• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.237-243
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• 2012

In this paper, an atmospheric effect of repetitive measurements of X-band (9.65 GHz) arc-rail type GB-SAR (ArcSAR) system was quantitatively analyzed. Four artificial triangular trihedral corner reflectors as stationary targets for getting stable back scattered signal during 43 hours continually. The results of the analysis showed that the phase of those stationary targets had changed maximum of 5 radian (12.4 mm) and total RMS error had was 1.62 radian (4 mm) during 65 repeated measuring time. The refractive index of air which was calculated using the temperature;humidity and pressure of atmosphere showed very close relationship with the phase difference. We could check the atmospheric correction was fulfilled by the correction of an atmospheric effect using refractive index during the selected 16 hours period showed that RMS error was dropped from 1.74 radian (4.3 mm) to 0.10 radian (0.24 mm).

• Journal of Korean Foot and Ankle Society
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• v.16 no.1
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• pp.53-57
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• 2012

Purpose: To study computerized measurements of angular parameters on 100% and 150% resized digital radiography of hallux valgus deformity Materials and Methods: 30 digital radiography of standing foot anteroposterior view of hallux valgus patients were included. Two observers(A, B) independently measured hallux valgus angle (HVA), 1-2 intermetatarsal angle (IMA), and distal metatarsal articular angle (DMAA) in two times on both 100%-size and 150% magnified images respectively, using computerized measurement software tools. The results were interpreted with the statistical software program, Statistical Analysis System, version 9.2. Results: In repeated measurements of each observer, measurements on 150% magnified image showed no differences of all three parameters and with 100%-size image, there were differences of HVA (observer A) and 1-2 IMA (observer B) (p>0.05). When testing interobserver reliability, both observers showed differences in measurement of HVA and DMAA (p<0.05), but no differences in measurement of 1-2 IMA in both images. Within the 95% confidence interval, limits of error of measurements between two observers on HVA, IMA and DMAA were $2.7^{\circ}$ $1.4^{\circ}$ and $5.0^{\circ}$ respectively in 100%-size images, and $2.6^{\circ}$, $1.6^{\circ}$ and $4.7^{\circ}$ respectively in 150% magnified images. Conclusion: In computerized measurements for angular parameters of hallux valgus with digital radiography, 150% magnified images showed intraobserver reliability. Both 100% and 150% magnified images failed to show interobserver reliability. Measurement of 1-2 IMA in both 100% and 150% images showed less interobserver error.

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1360-1367
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• 2016

This paper introduces a boron meter with improved accuracy compared with other commercially available boron meters. Its design includes a new fitting function and a multi-detector. In pressurized water reactors (PWRs) in Korea, many boron meters have been used to continuously monitor boron concentration in reactor coolant. However, it is difficult to use the boron meters in practice because the measurement uncertainty is high. For this reason, there has been a strong demand for improvement in their accuracy. In this work, a boron meter evaluation model was developed, and two approaches were considered to improve the boron meter accuracy: the first approach uses a new fitting function and the second approach uses a multi-detector. With the new fitting function, the boron concentration error was decreased from 3.30 ppm to 0.73 ppm. With the multi-detector, the count signals were contaminated with noise such as field measurement data, and analyses were repeated 1,000 times to obtain average and standard deviations of the boron concentration errors. Finally, using the new fitting formulation and multi-detector together, the average error was decreased from 5.95 ppm to 1.83 ppm and its standard deviation was decreased from 0.64 ppm to 0.26 ppm. This result represents a great improvement of the boron meter accuracy.

• Physical Therapy Rehabilitation Science
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• v.3 no.2
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• pp.134-141
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• 2014

Objective: The purpose of this study was to compare with different distance across three conditions in stroke survivors with the grading of cognitive state. Design: Cross-sectional study. Methods: Twelve stroke patients who agreed to active participation were included. Participants were allotted to normal cognitive (CN) group (n=7) and cognitive impairment (CI) group (n=5) and then walked on a self-paced walkway at three conditions on the Time Up and Go (TUG) test and the 6 minute walk test (6MWT): 1) walking with your comfortable speed, 2) walking while carrying a tray with glasses, 3) walking with a verbal cognitive task. The TUG test was repeated three successful times on each condition. For the 6MWT, participants were tested one time. Results: The CI group walked slower than the CN group at the three conditions on the TUG test. However, there was no significant difference between two groups to each condition. A significant effect of dual tasking was found only in error of verbal cognitive task condition for the TUG test (p<0.05). On the 6MWT, the participants in the CI group walked short distance rather than the CN group (p<0.05). There were significant differences between two groups not only at all conditions but also at error of verbal cognitive task condition as well (p<0.05). Conclusions: To consider the results of different distances such as the TUG test and the 6MWT, we think that exercises in long distance would be more effective to patients with CI. Those would be improved patient's endurance in cognitive problem.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.6
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• pp.91-97
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• 2019

Rotating machining unit is a revolutionary product that can process worm shaft or spiral shaft with fast and precise, a rotary type cutting tool, which is attached to automatic lathe and processes spiral groove on outer circumference of round bar. In this work, a study on micro tooth shape modification method of driving gear train in the rotating machining unit was presented. To observe the effect on power transmission characteristics of the driving gear pair, visualize the gear meshing condition and the load distribution on the gear teeth by using the professional gear train analysis program RomaxDesigner. By comparing the repeated analysis results, the effect of micro tooth shape modification on power transmission characteristics on driving gear can be summarized. The optimized gears were fabricated and measured by precision tester as a validation in this research.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.4
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• pp.93-99
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• 2019

A cross drilling/milling Unit is an important mechanical part which is widely used in many kinds of machining tool, and various gear trains with good accuracy and reliability features are widely used in power transmission systems. A study on a novel power transmission optimization method for driving gear trains in cross drilling/milling units is presented in this paper. A commercial program for gear system simulation, Romax Designer, was used in this research to intuitively observe the gear meshing and the load distribution conditions on the gear teeth. We obtained the optimal modification value through comparing the results of repeated experiments. For validation, optimized gears were fabricated and then measured with a precision tester.

• The korean journal of orthodontics
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• v.51 no.2
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• pp.77-85
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• 2021

Objective: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. Methods: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction. Results: The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm. Conclusions: Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.617-624
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• 2023

Recently, miniaturization and low power consumption of electronic products and improved efficiency and power factor improvement have become a matter of great interest. In this paper, an AC-DC converter based on PWM control was designed and made. The AC-DC converter is designed with a structure in which one rectifier circuit and one output voltage control circuit are connected in series. The rectifier circuit is a diode-based single phase full-wave current circuit and the output voltage control circuit is a DC-DC conversion circuit based on PWM control. Arduino was used as the main control device for PWM control, and LCD was configured at the output stage so that the control result could be checked. The error between the output voltage displayed on the oscilloscope and LCD and the target output voltage was confirmed through repeated experiments with the test circuit, and the validity of the proposed design methodology was confirmed by showing an error rate of about 5% based on the oscilloscope measurement value.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.169-180
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• 2023

The performance of underwater acoustic communication is greatly affected by multipath propagation and Doppler spread. This paper proposes a new communication technique, the Triangle Spread Carrier (TSC) technique, by modifying the existing Sweep Spread Carrier (SSC) technique that is strong in a multipath propagation environment. The proposed TSC technique is a form in which the up-chirp and down-chirp signals have repeated carriers, and each correlation function characteristic is used to estimate and correct the Doppler shift frequency of the receiving signal. To demonstrate the performance of the proposed TSC technique, we present the results of simulations using underwater channel simulators and sea trial conducted in the East Sea. When demodulating using only the estimated Doppler shift frequency as a result of the sea trial, the uncoded bit error rate was up to 0.194, but when the proposed method was applied, the uncoded bit error rate was reduced to 0.001.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.6-11
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• 2011

This paper proposes a new collision risk assessment system for pedestrians's safety. Monte Carlo Simulation (MCS) method is a one of the most popular method that rely on repeated random sampling to compute their result, and this method is also proper to get the results when it is unfeasible or impossible to compute an exact result. Nevertheless its advantages, it spends much time to calculate the result of some situation, we apply not only MCS but also Neural Networks in this problem. By Monte carlo method, we make some sample data for input of neural networks and by using this data, neural networks can be trained for computing collision probability of whole area where can be measured by sensors. By using this trained networks, we can estimate the collision probability at each positions and velocities with high speed and low error rate. Computer simulations will be shown the validity of our proposed method.