We study the Gaussian fluctuations of a nonlinear stochastic heat equation in spatial dimension two. The equation is driven by a Gaussian multiplicative noise. The noise is white in time, smoothed in ...space at scale
ε
, and tuned logarithmically by a factor
1
log
ε
-
1
in its strength. We prove that, after centering and rescaling, the solution random field converges in distribution to an Edwards-Wilkinson limit as
ε
↓
0
. The tool we used here is the Malliavin-Stein’s method. We also give a functional version of this result.
The rapid development of modern technology and civilization has made the survival of non-heritage culture more and more serious, and the protection and inheritance of intangible cultural heritage is ...a heavy task and a long way to go. This paper takes the feasibility of non-heritage animation creation as an entry point, analyzes the ideological mechanism in the process of non-heritage animation creation, and explores the economic realization brought by deep learning technology assisting non-heritage animation creation. For the lens scene switching in the process of non-heritage animation creation, this paper utilizes the CNN network for the initial positioning of the lens boundary. It establishes the tangent detection model of a non-heritage animation lens by combining it with the 3D-CNN network. To understand the diversity of non-heritage animation creation styles, this paper establishes a model for style migration of non-heritage cultural images based on the VGG-Net network and conducts experimental investigations. The results show that when the hyperparameter value of the model is set to
= 3,
= 1.2, the model retains only 5.19% of the candidate boundary frames, and the accuracy of the detection of the non-heritage animation creation tangent shots is 0.939. The total loss value in the process of style migration fluctuates around 0.005, and the subjective evaluation score of the images generated by the style migration network is 4.82. The deep learning algorithm that promotes the creation of non-heritage animation can expand the content and characteristics of non-heritage animation creation and can also realize the economic realization of non-heritage animation.
Siamese Instance Search for Tracking Ran Tao; Gavves, Efstratios; Smeulders, Arnold W. M.
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
2016-June
Conference Proceeding
Open access
In this paper we present a tracker, which is radically different from state-of-the-art trackers: we apply no model updating, no occlusion detection, no combination of trackers, no geometric matching, ...and still deliver state-of-the-art tracking performance, as demonstrated on the popular online tracking benchmark (OTB) and six very challenging YouTube videos. The presented tracker simply matches the initial patch of the target in the first frame with candidates in a new frame and returns the most similar patch by a learned matching function. The strength of the matching function comes from being extensively trained generically, i.e., without any data of the target, using a Siamese deep neural network, which we design for tracking. Once learned, the matching function is used as is, without any adapting, to track previously unseen targets. It turns out that the learned matching function is so powerful that a simple tracker built upon it, coined Siamese INstance search Tracker, SINT, which only uses the original observation of the target from the first frame, suffices to reach state-of-the-art performance. Further, we show the proposed tracker even allows for target re-identification after the target was absent for a complete video shot.
This essay draws on an original cross-sectional survey of 1,010 children and their guardians in highly migratory regions of Anhui and Jiangxi provinces located in China's interior. It uses propensity ...score matching, a technique that mitigates endogenity, to examine the impact of parental migration and post-migration guardianship arrangements on the children's educational performance as measured by test scores for Chinese and mathematics. One core finding is that the educational performance of children is adversely affected by parental migration only when both parents migrate or when a non-parent guardian is the principal carer. Additionally, longer durations of parental absence are associated with poorer educational performance. The migration of two parents only significantly adversely affects the educational performance of boys. There is no significant effect on the educational performance of girls. On the basis of our findings we argue that rather than support left-behind children within the countryside, the long-term policy response should be to remove the institutional obstacles that prevent family resettlement in the cities.
Limited by the size of microelectronics, as well as the space of electrical vehicles, there are tremendous demands for lithium-ion batteries with high volumetric energy densities. Current lithium-ion ...batteries, however, adopt graphite-based anodes with low tap density and gravimetric capacity, resulting in poor volumetric performance metric. Here, by encapsulating nanoparticles of metallic tin in mechanically robust graphene tubes, we show tin anodes with high volumetric and gravimetric capacities, high rate performance, and long cycling life. Pairing with a commercial cathode material LiNi
Mn
Co
O
, full cells exhibit a gravimetric and volumetric energy density of 590 W h Kg
and 1,252 W h L
, respectively, the latter of which doubles that of the cell based on graphite anodes. This work provides an effective route towards lithium-ion batteries with high energy density for a broad range of applications.
Loss of the E3 ubiquitin ligase Parkin causes early onset Parkinson's disease, a neurodegenerative disorder of unknown etiology. Parkin has been linked to multiple cellular processes including ...protein degradation, mitochondrial homeostasis, and autophagy; however, its precise role in pathogenesis is unclear. Recent evidence suggests that Parkin is recruited to damaged mitochondria, possibly affecting mitochondrial fission and/or fusion, to mediate their autophagic turnover. The precise mechanism of recruitment and the ubiquitination target are unclear. Here we show in Drosophila cells that PINK1 is required to recruit Parkin to dysfunctional mitochondria and promote their degradation. Furthermore, PINK1 and Parkin mediate the ubiquitination of the profusion factor Mfn on the outer surface of mitochondria. Loss of Drosophila PINK1 or parkin causes an increase in Mfn abundance in vivo and concomitant elongation of mitochondria. These findings provide a molecular mechanism by which the PINK1/Parkin pathway affects mitochondrial fission/fusion as suggested by previous genetic interaction studies. We hypothesize that Mfn ubiquitination may provide a mechanism by which terminally damaged mitochondria are labeled and sequestered for degradation by autophagy.
With the rapid development of spaceborne imaging techniques, object detection in optical remote sensing imagery has drawn much attention in recent decades. While many advanced works have been ...developed with powerful learning algorithms, the incomplete feature representation still cannot meet the demand for effectively and efficiently handling image deformations, particularly objective scaling and rotation. To this end, we propose a novel object detection framework, called Optical Remote Sensing Imagery detector (ORSIm detector), integrating diverse channel features extraction, feature learning, fast image pyramid matching, and boosting strategy. An ORSIm detector adopts a novel spatial-frequency channel feature (SFCF) by jointly considering the rotation-invariant channel features constructed in the frequency domain and the original spatial channel features (e.g., color channel and gradient magnitude). Subsequently, we refine SFCF using learning-based strategy in order to obtain the high-level or semantically meaningful features. In the test phase, we achieve a fast and coarsely scaled channel computation by mathematically estimating a scaling factor in the image domain. Extensive experimental results conducted on the two different airborne data sets are performed to demonstrate the superiority and effectiveness in comparison with the previous state-of-the-art methods.
Traditional micro-Doppler (m-D)-based human activity classification system using monostatic radar suffers from the drawback that classification performance is vulnerable to the variation of human ...motion aspect angle. This leads to a performance degradation if the human movements are not directly toward or away with respect to the radar line of sight. The multistatic radar system has been suggested as an effective solution to solve the problem, as it can observe the target from multiple views and achieve favorable aspect angles to the targets. In this article, a novel human activity classification method based on motion orientation determining using multistatic m-D signals is proposed. First, the aspect angles of target motion direction with respect to each radar nodes are inferred by using the proposed motion orientation estimation method. The multistatic m-D data are then divided into several intervals based on the measured angle, and the data in the same interval are fused at the data level. Finally, the classification results are obtained through the adaptive weighted decision-level fusion. Compared with the traditional multistatic classification method, due to the consideration of the time-varying human motion aspect angle, the proposed method is more reasonable in data fusion and has better classification performance.
Novel composite separators containing metal–organic‐framework (MOF) particles and poly(vinyl alcohol) are fabricated by the electrospinning process. The MOF particles containing opened metal sites ...can spontaneously adsorb anions while allowing effective transport of lithium ions in the electrolyte, leading to dramatically improved lithium‐ion transference number tLi+ (up to 0.79) and lithium‐ion conductivity. Meanwhile, the incorporation of the MOF particles alleviates the decomposition of the electrolyte, enhances the electrode reaction kinetics, and reduces the interface resistance between the electrolyte and the electrodes. Implementation of such composite separators in conventional lithium‐ion batteries leads to significantly improved rate capability and cycling durability, offering a new prospective toward high‐performance lithium‐ion batteries.
An electrospun composite separator comprising metal–organic frameworks with open metal sites (OMSs) is developed for high‐rate lithium‐ion batteries, where the OMSs can efficiently immobilize anions in the electrolyte and afford highly mobile lithium ions. This work opens up new opportunities for functional separators aiming at regulating ion transport in the electrolyte and achieving a high rate capability of batteries.
•Neyman-Pearson detection is applied to estimate large coefficients of noise-corrupted signals in the fractional Fourier domain.•Distribution of phase error is obtained via Parzen-Rosenblatt window ...method.•Location error correction method is proposed.•Important properties of the proposed optimized sparse fractional Fourier transform are investigated via extensive simulations.•Real data collected from a continuous-wave radar is processed and the velocity of a free falling target is estimated.
For the input signals that can be sparsely represented in the fractional Fourier domain, sparse discrete fractional Fourier transform (SDFrFT) has been proposed to accelerate the numerical computation of discrete fractional Fourier transform. While significantly alleviating the computational load, SDFrFT has narrow applicability since it is more suitable for large-scale input signals. In this regard, the objective of this work is to overcome the limitation and further optimize the numerical computation of SDFrFT by exploiting the underlying phase information. We first employ Neyman-Pearson approach to achieve a noise-robust detection. Then, we derive the probability distribution function of the phase error in the location stage and, accordingly, design a location error correction algorithm. The proposed algorithm, termed optimized sparse fractional Fourier transform (OSFrFT), can reduce the computational complexity while guarantee sufficient robustness and estimation accuracy. Simulation results are provided to validate the effectiveness of the proposed algorithm. A successful application of OSFrFT to continuous wave radar signal processing is also presented.
PDF
