Background. Industrial Internet of Things (IIoT) traffic in factory-automation networks is overwhelmingly benign, so the attack class that matters most operationally, a rare command-injection intrusion that can alter a controller's behaviour, is also the...
Adaptive machine-learning frameworks for fraud prevention combine several design choices — the learning algorithm, the treatment of class imbalance, the training window, the alert threshold and the policy for updating the model — yet these are usually...
Machine-learning cash-flow forecasting is increasingly offered to small and medium-sized enterprises (SMEs) as part of AI-driven financial planning and analysis [1]. Most evaluations of such tools report only point accuracy, yet SME owners use forecasts to...
Enterprises increasingly rely on machine learning models embedded in real-time streaming analytics pipelines to support operational decisions as events occur, rather than hours or days later in a batch report. This shift creates a tension the explainable-AI...
Explainable AI has been studied separately for cancer classification and for other image-based clinical decision support tasks such as pneumonia detection, but a unified account of what these two literatures share, and where they diverge, is largely...
Introduction The Metascience (An International Multidisciplinary Research Journal) is a double-blind, peer-reviewed, open-access...
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