• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.612-624
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• 2005

In this paper, we propose a surface-based registration using a gaussian weighted distance map for PET-CT brain image fusion. Our method is composed of three main steps: the extraction of feature points, the generation of gaussian weighted distance map, and the measure of similarities based on weight. First, we segment head using the inverse region growing and remove noise segmented with head using region growing-based labeling in PET and CT images, respectively. And then, we extract the feature points of the head using sharpening filter. Second, a gaussian weighted distance map is generated from the feature points in CT images. Thus it leads feature points to robustly converge on the optimal location in a large geometrical displacement. Third, weight-based cross-correlation searches for the optimal location using a gaussian weighted distance map of CT images corresponding to the feature points extracted from PET images. In our experiment, we generate software phantom dataset for evaluating accuracy and robustness of our method, and use clinical dataset for computation time and visual inspection. The accuracy test is performed by evaluating root-mean-square-error using arbitrary transformed software phantom dataset. The robustness test is evaluated whether weight-based cross-correlation achieves maximum at optimal location in software phantom dataset with a large geometrical displacement and noise. Experimental results showed that our method gives more accuracy and robust convergence than the conventional surface-based registration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.341-353
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• 2014

In order to deliver a centimeter-level kinematic positioning solution with GPS carrier-phase measurements, it is prerequisite to use correctly resolved integer ambiguities. Based on the mathematical modeling of GPS network with application of its geometrical constraints, this research has investigated an instantaneous ambiguity resolution procedure for the so-called 'integer constrained least-squares' technique which can be effectively implemented in real-time structure monitoring. In this process, algorithms of quality control for the float solutions and hypothesis tests using the constrained baseline for the ambiguity validation are included to enhance reliability of the solutions. The proposed procedure has been implemented by MATLAB, the language of technical computing, and processed field trial data obtained at a cable-stayed bridge to access its real-world applicability. The results are summarized in terms of ambiguity successful rates, impact of the stochastical models, and computation time to demonstrate performance of the instantaneous ambiguity resolution proposed.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.1
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• pp.42-47
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• 1999

This study considers pseudosteady-state flow to a restricted-entry well in a single or multilayer aquifer with crossflow. A simple method for calculating the pseudoskin factor caused by partial penetration is presented to overcome a limited applicability in geometrical or computational aspects of previous methods. The computation is based on the solution of a simplified pseudosteady-state equation that describes the long-time behavior of the closed radial system. We illustrate the applicability of this method to various types of cylindrical systems and provide the results graphically. Comparisons with previously published results have indicated that this method yields highly accurate estimates of pseu-doskin factor with minimum computational effort. This method has also shown to be particularly useful for geometrically-complicated systems. Greatly improved computational efficiency of pseudosteady-state approach permits the engineer to easily account for the effect of partial penetration on the late-time performance of a well.

• Journal of the Korean Magnetic Resonance Society
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• v.19 no.2
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• pp.67-73
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• 2015

The microcystin is a cyclic heptapeptide from metabolites of cyanobacteria in the genera mycrocystis, anabaeba as a result of eutrophication. It has been known that microcystin-LR is a potent inhibitor of the catalytic subunits of protein phosphatase-1 (PP-1) as well as powerful tumor promoter. The active site of microcystin actually has two metal ions $Fe^{2+}/Zn^{2+}$ close to the nucleophilic portion of PP-1-microcystin complex. We report the isolation and purification of this microcystin-LR from cyanobacteria (blue-green algae) obtained from Daechung Dam in Chung-cheong Do, Korea. Microcystin-LR was extracted from solid-phase extraction (SPE) sample preparation using a CN cartridge. The cyanobacteria extract was purified to obtain microcystin-LR by HPLC method and identified by LC/MS. The detail structural studies that can elucidate the possible role of monovalent and divalent metal ions in PP-1-microcystin complexation were carried out by utilizing molecular dynamics. Conformational changes in metal binding for ligands were monitored by molecular dynamic computation and potential of mean force (PMF) using the method of the free energy perturbation. The microcystin-metal binding PMF simulation results exhibit that microcystin can have very stable binding free energy of -10.95 kcal/mol by adopting the $Mg^{2+}$ ion at broad geometrical distribution of $0.5{\sim}4.5{\AA}$, and show that the $K^+$ ion can form a stable metal complex rather than other monovalent alkali metal ions.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.451-459
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• 2016

While an object detection algorithm plays a key role in many computer vision applications, it requires extensive computation to show robustness under varying lightning and geometrical distortions. Recently, some approaches formulate the problem in a classification framework and show improved performances in object recognition. Among them, random fern algorithm drew a lot of attention because of its simple structure and high recognition rates. However, it reveals performance degradation under the illumination changes and noise addition, since it computes patch features based only on pixel intensities. In this paper, we propose a new structure of combined random fern which incorporates depth information into the conventional random fern reflecting 3D structure of the patch. In addition, a new structure of object tracker which exploits the combined random fern is also introduced. Experiments show that the proposed method provides superior performance of object detection under illumination change and noisy condition compared to the conventional methods.

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.23-33
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• 2000

In this paper, we describe an algorithm which can extract human faces with natural pose from complex backgrounds. This method basically adopts the concept that facial region has the nearly same gray level for all pixels within appropriately scaled blocks. Based on the idea, we develop a hierarchial process that first, a block image data with pyramid structure of input image is generated, and some candidate regions for facial regions in the block image are Quickly determined, then finally the detailed facial features; organs are decided. To find the features easily, we introduce a local gray level transform which emphasizes dark and small regions, and estimate the geometrical triangle constraints among the facial features. The merit of our method is that we can be freed from the parameter assignment problem since the algorithm utilize a simple brightness computation, consequently robust systems not being depended on specific parameter values can be easily constructed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.381-391
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• 2001

This paper presents an efficient approach to build an image mosaics from image sequences. Unlike general panoramic stitching methods, which usually require some geometrical feature points or solve the iterative nonlinear equations, our algorithm can directly recover the 8-parameter planar perspective transforms. We use four quasi-feature points in order to compute the projective transform between two images. This feature is based on the graylevel distribution and defined in the overlap area between two images. Therefore the proposed algorithm can reduce the total amount of the computation. We also present an algorithm lot efficiently matching the correspondence of the extracted feature. The proposed algorithm is applied to various images to estimate its performance and. the simulation results present that our algorithm can find the correct correspondence and build an image mosaics.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.4
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• pp.277-284
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• 2020

The remaining range between missile and target can be used to calculate the guidance command as well as to determine the explosion time of the warhead. Since the range, however, is not directly measured by on-board sensors of the missile, it is usually estimated by filter-based techniques using angle-only measurements. Conventional filter-based techniques are complex and require huge computation. In this paper, we propose a range estimation algorithm based on the geometrical triangulation principle for two points of missiles and a target. The proposed algorithm has a simple structure but the accuracy is largely dependent on the measurement errors. To improve the accuracy of estimation, Digital Fading Memory Filter (DFMF) is applied. The performance of the proposed algorithm is analyzed through numerical simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.7-13
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• 2002

Almost applications using fuzzy theory are based on the fuzzy inference. However fuzzy inference needs much time in calculation process for the fuzzy system with many input variables or many fuzzy labels defined on each variable. Inference time is dependent on the number of arithmetic Product in computation Process. Especially, the inference time is a primary constraint to fuzzy control applications using microprocessor or PC-based controller. In this paper, a simple fast fuzzy inference algorithm(FFIA), without loss of information, was proposed to reduce the inference time based on the fuzzy system with triangular membership functions in antecedent part of fuzzy rule. The proposed algorithm was induced by using partition of input state space and simple geometrical analysis. By using this scheme, we can take the same effect of the fuzzy rule reduction.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2162-2172
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• 2020

Due to its computational efficiency and geometrical flexibility, the Method of Characteristics (MOC) has been widely used for light water reactor lattice physics analysis. Usually acceleration methods are necessary for MOC to achieve acceptable convergence on practical reactor physics problems. Among them, Coarse Mesh Finite Difference (CMFD) is very popular and can drastically reduce the number of transport iterations. In OpenMOC, CMFD acceleration was implemented but had the limitation of supporting only a uniform CMFD mesh, which would often lead to splitting MOC source regions, thus creating an unnecessary increase in computation and memory use. In this study, CMFD acceleration with a non-uniform Cartesian mesh is implemented into OpenMOC. We also propose a quadratic fit based CMFD prolongation method in the axial direction to further improve the acceleration when multiple MOC source regions are contained in one CMFD coarse mesh. Numerical results are presented to demonstrate the improvement of the CMFD acceleration capability in OpenMOC in terms of both efficiency and stability.