Respiratory muscle strength and oxygenation as predictors of length of hospital stay in patients with COVID-19 by E. S. Pan’ko, S. V. Zhavoronok, A. M. Solovchuk, S. V. Pan’ko

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Genomic selection in pig breeding: comparative analysis of machine learning algorithms by Ruilin Su, Jingbo Lv, Yahui Xue, Sheng Jiang, Lei Zhou, Li Jiang, Junyan Tan, Zhencai Shen, Ping Zhong, Jianfeng Liu

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The malaria secretome: from algorithms to essential function in blood stage infection. by Christiaan van Ooij, Pamela Tamez, Souvik Bhattacharjee, N Luisa Hiller, Travis Harrison, Konstantinos Liolios, Taco Kooij, Jai Ramesar, Bharath Balu, John Adams, Andrew P Waters, Chris J Janse, Kasturi Haldar

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Hybrid Human and Machine Learning Algorithms to Forecast the European Stock Market by Germán G. Creamer, Yasuaki Sakamoto, Jeffrey V. Nickerson, Yong Ren

“…Additionally, this paper shows that the groups of humans, algorithms, and expert weighting algorithms have associated with them, particularly, news topics that these groups are good at making predictions from.…”
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Optimization based machine learning algorithms for software reliability growth models by Myeongguen Shin, Juwon Jung, Jihyun Lee, Insoo Ryu, Sanggun Park

“…However, many previous studies have relied on single optimization methods or deep learning approaches, which are prone to local optima and extrapolation issues, reducing prediction accuracy. To fill this gap, current study employs a broader range of optimization algorithms based on the Least Squares Method (LSM) and Maximum Likelihood Estimation (MLE) to approximate global optima. …”
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Efficiency comparison of exact and approximate algorithms for solving set covering problem by Igor S. Konovalov, Sergey S. Ostapenko, Valery G. Kobak

“…Research Results. The genetic algorithm in all its modifications on time response characteristics has shown predictability and stability in all series of experiments. …”
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Research on Tilt Correction Algorithms of Destorted Data Matrix Code Image by GUAN Bo-yi, DONG Jing-wei, MA Xiao-feng, XU Bo

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Two-test algorithms for infectious disease diagnosis: Implications for COVID-19. by Sunil Pokharel, Lisa J White, Jilian A Sacks, Camille Escadafal, Amy Toporowski, Sahra Isse Mohammed, Solomon Chane Abera, Kekeletso Kao, Marcela De Melo Freitas, Sabine Dittrich

“…We tested the model using hypothetical prevalence data for COVID-19, representing low- and high-prevalence contexts and performance characteristics of RT-PCR and Ag-RDTs. The two-test algorithm when RT-PCR was applied to samples negative by Ag-RDT predicted gains in sensitivity of 27% and 7%, respectively, compared with Ag-RDT and RT-PCR alone. …”
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Application of modified genetic algorithms for solving evolutionary problems of the theory of schedules by D. S. Zakharov

“…The article proposes ways to modify genetic algorithms used to automate the process of scheduling.Method. …”
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Hemisphere mass up to four-loops with generalised $$k_t$$ k t algorithms by Kamel Khelifa-Kerfa, Mohamed Benghanem

“…We compare the resulting resummed expressions for both jet algorithms with the standard Sudakov form factor and demonstrate that neglecting these logarithms leads to unreliable phenomenological predictions for the observable’s distribution.…”
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Getting the Best Out of Both Worlds: Algorithms for Hierarchical Inference at the Edge by Vishnu Narayanan Moothedath, Jaya Prakash Champati, James Gross

“…The resulting online learning problem turns out to be a Prediction with Expert Advice (PEA) problem with continuous expert space. …”
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Semianalytical algorithms to study longitudinal beam instabilities in double rf systems by A. Gamelin, V. Gubaidulin, M. B. Alves, T. Olsson

“…In this paper, we provide semianalytical algorithms designed to predict and analyze these instabilities with improved accuracy and robustness. …”
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A Closer Look at Invalid Action Masking in Policy Gradient Algorithms by Shengyi Huang, Santiago Ontañón

“…In recent years, Deep Reinforcement Learning (DRL) algorithms have achieved state-of-the-art performance in many challenging strategy games. …”
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Self-Stabilizing TDMA Algorithms for Dynamic Wireless Ad Hoc Networks by Pierre Leone, Elad M. Schiller

“…We propose a self-stabilizing MAC algorithm for DynWANs that guarantees a short convergence period, and by that, it can facilitate the satisfaction of severe timing requirements, such as the above. …”
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Efficient Machine Learning Algorithms in Hybrid Filtering Based Recommendation System by . Ruchika, Mayank Sharma, Syed Akhter Hossain

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Advancing Hyperspectral Image Classification with Deep Features Learning and Evolutionary Algorithms by M. B. Amri, M. B. Amri, D. Yedjour, M. E. A. Larabi, F. Berrichi

“…In addition, the experiments conducted on simulated benchmarks validate the superior performance of the proposed approach compared to the baseline ML model in terms of prediction accuracy and F1-score.…”
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Comparison of algorithms using deep reinforcement learning for optimization of hyperbolic metamaterials by Kenta Hamada, Hui-Hsin Hsiao, Wakana Kubo

“…By analyzing the absorption spectra obtained from the three algorithms with limited number of datasets, we assessed the prediction accuracy of each algorithm. …”
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An Exploratory Application of Machine Learning Algorithms in Estimating Net Salaries in Romania by Adriana Aiftincăi

“…The results demonstrate a high prediction accuracy (MAE: 59.47 lei, RMSE: 97.60 lei – Random Forest model), providing realistic values for future salary scenarios. …”
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Wind Farm Layout Optimization Problem Using Nature-Inspired Algorithms by Mukesh Kumar, Ajay Sharma, Nirmala Sharma, Fani Bhushan Sharma, Mahendra Bhadu

“…Nowadays, researchers from a variety of fields are developing nature-inspired algorithms (NIAs) to solve difficult real-world problems. …”
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Scattering-Based Machine Learning Algorithms for Momentum Estimation in Muon Tomography by Florian Bury, Maxime Lagrange

“…Several real-life requirements are considered, such as the inclusion of hit reconstruction efficiency and resolution and the need for a momentum resolution prediction that can improve reconstruction methods.…”
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