• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.163-168
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• 2009

Given the specific mean shift outlier model, the standard approaches to obtaining test statistics for outliers are discussed. Accuracy of outlier tests is investigated using subset curvatures. These subset curvatures appear to be reliable indicators of the adequacy of the linearization based test. Also, we consider obtaining graphical summaries of uncertainty in estimating parameters through confidence curves. The results are applied to the problem of assessing the accuracy of outlier tests.

• Advances in concrete construction
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• v.13 no.5
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• pp.395-410
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• 2022

This study collected the results of material tests and full-scale pumping tests using 127 types of concrete mixtures with compressive strength ranging from 24 to 200 MPa. The results of 242 material tests showed high correlations between the viscosity of the lubricating layer and concrete, between the slump and the yield stress of concrete, between the water-binder ratio and the viscosity of lubricating layer, and between the time required to reach 500 mm of slump flow and concrete viscosity. Based on these correlations, pumpability was predicted using 101 pumping test conditions, and their accuracy was compared to the actual test results. When the rheological properties of concrete and the lubricating layer were directly measured, the prediction result showed the highest accuracy. A high accuracy can be achieved when the measured viscosity of the lubricating layer, a key determinant of concrete pumpability, is reflected in the prediction of pumpability. When measuring rheological properties is difficult, the slump test can be used to quantitatively predict the pumpability despite the lower accuracy than those of other prediction methods.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.657-660
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• 2015

Background: A diagnosis of H. pylori infection can be made by invasive or non-invasive methods. Several noninvasive diagnostic tests based on the detection of H. pylori stool antigen (HpSA) have been developed. The Genx H. pylori stool antigen card test is a new rapid, non-invasive test that is based on monoclonal immunochromatographic assay. The aim of this study was to determine its sensitivity, specificity, and diagnostic accuracy for diagnosing H. pylori infection in adult patients. Materials and Methods: A total of 162 patients were included in the study. A gastric biopsy was collected for histopathology and rapid urease testing. Stool specimens for HpSA testing were also collected. Patients were considered H. pylori positive if two invasive tests (histological and rapid urease tests) were positive. Results: Using the reference test, 50.6% of the samples were positive for H. pylori infection. The Genx H. pylori antigen test was positive in 19.7% of patients. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of the Genx H. pylori antigen test were 51.6%, 96.0%, 88.8%, 76.1%, and 79.0%, respectively. Conclusions: The Genx H. pylori stool antigen card test is a new non-invasive method that is fast and simple to perform but provides less reliable results.

• Journal of Ocean Engineering and Technology
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• v.16 no.6
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• pp.25-31
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• 2002

A system identification method is introduced to increase the prediction accuracy of a ship's maneuverability in PMM test, analysis. To improve the accuracy of linear hydrodynamic coefficients, the analysis techniques of pure sway and yaw tests are developed, and confirmed. In the analysis of sway tests, accuracy to linear hydrodynamic coefficients depends on the frequency of sway motion. To obtain nonlinear hydrodynamic coefficients for large drift angles, a combined yaw test is introduced. Using this system identification method, runs of PMM test can be reduced while retaining sufficient accuracy, compared to the Fourier integration method. Through the comparisons with sea trial results and the Fourier integration method, the accuracy and efficiency of the newly proposed system identification method, based on least square method, has been validated.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.619-632
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• 2023

Purpose: The main function of INS (Inertial Navigation System) is to measure the position of an armed vehicle and its performance is confirmed through the positioning accuracy test of Korean Defense Standards (KDS). The current standards, however, do not provide clear test methods and the conditions for performing positioning accuracy tests. Accordingly, the purpose of this study is to develop a new method for positioning accuracy test which would be effective. Methods: In this study, a new INS positioning accuracy test method is suggested based on the analysis of test data collected through a statistical experiment known as central composite design. For the positioning accuracy experiment of K105A1, a self-propelled artillery, two factors of driving velocity and driving distance are considered. Results: Based on the analysis of experimental data, a regression model for the positioning error is fitted and the positioning accuracy test of INS is so developed to maximize the positioning error. The standard proximity rate is used as an additional test criterion to evaluate the performance level of INS. Conclusion: The proposed new positioning accuracy test for INS has the advantage of finding the nonconforming items effectively. It is also expected to be utilized for the other similar INS positioning accuracy tests.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.435-441
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• 2012

This paper provides simulation-based results of effect analysis of sample size and sampling periods on accuracy of reliability estimation methods using multiple comparisons with analysis of variance. Sum of squared errors in estimated reliability measures were evaluated through applying seven estimation methods for one-shot systems to simulated quantal-response data. Analysis of variance was implemented to investigate change in these errors according to variations of sample size and sampling periods for each estimation method, and then the effect analysis on accuracy in reliability estimation was performed using multiple comparisons based on sample size and sampling periods. An efficient way to allocate both sample size and sampling periods for reliability estimation tests of one-shot systems is proposed in this paper from the effect analysis results.

• Structural Engineering and Mechanics
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• v.68 no.1
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• pp.17-38
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• 2018

In this paper, we compare and assess the performance of the standard 3- and 6-node MITC shell elements (Lee and Bathe 2004) with the recently developed MITC triangular elements (Lee et al. 2014, Jeon et al. 2014, Jun et al. 2018) which were based on the partitions of unity approximation, bubble node, or both. The convergence behavior of the shell elements are measured in well-known benchmark tests; four plane stress tests (mesh distortion test, cantilever beam, Cook's skew beam, and MacNeal beam), two plate tests (Morley's skew plate and circular plate), and six shell tests (curved beam, twisted beam, pinched cylinder, hemispherical shells with or without hole, and Scordelis-Lo roof). To precisely compare and evaluate the solution accuracy of the shell elements, different triangular mesh patterns and distorted element mesh are adopted in the benchmark problems. All shell finite elements considered pass the basic tests; namely, the isotropy, the patch, and the zero energy mode tests.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.15-22
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• 2023

In this study, We conduct a comparative study of deep learning-based classification of agricultural field attributes using Tagged Image File (TIF) and Enhanced Compression Wavelet (ECW) images. The goal is to interpret and classify the attributes of agricultural fields by analyzing the differences between these two image formats. "FarmMap," initiated by the Ministry of Agriculture, Food and Rural Affairs in 2014, serves as the first digital map of agricultural land in South Korea. It comprises attributes such as paddy, field, orchard, agricultural facility and ginseng cultivation areas. For the purpose of comparing deep learning-based agricultural attribute classification, we consider the location and class information of objects, as well as the attribute information of FarmMap. We utilize the ResNet-50 instance segmentation model, which is suitable for this task, to conduct simulated experiments. The comparison of agricultural attribute classification between the two images is measured in terms of accuracy. The experimental results indicate that the accuracy of TIF images is 90.44%, while that of ECW images is 91.72%. The ECW image model demonstrates approximately 1.28% higher accuracy. However, statistical validation, specifically Wilcoxon rank-sum tests, did not reveal a significant difference in accuracy between the two images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.333-342
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• 2022

This paper has theoretically and practically reviewed the ISO (International Standard Organization) 17123-8 standard not only to raise the appropriateness for introducing performance criteria of GNSS (Global Navigation Satellite Systems) surveying equipment based on RTK (Real-Time Kinematic) accuracy but also to derive its proper test procedure by introducing the international standard. Field experiments have been performed to appreciate the GNSS-RTK accuracy of five selected receivers via the full testing procedure of the ISO standard, which statistically compares the so-called experimental standard deviations with themselves and with the reference accuracy. A series of statistical tests have revealed that the RTK accuracy of the same class receivers is not identical, whereas that of the different classes can be equivalent. Such a result evidences the urgency of adopting an RTK accuracy-based specification of the GNSS equipment to the performance standard, currently referenced to the static observation technique only. It is believed that this transition helps the maximization of a new generation of cost-effective receivers to legal surveying applications. Finally, this study proposes the ISO full test, comparing an experimental standard deviation with its referenced value, for a potential field verification procedure of the new performance standard.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2468-2478
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• 2018

We propose the Sparse Feature Convolutional Neural Network (SFCNN) to reduce the volume of convolutional neural networks (CNNs). Despite the superior classification performance of CNNs, their enormous network volume requires high computational cost and long processing time, making real-time applications such as online-training difficult. We propose an advanced network that reduces the volume of conventional CNNs by producing a region-based sparse feature map. To produce the sparse feature map, two complementary region-based value extraction methods, cluster max extraction and local value extraction, are proposed. Cluster max is selected as the main function based on experimental results. To evaluate SFCNN, we conduct an experiment with two conventional CNNs. The network trains 59 times faster and tests 81 times faster than the VGG network, with a 1.2% loss of accuracy in multi-class classification using the Caltech101 dataset. In vehicle classification using the GTI Vehicle Image Database, the network trains 88 times faster and tests 94 times faster than the conventional CNNs, with a 0.1% loss of accuracy.