotic degree of each characters attractor, it gets last features of character image after calculating box-counting Dimension, Natural Measure, Information Bit, Information Dimension which are meant fractal dimension. An experimental result shows 97.49% character classification rates for 2350 Korean characters using proposed method in this paper.

• Current Optics and Photonics
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• v.2 no.1
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• pp.69-78
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• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.74-75
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• 2008

This work has suggested corrugation beam as a new structure for mechanical resonators. Micro beam resonators based on 3C-SiC films which have two side corrugations along the length of beams were simulated by finite-element modeling and compared to a flat rectangular beam with the same dimension. With the dimension of $36\times12\times0.5{\mu}m^3$, the flat cantilever has resonant frequency of 746 kHz. Meanwhile, this frequency reaches 1.252 MHz with the corrugated cantilever which has the same dimension with flat type but corrugation width of $6{\mu}m$ and depth of $0.4{\mu}m$. It is expected that mechanical resonators with corrugations will be very helpful for the research of sensing devices with high-resolution, high-performance oscillators and filters in wireless communications as well as measurement in basic physics.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.454-462
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• 2014

Retention of possible churning customer is one of the most important issues in customer relationship management, so companies try to predict churn customers using their large-scale high-dimensional data. This study focuses on dealing with large data sets by reducing the dimensionality. By using six different dimension reduction methods-Principal Component Analysis (PCA), factor analysis (FA), locally linear embedding (LLE), local tangent space alignment (LTSA), locally preserving projections (LPP), and deep auto-encoder-our experiments apply each dimension reduction method to the training data, build a classification model using the mapped data and then measure the performance using hit rate to compare the dimension reduction methods. In the result, PCA shows good performance despite its simplicity, and the deep auto-encoder gives the best overall performance. These results can be explained by the characteristics of the churn prediction data that is highly correlated and overlapped over the classes. We also proposed a simple out-of-sample extension method for the nonlinear dimension reduction methods, LLE and LTSA, utilizing the characteristic of the data.

• Structural Engineering and Mechanics
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• v.41 no.5
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• pp.663-673
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• 2012

A number of mode shape-based structure damage identification methods have been verified by numerical simulations or experiments for on-line structure health monitoring (SHM). However, many of them need a baseline mode shape generated by the healthy structure serving as a reference to identify damages. Otherwise these methods can hardly perform well when multiple cracks conditions occur. So it is important to solve the problems above. By aid of the fractal dimension method (FD), Qiao and Wang proposed a generalized fractal dimension (GFD) to detect the delamination damage. As a modification of GFD, Qiao and Cao proposed the approximate waveform capacity dimension (AWCD) technique to simplify the calculation of fractal and overcome the false peak appearing in the high mode shapes. Based on their valued work, this paper combined and applied the AWCD method and curvature mode shape data to detect multiple damages in beam. In the end, the identification properties of the AWCD for multiple damages have been verified by groups of Monte Carlo simulations and experiments.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2099-2106
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• 2018

This study presents a novel approach of discriminative feature vectors based on manifold learning using nonlinear dimension reduction (DR) technique to improve loss function, and combine with the Adversarial examples to regularize the object function for image classification. The traditional convolutional neural networks (CNN) with many new regularization approach has been successfully used for image classification tasks, and it achieved good results, hence it costs a lot of Calculated spacing and timing. Significantly, distrinct from traditional CNN, we discriminate the feature vectors for objects without empirically-tuned parameter, these Discriminative features intend to remain the lower-dimensional relationship corresponding high-dimension manifold after projecting the image feature vectors from high-dimension to lower-dimension, and we optimize the constrains of the preserving local features based on manifold, which narrow the mapped feature information from the same class and push different class away. Using Adversarial examples, improved loss function with additional regularization term intends to boost the Robustness and generalization of neural network. experimental results indicate that the approach based on discriminative feature of manifold learning is not only valid, but also more efficient in image classification tasks. Furthermore, the proposed approach achieves competitive classification performances for three benchmark datasets : MNIST, CIFAR-10, SVHN.

• Progress in Superconductivity and Cryogenics
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• v.4 no.2
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• pp.11-15
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• 2002

High speed probe for measurement of sin91e flux quantum circuits is comprised of coaxial cables and microstrip lines in order to carry high speed signals without loss. For the impedance matching between coaxial cable and microstrip line, we have determined the dimension of the microstrip line with 50${\Omega}$ impedance by simulation and then have investigated the effect of line width and cross-sectional shape of signal line, dielectric material, thickness of soldering lead at the coaxial-to-microstrip transition Point, and the an91c between dielectric material and end part of the signal line on the characteristics of signal transmission of the microstrip line. From the simulation, we have found that these all parameter's had influenced on the characteristic of signal transmission on the microstrip line and should be reflected in fabricating high speed probe, We have also determined the dimension of coplanar waveguide to fabricate testing sample for performance test of high speed probe.

• Journal of the Korean Home Economics Association
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• v.28 no.3
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• pp.13-24
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• 1990

The main purpose of this study are as follows ; 1) To examine closely the effect of personality dimension on brand image. 2) To investigate the difference of variables about brand image according to the characteristics of the population statistics and draw the strategies of marketing for our wear enterprises. A 300 Samples were selected from female in Seoul and the investigation was conducted during 21 days, from 1998. 9. 21 to 1988. 10. 11. As for survey methozs, the personality dimension test developed by Eysenk was adopted. To measure the brand image, the adjectives of the semantic differentia scale developed by Malhotra and adjective that has been used in various were image analysis were adopted. The data were analysed using the statistical technic of Correlation Coefficient, F-test, and X2 test. The Results obtained from this study were as follows. 1. There were partially significant relationships between adult female's four subordinate variables of the personality dimension and preferred brand image on Women's ready-made wear. 1) The people having a high Psychoticism tendency preferred "individual" image and less preferred "practical" image than the people of low Psychoticism. 2) The people having a high extraversion tendency preferred "bold", "aged" image and less preferred "feminine", "practical" image. 3) The unstable female having a high neuroticism tendency preferred "abscure" image and less preferred "Practical" "gaudy", "Open hearted" image. 4) The people having a high lie tendency perferred "intricate", "classical" image and less preferred "bold", "citified", "incongruous" image. 2. There were partially significant differences in adult female's preferred brand image on women's ready made wear according to the characteristics of the population statistics.

• The Journal of Natural Sciences
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• v.4
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• pp.191-220
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• 1991

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The fractal dimension is used to measure the roughness of the textural regions. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. For the boundaries, a binary image representing all the boundaries is created. For regions belonging to perceived constant intensity, only the mean intensity values need to be transmitted. The smooth and rough texture regions are modeled first using polynomial functions, so only the coefficients characterizing the polynomial functions need to be transmitted. The bounda-ries, the means and the polynomial functions are then each encoded using an errorless coding scheme. Good quality reconstructed images are obtained with about 0.08 to 0.3 bit per pixel for three different types of imagery ; a head and shoulder image with little texture variation, a complex image with many edges, and a natural outdoor image with highly textured areas.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10a
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• pp.34-38
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• 2003

In metal working, cold forging that has profit to satisfy dimension accuracy is using in various manufacturing products. Recently, most of the interest thing is precision forging of gear. Gear forging product is more strength than broaching gear, and it has many advantages with reduction of factory expenses. The reason of difficulty to improve accuracy of gear dimension compare to another products is the dimension accuracy is very high, approximately 10$\mu\textrm{m}$, and because die of involute teeth and elastic strain of forged tool differ from standard curve. This paper represent quantitative analysis of die and teeth of forged tool, namely difference of curves, with experiments and analyze the factor of dimension gap, finally, will design compensated involute curve.