A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

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Reference library for suspect screening of environmental toxicants using ion mobility spectrometry-mass spectrometry by Devin Teri, Noor A. Aly, James N. Dodds, Jian Zhang, Paul A. Thiessen, Evan E. Bolton, Kara M. Joseph, Antony J. Williams, Emma L. Schymanski, Ivan Rusyn, Erin S. Baker

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Application of multiple linear regression model and long short-term memory with compartmental model to forecast dengue cases in Selangor, Malaysia based on climate variables by Xinyi Lu, Su Yean Teh, Chai Jian Tay, Nur Faeza Abu Kassim, Pei Shan Fam, Edy Soewono

“…Extended validation across subsequent periods also indicates relatively satisfactory forecasting performance (with MAPE ranging from 13.12 to 17.09). This research contributed to the field by introducing a novel framework for the prediction of dengue cases over an extended temporal range.…”
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Wearable Devices for Quantifying Atrial Fibrillation Burden: A Systematic Review and Bayesian Meta-Analysis by Ioannis Anagnostopoulos, Dimitrios Vrachatis, Maria Kousta, Sotiria Giotaki, Dimitra Katsoulotou, Christos Karavasilis, Gerasimos Deftereos, Nikolaos Schizas, Dimitrios Avramides, Georgios Giannopoulos, Theodore G. Papaioannou, Spyridon Deftereos

“…Bayesian analysis revealed no statistically significant differences between wearables and reference methods in AF burden quantification. The mean error was 1% (95% CrIs: −4% to 7%). Similar findings were observed in the subgroup analysis of studies assessing only smartwatches. …”
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Optimization design and experiment of cam-elliptical gear combined vegetables curved surface labeling mechanism by Lei Zhang, Lei Zhang, Heng Zhou, Jianneng Chen, Jianneng Chen, Junhua Tong, Junhua Tong, Yang Liu, Xiaowei Zhang

“…The correctness of the proposed method is validated through simulation studies and experiments. This research provides a theoretical basis for the design and optimization of long label and curved surface labeling mechanism for vegetables.…”
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Artificial Neural Network Approach to Predict Carbonation Depth in Metakaolin, Brick Powder and Calcined Sediments-Modified Mortars by Benamar Souheyla, Kameche Zine El Abidine, Mamoune Sidi Mohamed Aissa, Siad Hocine, Houmadi Youcef

“…This research uses Artificial Neural Network (ANN) as a soft computing technique to predict the carbonation depth and service life of cementitious materials with low clinker content. …”
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SVM-Assisted Realization and Demonstration of Indoor 4 Mb/s Non-Line-of-Sight Visible Light Communication With Second-Order Reflection by Yonghe Zhu, Chen Gong, Jianghua Luo, Zhengyuan Xu, Weiqiang Xu

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A Non-Contacted Height Measurement Method in Two-Dimensional Space by Phu Nguyen Trung, Nghien Ba Nguyen, Kien Nguyen Phan, Ha Pham Van, Thao Hoang Van, Thien Nguyen, Amir Gandjbakhche

“…Results indicate that the proposed method yields height measurements with a minimal error margin of approximately 1.2%. Future research will extend this approach to accommodate additional positions, such as lying down, cross-legged, and bent-legged. …”
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Advanced 3D Depth Imaging Techniques for Morphometric Analysis of Detected On-Tree Apples Based on AI Technology by Eungchan Kim, Sang-Yeon Kim, Chang-Hyup Lee, Sungjay Kim, Jiwon Ryu, Geon-Hee Kim, Seul-Ki Lee, Ghiseok Kim

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Coverage Estimation of Droplets Sprayed on Water-Sensitive Papers Based on Domain-Adaptive Segmentation by Dae-Hyun Lee, Baek-Gyeom Seong, Seung-Yun Baek, Chun-Gu Lee, Yeong-Ho Kang, Xiongzhe Han, Seung-Hwa Yu

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Bridging the Sim-to-Real Gap in Motion Planning for Autonomous Electric Vehicles Using Autoware: A Comparative Study of Simulation and Real-World Deployment by Manikandan Ganesan, Bharatiraja Chokkalingam, Sivanathan Kandhasamy, Rajesh Verma, Lucian Mihet-Popa

“…Velocity and steering angle tracking demonstrated minor deviations due to actuator constraints and road conditions. This research provides valuable insights into bridging the sim-to-real gap in AEV trajectory planning, paving the way for safer and more reliable autonomous driving systems.…”
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Comparison Between Broadband and Personal Exposimeter Measurements for EMF Exposure Map Development Using Evolutionary Programming by Alberto Nájera, Rocío Sánchez-Montero, Jesús González-Rubio, Jorge Guillén-Pina, Ricardo Chocano-del-Cerro, Pablo-Luis López-Espí

“…In this study, we provide a comparison of radiofrequency electromagnetic field exposure level maps as determined using two approaches: a broadband meter (NARDA EMR-300) equipped with an isotropic probe in the range of 100 kHz to 3 GHz, and a Personal Exposimeter (Satimo EME Spy 140) in the range of 88 MHz to 5.8 GHz. The aim of this research was to determine the necessary adjustments to the measurements made with personal exposimeters to obtain RF-EMF exposure maps equivalent to those made with broadband meters. …”
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Predicting the Fatigue Life of a Commercial Vehicle X-EPS Steering Gear with a Rigid–Flexible Coupling Dynamics Method by Feng Chen, Zhiquan Fu, Baoxiang Qiu, Chenfeng Si, Qizhang Zhu, Chenli Feng, Xiaoqing Sun, Huafang Liang, Lai Yang

“…Then, combined with the material S-N curve, the fatigue life is predicted through the NOCDE fatigue “five-block diagram”. The research results show that the screw and nut raceways are the key components prone to fatigue failure in the steering gear. …”
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The Potential for Hyperspectral Imaging and Machine Learning to Classify Internal Quality Defects in Macadamia Nuts by Michael B. Farrar, Marcela Martinez, Kim Jones, Negar Omidvar, Helen M. Wallace, Thomas Chen, Shahla Hosseini Bai

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Software Cost and Effort Estimation: Current Approaches and Future Trends by Chaudhary Hamza Rashid, Imran Shafi, Jamil Ahmad, Ernesto Bautista Thompson, Manuel Masias Vergara, Isabel de la Torre Diez, Imran Ashraf

“…Software cost and effort estimation is one of the most significant tasks in the area of software engineering. Research conducted in this field has been evolving with new techniques that necessitate periodic comparative analyses. …”
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Intra-Session Reliability and Predictive Value of Maximum Voluntary Isometric Contraction for Estimating One-Repetition Maximum in Older Women: A Randomised Split-Sample Study by José Aldo Hernández-Murúa, Ena Monserrat Romero-Pérez, Jorge Luis Guajardo-Cruztitla, Blas Sinahí Madrigal Olivares, Ángel Gallego-Selles, Diego González-Martín, Francisca Reyes-Merino, Nidia Sánchez-García, José Antonio de Paz

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UAV-Based Remote Sensing Monitoring of Maize Growth Using Comprehensive Indices by Tingrui Yang, Jinghua Zhao, Ming Hong, Mingjie Ma, Shijiao Ma, Yingying Yuan

“…Timely, efficient, and accurate acquisition of crop growth data is crucial for agricultural decision-making and management. This research focuses on maize, utilizing unmanned aerial vehicle (UAV) technology to monitor its growth and gather data on plant height, chlorophyll content, and leaf area index. …”
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Bonding behavior of lap-spliced reinforcing bars embedded in ultra-high-performance concrete with steel fibers by Krairerk Aiamsri, Teerasak Yaowarat, Suksun Horpibulsuk, Apichat Suddeepong, Apinun Buritatum, Kanchana Hiranwatthana, Kirati Nitichote

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Reliability and Accuracy of Ultrasonographic Muscle Thickness Measurements: Evaluating Key Postural Stabilisers in Rehabilitation by Arkadiusz Żurawski, Natalia Barańska, Aleksandra Tomala, Edyta Majorczyk, Joanna Macierzyńska

“…The transversus abdominis demonstrated the highest measurement precision, with the lowest Standard Error of Measurement (SEM = 0.79-1.05 mm) and Minimal Detectable Change (MDC = 2.19-2.91 mm). …”
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Random Forest Regression May Become the Optimal Regression Model for Osteoarthritis of the Knee in Elderly, in the Context of Embodied Cognition and Psychosomatic Medicine by Ma G, Chen J, Li J, Shi H, Chen Y

“…Five regression techniques—non-negative linear regression, stochastic gradient descent (SGD), AdaBoost, Random Forest, and Gradient Boosting Decision Trees (GBDT)—were evaluated using R², mean squared error (MSE), and mean absolute error (MAE). Bootstrap resampling and the Kruskal–Wallis test were applied to ensure robustness and compare model coefficients.Results: Random Forest regression achieved the highest performance (R² = 0.687, MSE = 0.589, MAE = 0.785), followed by AdaBoost. …”
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