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This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa. 相似文献
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为研究金针菇多糖(polysaccharide from Flammulina velutipes,FVP)对微冻大黄鱼及鱼片在贮藏期间肌原纤维蛋白性质的变化及水分分布的影响,实验分别选用0.03、0.06、0.09 g/L FVP浸渍处理大黄鱼和鱼片,以无菌水处理为对照组,分析微冻贮藏期间样品的感官指标得分、总挥发性盐基氮含量、总巯基含量、Ca2+-ATPase活性、蛋白流变学性质以及水分迁移变化规律。结果表明:FVP可有效抑制整鱼总挥发性盐基氮含量上升和感官得分的下降;减缓整鱼及鱼片在微冻过程中总巯基含量、Ca2+-ATPase活性下降和水分流失;此外FVP还能够延缓大黄鱼因腐败而出现的蛋白凝胶能力减弱。在本实验选取的多糖浓度范围内,0.09 g/L FVP处理组保鲜效果较强。该研究结果可为FVP用于水产品贮运保鲜提供理论参考。 相似文献
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Yujie Chen Yiping Song Zhen Zhang Yali Chen Qiliang Deng Shuo Wang 《Advanced functional materials》2021,31(41):2104885
Various products, including foods and pharmaceuticals, are sensitive to temperature fluctuations. Thus, temperature monitoring during production, transportation, and storage is critical. Facile indicators are required to monitor temperature conditions via color changes in real time. This study aimed to prepare and apply thiol-functionalized covalent organic frameworks (COFs) as a novel indicator for monitoring thermal history and temperature abuse. The COFs underwent obvious color changes from bright yellow to purple after exposure to different temperatures for varying durations. The reaction kinetics are analyzed under isothermal conditions, which reveal that the order of reaction rates is k−20°C < k4°C < k20°C < k35°C < k55°C. The activation energy (Ea) of the COFs is calculated using the Arrhenius equation as 50.71 kJ moL−1. The COFs are capable of sensitive color changes and offer a broad temperature tracking range, thereby demonstrating their application potential for the monitoring of temperature and time exposure history during production, transportation, and storage. This excellent performance thermal history indicator also shows promise for expanding the application field of COFs. 相似文献
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AbstractDifferent drying methods (spray drying (SD), vacuum drying (VD), microwave vacuum drying (MVD), and infrared vacuum drying (IFVD)) were applied in order to compare the hygroscopicity behavior of chicken powders. The hygroscopicity curves and glass transition temperature were used to evaluate the influence of ambient humidity and temperature on moisture absorption of powders. The results showed that the chicken powder dried by MVD had the lowest moisture absorption, followed by IFVD, VD, and SD. The hygroscopicity of SD chicken powders was different from other three kinds of chicken powders due to the physical properties of particles and the changes of protein secondary structure as detected by the Fourier transform-infrared spectrometer. For the three vacuum drying methods, the difference of protein secondary structure was the main reason of differences in hygroscopicity. Although MVD chicken powders were slightly inferior to SD chicken powders in taste, MVD chicken powders were the best in terms of smell and color as suggested by instrumental sensory parameter evaluations. It was found that MVD had a positive effect on reducing moisture absorption and maintaining sensory quality of chicken powders. 相似文献
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This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development. 相似文献