• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.243-248
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• 2007

This study proposed a procedure to improve the error defection of attached cadastral maps using digital map data. In addition, this study also provided the direction for the accuracy improvement of attached cadastral maps by comparing analysis methods. - such as centroid, Lee Sallee shape index, and area index. The analysis is performed as follows. First, by using centroid measurement, the center point of cadastral maps and attached cadastral maps are compared. Secondly by using Lee Sallee shape measurement, the location accuracy of range area is investigated. Thirdly, by using area measurement, the range area within allowable error scope is verified. Based on analysis, the discrepancy between cadastral maps and the attacked cadastral maps are detected as follows; 98.2% from Lee Sallee shape index, 41.8% from centroid, 15.4% from area index in the whole error.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.378-391
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• 2002

A 250mm stroke aerostatic stage, which detects position with laser scale and is driven by linear motor, is made and analyzed positioning error in 20$\pm$ 0.5 $^{\circ}C$ controlled atmosphere, aiming at investigating positioning characteristic of ultra-precision stage. We prove this aerostatic stage has a 10nm micro step resolution by experiment. By means of analyzing laser interferometer system, the scale of measuring error is about 0.2-0.4$\mu\textrm{m}$ according to refractive index error from missing the temperature change. To improve laser interferometer system, compensate refractive index error using measuring data from thermocouple. And, confirm 0.10$\mu\textrm{m}$ repeatability and 0.13 $\mu\textrm{m}$ positioning accuracy using the compensating refractive index. Also, we confirm 0.07 ${\mu}{\textrm}{m}$ repeatability of the stage using capacitive displacement sensor.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.7
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• pp.94-100
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• 2010

This paper describes the design and evaluation procedure of an ultra-precision rotary table for freeform generating machined tools. Design of the thrust and journal hydrostatic bearings and experimental evaluation of the table were performed. To get the compact size and less lost motion direct drive servomotor with ultra precision encoder. From the considered design, following performance were confirmed by experiment. The total stiffness of the prototype rotary table was 483.6 $N/{\mu}m$ and 97.6 $N/{\mu}m$ for axial and radial direction, respectively. Rotational accuracy of the table was investigated by capacitive sensor and reversal measurement technique, and 0.10 ${\mu}m$ radial direction and 0.05 ${\mu}m$ axial direction of the rotational accuracy were confirmed. The micro resolution of the table was also investigated with displacement of capacitive sensor, and $0.5/10000^{\circ}$ of micro resolution was confirmed. Index accuracy of the table was evaluated by the autocollimator and polygon mirror, and the $\pm0.39$ arcsec accuracy and $\pm0.16$ arcsec repeatability of the table were confirmed. Those are under the general requirements of ultra precision rotary tables for freeform generating machined tools.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.157-164
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• 2021

The aim of this study is to provide empirical evaluation of the accuracy of data-model fit using growing levels of invariance models. Overall model accuracy of factor solutions was evaluated by the examination of the order for testing three levels of measurement invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (∆𝛘²) between two groups, and root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) were used to evaluate the all-model fits. Factorial invariance result revealed that stability of the models was varying over increasing levels of measurement as a function of variable-to-factor ratio (VTF), subject-to-variable ratio (STV), and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratio (3:1, 6:1, and 9:1), the models started to show accuracy over levels of measurement when STV ratio was 6:1. Yet, the frequency of stability models over 1000 replications increased (from 69% to 89%) as STV ratio increased. The models showed more accuracy at or above 39:1 STV.

• Journal of Animal Science and Technology
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• v.47 no.6
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• pp.1095-1100
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• 2005

For the establishment of prediction strategies of carcass meat quality grade and for the enhancement of prediction accuracy, sixty six Hanwoo steers were ultrasonically tested at 24 months of age. Ultrasonic meat quality grade were predicted by standard ultrasonic image and decision tree method using ultrasonic meat quality index. From the results of decision tree method using ultrasonic meat quality index, it was found that the marbling score was mainly influenced by the distinctness of rib on ultrasound image. Prediction accuracy of meat quality grade by ultrasonic meat quality index was 86.4%, resulting in 7.6% higher accuracy than that by standard ultrasonic image (78.8%).

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.98-106
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• 2016

Remote sensing is an efficient technology for observing and monitoring the land surfaces inaccessible to humans. This research proposes a methodology for improving the accuracy of the land cover classification using the Landsat-8 operational land imager(OLI) image. The proposed methodology consists of the following steps. First, the normalized difference vegetation index(NDVI) and normalized difference water index(NDWI) images are generated from the given Landsat-8 OLI image. Then, a new image is generated by adding both NDVI and NDWI images to the original Landsat-8 OLI image using the layer-stacking method. Finally, the maximum likelihood classification(MLC), and support vector machine(SVM) methods are separately applied to the original Landsat-8 OLI image and new image to identify the five classes namely water, forest, cropland, bare soil, and artificial structure. The comparison of the results shows that the utilization of the layer-stacking method improves the accuracy of the land cover classification by 8% for the MLC method and by 1.6% for the SVM method. This research proposes a methodology for improving the accuracy of the land cover classification by using the layer-stacking method.

• Journal of Ecology and Environment
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• v.35 no.2
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• pp.91-98
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• 2012

This study was performed in order to suggest the possibility of tree species classification using high-resolution QuickBird-2 images spectral characteristics comparison(digital numbers [DNs]) of tree species, tree species classification, and accuracy verification. In October 2010, the tree species of three conifers and eight broad-leaved trees were examined in the areas studied. The spectral characteristics of each species were observed, and the study area was classified by image classification. The results were as follows: Panchromatic and multi-spectral band 4 was found to be useful for tree species classification. DNs values of conifers were lower than broad-leaved trees. Vegetation indices such as normalized difference vegetation index (NDVI), soil brightness index (SBI), green vegetation index (GVI) and Biband showed similar patterns to band 4 and panchromatic (PAN); Tukey's multiple comparison test was significant among tree species. However, tree species within the same genus, such as $Pinus$ $densiflora-P.$ $rigida$ and $Quercus$ $mongolica-Q.$ $serrata$, showed similar DNs patterns and, therefore, supervised classification results were difficult to distinguish within the same genus; Random selection of validation pixels showed an overall classification accuracy of 74.1% and Kappa coefficient was 70.6%. The classification accuracy of $Pterocarya$ $stenoptera$, 89.5%, was found to be the highest. The classification accuracy of broad-leaved trees was lower than expected, ranging from 47.9% to 88.9%. $P.$ $densiflora-P.$ $rigida$ and $Q.$ $mongolica-Q.$ $serrata$ were classified as the same species because they did not show significant differences in terms of spectral patterns.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.269-276
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• 2012

The objective of this short communication is to introduce several evaluation methods to crop model users because the evaluation of crop model performance is an important step to develop or select crop model. In this paper, mean error, mean absolute error, index of agreement, root mean square error, efficiency of model, accuracy factor and bias factor were explained and compared in terms of dimension and observed number. Efficiency of model and index of agreement are dimensionless and independent of number of observation. Relative root mean square, accuracy factor and bias factor are dimensionless and not independent of number of observation. Mean error and mean absolute error are affected by dimension and number of observation.

• Physical Therapy Korea
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• v.12 no.3
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• pp.39-45
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• 2005

Tracking is an experimental paradigm that can be used to study information processing in continuous movements involving accurate, ongoing control of motor performance. The purpose of this study was to identify the effects of knee tracking performance. Six patients with hemiplegia and six age-matched controls participated in the study. The tracking test was administrated. It was composed with regular ranges of $0^{\circ}C$ to $40^{\circ}C$ and randomized range .2 to .4 Hz. Using the Mann-Whitney U test, a comparison was made between subjects who had suffered from stroke and subjects who were well coordinated. The Wilcoxon Matched Pairs Signed Ranks Test was used to compare and analyze the paretic and nonparetic sides of the stroke patients. The results of study were as follows: accuracy index of the tracking test was significantly higher on the control side than paretic and nonparetic sides. Accuracy index scores were significantly higher for nonparetic sides with stroke compared with paretic sides with stroke. This study shows tracking is impaired in paretic and nonparetic knee of subjects with stroke.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.9-23
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• 2024

In this study, we propose a method to improve the classification accuracy of body mass index (BMI) estimation techniques based on three-dimensional gait data. In previous studies on BMI estimation techniques, the classification accuracy was only about 60%. In this study, we identify the reasons for the low BMI classification accuracy. According to our analysis, the reason is the use of the undersampling technique to address the class imbalance problem in the gait dataset. We propose applying oversampling instead of undersampling to solve the class imbalance issue. We also demonstrate the usefulness of anthropometric and spatiotemporal features in gait data-based BMI estimation techniques. Previous studies evaluated the usefulness of anthropometric and spatiotemporal features in the presence of undersampling techniques and reported that their combined use leads to lower BMI estimation performance than when using either feature alone. However, our results show that using both features together and applying an oversampling technique achieves state-of-the-art performance with 92.92% accuracy in the BMI estimation problem.