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

“…Since current state-of-the-art research is focusing on either continuous QoE monitoring of traditional video streaming services or objective delivery optimizations of point cloud content without any QoE validation, we believe this work brings a valuable contribution to current literature. …”
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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

“…Using Deep Reinforcement Learning (DRL) agent known as Proximal Policy Optimization (PPO), noise signals in the form of subtle millivolt and milliampere variations are strategically created to represent realistic cases of False Data Injection Attacks (FDIA). …”
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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

“…In the LS-MU-MIMO-UL scenario considered, the proposed system uses optimal Maximum Likelihood (ML) and Minimum Mean Square Error (MMSE) detectors as benchmarks for comparison with the proposed MP-based detectors. …”
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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

“…These findings underscore the effectiveness of the proposed approach in addressing challenges posed by low-data regimes in the computer-aided histopathology domain and the potential for optimizing foundation models with minimal labeled data using prototypical few-shot algorithms.…”
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How Small Can S-boxes Be? by Chenhao Jia, Tingting Cui, Qing Ling, Yan He, Kai Hu, Yu Sun, Meiqin Wang

“…As a contrast, the designer’s original circuit has an area of 23.33 GE, while the optimized result by Lu et al. achieves an area of 17.66 GE. …”
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Artificial Intelligence-Based Techniques for Fouling Resistance Estimation of Shell and Tube Heat Exchanger: Cascaded Forward and Recurrent Models by Ikram Kouidri, Abdennasser Dahmani, Furizal Furizal, Alfian Ma’arif, Ahmed A. Mostfa, Abdeltif Amrane, Lotfi Mouni, Abdel-Nasser Sharkawy

“…The training process is optimized using the Levenberg–Marquardt (LM) algorithm, ensuring rapid convergence and high accuracy. …”
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Deep learning-based technique for investigating the behavior of MEMS systems with multiwalled carbon nanotubes and electrically actuated microbeams by Muhammad Amir, Jamshaid Ul Rahman, Ali Hasan Ali, Ali Raza, Zaid Ameen Abduljabbar, Husam A. Neamah

“…The primary aim of this study is to investigate the nonlinear vibration properties of MEMS oscillators, specifically those related to nanotubes and electrically actuated microbeams, using DNN algorithms. Different optimizers are used to analyze the performance and capability of these non-linear dynamical models. …”
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Predicting weather-related power outages in large scale distribution grids with deep learning ensembles by L. Prieto-Godino, C. Peláez-Rodríguez, J. Pérez-Aracil, J. Pastor-Soriano, S. Salcedo-Sanz

“…This paper focuses on predicting daily reported incidences in electrical grids within specific regions, leveraging weather conditions as specific predictive variables. An optimization-based feature selection approach has been considered for selecting the optimal Reanalysis node locations used as predictors. …”
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SQNR Improvement Enabled by Nonuniform DAC Output Levels for IM-DD OFDM Systems by Jizong Peng, Lei Han, Qingming Zhu, Ciyuan Qiu, Yong Zhang, Christine Tremblay, Yikai Su

“…Our scheme enables transmission of such signals with no further optimization with ∼−25-dBm receiver sensitivity, while it is impossible using a conventional way. …”
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Deep Learning-Based Secrecy Performance of UAV-IRS NOMA Systems With Friendly Jamming by Kajal Yadav, Prabhat K. Upadhyay, Jules M. Moualeu, Amani A. F. Osman, Pedro H. J. Nardelli

“…Subsequently, the accuracy of the proposed theoretical framework is validated through comprehensive Monte Carlo simulations. We also propose an algorithm that determines an optimal power allocation. …”
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Experimental and numerical investigations on the bidirectional thermal contact performance by Chen Wang, Mingjun Qiu, Huijing Liu, Jun Hong, Feiyu Gu, Lifei Chen, Tao Wang, Hao Guan, Qiyin Lin

“…These results suggest an optimal TCR ratio threshold for maximizing thermal rectification coefficient. …”
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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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Multiplicity and stability of solutions in transport phenomena of non-Newtonian Carreau nanofluid with nonlinear Rosseland thermal approximations and neural prediction by Puneet Rana, Xinyi Zhu, Ioan Pop

“…The optimal number of neurons in a single hidden layer is determined and compared using metrics R2 and RMSE for each algorithm. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…The research methods include data collection and processing, construction and optimization of ML models, and the application of a risk assessment framework. …”
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Modify a dual ridge horn antenna for drone jamming applications by Alaa Hussein Hilal, Ahmed Hameed Reja, Mohammed J. Mohammed

“…This work presents a DRHA developed utilizing CST Studio and optimized by using genetic algorithm optimization (GA) that has been employed to improve parameters that enhance selected frequencies. …”
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High-voltage defibrillator unit with increased energy output from a controlled capacitor storage by E. E. Gorokhov-Miroshnikov, G. V. Slyusarev

“…The model of the proposed high-voltage unit shows the possibility of increasing the energy output from the capacitor bank when forming a pulse of optimal duration with a flat front. In this case, parallel-series restructuring of the battery capacitors is used, the algorithm of which is planned depending on the resistance of the patient's chest, which allows increasing the amount of energy given off by more than 85% of the accumulated energy of the capacitor bank. …”
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A Multi-Mode Switching Energy Management Strategy Based on Travel Habits for Range-Extended Electric Vehicle by Zhenhai Gao, Guoqing Zhang, Hanwu Liu, Cheng Chang, Jingwen Dong, Rongrong He, Yu Cai

“…To achieve the optimal energy allocation for the auxiliary power unit (APU) and battery of a range-extended electric vehicle (REEV), a travel habit-based multi-mode switching energy management strategy (M-MSEMS) has been introduced. …”
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Early feature study of Yunnan pine pinewood nematode disease based on hyperspectral remote sensing of ground objects by Xiao Zhang, Yingqun Gao, Lianjin Fu, Yiran Zhang, Zeyu Li, Qingtai Shu

“…Study identified the spectral ranges 455–677 nm and 1974–2340 nm as optimal diagnostic windows. Using Competitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA), we identified diagnostic spectral bands: CARS selected 20 moisture-sensitive bands in red-edge (680–760 nm) and SWIR regions, while SPA pinpointed 4 critical bands (758, 1074, 1124, 1663 nm) across red-edge, NIR, and SWIR. …”
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AI-driven modeling for predicting compressive strength of recycled aggregate concrete under thermal conditions for sustainable construction by Morteza Ghodratnama, Amir R. Masoodi, Amir H. Gandomi

“…The ANN models underwent optimization via Random Search Hyper-Parameter Tuning, resulting in high prediction accuracy, with correlation coefficients (R2) surpassing 0.9. …”
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