Browsing KINDI Center for Computing Research by Publisher "Elsevier Ltd"
Now showing items 1-14 of 14
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Cybersecurity of multi-cloud healthcare systems: A hierarchical deep learning approach
( Elsevier Ltd , 2022 , Article)With the increase in sophistication and connectedness of the healthcare networks, their attack surfaces and vulnerabilities increase significantly. Malicious agents threaten patients’ health and life by stealing or altering ... -
Dynamic ensemble deep echo state network for significant wave height forecasting
( Elsevier Ltd , 2023 , Article)Forecasts of the wave heights can assist in the data-driven control of wave energy systems. However, the dynamic properties and extreme fluctuations of the historical observations pose challenges to the construction of ... -
Dynamic security metrics for measuring the effectiveness of moving target defense techniques
( Elsevier Ltd , 2018 , Article)Moving Target Defense (MTD) utilizes granularity, flexibility and elasticity properties of emerging networking technologies in order to continuously change the attack surface. There are many different MTD techniques proposed ... -
EEG-based emotion recognition using random Convolutional Neural Networks
( Elsevier Ltd , 2022 , Article)Emotion recognition based on electroencephalogram (EEG) signals is helpful in various fields, including medical healthcare. One possible medical application is to diagnose emotional disorders in patients. Humans tend to ... -
Ensemble deep learning: A review
( Elsevier Ltd , 2022 , Other)Ensemble learning combines several individual models to obtain better generalization performance. Currently, deep learning architectures are showing better performance compared to the shallow or traditional models. Deep ... -
Experimental evaluation of stochastic configuration networks: Is SC algorithm inferior to hyper-parameter optimization method?
( Elsevier Ltd , 2022 , Article)To overcome the pitfalls of Random Vector Functional Link (RVFL), a network called Stochastic Configuration Networks (SCN) has been proposed. By constraining and adaptively selecting the range of randomized parameters using ... -
Jointly optimized ensemble deep random vector functional link network for semi-supervised classification
( Elsevier Ltd , 2022 , Article)Randomized neural networks have become more and more attractive recently since they use closed-form solutions for parameter training instead of gradient-based approaches. Among them, the random vector functional link network ... -
Oblique and rotation double random forest
( Elsevier Ltd , 2022 , Article)Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models’ core strength. ... -
A privacy-preserving handover authentication protocol for a group of MTC devices in 5G networks
( Elsevier Ltd , 2022 , Article)Machine Type Communication (MTC) has been emerging for a wide range of applications and services for the Internet of Things (IoT). In some scenarios, a large group of MTC devices (MTCDs) may enter the communication coverage ... -
PriviPK: Certificate-less and secure email communication
( Elsevier Ltd , 2017 , Article)We introduce PriviPK, an infrastructure that is based on a novel combination of certificateless (CL) cryptography and key transparency techniques to enable e2e email encryption. Our design avoids (1) key escrow and deployment ... -
Random vector functional link neural network based ensemble deep learning for short-term load forecasting
( Elsevier Ltd , 2022 , Article)Electric load forecasting is essential for the planning and maintenance of power systems. However, its un-stationary and non-linear properties impose significant difficulties in predicting future demand. This paper proposes ... -
Representation learning using deep random vector functional link networks for clustering: Representation learning using deep RVFL for clustering
( Elsevier Ltd , 2022 , Article)Random Vector Functional Link (RVFL) Networks have received a lot of attention due to the fast training speed as the non-iterative solution characteristic. Currently, the main research direction of RVFLs has supervised ... -
Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
( Elsevier Ltd , 2023 , Article)The reliable control of wave energy devices highly relies on the forecasts of wave heights. However, the dynamic characteristics and significant fluctuation of waves’ historical data pose challenges to precise predictions. ... -
Weighting and pruning based ensemble deep random vector functional link network for tabular data classification
( Elsevier Ltd , 2022 , Article)In this paper, we first integrate normalization to the Ensemble Deep Random Vector Functional Link network (edRVFL). This re-normalization step can help the network avoid divergence of the hidden features. Then, we propose ...
