FEATURES OF CONTROLLING ELECTROPNEUMATIC VALVES OF ACTUATOR TO CONTROL ITS CLUTCH WITH ACCELERATION VALVE by O. A. Yaryta, M. G. Mychalevych, D. N. Leontiev, V. I. Klymenko, V. A. Bogomolov, I. V. Gritsuk, Y. B. Novikova

“…The quantitative characteristics of single control pulses and PWM ones are determined. The error of operation accuracy for various ways of the control of the electropneumatic actuator to control the clutch of the robotic transmission is determined. …”
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Spatiotemporal Fusion Algorithm Based on Multikernal Adaptive Network by Qiuhui Wang, Qiong Ran, Ke Zheng, Jiaxin Li

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Optimization of Fused Deposition Modeling Parameters for Mechanical Properties of Polylactic Acid Parts Based on Kriging and Cuckoo Search by Yuan Yang, Yiyang Wang, Bowen Xue, Changxu Wang, Bo Yang

“…Finally, compared to the test data, the relative prediction error of Kriging model was 0.62%, and the optimal strength (38.27 MPa) increased by about 12.7% compared to the average value (33.97 MPa) of experimental data. …”
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Determination of Pear Cultivars (Pyrus communis L.) Based on Colour Change Levels by Using Data Mining by Dilara Gerdan, Abdullah Beyaz, Mustafa Vatandaş

“…The classifier performance (accuracy, error, F-Measure, Cohen's Kappa, recall, precision, true positive (TP), false positive (FP), true negative (TN), false negative (FN) values were given at the conclusion section of the research. …”
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Biostrap Kairos Wristband Versus Electrocardiography for Resting Heart Rate Variability Assessment by Andrew A. Flatt, Ann Claire E. Blalock, Allison N. Wade, Bryan L. Riemann

“…The Kairos wristband offers on-demand heart rate variability (HRV) assessment through its “Spot Check” feature, enabling standardized recordings for clinical, research, or self-tracking purposes, but its validity is untested. …”
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Financial Policies and Corporate Income Tax Administration in Nigeria by Cordelia Onyinyechi Omodero, Joy Limaro Yado

“…This investigation applies autoregressive distributed lag and error correction models, acknowledging the existence of a long-term relationship within the series. …”
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Modeling and Analysis of Optical Time-domain Reflectometry in Strongly-coupled Multi-core Fiber by XING Rui, YANG Zhiqun, YAN Hui, LIU Yaping, WANG Xutao, WANG Yanze, ZHANG Wendou, ZHANG Lin

“…The simulation results show that the received scattering power is consistent with the set parameters, with an error within 5%.【Conclusion】The high precision of the results indicates that the model proposed in the article effectively reflects the Rayleigh scattering effects in coupled-core optical fibers, laying a theoretical foundation for accurately testing parameters of coupled-core optical fibers using optical time-domain reflectometry technology.…”
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Eigen‐Swarm: Swarm's Thermospheric Mass Density Modeling via Eigen‐Decomposition by Charles Owolabi, Hyunju Connor, Don Hampton, Denny M. Oliveira, Andres Calabia, V. Sai Gowtam, Eftyhia Zesta

“…The Eigen‐Decomposition model performance is validated by comparison with the Jacchia‐Bowman 2008 (JB2008), Naval Research Laboratory Mass Spectrometer Incoherent Scatter 2.0 (NRLMSIS2.0), and Calabia and Jin (CAJIN) models, as well as TMD data from the Gravity Recovery and Climate Experiment Follow‐On mission during 2018–2020, using root mean square error (RMSE) as the evaluation metric. …”
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The two-mode network approach to digital skills and tasks among technology park employees by Anna Ujwary-Gil, Bianka Godlewska-Dzioboń

“…Here, employees serve park tenants mainly from the creative, game, IT and multimedia industries, and broadly understood audiovisuals. Research Design & Methods: The questionnaire previously validated by other authors was used to measure employees’ digital skills and two non-parametric network statistics tests based on data permutation were conducted: the quadratic assignment procedure (QAP) and the multiple regression quadratic assignment procedure (MRQAP), which are good at error autocorrelation. …”
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Value sets and the problem of redundancy in value set repositories. by Sigfried Gold, Harold P Lehmann, Lisa M Schilling, Wayne G Lutters

“…When users encounter multiple value sets with the same name or ostensibly representing the same clinical condition, it can be difficult to choose amongst them or determine if any differences among them are due to error or intentional decision.<h4>Methods</h4>This paper offers a view of value set development and reuse based on a field study of researchers and informaticists. …”
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Arabic version of the patient education materials assessment tool (PEMAT): translation and validation by Marwan A. Alrasheed, Aliyah Almobarak, Hisham M. Alfayyadh, Abdulelah Alkahtani, Bander Balkhi

“…Pearson correlation and the Standard Error of Measurement (SEM) were also calculated. …”
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Evaluation of Three Human-Use Glucometers for Blood Glucose Measurement in Dogs by Matheus Albuquerque Basilio dos Santos, Alesssandra Martins Vargas, Paula Nunes Rosato, Carolina Gomes Andrade, Camila Marinelli Martins, Giuliana Petri

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A comparative ensemble approach to bedload prediction using metaheuristic machine learning by Ajaz Ahmad Mir, Mahesh Patel, Fahad Albalawi, Mohit Bajaj, Milkias Berhanu Tuka

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Integrating QR Technology into Enterprise Systems: Accounting and Managerial Innovations in E-Document Flow

“…The advantages of QR coding have been substantiated: the ability to store large arrays of heterogeneous data, ease of use, the possibility of rapid decoding and error correction, as well as integration with corporate information systems. …”
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Long-term electricity demand forecasting of a university campus based on advanced deep learning artificial neural network algorithms by Saad A. Alsamraee, Sanjeev Khanna

“…The results show that while all models performed well, the hybrid CNN-RNN models, particularly CNN-BiLSTM and CNN-BiGRU models, showed higher performance, achieving 0.98 and 0.97 accuracy during training and 0.92 and 0.93 during testing, with a validation loss error of 0.073 and 0.062, respectively. Subsequently, the models were used to predict energy demand for the entire year 2024. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…One of the major challenges confronting researchers is how to predict biogas yield because it is a herculean task since research in the field of modeling and optimization of biogas yield is still limited, especially with the adaptive neuro-fuzzy inference system (ANFIS). …”
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Reduced order data driven framework for computation of the unsteady lid-driven cavity flow using dynamic mode decomposition by Karim Mazaheri, Mohammad Kazem Moayyedi, Mohammad Hadi Dehghan

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Multi-scale attention patching encoder network: a deployable model for continuous estimation of hand kinematics from surface electromyographic signals by Chuang Lin, Qiong Xiao, Penghui Zhao

“…Abstract Background Simultaneous and proportional control (SPC) based on surface electromyographic (sEMG) signals has emerged as a research hotspot in the field of human–machine interaction (HMI). …”
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Tri-manual interaction in hybrid BCI-VR systems: integrating gaze, EEG control for enhanced 3D object manipulation by Jian Teng, Jian Teng, Sukyoung Cho, Shaw-mung Lee

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Temporal Synchrony in Bodily Interaction Enhances the Aha! Experience: Evidence for an Implicit Metacognitive Predictive Processing Mechanism by Jiajia Su, Haosheng Ye

“…Grounded in the theory of metacognitive prediction error minimization, this study is the first to propose and empirically validate the mechanism of implicit metacognitive predictive processing by which bodily interaction influences the Aha! …”
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