Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. …”
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Adding Data Quality to Federated Learning Performance Improvement by Ernesto Gurgel Valente Neto, Solon Alves Peixoto, Valderi Reis Quietinho Leithardt, Juan Francisco de Paz Santana, Julio C. S. Dos Anjos

“…This study develops a data quality analysis algorithm for both FL and centralized environments to address these challenges. …”
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Spectral Approximation of an Oldroyd Liquid Draining down a Porous Vertical Surface by F. Talay Akyildiz, Mehmet Emir Koksal, Nurhan Kaplan

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Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method by Kai Zhao, Haiqing Tian, Jue Zhang, Yang Yu, Lina Guo, Jianying Sun, Haijun Li

“…The variable combination population analysis–iteratively retains informative variables algorithm was iterated to optimize effective features. …”
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JAK2 Inhibitors and Emerging Therapies in Graft-Versus-Host Disease: Current Perspectives and Future Directions by Behzad Amoozgar, Ayrton Bangolo, Abdifitah Mohamed, Charlene Mansour, Daniel Elias, Christina Cho, Siddhartha Reddy

“…Recent advances in biomarker development, such as the MAGIC Algorithm Probability (MAP), are enabling early risk stratification and response prediction. …”
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Machine learning and response surface methodology forecasting comparison for improved spray dry scrubber performance with brine sludge-derived sorbent by B.J. Chepkonga, L. Koech, R.S. Makomere, H.L. Rutto

“…The response surface methodology (RSM) model also proved to be a reliable forecasting tool, indicating its potential as a practical alternative to complex algorithmic computations in scenarios with limited raw data.…”
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Multi-Omics Profiling Reveals Glycerolipid Metabolism-Associated Molecular Subtypes and Identifies ALDH2 as a Prognostic Biomarker in Pancreatic Cancer by Jifeng Liu, Shurong Ma, Dawei Deng, Yao Yang, Junchen Li, Yunshu Zhang, Peiyuan Yin, Dong Shang

“…These findings establish a novel avenue for studying prognostic prediction and precision medicine in PC patients.…”
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Solving the Multi Objective Programming Problem Using Mean and Median Value by Najmaddin Sulaiman, Gulnar Sadiq

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How Small Can S-boxes Be? by Chenhao Jia, Tingting Cui, Qing Ling, Yan He, Kai Hu, Yu Sun, Meiqin Wang

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RECOMMENDED TACTICS FOR THE EVALUATION OF POTENTIALLY MALIGNANT DISORDERS IN THE ORAL CAVITY by S.V. Kolomiiets, K.O. Udaltsova, V.I. Shynkevych

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The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa by F. Merk, T. Schaffhauser, F. Anwar, Y. Tuo, J.-M. Cohard, M. Disse

“…Moreover, the benchmarking highlights that, if it only accounts for the LAI but disregards AET data, an optimization process's prediction of AET still yields an adequate performance with SWAT-T for all PET methods and land cover types. …”
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Multiple-omics analysis of aggrephagy-related cellular patterns and development of an aggrephagy-related signature for hepatocellular carcinoma by Jiafen Xie, Xiaoming Wang

“…At the single-cell level, the AGG scores were calculated using AUCell algorithm, and cell interactions and pseudotime trajectory analyses were conducted. …”
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Development of a three-species gut microbiome diagnostic model for acute pancreatitis and its association with systemic inflammation: a prospective cross-sectional study by Yuanyuan Gou, Long Yao, Wenli Yang, Qian Chen, Yuetao Wen, Jie Cao

“…High-throughput 16S rRNA sequencing analyzed taxonomic profiles, while a random forest algorithm was employed to construct a diagnostic model based on differentially abundant species. …”
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Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems by D. T. Yakupov, O. N. Rozhko

“…The authors consider the possibility of forecasting to use ANN for these economic indicators not as an alternative to the traditional methods of statistical forecasting, but as one of the available simple means for solving complex problems.Materials and methods. When predicting the ANN, three methods of learning were used: 1) the Levenberg-Marquardt algorithm-network training stops when the generalization ceases to improve, which is shown by the increase in the mean square error of the output value; 2) Bayes regularization method - network training is stopped in accordance with the minimization of adaptive weights; 3) the method of scaled conjugate gradients, which is used to find the local extremum of a function on the basis of information about its values and gradient. …”
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A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease by Giles Dixon, Hannah Thould, Matthew Wells, Krasimira Tsaneva-Atanasova, Chris J. Scotton, Michael A. Gibbons, Shaney L. Barratt, Jonathan C.L. Rodrigues

“…Hurdles exist to widespread adoption including governance concerns, appropriate algorithm anchoring and standardisation of image acquisition. …”
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Mapping the air temperature in China from time-normalized MODIS land surface temperature data via zone-based stacking ensemble models by Yan Xin, Yongming Xu, Xudong Tong, Yaping Mo, Yonghong Liu, Shanyou Zhu

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AI-based virtual immunocytochemistry for rapid and robust fine needle aspiration biopsy diagnosis by Irfan Ahmed, Wei Zhang, Pikting Cheung, Vardhan Basnet, Zulfiqar Ali, May PY Tse, Fraser Hill, Tom Tak Lam Chan, Haibo Hu, Xinyue Li, Condon Lau

“…In total, the geometrical features of 8.48 million segmented cells (4.24 million pairs) were translated into a tabular format and paired based on the Euclidean cell matching algorithm. This approach facilitated the prediction of cell labels, achieving sensitivity and specificity of 0.98 and 0.97 (0.94 and 0.99), respectively for CD3 (PAX5). …”
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Quantifying training response in cycling based on cardiovascular drift using machine learning by Artur Barsumyan, Artur Barsumyan, Raman Shyla, Anton Saukkonen, Christian Soost, Jan Adriaan Graw, Rene Burchard, Rene Burchard, Rene Burchard

“…Based on aerobic decoupling (power-to-heart rate ratio) and cardiovascular drift of each test ride, a prediction model was created using ML (Logistic regression, Variational Gaussian Process models and k-nearest neighbors algorithm) that indicated whether or not an athlete was responding to the training. …”
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Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy by Hassan H. Alhassan

“…Among all models, the Random Forest (RF) algorithm had the best prediction accuracy, with a value of 0.6832 on the test set and 0.7432 on the training set, and was employed to screen the target library of 11,032 phytochemicals. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…This research study proposes an automatic diagnostics prediction of leukemia by analyzing blood images according to the shape of the blast cells using digital image processing and machine learning. …”
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