To achieve the dual demand of resisting violent impact and attenuating vibration in vibration-impact-safety of protection for precision equipment such as MEMS packaging system, a theo- retical mathematical model of mu...To achieve the dual demand of resisting violent impact and attenuating vibration in vibration-impact-safety of protection for precision equipment such as MEMS packaging system, a theo- retical mathematical model of multi-medium coupling shock absorber is presented. The coupling of quadratic damping, linear damping, Coulomb damping and nonlinear spring are considered in the model. The approximate theoretical calculating formulae are deduced by introducing transformation-tactics. The contrasts between the analytical results and numerical integration results are developed. The resisting impact characteristics of the model are also analyzed in progress. In the meantime, the optimum model of the parameters matching selection for design of the shock absorber is built. The example design is illustrated to confirm the validity of the modeling method and the theoretical solution.展开更多
The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which ...The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which is crucial for enhancing aircraft positioning accuracy.Traditional methods for image matchability analysis are often limited by their reliance on manual feature parameter design and threshold-based filtering,resulting in suboptimal accuracy and efficiency.This paper proposes a novel network architecture for selecting suitable navigation areas using image Matching Level Segmentation(MLSNet).The approach involves two key innovations:a method for generating segmentation labels that quantify matchability levels and an end-to-end network architecture for rapid and precise prediction of reference image matchability segmentation maps.The network includes two core modules:the saliency analysis module uses multi-layer convolutional networks to accurately detect image saliency features across various levels and scales;the multidimensional attention module utilizes attention mechanisms to focus on feature channels and spatial neighborhood scenes to assess the image’s matchability.Our method was rigorously tested on an extensive collection of remote sensing images,where it was benchmarked against a range of both traditional and cutting-edge deep learning methods.The findings indicate that MLSNet is significantly superior to traditional methods in accuracy and efficiency of matchability analysis,and is also relatively ahead of state-of-the-art deep learning models.展开更多
Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving...Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.展开更多
基金This project is supported by National Defense Science Foundation of China (No.00J16.2.5.DZ0502)Foundation for Qualified Personnel of Jiangsu University, China(No.04JDG027)Provincial Natural Science Foundation of Guangxi. China(No.0339037, No.0141042).
文摘To achieve the dual demand of resisting violent impact and attenuating vibration in vibration-impact-safety of protection for precision equipment such as MEMS packaging system, a theo- retical mathematical model of multi-medium coupling shock absorber is presented. The coupling of quadratic damping, linear damping, Coulomb damping and nonlinear spring are considered in the model. The approximate theoretical calculating formulae are deduced by introducing transformation-tactics. The contrasts between the analytical results and numerical integration results are developed. The resisting impact characteristics of the model are also analyzed in progress. In the meantime, the optimum model of the parameters matching selection for design of the shock absorber is built. The example design is illustrated to confirm the validity of the modeling method and the theoretical solution.
基金supported in part by the National Natural Science Foundation of China(No.42271446)in part by the Tianjin Key Laboratory of Rail Transit Navigation Positioning and Spatio-Temporary Big Data Technology,China(No.TKL2024B13)in part by the Science and Technology Program of Tianjin,China(No.24YFYSHZ00080)。
文摘The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which is crucial for enhancing aircraft positioning accuracy.Traditional methods for image matchability analysis are often limited by their reliance on manual feature parameter design and threshold-based filtering,resulting in suboptimal accuracy and efficiency.This paper proposes a novel network architecture for selecting suitable navigation areas using image Matching Level Segmentation(MLSNet).The approach involves two key innovations:a method for generating segmentation labels that quantify matchability levels and an end-to-end network architecture for rapid and precise prediction of reference image matchability segmentation maps.The network includes two core modules:the saliency analysis module uses multi-layer convolutional networks to accurately detect image saliency features across various levels and scales;the multidimensional attention module utilizes attention mechanisms to focus on feature channels and spatial neighborhood scenes to assess the image’s matchability.Our method was rigorously tested on an extensive collection of remote sensing images,where it was benchmarked against a range of both traditional and cutting-edge deep learning methods.The findings indicate that MLSNet is significantly superior to traditional methods in accuracy and efficiency of matchability analysis,and is also relatively ahead of state-of-the-art deep learning models.
基金financially supported by the Fundamental Research Funds for the Central Universities Nos.DL12EB01-03the planning subject of "the Twelfth Five-Year-Plan" in National Science and Technology Nos.2012AA102003-2Heilongjiang Natural Science Fund in China Nos.F201116
文摘Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.
