Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…We examine various metaheuristic algorithms employed and, in particular, their effectiveness in improving model performance across diverse applications. …”
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5G OFDM channel estimation method based on complex-valued generative adversarial network by LU Yuanzhi, WEI Xianglin, YU Long, YAO Changhua

“…Accurate channel estimation is a critical component in the design of 5G OFDM communication system receivers, since it can significantly reduce the bit error rate (BER), thus improving wireless communication efficiency and quality. …”
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Understanding discrepancies in soil moisture from SMAP and AMSR2: insights into performance and dry-down behavior by Zhiqing Peng, Tianjie Zhao, Jiancheng Shi, Lu Hu, Thomas J. Jackson, Michael H. Cosh, Hui Lu, Xiaodong Gao, Jingyao Zheng, Panpan Yao, Qian Cui, Peng Guo, Peilin Song, Zushuai Wei, Mengjia Wang, Anmin Fu

“…These results highlight the importance of considering differences in payload configurations when using remote sensing SM products for studies of land–atmosphere interactions in hydrometeorology and for improving land surface models (LSMs).…”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…A cost-effectiveness study estimated cost per point improvement in the Roland–Morris Disability Questionnaire. …”
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The impact of using advanced computer programs on the interior architectural design of the home أثر استخدام برامج الحاسوب المتقدمه في التصميم المعماري الداخلي للمسكن... by Mohamed Abdel Hamed

“…The study focuses on three-dimensional modeling technology and modern design and drafting software, highlighting their role in enhancing precision and detail in the design of interior spaces. …”
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Accuracy Evaluation of Multi-Technique Combination Nonlinear Terrestrial Reference Frame and EOP Based on Singular Spectrum Analysis by Qiuxia Li, Xiaoya Wang, Yabo Li

“…The unlabeled jumps could be detected by the sequential <i>t</i>-test analysis of regime shifts (STARS) combined with the generalized extreme Studentized deviate (GESD) algorithms introduced in our earlier paper. These nonlinear time-dependent periodic signals could be modeled better by singular spectrum analysis (SSA) with respect to least squares fitting; the fitting period is no longer composed of semi-annual and annual items, as with ITRF2014. …”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…This approach enhances the flexibility of algorithms by incorporating diverse data. A growing quantity of current research has focused on the exploration of extracting data from multiple sources and constructing precise multimodal machine/deep learning models for medical examinations. …”
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Identifying potential three key targets gene for septic shock in children using bioinformatics and machine learning methods by Wei Guo, Hao Chen, Feng Wang, Yingjiao Chi, Wei Zhang, Shan Wang, Kezhu Chen, Hong Chen

“…Early prediction of the risk of death in children with septic shock is helpful for clinicians to judge the severity of the disease, take active treatment measures, and improve the adverse outcomes of patients. However, the mechanism of death from sepsis in children remains unclear. …”
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GaussianMix: Rethinking Receptive Field for Efficient Data Augmentation by A. F. M. Shahab Uddin, Maryam Qamar, Jueun Mun, Yuje Lee, Sung-Ho Bae

“…Mixed Sample Data Augmentation (MSDA) enhances deep learning model generalization by blending a source patch into a target image. …”
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MoCoUTRL: a momentum contrastive framework for unsupervised text representation learning by Ao Zou, Wenning Hao, Dawei Jin, Gang Chen, Feiyan Sun

“…This paper presents MoCoUTRL: a Momentum Contrastive Framework for Unsupervised Text Representation Learning. This model improves two aspects of recently popular contrastive learning algorithms in natural language processing (NLP). …”
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Postmarketing safety evaluation of pemetrexed using FAERS and JADER databases by Luo Lv, Xiangyang Wu, Yubo Ren, Yuli Guo, Haixiong Wang, Xiaofang Li

“…Continuous pharmacovigilance is essential to optimize its clinical use and improve patient safety.…”
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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…AI integrated approaches such as stress prediction, irrigation optimization, and image-based phenotyping have enhanced agriculture, while machine learning models like Random Forest and Gradient Boosting improve stress management. …”
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Age and Saving Lives in Crisis Standards of Care: A Multicenter Cohort Study of Triage Score Prognostic Accuracy by Michael Hermsen, MD, MS, Patrick G. Lyons, MD, MS, Govind Persad, JD, PhD, Alice F. Bewley, MS, Chengsheng Mao, PhD, Kaveri Chhikara, MS, Anoop Mayampurath, PhD, Matthew Churpek, MD, PhD, Monica E. Peek, MD, MPH, MSc, Yuan Luo, PhD, William F. Parker, MD, PhD

“…To determine if adding age to triage protocols used in disaster scenarios improves the identification of critically ill patients likely to survive. …”
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Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort by Kyndaron Reinier, Harpriya S. Chugh, Audrey Uy-Evanado, Elizabeth Heckard, Marco Mathias, Nichole Bosson, Vinicius F. Calsavara, Piotr J. Slomka, David A. Elashoff, Alex A.T. Bui, Sumeet S Chugh

“…Background: Out-of-hospital sudden cardiac arrest (SCA) is a major cause of mortality and improved risk prediction is needed. The Observational Study of Sudden Cardiac Arrest Risk (OSCAR) is an electronic health records (EHR)-based cohort study of patients receiving routine medical care in the Cedars-Sinai Health System (CSHS) in Los Angeles County, CA designed to evaluate predictors of SCA. …”
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Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data by In-Seon Lee, Won-mo Jung, Hi-Joon Park, Younbyoung Chae

“…Identification of distinct neural patterns of body surfaces will help in improving neural biomarkers for pain and other sensory percepts in the future.…”
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Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review by Émile Lemoine, Joel Neves Briard, Bastien Rioux, Oumayma Gharbi, Renata Podbielski, Bénédicte Nauche, Denahin Toffa, Mark Keezer, Frédéric Lesage, Dang K. Nguyen, Elie Bou Assi

“…Background: Computational analysis of routine electroencephalogram (rEEG) could improve the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic performances of computed biomarkers for epilepsy in individuals undergoing rEEG. …”
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Development and Training of a Neural Network Filter for Satellite Images Processing by N. Andriyanov, A. Kim

“…The authors also investigated the effect of using data augmentations on improving the filtering quality. Experimental results showed that neural network models are able to outperform classical filters in terms of accuracy in processing real satellite images. …”
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Investigating the Role of Code Smells in Preventive Maintenance by Junaid Ali Reshi, Satwinder Singh

“…Further, different code smells, derived subjectively through iPlasma, are taken into conjugation and three efficient, but subjective models are developed to detect code smells on each of Random Forest, J48 and SVM machine learning algorithms. …”
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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

“…The empirical study revealed that the proposed approach outperforms with an improvement of 0.146–0.473 kendall’s score in comparison with baseline approaches.…”
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Dual-stage gated segmented multimodal emotion recognition method by MA Fei, LI Shuzhi, YANG Feixia, XU Guangxian

“…In the interaction stage, the OAGL fusion strategy was employed to model global-local cross-modal interactions, improving the efficiency of feature fusion. …”
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