Bridging the Gap: A Review of Machine Learning in Water Quality Control by Herlina Abdul Rahim, Nur Athirah Syafiqah Noramli, Indrabayu

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Integrating Equation Coding with Residual Networks for Efficient ODE Approximation in Biological Research by Ziyue Yi

“…Biological research traditionally relies on experimental methods, which can be inefficient and hinder knowledge transfer due to redundant trial-and-error processes and difficulties in standardizing results. …”
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Approaches for Localizing the Origin of PVCs in the Outflow Tract: Future Perspectives and Challenges by Baiping Sui, Yingjie Ji, Ying Wang, Ling Gao, Minghao Li

“…To mitigate these influences, combining this approach with imaging modalities such as cardiac MRI, CT, and echocardiography can help identify structural abnormalities at the foci of premature ventricular contractions (PVCs), thereby enhancing the precision of IVA localization. To decrease human error and achieve more efficient PVC localization, algorithmic analysis and anatomical modeling with computer-based methods have emerged as promising new approaches. …”
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Variational AutoEncoder for synthetic insurance data by Charlotte Jamotton, Donatien Hainaut

“…This article explores the application of Variational AutoEncoders (VAEs) to insurance data. …”
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Analysis of chemical reactive nanofluid flow on stretching surface using numerical soft computing approach for thermal enhancement by Saleem Nasir, Abdallah S. Berrouk, Taza Gul

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Large-scale combinatorial optical barcoding of cells with laser particles by Nicola Martino, Hao Yan, Geoffrey Abbott, Marissa Fahlberg, Sarah Forward, Kwon-Hyeon Kim, Yue Wu, Han Zhu, Sheldon J. J. Kwok, Seok-Hyun Yun

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Backtesting framework for concentrated liquidity market makers on Uniswap V3 decentralized exchange by Andrey Urusov, Rostislav Berezovskiy, Yury Yanovich

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Spin-orbit coupling in van der Waals materials for optical vortex generation by Jaegang Jo, Sujeong Byun, Munseong Bae, Jianwei Wang, Haejun Chung, Sejeong Kim

“…Abstract An optical vortex beam has attracted significant attention across diverse applications, including optical manipulation, phase-contrast microscopy, optical communication, and quantum photonics. …”
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Penalty Strategies in Semiparametric Regression Models by Ayuba Jack Alhassan, S. Ejaz Ahmed, Dursun Aydin, Ersin Yilmaz

“…The simulation results reveal that aLasso and shrinkage estimators, particularly the positive shrinkage estimator, consistently outperform the other methods in terms of Mean Squared Error (MSE) relative efficiencies (RE), especially when the sample size is small and multicollinearity is high. …”
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Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

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Experimental demonstration of 8190-km long-haul semiconductor-laser chaos synchronization induced by digital optical communication signal by Anbang Wang, Junli Wang, Lin Jiang, Longsheng Wang, Yuncai Wang, Lianshan Yan, Yuwen Qin

“…Results show that high-quality synchronization can be achieved as the drive signal rate is larger than the laser relaxation frequency and the transmission bit error ratio is below a critical value. Chaos synchronization over 8191-km fiber transmission was experimentally achieved. …”
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Machine learning-based state of charge estimation: A comparison between CatBoost model and C-BLSTM-AE model by Abderrahim Zilali, Mehdi Adda, Khaled Ziane, Maxime Berger

“…The C-BLSTM-AE model achieves a low Mean Absolute Error (MAE) of 0.52 % under fixed ambient temperature conditions and maintains a MAE of 1.03 % for variable ambient temperatures. …”
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Predictive modelling of graphene-enhanced greases using classical feedback control and quantum kernel regression by Ethan Stefan-Henningsen, Amirkianoosh Kiani

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Prediction of retention time in larger antisense oligonucleotide datasets using machine learning by Manal Rahal, Bestoun S. Ahmed, Christoph A. Bauer, Johan Ulander, Jörgen Samuelsson

“…Through feature engineering and grid search optimization, key predictors were identified and compared for model accuracy using root mean square error, coefficient of determination R-squared, and run time. …”
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Using large language models to extract plant functional traits from unstructured text by Viktor Domazetoski, Holger Kreft, Helena Bestova, Philipp Wieder, Radoslav Koynov, Alireza Zarei, Patrick Weigelt

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Investigation of the impact of token embeddings in Transformer-based models on short-term tropical cyclone track and intensity predictions by Yuan-Jiang Zeng, Yi-Qing Ni, Zheng-Wei Chen, Guang-Zhi Zeng, Jia-Yao Wang, Pak-Wai Chan

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Approximations related to tempered stable distributions by Kalyan Barman, Neelesh S Upadhye, Palaniappan Vellaisamy

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Process-induced shrinking and warping in additively manufactured polycarbonate plates by P. Sreejith, Albert E. Patterson, K.R. Rajagopal, Bhaskar Vajipeyajula

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Advanced Hybrid Brain Tumor Segmentation in MRI: Elephant Herding Optimization Combined with Entropy-Guided Fuzzy Clustering by Baiju Karun, Arunprasath Thiyagarajan, Pallikonda Rajasekaran Murugan, Natarajan Jeyaprakash, Kottaimalai Ramaraj, Rakhee Makreri

“…The results demonstrate marked improvements across several performance metrics, including Dice similarity, mean squared error (MSE), peak signal-to-noise ratio (PSNR), and the Tanimoto coefficient (TC), underscoring this method’s robustness and segmentation accuracy. …”
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From pixels to letters: A high-accuracy CPU-real-time American Sign Language detection pipeline by Jonas Rheiner, Daniel Kerger, Matthias Drüppel

“…We propose a straightforward method to determine the amount of data needed for validation and testing and to quantify the remaining statistical error. For this we calculate accuracy as a function of validation set size, and thus ensure sufficient data is allocated for evaluation. …”
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