• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.158-163
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• 2009

In recent years, there has been increased interest in characterizing and extracting 3D information from 2D images for human tracking and identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In the proposed method, 2D features of target object is back-projected into the 3D scene space where its coordinate system is given by a rectangular marker. Then the position and the height are estimated in the 3D space. In addition, geometric error caused by inaccurate projective mapping is corrected by using geometric constraints provided by the marker. The accuracy and the robustness of our technique are verified on the experimental results of several real video sequences from outdoor environments.

• Journal of KIBIM
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• v.7 no.1
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• pp.18-27
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• 2017

Although Industry Foundation Classes (IFC) provide standards for exchanging Building Information Modeling (BIM) data, authoring tools still require manual mapping between BIM entities and IFC classes. This leads to errors and omissions, which results in corrupted data exchanges that are unreliable and thus compromise the validity of IFC. This research explored precedent work by Krijnen and Tamke, who suggested ways to automate the mapping of IFC classes using a machine learning technique, namely anomaly detection. The technique incorporates geometric features of individual components to find outliers among entities in identical IFC classes. This research primarily focused on applying this approach on two architectural BIM models and determining its feasibility as well as limitations. Results indicated that the approach, while effective, misclassified outliers when an IFC class had several dissimilar entities. Another issue was the lack of entities for some specific IFC classes that prohibited the anomaly detection from comparing differences. Future research to improve these issues include the addition of geometric features, using novelty detection and the inclusion of a probabilistic graph model, to improve classification accuracy.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.3
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• pp.14-19
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• 2007

Rapid prototyping (RP) technology can fabricate any 3D physical model regardless of geometric complexity using the layered manufacturing (LM) process. Stereolithography (SL) is the best-known example of RP technology. In general, the surface quality of a raw SL-generated part is unsatisfactory for industrial purposes due to the step artefact created by the LM process. Despite of the increased number of applications for SL parts, this side effect limits their uses. In order to improve their surface quality, additional post-machining finishing, such as traditional grinding, is required, but post-machining is time consuming and can reduce the geometric accuracy of a part. Therefore, this study proposes a post-machining technology combining coating and grinding processes to improve the surface quality of SL parts. Paraffin wax and pulp are used as the coating and grinding materials. By grinding the coating wax only up to the boundary of the part, the surface smoothness can be improved without damaging the surface. Finally, moulding and casting experiments were performed to confirm the suitability of the SL parts finished using the proposed process with rapid tooling (RT) techniques.

• Journal of KSNVE
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• v.9 no.5
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• pp.975-983
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• 1999

This paper describes the dynamic characteristics of the joint structures in case of using the simplified beam model in the F. E. analysis. The modeling errors, when replace the shell with the beam, are investigated through F. E. normal modes analysis. Normal mode analysis were performed to obtain the natural frequencies of the L and T shaped joints with various type of channels. The results were analyzed to access the effects of the models on the accuracy of F.E. analysis by identifying the geometric factors which cause the error. The geometric factors considered are joint angle, channel length, thickness and area ratio of the hollow section to the filled one. The joint stiffness evaluation technique is developed in this study using normal modes analysis with Lumped Mass. With this method, the progressively improved results of F. E. analysis are obtained using the simplified beam model. The static and normal modes analysis are performed with the joint stiffness values obtained by the Kazunori Shimonkakis' virtual stiffness method and the proposed method and these simplified modeling errors are compared.

• Atmosphere
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• v.30 no.4
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• pp.347-360
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• 2020

The automatic algorithm optimized for the Korean Peninsula was developed to detect and track the center of typhoon based on a geometrical method using high-resolution retrieved WISSDOM (WInd Syntheses System using DOppler Measurements) wind and reflectivity data. This algorithm analyzes the center of typhoon by detecting the geometric circular structure of the typhoon's eye in radar reflectivity and vorticity 2D field data. For optimizing the algorithm, the main factors of the algorithm were selected and the optimal thresholds were determined through sensitivity experiments for each factor. The center of typhoon was detected for 5 typhoon cases that approached or landed on Korean Peninsula. The performance was verified by comparing and analyzing from the best track of Korea Meteorological Administration (KMA). The detection rate for vorticity use was 15% higher on average than that for reflectivity use. The detection rate for vorticity use was up to 90% for DIANMU case in 2010. The difference between the detected locations and best tracks of KMA was 0.2° on average when using reflectivity and vorticity. After the optimization, the detection rate was improved overall, especially the detection rate more increased when using reflectivity than using vorticity. And the difference of location was reduced to 0.18° on average, increasing the accuracy.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.129-138
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• 2023

Acquiring precise coordinates of ground targets can be regarded as the key mission of the tactical-level military UAS(Unmanned Aerial System) operations. The coordinates deviations for the ground targets estimated from UAV (Unmanned Aerial Vehicle) images may depend on the sensor specifications and slant ranges between UAV and ground targets. It has an order of several tens to hundreds of meters for typical tactical UAV mission scenarios. In this paper, we propose a scheme that precisely acquires target coordinates from UAS by mapping image pixels to geographical coordinates based on GCP(Ground Control Points). This scheme was implemented and tested from ground control station for UAS. We took images of targets of which exact location is known and acquired the target coordinates using our proposed scheme. The experimental results showed that errors of the acquired coordinates remained within an order of several meters and the coordinates accuracy was significantly improved.

• Geomechanics and Engineering
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• v.35 no.4
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• pp.425-436
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• 2023

An effective tool for researching actual problems in geotechnical and mining engineering is to conduct physical modeling tests using similar materials. A reliable geometric scaled model test requires selecting similar materials and conducting tests to determine physical properties such as the mixing ratio of the mixed materials. In this paper, a method is proposed to determine similar materials that can reproduce target properties using a polynomial model based on experimental results on modeling materials using a gypsum-sand mixture (GSM) to simulate rocks. To that end, a database is prepared using the unconfined compressive strength, elastic modulus, and density of 459 GSM samples as output parameters and the weight ratio of the mixing materials as input parameters. Further, a model that can predict the physical properties of the GSM using this database and a polynomial approach is proposed. The performance of the developed method is evaluated by comparing the predicted and observed values; the results demonstrate that the proposed polynomial model can predict the physical properties of the GSM with high accuracy. Sensitivity analysis results indicated that the gypsum-water ratio significantly affects the prediction of the physical properties of the GSM. The proposed polynomial model is used as a powerful tool to simplify the process of determining similar materials for rocks and conduct highly reliable experiments in a physical modeling test.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• Geomechanics and Engineering
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• v.39 no.1
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• pp.105-113
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• 2024

Recently, electrical resistivity surveys have been used to obtain information related to underground structures including burial structure type and depth. However, various field conditions hinder understanding measured electrical resistance, and thus there is a need to understand how various geometries affect electrical resistance. This study explores the effect of geometric parameters of a structure and electrodes on electrical resistance in the framework of the finite element method. First, an electrical resistance module is developed using the generalized mesh modeling technique, and the accuracy of the module is verified by comparing the results with the analytical solution for a cylindrical electrode with conical tip. Then, 387 cases of numerical analysis including geometric parameters of a buried structure and electrodes are conducted to quantitatively estimate the detection depth under a steady-state current condition. The results show that electrical resistance is increased as (1) shallower burial depth of structure, (2) closer distance between ground electrode and structure, (3) longer horizontal electrode distance. In addition, the maximum detection depth corresponding to converged electrical resistance is deeper as (4) closer distance between ground electrode and structure, (5) shorter horizontal electrode distance. The distribution of the electric potential around the electrodes and underground structure is analyzed to provide a better understanding of the measured electrical resistance. As engineering purpose, the empirical equation is proposed to calculate maximum detection depth as first approximation.

• Advances in nano research
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• v.17 no.1
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• pp.61-73
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• 2024

This paper presents nonlinear vibration analysis of a composite cylindrical shell. The core of the shell is made of functionally graded (FG) porous materials and layers is fabricated of carbon nanotubes (CNTs) reinforced nanocomposites. To increase the accuracy of results, neutral surface position is considered. First-order shear deformation theory is used as displacement field to derive the basic relations of equation motions. In addition, von-Karman nonlinear strains are employed to account geometric nonlinearity and to enhance the results' precision, the exact position of the neutral surface is considered. To governing the partial equations of motion, the Hamilton's principle is used. To reduce the equation motions into a nonlinear motion equation, the Galerkin's approach is employed. After that the nonlinear motion equation is solved by multiple scales method. Effect of various parameters such as volume fraction and distribution of CNTs along the thickness directions, different patterns and efficiency coefficients of porous materials, geometric characteristics and initial conditions on nonlinear to linear ratio of frequency is investigated.