818 research outputs found
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness
Adversarial attacks can mislead neural network classifiers. The defense
against adversarial attacks is important for AI safety. Adversarial
purification is a family of approaches that defend adversarial attacks with
suitable pre-processing. Diffusion models have been shown to be effective for
adversarial purification. Despite their success, many aspects of diffusion
purification still remain unexplored. In this paper, we investigate and improve
upon three limiting designs of diffusion purification: the use of an improved
diffusion model, advanced numerical simulation techniques, and optimal control
of randomness. Based on our findings, we propose Purify++, a new diffusion
purification algorithm that is now the state-of-the-art purification method
against several adversarial attacks. Our work presents a systematic exploration
of the limits of diffusion purification methods
Enhancing Adversarial Robustness via Score-Based Optimization
Adversarial attacks have the potential to mislead deep neural network
classifiers by introducing slight perturbations. Developing algorithms that can
mitigate the effects of these attacks is crucial for ensuring the safe use of
artificial intelligence. Recent studies have suggested that score-based
diffusion models are effective in adversarial defenses. However, existing
diffusion-based defenses rely on the sequential simulation of the reversed
stochastic differential equations of diffusion models, which are
computationally inefficient and yield suboptimal results. In this paper, we
introduce a novel adversarial defense scheme named ScoreOpt, which optimizes
adversarial samples at test-time, towards original clean data in the direction
guided by score-based priors. We conduct comprehensive experiments on multiple
datasets, including CIFAR10, CIFAR100 and ImageNet. Our experimental results
demonstrate that our approach outperforms existing adversarial defenses in
terms of both robustness performance and inference speed
Mutual effects between Pinus armandii and broadleaf litter during mixed decomposition
Mixed-decomposition effects are commonly observed in natural and planted forests and affect nutrient cycling in a forest ecosystem. However, how one litter type affects the decomposition of another is still poorly understood. In this study, Pinus armandii litter was mixed with Betula albosinensis, Catalpa fargesii, Populus purdomii, Eucommia ulmoides, and Acer tsinglingense litter. The mixtures were placed in litterbags and buried in soil with consistent moisture for a 180-day indoor simulated decomposition experiment. The litterbags were periodically harvested during decomposition; the litter residues of different species were separated, and the biomass dynamics of each litter type were simulated. In addition, the soil sucrase, cellulase and polyphenol oxidase activities were also detected three times. The mutual effects of needle and broadleaf litter during mixed decomposition and the possible underlying mechanisms were investigated. The results indicated that (i) during the decomposition experiment, P. armandii needles significantly inhibited the decomposition of broadleaf litter in the first 3 months, while the broadleaf litter accelerated the decomposition of P. armandii needles in only approximately 40% of the cases. However, the inhibitory effects of needles on broadleaf litter decomposition subsequently exhibited significant weakening, while the accelerating effects of broadleaf litter were significantly enhanced. The effects of mixed decomposition on the activities of three enzymes can only partially explain the interactions between different litter types; (ii) the prediction by the decomposition model showed that most of the broadleaf litter types could continuously accelerate the decomposition of P. armandii needles throughout the mixed decomposition process, while the decomposition of broadleaf litter would be significantly inhibited at least in the short term. In general, four of the five broadleaf litter types (excluding E. ulmoides) could accelerate the early decomposition of P. armandii needles and consequently accelerate nutrient cycling in P. armandii pure forests. These species could be used for the transformation of pure P. armandii pure forests to mixed forests
Effect of Copper Vapor on Radiation Properties of C4F7N Gas Mixtures
C4F7N and its mixture with buffer gases are regarded as the most promising SF6-alternative gases in gas circuit breakers. The switching arc can severely ablate the electrodes, producing copper metal vapor that combine with the C4F7N gas mixture to chang radiation characteristics. This paper compares the net emission coefficient of C4F7N mixtures at various mixing ratios and assesses the effect of 20% copper vapor. It is found that adding copper vapor can greatly enhance radiation
Holographic Integrated Sensing and Communications: Principles, Technology, and Implementation
Integrated sensing and communication (ISAC) has attracted much attention as a
promising approach to alleviate spectrum congestion. However, traditional ISAC
systems rely on phased arrays to provide high spatial diversity, where enormous
power-consuming components such as phase shifters are used, leading to the high
power consumption of the system. In this article, we introduce holographic
ISAC, a new paradigm to enable high spatial diversity with low power
consumption by using reconfigurable holographic surfaces (RHSs), which is an
innovative type of planar antenna with densely deployed metamaterial elements.
We first introduce the hardware structure and working principle of the RHS and
then propose a novel holographic beamforming scheme for ISAC. Moreover, we
build an RHS-enabled hardware prototype for ISAC and evaluate the system
performance in the built prototype. Simulation and experimental results verify
the feasibility of holographic ISAC and reveal the great potential of the RHS
for reducing power consumption. Furthermore, future research directions and key
challenges related to holographic ISAC are discussed
Recovery of Dairy Aroma Compounds and Concentration of Dairy Solutions by Membranes
This study explores the potential of using different types of poly(ether block amide) (PEBA) membranes for recovering aroma compounds from dairy solutions and concentration of dairy products by membrane processes.
The selective recovery of eight aroma compounds from their binary and multicomponent aqueous solutions by pervaporation using PEBA 2533 membrane was studied. This membrane was proved to be effective for recovering not only hydrophobic aroma compounds but also hydrophilic ones, which were not easy to be enriched by other organophilic PV membranes. The effects of feed concentration and temperature on aroma recovery were also investigated. In addition, the coupling effect among aroma species was found to be significant in multicomponent aroma system, even if the aroma concentrations in feed were low.
The performance of PEBA 2533 for recovering aromas by batch pervaporation was evaluated, and the experimental data were analyzed with a batch pervaporation model. The maximum amounts of almost pure aroma compounds obtained in the permeate during the process were predicted. The effects of initial feed amount and membrane area on the recovery of aroma compounds from their aqueous feed solution were also simulated, and a large membrane area and/or a small initial amount of feed solution were found to be favorable to for a good aroma recovery.
Four non-volatile dairy components, that is NaCl, lactose, whey protein and milk fat, were confirmed to influence the recovery of aroma compounds from their aqueous solutions. It was found that the permeation of hydrophobic aroma could be enhanced by the presence of NaCl in the feed, but reduced by the presence of lactose, protein, and fat in the feed.
PEBA 1074 membrane for pervaporative concentration of dairy solutions was investigated by comparing the performance of PEBA 1074 with that of representative ultrafiltration, nanofiltration and reverse osmosis membranes. The PEBA 1074 membrane showed a high water permeance and a low flux decline with time during the operations. A high milk solid retention (almost 100%) was obtained, and the membrane was easily cleaned. The effects of feed solid content and transmembrane pressure on membrane filtrations were revealed using the resistance-in-series model. At a higher feed solid content and transmembrane pressure, the resistance of membrane fouling was higher, which lead to a more rapid flux decline
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