• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.47-54
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• 2005

One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.

• Journal of Chest Surgery
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• v.7 no.2
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• pp.189-200
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• 1974

The mitral valve replacement with Beall prosthetic valve was performed on three patients, and double valve replacement. aortic and mitral valve, was performed in this department.1) The preoperative studies about the first case were compatible with mitral steno-insufficency.The diseased mitral valve was replaced with the medium sized Beall prosthetic valve under the cardiopulmonary hypass using hypothermic hemodilution technique. The total perfusion time was eighty minutes. Immediate postoperative course was smooth, but this patient was died of asphyxia due to tracheomalacia complicated after tracheostomy 3 months after operation. Autopsy on this patient revealed that no thrombus and no ball variance could be found, and endothelization on the valve cuff was satisfactory. 2) The preoperative studies on the second case were compatible with mitral insufficiency. The diseased mitral valve was replaced with the medium sized Beall prosthetic valve under the cardiopulmonary bypass using hypothermic hemodilution technigue. The total perfusion time was 123 minutes. This patient was discharged in good condition and follow-up study after 16 months revealed the patient had enjoyed healthy life. 3) The preoperative studies about the third case were compatible with aortic insufficiency and mitral stenoinsufficiency. The diseased valves were replaced with type 2 sutureless Magovern aortic valve and the medium sized Beall mitral prosthesis under cardiopulmonary bypass using hypothermic hemodilution technIque and coronary artery perfusion. The total perfusion time was 155 minutes. This patient was discharged in good condition, but thromboembolism was developed 2 months after discharge. 4) The preoperative studies about the fourth case were compatible with mitral insufficiency. The diseased mitral valve was replaced with the medium sized Beall prosthetic valve. The total perfusion time was 132 minutes. The atrioventricular block developed just after operation but converted to normal sinus rhythmn on the third postperative day. The preoperative NYHA functional classification IV was converted to Class 1 or 11 at the time of discharge and this patient enjoyed healthy life. Attendum; The fifth case, nineteen years old male with mital insufficiency underwent Beall valve replacement and his course was uneventful 2 weeks after operation.

• Journal of KIISE
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• v.43 no.11
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• pp.1245-1258
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• 2016

Cryptographic technologies providing confidentiality and integrity such as encryption algorithms and message authentication codes (MACs) are necessary for preventing security threats in the Internet of Things (IoT) where various kinds of devices are interconnected. As a number of encryption schemes that have passed security verification are not necessarily suitable for low-power and low-performance IoT devices, various lightweight cryptographic schemes have been proposed. However, a study of lightweight MACs is not sufficient in comparison to that of lightweight block ciphers. Therefore, in this paper, we reviewed various kinds of MACs for their classification and analysis and then, we presented a new way for future MAC development. We also implemented major MAC algorithms and performed experiments to investigate their performance degradation on low-end micro-controllers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

• Journal of IKEEE
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• v.23 no.4
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• pp.1393-1399
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• 2019

With the rapid growth of the Internet, millions of indiscriminate advertising SMS are sent every day because of the convenience of sending and receiving data. Although we still use methods to block spam words manually, we have been actively researching how to filter spam in a various ways as machine learning emerged. However, spam words and patterns are constantly changing to avoid being filtered, so existing machine learning mechanisms cannot detect or adapt to new words and patterns. Recently, the concept of Lifelong Learning emerged to overcome these limitations, using existing knowledge to keep learning new knowledge continuously. In this paper, we propose a method of spam filtering system using ensemble techniques of naive bayesian which is most commonly used in document classification and LLML(Lifelong Machine Learning). We validate the performance of lifelong learning by applying the model ELLA and the Naive Bayes most commonly used in existing spam filters.

• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.28-35
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• 2009

H.264/AVC, a recently developed video compression standard, is used for various applications because of its high coding efficiency. Variable block mode plays important role in the high coding efficiency of H.264/AVC but involves significant computations to select the optimal mode. In this paper, a fast mode decision method for H.264/AVC P slices is presented. To reduce computations for mode decision, the proposed mode decision method skips the mode decision processes for small partition modes using distortions of SKIP mode and intra16x16 mode. The experimental results show that the proposed method can reduce encoding time up to 66.41% while maintaining compression efficiency.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.95-104
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• 2012

In the image captured by the camera in a moving vehicle, there exist various motions due to the change of background, motion of objects in the image that make difficult to extract a pure vibrational motion by the camera. In this paper, we suggest an image stabilization with the elimination of various motion components based on the classification of motions in the image by their characteristics. After the elimination of various local motions, images are compensated and stabilized with the global motion caused by the camera. Also, we suggest an accurate and fast image stabilization by excluding regions of little information based on block differences and edge densities.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.3
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• pp.174-183
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• 1997

Turbine rotor disc consists of disc, bore, keyway, hub, and rim in which the typical defects are located. And these part of disc has very complicated geometry, therefore proper transducer selection, wedge design, fabrication, classification and evaluation of the signal identification are required. In this research, test block with the artificial flaws at keyway and boresurface parts have been used in order to establish the ultrasonic inspection technique for flaw detectability on disc. The analysis of the signals from the test blocks was performed. The wedges were designed according to the curvature from the discs. All the ultrasonic signals were collected and identified for evaluation. The ultrasonic inspection technique for the flaw-detection was established from this research. And it is proved that the result of this research can be applicable in the field inspection.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.57-62
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• 1999

Estimation of the point spread function (PSF) is one of the main research topic of image processing, because it determines the performance of the auto-focusing system. In this paper, a new algorithm for PSF estimation is proposed, and its application to image restoration is also presented. The procedure for complete realization of the auto-focusing system consists of two steps: PSF estimation based on edge classification, and image restoration using the estimated PSF. More specifically, we divide imput image into multiple small image or block, estimate unit step response and average them on the blocks which contain edge, and estimate 2-dimensional isotropic PSF from the 1 dimensional step response. Finally we obtain in-focused image by using image restoration based on the estimated PSF.