39 research outputs found

    Analysis of a Class of Fractional Nonlinear Multidelay Differential Systems

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    We address existence and Ulam-Hyers and Ulam-Hyers-Mittag-Leffler stability of fractional nonlinear multiple time-delays systems with respect to two parameters’ weighted norm, which provides a foundation to study iterative learning control problem for this system. Secondly, we design PID-type learning laws to generate sequences of output trajectories to tracking the desired trajectory. Two numerical examples are used to illustrate the theoretical results

    Hyers-Ulam Stability and Existence of Solutions for Nigmatullin’s Fractional Diffusion Equation

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    We discuss stability of time-fractional order heat conduction equations and prove the Hyers-Ulam and generalized Hyers-Ulam-Rassias stability of time-fractional order heat conduction equations via fractional Green function involving Wright function. In addition, an interesting existence result for solution is given

    Sample Imbalance Adjustment and Similar Object Exclusion in Underwater Object Tracking

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    Although modern trackers exhibit competitive performance for underwater image degradation assessment, two problems remain when these are applied to underwater object tracking (UOT). A single-object tracker is trained on open-air datasets, which results in a serious sample imbalance between underwater objects and open-air objects when it is applied to UOT. Moreover, underwater targets such as fish and dolphins usually have a similar appearance, and it is challenging for models to discriminate weak discriminative features. Existing detection-based post-processing approaches struggle to distinguish a tracked target from similar objects. In this study, the UOSTrack is proposed, which involves the use of underwater images and open-air sequence hybrid training (UOHT), and motion-based post-processing (MBPP). The UOHT training paradigm is designed to train the sample-imbalanced underwater tracker. In particular, underwater object detection (UOD) images are converted into image pairs through customised data augmentation, such that the tracker is exposed to more underwater domain training samples and learns the feature expressions of underwater objects. The MBPP paradigm is proposed to exclude similar objects near the target. In particular, it employs the estimation box predicted using a Kalman filter and the candidate boxes in each frame to reconfirm the tracked target that is hidden in the candidate area when it has been lost. UOSTrack provides an average performance improvement of 3.5 % compared to OSTrack on similar object challenge attribute in UOT100 and UTB180. The average performance improvements provided by UOSTrack are 1 % and 3 %, respectively. The results from two UOT benchmarks demonstrate that UOSTrack sets a new state-of-the-art benchmark, and the effectiveness of UOHT and MBPP, and the generalisation and applicability of the MBPP for use in UOT

    UnitModule: A Lightweight Joint Image Enhancement Module for Underwater Object Detection

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    Underwater object detection faces the problem of underwater image degradation, which affects the performance of the detector. Underwater object detection methods based on noise reduction and image enhancement usually do not provide images preferred by the detector or require additional datasets. In this paper, we propose a plug-and-play Underwater joint image enhancement Module (UnitModule) that provides the input image preferred by the detector. We design an unsupervised learning loss for the joint training of UnitModule with the detector without additional datasets to improve the interaction between UnitModule and the detector. Furthermore, a color cast predictor with the assisting color cast loss and a data augmentation called Underwater Color Random Transfer (UCRT) are designed to improve the performance of UnitModule on underwater images with different color casts. Extensive experiments are conducted on DUO for different object detection models, where UnitModule achieves the highest performance improvement of 2.6 AP for YOLOv5-S and gains the improvement of 3.3 AP on the brand-new test set (URPCtest). And UnitModule significantly improves the performance of all object detection models we test, especially for models with a small number of parameters. In addition, UnitModule with a small number of parameters of 31K has little effect on the inference speed of the original object detection model. Our quantitative and visual analysis also demonstrates the effectiveness of UnitModule in enhancing the input image and improving the perception ability of the detector for object features

    Synthesis of Ultra High Molecular Weight HPAM and Viscosity Forecast by BP Neural Network

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    Hydrolyzed polyacrylamide (HPAM) is widely used to increase the sweep efficiency of water phase in oil reservoirs. It is very important to select proper polymer for the reservoirs. In this study, a series of ultra high molecular weight HPAMs were synthesized and characterized by FT-IR analysis. Their physical properties were tested under reservoir condition. BP neural network (BPNN) was employed to forecast the viscosity of high molecular weight HPAM in produced water. The input indices including molecular weight, solid content, degree of hydrolysis, water-insoluble residue, polymer concentration, temperature of reservoir and salinity of produced water. The results show that all physical properties fulfill the requirements of Q/SY DQ1059-2005. This BPNN can predict the viscosity of ultra high molecular weight HPAM accurately. It is proposed that this BPNN can be used to screen proper polymers for enhance oil recovery.DOI: http://dx.doi.org/10.5755/j01.ms.21.4.9698</p

    Hierarchical Structure, Gelatinization, and Digestion Characteristics of Starch from Longan (<em>Dimocarpus longan</em> Lour.) Seeds

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    Starch was isolated from longan seeds of three widely distributed cultivars (Chuliang, Shixia, and Caopu) in China. Comparisons of the multi-level structure of the starch of longan seeds among various cultivars were made, and the relations between these structural and property characteristics are discussed. The isolated starch, accounting for 44.9–49.5% (w/w) in longan seeds, had an oval or an irregular polygonal shape with a smooth surface. Their chain-length distributions (CLDs) varied with longan cultivar; Chuliang showed a larger proportion of longer amylopectin chains with a degree of polymerization (DP) 30~100. This is attributed to the slightly higher relative crystallinity of Chuliang longan seed starch. Apparent differences were also detected in amylose structure. Caopu showed a higher amylose content than Chuliang and Shixia, resulting in its lower gelatinization temperatures and enthalpy change. All longan seed starch had a typical A-type crystal structure with relative crystallinity ranging 28.6–28.9%. For raw starch, Caopu showed the lowest digestion rate, followed by Chuliang; Shixia showed the highest. This is because Caopu had the highest amylose content. Chuliang had a more intact structure than Shixia, as suggested by its higher crystallinity, although they had similar amylose content. After being fully gelatinized, all starch showed a similar digestion process, indicating that the digestibility of gelatinized starch does not differ with starch source or structure

    Characterization and Prebiotic Potential of Longan Juice Obtained by Enzymatic Conversion of Constituent Sucrose into Fructo-Oligosaccharides

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    The prebiotic potential of longan juice obtained by a commercial Viscozyme L for conversion of constituent sucrose to fructo-oligosaccharide was investigated. The physicochemical properties and carbohydrate composition of the longan juice was evaluated before and after enzymatic treatment. The stimulation effects of the treated longan juice on probiotic bacteria growth were also studied in vitro. The results showed that total soluble solids, yield and clarity of longan juice were all significantly improved after enzyme treatment. The water-soluble polysaccharide content, including pectin, was significantly increased. Compared with the natural longan pulp, the enzyme treated juice showed a significant decrease in sucrose content. Substantial fructo-oligosaccharides including 1-kestose and nystose were synthesized after enzyme treatment. The molecular weight distribution and the monosaccharide composition of the water-soluble polysaccharide were significantly changed by enzyme treatment. The treated longan juice and its ethanol-soluble sugar fraction promoted the growth of Streptococus thermophiles, Lactobacillus acidophilus and Lactobacillus delbrueckii, showing a good potential of the treated longan juice for producing functional foods and nutraceuticals
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