Uniform Quantization for Multi-Antenna Amplify–Quantize–Forward Relay by Gangsan Jeong, Xianglan Jin

“…We start with theoretical analyses to determine quantization step sizes by deriving the power and mean square error of the quantized signals as functions of these step sizes. …”
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Balancing complexity and accuracy for defect detection on filters with an improved RT-DETR by Maoyuan Zhang, Xiaojuan Wei, Guojun Liu, Mengxu Chen, Chunxia Zhao, Yingxiao Liu, Zhikang Bao, Yunfeng Guo, Run An, Pengcheng Zhao

“…However, existing defect detection algorithms often struggle to balance between detection accuracy and the computational efficiency required for industrial deployment. …”
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Effortless alkalinity analysis using AI and smartphone technology, no equipment needed, from freshwater to saltwater by Zachary Y. Han, Zihan Zheng, Alan Y. Han, Huichun Zhang

“…After examining the effects of container type, lighting condition, ML algorithms, and sample size, we obtained the best models with R2 values of 0.868 ± 0.024 and 0.978 ± 0.008, and root-mean-square-error values of 29.5 ± 2.6 and 14.1 ± 2.0 for freshwater and saltwater, respectively. …”
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A Comprehensive Monte Carlo-Simulated Dataset of WAXD Patterns of Wood Cellulose Microfibrils by Ricardo Baettig, Ben Ingram

“…It enables the development, validation, and benchmarking of novel algorithms and machine learning models for MFA prediction from diffraction patterns. …”
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A Comparison of Effective doses for the 16, 64, and 128-slice Computed Tomography Scanners: A First Health Cluster Study in Riyadh by Mansour Al Moudi, Sultan Al Dosari, Abdullah Ibrahim Al Hussain, Mazen Abounassif

“…Several strategies have been implemented to reduce the radiation dose from CT, including a low tube voltage, a high pitch protocol, automatic tube current modulation, and iterative reconstruction algorithms. These strategies have reduced the radiation dose from the previously reported >20 mSv to <3–5 mSv or even <1 mSv. …”
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Evaluating a Procedural Content Orchestrator Gameplay Data and Classifying User Profiles by Leonardo Tórtoro Pereira, T. Yuji Teoi, Claudio Fabiano Motta Toledo

“… Background: Content Orchestration is a novel research field focused on coordinating distinct types of algorithmically generated game content. Purpose: Thus, the lack of research in this area hinders the analysis of gameplay data and player profiling in games with orchestrated content. …”
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Capturing spatiotemporal variation in salt marsh belowground biomass, a key resilience metric, through geoinformatics by Kyle D. Runion, Deepak R. Mishra, Merryl Alber, Mark A. Lever, Jessica L. O'Connell

“…We used the BERM machine learning algorithms to evaluate how variables relating to biological, climatic, hydrologic, and physical attributes covaried with these BGB observations. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Performance was evaluated using Loss function values, predicted Local Distance Difference Test (pLDDT), distance-based Root Mean Square Deviation (dRMSD), and Template Modeling (TM) scores. …”
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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

“…The coefficient of determination (R 2) and root mean square error (RMSE) values vary between various models; however, XGB showed R 2 = 0.99 and RMSE = 0.11. …”
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Enhancing Wind Turbine Power Output Estimation Using Causal Inference and Adaptive Neuro-Fuzzy Inference System ANFIS by Ahmed A. Mostfa, Nawfal A. Zakar, Rasha Raad Al-Mola, Abdel-Nasser Sharkawy

“…To meet the demand for renewable energy at the lowest cost, wind energy became the target of machine learning algorithms and was employed to predict the output power of wind turbines. …”
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SIGNAL MODEL FOR SPATIAL POSITION SENSORS IN MAGNETIC TRACKING SYSTEMS by Roman Holyaka, Tetyana Marusenkova, Dmytro Fedasyuk

“…For verification of the introduced signal model we propose to use the mean square deviation of normalized signals. Conclusions. …”
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Using machine learning to identify key predictors of maternal success in sheep for improved lamb survival by Ebru Emsen, Bahadir Baran Odevci, Muzeyyen Kutluca Korkmaz

“…Several machine learning algorithms, including Random Forest, Decision Trees, Logistic Regression, and Support Vector Machines (SVM), were evaluated for predictive accuracy. …”
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RESEARCH OF THE HIGH HARMONICS INDIVIDUAL BLADE CONTROL EFFECT ON VIBRATIONS CAUSED BY THE HELICOPTER MAIN ROTOR THRUST by B. S. Kritsky, R. M. Mirgazov, Le Van Chung

“…The largest values of deviation from the mean amplitude thrust are received. The analysis of variable loads with a traditional control system is made. …”
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A deep-learning approach to predict reproductive toxicity of chemicals using communicative message passing neural network by Owen He, Daoxing Chen, Yimei Li

“…In independent test sets, ReproTox-CMPNN achieved a mean AUC of 0.946, ACC of 0.857 and F1 score of 0.846, surpassing traditional algorithms to establish itself as a new state-of-the-art model in this field. …”
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Solar radiation prediction: A multi-model machine learning and deep learning approach by C Vanlalchhuanawmi, Subhasish Deb, Md. Minarul Islam, Taha Selim Ustun

“…A feature selection process using Pearson’s coefficient identified the most relevant inputs, while quantile regression was employed for uncertainty assessment, mean prediction interval, and prediction interval coverage probability models. …”
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Relationship Between Weight Status and Health-Related Quality of Life in School-age Children in China by Mandana Zanganeh, Peymané Adab, Bai Li, Miranda Pallan, Wei J. Liu, Lin Rong, Wei Liu, James Martin, Kar K. Cheng, Emma Frew

“…CHU-9D-CHN utility scores were generated using 2 scoring algorithms (UK and Chinese tariffs). Height and weight measures were taken at school by trained researchers using standardized methods, and BMI _z_ scores were calculated using the World Health Organization 2007 growth charts. …”
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Enhancing Reliability in Redundant Homogeneous Sensor Arrays with Self-X and Multidimensional Mapping by Elena Gerken, Andreas König

“…Initially, four individual TMR sensors exhibited mean absolute error (MAE) of 4.709°, 5.632°, 2.956°, and 1.749°, respectively. …”
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The Impact of AI-Generated Instructional Videos on Problem-Based Learning in Science Teacher Education by Nikolaos Pellas

“…The limited impact of the preview feature highlights the need for careful design and evaluation of instructional elements, such as interactivity and adaptive learning algorithms, to fully realize their potential.…”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. …”
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Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model by Md. Siddikur Rahman, Miftahuzzannat Amrin, Md. Abu Bokkor Shiddik

“…Results Our study findings detected a nonlinear effect of climatic parameters on dengue at different thresholds such as mean (27°C), minimum (22°C), maximum temperatures (32°C), and relative humidity (82%). …”
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