• Geotechnical Engineering
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• v.6 no.2
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• pp.47-54
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• 1990

The accuracy of a limit equilibrium analysis of slope stability depends on the accuracy with which the strength properties and geometric conditions can be defined, and on the inherent accuracy of the method of analysis. Most of the slope stability analysis method have been computer coded, and this is a comparative study on the accuracy of these programs. Comparative analyses have shown that for the slopes with relatively simple conditions Host of the programs which are widely used in this country result in the same value of safety factor with an accuracy no worse than $\pm$5%. Similar results can be obtained from the examination of the several slope failure for which accurate information is available on the strength and geometric conditions of the earth slope. The critical failure surface, however, can be different from the actual slip surface, although nearly the same factors of safety are obtained from the analyses of each surface.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.399-407
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• 2021

Stock movement is difficult to predict because it has dynamic characteristics and is influenced by many factors. Even so, there are some approaches to predict stock price movements, namely technical analysis, fundamental analysis, and sentiment analysis. Many researches have tried to predict stock price movement by utilizing these analysis techniques. However, the results obtained are varied and inconsistent depending on the variables and object used. This is because stock price movement is influenced by a variety of factors, and it is likely that those studies did not cover all of them. One of which is that no research considers the use of fundamental analysis in terms of currency exchange rates and the use of foreign stock price index movement related to the technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The result obtained has a prediction accuracy rate of 65,33% on an average. The inclusion of currency exchange rate and foreign stock price index movement as a predictor in this research which can increase average prediction accuracy rate by 11.78% compared to the prediction without using these two variables which only results in average prediction accuracy rate of 53.55%.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1153-1160
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• 2019

In this paper, we experimented to find out how the number of convolution layers, the size, and the number of kernels affect the CNN. In addition, the general CNN was also tested for analysis and compared with the CNN used in the experiment. The neural networks used for the analysis are based on CNN, and each experimental model is experimented with the number of layers, the size, and the number of kernels at a constant value. All experiments were conducted using two layers of fully connected layers as a fixed. All other variables were tested with the same value. As the result of the analysis, when the number of layers is small, the data variance value is small regardless of the size and number of kernels, showing a solid accuracy. As the number of layers increases, the accuracy increases, but from above a certain number, the accuracy decreases, and the variance value also increases, resulting in a large accuracy deviation. The number of kernels had a greater effect on learning speed than other variables.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.12
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• pp.1036-1043
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• 2016

In this paper, an analysis about the elevation angle accuracy degradation of an APAR(Airport Precision Approach Radar) due to the multi-path effect using a phased array antenna was performed. An APAR installed around a runway of airport will be continuously affected in a runway surface of the fixed environment. In this paper, an analysis about the elevation angle accuracy degradation of APAR due to the multi-path effect of runway surface was conducted through a calculation of monopluse slope and sum/difference beam pattern analysis of array antenna. Also, a difference pattern for monopulse to minimize this degradation was optimized in an appropriate configuration to improve a elevation angle accuracy. Finally, a degree of improvement of elevation angle accuracy was confirmed by calculating a monopulse slope including the ground reflection after applying optimized difference patterns of array antenna.

• Journal of Periodontal and Implant Science
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• v.54 no.1
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• pp.3-12
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• 2024

Deep learning (DL) offers promising performance in computer vision tasks and is highly suitable for dental image recognition and analysis. We evaluated the accuracy of DL algorithms in identifying and classifying dental implant systems (DISs) using dental imaging. In this systematic review and meta-analysis, we explored the MEDLINE/PubMed, Scopus, Embase, and Google Scholar databases and identified studies published between January 2011 and March 2022. Studies conducted on DL approaches for DIS identification or classification were included, and the accuracy of the DL models was evaluated using panoramic and periapical radiographic images. The quality of the selected studies was assessed using QUADAS-2. This review was registered with PROSPERO (CRDCRD42022309624). From 1,293 identified records, 9 studies were included in this systematic review and meta-analysis. The DL-based implant classification accuracy was no less than 70.75% (95% confidence interval [CI], 65.6%-75.9%) and no higher than 98.19 (95% CI, 97.8%-98.5%). The weighted accuracy was calculated, and the pooled sample size was 46,645, with an overall accuracy of 92.16% (95% CI, 90.8%-93.5%). The risk of bias and applicability concerns were judged as high for most studies, mainly regarding data selection and reference standards. DL models showed high accuracy in identifying and classifying DISs using panoramic and periapical radiographic images. Therefore, DL models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.285-288
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• 2007

The use of commercial finite element analysis software to perform the entire process analysis and springback analysis has increased fast for last decade. Pamstamp2G is one of commercial software to be used widely in the world but it has still not been perfected in the springback prediction accuracy. We must select the combination of input parameters for the highest springback prediction accuracy in Pamstamp2G because springback prediction accuracy is sensitive to input parameters. Then we study the affect of input parameters to use member part for acquiring high springback prediction accuracy in Pamstamp2G. First, we choose important four parameters which are adaptive mesh level at drawing stage and cam flange stage, Gauss integration point number through the thickness and cam offset on basis of experiment. Second, we make a orthogonal array table L82[(7)] which is consist of 8 cases to be combined 4 input parameters, compare to tryout result and select main factors after analyzing affect factors of input parameters by Taguchi's method in 6 sigma. Third, we simulate after changing more detail the conditions of parameters to have big affect. At last, we find the best combination of input parameters for the highest springback prediction accuracy in Pamstamp2G. The results of the study provide the selection of input parameters to Pamstamp2G users who want to Increase the springback prediction accuracy.

• The Journal of Advanced Prosthodontics
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• v.15 no.3
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• pp.145-154
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• 2023

PURPOSE. The objective of this study was to investigate how internal structures influence the overall and marginal accuracy of full arch preparations fabricated through additive manufacturing in different printing systems. MATERIALS AND METHODS. A full-arch preparation digital model was set up with three internal designs, including solid, hollow, and grid. These were printed using three different resin printers with nine models in each group. After scanning, each data was imported into the 3D data processing software together with the master cast, aligned and trimmed, and then put into the 3D data analysis software again to compare the overall and marginal deviation whose results are expressed using root mean square values and color maps. To evaluate the trueness of the resin model, the test data and reference data were compared, and the precision was evaluated by comparing the test data sets. Color maps were observed for qualitative analysis. Data were statistically analyzed by one-way analysis of variance and Bonferroni method was used for post hoc comparison (α = .05). RESULTS. The influence of different internal structures on the accuracy of 3D printed resin models varied significantly (P < .05). Solid and grid models showed better accuracy, while the hollow model exhibited poor accuracy. The color maps show that the resin models have a tendency to shrink inwards. CONCLUSION. The internal structure design influences the accuracy of the 3D printing model, and the effect varies in different printing systems. Irrespective of the kind of printing system, the printing accuracy of hollow model was observed to be worse than those of solid and grid models.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.640-647
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• 2018

This study analyzes the tracking accuracy(tracking errors) of fighter radar. Measurement error, detection failure, and radar cross section(RCS) fluctuation in radar measurements degrade the measurement quality and hence affect the tracking accuracy. Therefore, these radar measurement characteristics need to be considered when analyzing the tracking accuracy. In this paper, a method for analyzing the tracking accuracy is proposed; this method considers the detection error, detection probability, and RCS fluctuation. Results from experiments conducted with the proposed method show that the detection probability and RCS fluctuation affect tracking accuracy.

• Journal of Korean Academy of Nursing Administration
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• v.17 no.2
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• pp.189-197
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• 2011

Purpose: This study was an analysis of the relationship between perception for appraisal of staff nurses in operating rooms and performance and organizational commitment. Method: The survey was conducted with 176 staff nurses in operating rooms in 2 hospitals in Seoul. Data were analyzed using frequency, one-way ANOVA, Pearson correlation analysis, and stepwise multiple regression. Result: 1. Perception for appraisal including accuracy and justice was significantly related to organizational commitment (r=.496, P=.000). Perception for appraisal including accuracy and justice was slightly related to performance (r=.220, P=.003). 2. In order to determine the percentage of the variance of performance and organizational commitment that could be predicted by perception for appraisal, perception for appraisal was entered in the regression equation. Accuracy accounted for 25% of the variance in the organizational commitment. To determine the percentage of the variance of performance that could be predicted by perception for appraisal and organizational commitment, the perception for appraisal and organizational commitment were entered in the regression equation. Organizational commitment accounted for 21% of the variance in the performance. Consequently accuracy predicted organizational commitment. Organizational commitment predicted performance. Conclusions: Findings indicate the need to increase accuracy of performance appraisal to promote organizational commitment and performance in perioperative nurses.