On Complexities of Impact Simulation of Fiber Reinforced Polymer Composites: A Simplified Modeling Framework by M. Alemi-Ardakani, A. S. Milani, S. Yannacopoulos

“…Different numerical algorithms have been developed over the past decades for impact modeling of composites, yet a considerable gap often exists between predicted and experimental observations. …”
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A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

“…Results Experimental outcomes demonstrate that our algorithm outperforms several classical algorithms in terms of classification accuracy and feature dimension reduction, while also identifying highly correlated feature subsets. …”
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De novo KCNK4 variant caused epilepsy with febrile seizures plus, neurodevelopmental abnormalities, and hypertrichosis by Hong-Jun Yan, Wen-Hui Liu, Min-Xing Xu, Peng-Yu Wang, Yu-Jie Gu, Hua Li, Jing Guo, Sheng Luo

“…The identified variant was absent in normal populations, indicated to alter hydrogen bonds with surrounding residues by various protein modeling, predicted to be damaging for protein function by twenty algorithms, located in residues of high conservation across species, and classified as pathogenic by the ACMG guidelines. …”
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Early Childhood Anemia in Ghana: Prevalence and Predictors Using Machine Learning Techniques by Maryam Siddiqa, Gulzar Shah, Mahnoor Shahid Butt, Asifa Kamal, Samuel T. Opoku

“…We used discrimination and calibration parameters to evaluate the performance of each machine learning algorithm. <b>Results</b>: Key predictors of childhood anemia are the father’s education, socioeconomic status, iron intake during pregnancy, the mother’s education, and the baby’s postnatal checkup within two months. …”
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Enhancing DDoS Attack Classification through SDN and Machine Learning: A Feature Ranking Analysis by Aymen AlAwadi, Kawthar Rasoul ALesawi

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Thermal performance analysis of gas turbine power plant using soft computing techniques: a review by Ravindra S. Surase, Ramakrishna Konijeti, Ramchandra P. Chopade

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Machine learning validation of the AVAS classification compared to ultrasound mapping in a multicentre study by Katerina Lawrie, Petr Waldauf, Peter Balaz, Radoslav Bortel, Ricardo Lacerda, Emma Aitken, Krzysztof Letachowicz, Mario D’Oria, Vittorio Di Maso, Pavel Stasko, Antonio Gomes, Joana Fontainhas, Matej Pekar, Alena Srdelic, VAVASC Study Group, Stephen O’Neill

“…Demographics, risk factors, vessels parameters, types of predicted and created VA (pVA, cVA) were collected. …”
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Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. …”
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The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis by Zeyu Chen, Zheng Lin, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

“…Compared to human visualization, AI algorithms show a higher efficiency in calculating and extracting deep features and a lower inter-observer variation. …”
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Butterfly magnetoreception based neighbour awareness strategy protocol for autonomous aerial vehicles by Janjhyam Venkata Naga Ramesh, C. Dastagiraiah, Suraya Mubeen, W. Deva Priya, M. Kameswara Rao, B. H. K. Bhagat Kumar

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Comment on “Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation” by Hinpetch Daungsupawong, Viroj Wiwanitkit

“…By incorporating advanced imaging techniques and machine learning algorithms, researchers can improve the accuracy and efficiency of diagnostic processes. …”
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Opinion mining in e-commerce: Evaluating machine learning approaches for sentiment analysis by L. Lakshmi, Ali B.M. Ali, K Dhana Sree Devi, Muhammad Rafiq, Iskandar Shernazarov, Nashwan Adnan Othman, M. Ijaz Khan

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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

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Performing a Multi-Stage Mathematical and Informational Task "Framing the First-Order Mandelbrot Set, Julia Sets, the Structure of Fixed Points of a Family of Polynomials of the Th... by Valeriy Sekovanov, Vladimir Ivkov, Elena Smirnova, Larisa Rybina

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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

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PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning by Boris I. Evstatiev, Dimitar T. Trifonov, Katerina G. Gabrovska-Evstatieva, Nikolay P. Valov, Nicola P. Mihailov

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Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). …”
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An Exploration on Aperiodic Activities and Transient Oscillations During Semantic Processing: A Study With Wearable MEG by Xiaoyu Liang, Yuyu Ma, Ruonan Wang, Huanqi Wu, Changzeng Liu, Fuzhi Cao, Nan An, Min Xiang, Yueyang Zhai, Xiaolin Ning

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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

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CASSNet: Cross-Attention Enhanced Spectral&#x2013;Spatial Interaction Network for Hyperspectral Image Super-Resolution by Zhanxu Zhang, Linzi Yang, Guanglian Zhang, Jiangwei Deng, Lifeng Bian, Chen Yang

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