Residual computation is an effective method for gray-scale image steganalysis. For binary images, the residual computation calculated by the XOR operation is also employed in the local residual patterns(LRP) model for...
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Residual computation is an effective method for gray-scale image steganalysis. For binary images, the residual computation calculated by the XOR operation is also employed in the local residual patterns(LRP) model for steganalysis. A binary image steganalytic scheme based on symmetrical local residual patterns(SLRP) is proposed. The symmetrical relationships among residual patterns are introduced that make the features more compact while reducing the dimensionality of the features set. Multi-scale windows are utilized to construct three SLRP submodels which are further merged to construct the final features set instead of a single *** with higher probability to be modified after embedding are emphasized and selected to construct the feature sets for training the support vector machine classifier. The experimental results show that the proposed steganalytic scheme is effective for detecting binary image steganography.
The superconducting ground state of kagome metals AV_(3)Sb_(5)(where A stands for K,Rb,or Cs)emerges from an exotic charge density wave(CDW)state that potentially breaks both rotational and time reversal ***,the speci...
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The superconducting ground state of kagome metals AV_(3)Sb_(5)(where A stands for K,Rb,or Cs)emerges from an exotic charge density wave(CDW)state that potentially breaks both rotational and time reversal ***,the specifics of the Cooper pairing mechanism,and the nature of the interplay between these two states remain elusive,largely due to the lack of momentum-space(k-space)superconducting energy gap *** implementing Bogoliubov quasiparticle interference(B QPI)imaging,we obtain k-space information on the multiband superconducting gap structureΔ_(SC)^(i)(k)in pristine CsV_(3)Sb_(5).We show that the estimated energy gap on the vanadium d_(xy/x^(2)-y^(2))orbital is anisotropic but nodeless,with a minimal value located near the M ***,a comparison ofΔ_(SC)^(i)(k)with the CDW gapΔ_(CDW)^(i)(k)obtained by angle-re solved photoemission spectro scopy(ARPES)reveals direct k-space competition between the se two order parameters,i.e.,the opening of a large(small)CDW gap at a given momentum corresponds to a small(large)superconducting *** the long-range CDW order is suppressed by replacing vanadium with titanium,we find a nearly isotropic energy gap on both the V and Sb *** information will be critical for identifying the microscopic pairing mechanism and its interplay with intertwined electro nic orders in this kagome superconductor family.
Recently,the global background concentration of ozone(O_(3))has demonstrated a rising *** various methods,groun-basedmonitoring of O_(3)concentrations is highly reliable for research *** obtain information on the spat...
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Recently,the global background concentration of ozone(O_(3))has demonstrated a rising *** various methods,groun-basedmonitoring of O_(3)concentrations is highly reliable for research *** obtain information on the spatial characteristics of O_(3)concentrations,it is necessary that the groundmonitoring sites be constructed in sufficient *** recent years,many researchers have used machine learning models to estimate surface O_(3)concentrations,which cannot fully provide the spatial and temporal information contained in a sample *** solve this problem,the current study utilized a deep learning model called the Residual connection Convolutional Long Short-Term Memory network(RConvLSTM)to estimate daily maximum8-hr average(MDA8)O_(3)over Jiangsu province,China during *** this research,the R-ConvLSTM model not only provides the spatiotemporal information ofMDA8 O_(3),but also involves residual connection to avoid the problem of gradient explosion and gradient disappearance with the deepening of network *** utilized the TROPOMI total O_(3)column retrieved fromSentinel-5 Precursor,ERA5 reanalysismeteorological data,and other supplementary data to build a pre-trained *** R-ConvLSTM model achieved an overall sample-base cross-validation(CV)R^(2)of 0.955 with root mean square error(RMSE)of 9.372μg/m^(3).Model estimation also showed a city-based CV R^(2)of 0.896 with RMSE of 14.029μg/m^(3),the highest MDA8 O_(3)in spring being 122.60±31.60μg/m^(3)and the lowest in winter being 69.93±18.48μg/m^(3).
This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time ***,the authors propose an online algorithm with critic and actor NNs to...
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This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time ***,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation ***,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation ***,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno ***,the authors provide a numerical example to illustrate the effectiveness of the proposed method.
The propagation characteristics of ultra-low frequency (ULF) electromagnetic (EM) waves in the ocean and within the ocean-ionosphere waveguide model have been studied. Numerical simulations were conducted using the al...
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Fourier ptychographic microscopy (FPM) combines the concepts of phase retrieval algorithms and synthetic apertures and can solve the problem in which it is difficult to combine a large field of view with high resoluti...
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Fourier ptychographic microscopy (FPM) combines the concepts of phase retrieval algorithms and synthetic apertures and can solve the problem in which it is difficult to combine a large field of view with high resolution. However, the use of the coherent transfer function in conventional calculations to describe the linear transfer proc-ess of an imaging system can lead to ringing artifacts. In addition, the Gerchberg-Saxton iterative algorithm can cause the phase retrieval part of the FPM algorithm to fall into a local optimum. In this paper, Gaussian apodization coherent transfer function is proposed to describe the imaging process and is combined with an iterative method based on amplitude weighting and phase gradient descent to reduce the presence of ringing artifacts while ensuring the accuracy of the reconstructed results. In simulated experiments, the proposed algorithm is shown to give a smaller mean square error and higher structural similarity, both in the presence and absence of noise. Finally, the proposed algorithm is validated in terms of giving reconstruction results with high accuracy and high resolution, using images acquired with a new microscope system and open-source images. (c) 2023 Optica Publishing Group
Contrastive learning can reduce the impact of ex-posure bias associated with training using maximum likelihood estimation, which aims to pull together positive samples to increase the likelihood of high-quality summar...
Contrastive learning can reduce the impact of ex-posure bias associated with training using maximum likelihood estimation, which aims to pull together positive samples to increase the likelihood of high-quality summaries and push away irrelevant negative samples to reduce the likelihood of low-quality summaries. In contrastive learning-based text summarization methods, a standard method for selecting positive and negative samples is randomly selected within a batch. This method can lead to sampling bias to the extent that the consistency of the representation space is compromised. Therefore, we propose a new method to penalize false negatives based on ROUGE metric scores as weights to sample from the dynamic output of the model training process. The method calculates ROUGE metric scores for penalizing false negatives in real-time and can distinguish between positive and negative samples to ensure spatial consistency and alleviate exposure bias. Experimental results on XSum, CNN/DM, and Multi-News datasets show that our approach effectively improves the performance of the latest text summarization pre-training models.
作者：
Dong, HaoZhou, JianAnhui University
Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Hefei China
In this paper, we propose an innovative multi scale model called Dual-3DCRU, designed to extract more discriminative feature from both the left and right hemispheres. Byleveraging spatial relationships of electrode lo...
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Aspect-based sentiment analysis (ABSA) is an NLP task that classify fine-grained sentiment towards one specific aspect from the same text. While attention mechanism has achieved great success, attaching aspects to abs...
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Accurate spectroscopic data for H_(2)^(16)O in the 1.1μm region are particularly important for the study of Earth's *** pure water vapor molecular spectra were measured based on direct laser absorption spectrosco...
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Accurate spectroscopic data for H_(2)^(16)O in the 1.1μm region are particularly important for the study of Earth's *** pure water vapor molecular spectra were measured based on direct laser absorption spectroscopy using a narrow line-width external cavity diode laser combined with a high-precision Fabry-Pérot etalon.A total of 31 H_(2)^(16)O transitions were studied for the first time by using the speed-dependent Nelkin-Ghatak profile and the Hartmann-Tran *** an accurate line-shape analysis,we obtained the line intensities and the self-broadening coefficients,and they are compared with the available data reported in the HITRAN 2016 database and the HITRAN 2020 ***,we obtained information on the influence of Dicke narrowing,as well as the correlations between Dicke narrowing and speed dependence,and of speed-dependent effects.
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