Integrating artificial intelligence in nanomembrane systems for advanced water desalination by Anbarasu Krishnan, Thanigaivel Sundaram, Beemkumar Nagappan, Yuvarajan Devarajan, Bhumika

“…However, challenges remain, such as the development of desalination-specific AI algorithms, ensuring scalability and compatibility, and addressing data privacy and security concerns. …”
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Venous thromboembolism prophylaxis in patients with intracranial hemorrhage: a systematic review of considerations for neurosurgical management by Michael Del Sesto, Diana Feier, Brian Kent, Connor Rupp, Luca Bertola, Brandon Lucke-Wold

“…Advanced machine learning algorithms with model transparency offers further advancements.…”
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Charting the path forward: CT image quality assessment - an in-depth review by Siyi Xun, Qiaoyu Li, Xiaohong Liu, Pu Huang, Guangtao Zhai, Yue Sun, Peter H. N. de With, Mingxiang Wu, Tao Tan

“…It helps improve the accuracy of CT scanning equipment and the performance of CT system reconstruction algorithms, and provides a new idea for CT image processing algorithms. …”
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Feasibility of Conflict Prediction of Drone Trajectories by Means of Machine Learning Techniques by Victor Gordo, Javier A. Perez-Castan, Luis Perez Sanz, Lidia Serrano-Mira, Yan Xu

“…The obtained results suggest that the Random Forest, Artificial Neural Networks and Logistic Regression algorithms could detect nearly all near-collisions up to 10 s before they occur, and the first two algorithms could also detect a significant number of near-collisions more than 60 s earlier.…”
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Feature Extraction and Diagnosis of Power-Shift System Faults in Unmanned Hydro-Mechanical Transmission Tractors by Ya Li, Kuan Liu, Xiaohan Chen, Kejia Zhai, Yangting Liu, Yehui Zhao, Guangming Wang

“…The fault diagnosis accuracy of W_SCBAM for the radial-inlet clutch system has an expectation of 98.5% and a variance of 1.6%, respectively, outperforming other algorithms. W_SCBAM also excels in diagnosing faults in the axial-inlet clutch system, achieving 97.6% accuracy even with environmental noise. …”
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Comprehensive Analysis of BDS/GNSS Differential Code Bias and Compatibility Performance by Yafeng Wang, Dongjie Yue, Hu Wang, Hongyang Ma, Zhiqiang Liu, Caiya Yue

“…Variations in GNSS signal processing and receiver algorithms also impact DCB stability. Converting DCBs to OSBs and performing RMS statistics revealed that smaller differences between signals increase the susceptibility of observation equations to observation quality.…”
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The Application of Reinforcement Learning to Pumps—A Systematic Literature Review by Adetoye Ayokunle Aribisala, Usama Ali Salahuddin Ghori, Cristiano A. V. Cavalcante

“…Future trends include the use of Internet-of-Things sensors on pumps, a hybrid of model-free and model-based reinforcement learning algorithms, and the development of “weighted” models. …”
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Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

“…Evaluating the results of image denoising algorithms in Computed Tomography (CT) scans typically involves several key metrics to assess noise reduction while preserving essential details. …”
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In the Refractory Hypertension “Labyrinth”. Focus on Primary Hyperaldosteronism by O. V. Tsygankova, T. I. Batluk, L. D. Latyntseva, E. V. Akhmerova, N. M. Akhmedzhanov

“…The success of a treatment and a prognosis of these patients depend on correct choice of screening (aldosterone/renin ratio) and clarifying diagnostic methods. There are clear algorithms for conducting these tests in accordance with Russian and International recommendations in the respective groups of patients. …”
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Impact of Data Capture Methods on 3D Reconstruction with Gaussian Splatting by Dimitar Rangelov, Sierd Waanders, Kars Waanders, Maurice van Keulen, Radoslav Miltchev

“…These insights provide valuable guidelines for professionals in forensics, architecture, and cultural heritage preservation, helping them capture realistic high-quality 3D representations. This study also highlights the potential for future research to expand on these findings by exploring other algorithms, camera parameters, and real-time adjustment techniques.…”
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Pollen holographic images and light-induced fluorescence measurements at the species level by Sophie Erb, Alexis Berne, Bernard Clot, Maria Lbadaoui-Darvas, Gian-Duri Lieberherr, Marie-Pierre Meurville, Fiona Tummon, Benoît Crouzy

“…Their potential reuse can also be to study pollen morphological and compositional variability at the species level.…”
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A Systematic Literature Review: Fourier Analysis as a Mathematical Tool for Robot Navigation by Prithvi Narayan, Sandeep Ameet Kumar, Avinesh Prasad, Bibhya Nand Sharma

“…The introduction of Fourier analysis or series in robot navigation algorithms greatly improves the capability to find solutions to many inherent applications and tasks of robotic systems. …”
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Adjacent Inputs With Different Labels and Hardness in Supervised Learning by Sebastian A. Grillo, Julio Cesar Mello Roman, Jorge Daniel Mello-Roman, Jose Luis Vazquez Noguera, Miguel Garcia-Torres, Federico Divina, Pedro Esteban Gardel Sotomayor

“…An important aspect of the design of effective machine learning algorithms is the complexity analysis of classification problems. …”
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Machine Learning‐Assisted Pd‐Au/MXene Sensor Array for Smart Gas Identification by Yiheng Chen, Jiawang Hu, Nanlin Hu, Shikai Wu, Yuan Lu

“…Moreover, machine learning (ML) algorithms are employed to strengthen IISP's capacity for gas identification in complex application scenarios. …”
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Advancements in Intelligent Sensing Technologies for Food Safety Detection by Wenhui Jiang, Changhong Liu, Wei Liu, Lei Zheng

“…It also presents current challenges and development trends associated with intelligent sensing technologies in food safety, including novel sensing materials, edge-cloud computing frameworks, and the co-design of energy-efficient algorithms with hardware architectures. …”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…To verify the optimization ability and transferability of MCSP, the MCSP cost is integrated into three classical disparity estimation algorithms respectively. The experimental results demonstrate that the MCSP is suitable for both aerial images and satellite remote sensing images. …”
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Implementation and Performance of Lightweight Authentication Encryption ASCON on IoT Devices by Gabriela Cagua, Valerie Gauthier-Umana, Carlos Lozano-Garzon

“…While this expansion drives significant advancements across industries, it also introduces critical challenges in ensuring secure device communication. …”
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A multi-scale multi-channel CNN introducing a channel-spatial attention mechanism hyperspectral remote sensing image classification method by Ru Zhao, Chaozhu Zhang, Dan Xue

“…The CSAM-MMC model in this paper further improves 0.13%, 0.35%, and 0.71% relative to the MMC-CNN model, which provides higher overall accuracies relative to other state-of-the-art algorithms.…”
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Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning by Mangalpady Aruna, Harsha Vardhan, Abhishek Kumar Tripathi, Satyajeet Parida, N. V. Raja Sekhar Reddy, Krishna Moorthy Sivalingam, Li Yingqiu, P. V. Elumalai

“…A comparative analysis with the industry-standard Minimate Blaster indicates high accuracy of the IoT device, with percentage errors as low as 0.803% across multiple blasts. The study also employed Support Vector Regression (SVR), Gradient Boosting Regression (GBR), and Random Forest (RF) algorithms to predict Peak Particle Velocity (PPV) values. …”
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DC-WUnet: An Underwater Ranging Signal Enhancement Network Optimized with Depthwise Separable Convolution and Conformer by Xiaosen Liu, Juan Li, Jingyao Zhang, Yajie Bai, Zhaowei Cui

“…Experimental evaluations under an SNR of −10 dB indicate that the proposed method achieves at least a 32% improvement in delay estimation accuracy and a 2.3 dB enhancement in output SNR relative to state-of-the-art baseline algorithms. Consistent performance advantages are also observed under varying SNR conditions, thereby validating the effectiveness of the proposed approach in shipborne noisy environments.…”
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