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"A Cost-Sensitive Machine Learning Model With Multitask Learning for In" by Akbar Telikani, Nima Esmi Rudbardeh et al.

A problem with machine learning (ML) techniques for detecting intrusions in the Internet of Things (IoT) is that they are ineffective in the detection of low-frequency intrusions. In addition, as ML models are trained using specific attack categories, they cannot recognize unknown attacks. This article integrates strategies of cost-sensitive learning and multitask learning into a hybrid ML model to address these two challenges. The hybrid model consists of an autoencoder for feature extraction a...
Eep Learning Dl Nternet Of Things Internet Of Things Iot Intrusion Detection Mathematical Models Ultitask Learning
Source: uow.edu.au

"The first step towards intelligent wire arc additive manufacturing: An" by Donghong Ding, Fengyang He et al.

Wire Arc Additive Manufacturing (WAAM) has revolutionized the manufacturing paradigm for fabricating medium to large scale metallic parts featuring high buy-to-fly ratios such as aerospace components. As a promising technology for the manufacturing industry, it is necessary to develop an automated WAAM system with high efficiency and low labour cost. Generally, to achieve a fully intelligent WAAM system, the first step is to develop an intelligent weld bead modelling system which is able to prov...
Arc Additive Manufacturing Support Vector Machines Bead Modelling Machine Learning Robotic Welding Upport Vector Machine Svm
Source: uow.edu.au

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