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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Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance by Velpuri Leela Devi, Piyush Kuchhal, Debasis de, Abhinav Sharma, Neeraj Kumar Shukla, Mona Aggarwal

“…In this research work, among those eight ML models, the XGBoost algorithm shows high accuracy for predicting the power conversion efficiency (PCE) of the cell, achieving root mean square error (RMSE) of 0.052 and a coefficient of determination (R2) of 0.999. …”
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Data-driven machine learning with lattice distortion and thermodynamic parameters guided strength optimization of refractory high-entropy alloys by Shujian Ding, Yifan Zhang, Siyang Lei, Xiang Weng, Wenhui Li, Wei Ren, Jian Chen, Weili Wang

“…The LightGBM algorithm was utilized to train the model based on a RHEA yield strength dataset. …”
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Rapid screening and optimization of CO2 enhanced oil recovery operations in unconventional reservoirs: A case study by Shuqin Wen, Bing Wei, Junyu You, Yujiao He, Qihang Ye, Jun Lu

“…Based on the results of model interpretability, the genetic algorithm (GA) was coupled with RF (RF-GA model) to optimize the CO2-EOR process. …”
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Russian Cross-disciplinary Consensus on the diagnosis and treatment of spondyloarthritis associated with inflammatory bowel diseases by Galina V. Lukina, Oleg V. Knyazev, Elena A. Belousova, Diana I. Abdulganieva, Elena N. Aleksandrova, Igor G. Bakulin, Olga I. Barysheva, Maria А. Borisova, Bella А. Vykova, Alla А. Godzenko, Irina V. Gubonina, Tatiana V. Dubinina, Tatiana N. Zhigalova, Evgeny V. Zhilyaev, Anna V. Kagramanova, Tatiana V. Korotaeva, Alexander V. Kuzin, Maria A. Livzan, Aleksander M. Lila, Vadim I. Mazurov, Evgeny L. Nasonov, Alexander A. Novikov, Marina F. Osipenko, Asfold I. Parfenov, Larisa V. Tarasova, Olga V. Khlynova, Marina V. Shapina, Oksana B. Shchukina, Shandor F. Erdes, Aleksei A. Iakovlev

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Developments in solar-driven desalination: Technologies, photovoltaic integration, and processes by Mohamed El-Sayed M. Essa, Hemdan S. El-sayed, Elwy E. El-kholy, Mohammed Amer, Mahmoud Elsisi, Uzair Sajjad, Khalid Hamid, Hilmy El-sayed Awad

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Development of an MRI based artificial intelligence model for the identification of underlying atrial fibrillation after ischemic stroke: a multicenter proof-of-concept analysisRes... by Zijie Zhang, Yang Ding, Kaibin Lin, Wenli Ban, Luyue Ding, Yudong Sun, Chuanliang Fu, Yihang Ren, Can Han, Xue Zhang, Xiaoer Wei, Shundong Hu, Yuwu Zhao, Li Cao, Jun Wang, Saman Nazarian, Ying Cao, Lan Zheng, Min Zhang, Jianliang Fu, Jingbo Li, Xiang Han, Dahong Qian, Dong Huang

“…Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were calculated for model evaluation. …”
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Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

“…Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. …”
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Exploring high entropy alloys: A review on thermodynamic design and computational modeling strategies for advanced materials applications by Peter Ifeolu Odetola, Bukola Joseph Babalola, Ayodeji Ebenezer Afolabi, Ufoma Silas Anamu, Emmanuel Olorundaisi, Mutombo Christian Umba, Thabang Phahlane, Olusoji Oluremi Ayodele, Peter Apata Olubambi

“…By dissecting the foundational ''four core effects'' intrinsic to HEAs—high entropy, sluggish diffusion, severe lattice distortion, and cocktail effect—we illuminate the path towards predictable and tailored material properties. Central to the present discourse is the application of valence electron concentration (VEC) and cutting-edge strategies, including the CALculation of PHAse Diagrams (CALPHAD) method, first-principles approach, and machine-learning algorithms, which collectively empower the prediction and understanding of HEA behavior. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This framework is underpinned by a sophisticated model integrating advanced monitoring systems with a Hybrid Simulated Annealing Genetic Algorithm (H-SAGA), further enhanced by neural network-driven real-time predictions. …”
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Iron Ore Information Extraction Based on CNN-LSTM Composite Deep Learning Model by Haili Chen, Mengxiang Xia, Yaping Zhang, Ruonan Zhao, Bingran Song, Yang Bai

“…In contrast, with the use of data-driven and sophisticated algorithms, modern hyperspectral technology can quickly deliver high-precision iron ore information, increasing efficiency. …”
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Multi-modality radiomics diagnosis of breast cancer based on MRI, ultrasound and mammography by Jiao Wu, YongXin Li, Wanqing Gong, Qian Li, Xue Han, Tingting Zhang

“…Conclusions The multi-modality radiomics model based on MRI, ultrasound, and mammography can predict benign and malignant breast lesions.…”
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A Meta-Learning-Based Ensemble Model for Explainable Alzheimer’s Disease Diagnosis by Fatima Hasan Al-bakri, Wan Mohd Yaakob Wan Bejuri, Mohamed Nasser Al-Andoli, Raja Rina Raja Ikram, Hui Min Khor, Zulkifli Tahir, The Alzheimer’s Disease Neuroimaging Initiative

“…The findings demonstrated significant progress in diagnostic transparency, as the algorithm consistently linked predictions to observed structural changes in the dilated lateral ventricles of the brain, which serve as a clinically reliable biomarker for AD and can be easily verified by medical professionals. …”
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Wood Species Identification Based on Gray Level Co-Occurrence Matrix (GLCM) Features on Macroscopic Images by Muhammad Ghiffaari Ilham Ramadhan, Bambang Sugiarto, Okta Dwi Mulya, Defti Septian Chairulsyah, Adyanto Syahrizal, Gunawan Gunawan, Riffa Haviani Laluma, Rini Nuraini Sukmana, Teguh Wiharko

“…For the classifier, the Random Forest algorithm is proposed for the identification of the machine learning model. …”
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Application of Fourier transform infrared spectroscopy to exhaled breath analysis for detecting helicobacter pylori infection by Meiqi Qiu, Fei Liao, Yulin Tan, Junlong Zhang, Changjun Zheng, Hanyu Wang, Huangming Zhuang, Wanli Xiong, Qingfang Xie, Weiguo Dong

“…Individual exhalation spectral data after deducting baseline spectral data were used as the basis for the training and test sets through K-center clustering algorithm. Results: A total of 278 samples were collected (63 H. pylori infection cases, 215 healthy controls). …”
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Developing A Digital Twin of a TRUEX Extraction Process that Enables Non-proliferation and Safeguards Monitoring through Optical Spectroscopy and Machine Learning [version 1; peer... by Justin T. Cooper, Ramedy Flores, Addyson Barnes, Eduardo Trevino, Kathrine Jesse, Kolton Heaps, Adam J. Pluth, Ashley Shields, Jaren Brownlee

“…Furthermore, the digital twin’s ML anomaly detection algorithm was shown to be successful in identifying several non-ideal process upset conditions.…”
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Multi-Frequency Microwave Sensing System with Frequency Selection Method for Pulverized Coal Concentration by Haoyu Tian, Feng Gao, Yuwei Meng, Xiaoyan Jia, Rongdong Yu, Zhan Wang, Zicheng Liu

“…To address this issue, we proposed an innovative frequency selection method based on principal component analysis (PCA) and orthogonal matching pursuit (OMP) algorithms and implemented a multi-frequency microwave sensing system for PCC measurement. …”
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Echocardiographic Left Ventricular Function in the Third Year After COVID-19 Hospitalization: A Follow-Up Pilot Study in South-East of Romania by Constantin-Marinel Vlase, Cristian Gutu, Roxana Elena Bogdan Goroftei, Andreea Boghean, Traian Florin Daniel Iordachi, Anca-Adriana Arbune, Manuela Arbune

“…<i>Conclusions</i>: COVID-19 is an independent predictive factor for GLS impairment, which can indicate myocardial contractile dysfunction, even in patients with asymptomatic heart disease. …”
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Artificial Neural Network Modelling of Photodegradation in Suspension of Manganese Doped Zinc Oxide Nanoparticles under Visible-Light Irradiation by Yadollah Abdollahi, Azmi Zakaria, Nor Asrina Sairi, Khamirul Amin Matori, Hamid Reza Fard Masoumi, Amir Reza Sadrolhosseini, Hossein Jahangirian

“…To obtain the optimum topologies, ANN was trained by quick propagation (QP), Incremental Back Propagation (IBP), Batch Back Propagation (BBP), and Levenberg-Marquardt (LM) algorithms for testing data set. The topologies were determined by the indicator of minimized root mean squared error (RMSE) for each algorithm. …”
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Computer guided versus freehand dental implant surgery: Randomized controlled clinical trial by Nermine Ramadan Mahmoud, Mohamed Hatem Kamal Eldin, Mai Hassan Diab, Omar Samy Mahmoud, Yasser El-Sayed Fekry

“…A secondary aim is to propose an algorithm for predicting the accuracy of implant placement. …”
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