Assessment of the active method to determine soil moisture by José Luis Serna Farfan, José Francisco Muñoz, Francisco Suárez

“…Our analysis allowed obtaining volumetric water contents ranging from 0.14 to 0.46 m3/m3, with errors that are smaller than 0.08 m3/m3.…”
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A Comparative Analysis of Buckling Pressure Prediction in Composite Cylindrical Shells Under External Loads Using Machine Learning by Hyung Gi Lee, Jung Min Sohn

“…</b> The results demonstrated that the random forest model and XGBoost regression achieved superior accuracy with minimal prediction errors. The study highlights the critical role of machine learning in predicting buckling pressure, which is essential for ensuring structural integrity and optimizing performance in marine engineering and other applications involving composite materials.…”
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Heuristics Influence on Investment Decision Making at Pakistan Stock Exchange: Mediation of Digital Financial Literacy and Moderation of AI Adoption by Akbar Saeed, Azam Anwar Khan

“…The study also tries to estimate how digital financial literacy works as a mediator since those who have higher digital skills will be able to interpret and evaluate the financial information more effectively while mitigating cognitive errors. Additionally, the paper considers how the increasing applicability of AI in investment frameworks can diminish the role of cognitive heuristics based on analysis by Susskind and Susskind (2015). …”
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Comparative Study of the Nonlinear Fractional Generalized Burger-Fisher Equations Using the Homotopy Perturbation Transform Method and New Iterative Transform Method by Mashael M. AlBaidani

“…In terms of absolute errors, the results obtained have been compared with those of alternative methods, including the Haar wavelet, OHAM, and q-HATM. …”
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A Graph Representation Learning-Based Method for Event Prediction by Xi Zeng, Guangchun Luo, Ke Qin, Pengyi Zheng

“…However, the existing methods suffer from poor data quality, insufficient feature information, limited generalization capability of the models, and difficulties in evaluating prediction errors. This paper proposes a novel event prediction method based on graph representation learning, aiming to improve the accuracy of event prediction while reducing the time cost. …”
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New tools for approaching translation studies by simulation environments: EVOLI and ECORE by Aba-Carina PÂRLOG, Marius-Mircea CRIŞAN

“…Some of the theorists we have considered in our research are Richard Andrews (on ICTs), Anthony William Bates (digital teaching), Roger Thomas Bell (translation studies), Pitt Corder (translation errors), Eric Sotto (learners’ motivation), alongside those of the translation studies (TS) leading personalities above. …”
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Optimization of periodic synchronization of UAV's clock by differential phase method by A.I. Sulimov

“…According to the simulation results, aside from the positioning errors of the UAVs, the systematic Doppler phase shift of the synchronizing signal in the propagation channel is the main obstacle to differential phase synchronization. …”
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Leveraging Deep Learning for Robust Structural Damage Detection and Classification: A Transfer Learning Approach via CNN by Burak Duran, Saeed Eftekhar Azam, Masoud Sanayei

“…This study highlights the integration of simulation data into the Deep Learning-based SHM framework, demonstrating that a generalized model created via Joint Learning utilizing FEM can potentially reduce the consequences of modeling errors and operational uncertainties unavoidable in real-world applications.…”
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Development and calibration of roundabout safety performance functions using machine learning: a case study from Amman, Jordan by Diana Al-Nabulsi, Aya Hassouneh

“…The linear regression model yielded an R 2 of 0.542 with a high sum of squared errors (SSE = 3750.38), underscoring its limited capacity to capture non-linear relationships. …”
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Modelado de propiedades mecánicas de mezclas asfálticas espumadas recicladas mediante regresión no lineal y redes neuronales artificiales y clasificación de diferentes diseños util... by Mehrdad Mirshekarian Babaki, Ali Pirhadi Tavandashti

“…The ANN model demonstrated greater accuracy with significantly lower prediction errors compared to the nonlinear regression model. …”
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Robust Hybrid Data-Level Approach for Handling Skewed Fat-Tailed Distributed Datasets and Diverse Features in Financial Credit Risk by Musara Keith R, Ranganai Edmore, Chimedza Charles, Matarise Florence, Munyira Sheunesu

“…The popularized DL approach in contemporary studies is the synthetic minority over-sampling technique (SMOTE) and its variants that are capable of mitigating the risk of overfitting and minimizing the generalization errors. However, these approaches can introduce noisy instances that adversely diminish the robustness of the ML algorithms. …”
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Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection by Qifan Yang, Yu-Ang Chen, Yifan Shi

“…Intrusion detection systems are crucial for cybersecurity applications. Network traffic data originate from diverse terminal sources, exhibiting multi-view feature spaces, while the collection of unknown intrusion data is costly. …”
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Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods by Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein, Narinderjit Singh Sawaran Singh, Barno Abdullaeva, Zubair Ahmad, Soheil Salahshour, Mohammadreza Baghoolizadeh, Mostafa Pirmoradian

“…Evaluating the performance of algorithms is based on the evaluation indices of Correlation coefficient (R), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Standard Deviation (STD). …”
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Wide-Field-of-View Modulating Retro-Reflector System Based on a Telecentric Lens for High-Speed Free-Space Optical Communication by Jiahan Tian, Tingbiao Guo, Nan He, Ji Du, Qiangsheng Huang, Xiaojian Hong, Chao Fei, Yuan Wang, Tianyi Zhang, Junping Zhang, Sailing He

“…The experimental results validate the proposed MRR has a FOV of up to 110&#x00B0; where the measured bit error rate (BER) is lower than 3.8 &#x00D7; 10^&#x2212;3 for both downstream and upstream signals. …”
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0.01% atropine combined with carteolol hydrochloride can inhibit the scleral remodeling in guinea pigs with form-deprivation myopia by Qin Xiang, Jing Yang, Qing Liu, Jing Fang, Xin Li, Xinyu Fu, Xu Gao, Zhou Fu

“…Abstract Myopia is the most widespread refractive error caused by an increase in the axial length (AL) of the eyeball, and is also a major risk factor for other blinding eye diseases, seriously endangering human health and quality of life. …”
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Distributed Non-Fragile State Estimation for Uncertain Nonlinear Systems of Sensor Networks Subject to Sensor Nonlinearities by Shihui Tian, Ke Xu, Fengshan Huang

“…In particular, the sensor nonlinearities in the sensor network and state estimation gain fluctuations are taken into account for more general applicability. With the help of the Lyapunov–Krasovskii approach, sufficient convex optimization criteria can be given so that the passivity performance of its resultant state estimation error system can be guaranteed. …”
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Basic assumptions, core connotations, and path methods of model modification—using confirmatory factor analysis as an example by Zhangbo Xiong, Huixian Xia, Jianjun Ni, Hongzhen Hu

“…Except for certain specific models, error correlations should only be established based on theoretical support to improve the model’s goodness-of-fit. …”
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A Comprehensive Ensemble Model for Marine Atmospheric Boundary-Layer Prediction in Meteorologically Sparse and Complex Regions: A Case Study in the South China Sea by Yehui Chen, Tao Luo, Gang Sun, Wenyue Zhu, Qing Liu, Ying Liu, Xiaomei Jin, Ningquan Weng

“…Based on the categorization of the total cloud cover data into weather conditions such as clear/slightly cloudy, cloudy/transitional, and overcast/rainy, the SOEM demonstrates enhanced performance with an average mean absolute percentage error of 3.7%, significantly lower than the planetary boundary-layer-height products of ERA5. …”
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Optimizing wind energy conversion system efficiency using advanced modified super-twisting direct power control: Real-time implementation on dSPACE 1104 board by Mourad Yessef, Habib Benbouhenni, Ahmed Lagrioui, Youness El Mourabit, Nicu Bizon, Ilhami Colak, Badre Bossoufi, Ayman Alhejji

“…Furthermore, the steady-state error, overshoot, and reactive power ripples were reduced by 60 %, 81.25 %, and 66.66 %, respectively, compared to the classical direct power control strategy.…”
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Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations by Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene

“…The model's high accuracy, with a coefficient of determination (R2) of 0.72 and a root mean square error (RMSE) of 21.2 min, indicates the potential of XAI in enhancing traffic management systems.…”
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