Reconstructing Equatorial Electron Flux Measurements From Low‐Earth‐Orbit: A Conjunction Based Framework by D. L. Stumbaugh, J. Bortnik, S. G. Claudepierre

“…We present our model's prediction for the out‐of‐sample data that agrees well with observations, giving R2 > 0.70. We demonstrate the ability to nowcast and reconstruct equatorial electron flux measurements from LEO without the need for an in‐situ equatorial satellite. …”
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THE EFFECT OF LIGHTNING ON HIGH VOLTAGE ELECTRICAL SUBSTATIONS’ LOW VOLTAGE SYSTEMS by M. I. Fursanov, P. V. Kriksin

“…The factors that had been included in the models were studied and were defined in accordance with their nature (natural or artificial), the range of possible values in a substation was determined; the coefficients of elasticity were calculated. The obtained results enable to ascertain the contribution of the factor in the effect of lightning and the ability to control the factor. …”
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Prediction of Traction Requirements and Slippage Percentage for Three Plow Types under Various Operational Conditions by Mustafa F. Almoosa, Salim A. Almaliki, Salah M. S. Al-Atab

“…The data analysis shows that the developed model has a good ability for prediction compared to the field data, as the coefficients of determination of the draft force and slippage are 0.9531 and 0.9480 respectively. …”
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A Meta-Reinforcement Learning-Based Poisoning Attack Framework Against Federated Learning by Wei Zhou, Donglai Zhang, Hongjie Wang, Jinliang Li, Mingjian Jiang

“…A novel scaling and noise injection attack is introduced by designing unique scaling coefficients and noise values for the gradient of each layer’s parameters using reinforcement learning. …”
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Prediction of Traction Requirements and Slippage Percentage for Three Plow Types under Various Operational Conditions by Mustafa F. Almoosa, Salim A. Almaliki, Salah M. S. Al-Atab

“…The data analysis shows that the developed model has a good ability for prediction compared to the field data, as the coefficients of determination of the draft force and slippage are 0.9531 and 0.9480 respectively. …”
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Prediction acrylamide contents in fried dough twist based on the application of artificial neural network by Xinyu Wu, Haiyang Yan, Yue Cao, Yuan Yuan

“…The results showed that the Levenberg-Marquardt back-propagation training algorithm of the BP-ANN model with 5 hidden layer neurons and 0.005 learning rate was the best predictive performance, which the correlation coefficients (R) of test and validation were 0.9640 and 0.8999, suggesting a good fitting and strong approximation ability. …”
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The Impact of Digital Transformation on Risk-Taking: An Empirical Study of Japanese Companies by Shah Mehmood Wagan, Sidra Sidra

“…Specifically, a comparison of the estimated coefficients obtained across the state-owned enterprises versus their non-state-owned counterparts shows a large difference in the magnitude for the latter. …”
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Arabic speech recognition using end‐to‐end deep learning by Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, Islam Hegazy, Zaki T. Fayed

“…Abstract Arabic automatic speech recognition (ASR) methods with diacritics have the ability to be integrated with other systems better than Arabic ASR methods without diacritics. …”
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DETERMINATION OF THE OPTIMUM DOSAGE OF FOOD ADDITIVE «SELEX» FOR FUNCTIONAL BAKERY GOODS PRODUCTION by Naumova N.L.

“…One of the important quality factors of a functional food is the ability to preserve its curative and preventive properties for the entire shelf life. …”
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Active Disturbance Rejection Control of Output Voltage of Solid Oxide Fuel Cell Based on Reinforcement Learning by GUAN Chaojun, LEI Zhengling, HUO Haibo, WANG Fang, YAO Guoquan, LIU Tao

“…An improved NLADRC controller based on the twin delayed deep deterministic policy gradient (TD3) was proposed to optimize the coefficients of nonlinear error feedback control law.ResultsThe designed controller can improve SOFC output voltage tracking performance without violating fuel utilization constraints.ConclusionsThe designed controller has the advantages of strong adaptability, high stability, and the ability to overcome uncertainty, providing theoretical reference for designing output voltage controllers in practical SOFC systems.…”
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QFCOI-Enhancing Objective Quality Assessment for Compressed Omnidirectional Images With Fusion of Measures by Marek Simka, Ladislav Polak, Adam Zizien, Karel Fliegel

“…The QFCOI performance was validated through correlation coefficients, statistical significance testing, and Receiver Operating Characteristic (ROC) analyses. …”
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Psychometric Properties of the Persian Version of the Propensity to Learn from Experience Related to Safety Events Questionnaire in the Industries of Mazandaran province by Arezoo Sammak-Amani, Zahra Naghavi-Konjin, Abolfazl Hosseinnataj, Siavash

“…Introduction: Using leading indicators to determine organizations’ ability and willingness to learn from safety-related events can significantly enhance occupational health and safety management systems and help prevent future incidents. …”
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Applicability of China’s First Generation of Global Land Surface Reanalysis Monthly Precipitation Products in the Yangtze River Basin by WANG Wen-peng, ZHANG Xin-yue, CUI Jun-hao, WU Guang-dong, ZHANG Tian-yu, LIU Bo

“…The multi-year average precipitation derived from CRA data is only 1.2% lower than the observed data. The correlation coefficients of monthly data all exceed 0.9. Nevertheless, the efficiency coefficients during the main flood season (July and August) are below 0.9, slightly lower than those in other months. …”
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Spectral solutions for QS with distribution laws in the form of probabilistic mixtures by Veniamin N. Tarasov, Nadezhda F. Bakhareva

“…The shift of the distribution laws in time leads to a decrease in their variation coefficients. Due to the quadratic dependence of the average waiting time on the variation coefficients of the arrival and service time intervals, a noticeable decrease in the average waiting time follows in systems with time shifts.…”
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Spectral feature modeling with graph signal processing for brain connectivity in autism spectrum disorder by Ayesha Jabbar, Huang Jianjun, Muhammad Kashif Jabbar, Khalil ur Rehman, Anas Bilal

“…We extract advanced GSP features such as Graph Fourier Transform coefficients, spectral entropy, and clustering coefficients, and combine them using Principal Component Analysis (PCA). …”
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Properties of the SURE Estimates When Using Continuous Thresholding Functions for Wavelet Shrinkage by Alexey Kudryavtsev, Oleg Shestakov

“…The advantages of these methods lie in their computational efficiency and the ability to adapt to the local features of the estimated function. …”
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Relative Validity and Reproducibility of a Quantitative Food Frequency Questionnaire for Adolescents with Type 1 Diabetes: Validity of a Food Frequency Questionnaire by Rosana de Moraes Borges Marques, Amanda Cristine de Oliveira, Sheylle Almeida da Silva Teles, Maria Luiza Ferreira Stringuini, Nélida Shimid Fornés, Giulliano Gardenghi

“…Statistical analysis included performing t-tests, obtaining Pearson correlation coefficients when necessary, correcting measurements for randomness by the weighted kappa method, calculating intraclass correlation coefficients, and generating Bland-Altman plots (P<0,05). …”
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Speckle-Based Transmission and Dark-Field Imaging for Material Analysis with a Laboratory X-Ray Source by Diego Rosich, Margarita Chevalier, Tatiana Alieva

“…Contrast-to-noise ratio (CNR) and linear attenuation, absorption and diffusion coefficients obtained from BF, T and DF images are studied for two object-to-detector distances (ODDs). …”
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Exploration of demographic prevalence of mild cognitive impairment using Montreal cognitive assessment: A cross-sectional pilot study in the Cape Coast Metropolis, Ghana. by David Larbi Simpong, George Nkrumah Osei, Richeal Odarko Mills, Christopher Amaleyele Anyebem, Benjamin Kofi Aikins, Charlotte Gyanwaa Melfah, Bridget Amoanimaa Osei, Ansumana Bockarie

“…The Pearson correlation coefficient was used to determine the relationship between educational level and MoCA score. …”
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Modeling the spread of forest fires through cellular automata by leveraging deep learning to derive transition rules by Zucheng Zhou, Quanli Xu, Junhua Yi, Youyou Li, Shiying Zhang, Wenhui Li

“…The Transformer model excels in capturing fire-spread patterns owing to its robust feature extraction abilities and capacity to manage long-range dependencies, enabling the automatic generation of CA transition rules that more accurately reflect real fire behavior and ultimately improve the simulation of fire spread. …”
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