• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.3
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• pp.167-174
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• 2022

This study investigates the behavior of a jointless bridge that integrates superstructure and abutment without an expansion joint. Based on the sensitivity analyses conducted in previous studies, a shell-based model was determined to be the most suitable numerical analysis model for jointless bridges due to the similarity of the model's results compared with the obtained displacement shape, which was influenced by relative errors, precision, and practical aspects. Accordingly, the behavior of a jointless bridge was analyzed at various wall depths using shell element-based and solid element models. In addition, the results of MIDAS Civil and ABAQUS analysis programs were compared. In the case of semi-integrated bridges (A and B), the displacement decreased as the wall depth increased due to the ground reaction force in Case 1 under a linear spring condition and +30℃. In the case where temperature was -30℃, the change in displacement was small because the ground reaction did not occur. As for bridge C (a fully integrated alternating bridge) and bridge D (an integrated chest wall alternating bridge), the displacement decreased as the wall depth increased at both +30 and -30℃ due to pile resistance. As for the comparison between the analysis programs used, the relative error in Case 1 was small, whereas a significant difference in Case 2 was observed. The foregoing variation is possibly due to the difference in the application of the nonlinear spring in the programs.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.579-584
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• 2006

This paper proposes a nonlinear template matching measure, called counting measure, as a signal detection measure that is defined as the number of on pixels in the spot area. It is applied to classify probes for an on-off type DNA chip, where each probe spot is classified as hybridized or not. The counting measure also incorporates the maximum response search method, where the expected signal is obtained by taking the maximum among the measured responses of the various positions and sizes of the spot template. The counting measure was compared to existing signal detection measures such as the normalized correlation and the median for 2390 patient samples tested on the human papiliomavirus (HPV) DNA chip. The counting measure performed the best regardless of whether or not the maximum response search method was used. The experimental results showed that the counting measure combined with the positional search was the most preferable.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.280-285
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• 2015

We consider a linear transceiver design method for multi-user multiple-input multiple-output (MIMO) downlink channels where a base station (BS) equipped with a finitely large number of antennas. Although a matched-filter precoder is a capacity-achieving method in massive MIMO downlink systems, it cannot guarantee to achieve the multi-user MIMO capacity in a finitely large number of antennas due to inter-user interferences. In this paper, we propose a two-stage precoder design method that maximizes the sum-rate of cell-edge users when the BS equipped with a finitely large number of antennas. At the first stage, a matched-filter precoder is adopted to exploit both beamforming gain and the reduction of the dimension of effective channels. Then, we derive the second stage precoder that maximizes the sum-rate by minimizing the weighted mean square error (WMSE). From simulation and analysis, we verify the effectiveness of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.3-12
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• 2016

Recently, the study on 5G mobile communication systems using the millimeter-wave frequency band have been actively promoted and the importance of compensation of the nonlinearity of power amplifier caused by the characteristics of millimeter-wave frequency propagation attenuation is increasing. In the paper, we propose a piecewise polynomial model based on subdivision coefficient which are characteristics of power amplifier separated linear section and a non-linear section. In addition, the structure of digital predistortion based on the proposed model and direct learning method are proposed to implement a digital predistortion. To verify the proposed model, digital predistortion based on the proposed model and direct learning method for 60 GHz power amplifier using LTE signal implemented in the FPGA. And the hardware test bench measured performance and complexity. The proposed model achieves 3.3 dB gain over the single polynomial model in terms of the ACLR and reduces 7.5 percent in terms of the complexity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.667-675
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• 2011

In this paper, we propose an automatic image-to-image registration between high resolution multi-sensor images. To do this, TerraSAR-X image was shifted according to the initial translation differences of the x and y directions between images estimated using Mutual Information method. After that, the Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on the similarities of their locations and gradient orientations. For extracting large number of evenly distributed matching points, only one point within each regular grid constructed throughout the image was extracted to the final matching point pair. The model, which combined the piecewise linear function with the global affine transformation, was applied to increase the accuracy of the geometric correction, and the proposed method showed RMSE lower than 5m in all study sites.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.57-61
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• 1999

In the field of image compression, Classified Vector Quantization(CVQ) reveals attractive characteristics for preserving perceptual features, such as edges. However, the classification scheme is not generalized to effectively reconstruct different kinds of edge patterns in the original CVQ that predefines several linear-type edge classes: vortical edge horizontal edge diagonal edge classes. In this paper, we propose a new classification scheme, especially for edge blocks based on the similarity measure for edge patterns. An edge block is transformed to a feature vector that describes the detailed shape of the edge pattern The classes for edges are formulated automatically from the training images to result in the generalization of various shapes of edge patterns. The experimental results show the generated linear/nonlinear types of edge classes. The integrity of all the edges is faithfully preserved in the reconstructed image based on the various type of edge codebooks generated at 0.6875bpp.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.1-8
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• 2005

This paper describes a new objective methodology of seismic building damage assessment which is called Advanced Component Method(ACM). ACM is a major attempt to replace the conventional loss estimation procedure, which is based on subjective measures and the opinions of experts, with one that objectively measures both earthquake intensity and the response ol buildings. First, response of typical buildings is obtained analytically by nonlinear seismic static analysis, push-over analyses. The spectral displacement Is used as a measure of earthquake intensity in order to use Capacity Spectrum Method and the damage functions for each building component, both structural and non-structural, are developed as a function of component deformation. Examples of components Include columns, beams, floors, partitions, glazing, etc. A repair/replacement cost model is developed that maps the physical damage to monetary damage for each component. Finally, building response, component damage functions, and cost model were combined probabilistically, using Wonte Carlo simulation techniques, to develop the final damage functions for each building type. Uncertainties in building response resulting from variability in material properties and load assumptions were incorporated in the Latin Hypercube sampling technique. The paper also presents and compares ACM and conventional building loss estimation based on historical damage data and reported loss data.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.1
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• pp.57-64
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• 2022

This study investigated the structural performance of the RC boundary beam-wall system subjected to axial loads that required lesser construction quantity and smaller floor height in comparison with the conventional RC transfer girder system. Four specimens of 1/2 scale were constructed, and their peak strengths under axial loads and failure characteristics were compared and analyzed. Test parameters included the ratio of the lower to the upper wall length, lower wall thickness, and stirrup details of the lower wall. In addition, three-dimensional nonlinear finite element analysis was performed to verify the effectiveness of the boundary beam-wall system. The peak strength of each specimen was similar to the nominal axial strength of the lower wall, indicating that the axial load was transferred smoothly from the upper to the lower wall. The contribution of the lower wall cross-section was high if the ratio of the lower to the upper wall length was small; the contribution was low if the out-of-plane eccentricity existed in the lower wall. The specimen with smaller stirrup distance and cross-ties in the lower wall showed higher initial stiffness and peak load than other specimens.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.187-197
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• 2005

In this paper, we propose a method to estimate camera motion parameter based on invariant point features, Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time, The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum, In order to complement these shortfalls, we, first proposed constructing feature models using invariant vector of geometry, Secondly, we proposed a two-stage calculation method to improve accuracy and convergence by using 2D homography and LM method, In the experiment, we compared and analyzed the proposed method with existing method to demonstrate the superiority of the proposed algorithms.