• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.9-14
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• 2006

Estimations of depth, magnetic orientation, and strength of dipole moments aid discrimination between unexploded ordnance (UXO) and non-UXO using magnetic surveys. Such estimations may be hindered by geologic noise, magnetic clutter, and overlapping tails of nearby dipole fields. An improved method of inversion for anomalies of single or multiple dipoles with arbitrary polarization was developed to include intra-inversion filtering and estimation of background field gradients. Data interpolated to grids are flagged so that only nodes nearest to measurement stations are used. To apply intra-inversion filtering to such data requires a gapped filter. Moreover, for data with significant gaps in coverage, or along the edges or corners of survey areas, intra-inversion filters must be appropriately modified. To that end, edge-adaptive and gapped gradient-nulling filters have been designed and tested. Applications are shown for magnetic field data from Chongcho Lake, Sokcho, Korea and the U. S. Army's Aberdeen Proving Ground in Maryland.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2128-2131
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• 2003

We present an efficient algorithm for skew correction of business card images obtained by a PDA camera. The proposed method is composed of four parts: block adaptive binarization (BAB), stripe generation, skew angle calculation, and image rotation. In the BAB, an input image is binarized block by block so as to lessen the effects of irregular illumination and shadows over the input image. In the stripe generation, character string clusters are generated merging character strings and their inter-spaces, and then only clusters useful for skew angle calculation are output as stripes. In the skew angle calculation, the direction angles of the stripes are calculated using their central moments and then the skew angle of the input image is determined averaging the direction angles. In the image rotation, the input image is rotated by the skew angle. Experimental results shows that the proposed method yields correction rates of 97％ for business card images.

• Transactions of Materials Processing
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• v.9 no.6
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• pp.574-581
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• 2000

A vertically-walled auto-body part is one of the most difficult stamping parts because of angle change, wall curl, and twisting of the blank after springback as well as fracture and wrinkle. In this study, computational simulations of the vertically-walled auto-body part are carried out focusing on angle change, wall curl, and twisting after springback. Binderwrap blank shape is used in forming analysis for precise initial contacts between punch and blank. An adaptive mesh method is used in springback analysis for precise calculation of bending moments. In springback analysis, the differences of 2 and 3 dimensional analysis are compared and the effects of blank holdig force and friction coefficient are evaluated. In order to verify the validity of simulation results, they are compared with measured ones. The predicted thickness distribution and formed shape are agreed well with those of the measurement. The Predicted springback amount is less than that of the measurement.

• Journal of Communications and Networks
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• v.9 no.2
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• pp.185-191
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• 2007

Alpha stable distribution is better for modeling impulsive noises than Gaussian distribution in signal processing. This class of process has no closed form of probability density function and finite second order moments. In general, Wiener filter theory is not meaningful in S$\alpha$SG environments because the expectations may be unbounded. We proposed a new adaptive recursive least p-norm Kalman filtering algorithm based on least p-norm of innovation process with infinite variances, and a new robust multiuser detection method based on least p-norm Kalman filtering. The simulation experiments show that the proposed new algorithm is more robust than the conventional Kalman filtering multiuser detection algorithm.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.1
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• pp.37-55
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• 2023

In this paper we propose a new algorithm for detecting and counting flowers in a complex background based on digital images. The algorithm mainly includes the following parts: edge contour extraction of flowers, edge contour determination of overlapped flowers and flower counting. We use a contour detection technique in Computer Vision (CV) to extract the edge contours of flowers and propose an improved algorithm with a concave point detection technique to find accurate segmentation for overlapped flowers. In this process, we first use the polygon approximation to smooth edge contours and then adopt the second-order central moments to fit ellipse contours to determine whether edge contours overlap. To obtain accurate segmentation points, we calculate the curvature of each pixel point on the edge contours with an improved Curvature Scale Space (CSS) corner detector. Finally, we successively give three adaptive judgment criteria to detect and count flowers accurately and automatically. Both experimental results and the proposed evaluation indicators reveal that the proposed algorithm is more efficient for flower counting.

• Journal of Biomedical Engineering Research
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• v.27 no.2
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• pp.47-52
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• 2006

The purpose of this study was to predict successful defibrillation in ventricular fibrillation using parameters extracted by wave analysis method and neuro-fuzzy. Total 15 dogs were tested for predicting successful defibrillation. Feature parameters were extracted for return of spontaneous circulation (ROSC) and non-ROSC by wave analysis method, and these parameters are an irregularity factor, spectral moments, mean power of level-crossing spectrum, and mean of alpha-significant value. Additionally, two parameters by analyzing method of frequency were extracted into a mean of power spectrum and a mean frequency. Then extracted parameters were analyzed in which parameters result to have high performance of discriminating ROSC and non-ROSC by a statistical method of t-test. The average of sensitivity and specificity were 62.5% and 75.0%, respectively. The average of positive predictive factor and negative predictive factor were 61.2% and 75.8%, respectively.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.43-56
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• 2011

An integrated system composed of guidance, navigation and control (GNC) system for autonomous proximity operations and the docking of two spacecraft was developed. The position maneuvers were determined through the integration of the state-dependent Riccati equation formulated from nonlinear relative motion dynamics and relative navigation using rendezvous laser vision (Lidar) and a vision sensor system. In the vision sensor system, a switch between sensors was made along the approach phase in order to provide continuously effective navigation. As an extension of the rendezvous laser vision system, an automated terminal guidance scheme based on the Clohessy-Wiltshire state transition matrix was used to formulate a "V-bar hopping approach" reference trajectory. A proximity operations strategy was then adapted from the approach strategy used with the automated transfer vehicle. The attitude maneuvers, determined from a linear quadratic Gaussian-type control including quaternion based attitude estimation using star trackers or a vision sensor system, provided precise attitude control and robustness under uncertainties in the moments of inertia and external disturbances. These functions were then integrated into an autonomous GNC system that can perform proximity operations and meet all conditions for successful docking. A six-degree of freedom simulation was used to demonstrate the effectiveness of the integrated system.

• KIEAE Journal
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• v.14 no.3
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• pp.97-103
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• 2014

This study aimed at developing integrated logic for controlling heating device and openings of the double skin facade buildings. Two major logics were developed-rule-based control logic and artificial neural network based control logic. The rule based logic represented the widely applied conventional method while the artificial neural network based logic meant the optimal method. Applying the optimal method, the predictive and adaptive controls were feasible for supplying the advanced thermal indoor environment. Comparative performance tests were conducted using the numerical computer simulation tools such as MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation). Analysis on the test results in the test module revealed that the artificial neural network-based control logics provided more comfortable and stable temperature conditions based on the optimal control of the heating device and opening conditions of the double skin facades. However, the amount of heat supply to the indoor space by the optimal method was increased for the better thermal conditioning. The number of on/off moments of the heating device, on the other hand, was significantly reduced. Therefore, the optimal logic is expected to beneficial to create more comfortable thermal environment and to potentially prevent system degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1225-1238
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• 2003

We present an efficient algorithm for skew correction of business card images obtained by a PDA (personal digital assistant) camera. The proposed method is composed of four parts: block adaptive binarization (BAB), stripe generation, skew angle calculation, and image rotation. In the BAB, an input image is binarized block by block so as to lessen the effect of irregular illumination and shadow over the input image. In the stripe generation, character string clusters are generated merging adjacent characters and their strings, and then only clusters useful for skew angle calculation are output as stripes. In the skew angle calculation, the direction angles of the stripes are calculated using their central moments and then the skew angle of the input image is determined averaging the direction angles. In the image rotation, the input image is rotated by the skew angle. Experimental results shows that the proposed method yields skew correction rates of about 93% for test images of several types of business cards acquired by a PDA under various surrounding conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.920-926
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• 2004

The human being receives a new information from outside and the information shows gradual oblivion with time. But the information remains in memory and isn't forgotten for a long time if the information is read several times over. For example, we assume that we memorize a telephone number when we listen and never remind we may forget it soon, but we commit to memory long time by repeating. If the human being received new information with strong stimulus, it could remain in memory without recalling repeatedly. The moments of almost losing one's life in an accident or getting a stroke of luck are rarely forgiven. The human being can keep memory for a long time in spite of the limit of memory for the mechanism mentioned above. In this paper, we propose a model to explain the mechanism mentioned above using a neural network and fuzzy.