Early Detection of Seasonal Outbreaks from Twitter Data Using Machine Learning Approaches by Samina Amin, Muhammad Irfan Uddin, Duaa H. alSaeed, Atif Khan, Muhammad Adnan

“…This work proposes a machine-learning-based approach to detect dengue and flu outbreaks in social media platform Twitter, using four machine learning algorithms: Random Forest (RF), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree (DT), with the help of Term Frequency and Inverse Document Frequency (TF-IDF). …”
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Localization and detection of deepfake videos based on self-blending method by Junfeng Xu, Xintao Liu, Weiguo Lin, Wenqing Shang, Yuefeng Wang

“…Abstract Deepfake technology, which encompasses various video manipulation techniques implemented through deep learning algorithms-such as face swapping and expression alteration-has advanced to generate fake videos that are increasingly difficult for human observers to detect, posing significant threats to societal security. …”
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Characterization of soundscapes with acoustic indices and clustering reveals phenology patterns in a subtropical rainforest by Yan-Tin Lai, Sheng-Shan Lu, Ming-Tang Shiao

“…Our study confirms that acoustic indices can extract meaningful ecological features, and unsupervised algorithms offer valuable insights into biodiversity exploration data-scarce regions. …”
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Bidimensional Increment Entropy for Texture Analysis: Theoretical Validation and Application to Colon Cancer Images by Muqaddas Abid, Muhammad Suzuri Hitam, Rozniza Ali, Hamed Azami, Anne Humeau-Heurtier

“…Entropy algorithms are widely applied in signal analysis to quantify the irregularity of data. …”
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An Improved Tree Crown Delineation Method Based on a Gradient Feature-Driven Expansion Process Using Airborne LiDAR Data by Jiaxuan Jia, Lei Zhang, Kai Yin, Uwe Sörgel

“…However, the accuracy of current existing algorithms is limited due to the influence of understory vegetation and variations in tree crown geometry (e.g., the delineated crown boundaries consistently extend beyond their actual boundaries). …”
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A Comparison of Machine Learning-Based Approaches in Estimating Surface PM_2.5 Concentrations Focusing on Artificial Neural Networks and High Pollution Events by Shijin Wei, Kyle Shores, Yangyang Xu

“…This study compares various machine learning models, including linear models, tree-based algorithms, and artificial neural networks (ANNs) for estimating PM_2.5 concentrations using the MERRA-2 dataset from 2012 to 2023. …”
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ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

“…It is trained using 139 datasets built upon 60 base datasets from 11 diverse domains (finance, healthcare, network security) and 80 ML and DL models composed of 22 base anomaly detection algorithms. It uses meta-features and correlation functions to evaluate 300 features. …”
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Network Intrusion Detection and Prevention System Using Hybrid Machine Learning with Supervised Ensemble Stacking Model by Godfrey A. Mills, Daniel K. Acquah, Robert A. Sowah

“…Three machine learning algorithms comprising a multilayer perceptron neural network, a modified self-organizing map, and a decision tree were used for the detection framework. …”
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Phylogenetic relationships between Palaearctic species of the Anopheles maculipennis complex (Diptera: Culicidae) revealed by different approaches and markers. The problem of conse... by O. V. Vaulin, Yu. M. Novikov

“…We constructed phylogenetic schemes on the sequences of a COI gene fragment, the D2 variable region of 28S rDNA and ITS2 of rRNA genes using various algorithms (Neighborjoining, Minimum Evolution, Maximum parsimony and Maximum likelihood). …”
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Unveiling unexpected adverse events: post-marketing safety surveillance of gilteritinib and midostaurin from the FDA Adverse Event Reporting database by Tingting Jiang, Yanping Li, Ni Zhang, Lanlan Gan, Hui Su, Guiyuan Xiang, Yuanlin Wu, Yao Liu

“…We have separately retained significant disproportionality AEs across two algorithms, with a total of 53 AEs for gilteritinib and 46 for midostaurin. …”
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Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics. by Wenlong Kuang, Jianwu Huang, Yulu Yang, Yuhua Liao, Zihua Zhou, Qian Liu, Hailang Wu

“…The 10 MI-related hub MitoDEGs were then obtained by eight different algorithms. Immunoassays showed a significant increase in monocyte macrophage and T cell infiltration. …”
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Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

“…An ensemble model was created by using 11 different algorithms (Artificial Neural Network, Classification Tree Analysis, eXtreme Gradient Boosting, Flexible Discriminant Analysis, Generalised Additive Model, Generalised Boosting Model, Generalised Linear Model, Multivariate Adaptive Regression Splines, Maximum Entropy, Random Forest, Surface Range Envelope) to predict the potential suitable habitats of C. detrita. …”
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Information: on the question as for the meaningful evolution of the term by O. S. Bakumov, M. I. Marchuk, T. I. Gudz, О. О. Venglinskyi

“…The importance of the category "information" for jurisprudence is emphasized, because information is actually enshrined in law about the limits of what is allowed and the algorithms of human and state activities. The tools of modern legal methodology are used in the work, in particular formal legal, historical legal, systemic, logical semantic, method of analysis and synthesis, etc. …”
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Modeling of Inscribed Dual Band Circular Fractal Antenna for Wi‐Fi Application Using Descartes Circle Theorem by SatheeshKumar Palanisamy, Anitha R. Vaddinuri, Arfat Ahmad Khan, Muhammad Faheem

“…The exploration of unconventional fractal shapes and the utilization of advanced optimization algorithms present promising avenues for enhancing antenna performance and achieving miniaturization. …”
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Identification and mechanistic insights of cell senescence-related genes in psoriasis by Guiyan Deng, Cheng Xu, Dunchang Mo

“…Protein-protein interaction networks, Gene Ontology, and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the functions and pathways of these genes. Machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support vector machine-recursive feature elimination (SVE-RFE), were used to select feature genes that were validated by qRT-PCR. …”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Ultimately, AGNet’s true positive rate (TPR), positive predictive value (PPV), and f-measure exceed those of the state-of-the-art (SOTA) algorithms by 1.88%, 0.05%, and 0.77%, respectively, and with a consistent model architecture, its parameter quantity is reduced by 56%.…”
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Data-driven modeling approaches for pressure drop prediction in a multi-phase flow system by Nezar M. Alyazidi, Aiman F. Bawazir, Ala S. AL-Dogai

“…This study helps the creation of more advanced control algorithms by providing a reliable way to guess when the pressure drops and showing how to choose a model that fits the properties of the multi-phase flow. …”
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Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Com... by L. E. Simms, N. Yu. Ganushkina, M. Van derKamp, M. Balikhin, M. W. Liemohn

“…Abstract We screen several algorithms for their ability to produce good predictive models of hourly 40–150 keV electron flux at geostationary orbit (data from GOES‐13) using solar wind, Interplanetary Magnetic Field, and geomagnetic index parameters that would be available for real time forecasting. …”
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Leveraging Deep Spatiotemporal Sequence Prediction Network with Self-Attention for Ground-Based Cloud Dynamics Forecasting by Sheng Li, Min Wang, Minghang Shi, Jiafeng Wang, Ran Cao

“…However, the inherent fuzziness and dynamism of ground-based clouds have hindered the development of effective prediction algorithms, resulting in low accuracy. This paper presents CloudPredRNN++, a novel method for predicting ground-based cloud dynamics, leveraging a deep spatiotemporal sequence prediction network enhanced with a self-attention mechanism. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. Notably, compared to Hourglass, HRNet, and HigherHRNet, YOLORM reduced parameters by 99.3%, 92.9%, and 96.8%, and computational cost by 98.8%, 90.2%, and 95.3%, respectively, while concurrently improving precision and recall. …”
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