Predicting the permeability and compressive strength of pervious concrete using a stacking ensemble machine learning approach by Fan Yu, Wei Chu, Rui Zhang, Zhang Gao, Yunan Yang

“…Firstly, six independent models, the multiple linear regression and the Stacking algorithm were applied to construct the ensemble model. …”
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Mechanistic insights into synergistic effects using coupled PK-PD modeling by Jinzhou Sun, Qianqian Chen, Chumeng Zhuang, Xiaohong Li, Li Yu, Weifeng Jin

“…The model also showed that CA had a larger apparent volume of distribution and clearance in rats, while HSYA had a shorter mean retention time and elimination half-life. …”
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Data-driven robust outpatient physician scheduling with medical visiting information by Qingyun He, Shuqun Shen, Zhiyu Lv, Shixin Yang

“…In this study, we develop a data-driven optimization framework for a mid-term period spanning several weeks within the outpatient department of a dermatology hospital. …”
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Controversies in treating nutcracker syndrome by Vitorio Perić, Thomas Ferenc, Tomica Bratić, Jana Bebek, Ivan Antun Mašić, Filip Ferega, Vid Vrčić, Danko Milošević, Helga Sertić Milić, Vinko Vidjak

“…Moreover, due to the lack of standardized treatment guidelines, the optimal management of anterior NCS remains a topic of debate. …”
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Proposal of Low-Speed Sensorless Control of IPMSM Using a Two-Interval Six-Segment High-Frequency Injection Method with DC-Link Current Sensing by Daniel Konvicny, Pavol Makys, Alex Franko

“…The dual-period structure, termed the two-interval six-segment high-frequency injection, allows for more precise current measurement during the signal injection period while maintaining optimal motor control during the field-oriented control period. …”
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Externally bonded reinforcement side extended (EBRSE) technique to postpone debonding of FRP laminates in strengthened concrete elements by Mehdi Aghabagloo, Laura Carreras, Cristina Barris, Alba Codina, Marta Baena

“…Additionally, a numerical approach was applied, combining the finite difference method with a metaheuristic optimization algorithm, to derive the bond-slip law governing the constitutive behavior of both systems. …”
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ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…Haar wavelet downsampling (HWD) was applied to optimize the Adaptive Downsampling module (Adown) of the initial model, thereby increasing the precision of object detection. …”
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Potential effects of climate change on the threatened Malagasy poison frogs: A multispecies approach by Albert Carné, David R. Vieites, Neftalí Sillero

“…Range shifts tracking their optimal niche conditions are expected for nearly all species, but the receptor areas are not always suitable. …”
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Development and validation of machine learning models to predict unplanned hospitalizations of patients with diabetes within the next 12 months by A. E. Andreychenko, A. D. Ermak, D. V. Gavrilov, R. E. Novitskiy, A. V. Gusev

“…The creation and inference of a machine learning model for predicting hospitalizations of patients with DM to an inpatient medical facility will make it possible to personalize the provision of medical care and optimize the load on the entire healthcare system.AIM: Development and validation of models for predicting unplanned hospitalizations of patients with diabetes due to the disease itself and its complications using machine learning algorithms and data from real clinical practice.MATERIALS AND METHODS: 170,141 depersonalized electronic health records of 23,742 diabetic patients were included in the study. …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…The BP neural network algorithm adjusts weights to minimize prediction errors, while multi-scale feature learning captures the diversity and regularity of user behavior by extracting data from various time dimensions, such as daily, weekly, and monthly intervals. …”
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Analyzing the applicability of psychometric QoE modeling for projection-based point cloud video quality assessment by Sam Van Damme, Jeroen van der Hooft, Filip De Turck, Maria Torres Vega

“…Satisfying results are yet obtained with correlation values often going above 0.700 on GOP- and frame-level while maintaining root mean squared error (RMSE) below 10 on a 0–100 scale. …”
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A study on the correlation between MBTI dimensions and driving behavior characteristics by Liwei Bai, Tao Wang, Jianyao Tu, Bozhezi Peng, Zhuoyu Wang

“…These findings provide theoretical support for personalized traffic management strategies and the optimization of autonomous driving systems.…”
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Dataset of noise signals generated by smart attackers for disrupting state of health and state of charge estimations of battery energy storage systemsMendeley by Alaa Selim, Huadong Mo, Hemanshu Pota

“…The low-magnitude noise signals are specifically crafted to be stealthy, evading easy detection while still effectively causing malfunctions in the estimation processes. …”
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Graph Neural Network Aided Detection for the Multi-User Multi-Dimensional Index Modulated Uplink by Xinyu Feng, Mohammed El-Hajjar, Chao Xu, Lajos Hanzo

“…The GEPNet detector maximizes the detection performance, while the GNN-AMP detector strikes a performance versus complexity trade-off. …”
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Prototypical Few-Shot Learning for Histopathology Classification: Leveraging Foundation Models With Adapter Architectures by Kazi Rakib Hasan, Sijin Kim, Junghwan Cho, Hyung Soo Han

“…The iBOT model with multilayer perception adapters fine-tuned using the bias-diminishing cosine similarity-based prototypical network algorithm achieved remarkable accuracy, reaching 95.04% on Camelyon17 Wilds and 96.55% on the NCT dataset with 20 images per class while using less than 0.002% of the dataset. …”
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Assessment of salt tolerance in peas using machine learning and multi-sensor data by Zehao Liu, Qiyan Jiang, Yishan Ji, Rong Liu, Hongquan Liu, Xiuxiu Ya, Zhenxing Liu, Zhirui Wang, Xiuliang Jin, Tao Yang

“…The results show that: 1) multi-source data fusion significantly improved the accuracy of AGB and SPAD estimation; 2) the CatBoost algorithm achieved the highest performance for AGB estimation (R² = 0.70, RMSE = 1.59 t/hm2, NRMSE = 13.94 %), while the LightGBM algorithm performed best for SPAD estimation (R² = 0.60, RMSE = 2.33, NRMSE = 14.53 %); and 3) The PSTS established based on the optimal estimation data exhibits a strong consistency with the ground-measured data. …”
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Development and evaluation of a soft pneumatic muscle for elbow joint rehabilitation by Mostafa Orban, Mostafa Orban, Mostafa Orban, Kai Guo, Kai Guo, Caijun Luo, Caijun Luo, Hongbo Yang, Hongbo Yang, Karim Badr, Karim Badr, Mahmoud Elsamanty, Mahmoud Elsamanty

“…The algorithm achieved a high predictive accuracy of 99.8% in spatial coordination tracking, indicating the precision of the system in monitoring and controlling the actuator’s motion.…”
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Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix by Jitendra Singh, Aditya K. Jagannatham, Lajos Hanzo

“…Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. …”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study synergized the strengths of RTM and machine learning algorithm while overcoming the limitations of RTM parameterization and generalization, providing an efficient and robust Landsat FAPAR estimation approach. …”
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Feasibility of automating the determination of changes in forest areas using satellite images (Case Study: Central Alborz protected area) by Amir Satari Rad, Behzad Rayegani, Ali Jahani, Hamid Goshtasb Meigooni

“…Then, using the Google Earth system, these points were validated.Results By applying PCA to the images, the amount of noise was reduced to the optimal level while maintaining the original information of the images. …”
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