Mobile Networks and Applications - Inverse kinematics is an important basic theory in walking control of biped robot. This study focuses on the parameter setting using the improved algorithm in... 相似文献
Surface passivation treatment is a widely used strategy to resolve trap-mediated nonradiative recombination toward high-efficiency metal-halide perovskite photovoltaics. However, a lack of passivation with mixture treatment has been investigated, as well as an in-depth understanding of its passivation mechanism. Here, a systematic study on a mixed-salt passivation strategy of formamidinium bromide (FABr) coupled with different F-substituted alkyl lengths of ammonium iodide is demonstrated. It is obtained better device performance with decreasing chain length of the F-substituted alkyl ammonium iodide in the presence of FABr. Moreover, they unraveled a synergistic passivation mechanism of the mixed-salt treatment through surface reconstruction engineering, where FABr dominates the reformation of the perovskite surface via reacting with the excess PbI2. Meanwhile, ammonium iodide passivates the perovskite grain boundaries both on the surface and top perovskite bulk through penetration. This synergistic passivation engineer results in a high-quality perovskite surface with fewer defects and suppressed ion migration, leading to a champion efficiency of 23.5% with mixed-salt treatment. In addition, the introduction of the moisture resisted F-substituted groups presents a more hydrophobic perovskite surface, thus enabling the decorated devices with excellent long-term stability under a high humid atmosphere as well as operational conditions. 相似文献
The design of highly stable and efficient porous materials is essential for developing breakthrough hydrocarbon separation methods based on physisorption to replace currently used energy-intensive distillation/absorption technologies. Efforts to develop advanced porous materials such as zeolites, coordination frameworks, and organic polymers have met with limited success. Here, a new class of ionic ultramicroporous polymers (IUPs) with high-density inorganic anions and narrowly distributed ultramicroporosity is reported, which are synthesized by a facile free-radical polymerization using branched and amphiphilic ionic compounds as reactive monomers. A covalent and ionic dual-crosslinking strategy is proposed to manipulate the pore structure of amorphous polymers at the ultramicroporous scale. The IUPs exhibit exceptional selectivity (286.1–474.4) for separating acetylene from ethylene along with high thermal and water stability, collaboratively demonstrated by gas adsorption isotherms and experimental breakthrough curves. Modeling studies unveil the specific binding sites for acetylene capture as well as the interconnected ultramicroporosity for size sieving. The porosity-engineering protocol used in this work can also be extended to the design of other ultramicroporous materials for the challenging separation of other key gas constituents. 相似文献
Traffic sign recognition and lane detection play an important role in traffic flow planning, avoiding traffic accidents, and alleviating traffic chaos. At present, the traffic intelligent recognition rate still needs to be improved. In view of this, based on the neural network algorithm, this study constructs an intelligent transportation system based on neural network algorithm, and combines machine vision technology to carry out intelligent monitoring and intelligent diagnosis of traffic system. In addition, this study discusses in detail the core of the monitoring system: multi-target tracking algorithm, and introduces the complete implementation process and details of the system, and highlights the implementation and tracking effect of the multi-target tracker. Finally, this study uses case identification to analyze the effectiveness of the algorithm proposed by this paper. The research results show that the proposed method has certain practical effects and can be used as a reference for subsequent system construction.
The decision making trial and evaluation laboratory (DEMATEL) method is a useful tool for analyzing correlations among factors
using crisp values. However, the crisp values are inadequate to model real-life situations due to the fuzziness and uncertainty
that are frequently involved in judgments of experts. The aim of this paper is to extend the DEMATEL method to an uncertain
linguistic environment. In this paper, the correlation information among factors provided by experts is in the form of uncertain
linguistic terms. A formula is first presented to transform correlation information from uncertain linguistic terms to trapezoidal
fuzzy numbers. Then, we aggregate the transformed correlation information of each expert into group information using the
operations of trapezoidal fuzzy numbers. The importance and classification of factors are determined via fuzzy matrix operations.
Furthermore, a causal diagram is constructed to vividly show the different roles of factors. Finally, an example is used to
illustrate the procedure of the proposed method. 相似文献
The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 m resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5 satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of China. 相似文献