• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.939-942
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• 1996

This paper presents a stable learning algorithm for diagonal recurrent neural network(DRNN). DRNN is applied to a problem of controlling nonlinear dynamical systems. A architecture of DRNN is a modified model of the Recurrent Neural Network(RNN) with one hidden layer, and the hidden layer is comprised of self-recurrent neurons. DRNN has considerably fewer weights than RNN. Since there is no interlinks amongs in the hidden layer. DRNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. To guarantee convergence and for faster learning, an adaptive learning rate is developed by using Lyapunov function. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed algorithm is demonstrated by computer simulation.

• Nonlinear Functional Analysis and Applications
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• v.26 no.2
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• pp.411-432
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• 2021

In this paper, an inertial Halpern-type forward backward iterative algorithm for approximating solution of a monotone inclusion problem whose solution is also a fixed point of some nonlinear mapping is introduced and studied. Strong convergence theorem is established in a real Hilbert space. Furthermore, our theorem is applied to variational inequality problems, convex minimization problems and image restoration problems. Finally, numerical illustrations are presented to support the main theorem and its applications.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.55-63
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• 2021

The design functionality put forward by mapping the interactiveness of information. The presentation of such information with the user interface model indicates that the guidelines, concepts, and workflows form the deliverables and milestones for achieving a visualized design, therefore forming the right trend is significant to ensure compliance in terms of changing consideration and applying evaluation in the early stages. It is evidenced that prototype design is guided by improvement specifications, includes modes, and variables that increase improvements. The study presents five user interface testing methods. The testing methods are heuristic evaluation, perspective-based user interface testing, cognitive walkthrough, pluralistic walkthrough, and formal usability inspection. It appears that the five testing methods can be combined and matched to produce reasonable results. At last, the study presents different mobile application designs for student projects besides the evaluation of mobile application designs to consider the user needs and usability.

• Economic and Environmental Geology
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• v.43 no.6
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• pp.615-623
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• 2010

Seismic refraction survey is a geophysical method that delineates subsurface velocity structure using direct wave and critically refracted wave. The generalized reciprocal method(GRM) is an inversion technique which uses travel-time data from several forward and reverse shots and which can provide the geometry of irregular inclined refractors and structures underlain by hidden layer such as low velocity zone and thin layer. In this study, a simple Excel-GRM routine was tested for fast mapping of the interface between weathering layer and bedrock during the survey, with employing a pair of forward and reverse shots. This routine was proved to control the maximum dip of approximately $30^{\circ}C$ and maximum velocity contrast of 0.6, based on the panel tests in terms of dipping angle and velocity contrast for the two-layer inclined models. In contrast with conventional operation of five to seven shots with sufficient offset distance and indoor data analysis thereafter, this routine was performed in the field shortly after data acquisition. Depth to the bedrock provided by Excel-GRM, during the field survey for Cheongju granite area, correlates well with the elevation of the surface of soft rock from the drill core and SPS logging data. This cost-effective routine developed for quickly delineating the bedrock surface in the field survey will be readily applicable to mapping of weathering zone in narrow zone with small variation of elevation of bedrock.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.110-117
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• 2023

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.329-336
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• 2008

Recently, causality analysis of source time series extracted from EEG or MEG signals is becoming of great importance in human brain mapping studies and noninvasive diagnosis of various brain diseases. Two approaches have been widely used for the analyses: one is independent component analysis (ICA), and the other is multiple signal classification (MUSIC). To the best of our knowledge, however, any comparison studies to reveal the difference of the two approaches have not been reported. In the present study, we compared the performance of the two different techniques, ICA and MUSIC, especially focusing on how accurately they can estimate and separate various brain electrical signals such as linear, nonlinear, and chaotic signals without a priori knowledge. Results of the realistic simulation studies, adopting directed transfer function (DTF) and Granger causality (GC) as measures of the accurate extraction of source time series, demonstrated that the MUSIC-based approach is more reliable than the ICA-based approach.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.740-743
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• 1998

This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.

• Computers and Concrete
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• v.10 no.4
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• pp.331-347
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• 2012

This paper describes the varying material model, the analysis method and the software development for reinforced concrete circular columns confined by spiral or hoop transverse steel reinforcement and subjected to eccentric loading. The widely used Mander model of concentric loading is adapted here to eccentric loading by developing an auto-adjustable stress-strain curve based on the eccentricity of the axial load or the size of the compression zone to generate more accurate interaction diagrams. The prediction of the ultimate unconfined capacity is straight forward. On the other hand, the prediction of the actual ultimate capacity of confined concrete columns requires specialized nonlinear analysis. This nonlinear procedure is programmed using C-Sharp to build efficient software that can be used for design, analysis, extreme event evaluation and forensic engineering. The software is equipped with an elegant graphics interface that assimilates input data, detail drawings, capacity diagrams and demand point mapping in a single sheet. Options for preliminary design, section and reinforcement selection are seamlessly integrated as well. Improvements to KDOT Bridge Design Manual using this software with reference to AASHTO LRFD are made.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.75-80
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• 2023

We show the design of fast invertible block transforms that can replace the DCT in future wireless and portable computing application. This is called binDCT. In binDCT, both the forward and the inverse transforms can be implemented using only binary shift and addition operation. And the binDCT inherits all desirable DCT characteristics such as high coding gain, no DC leakage, symmetric basis functions, and recursive construction. The binDCT also inherits all lifting properties such as fast implementations, invertible integer-to-integer mapping, in-place computation. Thus, this method has advantage of fast implementation for complex DCT calculations. In this paper, we present computation costs and performance analysis between DCT and binDCT using Shapiro's EZW.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1303-1310
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• 2009

Glassless 3D display requires multiple images taken from different viewpoints to show a scene. The simplest way to get multi-view image is using multiple camera that as number of views are requires. To do that, synchronize between cameras or compute and transmit lots of data comes critical problem. Thus, generating such a large number of viewpoint images effectively is emerging as a key technique in 3D video technology. Image-based view synthesis is an algorithm for generating various virtual viewpoint images using a limited number of views and depth maps. In this paper, because the virtual view image can be express as a transformed image from real view with some depth condition, we propose an algorithm to compute multi-view synthesis from two reference view images and their own depth-map by stepwise duplex forward mapping. And also, because the geometrical relationship between real view and virtual view is repetitively, we apply our algorithm into OpenGL Shading Language which is a programmable Graphic Process Unit that allow parallel processing to improve computation time. We demonstrate the effectiveness of our algorithm for fast view synthesis through a variety of experiments with real data.