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  1. 1321
  2. 1322

    Research on action matching of skeletal point coordinates and sports teaching application based on Open-pose by Shunmin Su

    Published 2025-12-01
    “…This study addresses the challenges of high matching errors and low recognition rates in traditional skeletal point-based human action matching methods, a skeleton point coordinate and human posture action matching technology is studied based on Open-pose open-source model. …”
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  3. 1323

    No-Code Technology in Designing a Web-Based Stock Recording Applications Using AppSheet by Amanda Putri Herawati, Thomas Budiman, Anton Zulkarnain Sianipar, Balthasar Sebastian Lumbantobing

    Published 2025-07-01
    “…Digital transformation also helps minimize errors and maintain service quality. Manual inventory recording at the Dermaga Baut Mandiri Store in Tangerang causes difficulties in monitoring inventory availability, a high risk of data errors, and delays in reporting, which impacts operational and service continuity. …”
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  4. 1324
  5. 1325

    A Robust Framework for Probability Distribution Generation: Analyzing Structural Properties and Applications in Engineering and Medicine by Aadil Ahmad Mir, Shamshad Ur Rasool, S. P. Ahmad, A. A. Bhat, Taghreed M. Jawa, Neveen Sayed-Ahmed, Ahlam H. Tolba

    Published 2025-04-01
    “…Extensive simulation studies confirm these estimation techniques’ robustness, showing that biases, mean squared errors, and root mean squared errors consistently decrease as sample sizes increase. …”
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  6. 1326
  7. 1327

    APPLICATION OF BAGGING CART IN THE CLASSIFICATION OF ON-TIME GRADUATION OF STUDENTS IN THE STATISTICS STUDY PROGRAM OF TANJUNGPURA UNIVERSITY by Widad Imtiyaz, Neva Satyahadewi, Hendra Perdana

    Published 2023-12-01
    “…Based on the accuracy value obtained, the application of the CART Bagging method can increase accuracy and correct classification errors on a single CART classification tree by 15.71% by resampling 25 times.…”
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  8. 1328
  9. 1329

    Multiband THz MIMO antenna with regression machine learning techniques for isolation prediction in IoT applications by Md Ashraful Haque, Kamal Hossain Nahin, Jamal Hossain Nirob, Md. Kawsar Ahmed, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Abeer D. Algarni, Mohammed ElAffendi, Ahmed A. Abd El-Latif, Abdelhamied A. Ateya

    Published 2025-03-01
    “…Various metrics, including variance score, R-squared, mean squared error (MSE), mean absolute error (MAE), and root mean square error (RMSE), were used to evaluate the machine learning models. …”
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  10. 1330

    Prediction of Rice Yields in a Changing Climate Using the Mobile Rice Yield Prediction Application by Mohamad Farhan Mohamad Mohsin, Mohamad Ghozali Hassan, Kamal Imran Mohd Sharif, Mohd Azril Ismail, Liew Jun Hong, Muhammad Khalifa Umana, Hairazi Rahim@Abdul Rahim

    Published 2025-04-01
    “…A 10-year dataset from the Malaysian Meteorological Department (MetMalaysia) and the Department of Statistics Malaysia (DOA) were trained and tested on varying data splits and then evaluated using performance metrics such as R-squared, Mean Absolute Error, Mean Square Error, and Root Mean Square Error. …”
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  11. 1331
  12. 1332

    Verification tests of a method of determining sound intensity with the application of a two microphone technique by Ryszard PANUSZKA, Jacek CIEŚLIK

    Published 2015-07-01
    “…These tests led to the development of software and instrumentation for the method of measuring the acoustical intensity with the application of a two microphone technique. Results of a quantitative evaluation of chosen method errors occuring for the accepted for investigation pair of microphones were presented, as well as results of investigations leading to the evaluation of the accuracy of intensity measurements done with the developed measuring system.…”
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  13. 1333

    System Development for Liquid Chemicals Point Injection Based on Convolutional Neural Network Models by V. S. Semenyuk, E. A. Nikitin

    Published 2021-06-01
    “…They showed that the predicted error on the validation data was 0.18758. In practice, it could differ from the declared one by no more than 10-15 percent. …”
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  14. 1334

    Utilization of aspen DMC3 in process control of crude distillation unit (CDU) by Bol Ram, Z Ahmad, N Md Nor

    Published 2025-06-01
    “…The performance of the DMC controller is compared against conventional Proportional-Integral-Derivative (PID) controllers implemented in Aspen Dynamics using key indicators such as settling time, offset error, maximum deviation, and response smoothness. …”
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  15. 1335

    Application of quantum-inspired evolutionary algorithm in the analysis of near infrared diffuse transmission spectroscopy of apples by LI Jun-liang, WANG Cong-qing

    Published 2011-07-01
    “…The results showed that the GA-PLS model had 110 variables, with RMSEC (root mean standard error of calibration) of 0.582 0, RMSEP (root mean standard error of prediction) of 0.612 3, but the QEA-PLS model had 194 variables, with RMSEC of 0.492 7, RMSEP of 0.526 0. …”
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  16. 1336

    Optimisation of Ensemble Learning Algorithms for Geotechnical Applications: A Mathematical Approach to Relative Density Prediction by Mahdy Khari, Ali Dehghanbanadaki, Danial Jahed Armaghani, Manoj Khandelwal

    Published 2025-01-01
    “…The mathematical formulation of the GBR model was rigorously examined and optimised using advanced tuning functions, achieving exceptional performance metrics (mean squared error [MSE] = 11.91, mean absolute error [MAE] = 1.93, R2 = 0.997). …”
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  18. 1338

    APPLICATION OF DIFFERENTIAL EQUATIONS IN POPULATION GROWTH ESTIMATION OF KEDIRI CITY AS THE IMPLEMENTATION OF THE 2030 SDGS TARGET by Nova Andini, Dewi Hamidah, Agus Miftakus Surur

    Published 2024-07-01
    “…To validate the accuracy of the logistic growth model, the Mean Absolute Percentage Error (MAPE) method was applied, resulting in an error percentage that falls within the highly accurate category, thus affirming the reliability of the model in predicting population growth trends.…”
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  19. 1339

    Structuring a textile knitting dataset for machine learning and data mining applicationsMendeley Data by Toufique Ahmed, Abu Saleh Muhammad Junayed

    Published 2025-08-01
    “…Among various machine learning models to predict GSM, Random Forest and XGBoost consistently outperformed across all metrics (R² score, Mean Absolute Error, and Mean Square Error).…”
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  20. 1340