251 research outputs found
Generalization Error Analysis of Neural networks with Gradient Based Regularization
We study gradient-based regularization methods for neural networks. We mainly
focus on two regularization methods: the total variation and the Tikhonov
regularization. Applying these methods is equivalent to using neural networks
to solve some partial differential equations, mostly in high dimensions in
practical applications. In this work, we introduce a general framework to
analyze the generalization error of regularized networks. The error estimate
relies on two assumptions on the approximation error and the quadrature error.
Moreover, we conduct some experiments on the image classification tasks to show
that gradient-based methods can significantly improve the generalization
ability and adversarial robustness of neural networks. A graphical extension of
the gradient-based methods are also considered in the experiments
A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice
The evaluation of yield-related traits is an essential step in rice breeding, genetic research and functional genomics research. A new, automatic, and labor-free facility to automatically thresh rice panicles, evaluate rice yield traits, and subsequently pack filled spikelets is presented in this paper. Tests showed that the facility was capable of evaluating yield-related traits with a mean absolute percentage error of less than 5% and an efficiency of 1440 plants per continuous 24 h workday
Curriculum Temperature for Knowledge Distillation
Most existing distillation methods ignore the flexible role of the
temperature in the loss function and fix it as a hyper-parameter that can be
decided by an inefficient grid search. In general, the temperature controls the
discrepancy between two distributions and can faithfully determine the
difficulty level of the distillation task. Keeping a constant temperature,
i.e., a fixed level of task difficulty, is usually sub-optimal for a growing
student during its progressive learning stages. In this paper, we propose a
simple curriculum-based technique, termed Curriculum Temperature for Knowledge
Distillation (CTKD), which controls the task difficulty level during the
student's learning career through a dynamic and learnable temperature.
Specifically, following an easy-to-hard curriculum, we gradually increase the
distillation loss w.r.t. the temperature, leading to increased distillation
difficulty in an adversarial manner. As an easy-to-use plug-in technique, CTKD
can be seamlessly integrated into existing knowledge distillation frameworks
and brings general improvements at a negligible additional computation cost.
Extensive experiments on CIFAR-100, ImageNet-2012, and MS-COCO demonstrate the
effectiveness of our method. Our code is available at
https://github.com/zhengli97/CTKD.Comment: AAAI 202
The evolution of glacial lake and glaciers and their potential impact on glacial debris flow activity in the Palong Zangbu catchment in Southeastern Tibet
Due to warm and humid air currents of the Indian Ocean and the southwest monsoon, the Palong Zangbo catchment in southeastern Tibet has developed oceanic glaciers in the valley, and the activity of glacial debris flows has been gradually intensified under neotectonic activity, frequent earthquakes, climate change, and extreme rainfall. In this paper, the topographic and morphological data of the debris flow basin, the dynamic evolution characteristics of glaciers and glacial lakes were analyzed by using multisource long-term series of remote sensing images. Simultaneously, the distribution of moraines and landslide sources were extracted based on satellite image. In addition, climate change in the study area was analysed using temperature and rainfall data from the last 40 years, revealing that the average temperature in the study area from May to October presented a fluctuating tendency as a whole, especially after 2013, when the temperature gradually increased. As these temperature changes led to continuous melting of the glaciers in the study area, the glacier area decreased from 8,300 km2 in 1988–4,584 km2 in 2019, which decreased nearly 45%. However, the number and area of glacial lakes in the study area gradually increased under a power-law trend, which further led to a significant increase on the possibility of glacial lake rupture in the study area. Due to the joint effects of earthquakes, glacier melting and glacial lake collapse, the debris flows in the study area were well developed, and a total of 122 debris flows were found with varying channel lengths, areas and material sources. Importantly, the characteristics of the glaciers, glacial lakes and climate change in the study area have indicated that the glaciers have retreated, the number of glacial lakes has increased, and the risk of debris flow in this basin will increase in the future. Therefore, it is necessary to strengthen monitoring and early warnings on floods due to glacial lake collapses and debris flows in the study area to improve the risk management of debris flows and floods and the prevention and mitigation of disasters
Plasma noise in TianQin time delay interferometry
TianQin is a proposed geocentric space-based gravitational wave observatory
mission, which requires time-delay interferometry (TDI) to cancel laser
frequency noise. With high demands for precision, solar-wind plasma environment
at km above the Earth may constitute a non-negligible noise source
to laser interferometric measurements between satellites, as charged particles
perturb the refractivity along light paths. In this paper, we first assess the
plasma noises along single links from space-weather models and numerical
orbits, and analyze the time and frequency domain characteristics.
Particularly, to capture the plasma noise in the entire measurement band of
Hz, we have performed additional space-weather
magnetohydrodynamic simulations in finer spatial and temporal resolutions and
utilized Kolmogorov spectra in high-frequency data generation. Then we evaluate
the residual plasma noises of the first- and second-generation TDI
combinations. Both analytical and numerical estimations have shown that under
normal solar conditions the plasma noise after TDI is less than the secondary
noise requirement. Moreover, TDI is shown to exhibit moderate suppression on
the plasma noise below Hz due to noise correlation between
different arms, when compared with the secondary noise before and after TDI.Comment: 12 pages, 15 figures, accepted by Phys. Rev.
Risk factors for symptomatic rotator cuff tears: a retrospective case–control study
BackgroundThe incidence and diagnostic rate of rotator cuff tears (RCTs) have increased significantly. The purpose of this study was to investigate and analyze the risk factors for symptomatic RCTs to provide a basis for their prevention and treatment.MethodsWe retrospectively analyzed the relevant clinical indicators of 193 patients with RCTs and 161 patients without RCTs hospitalized with shoulder pain as the main complaint from January 1, 2017, to August 31, 2021. Univariate analysis and multivariate logistic regression analysis were used to analyze the differences in potential risk factors between the two groups.ResultsUnivariate analysis revealed that age (p < 0.001), body mass index (BMI) (p = 0.036), hypertension (p < 0.001), coronary heart disease (p = 0.028), history of shoulder trauma (p < 0.001), hyperlipidemia (p = 0.025), type III acromion (p = 0.012) and critical shoulder angle (CSA) (p < 0.001) increased the risk of RCTs. Multivariate logistic regression analysis revealed that age ≥ 60 years (OR = 2.61, 95% CI = 1.23 to 5.12), CSA ≥ 35° (OR = 4.24, 95% CI = 1.60 to 11.22), hypertension (OR = 2.34, 95% CI = 1.33 to 4.11) and history of shoulder trauma (OR = 5.20, 95% CI = 2.87 to 9.45) were independent risk factors for symptomatic RCTs.ConclusionThe results of this study showed that age ≥ 60 years, CSA ≥35°, hypertension and history of shoulder trauma are independent risk factors for symptomatic RCTs and can provide directions for further development of prevention and treatment strategies. Future studies need to clarify the mechanism underlying the association between these risk factors and symptomatic RCTs
Congestion window control based on queuing delay and packet loss
A method of controlling size of a congestion window, includes, at a transmitting device, transmitting a plurality of data packets over a communication channel from the transmitting device to a receiver, determining a queuing delay and a loss rate of the transmission, comparing the queuing delay to a threshold queuing delay, comparing the loss rate to a threshold loss rate, and in response to a determination that the queuing delay is greater than the threshold queuing delay and the loss rate is greater than the threshold loss rate, resetting the size of the congestion window in accordance with a function of the current size of the congestion window, the queuing delay, and the loss rate, wherein at equilibrium the function generates a value inversely proportional to a weighted sum of an excess queuing delay and an excess loss rate
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