Value of Low Tube Voltage Combined with Deep Learning Image Reconstruction Algorithm to Reduce Radiation Dose in Combined Thoracoabdominal Enhanced CT by Weiwei QI, Jin CHENG, Chuhan CHEN, Bei AN, Xiaoyi LIU, Ling FU, Yi WANG

“…Conclusion: The combination of a low tube voltage and deep learning image reconstruction algorithm can ensure equivalent or even higher image quality while reducing radiation dose, providing a feasible solution for optimizing radiation dose in large-scale CT scans such as the combined thoracoabdominal enhanced CT.…”
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Development of compact mechanism for lithium-ion battery venting gas fires using Cantera ordinary differential equation neural network algorithm by Mengjie Li, Hao Hu, Li Lu, Huangwei Zhang

“…The resulting COM mechanism, with 30 species and 213 reactions, achieves a high fidelity of 94.8 % in predicting ignition delay times across equivalence ratios from 0.3 to 2.5, demonstrating the reliability and robustness of CODENN algorithm. Further analysis of speciation data and CO net production rates shows that the COM mechanism closely aligns with the species evolution of the ORI mechanism during autoignition, while exhibiting notably more intense CO production and consumption than the ORI mechanism. …”
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Applicable Image Security Based on Computational Genetic Approach and Self-Adaptive Substitution by Nawal Shaltout, Ahmed A.Abd El-Latif, Waleed M. Al-Adrousy, Samir Elmougy

“…Hence, it is essential to investigate and develop new cryptographic algorithms to ensure the protection and privacy of multimedia data at rest and during transmission through the communication channel while attempting to overcome the limitations of traditional cryptographic methods. …”
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Multidimensional routing with the increased navigation accuracy with the maintenance of flight notifications of the flight vehicles by V. I. Goncharenko, G. N. Lebedev, V. B. Malygin

“…Optimal solution can be obtained both by the enumeration of the solution versions and with the help of the genetic algorithm, which is allowed for a smaller number of iterations, to obtain suboptimal in real time, which corresponds to the conditions of the task solution. …”
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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…This suggested framework leverages an attention-based convolutional neural network (CNN) and a genetic algorithm (GA) to enhance detection accuracy while optimizing the hyperparameters of the proposed model. …”
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Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study by Océane Dorémus, Dylan Russon, Benjamin Contrand, Ariel Guerra-Adames, Marta Avalos-Fernandez, Cédric Gil-Jardiné, Emmanuel Lagarde

“…These methods pave the way for a broader availability of pseudonymized clinical texts, enabling their use for research purposes and the optimization of the health care system.…”
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Comparative analysis of forest disturbance detection in the key state-owned forest region of the Greater Khingan Range of China based on different algorithms by Ke Xu, Wenshu Lin, Ning Zhang

“…Results showed that: (1) all three algorithms can identify the major forest disturbances with a spatial accuracy higher than 80%, and LandTrendr performed the best (OA=86.2%). (2) All three algorithms can detect the occurrence time of major disturbances with a temporal accuracy higher than 70%, and LandTrendr achieved the highest accuracy (76.4%). (3) The highest fragmentation was observed using the CCDC (184,074 disturbance patches), while LandTrendr disturbance mapping was the most complete (102,143 disturbance patches). …”
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Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
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Methodology for Evaluating the Performance of a New Pulse Oximeter Model and Pulse Oximetry Algorithm in Neonates in a Clinical Trial (Exploratory Study) by T. S. Adylov, E. V. Shestak, V. Yu. Starkov

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Min3GISG: A Synergistic Feature Selection Framework for Industrial Control System Security with the Integrating Genetic Algorithm and Filter Methods by Saiprasad Potharaju, Swapnali N. Tambe, G. Madhukar Rao, M. V. V. Prasad Kantipudi, Kalyan Devappa Bamane, Mininath Bendre

“…Compared to the full dataset (225 features), which yielded 97.51%, 99.93%, and 96.17%, respectively, our optimized feature subset maintained or enhanced classification performance while reducing computational complexity. …”
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A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning by Junyao Ding, Jianchao Du, Hejie Wang, Song Xiao

“…Then, the improved genetic algorithm is used to search for the global optimal feature subset further. …”
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Using PAT for Energy Recovery and Pressure Reduction in Water Distribution Networks by Hamed Mohammadi, Mahnaz Ghaeini-Hessaroeyeh, Ehsan Fadaei-Kermani

“…At first, the aim of optimization is to determine the optimum output of PRVs. …”
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HiGMA-DADCN: Hirudinaria granulosa multitropic algorithm optimised double attention enabled deep convolutional neural network for psoriasis classification by Soumya C S, Jayanna H S

“…The HiGMA algorithm plays a crucial role in identifying and extracting the most relevant regions of affected skin through optimal segmentation. …”
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Modern approaches to the diagnosis and treatment of cardiac sarcoidosis: results of a cohort study by S. V. Mairina, D. V. Ryzhkova, L. B. Mitrofanova, A. V. Ryzhkov, P. M. Murtazalieva, O. M. Moiseeva

“…To analyze clinical and paraclinical data in patients with documented cardiac sarcoidosis, outlining the key points of diagnosis and selection of the optimal treatment.Material and methods. For the period from 2016 to 2021, 63 patients (50,4±14,1 years) were included in the cohort study on negotiability. …”
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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…In this study, we introduced XNANet, a self-attention-based CNN network for image classification. Bayesian optimization has been used to initialize the hyperparameters of the proposed model to improve training on the radiographic images. …”
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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…STATA version 17 was used for data cleaning and descriptive statistics, while Python 3.9 was employed for machine learning predictions. …”
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Utilizing molecular simulation, ideal adsorbed solution theory and ensemble learning algorithms to investigate adsorption and separation of sulfides on amorphous nanoporous materia... by Xuan Peng, Xingbang Zhang

“…Using grand canonical Monte Carlo method, we investigated the adsorption of pure H2S and SO2 gases on amorphous materials, and the separation of CH4-H2S and CO2-SO2 mixtures. At 303 K, the optimal adsorbent for both gases was found to be HCP-Colina-id016, with 16 mmol/g. …”
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Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…It was proven  through the experimental results that  the proposed distance measure Weighted Euclidean distance  had the advantage over improving the work of the HFCM algorithm through the criterion (Obj_Fun, Iteration, Min_optimization, good fit clustering and overlap) when (c = 2,3) and according to the simulation results, c = 2 was chosen to form groups for the real data, which contributed to determine the best objective function (23.93, 22.44, 18.83) at degrees of fuzzing (1.2, 2, 2.8), while according to the degree of fuzzing (m = 3.6), the objective function for Euclidean Distance (ED) was the lowest, but the criteria were (Iter. = 2, Min_optimization = 0 and )  which confirms that (WED) is the best.…”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…This study aimed to develop an accurate and reliable model for predicting suspended sediment load (SL) in river systems, which is crucial for water resource management and environmental protection. While Xtreme Gradient Boosting (XGB), a powerful ensemble machine learning (ML) model, has been employed in previous studies, the novelty of this research lies in the introduction of a hybrid approach that synergistically combines XGB with the bio-inspired Marine Predators Algorithm (XGB-MPA) to estimate SL in the Yeşilirmak River (Turkey). …”
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Microstrip Patch Antenna Design Using a Four-Layer Feed Forward Artificial Neural Network Trained by Levenberg-Marquardt Algorithm by Jitu Prakash Dhar, Maodudul Hasan, Eisuke Nishiyama, Ichihiko Toyoda

“…The ANN contains a multi-layered network architecture that learns and generalizes complex patterns through the LM algorithm and weight optimization based on the datasets without any feature extraction like Deep Neural Network (DNN). …”
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