• Computers and Concrete
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• v.6 no.3
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• pp.203-223
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• 2009

Regression analysis (RA) can establish an explicit formula to predict the strength of High-Performance Concrete (HPC); however, the accuracy of the formula is poor. Back-Propagation Networks (BPNs) can establish a highly accurate model to predict the strength of HPC, but cannot generate an explicit formula. Genetic Operation Trees (GOTs) can establish an explicit formula to predict the strength of HPC that achieves a level of accuracy in between the two aforementioned approaches. Although GOT can produce an explicit formula but the formula is often too complicated so that unable to explain the substantial meaning of the formula. This study developed a Backward Pruning Technique (BPT) to simplify the complexity of GOT formula by replacing each variable of the tip node of operation tree with the median of the variable in the training dataset belonging to the node, and then pruning the node with the most accurate test dataset. Such pruning reduces formula complexity while maintaining the accuracy. 404 experimental datasets were used to compare accuracy and complexity of three model building techniques, RA, BPN and GOT. Results show that the pruned GOT can generate simple and accurate formula for predicting the strength of HPC.

• BMB Reports
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• v.44 no.2
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• pp.118-122
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• 2011

Most widely used secondary structure assignment methods such as DSSP identify structural elements based on N-H and C=O hydrogen bonding patterns from X-ray or NMR-determined coordinates. Secondary structure assignment algorithms using limited $C{\alpha}$ information have been under development as well, but their accuracy is only ~80% compared to DSSP. We have hereby developed SABA (Secondary Structure Assignment Program Based on only Alpha Carbons) with ~90% accuracy. SABA defines a novel geometrical parameter, termed a pseudo center, which is the midpoint of two continuous $C{\alpha}s$. SABA is capable of identifying $\alpha$-helices, $3_{10}$-helices, and $\beta$-strands with high accuracy by using cut-off criteria on distances and dihedral angles between two or more pseudo centers. In addition to assigning secondary structures to $C{\alpha}$-only structures, algorithms using limited $C{\alpha}$ information with high accuracy have the potential to enhance the speed of calculations for high capacity structure comparison.

• Korean Journal of Geomatics
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• v.3 no.2
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• pp.129-140
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• 2004

This paper addresses solutions th the challenges of carrier phase integer ambiguity resolution and cycle slip detection/identification, for maintaining high accuracy of an integrated GPS/Pseudolite/INS system. Such a hybrid positioning and navigation system is an augmentation of standard GPS/INS systems in localized areas. To achieve the goal of high accuracy, the carrier phase measurements with correctly estimated integer ambiguities must be utilized to update the system integration filter's states. The contribution presents an effective approach to increase the reliability and speed of integer ambiguity resolution through using pseudolite and INS measurements, with special emphasis on reducing the ambiguity search space. In addition, an algorithm which can effectively detect and correct the cycle slips is described as well. The algorithm utilizes additional position information provided by the INS, and applies a statistical technique known as th cumulative-sun (CUSUM) test that is very sensitive to abrupt changes of mean values. Results of simulation studies and field tests indicate that the algorithms are performed pretty well, so that the accuracy and performance of the integrated system can be maintained, even if cycle slips exist in the raw GPS measurements.

• Journal of IKEEE
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• v.18 no.4
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• pp.536-543
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• 2014

Terrain classification is still a challenging issue in image processing, especially with high resolution satellite images. The well-known obstacles include low accuracy in the detection of targets, especially for the case of man-made structures, such as buildings and roads. In this paper, we present an efficient approach to classify and detect building footprints, foliage, grass and road from high resolution grayscale satellite images. Our contribution is to build a strong classifier using AdaBoost based on a combination of co-occurrence and Haar-like features. We expect that the inclusion of Harr-like feature improves the classification performance of the man-made structures, since Haar-like feature is extracted from corner features and rectangle features. Also, the AdaBoost algorithm selects only critical features and generates an extremely efficient classifier. Experimental result indicates that the classification accuracy of AdaBoost classifier is much higher than that of the conventional classifier using back propagation algorithm. Also, the inclusion of Harr-like feature significantly improves the classification accuracy. The accuracy of the proposed method is 98.4% for the target detection and 92.8% for the classification on high resolution satellite images.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.84-92
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• 2014

In this paper, a novel 5-axis hybrid-kinematic machine tool is introduced and the research results on accuracy improvement of the prototype machine tool are presented. The 5-axis hybrid machine tool is made up of a 3-DOF parallel manipulator and a 2-DOF serial one connected in series. The machine tool maintains high ratio of stiffness to mass due to the parallel structure and high orientation capability due to the serial-type wrist. In order to acquire high accuracy, the methodology of measuring the output shafts by additional sensors instead of using encoder outputs at the motor shafts is proposed. In the kinematic view point, the hybrid manipulator reduces to a serial one, if the passive joints in the U-P serial chain at the center of the parallel manipulator are directly measured by additional sensors. Using the method of successive screw displacements, the kinematic error model is derived. Since a ball-bar is less expensive than a full position measurement device and sufficiently accurate for calibration, the kinematic calibration method of using a ball-bar is presented. The effectiveness of the calibration method has been verified through the simulations. Finally, the calibration experiment shows that the position accuracy of the prototype machine tool has been improved from 153 to $86{\mu}m$.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.175-177
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• 2006

According to the recommendation of International Maritime Organization, the Ministry Of Maritime Affairs and Fisheries (MOMAF) of Korea provides the real time Differential Global Positioning System service using maritime radio beacon from 1999. Due to the benefit of DGPS service, the need of this system is increased from various user groups for acquiring the better accuracy and integrity. Therefore, MOMAF has extended their service to inland by installing the additional 6 DGPS stations. This nationwide DGPS service will be fully deployed at 2007. In addition to the extension of service area, MOMAF has a plan to upgrade their nationwide DGPS to High Accuracy Nationwide DGPS (HANDGPS). The planned HANDGPS service of Korea will be a kind of long range RTK or Wide Area RTK techniques to provide under 1m accuracy and start their service from 2009 using the various broadcasting and communication media like as radio beacon, Wibro, Digital Multimedia Broadcasting, High Speed Packet Data Access. The introduction of nationwide DGPS system of Korea and its evolution plan will be addressed in this paper. The research activities related with HANDGPS in Korea is also presented.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• Structural Engineering and Mechanics
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• v.82 no.2
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• pp.245-258
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• 2022

Many Structural Health Monitoring (SHM) methods have been proposed for structural damage diagnosis and prognosis. However, SHM for pinched hysteretic structures can be problematic due to the high level of nonlinearity. The model-free hysteresis loop analysis (HLA) has displayed notable robustness and accuracy in identifying damage for full-scaled and scaled test buildings. In this paper, the performance of HLA is compared with seven other SHM methods in identifying lateral elastic stiffness for a six-story numerical building with highly nonlinear pinching behavior. Two successive earthquakes are employed to compare the accuracy and consistency of methods within and between events. Robustness is assessed across sampling rates 50-1000 Hz in noise-free condition and then assessed with 10% root mean square (RMS) noise added to responses at 250 Hz sampling rate. Results confirm HLA is the most robust method to sampling rate and noise. HLA preserves high accuracy even when the sampling rate drops to 50 Hz, where the performance of other methods deteriorates considerably. In noisy conditions, the maximum absolute estimation error is less than 4% for HLA. The overall results show HLA has high robustness and accuracy for an extremely nonlinear, but realistic case compared to a range of leading and recent model-based and model-free methods.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.136-149
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• 2023

Objectives: Facial diagnosis is an important part of clinical diagnosis in traditional East Asian Medicine. In this paper, we proposed a model to quantitatively classify cold sensitivity using a fully automated facial image analysis system. Methods: We investigated cold sensitivity in 452 subjects. Cold sensitivity was determined using a questionnaire and the Cold Pattern Score (CPS) was used for analysis. Subjects with a CPS score below the first quartile (low CPS group) belonged to the cold non-sensitivity group, and subjects with a CPS score above the third quartile (high CPS group) belonged to the cold sensitivity group. After splitting the facial images into train/validation/test sets, the train and validation set were input into a convolutional neural network to learn the model, and then the classification accuracy was calculated for the test set. Results: The classification accuracy of the low CPS group and high CPS group using facial images in all subjects was 76.17%. The classification accuracy by sex was 69.91% for female and 62.86% for male. It is presumed that the deep learning model used facial color or facial shape to classify the low CPS group and the high CPS group, but it is difficult to specifically determine which feature was more important. Conclusions: The experimental results of this study showed that the low CPS group and the high CPS group can be classified with a modest level of accuracy using only facial images. There was a need to develop more advanced models to increase classification accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.663-667
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• 2000

The spindle unit is core parts in high precision machine tools. Diverse static and dynamic charateristics of spindle unit are needed for special purpose of machine tools. Specially, high damping ability may be very useful to high precision and high speed spindle unit. But commercial bearing system has very low damping value and high stiffness. In this paper, the combined bearing system with ball-hydrostatic bearing is suggested for high damping spindle unit. The suggested bearing system has 30% damping ability more than general ball bearing's. The average rotational accuracy of spindle with combined bearing in working speed is 24% better than with ball bearing. The unbalance rotating experiment in spindle show that rotating error with combined bearing is only half value of with ball bearing.