Tumor angiogenesis concerns the development of new blood vessels supplying the necessary nutrients for the further development of existing tumor cells. The entire process is complex, involving the production and consu...
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This paper introduces new and practically relevant non-Gaussian priors for the Sparse Bayesian Learning (SBL) framework applied to the Multiple measurement Vector (MMV) problem. We extend the Gaussian Scale Mixture (G...
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Industrial control systems (ICSs) and supervisory control and data acquisition (SCADA) are frequently used and are essential to the operation of vital infrastructure such as oil and gas pipelines, power plants, distri...
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For low signal-to-noise ratio (SNR) broadband signal detection, traditional energy detectors face the issue of 'clutter loss' and do not fully utilize prior information about target echoes. This article propos...
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In this paper, the adoption of Machine Learning (ML) classifiers is addressed to improve the performance of highly wearable, single-channel instrumentation for Brain-computer Interfaces (BCIs). The proposed BCI is bas...
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ISBN:
(纸本)9781665483605
In this paper, the adoption of Machine Learning (ML) classifiers is addressed to improve the performance of highly wearable, single-channel instrumentation for Brain-computer Interfaces (BCIs). The proposed BCI is based on the classification of Steady-State Visually Evoked Potentials (SSVEPs). In this setup, Augmented Reality Smart Glasses are used to generate and display the flickering stimuli for the SSVEP elicitation. An experimental campaign was conducted on 20 adult volunteers. Successively, a Leave-One-Subject-Out Cross Validation was performed to validate the proposed algorithm. The obtained experimental results demonstrate that suitable ML-based processing strategies outperform the state-of-the-art techniques in terms of classification accuracy. Furthermore, it was also shown that the adoption of an inter-subjective model successfully led to a decrease in the 3-sigma uncertainty: this can facilitate future developments of ready-to-use systems.
In this paper, we present a simulation study for a bike-sharing network. The model is analyzed with the Birth-Death process as well as a multidimensional Markov queueing system. We evaluate the steady-state probabilit...
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The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributed computing architectures. We present a new distributed algorithm for st...
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ISBN:
(纸本)9781665401623
The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributed computing architectures. We present a new distributed algorithm for state space exploration of concurrent systems on computing clusters. Our algorithm relies on Remote Direct Memory Access (RDMA) for low-latency transfer of states between computing elements, and on state reconstruction trees for compact representation of states on the computing elements themselves. For the distribution of states between computing elements, we propose a concept of state stealing. We have implemented our proposed algorithm using the OpenSHMEM API for RDMA and experimentally evaluated it on the Grid'5000 testbed with a set of benchmark models. The experimental results show that our algorithm scales well with the number of available computing elements, and that our state stealing mechanism generally provides a balanced workload distribution.
Visual SLAM systems are well established and the use of point clouds as a data source is also increasing. There are also higher demands on the registration of point cloud data. Traditional ICP algorithms are prone to ...
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The increasing penetration of distributed renewable energies at reduced voltages is transforming distribution networks (DNs) into active grids. The necessities for active distribution networks (ADNs) include greater n...
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Recently neural network transformers models have been gaining in popularity. They are not only used in natural language processing, but also can be applied in dense prediction tasks. The attention mechanism plays the ...
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