• Steel and Composite Structures
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• v.31 no.6
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• pp.601-615
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• 2019

In cold-formed steel (CFS) structures, such as trusses, wall frames and columns, the use of back-to-back built-up CFS angle sections are becoming increasingly popular. In such an arrangement, intermediate fasteners are required at discrete points along the length, preventing the angle-sections from buckling independently. Limited research is available in the literature on the axial strength of back-to-back built-up CFS angle sections. The issue is addressed herein. This paper presents the results of 16 experimental tests, conducted on back-to-back built-up CFS screw fastened angle sections under axial compression. A nonlinear finite element model is then described, which includes material non-linearity, geometric imperfections and explicit modelling of the intermediate fasteners. The finite element model was validated against the experimental test results. The validated finite element model was then used for the purpose of a parametric study comprising 66 models. The effect of fastener spacing on axial strength was investigated. Four different cross-sections and two different thicknesses were analyzed in the parametric study, varying the slenderness ratio of the built-up columns from 20 to 120. Axial strengths obtained from the experimental tests and finite element analysis were used to assess the performance of the current design guidelines as per the Direct Strength Method (DSM); obtained comparison showed that the DSM is over-conservative by 13% on average. This paper has therefore proposed improved design rules for the DSM and verified their accuracy against the finite element and test results of back-to-back built-up CFS angle sections under axial compression.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2853-2864
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• 2018

Discriminant analysis predicts a class label of a new observation with an unknown label, using information from the existing labeled data. Hence, observed labels play a critical role in the analysis and we usually assume that these labels are correct. If the observed label contains an error, the data has label noise. Label noise can frequently occur in real data, which would affect classification performance. In order to resolve this, a comparative study was carried out using simulated data with label noise. In particular, we considered 4 different classification techniques such as LDA (linear discriminant analysis classifiers), QDA (quadratic discriminant analysis classifiers), KNN (k-nearest neighbour), and SVM (support vector machine). Then we evaluated each method via average accuracy using generated data from various scenarios. The effect of label noise was investigated through its occurrence rate and type (noise location). We confirmed that the label noise is a significant factor influencing the classification performance.

• Journal of the Korean Physical Society
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• v.73 no.12
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• pp.1821-1826
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• 2018

Uniformity is a key feature of state-of-the-art infrared focal planed array (IRFPA) and infrared imaging system. Unlike traditional infrared telescope facility, a ground-based infrared radiant characteristics measurement system with an IRFPA not only provides a series of high signal-to-noise ratio (SNR) infrared image but also ensures the validity of radiant measurement data. Normally, a long integration time tends to produce a high SNR infrared image for infrared radiant characteristics radiometry system. In view of the variability of and uncertainty in the measured target's energy, the operation of switching the integration time and attenuators usually guarantees the guality of the infrared radiation measurement data obtainted during the infrared radiant characteristics radiometry process. Non-uniformity correction (NUC) coefficients in a given integration time are often applied to a specified integration time. If the integration time is switched, the SNR for the infrared imaging will degenerate rapidly. Considering the effect of the SNR for the infrared image and the infrared radiant characteristics radiometry above, we propose a-wide-dynamic-range NUC algorithm. In addition, this essasy derives and establishes the mathematical modal of the algorithm in detail. Then, we conduct verification experiments by using a ground-based MWIR(Mid-wave Infared) radiant characteristics radiometry system with an Ø400 mm aperture. The experimental results obtained using the proposed algorithm and the traditional algorithm for different integration time are compared. The statistical data shows that the average non-uniformity for the proposed algorithm decreased from 0.77% to 0.21% at 2.5 ms and from 1.33% to 0.26% at 5.5 ms. The testing results demonstrate that the usage of suggested algorithm can improve infrared imaging quality and radiation measurement accuracy.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.2
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• pp.1-11
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• 2023

Objective : The purpose of this study was to investigate the effects of computerized cognitive rehabilitation on the attention of children with autism spectrum disorder (ASD). Methods : A multiple-baseline design was used in combination with a single-subject experimental research design. A total of 15 sessions were conducted three times a week, each lasting for 30 minutes. The maintenance and selective attention tests in the attention area of the computerized cognitive rehabilitation program were evaluated in random order after each session was completed. To evaluate the participants' selective attention, star cancellation tests was performed as pre- and post-tests. Results : After the computerized cognitive rehabilitation intervention, the accuracy of the participants' attention improved in terms of the maintenance and selective attention tests. In the analysis involving the two standard deviation bands, participants 1 and 2 showed a significant improvement, whereas participant 3 did not show a significant improvement, although the average value improved. Conclusion : The results of this study confirmed that cognitive rehabilitation involving a computerized cognitive rehabilitation program had a positive effect on the attention of three children with ASD.

• Journal of Drive and Control
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• v.21 no.3
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• pp.46-55
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• 2024

In the agricultural machinery field, load analysis is mostly done through field tests. However, field tests are time-consuming and costly. There are also limitations in test conditions due to weather conditions. To overcome these environmental limitations, research on load analysis through simulation in a virtual environment is actively being conducted. This study aimed to select the most appropriate soil particle size for modeling by analyzing the effect of soil particle size on the prediction of draft force of the implement using simulation and soil particle modeling in a virtual environment with the discrete element method (DEM) software. The accuracy was verified by simulating the draft force for the same moving speed by soil particle size. For soil particle modeling, DEM soil modeling was performed by designing soil property measurement procedure. Soil particle correction was performed with a virtual vane shear test. Average DEM simulation results showed an error of 27.39% (19.43~40.66%) compared to actual measured data. The possibility of improvement was confirmed through additional research. Results of this study provide useful information for selecting soil particle size in soil modeling using DEM from the perspective of agricultural machinery research.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.606-612
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• 2019

In this study, to estimate the occurrence of frost that has a negative effect on th growth of crops, we constructed to the statistical model. We factored such various meteorological elements as the minimum temperature, temperature at 18:00, temperature at 21:00, temperature at 24:00, average wind speed, wind speed at 18:00, wind speed at 21:00, amount of cloud, amount of precipitation within 5 days, amount of precipitation within 3 days, relative humidity, dew point temperature, minimum grass temperature and ground temperature. Among the diverse variables, the several weather factors were selected for frost occurrence estimation model using statistical methods: T-test, Variable importance plot of Random Forest, Multicollinearity test, Akaike Informaiton Criteria, and Wilk's Lambda values. As a result, the selected meteorological factors were the amount of cloud, temperature at 24:00, dew point temperature, wind speed at 21:00. The accuracy of the frost occurrence estimation model using Random Forest was 70.6%. When it applied to the main production areas of vegetables, a estimation accuracy of the model was 65.2 and 78.6%.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.967-976
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• 2009

In this paper, we propose an automatic lower extremity vessel extraction based on rigid registration and bone elimination techniques in CT and CT angiography images. First, automatic partitioning of the lower extremity based on the anatomy is proposed to consider the local movement of the bone. Second, rigid registration based on distance map is performed to estimate the movement of the bone between CT and CT angiography images. Third, bone elimination and vessel masking techniques are proposed to remove bones in CT angiography image and to prevent the vessel near to bone from eroding. Fourth, post-processing based on vessel tracking is proposed to reduce the effect of misalignment and noises like a cartilage. For the evaluation of our method, we performed the visual inspection, accuracy measures and processing time. For visual inspection, the results of applying general subtraction, registered subtraction and proposed method are compared using volume rendering and maximum intensity projection. For accuracy evaluation, intensity distributions of CT angiography image, subtraction based method and proposed method are analyzed. Experimental result shows that bones are accurately eliminated and vessels are robustly extracted without the loss of other structure. The total processing time of thirteen patient datasets was 40 seconds on average.

• Imaging Science in Dentistry
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• v.34 no.3
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• pp.151-157
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• 2004

Purpose : To evaluate the quantitative accuracy of three-dimensional (3D) images by means of comparing distance measurements on the 3D images with direct measurements of dry human skull according to slice thickness and scanning modes. Materials and Mathods : An observer directly measured the distance of 21 line items between 12 orthodontic landmarks on the skull surface using a digital vernier caliper and each was repeated five times. The dry human skull was scanned with a Helical CT with various slice thickness (3, 5, 7 mm) and acquisition modes (Conventional and Helical). The same observer measured corresponding distance of the same items on reconstructed 3D images with the internal program of V-works 4.0/sup TM/(Cybermed Inc., Seoul, Korea). The quantitative accuracy of distance measurements were statistically evaluated with Wilcoxons' two-sample test. Results: 11 line items in Conventional 3 mm, 8 in Helical 3mm, 11 in Conventional 5mm, 10 in Helical 5mm, 5 in Conventional 7mm and 9 in Helical 7mm showed no statistically significant difference. Average difference between direct measurements and measurements on 3D CT images was within 2mm in 19 line items of Conventional 3mm, 20 of Helical 3mm, 15 of Conventional 5mm, 18 of Helical 5mm, II of Conventional 7mm and 16 of Helical 7mm. Conclusion: Considering image quality and patient's exposure time, scanning protocol of Helical 5mm is recommended for 3D image analysis of the skull in CT.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.11-18
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• 2016

Since GNSS signals get blocked by buildings in urban canyons or narrow alleys, it is very difficult to secure a enough number of visible satellites for satellite navigation in those poor signal-reception environments. In those situations, one cannot get their coordinates or obtain accurate positions. In this study, a couple of strategies for improving positioning accuracy in urban canyons were developed and their performance was verified. First of all, we combined GPS and GLONASS measurements together and devised algorithms to quality-control observed signals and eliminate outliers. Also, a new multipath reduction scheme was applied to minimize its effect by utilizing SNR values of the observed signals. For performance verification of the developed technique, a narrow alley of 10m width located near the back gate of the Inha University was selected as the test-bed, and then we conducted static and kinematic positioning at four pre-surveyed points. We found that our new algorithms produced an 45% improvement in an open-sky environment compared with the positioning result of a low-cost u-blox receiver. In the alleys, 3-D accuracy improved by an average of 37%. In the case of kinematic positioning, especially, biases showing up in regular receivers got eliminated significantly through our new filtering algorithms.

• Journal of Food Hygiene and Safety
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• v.33 no.2
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• pp.110-117
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• 2018

The aim of this study was to develop an analytical method for the quantification of diazepam residues in fishery products, using liquid and gas chromatography-tandem mass spectrometry (LC-MS/MS and GC-MS/MS). The sample utilized in the study was extracted from the fish sample (crucian carp) using 0.1% formic acid in acetonitrile. For the utilization of the purification process, the dispersive solid phase extraction (dSPE) was used for LC-MS/MS, dSPE and SPE was used for GC-MS/MS, respectively. To be sure, the standard calibration curves showed a good linearity as the noted correlation coefficients, $r^2$ was > 0.99. The average recoveries for accuracy ranged in 99.8~124% for the samples which were fortified at three different levels (0.001, 0.002 and 0.010 mg/kg). The correlation coefficient for the precision effect was measured at a range of 4.01~11.8%. The limit of detection (LOD) for the diazepam analysis was 0.0004 mg/kg, and the limit of the quantification (LOQ) was 0.001 mg/kg. The proposed analytical method was characterized with a high accuracy and acceptable sensitivity to meet the established Codex Alimentarius Commission (CAC/GL71-2009) guideline requirements. We therefore established the optimal analysis method for the determination of diazepam in the fishery products using LC-MS/MS and GC-MS/MS. It would be applicable to analyze the diazepam residues in fishery products in further studies on this subject.