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This paper presents a multiplierless image-cipher, with extendable 2048-bit key-space, based on a 4-dimensional (4D) quantized piece-wise linear cat map (PWLCM). The quantized PWLCM exhibits limit-cycles of 4-bit encoded integers with periods greater than 107. The synthesis of the PWLCM in a finite state space allows to eliminate the undesirable finite precision effect due to the hardware realization. The proposed image-cipher combines chaos, modular arithmetic, and lattice-based cryptography to encrypt a color image by performing pixel permutation and diffusion in a single operation. Further, an image-dependent confusion operation based on an 8-bit 2D-PWLCM is performed on the whole image to enhance security. |
Thanks to the development of depth sensors and pose estimation algorithms, skeleton-based action recognition has become prevalent in the computer vision community. Most of the existing works are based on spatio-temporal graph convolutional network frameworks, which learn and treat all spatial or temporal features equally, ignoring the interaction with channel dimension to explore different contributions of different spatio-temporal patterns along the channel direction and thus losing the ability to distinguish confusing actions with subtle differences. In this paper, an interactional channel excitation (ICE) module is proposed to explore discriminative spatio-temporal features of actions by adaptively recalibrating channel-wise pattern maps. |
Random numbers play a key role in a wide variety of applications, ranging from mathematical simulation to cryptography. Generating random or pseudo-random numbers is not an easy task, especially when hardware, time and energy constraints are considered. In order to assess whether generators behave in a random fashion, there are several statistical test batteries. ENT is one of the simplest and most popular, at least in part due to its efficacy and speed. Nonetheless, only one of the tests of this suite provides a p value, which is the most useful and standard way to determine whether the randomness hypothesis holds, for a certain significance level. As a consequence of this, rather arbitrary and at times misleading bounds are set in order to decide which intervals are acceptable for... |
This paper aims at studying a generalized Camassa–Holm equation under random perturbation. We establish a local well-posedness result in the sense of Hadamard, i.e., existence, uniqueness and continuous dependence on initial data, as well as blow-up criteria for pathwise solutions in the Sobolev spaces Hs with s>3/2 for x∈R
. The analysis on continuous dependence on initial data for nonlinear stochastic partial differential equations has gained less attention in the literature so far. |
This paper studies intergenerational links in home ownership, an increasingly important wealth marker and a measure of economic status in itself. Repeated cross sectional UK data show that home ownership rates have fallen rapidly over time, most markedly amongst younger people in more recent birth cohorts. Evidence from British birth cohorts data supplemented by the Wealth and Assets Survey show a significant rise through time in the intergenerational persistence of home ownership, as home ownership rates shrank disproportionately among those whose parents did not own their own home. Given the close connection between home ownership and wealth, these results on strengthening intergenerational persistence in home ownership are therefore also suggestive of a fall in intergenerational ... |
Using new data from a three-wave panel survey administered in Germany between May 2020 and May 2021, this paper studies the impact of a negative shock affecting all strata of the population, such as the development of COVID-19, on preferences for redistribution. Exploiting the plausibly exogenous change in the severity of the infection rate at the county level, we show that, contrary to some theoretical expectations, the worse the crisis, the less our respondents expressed support for redistribution. We provide further evidence that this is not driven by a decrease in inequality aversion but might be driven by the individuals’ level of trust. |
Monitoring Consumption Switzerland is a public–private partnership between the University of St. Gallen and the payment companies Worldline and SIX that processes and publishes payment data on transactions in Switzerland processed by Wordline/SIX in real time. This paper provides background information on this novel source of data and presents their attributes, aggregation and granularity, and their interpretability. The paper presents several use cases that show the strengths of the data, and it alerts future users of the data to possible challenges. The paper also discusses the project's impact and provides an outlook. |
Tactile perception plays a critical role in the interaction of humans and environment. It begins with the mechanical stimulation induced by friction and is processed in the somatosensory cortex. To quantify the tactile perceptions of textile fabrics, the mechanical properties of fabrics and the features extracted from the friction and vibration signals were correlated with the subjective sensation rated by questionnaires. Meanwhile, the technique of functional magnetic resonance imaging (fMRI) was used to identify the brain areas responsible for the tactile perception of textile fabrics. |
Herein, a porous oil-containing material with hierarchical pore structure was successfully prepared through microtexturing large pores on the surface of porous polyimide (PPI) with single-level small pores. Compared to the conventional oil-containing material, the hierarchically porous oil-containing material exhibited high oil-content, and retained excellent mechanical properties and high oil-retention because of the synergistic effects of large pores and small pores. Furthermore, the lubricant stored in the hierarchically porous polyimide could release to the interface under thermal-and-mechano-stimuli, and the released lubricant could be reabsorbed into the hierarchically porous polyimide via the capillary-force offered by the porous channel. Based on the high oil-content and rec... |
Recent years have witnessed the popularity of using two-stream convolutional neural networks for action recognition. However, existing two-stream convolutional neural network-based action recognition approaches are incapable of distinguishing some roughly similar actions in videos such as sneezing and yawning. To solve this problem, we propose a Multi-head Attention-based Two-stream EfficientNet (MAT-EffNet) for action recognition, which can take advantage of the efficient feature extraction of EfficientNet. The proposed network consists of two streams (i.e., a spatial stream and a temporal stream), which first extract the spatial and temporal features from consecutive frames by using EfficientNet. |
