• Journal of Elementary Mathematics Education in Korea
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• v.11 no.2
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• pp.199-216
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• 2007

The purpose of the present study was to analyze the types of errors made by students in the figure domain at the stages of first and second semester of 4th grade in elementary school that include the definition and the properties of figure, to identify the causes of such errors, and to help the teaching of the 4th grade figure domain. When the trends of errors were analyzed for each question, the most common error was the wrong use of theorems or definitions, and its main causes were student's low level in geometry and limited concept images. Thus, it is necessary to make them have clear understanding of these concepts and terms and students need to do various activities suitable for their level in geometry. In addition, figure images presented in the mathematics textbooks and the mathematics practice book have limitations. Thus, figures of various positions and lengths should be presented and described accurately, and the books should be redesigned for various practical activities.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.79-87
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• 2016

As 3D geospatial information is demanded, terrestrial laser scanners which can obtain 3D model of objects have been applied in various fields such as Building Information Modeling (BIM), structural analysis, and disaster management. To acquire precise data, performance evaluation of a terrestrial laser scanner must be conducted. While existing 3D surveying equipment like a total station has a standard method for performance evaluation, a terrestrial laser scanner evaluation technique for users is not established. This paper categorizes and analyzes error sources which generally occur in terrestrial laser scanning. In addition to the prior researches about categorizing error sources of terrestrial Laser scanning, this paper evaluates the error sources by the actual field tests for the smooth in-situ applications.The error factors in terrestrial laser scanning are categorized into interior error caused by mechanical errors in a terrestrial laser scanner and exterior errors affected by scanning geometry and target property. Each error sources were evaluated by simulation and actual experiments. The 3D coordinates of observed target can be distortedby the biases in distance and rotation measurement in scanning system. In particular, the exterior factors caused significant geometric errors in observed point cloud. The noise points can be generated by steep incidence angle, mixed-pixel and crosstalk. In using terrestrial laser scanner, elaborate scanning plan and proper post processing are required to obtain valid and accurate 3D spatial information.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.735-739
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• 2013

The error motion of a machine tool spindle directly affects the surface errors of machined parts. Spindle motion errors such as three translational motions and two rotational motions are undesirable. These are usually due to the imperfectness of bearings, stiffness of spindle, assembly errors, and external force or unbalance of rotors. The error motions of the spindle need to be reduced for achieving the desired performance. Therefore, the level of error motion needs to be estimated during the design and assembly process of the spindle. In this study, an estimation method for five degree-of-freedom (5 DOF) error motions for a spindle with an angular contact ball bearing is suggested. To estimate the error motions of the spindle, the waviness of the inner-race of bearings and an external force model were used as input data. The estimation model considers the geometric relationship and force equilibrium of the five DOFs. To calculate the error motions of the spindle, not only the imperfections of the shaft and bearings but also driving elements such as belt pulley and direct driving motor systems are considered.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.4
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• pp.295-301
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• 2016

The out-of-squareness is one of the error sources that affect the positioning accuracy of machine tools and coordinate measuring machines. Laser interferometer is widely used to measure the position and angular errors, and can measure the squareness using an optical square. However, the squareness measurement using the laser interferometer is difficult, as compared to other errors due to complicated optics setup and Abbe's error occurrence. The effect of out-of-squareness mainly appears at the face-diagonal of the movable plane. The diagonal displacements are also affected by the position dependent geometric errors. In this study, the squareness estimation techniques via diagonal displacement measurement using the laser interferometer without an optical square were proposed. For accurate estimation and measurement time reduction, the errors selected from proposed discriminant were measured. Discrepancy between the proposed technique with the laser interferometer (with an optical square) result was $0.6{\mu}rad$.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.2
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• pp.173-180
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• 1994

One can see more and more photograrmmetric applications dealing with the extraction of information from images obtained with CCD (Charge Coupled Device) camera scanners. In order for this information to be useful, the scanning errors of scanners must be known through a calibration. Investigation of this study is given to the detailed procedure of the correction for scanning errors created during the scanning of photographs with CCD camera scanner using the three kinds of high resolution reseal plates prepared. The geometric corrected digital images for scanning errors were generated and the accuracy of the resulting new images for each types of plates were checked comparing its image coordinates with there corresponding ground coordinates for the check points.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.483-496
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• 2008

Qualified ground control points (GCPs) are required to construct a digital elevation model (DEM) from a pushbroom stereo pair. An inverse geolocation algorithm for extracting GCPs from ERS SAR data and the SRTM DEM was recently developed. However, not all GCPs established by this method are accurate enough for direct application to the geometric correction of pushbroom images such as SPOT, IRS, etc, and thus a method for selecting and removing inaccurate points from the sets of GCPs is needed. In this study, we propose a method for evaluating GCP accuracy and winnowing sets of GCPs through orientation modeling of pushbroom image and validate performance of this method using SPOT stereo pair of Daejon City. It has been found that the statistical distribution of GCP positional errors is approximately Gaussian without bias, and that the residual errors estimated by orientation modeling have a linear relationship with the positional errors. Inaccurate GCPs have large positional errors and can be iteratively eliminated by thresholding the residual errors. Forty-one GCPs were initially extracted for the test, with mean the positional error values of 25.6m, 2.5m and -6.1m in the X-, Y- and Z-directions, respectively, and standard deviations of 62.4m, 37.6m and 15.0m. Twenty-one GCPs were eliminated by the proposed method, resulting in the standard deviations of the positional errors of the 20 final GCPs being reduced to 13.9m, 8.5m and 7.5m in the X-, Y- and Z-directions, respectively. Orientation modeling of the SPOT stereo pair was performed using the 20 GCPs, and the model was checked against 15 map-based points. The root mean square errors (RMSEs) of the model were 10.4m, 7.1m and 12.1m in X-, Y- and Z-directions, respectively. A SPOT DEM with a 20m ground resolution was successfully constructed using a automatic matching procedure.

• Journal of the Ergonomics Society of Korea
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• v.7 no.2
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• pp.31-44
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• 1988

If an error occurs in the automatic mode when the advanced teleoperator system performs a task in hostile environment then the automatic mode changes into the manual mode. The operation by the control program and the operation by a human recover the error in the manual mode. The system resumes the automatic mode and continues the given task. It is necessary to improve the manual mode in order to make the best use of a man-robot system, as a part of the human interface technique. Therefore, the error recovery task is performed by combining the operation by the control program representing autonomy of a robot and the operation by a human representing versatility of a human operator effectively in the view point of human factors engineering. The geometric inverse kinematics is used for the calculation of the robot joint values in the operation by the control program. The singularity operation error and the parameter operation error often occur in this procedure. These two operation errors increase the movement time of the robot and the coordinate reading time, during the error recovery task. A singularity algorithm, parameter algorithm and fuzzy control are studied so as to remove the disadvantages of geometric inverse kinematics. And the geometric straight line motion is studied so as to improve the disadvantages of the operation by a human.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.69-82
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• 1998

SAR imagery can overcome the limitations of electro-optical sensor imagery and provide us Information which plays a supplementary role. But it is necessary to remove a variety of geometric errors in SAR imagery. An accurate geometric correction of SAR imagery is not easy task to achieve, though some techniques and theories are introduced. We also have difficulties such as transformation problem between 'International' ellipsoid in Radarsat system and 'Bessel' ellipsoid. Two widely used correction method, one is made by simulated image, and the other by collinearity equation, usually use DEM. In this study, the merits and demerits of geocoding methods respectively and the effective method for Korean terrain were found.

• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.