This paper considers the circuit method for neutralizing the effect of parasitic components of the collector load in silicon-germanium (SiGe) and silicon-on-insulator (SOI) classical cascade amplifiers and common-base...
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This work incorporates an adaptive learning-based boosting (ADboost) ML classifier to classify four types of fuel: agricultural residue, coals, wood, and produced biomass. Further, the ADboost's hyperparameters, s...
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Precise localization is essential for the operation of Connected and Automated Vehicles (CAVs) in urban scenarios. Camera and LiDAR-based solutions are currently used in some of the CAVs around the world, but they ent...
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In this paper, the objective for a group of unmanned aerial vehicle agents (UAVs) to achieve three dimensional circumnavigation around a moving target which information is made available to all agents in the group. Th...
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Many of the currently available services and commodities extensively share personal data and digital identities, raising privacy, security and ethical *** this paper, we present a novel software, MINOS, designed to en...
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ISBN:
(数字)9798350387537
ISBN:
(纸本)9798350387544
Many of the currently available services and commodities extensively share personal data and digital identities, raising privacy, security and ethical *** this paper, we present a novel software, MINOS, designed to enhance users’ privacy awareness while browsing the web. Our approach combines a user-friendly browser with a backend tailored to record and analyze HTTP requests directed to countries outside the European Economic Area (EEA).As opposed to other available tools, our solution uniquely addresses the issue of data transfers to third *** simulations have yielded promising results and clear directions for further research and development of the tool.
In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achi...
In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achieved using motion parameterization techniques based on dual numbers and dual vectors. Considering an imposed velocity field over the motion of the 3D point features ensemble, this work proposes a close-form solution to a visual servoing problem. The solution provides stable motion control while preserving the image features in the field of view. However, when some point features leave the field of view, their contribution to the control law is dropped without losing stability. The proposed solution is easy to tune and implement. Various scenarios are used in simulations and real experiments to show how the proposed solution overcomes classic servoing problems.
Smart Healthy Schools (SHS) are a new paradigm in building engineering and infection risk control in school buildings where the disciplines of Indoor Air Quality (IAQ), IoT (Internet of Things) and Artificial Intellig...
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Heat pumps can play a crucial role in the European energy strategy 2050, which aims to achieve net-zero greenhouse gas emissions. When coupled with thermal energy storage and integrated with advanced control strategie...
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Electroencephalography (EEG) is one of the most popular techniques to investigate normal as well as pathological cerebral mechanisms, as it allows to measure, non-invasively and in real-time, the brain activity. Howev...
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Electroencephalography (EEG) is one of the most popular techniques to investigate normal as well as pathological cerebral mechanisms, as it allows to measure, non-invasively and in real-time, the brain activity. However, modeling EEG is still extremely challenging, because of its high-dimensionality, low signal-to-noise ratio, and high individual variability. This paper proposes a novel latent representation to study brain networks using EEG by means of a robust dynamic factor analysis (RDFA) approach. We investigate the ability of this latent representation to discriminate between two groups of subjects, i.e. alcoholic and healthy. By RDFA, we can extract a limited number of highly explanatory factors, as low as 8, significantly discriminating between the two groups. Also, we show that different brain patterns can be identified across different stimulation scenarios and EEG locations. Although preliminary, this work could give support to domain experts while providing some clinically-meaningful insights to identify common patterns as well as individual characteristics in different groups of healthy and pathological subjects.
Reinforcement learning yields a feedback controller that achieves specific control goal (which is often translated as a reward function). However, it often suffers from the Sim2Real gap, and domain randomization is kn...
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