Performance of digital filtering and synchronization method for APD communication receiver by Hui-Jun Zhang, Peng Lin, Tong Wang, Zi-Qi Zhang, Bai-Qiu Zhao, Wen-Fang Jiao, Xiao-Nan Yu

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Meta-Learning Amidst Heterogeneity and Ambiguity by Kyeongryeol Go, Mingyu Kim, Seyoung Yun

“…However, typical meta-learning algorithms have assumed the tasks to be similar such that a single meta-learner is sufficient to aggregate the variations in all aspects. …”
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Error-Mask-Adaptive Dynamic Filtering for Image Inpainting by Keunsoo Ko, Seunggyun Woo, Chang-Su Kim

“…Experimental results on diverse datasets show that the proposed EMDF algorithm outperforms existing inpainting algorithms significantly. …”
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Edge of excellence: JEC's Scopus achievement, doors 2025 breakthroughs, and Volume 4 Issue 1 (2025) highlights by Serhiy O. Semerikov, Tetiana A. Vakaliuk

“…The paper examines innovative solutions addressing distributed systems challenges, including IoT-based monitoring systems, intelligent traffic prediction algorithms, and security implementations for resource-constrained environments. …”
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The Military Aleatory: Weaponizing Winds by Ryan Bishop

“…From signal interpretation with remote sensing systems to telecommunciations to algorithms, media and information theory, and the weather, the unintended consequences of both dynamic systems in nature and technological attempts to control them led to innovations and accidents, developments and prediction advances that furnish large swaths of our current global sensorial domain. …”
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Deep-learning structure elucidation from single-mutant deep mutational scanning by Zachary C. Drake, Elijah H. Day, Paul D. Toth, Steffen Lindert

“…Abstract Deep learning has revolutionized the field of protein structure prediction. AlphaFold2, a deep neural network, vastly outperformed previous algorithms to provide near atomic-level accuracy when predicting protein structures. …”
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A Traffic Information Detection Method at Single Intersection Based on Wi-Fi Data by Qingmiao Wang, Jinghe Feng, Shuguang Li

“…K-means clustering algorithms and the LSTM neural network prediction model are used to obtain the space mean speed and vehicle steering ratio of the intersection sections. …”
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Enhancing Sports Team Management Through Machine Learning by Ling Zhang, Yifan An

“…The 34 performance characteristics identified achieved a prediction accuracy of 63.4% for match outcomes.…”
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A Decade of Computational Mass Spectrometry from Reference Spectra to Deep Learning by Michael A. Stravs

“…Herein, advances in CompMS for small molecule chemistry are discussed in the areas of spectral libraries, spectrum prediction, and tentative structure identification (annotation): Automatic spectrum curation is facilitating the expansion of openly available spectral libraries, a crucial resource both for compound annotation directly and as a resource for machine learning algorithms. …”
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Forecasting COVID-19 cases based on mobility by Mehmet Şahin

“…In this context, various machine learning algorithms are implemented to obtain accurate predictions. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…The predictive model was developed by integrating Th1/Th2 cytokines with clinical features, aiming to enhance the accuracy of 30-day mortality prediction. …”
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The Utility of Follow-up Transthoracic Echocardiogram to Screen for Severe Portopulmonary Hypertension (POPH) in Patients Granted POPH Model for End-stage Liver Disease (MELD) Exce... by Kathryn T. del Valle, MD, Dana Kay, MD, Michael J. Krowka, MD, James R. Runo, MD, Corey Sadd, MD, Julie K. Heimbach, MD, Rodrigo Cartin-Ceba, MD, Hector R. Cajigas, MD, Charles D. Burger, MD, John E. Moss, MD, Hilary M. DuBrock, MD

“…However, echocardiograms with RVSP ≥48 mm Hg had 100% sensitivity for detecting hemodynamically severe POPH, with 100% negative predictive value. In external validation of 13 paired echocardiograms and RHCs, our algorithm had 64% specificity and 100% negative predictive value. …”
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Deep Learning Technology for Classification of Thyroid Nodules Using Multi-View Ultrasound Images: Potential Benefits and Challenges in Clinical Application by Jinyoung Kim, Min-Hee Kim, Dong-Jun Lim, Hankyeol Lee, Jae Jun Lee, Hyuk-Sang Kwon, Mee Kyoung Kim, Ki-Ho Song, Tae-Jung Kim, So Lyung Jung, Yong Oh Lee, Ki-Hyun Baek

“…Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. …”
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Random k conditional nearest neighbor for high-dimensional data by Jiaxuan Lu, Hyukjun Gweon

“…The k nearest neighbor (kNN) approach is a simple and effective algorithm for classification and a number of variants have been proposed based on the kNN algorithm. …”
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Remote Embedded System for Agricultural Field Monitoring: Enhancing Resource Allocation in Agriculture by Ronald J. Contijo, Lucas C. de Camargo, Renan O. A. Takeuchi, André L. S. Moscato, Lafaiete H. R. Leme, Wenderson N. Lopes

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Real-time monitoring of soil moisture in cotton fields using electromagnetic induction technology by Yang Gao, Quanze Hu, Jiaojiao Hui, Lin Chang, Mei Zeng, Qingsong Jiang

“…Currently, electromagnetic induction technology provides a non-destructive alternative, using the inversion simulation of soil apparent electrical conductivity (ECa) to construct an empirical θg model, but the prediction accuracy of the constructed model is questioned when dealing with dynamic or highly uncertain data, resulting in large errors in the prediction results and cannot meet the needs of practical applications. …”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…Combining this with the prior yields an accurate prediction for the posterior, measured for DNNs trained with stochastic gradient descent. …”
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Echo state networks for modeling turbulent convection by Mohammad Sharifi Ghazijahani, Christian Cierpka

“…Meanwhile, Echo State Networks (ESN) are among the most fundamental machine learning algorithms suited for modeling sequential data. The current study conducts reduced order modeling of experimental RBC. …”
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Post-Pandemic Urban Future: Identification of the main trends of change in Latin America, through the application of the Delphi method by Yeimis Milton Palomino Pichihua

“…Additionally, it employs machine learning algorithms to transform them into predictions. The sample is made up of 26 panelists from different Latin American countries, who participated in successive questionnaires until stable results were reached. …”
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Digital Transformation in the Context of European Union’s Green Deal by Bertoncelj, Andrej

“…Both concepts have one thing in common, that is smart technologies, which is predicted to exponentially increase in market value and scope with time. …”
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