This paper proposes a mixed-integer linear programming optimization model used to define an energy management system tailored for nanogrids in buildings, integrating renewable energy sources, battery energy storage sy...
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This paper proposes a mixed-integer linear programming optimization model used to define an energy management system tailored for nanogrids in buildings, integrating renewable energy sources, battery energy storage systems and task-executing autonomous mobile robots. Focused on a nanogrid to be realised at the Savona Campus of the University of Genoa, the energy management system optimizes power flows and robot task scheduling in order to minimize the operating costs, the curtailment of the photovoltaic source and the number of unperformed tasks. Its novelty lies in combining energy and task planning constraints, offering significant potential for sustainable building energy management.
Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms ...
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ISBN:
(数字)9798350360585
ISBN:
(纸本)9798350360592
Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms.
In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consumi...
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ISBN:
(数字)9798331530839
ISBN:
(纸本)9798331530846
In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection.
Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires ...
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Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and ...
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Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising po...
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Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is con...
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Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is confined in an optical *** the case of 2D HOIPs,they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the ***,the fundamental properties of these self-hybridized E–Ps in 2D HOIPs,including their role in ultrafast energy and/or charge transfer at interfaces,remain ***,we demonstrate that>0.5µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P *** E–Ps have high Q factors(>100)and modulate the optical dispersion for the crystal to enhance sub-gap absorption and *** varying excitation energy and ultrafast measurements,we also confirm energy transfer from higher energy E–Ps to lower energy E–***,we also demonstrate that E–Ps are capable of charge transport and transfer at *** findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.
Water is an essential component of the Earth’s climate,but monitoring its properties using autonomous underwater sampling robots remains a significant challenge due to lack of underwater geolocalization *** methods f...
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Water is an essential component of the Earth’s climate,but monitoring its properties using autonomous underwater sampling robots remains a significant challenge due to lack of underwater geolocalization *** methods for underwater geolocalization rely on tethered systems with limited coverage or daytime imagery data in clear waters,leaving much of the underwater environment *** in turbid waters or at night has been considered unfeasible due to absence of identifiable *** this paper,we present a novel method for underwater geolocalization using deep neural networks trained on -10 million polarization-sensitive images acquired globally,along with camera position sensor *** approach achieves longitudinal accuracy of -55 km(-1000 km)during daytime(nighttime)at depths up to -8 m,regardless of water *** clear waters,the transfer learning longitudinal accuracy is -255 km at 50 m *** leveraging optical data in conjunction with camera position information,our novel method facilitates underwater geolocalization and offers a valuable tool for untethered underwater navigation.
Various obstacles[poor tissue penetration,hypoxic tumor microenvironment,and reactive oxygen species(ROS)production quenching due to aggregation]obstruct imaging-guided high-efficiency phototherapy targeting ***,nanop...
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Various obstacles[poor tissue penetration,hypoxic tumor microenvironment,and reactive oxygen species(ROS)production quenching due to aggregation]obstruct imaging-guided high-efficiency phototherapy targeting ***,nanophthalocyanine(ZnPcN4-TF)is elaborately designed based on a synthetic phthalocyanine derivative(ZnPcN4)and nonimmunogenic transferrin(TF)through multiple noncovalent interactions for photoacoustic(PA)imaging-guided *** conjugating electron-rich amino groups effectively suppressed fluorescence and ROS generation due to the strong photoinduced electron transfer effect,ZnPcN4 became an ideal photothermal and PA imaging ***4-TF not only effectively targeted tumor sites and accumulated there,but also,surprisingly,facilitated the enhancement of ROS production via a type I process in an aggregate compared to ZnPcN4 itself,potentially due to accelerated electron ***,ZnPcN4-TF had a substantially more powerful photothermal effect than ZnPcN4 ***,this design effectively overcomes the obstacles to photodynamic therapy(aggregation-related ROS generation quenching in a hypoxic environment).Furthermore,PA imaging solves the tissue penetration challenge in optical *** study provides a broader base for designing novel photosensitizers to improve phototherapy under hypoxia.
In this study, we report the process variation effect (PVE) including the work function fluctuation (WKF) on the DC/AC characteristic fluctuation of stacked gate-all-around silicon complementary field-effect transisto...
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