Category: Engineering & Energy
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Upper bounds found for perfect matchings in bipartite hypergraphs
This research indicates that certain bipartite hypergraphs, Latin squares, and regular hypergraphs have explicit upper bounds on the number of perfect matchings, transversals, or proper edge-colorings.
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Sociotechnical barriers hinder digital engineering transformation
This research indicates that digital engineering transformation is often hindered by sociotechnical barriers, especially workforce readiness, leadership support, and cultural alignment, and that technological investments alone are not sufficient.
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Bioinspired underwater soft robots draw on four biological principles
This research indicates that underwater soft robot design can be guided by four biological principles and by a bidirectional loop between biology and robotics.
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Rarefaction weakens electromagnetic flow control in hypersonic plasma
This research indicates that rarefaction weakens the influence of electromagnetic control in hypersonic flows around a hemisphere, and that multiscale modelling is needed for plasma flow applications.
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Stochastic methods improve aggregator profit and risk handling
This research indicates that stochastic optimization methods can outperform deterministic methods for aggregators of consumer energy resources, with the best choice depending on whether uncertainty is captured correctly.
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More matched pairs changed win ratio and confidence intervals
This research indicates that increasing the number of matched data pairs affects the win ratio statistic and its 95% confidence intervals for two composite endpoints.
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Controlled reinforced dielectric elastomer prosthesis matched facial muscle signals
This research indicates that a reinforced dielectric elastomer actuator model and closed-loop control can improve the precision of facial prosthesis actuation for restored smiling movements.
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Soft actuators may benefit from human muscle control principles
This research indicates that soft actuators share key mechanical characteristics with human muscles and could benefit from control mechanisms inspired by human sensorimotor control.
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Lightweight models achieved over 93% cloud-mask accuracy
This research indicates that lightweight machine learning models can accurately mask clouds and cloud shadows in hyperspectral satellite imaging, with a convolutional neural network using feature reduction offering the best balance of accuracy, storage, and inference speed.
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Virtual energy station model improves multi-energy scheduling
This research indicates that a virtual energy station framework can improve multi-energy scheduling under uncertainty while reducing operating costs and improving exergy utilization.
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