• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.4
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• pp.447-457
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• 2021

Graphite Isotope Ratio Method (GIRM) can be used to estimate plutonium production in a graphite-moderated reactor. This study presents verification results for the GIRM combined with a 3-D polynomial regression function to estimate cumulative plutonium production in a graphite-moderated reactor. Using the 3-D Monte-Carlo method, verification was done by comparing the cumulative plutonium production with the GIRM. The GIRM can estimate plutonium production for specific sampling points using a function that is based on an isotope ratio of impurity elements. In this study, the ¹⁰B/¹¹B isotope ratio was chosen and calculated for sampling points. Then, 3-D polynomial regression was used to derive a function that represents a whole core cumulative plutonium production map. To verify the accuracy of the GIRM with polynomial regression, the reference value of plutonium production was calculated using a Monte-Carlo code, MCS, up to 4250 days of depletion. Moreover, the amount of plutonium produced in certain axial layers and fuel pins at 1250, 2250, and 3250 days of depletion was obtained and used for additional verification. As a result, the difference in the total cumulative plutonium production based on the MCS and GIRM results was found below 3.1% with regard to the root mean square (RMS) error.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• Journal of the Korean Society of Food Culture
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• v.10 no.3
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• pp.167-174
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• 1995

A hazard analysis which included watching operations, measuring temperatures of foods throughout preparation and display, and sampling and testing for microorganisms of total plate counts and coliform bacteria was conducted in various phases of product flow of Naeng-myeun (Cold noodles) and Pi-bim bab (mixed rice) prepared at Korean restaurants. Large numbers of total plate counts were counted from the cooked foods after handling and holding. Ingestion of these foods must be considered high risk. Critical control points identified were, pre-preparation, food handling after cooking, and holding on display in product flow of Nang-Meon and pre-preparation, preparation, and holding on display in product flow of Pi-bim bab. It need for effective quality control of Nang-Meon and Pi-bim bab that training program consist of surveillance, education of the staff, standard operation procedures, forbidding dangerous processes and control of critical points.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1169-1175
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• 2008

The validation technique is classified with two methods whether to demand of additional experimental points. The method which requires additional experimental points such as RSME is actually impossible in engineering field. Therefore, the method which only use experimented points such as the cross validation technique is only available. But the cross validation not only requires considerable computational costs for generating metamodel each iterations, but also cannot measure quantitatively the fidelity of metamodel. In this research we propose a new validation technique for representative metamodels using an variance of metamodel and confidence interval information. The proposed validation technique computes confidence intervals using a variance information from the metamodel. This technique will have influence on choosing the accurate metamodel, constructing ensemble of each metamodels and advancing effectively sequential sampling technique.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.224-238
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• 2004

Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.4
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• pp.305-312
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• 2005

In this thesis, Lohmann's algorithm and FFT (fast Fourier transform) are used to synthesize binary-phase holograms. FFT computing is carried out for the calculation of complex wavefronts of $128{\times}128$ sampling points of an object that is numerically specified. Then using the Lohmann's algorithm, the amplitude and the phase of complex wavefronts are encoded in binary holograms on each sampling points. PC (personal computer) and laser printer are used to plot binary-phase holograms and CGH (computer generated holograms) films are obtained from this plot by photographic reduction. Holographic images of numerically specified objects are reconstructed from the He-Ne laser and the inverse Fourier optics system. We estimate the quality of holographic images according to the sampling number, application of random phase, amplitude clipping and bleaching the CGH film. We derive optimized conditions to reconstruct better holographic images and to reduce the speckle noise. FFT and Lohmann's algorithm are implemented with MS Visual BASIC 6.0 for the programming of binary-phase hologram.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.16-22
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• 2013

In this study, we propose the method of optimally changing material of BIW for minimizing weight while satisfying vehicle requirements on static stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the linear polynomial regression (PR) model. Using the linear PR model, optimization is carried out an evolutionary algorithm (EA) that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 44.8% while satisfying all the design constraints.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.8-14
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• 2013

In this study, we propose the method of optimally selecting material of front pillar (A-pillar) and package tray for minimizing weight while satisfying vehicle requirements on static stiffness and dynamic stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness and dynamic stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the radial basis function regression (RBFr). Using the RBFr models, optimization is carried out an evolutionary algorithm that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 49.8% while satisfying all the design constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4940-4957
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• 2019

Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.401-410
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• 2016

3D registration is a computer vision technique of aligning multi-view range images with respect to a reference coordinate system. Various 3D registration algorithms have been introduced in the past few decades. Iterative Closest Point (ICP) is one of the widely used 3D registration algorithms, where various modifications are available nowadays. In the ICP-based algorithms, the closest points are considered as the corresponding points. However, this assumption fails to find matching points accurately when the initial pose between point clouds is not sufficiently close. In this paper, we propose a new method to solve this problem using the 6D distance (3D color space and 3D Euclidean distances). Moreover, a color segmentation-based adaptive sampling technique is used to reduce the computational time and improve the registration accuracy. Several experiments are performed to evaluate the proposed method. Experimental results show that the proposed method yields better performance compared to the conventional methods.