An intelligent reflecting surface(IRS),or its various equivalents such as an reconfigurable intelligent surface(RIS), is an emerging technology to control radio signal propagation in wireless systems. An IRS is a digi...
An intelligent reflecting surface(IRS),or its various equivalents such as an reconfigurable intelligent surface(RIS), is an emerging technology to control radio signal propagation in wireless systems. An IRS is a digitally controlled metasurface consisting of a large number of passive reflecting elements, which are connected to a smart controller to enable dynamic adjustments of the amplitude and/or phase of the incident signal on each element independently [1].
Knowledge distillation (KD) compresses the network capacity by transferring knowledge from a large (teacher) network to a smaller one (student). It has been mainstream that the teacher directly transfers knowledge to ...
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Waveguide-integrated mid-infrared(MIR)photodetectors are pivotal components for the development of molecular spectroscopy applications,leveraging mature photonic integrated circuit(PIC)*** various strategies,critical ...
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Waveguide-integrated mid-infrared(MIR)photodetectors are pivotal components for the development of molecular spectroscopy applications,leveraging mature photonic integrated circuit(PIC)*** various strategies,critical challenges still remain in achieving broadband photoresponse,cooling-free operation,and large-scale complementary-metal-oxide-semiconductor(CMOS)-compatible *** leap beyond these limitations,the bolometric effect-a thermal detection mechanism-is introduced into the waveguide *** importantly,we pursue a free-carrier absorption(FCA)process in germanium(Ge)to create an efficient light-absorbing medium,providing a pragmatic solution for full coverage of the MIR spectrum without incorporating exotic materials into ***,we present an uncooled waveguide-integrated photodetector based on a Ge-on-insulator(Ge-OI)PIC architecture,which exploits the bolometric effect combined with ***,our device exhibits a broadband responsivity of 28.35％/mW across 4030-4360 nm(and potentially beyond),challenging the state of the art,while achieving a noise-equivalent power of 4.03×10-7W/Hz0.5 at 4180 *** further demonstrate label-free sensing of gaseous carbon dioxide(CO2)using our integrated photodetector and sensing waveguide on a single *** approach to room-temperature waveguide-integrated MIR photodetection,harnessing bolometry with FCA in Ge,not only facilitates the realization of fully integrated lab-on-a-chip systems with wavelength flexibility but also provides a blueprint for MIR PICs with CMOS-foundry-compatibility.
Pretrained language models leverage selfsupervised learning to use large amounts of unlabeled text for learning contextual representations of sequences. However, in the domain of medical conversations, the availabilit...
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Multi-user Augmented Reality (MuAR) allows multiple users to interact with shared virtual objects, facilitated by exchanging environment information. Current MuAR systems rely on 3D point clouds for real-world analysi...
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Incredible progress has been made in human action recognition(HAR),significantly impacting computer vision applications in sports ***,identifying dynamic and complex movements in sports like badminton remains challeng...
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Incredible progress has been made in human action recognition(HAR),significantly impacting computer vision applications in sports ***,identifying dynamic and complex movements in sports like badminton remains challenging due to the need for precise recognition accuracy and better management of complex motion *** learning techniques like convolutional neural networks(CNNs),long short-term memory(LSTM),and graph convolutional networks(GCNs)improve recognition in large datasets,while the traditional machine learning methods like SVM(support vector machines),RF(random forest),and LR(logistic regression),combined with handcrafted features and ensemble approaches,perform well but struggle with the complexity of fast-paced sports like *** proposed an ensemble learning model combining support vector machines(SVM),logistic regression(LR),random forest(RF),and adaptive boosting(AdaBoost)for badminton action *** data in this study consist of video recordings of badminton stroke techniques,which have been extracted into spatiotemporal *** three-dimensional distance between each skeleton point and the right hip represents the spatial *** temporal features are the results of Fast Dynamic Time Warping(FDTW)calculations applied to 15 frames of each video *** weighted ensemble model employs soft voting classifiers from SVM,LR,RF,and AdaBoost to enhance the accuracy of badminton action *** E2 ensemble model,which combines SVM,LR,and AdaBoost,achieves the highest accuracy of 95.38%.
Combining optical and electronic systems could enable information processing that is a million times faster than existing gigahertz technology. Imagine leveraging nature’s fastest processes to power the electronics i...
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Combining optical and electronic systems could enable information processing that is a million times faster than existing gigahertz technology. Imagine leveraging nature’s fastest processes to power the electronics in semiconductor chips, quantum sensors and quantum computers. Such transformative speed would not only greatly improve the performance of technology, but unveil new vistas for fundamental science as well.
Deep learning has recently become a viable approach for classifying Alzheimer's disease(AD)in medical ***,existing models struggle to efficiently extract features from medical images and may squander additional in...
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Deep learning has recently become a viable approach for classifying Alzheimer's disease(AD)in medical ***,existing models struggle to efficiently extract features from medical images and may squander additional information resources for illness *** address these issues,a deep three‐dimensional convolutional neural network incorporating multi‐task learning and attention mechanisms is *** upgraded primary C3D network is utilised to create rougher low‐level feature *** introduces a new convolution block that focuses on the structural aspects of the magnetORCID:ic resonance imaging image and another block that extracts attention weights unique to certain pixel positions in the feature map and multiplies them with the feature map ***,several fully connected layers are used to achieve multi‐task learning,generating three outputs,including the primary classification *** other two outputs employ backpropagation during training to improve the primary classification *** findings show that the authors’proposed method outperforms current approaches for classifying AD,achieving enhanced classification accuracy and other in-dicators on the Alzheimer's disease Neuroimaging Initiative *** authors demonstrate promise for future disease classification studies.
Black phosphorus(BP)is an attractive material for two-dimensional(2D)electronics and optoelectronics given its direct optical band gap in the ***,the vulnerability of BP to oxygen and moisture under ambient conditions...
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Black phosphorus(BP)is an attractive material for two-dimensional(2D)electronics and optoelectronics given its direct optical band gap in the ***,the vulnerability of BP to oxygen and moisture under ambient conditions has been a significant impediment for the adoption of this material towards practical *** vulnerability has also curtailed the development of additively manufactured,solution processed,ink-jet printed BP devices,which are cost-effective alternatives to lithographically patterned rigid electronics and optoelectronics based on *** this work,we have fabricated stable BP electronic devices on flexible and compliant substrates using low-cost,additive manufacturing techniques with ink-jet printing through scalable chemical exfoliation *** address the stability issues with BP,ionic liquids(ILs)were used as a passivation layer on the surface of the BP to minimize oxidative *** enhanced stability of BP was inferred through Raman spectroscopy and scanning probe microscopy techniques,where no observable changes in the A^(1)_(g)and A^(2)_(g)Raman vibrational modes were observed with time for the BP films passivated with ILs over a period of 168 h under ambient *** the other hand,a blue-shift in these Raman modes was evident for unpassivated *** probe microscopy measurements clearly revealed the difference in the surface characteristics through localized regions of degradation that intensified with time,which was clearly absent in IL/BP *** stability measurements were also conducted in electronic device platforms for IL coated BP devices,where the temperature T dependence of the I_(ds)-V_(ds)characteristic was measured from T~5.4 to 335 *** demonstrations of stabilized ILs/BP devices at ambient printed on flexible polyimide substrates were also *** irradiation with broadband radiation appears to have a significant influence on the electrical behavior of BP,evident through t
Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of hete...
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Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of heterogeneous big data as a consequence of the growth of power grid technologies,along with data processing and advanced *** main obstacles in turning the heterogeneous large dataset into useful results are computational burden and information *** original contribution of this paper is to develop a new big data framework for detecting various intrusions from the smart grid systems with the use of AI ***,an AdaBelief Exponential Feature Selection(AEFS)technique is used to efficiently handle the input huge datasets from the smart grid for boosting ***,a Kernel based Extreme Neural Network(KENN)technique is used to anticipate security vulnerabilities more *** Polar Bear Optimization(PBO)algorithm is used to efficiently determine the parameters for the estimate of radial basis ***,several types of smart grid network datasets are employed during analysis in order to examine the outcomes and efficiency of the proposed AdaBelief Exponential Feature Selection-Kernel based Extreme Neural Network(AEFS-KENN)big data security *** results reveal that the accuracy of proposed AEFS-KENN is increased up to 99.5%with precision and AUC of 99%for all smart grid big datasets used in this study.
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