• 한국지반공학회지:지반
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• 제6권2호
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• pp.47-54
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• 1990

사면안정해석의 정확도는 흙의 강도특성과 사면의 기하학적 조건의 파악정도와 해석방법 본말 의 정확도에 지배된다. 그리고 대부분의 사면안정해절방법은 컴퓨터 프로그랙으로작성되어 있다. 국내에서 실용되고 있는 프로그램의 정확성을 비교한 것이다. 비교적 간단한 조건의 각 프로그램으로 얻은 안전률의 차리는 5% 이내이다. 요면에 관한 정확한 타보입수가 가능한 파괴사례 연구에서도 유사한 결과를 얻었다. 그러나 컴퓨터가 찾아낸 임계파괴면과 실제 파괴면은 약간 상리한 경우도 있었다. 이 때에도 두 활동면을 해석하여 구한 안전률 값은 대차 없이 거의 동일하였다. 결국 국내에서 사용되고 있는 사면안정해석 컴퓨터 프로그램은 그 실용성이 인정된다고 할 수 있다.

• 품질경영학회지
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• 제51권4호
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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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• 제8권8호
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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%.

• 한국전자통신학회논문지
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• 제14권6호
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• pp.1153-1160
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• 2019

본 논문에서는 CNN의 컨볼루션 레이어 개수 및 커널의 크기와 개수가 CNN에 어떠한 영향을 끼치는지 실험을 통해 알아보기 위해 진행하였다. 또한 분석을 위해 일반적인 CNN도 실험하여 실험에 사용된 CNN과 비교하였다. 분석에 사용될 신경망들은 CNN을 기반으로 하며 각각의 실험모델들은 레이어 개수, 커널의 크기 및 개수를 일정한 값으로 고정해 실험을 진행하였다. 모든 실험에는 2계층의 완전연결계층을 고정으로 사용하였다. 다른 변수들은 모두 동일한 값을 주어 실험하였다. 분석결과 레이어의 수가 작을 경우 커널의 크기 및 개수와 상관없이 데이터의 분산 값이 작아 견고한 정확도를 보여주었다. 레이어의 수가 커질수록 정확도도 증가됐으나 일정 수치 이상부턴 오히려 정확도가 내려갔으며 분산 값도 커져 정확도 편차가 크게 나타났다. 커널의 개수는 다른 변수보다 학습속도에 큰 영향을 끼쳤다.

• 한국전자파학회논문지
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• 제27권12호
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• pp.1036-1043
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• 2016

본 논문에서는 위상배열 안테나를 활용해 다중 경로 효과에 의한 공항정밀접근레이다의 고각 정확도 열화에 관하여 분석을 수행하였다. 공항의 활주로 주변에 설치되는 정밀접근레이다는 고정 환경인 활주로면의 영향을 지속적으로 받게 된다. 본 논문에서는 활주로면에 의한 다중 경로 효과에 따른 정밀접근레이다 고각 정확도 열화에 관하여, 배열 안테나의 합/차 패턴 분석 및 이를 통한 모노펄스 기울기를 계산하여 분석하였다. 또한, 본 논문에서는 이러한 고각 정확도 열화를 최소화하기 위해 모노펄스용 차 패턴을 고각 정확도 개선에 적합한 형태로 최적화하였다. 최종적으로 최적화된 배열 안테나 차 패턴을 적용한 후 지면 반사 영향성이 고려된 모노펄스 기울기를 계산하여 고각 정확도 개선 정도를 확인하였다.

• Journal of Periodontal and Implant Science
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• 제54권1호
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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.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 춘계학술대회 논문집
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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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• 제15권3호
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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.

• 한국전자파학회논문지
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• 제29권8호
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• pp.640-647
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• 2018

본 논문은 전투기 레이다의 표적 추적정확도(추적오차)를 분석하는 방법에 대한 연구이다. 레이다 측정 시 발생하는 측정오차, 탐지실패, radar cross section(RCS) 요동은 측정 품질을 열화시키며, 이는 추적정확도에 영향을 미치는 요인이 될 수 있다. 따라서 정확한 추적성능분석을 위해 이러한 레이다 측정 특성을 고려하는 것이 필요하다. 본 논문에서는 측정오차, 탐지확률, RCS 요동과 같은 레이다 특성을 복합적으로 활용하여 추적정확도를 분석하는 방법에 대해서 제안한다. 제안한 분석 방법을 활용한 실험을 통해 탐지확률과 RCS 요동에 의한 추적정확도 열화를 확인할 수 있었다.

• 간호행정학회지
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• 제17권2호
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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.