• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.4
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• pp.307-314
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• 2009

The present paper briefly describes the space frame element and the fundamental strategies in computational elastic bifurcation theory of geometrically nonlinear, single load parameter conservative elastic spatial structures. A method for large deformation(rotation) analysis of space frame is based on an eulerian formulation, which takes into consideration the effects of large joint translations and rotations with finite deformation(rotation). The local member force-deformation relationships are based on the beam-column approach, and the change in member chord lengths caused by axial strain and flexural bowing are taken into account. and the derived geometric stiffness matrix is unsymmetric because of the fact that finite rotations are not commutative under addition. To detect the singular point such as bifurcation point, an iterative pin-pointing algorithm is proposed. And the path switching mode for bifurcation path is based on the non-negative eigen-value and it's corresponding eigen-vector. Some numerical examples for bifurcation analysis are carried out for a plane frame, plane circular arch and space dome structures are described.

• Management & Information Systems Review
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• v.4
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• pp.257-284
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• 2000

According as the drivers increase who have their cars, the comprehensive studies on the automobile for the traffic safety have been raised as the important problems. Visual Recognition System for radio-controled driving is a part of the sensor processor of Unmanned Autonomous Vehicle System. When a driver drives his car on an unknown highway or general road, it produces a model from the successively inputted road traffic information. The suggested Recognition System of the Road Traffic Safety Information Board is to recognize and distinguish automatically a Road Traffic Safety Information Board as one of road traffic information. The whole processes of Recognition System of the Road Traffic Safety Information Board suggested in this study are as follows. We took the photographs of Road Traffic Safety Information Board with a digital camera in order to get an image and normalize bitmap image file with a size of $200{\times}200$ byte with Photo Shop 5.0. The existing True Color is made up the color data of sixteen million kinds. We changed it with 256 Color, because it has large capacity, and spend much time on calculating. We have practiced works of 30 times with erosion and dilation algorithm to remove unnecessary images. We drawing out original image with the Region Splitting Technique as a kind of segmentation. We made three kinds of grouping(Attention Information Board, Prohibit Information Board, and Introduction Information Board) by RYB( Red, Yellow, Blue) color segmentation. We minimized the image size of board, direction, and the influence of rounding. We also minimized the Influence according to position. and the brightness of light and darkness with Eigen Vector and Eigen Value. The data sampling this feature value appeared after building the learning Code Book Database. The suggested Recognition System of the Road Traffic Safety Information Board firstly distinguished three kinds of groups in the database of learning Code Book, and suggested in order to recognize after comparing and judging the board want to recognize within the same group with Nearest Neighborhood Decision Making.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.224-228
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• 2015

In this paper, we study the method for desired signals estimation that array antennas are received signals. We apply sub spatial method of direction of arrival algorithm and adaptive array antennas in order to remove interference and noise signal of received antenna signals. Array response vector of adaptive array antenna is probability, it is correctly estimation of direction of arrival of targets to update weight signal. Desired signals are estimated updating covariance matrix after moving interference and noise signals among received signals. We estimate signals using eigen decomposition and eigen value, high resolution direction of arrival estimation algorithm is devided signal sub spatial and noise sub spatial. Though simulation, we analyze to compare proposed method with general method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.25-32
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• 2005

Frequency hopping system has been adopted to many communication systems in order to overcome the inferior situation such as jamming environment. But typically its processing gain being limited, data interfered by jamming signal could not be fully recovered. This can be enhanced by combing FH system with spatial interference canceller which is a kind of active beamformer In this Paper, we proposed the compensation method of weight vector discrepancy according to the hopped frequencies and the PMBF method which is able to eliminate the inference effectively with less computational complexity. That is, the steering vector of wanted signals can be calculated from the frame without jamming signals using eigen analysis. New projection matrix extracted by the steering vector of wanted signal eliminates the interferences from the covariance matrix of received signal including wanted signal and jamming signals. This PMBF has similar performance of SINR beamformer with less computational complexity.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.90-95
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• 2014

The researchs using brain-computer interface, the new interface system which connect human to macine, have been maded to implement the user-assistance devices for control of wheelchairs or input the characters. In recent researches, there are several trials to implement the speech recognitions system based on the brain wave and attempt to silent communication. In this paper, we studied how to extract features of vowel based on international phonetic alphabet (IPA), as a foundation step for implementing of speech recognition system based on electroencephalogram (EEG). We conducted the 2 step experiments with three healthy male subjects, and first step was speaking imagery with single vowel and second step was imagery with successive two vowels. We selected 32 channels, which include frontal lobe related to thinking and temporal lobe related to speech function, among acquired 64 channels. Eigen value of the signal was used for feature vector and support vector machine (SVM) was used for classification. As a result of first step, we should use over than 10th order of feature vector to analyze the EEG signal of speech and if we used 11th order feature vector, the highest average classification rate was 95.63 % in classification between /a/ and /o/, the lowest average classification rate was 86.85 % with /a/ and /u/. In the second step of the experiments, we studied the difference of speech imaginary signals between single and successive two vowels.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.89-101
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• 2007

This paper investigates the effects of the fusion of multifrequency (C and L bands) polarimetric SAR data in land-cover classification. NASA JPL AIRSAR C and L bands data were used to supervised classification in an agricultural area to simulate the integration of ALOS PALSAR and Radarsat-2 SAR data to be available. Several scattering features derived from target decomposition based on eigen value/vector analysis were used as input for a support vector machines classifier and then the posteriori probabilities for each frequency SAR data were integrated by applying a probabilistic ratio model as a decision level fusion methodology. From the case study results, L band data had the proper amount of penetration power and showed better classification accuracy improvement (about 22%) over C band data which did not have enough penetration. When all frequency data were fused for the classification, a significant improvement of about 10% in overall classification accuracy was achieved thanks to an increase of discrimination capability for each class, compared with the case of L band Shh data.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3
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• pp.123-128
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• 2007

This Paper Presents new transient signal classification algorithms for underwater transient signals. In general. the ambient noise has small spectral deviation and energy variation. while a transient signal has large fluctuation. Hence to detect the transient signal, we use the spectral deviation and power variation. To classify the detected transient signal. the feature Parameters are obtained by using the Wigner-Ville distribution based eigenvalue decomposition. The correlation is then calculated between the feature vector of the detected signal and all the feature vectors of the reference templates frame-by-frame basis, and the detected transient signal is classified by the frame mapping rate among the class database.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.35 no.3
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• pp.243-249
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• 1999

Specificity of catches has been analyzed to japanese tuna purse seine A principle component analysis was used to improve the efficiency of fishing and increase sustainable production and productivity of Korean tuna purse seine.The result are as follows;From the principal component analysis of the fish catches, the first principal component(Z1) to promote principal component score was skipjack Kastsuwonus Pelamis, LINNAEUS and yellowfin tuna Thunnus Albacares, BONNATERRE (Small : smaller than 10kg) and proportion was 86.8% of total. The second principal component(Z2) to increase principal component score was yellowfin tuna (Large : larger than 10kg) and proportion was 9.5%.On the other hand, fish operating that have caught skipjack and yellowfin tuna (Small and Larger) was not so much. Fish catches for one species raised volume of the catches while catches for multi-species decreased it since principal composition score for one species and both species together has been increased.Fish school could be divided into three groups of schools each of which was associated with drift objects, payaho and ship, school associated with shark, whale and porpoise and school of breezing, feeding and jumping from proportion of principal component analysis for fish catches of school types. However, the biological pattern is different among school associated with ship, payaho and school associated with drift objects for analysis eigen vector. School associated with ship, payaho and school associated with drifting object associated is judged as school which be assembled to vessel and drifted log temporary.

• 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 Association for Spatial Structures
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• v.15 no.2
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• pp.51-59
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• 2015

In this study, a shape design and an analysis considering structural stability were investigated to develop an icosahedron-based hemispherical modular dome. To design this modular dome, a program that can perform icosahedron shape modeling, modularization of joint connection members, and the analysis of structural stability was developed. Furthermore, based on the adopted numerical model, the eigen buckling mode, unstable behavior characteristics according to load vector, and the critical buckling load of the modular dome under uniformly distributed load and concentrated load were analyzed, and the resistance capacities of the structure according to different load vectors were compared. The analysis results for the modular dome suggest that the developed program can perform joint modeling for shape design as well as modular member design, and adequately expressed the nonlinear behaviors of structured according to load conditions. The critical buckling load results also correctly reflected the characteristics of the load conditions. The uniformly distributed load was more advantageous to the structural stability than concentrated load.