• Journal of Power System Engineering
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• v.7 no.2
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• pp.29-35
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• 2003

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a classification method of diagnosing the small reciprocating compressor for refrigerators using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them ate compared with each other. This paper is focused on the development of an advanced signal classifier to automatize the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• Tunnel and Underground Space
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• v.21 no.4
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• pp.251-263
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• 2011

The geomechanical characteristics of rock and the structural geological feature of the fault should be studied and examined for the successful construction of large-span tunnel. In this case study, that is a important case for the tunnel collapse and reinforcement during the construction for the waterway tunnel at large thrust fault zone in schist, we carried out geological and geotechnical survey for make the cause and mechanism of tunnel collapse. Also, we have designed the reinforcement and re-excavation for the safe construction for collapse zone and have carried out successfully the re-excavation and finished the final concrete lining.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.449-457
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• 2011

As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.135-139
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• 2009

We present a new ensemble learning method that employs the set of region experts, each of which learns to handle a subset of the training data. We split the training data and generate experts for different regions in the feature space. When classifying a data, we apply a weighted voting among the experts that include the data in their region. We used ten datasets to compare the performance of our new ensemble method with that of single classifiers as well as other ensemble methods such as Bagging and Adaboost. We used SMO, Naive Bayes and C4.5 as base learning algorithms. As a result, we found that the performance of our method is comparable to that of Adaboost and Bagging when the base learner is C4.5. In the remaining cases, our method outperformed the benchmark methods.

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.325-344
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• 2017

The present paper investigates the propagation of Love-type wave in a composite structure comprised of imperfectly bonded piezoelectric layer with lower fiber-reinforced half-space with rectangular shaped irregularity at the common interface. Closed-form expression of phase velocity of Love-type wave propagating in the composite structure has been deduced analytically for electrically open and short conditions. Some special cases of the problem have also been studied. It has been found that the obtained results are in well-agreement to the Classical Love wave equation. Significant effects of various parameters viz. irregularity parameter, flexibility imperfectness parameter and viscoelastic imperfectness parameter associated with complex common interface, dielectric constant and piezoelectric coefficient on phase velocity of Love-type wave has been reported. Numerical computations and graphical illustrations have been carried out to demonstrate the deduced results for various cases. Moreover, comparative study has been performed to unravel the effects of the presence of reinforcement and piezoelectricity in the composite structure and also to analyze the existence of irregularity and imperfectness at the common interface of composite structure in context of the present problem which serves as a salient feature of the present study.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.55-66
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• 2013

In these days, small devices like smartphones, TV, and projectors are popular, and they are being developed rapidly. The projector is being used in cinema and exhibition because it makes a big screen. This feature makes new expression named projection-mapping in art world. Projection-mapping is being utilized extensively in stages of performances, and it use variety of shape's screens. But projection-mapping has limitation in space. So in this paper, we propose new performance system for projection-mapping and it make possible to overcome many difficulties. Also, we discuss the result of using the system in actual performance. We hope to develop the utilization of projection-mapping in performance.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1024-1033
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• 2016

In this study, a system is proposed for analyzing whether driver's eyes are open or closed on the basis of images to determine driver's drowsiness. The proposed system converts eye areas detected by a camera to a color space area to effectively detect eyes in a dark situation, for example, tunnels, and a bright situation due to a backlight. In addition, the system used a thickness distribution of a detected eye area as a feature value to analyze whether eyes are open or closed through the Support Vector Machine(SVM), representing 90.09% of accuracy. In the experiment for the images of driver wearing glasses, 83.83% of accuracy was obtained. In addition, in a comparative experiment with the existing PCA method by using Eigen-eye and Pupil Measuring System the detection rate is shown improved. After the experiment, driver's drowsiness was identified accurately by using the method of summing up the state of driver's eyes open and closes over time and the method of detecting driver's eyes that continue to be closed to examine drowsy driving.

• Journal of Korean Neurosurgical Society
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• v.52 no.1
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• pp.48-51
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• 2012

Intravascular papillary endothelial hyperplasia (IPEH) is a rare vascular benign lesion that rarely involves the central nervous system with or without skull invasion. We report a rare case of IPEH on the skull bone, which displayed destructive radiologic development associated with hemorrhage. A 14-year-old male presented with an incidentally detected a small enhancing, left frontal osteolytic lesion. Previously, he underwent operation and received adjuvant chemoradiation therapy for cerebellar medulloblastoma. Follow-up magnetic resonance imaging revealed a left frontal bone lesion, which expanded to an approximately 2 cm-sized well-circumscribed osteolytic lesion associated with hemorrhage for 20 months. Frontal craniectomy and cranioplasty were performed. Destructive change was detected on the inner table and diploic space of the skull. The mass had a cystic feature with hemorrhagic content without dural attachment. Pathologic examination showed the capsule consisted of parallel collagen lamellae representing a vascular wall, vascular lumen, which was pathognomonic for IPEH. Immunohistochemical staining revealed that the capsule was positive for CD34 and factor VIII, which favor the final diagnosis of IPEH. This was the first case of intracalvarial IPEH.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.499-507
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• 2006

Recently human gait has been considered as a useful biometric supporting high performance human identification systems. This paper proposes a view-based pedestrian identification method using the dynamic silhouettes of a human body modeled with the Hidden Markov Model(HMM). Two types of gait models have been developed both with an endless cycle architecture: one is a discrete HMM method using a self-organizing map-based VQ codebook and the other is a continuous HMM method using feature vectors transformed into a PCA space. Experimental results showed a consistent performance trend over a range of model parameters and the recognition rate up to 88.1%. Compared with other methods, the proposed models and techniques are believed to have a sufficient potential for a successful application to gait recognition.