Evaluation of Factors Influencing Assistant Referee Decisions in Determining "Offside" in Football by Anatoly Abdula, Stanislav Marulin

“…The following research methods were used during the study: non-interventional observation, where regular observation was conducted from the side to study the decision-making process on the football field; video content analysis, where the technical aspects of referees' behavior were assessed; statistical methods to process the quantitative data obtained during experiments and observations; and the modeling method, which involved creating 3D computer models to analyze the impact of assistant referees' positions on the assessment of situations related to the interpretation of Law 11. …”
Get full text

Performance evaluation of rock fragmentation prediction based on RF‐BOA, AdaBoost‐BOA, GBoost‐BOA, and ERT‐BOA hybrid models by Junjie Zhao, Diyuan Li, Jian Zhou, Danial J. Armaghani, Aohui Zhou

“…The root mean square error (RMSE), the mean absolute error (MAE), and the coefficient of determination ( R 2) were used as the evaluation metrics. …”
Get full text

Assimilating satellite‐based canopy height within an ecosystem model to estimate aboveground forest biomass by E. Joetzjer, M. Pillet, P. Ciais, N. Barbier, J. Chave, M. Schlund, F. Maignan, J. Barichivich, S. Luyssaert, B. Hérault, F. vonPoncet, B. Poulter

“…The error budget was evaluated in details, and systematic errors related to the ORCHIDEE‐CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.…”
Get full text

Enhancing Time Series Product Demand Forecasting With Hybrid Attention-Based Deep Learning Models by Xuguang Zhang, Pan Li, Xu Han, Yongbin Yang, Yiwen Cui

“…Experimental results show that the HA-LSTM outperforms state-of-the-art baselines, including ARIMA, Prophet, and vanilla LSTM models, achieving a 15% improvement in Mean Absolute Percentage Error (MAPE) and a 12% reduction in Root Mean Square Error (RMSE). …”
Get full text

Calibration of DEM Polyhedron Model for Wheat Seed Based on Angle of Repose Test and Semi-Resolved CFD-DEM Coupling Simulation by Longbao Wang, Hanyu Yang, Zhinan Wang, Qingjie Wang, Caiyun Lu, Chao Wang, Jin He

“…In this scenario, the relative error of AOR was 2.3% and the maximum relative error of ejection velocity observed was 4.1%. …”
Get full text

Тhe effect of cancer patients’ positioning accuracy during radiation therapy sessions using medical linear electron accelerators on the parameters of their individual 3D dose distr... by M. N. Piatkevich, E. V. Titovich, G. V. Belkov

“…The purpose of the research is to determine the magnitude of the possible error for patients’ positioning during their radiotherapy treatments using medical linear accelerators by modeling the impact of the patient’s body on the treatment couch. …”
Get full text

Reducing Building Energy Performance Gap: Integrating Agent-Based Modelling and Building Performance Simulation by Chi-Li Chiang, John Calautit

Get full text

A WebGL Serious Game for Practicing English Conversations in Public Places Using Speech Recognition by Rickman Roedavan, Iis Kunia Nurhayati, Kemas Muslim Lhaksmana, Muhammad Yudhi Rezaldi, Esa Prakasa, Sritenaya Geovani Putri

“…The methodology includes system analysis using Word Error Rate (WER) and Average Word Error Rate per Sentence (Avg WER) to evaluate speech recognition accuracy. …”
Get full text

Accuracy of Wrist-Worn Heart Rate Monitors: A Comprehensive Review of Smartwatches in Exercise Monitoring by Katarzyna Paluch, Zofia Szypuła, Aleksandra Nowak, Oliwia Bochenek, Mateusz Koper, Jessica Kałuża, Adrian Konaszczuk, Klaudia Ratyna, Oliwia Kozyra, Małgorzata Skarbek

“…The Apple Watch consistently outperformed other devices, showing the lowest mean absolute percentage error (MAPE), particularly during moderate-intensity activities. …”
Get full text

A gradient-boosted tree framework to model the ice thickness of the world's glaciers (IceBoost v1.1) by N. Maffezzoli, N. Maffezzoli, N. Maffezzoli, E. Rignot, E. Rignot, C. Barbante, C. Barbante, T. Petersen, S. Vascon

“…Providing supervision by exposing the model to available glacier thickness measurements reduces the error by a factor of up to 2 to 3. A feature-ranking analysis reveals that geodetic data are the most informative variables, while ice velocity can improve the model performance by 6 % at high latitudes. …”
Get full text

Optimizing the Shape of Signals with Quadrature Amplitude Modulation According to the Criterion of Given Reduction Rate of Out-of-Band Emissions by S. B. Makarov, S. V. Zavjalov, A. S. Ovsyannikova

“…Almost all methods conventionally used to increase the data transfer rate in given frequency bands have been exhausted. …”
Get full text

Investigation of thermal-hydraulic coupling impact on transient modeling of steam flow in integrated energy systems by Wei Zhong, Meng Yuan, Xiaojie Lin, Liuliu Du-Ikonen, Long Jiang, Xiaolei Yuan, Long Huang

“…Through statistical analysis of actual industrial steam data, this study compares coupled numerical simulations against decoupled STAM solutions across diverse steam temperature fluctuations. …”
Get full text

Adaptation of Everyday Discrimination Scale (EDS) for Nurses: A Validity and Reliability Study in Turkish by Nazan Ulusoy, Hatice Ulusoy, Albert Nienhaus, Patrick Brzoska

“…Methods: The population and sample of the study consisted of nurses working in a university hospital in Turkey. Data were collected online between January and April 2023. …”
Get full text

Construction of a Surface Roughness and Burr Size Prediction Model Through the Ensemble Learning Regression Method by Ali Khosrozadeh, Seyed Ali Niknam, Fatemeh Hajizadeh

“…The model was trained using cutting parameters as inputs and evaluated with performance metrics such as mean absolute error (<i>MAE</i>), mean squared error (<i>MSE</i>), and the coefficient of determination (<i>R</i>²). …”
Get full text

Flaxseed protein content prediction based on hyperspectral wavelength selection with fractional order ant colony optimization by Bo Wang, Junying Han, Chengzhong Liu, Jianping Zhang, Yanni Qi

“…The FOACO-MLR model achieved a prediction accuracy of 0.9248, a root mean square error (RMSE) of 0.4346, a relative prediction deviation (RPD) of 3.6458, and a mean absolute error (MAE) of 0.3259. …”
Get full text

Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India by Waleed Makhdumi, Shwetha H. R., G. S. Dwarakish, Jagadeesha B. Pai

“…The model’s performance was evaluated using statistical metrics, including a correlation coefficient of 0.984, mean absolute error of 0.048, root mean square error of 0.058, and Kling-Gupta efficiency of 0.921, indicating superior accuracy compared to existing methods. …”
Get full text

Rudraksh: A compact and lightweight post-quantum key-encapsulation mechanism by Suparna Kundu, Archisman Ghosh, Angshuman Karmakar, Shreyas Sen, Ingrid Verbauwhede

“…We have done a scrupulous and extensive analysis and evaluation of different design elements, such as polynomial size, field modulus structure, reduction algorithm, and secret and error distribution of an LWE-based KEM. …”
Get full text

Method for Distinguishing the Digital Images in Different Formats by Kobozeva A.A., Bobok I.I., Kushnirenko N.I.

“…As a result of testing, Type I error was not detected, Type II error rate was 3.6%, ACC = 0.98. …”
Get full text

Assessment of geotechnical behavior of gypseous soil under leaching effect using machine learning by Saif M. Hassan Al-Riahi, Nur Irfah Mohd Pauzi, Mohammed Y. Fattah, Hasan Ali Abbas

“…Model performance was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (R). …”
Get full text

A deep learning based hybrid recommendation model for internet users by Amany Sami, Waleed El Adrousy, Shahenda Sarhan, Samir Elmougy

“…Furthermore, it incorporates Content-Based Filtering (CBF) with Term Frequency-Inverse Document Frequency (TF-IDF) for in-depth analysis of item attributes. A key contribution of this work is the innovative fusion of CF, NCF, RNN, and CBF, which collectively address significant challenges such as data sparsity, the cold-start problem, and the increasing demand for personalized recommendations. …”
Get full text