Additive manufacturing holds the potential to revolutionize circuit fabrication and enable the widespread adoption of printed electronics, particularly in flexible applications, such as wearable or conformable electro...
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Reinforcement learning has traditionally been studied with exponential discounting or the average reward setup, mainly due to their mathematical tractability. However, such frameworks fall short of accurately capturin...
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Renewable energy such as solar power has been widely adopted lately due to its sustainability and cost-effectiveness. However, due to the intermittent nature of photovoltaic systems, accurate solar forecasting is vita...
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Canonicalization provides an architecture-agnostic method for enforcing equivariance, with generalizations such as frame-averaging recently gaining prominence as a lightweight and flexible alternative to equivariant a...
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Canonicalization provides an architecture-agnostic method for enforcing equivariance, with generalizations such as frame-averaging recently gaining prominence as a lightweight and flexible alternative to equivariant architectures. Recent works have found an empirical benefit to using probabilistic frames instead, which learn weighted distributions over group elements. In this work, we provide strong theoretical justification for this phenomenon: for commonly-used groups, there is no efficiently computable choice of frame that preserves continuity of the function being averaged. In other words, unweighted frame-averaging can turn a smooth, non-symmetric function into a discontinuous, symmetric function. To address this fundamental robustness problem, we formally define and construct weighted frames, which provably preserve continuity, and demonstrate their utility by constructing efficient and continuous weighted frames for the actions of SO(d), O(d), and Sn on point clouds. Copyright 2024 by the author(s)
The accurate prediction of photovoltaic(PV)power generation is significant to ensure the economic and safe operation of power *** this end,the paper establishes a new digital twin(DT)empowered PV power prediction fram...
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The accurate prediction of photovoltaic(PV)power generation is significant to ensure the economic and safe operation of power *** this end,the paper establishes a new digital twin(DT)empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power *** this framework,considering potential data contamination in the collected PV data,a generative adversarial network is employed to restore the historical dataset,which offers a prerequisite to ensure accurate mapping from the physical space to the digital ***,a new DT-empowered PV power prediction method is ***,we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model(i.e.,a parallel network of convolution and bidirectional long short-term memory model)for capturing the hidden spatiotemporal *** proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model,resulting in enhanced prediction ***,a real dataset is conducted to assess the effectiveness of the proposed method.
The agricultural area has undergone a significant transformation owing to the progress made in IoT. It is imperative to have a dependable remote monitoring solution right now. This study aims to accomplish two goals. ...
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The logistics sector serves as a vital artery in global trade, with freight forwarders facilitating the movement of goods from source to destination. However, the accuracy of freight billing remains a persistent chall...
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Manipulating fluids by light at the micro/nanoscale has been a long-sought-after goal for lab-on-a-chip *** heating has been demonstrated to control microfluidic dynamics due to the enhanced and confined light absorpt...
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Manipulating fluids by light at the micro/nanoscale has been a long-sought-after goal for lab-on-a-chip *** heating has been demonstrated to control microfluidic dynamics due to the enhanced and confined light absorption from the intrinsic losses of ***,the counterpart of metals,has been used to avoid undesired thermal effects due to its negligible light ***,we report an innovative optofluidic system that leverages a quasi-BIC-driven all-dielectric metasurface to achieve subwavelength scale control of temperature and fluid *** experiments show that suspended particles down to 200 nanometers can be rapidly aggregated to the center of the illuminated metasurface with a velocity of tens of micrometers per second,and up to millimeter-scale particle transport is *** strong electromagnetic field enhancement of the quasi-BIC resonance increases the flow velocity up to three times compared with the off-resonant situation by tuning the wavelength within several nanometers *** also experimentally investigate the dynamics of particle aggregation with respect to laser wavelength and power.A physical model is presented and simulated to elucidate the phenomena and surfactants are added to the nanoparticle colloid to validate the *** study demonstrates the application of the recently emerged all-dielectric thermonanophotonics in dealing with functional liquids and opens new frontiers in harnessing non-plasmonic nanophotonics to manipulate microfluidic ***,the synergistic effects of optofluidics and high-Q all-dielectric nanostructures hold enormous potential in high-sensitivity biosensing applications.
Alzheimer's disease (AD) is the most well-known cause of dementia that affects memory. Alzheimer's patients have a neurodegenerative disorder that results in the loss of many brain functions. Today’s research...
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An ultrasonic filter detects signs of malignant tumors by analysing the image’s pixel quality fluctuations caused by a liver *** of malignant growth proximity are identified in an ultrasound filter through image pixe...
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An ultrasonic filter detects signs of malignant tumors by analysing the image’s pixel quality fluctuations caused by a liver *** of malignant growth proximity are identified in an ultrasound filter through image pixel quality variations from a liver’s *** changes are more common in alcoholic liver conditions than in other etiologies of cirrhosis,suggesting that the cause may be alcohol instead of liver *** Two-Dimensional(2D)ultrasound data sets contain an accuracy rate of 85.9%and a 2D Computed Tomography(CT)data set of 91.02%.The most recent work on designing a Three-Dimensional(3D)ultrasound imaging system in or close to real-time is *** this article,a Deep Learning(DL)model is implemented and modified to fit liver CT segmentation,and a semantic pixel classification of road scenes is *** architecture is called semantic pixel-wise segmentation and comprises a hierarchical link of encoder-decoder layers.A standard data set was used to test the proposed model for liver CT scans and the tumor accuracy in the training *** the normal class,we obtained 100%precision for chronic cirrhosis hepatitis(73%),offset cirrhosis(59.26%),and offensive cirrhosis(91.67%)for chronic hepatitis or cirrhosis(73,0%).The aim is to develop a computer-Aided Detection(CAD)screening tool to detect *** results proved 98.33%exactness,94.59%sensitivity,and 92.11%case with Convolutional Neural Networks(CNN)*** the classifier’s performance did not differentiate so clearly at this level,it was recommended that CNN generally perform better due to the good relationship between Area under the Receiver Operating Characteristics Curve(AUC)and accuracy.
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