• Computers and Concrete
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• v.12 no.3
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• pp.243-259
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• 2013

Recent developments in Artificial Intelligence (AI) and computational intelligence have made it viable in the construction industry and structural analysis. This study usesthe Adaptive Network-based Fuzzy Inference System (ANFIS) as a modelling tool to predict the strain in tie section for High Strength Self Compacting Concrete (HSSCC) deep beams. 3773 experimental data were collected. The input data andits corresponding strains in tie section as output data were recorded at all loading stages. Results from ANFIS are compared with the classical linear regression (LR). The comparison shows that the ANFIS's results are highly accurate, precise and satisfactory.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1727-1731
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• 2004

We propose an ART2 neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, fault classifier by ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters is used for fault isolation. The performances of the proposed fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

• Computational Structural Engineering
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• v.6 no.3
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• pp.99-112
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• 1993

One of the characteristics of Delaunay-Voronoii methods of mesh generation is local remeshing ability in comparison with other methods, which is very useful in adaptive finite element applications. Main part of the process is to construct remeshing element group out of the whole elements and to remesh it. Adjacent element array, accompanied with an additional algorithm of several lines, is introduced to make the process simple so that implementation of the concept is possible at the level of general PC users.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.616-621
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• 2004

This paper investigated the speed sensorless indirect vector control of a two-phase induction motor to implement adjustable-speed drive for low-power applications. The sliding mode observer estimates rotor speed. The convergence of the nonlinear time-varying observer along with the asymptotic stability of the controller was analyzed. To define the control action which maintains the motion on the sliding manifold, an 'equivalent control' concept was used. It was simulated and implemented on a sensorless indirect vector drive for 150W two-phase induction motor. The simulation and experimental results demonstrated effectiveness of the estimation method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.70-77
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• 1992

Generally, the conventional tracking algorithms are very limited in the practical applications because of that the computation load is exponentially increased as the number of targets being tracked is increase. Recently, to overcome this kind of limitation, some new tracking methods based on neural network algorithms which have learning and parallel processing capabilities are introduced. By application of neural networks to multi-target tracking problems, the tracking system can be made computationally independent of the number of objects being tracked, through their characteristics of massive parallelism and dense interconnectivity. In this paper, a new neural network tracking algorithm, which has capability of adaptive target tracking with little increase of the amount of calculation under the clutter and noisy environments, is suggested and the possibility of real-time multi-target tracking system based on neural networks is also demonstrated through some good computer simulation results.

• Journal of Information Technology Applications and Management
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• v.10 no.3
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• pp.45-54
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• 2003

Security system with web camera remarkably has been developed at an Internet era. Using transmitted images from remote camera, the system can recognize current situation and take a proper action through web. Existing motion detection methods use simply difference image, background image techniques or block matching algorithm which establish initial block by set search area and find similar block. But these methods are difficult to detect exact motion because of useless noise. In this paper, the proposed method is updating changed background image as much as $N{\times}M$pixel mask as time goes on after get a difference between imput image and first background image. And checking image pixel can efficiently detect motion by computing fixed distance pixel instead of operate all pixel.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.101.2-101.2
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• 2013

We present a new computational fluid dynamic (CFD) simulation code. The code employs the moving and polyhedral unstructured mesh scheme, which is known as a superior approach to the conventional SPH (smoothed particle hydrodynamics) and AMR (adaptive mesh refinement) schemes. The code first generates unstructured meshes by the Voronoi tessellation at every time step, and then solves the Riemann problem for surfaces of every Voronoi cell to update the hydrodynamic states as well as to move former generated meshes. For the second-order accuracy, the MUSCL-Hancock scheme is implemented. To increase efficiency for generating Voronoi tessellation we also develop the incremental expanding method, by which the CPU time is turned out to be just proportional to the number of particles, i.e., O(N). We will discuss the applications of our code in the context of cosmological simulations as well as numerical experiments for galaxy formation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.2
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• pp.1-8
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• 2003

Conventionally used linear or circular interpolator is undesirable for the precision machining of 3D free-form surface as the following reason: the transmission errors due to the huge number of data, discontinuity of segmentation, unsmooth motion speed. To this regard, modern CNC machine tools are designed with the function of machining arbitrary parametric curves. However, these systems don't consider the adaptive federate, which dominates the quality of the machining process. This paper proposes a NURBS interpolator for the constant material removal rate. That is accomplished by the variable federate using curvature of curve. The curvature-compensated feederate system has important Potential applications in ensuring part accuracy and protecting cutting tool. The simulated result show it can be applicable to the real machining.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.713-727
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• 2005

Among different regression approaches, nonparametric procedures perform well under different conditions. In practice it is very hard to identify which is the best procedure for the data at hand, thus model combination is of practical importance. In this paper, we focus on one dimensional regression with fixed design. Polynomial regression, local regression, and smoothing spline are considered. The data are split into two parts, one part is used for estimation and the other part is used for prediction. Prediction performances are used to assign weights to different regression procedures. Simulation results show that the combined estimator performs better or similarly compared with the estimator chosen by cross validation. The combined estimator generates a similar risk to the best candidate procedure for the data.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.550-553
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• 2005

To acquire radar target signature, various kinds of target are necessary. Measurement is one of the data acquiring method, but much time and high cost is required to get the target data from the real targets. Even if we can afford that, the targets we can access are very limited. To obtain target signatures avoiding these problems, we build the target CAD (Computer Aided Design) model for the calculation of target signatures. To speed up RCS calculation, we applied adaptive super-sampling and tested quite complex tank CAD model which is 1.4 hundred of thousands facet. We use calculated RCS data for ID range profile and 2D ISAR (Inverse Synthetic Aperture Radar) image formation. We adopted IFFT (Inverse Fast Fourier Transform) algorithm combined with polar formatting algorithm for the ISAR imaging. We could confirm the possibility of the construction of database from the images of CAD models for target classification applications.