• Title/Summary/Keyword: Accuracy of performance

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Accuracy Evaluation of DEM Produced by using KOMPSAT-5 InSAR Image (KOMPSAT 5호 InSAR영상을 이용한 DEM제작 정확도 평가)

  • Han, Seung-Hee
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.2
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    • pp.39-47
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    • 2017
  • The SAR payload of the KOMPSAT-5 is equipped with an X-band (9.66GHz) microwave-based sensor. Especially, since it has a fixed antenna that can be electronically steered with respect to the azimuth and elevation planes, various applications are expected. This study evaluates the production performance and the accuracy of the DEM by producing DEM using the HR and UH mode images of KOMPSAT-5. To evaluate the production performance of the DEM, the sensitivity of DEM was assessed through a baseline analysis and $2{\pi}$ ambiguity; it was found to have good production performance. In addition, to evaluate the accuracy of the produced DEM, 30 check points were compared with SRTM data. As a result, STDEV ${\pm}15-20m$ accuracy was obtained. If the accuracy of the DEM is improved by adjusting the parameters of the filtering method or phase unwrapping method in the future, it will be possible to widely use the KOMPSAT-5 image for environmental and disaster monitoring.

Prediction of Student's Interest on Sports for Classification using Bi-Directional Long Short Term Memory Model

  • Ahamed, A. Basheer;Surputheen, M. Mohamed
    • International Journal of Computer Science & Network Security
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    • v.22 no.10
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    • pp.246-256
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    • 2022
  • Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

A NEW SYSTEM OF VISUAL PRESENTATION OF ANALYSIS OF TEST PERFORMANCE: THE 'DOUBLE-RING' DIAGRAM

  • Stefadouros Miltiadis A.
    • 대한예방의학회:학술대회논문집
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    • 1994.02b
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    • pp.142-149
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    • 1994
  • Substitution of graphic representation for extensive lists of numerical statistical data is highly desirable by both editors and readers of medical journals, faced with an exploding abundance of contemporary medical literature. A novel graphic tool. the 'double-ring diagram', is described herein which permits visual representation of information regarding certain statistical variables used to describe the performance of a test or physical sign in the diagnosis of a disease. The diagram is relatively easy to construct on the basis of a number of primary data such as the prevalence and the true positive, true negative. false positive and false negative test results. These values are reflected in the diagram along with the values of other statistical variables derived from them. such as the sensitivity. specificity, predictive values for positive and negative test result. and accuracy. This diagram may be useful in visualizing a test's performance and facilitating visual comparison of performance of two or more tests.

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Performance Analysis of BDSBAS and MSAS in Korea

  • Noh, Jae Hee;Lim, Deok Won;Lee, Ju Hyun;Jo, Gwang Hee;Lee, Sang Jeong
    • Journal of Positioning, Navigation, and Timing
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    • v.9 no.3
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    • pp.249-259
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    • 2020
  • China has deployed BDS along with the service of SBAS by 2020. Currently, the correction information for testing BDSBAS is provided through the BDS B1I signal. Many research on SBAS other than BDSBAS has been conducted in Korea. However, studies on BDSBAS are insufficient although Korea is included in both the coverage area of MSAS and BDSBAS. Therefore, it is necessary to continuously analyze the performance of MSAS and BDSBAS. In this paper, the performance of MSAS and BDSBAS in Korea, China, and Japan is analyzed in the aspect of positioning accuracy using the GNSS RINEX data provided by IGS. A Software platform is designed to analyze the performance of GPS-only, BDS-only, GPS/MSAS and BDS/BDSBAS. From the result, it can be concluded that the accuracy enhancement can be hardly seen when using the correction information of MSAS and BDSBAS in Korea

Comparative Analysis of PM10 Prediction Performance between Neural Network Models

  • Jung, Yong-Jin;Oh, Chang-Heon
    • Journal of information and communication convergence engineering
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    • v.19 no.4
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    • pp.241-247
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    • 2021
  • Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.

A study on the improvement of cutting precision of CNC system using $H_{\infty}$ 2-degree-of-freedom controller ($H_{\infty}$ 2 자유도 제어기를 이용한 CNC 시스템의 가공 정밀도 향상에 관한 연구)

  • 최성규;최병욱;현용탁;강성귀;권욱현
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1040-1043
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    • 1996
  • The accuracy of the servo control in CNC system has a great influence on the duality of machine product. Tracking performance of the servo control is deteriorated mainly by the time delay of the servo system and the inertia of the work table or bed. Contouring errors occur in every interpolation steps by the effect of the tracking performance. In this paper, $H_{\infty}$ two-degree-of-freedom(TDF) controller is designed for improvement to improve the tracking performance. The designed controller is applied 3-axis machining center model and the cutting accuracy is simulated in case of corner cutting, circular and involute interpolation. Simulation results show that $H_{\infty}$ TDF controller designed in this paper has a good effect to improve tracking performance in CNC system.

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A Study on CNC Performance Test System using the Dynamometer (Dynamometer를 이용한 CNC제어기 성능평가 시스템 개발)

  • Kim Sung Chung;Lee Chan Ho;Park Byung Gyu;Jeong Eul Seob
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.14 no.3
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    • pp.16-22
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    • 2005
  • It is difficult to separate those of NC controller from the error of machine tools because the conventional testing methods to inspect the performance are including the errors of moving system, therefore it has been used as the methods that compare the other controllers. Also, it is hard to predict the machine itself errors with the methods assembling the NC controller and moving system on machine because of the variable load conditions. In this study, the performance inspecting system was developed by analyse the $axis\_rotating$ properties of servo system finally outputting from NC controller. The axis torque was controlled by motor dynamometer and the rotating position accuracy was measured by this developed system.

A Study on the Land Cover Classification and Cross Validation of AI-based Aerial Photograph

  • Lee, Seong-Hyeok;Myeong, Soojeong;Yoon, Donghyeon;Lee, Moung-Jin
    • Korean Journal of Remote Sensing
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    • v.38 no.4
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    • pp.395-409
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    • 2022
  • The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

Studying the Ephemeris Effect on Position Accuracy Based on Criteria Applied to Baseline Lengths by New MATLAB Program (NMP)

  • Shimaa Farouk;Mahmoud El-Nokrashy;Ahmed Abd-Elhay;Nasr Saba
    • Journal of Astronomy and Space Sciences
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    • v.40 no.3
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    • pp.113-122
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    • 2023
  • Although the Relative Global Navigation Satellite System (GNSS) positioning technique provides high accuracy, it has several drawbacks. The scarcity of control points, the long baselines, and using of ultra-rabid and rabid products increased position errors. This study has designed a New MATLAB Program that helps users automatically select suitable IGS stations related to the baseline lengths and the azimuth between GNSS points and IGS stations. This study presented criteria for the length of the baselines used in Egypt and an advanced estimated accuracy before starting the project. The experimental test studies the performance of the position accuracy related to the relation between three factors: observation session, final, rabid, and ultrarabid products, and the baseline lengths. Ground control point mediates Egypt was selected as a test point. Nine surrounding IGS stations were selected as reference stations, and the coordinates of the tested point were calculated based on them. Baselines between the tested point and the IGS stations were classified regarding proposal criteria. The coordinates of the tested point were obtained in different observation sessions (0.5, 1, 2, 4, 5, 6, 7, 7.5 h). The results indicated that the lengths of the baseline in Egypt were classified short (less than 600 km), medium (600-1,200 km), and long (greater than 1,200 km) and required a minimum observation time of 4, 5, and 7 h to obtain accuracy 10, 19, 48 mm sequentially. The position accuracy was superior for the rapid and the final than the ultra-rapid products by 16%. A short baseline was at the best case; there was a performance in position accuracy with a 57% deduction in observation time compared with the long baseline.

An Analysis of Performance Error of Roundness Measuring Instrument -by phase different method- (眞圓度 測定器의 誤差特性에 대한 解析 -위상차법-)

  • 한응교;허문석;박익근
    • Journal of the korean Society of Automotive Engineers
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    • v.10 no.3
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    • pp.31-37
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    • 1988
  • A phase different method to evaluate the instrument error of roundness measuring instrument and the form error of specimens for the calibration of the instrument is used. An instrument with a rotary table supported by an air bearing was calibrated by using the standard balls as a standard. The calibration was carried out repeatedly by setting the same ball in 12 phase angles(per 30.deg.) on the table and by recording their roundness errors with a magnification of 100,000 times. As a result of data analysis of all the observations, readout at each of 144 orientations(per 2.5.deg.) from recorded data file, the error of performance of the instrument and the specimens are separated. In the particular instrument used in the present experiment, the error of the instrument was determined with the accuracy of 0.0164 (.mu.m) and the form error of the specimens was determined with the accuracy of 0.0264,0.0172(.mu.m), respectively. If the instrument was calibrated by using the above specimens, then the accuracy of the measurement of roundness error can be improved to about 0.017 (.mu.m).

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