In order to achieve effective noise absorption by finite thickness fiber-based materials, fiber-based composites integrating porous, resonant and damping structures were prepared in this research. Here, the effects of...
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In order to achieve effective noise absorption by finite thickness fiber-based materials, fiber-based composites integrating porous, resonant and damping structures were prepared in this research. Here, the effects of gradient structure, number of constituent units, nonwovens thickness and micro-perforated membrane fabric (MPMF) arrangement on the noise reduction of the composites were simulated and measured. The results showed that the gradient fiber-based composite has excellent broadband sound absorption effect. Moreover, designing the arrangement of micro-perforated structures in the composite can further improve its noise reduction coefficient (NRC). The fiber-based composite (thickness of 1.34 cm) designed by the algorithm has an NRC of 0.51, which is much higher than other noise reduction products with the same thickness. The multi-layer fiber-based composites have the advantages of strong noise reduction capability, small thickness, simple processing and low manufacturing cost, which can be flexibly applied in various noise reduction fields.
The Chang'e-5 (CE-5) mission marks China's first lunar sample return endeavor, with its landing site (43.06 degrees N, 51.92 degrees W) situated in the Mons Rumker region of the northern Oceanus Procellarum on...
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The Chang'e-5 (CE-5) mission marks China's first lunar sample return endeavor, with its landing site (43.06 degrees N, 51.92 degrees W) situated in the Mons Rumker region of the northern Oceanus Procellarum on the Moon. This region hosts some of the youngest mare basalts of the Moon and contains a relatively youthful geologic unit characterized by crater's equilibrium diameters slightly over 100 m. By refining the Faster Region-based Convolutional Neural Network (Faster R-CNN) algorithm and leveraging high-resolution imagery to create training samples, accurate identification of lunar craters can be achieved. In this study, we enhance the algorithm in aspects such as anchor boxes and Region of Interest alignment. Additionally, we have utilized high-resolution images for training, and identify and statistics craters within the CE-5 landing area. Ultimately, our model attains a validation set Recall of 90%, Precision of 69%, and an Average Precision score of 0.83. Notably, in certain scales, such as for the crater larger than 400 m, recognition results reach Precision of 88% and Recall of 89%. The findings of this study are mapped into a crater catalog. Furthermore, we predict crater density and integrate it with geochronological functions to estimate the absolute model age of nine major geologic units within the CE-5 landing area. The results are generally in agreement with those of other studies who have used manual methods for crater counting, and verify the correctness of our automatic crater identification results.
In recent years, with the increasing demand for security, intelligent video surveillance system has become more and more widely used in national security, intelligent transportation, social life and other fields Among...
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In recent years, with the increasing demand for security, intelligent video surveillance system has become more and more widely used in national security, intelligent transportation, social life and other fields Among them, the detection and tracking of moving targets are the key points and difficult parts in the intelligent video surveillance system, which mainly involves in the related knowledge of pattern recognition, image processing and intelligent control and other fields, and is also the basis of subsequent steps such as target analysis and processing. In the detection and tracking of moving targets, the existing algorithms can not adapt to the changes of the external environment. Therefore, it is necessary to study an algorithm, which is robust and not afraid of complex background environment. In this paper, the detection and tracking algorithms of moving objects in complex scenes are studied comprehensively and in detail, and the existing algorithms are improved to solve the tracking problem and make some progress.
Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-...
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Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics.
S-boxes, the key nonlinear component in numerous cryptographic systems, play a crucial role in ensuring security. The quest for random highly nonlinear S-boxes, a desirable attribute for better diffusion and confusion...
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S-boxes, the key nonlinear component in numerous cryptographic systems, play a crucial role in ensuring security. The quest for random highly nonlinear S-boxes, a desirable attribute for better diffusion and confusion properties, is, therefore, a critical endeavor in cryptographic research. However, generating such nonlinear S-boxes often involves significant computational effort, presenting a major challenge for researchers. This paper addresses this gap by proposing an optimized version of the Simulated Annealing (SA) algorithm specifically tailored for efficient generation of highly nonlinear S-boxes. Our work introduces a multithreaded implementation of the SA algorithm, a heuristic search method known for its proficiency in combinatorial optimization. The multithreading feature enhances computational efficiency, making our approach more suitable for large-scale cryptographic applications. We further optimize the algorithm by incorporating additional exit criteria for both internal and external loops, which significantly reduces the computational complexity associated with the nonlinear substitution generation process. Furthermore, we undertake comprehensive experiments to identify the optimal parameters of the SA algorithm, aiming to maximize the probability of generating target S-boxes while minimizing the number of iterations. This optimization step provides a clear pathway to improve the success rate of the generation process. The results of our study demonstrate a significant improvement over previous works, showing a 30-40% enhancement in the generation of nonlinear S-boxes.
Nowadays, rod pump is widely used in oilfield. Since most oil production equipment like pumping pumps are distributed in the wild, they are usually checked by manual inspection. In the event of a faults, relying solel...
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Nowadays, rod pump is widely used in oilfield. Since most oil production equipment like pumping pumps are distributed in the wild, they are usually checked by manual inspection. In the event of a faults, relying solely on labor to observe the indicator diagrams and determine the fault will waste a lot of human and financial resources. If it is not discovered in time, it will cause serious damage to oil exploitation, even shutdown. Indicator diagrams can reflect the working state of the rod pumping well, which can effectively reflect various faults of the pumping well. This paper diagnoses the faults of pumping wells by classifying and identifying the indicator diagrams. Because support vector machine (SVM) has good effect on classification and recognition of small sample data and nonlinear data, this paper uses SVM for classification, and uses the chicken swarm optimization (CSO) to optimize support for the problem that the SVM parameters are difficult to determine. Aiming at the problems of traditional CSO in solving high-dimensional optimization problems, such as premature and rough precision, an improved CSO is proposed. The traditional CSO, particle swarm optimization (PSO) and bat algorithm (BA) are used to compare it. The simulation proves that the improved CSO has good optimization effect and is superior to the other three optimizationalgorithms.
Covariant residues identified by computational algorithms have provided new insights into enzyme evolutionary routes. However, the reliability and accuracy of routine statistical coupling analysis (SCA) are unable to ...
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Covariant residues identified by computational algorithms have provided new insights into enzyme evolutionary routes. However, the reliability and accuracy of routine statistical coupling analysis (SCA) are unable to satisfy the needs of protein engineering because SCA depends only on sequence information. Here, we set up a new SCA algorithm, ***, by integrating structure information and MD simulation data. The more reliable covariant residues with high-quality scores are obtained from sequence alignment weighted by residual movement for eight related subfamilies, belonging to alpha/beta hydrolase family, with Candida antarctica lipase B (CALB). The 38 predicted covariant residues are tested for function by high-throughput quantitative evaluation in combination with activity and thermostability assays of a mutant library and deep sequencing. Based on the landscapes of both activity and thermostability, most mutants play key roles in catalysis, and some mutants gain 2.4- to 6-fold increase in half-life at 50 degrees C and 9- to 12-fold improvement in catalytic efficiency. The activity of double mutants for A225F/T103A is higher than those of A225F and T103A which means that *** method might be useful for identifying the allosteric coupling. The *** algorithm can be used for protein coevolution and enzyme engineering research.
Aiming at the problem of large vibration of a high-subside stator inner cavity curve vane pump, the force analysis of the vane at the transition curve is carried out, and the functional relationship between the vane t...
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Aiming at the problem of large vibration of a high-subside stator inner cavity curve vane pump, the force analysis of the vane at the transition curve is carried out, and the functional relationship between the vane turning angle theta, the large arc radius R, the small arc radius r and the sliding friction is established. The particle swarm algorithm is used to optimize the solution of the objective function, and the optimized parameter values are brought into the MATLAB simulation program to obtain the optimized stator curve profile diagram. The dynamic performance of the vane pump before and after optimization is simulated using ADAMS. The results show that: the acceleration of the vane pump slide is significantly reduced;the friction between the slide and the slide groove is significantly reduced;the contact force between the slide and the stator is significantly reduced;the impact vibration of the optimized vane pump is significantly reduced;and the dynamic performance of the vane pump is improved.
Due to the lack of a perfect and convenient method to detect the grouting quality of shield tunnels, an optimized ultrasonic phased array tunnel grouting detection technology is proposed. The particle swarm genetic al...
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Due to the lack of a perfect and convenient method to detect the grouting quality of shield tunnels, an optimized ultrasonic phased array tunnel grouting detection technology is proposed. The particle swarm genetic algorithm is optimized to be used for phased array sparse, and the GA-VMD-SG algorithm is proposed to be used for noise reduction of ultrasonic detection signals, and numerical simulation and experimental methods are used to validate the optimized detection effect of the ultrasonic phased array. The results show that: the GA-PSO algorithm can better simplify the array and reduce the maximum sidelobe value;the GA-VMD-SG algorithm can well reduce the noise of ultrasonic signals;numerical simulation and experiments verify the feasibility of the ultrasonic phased array to detect the quality of grouting and the optimization effect of the two algorithms.
An improved genetic K-means clustering algorithm is proposed and is applied to image segmentation. According to the characteristics of the image, the feature vector of the pixel is properly chosen and the weight facto...
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ISBN:
(纸本)9780769535579
An improved genetic K-means clustering algorithm is proposed and is applied to image segmentation. According to the characteristics of the image, the feature vector of the pixel is properly chosen and the weight factors of the feature vector are adjusted, which enhances the segmentation precision. The selection of conventional genetic algorithm and the modification of mutation operations improve the speed of convergence. Computing time is reduced due to combining the membership matrix with the coding of chromosomes skillfully. The results of the experiments demonstrate that in the image segmentation the proposed algorithm is better than traditional genetic K-means algorithm.
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