Method for Determining the Sea Waves Curvature Using Wave Buoys Conventional Shape by K. A. Gleb

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A modified algorithm of 'forward-backward' solving the identification of automata Markov models by A.R. Nurutdinova

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Study of Prospects of Two-Phase Gravity Thermosiphons Used in Waste Heat Boilers of Cogeneration Units by Dolganov Yu.A., Yepifanov А.A., Patsurkovskyi P.A., Sorokina T.N., Lychko B.M.

“…The root-mean-square error of experimental results was calculated, being up to 5.7%. …”
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Design Method of a Cylindrical Skiving Tool for Internal Gear with Circular Arcs by Erkuo Guo, Mingfeng Chen, Xuechao Pan, Yayun Yuan, Hua Qiao

“…The experimental results demonstrated that the tooth profile error of the gear fell within ±0.004 mm, thereby satisfying the accuracy requirement for pin wheel housing gears. …”
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Cognitive control of memory in a food-storing and a non-storing bird species by Emily Kathryn Brown, David F. Sherry, Robert R. Hampton

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On the Criteria for Evaluating an Expert's Opinion and Forensic Methods by Participants in the Legal Proceedings by P. Giverts, A. Griber, A. V. Kokin

“…In particular, the structures of the so-called subjective methods do not provide calculations of a known or potential error rate as well as a mechanism for monitoring the conduct of various stages of a study. …”
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Mathematical modeling of blood flow with copper and graphene nanoparticles in inclined stenotic arteries by Pooriya Majidi Zar, Zahra Poolaei Moziraji, Ali Ahmadi Azar

“…Abstract This research investigates hemodynamic behavior in stenosed arteries using a rheological model that integrates hybrid nanoparticles (copper and graphene) suspended in blood. …”
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Intelligent Renewable Energy Agent-Based Distributed Control Design for Frequency Regulation and Economic Dispatch by Amjad Khan, Amjad Ullah Khattak, Bilal Khan, Sahibzada Muhammad Ali, Zahid Ullah, Faisal Mehmood

“…Intelligent renewable energy agents are trained through machine learning-based regression models that use root mean square error metrics for performance evaluations. The intelligent agents employ DAI control to overcome inherent limitations. …”
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AI chatbots in programming education: guiding success or encouraging plagiarism by Gökhan Akçapınar, Elif Sidan

“…Even more interestingly, despite the AI-generated response containing an obvious error, 22 of them (61%) copied and pasted the AI's response directly into the answer field. …”
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The use of the localization method for calculation of the robust PID regulator parameters for unmanned aircraft servo motor by A. A. Sanko, A. A. Sheinikov, T. A. Tishchenko, D. A. Smolskiy

“…For the synthesis of robust control circuits of an unmanned aercraft with given characteristics, mathematical dependences of the settling time and static error of a typical servo motor with LM PID controller from the quantization period of the input signal and the degree of uncertainty in its parameters are presented.…”
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Phase-Field Simulation of the Creep Mechanism in the AZ31 Magnesium Alloy Under Discontinuous Dynamic Recrystallization Dominance by Alireza Rezvani, Ramin Ebrahimi, Ebad Bagherpour

“…The model accurately predicts recrystallization kinetics and microstructural evolution, exhibiting a strong correlation with experimental results, with an error of approximately 5%. This research provides a robust and efficient approach for predicting creep behavior in high-temperature applications, vital for optimizing material selection and predicting component lifespan in industries. …”
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Mixture Design Study of Fiber-Reinforced Self-Compacting Concrete for Prefabricated Street Light Post Structures by Wael Zatar, Tu Nguyen

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Nanometer-Scale CO2-Shale Oil Minimum Miscibility Pressure Calculations Based on Modified PR-EOS by Yahui Bu, Qian Sun, Shuoran Fu, Lingkong Guo, Na Zhang

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Application of Seq2Seq models for predicting the development of thunderstorm activity to enhance the pilot’s situational awareness in flight by G. V. Kovalenko, I. A. Yadrov

“…The results showed that convolutional recurrent neural networks (ConvRNN, ConvLSTM, ConvGRU) outperform classical recurrent models and improve the thunderstorm forecast by 25–30% in terms of RMSE (root mean square error) metric compared to the baseline model, which always selects the most recent radar image available at the time of prediction. …”
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Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method by Annisa Zahara Lutfi, Heptari Elita Dewi, Djoko Koestiono, Ajeng Rizqya Shabrina, Aleisha Julia Deme Anak Julin

“…The results showed that SME SL applies executive opinion for forecasting, and the best model for forecasting product demand is the SARIMA model (0,1,1) (0,1,1)12, because it produces an MSE error value of 1.8868 and a MAPE value of 0.20% with the highest demand in January 2023 of 866.32 kg. …”
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Meta-Analysis of Predictive Role of Early Neurological Deterioration after Intravenous Thrombolysis by Haiwei Jiang, Jing Zuo, Dan Wang, Yi Huang, Chang Gao, Yue Wan

“…With the development of medical technology, research on the prediction of END after intravenous thrombolysis has gradually been carried out. …”
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Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

“…They are costly, lack the essential sensitivity or precision and are frequently susceptible to error. In this regard, an automated system that can analyse and diagnose pulmonary TB by using Chest X-Rays (CXR) can prove to be a cost effective, dependable and quick alternative to manual diagnostic methods. …”
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Analytical Solutions for Girder Distribution Factor in Steel-Concrete Composite Girders with the Effect of Parapets by Zejun Zhang, Yongjian Liu, Bowen Feng, Yinping Ma, Guojing Zhang

“…Then, finite-element (FE) model was established and verified by the field test data of strain and deflection. In addition, error study showed that the bending stiffness of the bridge was increased by about 92% and 19.1%, respectively, due to the effects of parapet and continuous layer. …”
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A Water Quality Prediction Model Based on Long Short-Term Memory Networks and Optimization Algorithms by Aihua Yu, Qingjie Xiao

“…In comparison with the previous prediction models such as SVR, LSTM, CNN-LSTM and CNN-GRU, obviously, the prediction effect of AWPSO-LSTMAT is significantly improved by means of modifying and optimizing the original algorithm. The mean absolute error (MAE) in predicting PH, dissolved oxygen (DO), ammonia nitrogen (AN) and total phosphorus (TP) are 0.039, 0.34, 0.119 and 0.019, respectively. …”
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From Traditional Marketplace to Online Shop: Shifting Shopping Patterns among University Students in Bangladesh by Md. Habibullah Balaly, Md. Rabiul Islam, Niaz Makhdum, A.M.M. Mubassher Shah, Hasanul Banna

“…Quantitative method was employed, and the data were collected using simple random sampling from 384 students, determined based on 95% confidence level and 5% margin of error, from three different universities in Bangladesh. …”
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