Path planning is a great challenge in the autonomous navigation of mobile robots. The Rapidly-exploring Random Tree* (RRT*) algorithm is widely used for its probabilistic completeness. In the literature, improved RRT*-based algorithms usually enhance search efficiency through different target bias strategies. However, these algorithms often fall into obstacle traps in complex environments with narrow passages or high obstacle densities due to the local minima problem in the optimization process. In addition, the existing algorithms also exhibit inefficient sampling and slow convergence in large-scale maps. To tackle with these problems, we propose an improved algorithm, called the RRT*-PRIME (Probabilistically Interpreted Mechanisms Enhanced RRT*) algorithm, in this paper. First, a powerful strategy, called the P-HOPE (Probability-Driven Heuristic Optimization for Path Exploration) strategy, that integrates multidimensional influencing factors is designed in the proposed RRT*-PRIME algorithm to optimize target sampling direction by considering angle, direction consistency, and obstacle distribution. Second, a flexible mechanism FLEX-OPT is developed to adaptively and dynamically adjust the search strategy through real-time feedback and monitoring of the cost function to tackle the above-mentioned local minima problem, which significantly improves the convergence speed and path quality of the algorithm. The experimental results suggest that the proposed RRT*-PRIME algorithm can reduce the initial solution search time by 76.32%, reduce the number of search nodes by about 80.67%, and improve the search path quality compared with the RRT* algorithm. In both narrow complex and large-scale map environments, the RRT*-PRIME algorithm significantly outperforms the RRT*, Informed-RRT*, h-RRT*, and PF-RRT* algorithms in terms of reliability and efficiency. In future, the RRT*-PRIME algorithm is expected to be extended to more applications based on target bias search, providing a highly flexible and adaptable solution for efficient path planning of UAVs and mobile robots.
Urbanization greatly contributes to the industrialization process and economic growth of a country or region, while excessive urbanization harms the development of national economy. Therefore, moderate urbanization and the determination of optimal city scale have been spotlighted. Based on literature review on determining criteria of optimal city scale, this paper concludes that to maximize urban residents' income is the fundamental criterion for the scale and the level of urbanization in China, which urges make full use of market's function in allocating resources to fuel the free flow of population and factor of production and to develop a city toward the best scale with maximized residents' income.
As the analysis of business efficiency factors, this essay will mainly concentrate on effect from inner and micro factors. Moreover, the essay adopts company scale, proprietorship, human capital, and market share rate as independent variables, and the malmquist index, Technical Change and Efficiency Change as variables to set the model. Then it is found that the employee quality and market share rate is the most significant inner factors of business efficiency and determinate factors for insurance companies.
The paper first analyzes the significance of cultivating core competence of employment of college student under severe employment situation,then describes the composition of core competence of employment of college students of financial university that should include the four dimensions: professional skills,career adaptability and development,team practice and personal qualities.Finally the paper discusses the specific strategies to cultivate and enhance the core competence of employment of college students from the four aspects of the concept of employment,training applied talents,the full process of career counseling and teaching staff.
Parallax processing and structure preservation has long been important and challenging tasks in image stitching. In this paper, an image stitching method based on sliding camera to eliminate perspective deformation and asymmetric optical flow to solve parallax is proposed. By maintaining the viewpoint of two input images in the mosaic non-overlapping area and creating a virtual camera by interpolation in the overlapping area, the viewpoint is gradually transformed from one to another image view-point so as to complete the smooth transition of the two image viewpoints and reduce perspective deformation. Two coarsely aligned warped images are generated with the help of a global projection plane. After that, the optical flow propagation and gradient descent method are used to quickly calculate the bidirectional asymmetric optical flow between the two warped images, and the optical flow-based method is used to further align the two warped images to reduce parallax. In the image blending, the softmax function and registration error are used to adjust the width of the blending area, further eliminating ghosting and reduce parallax. Finally, the comparative experiments show that our method can effectively eliminate perspective deformation, reduce misalignment, and save running time.
Foreign language teaching mode based on event originates from cognitive-function theory which considers form-meaning and form-function as one unit while traditional theory separates them.Typically unfolded teaching way of event mode is firstly to take the text as a whole in order to enable students to understand its rhetoric on macro basis.To grasp the internal semantic structure and analysis of event, we have to make division of it.Teaching model based on event,scientifically,conforms to essential feature of English semantic system and transition of English-Chinese functional system as well.
Developing green and low-carbon agriculture is an important and effective way to promote farmers’ income growth. Given the country’s “dual carbon” goal, the study of the impact of green and low-carbon agriculture on the income of farmers in ethnic minority areas is crucial for China to achieve the goals of socialist modernization and common prosperity. Taking Y Town, Zhijin County, Guizhou Province as an example, this paper uses the OLS regression method to empirically study the impact of green and low-carbon agricultural production methods on the income of farmers in ethnic minority mountainous agricultural areas based on the field survey data of 881 farmers. The regression results indicate that there is a positive correlation between green and low-carbon agricultural production and the household income levels of farmers; adopting green and low-carbon agricultural production technologies can effectively promote the growth of farmers’ household income. In addition, education level, health status, and the new rural social pension insurance have all had a significant effect on the income of rural households, however, due to the difficulty in establishing trust relationships, agricultural service outsourcing has reduced the household income level of farmers. As an example, the land transfer behavior in Y Town has no significant effect on increasing farmers’ incomes. Finally, it is recommended to increase fiscal and financial support as well as effectively enhancing farmers’ policy awareness and perception of green and low-carbon agricultural production technologies by improving farmers’ general trust and institutional trust by strengthening farmers’ agricultural education and skills training while cultivating technology-based farming. At the same time, it is necessary to break the geographical restrictions on land transfer scale and achieve moderate-scale land management while promoting the use and adoption of green and low-carbon agricultural production technologies, thereby improving agricultural production efficiency and product quality, and increasing the sustainable growth of farmers’ income. The main contribution of this study is to expand the research scope of green and low-carbon agriculture to ethnic minorities and mountainous agricultural areas.
In numerous practical applications, particularly in the field of autonomous driving, acquiring annotated datasets that include both images and LiDAR point clouds simultaneously presents significant challenges and incurs substantial costs. To overcome the limitations of limited sample annotations, we propose an innovative weakly supervised learning methodology that utilizes reciprocal knowledge transfer between image detection models and 3D point cloud detection models. To the best of our knowledge, this area has not been explored by prior research teams. Our approach effectively addresses the alignment challenge of diverse modal features from an aerial perspective. Through heatmap prediction, we successfully facilitate knowledge transfer between the image detection and 3D point cloud detection models. Additionally, we conduct extensive experiments to evaluate the performance of our models under different parameters in the domain adaptation process, employing Exponential Moving Average (EMA) progressive learning. Furthermore, we explore the advantages of incorporating regression and prediction fusion heads to enhance weakly supervised learning. Remarkably, our experimental results on the widely accessible KITTI datasets demonstrate that our proposed approach achieves outstanding performance in 3D object detection under weak supervision, surpassing the baseline performance of the original 3D point cloud detection model.
The fundamental aim of development is to promote the well-being of the people's livelihood. China's economy has entered a period of the new normal, and the speed of urbanization is increasing. With the constant improvement of the level of urbanization, China's economy develops rapidly, and the living standards are also continuously improving. Based on the usage of ordinary least square and instrumental variable estimate, and the research sample—Chinese Household Income Project Survey (CHIP) 2009, this paper does a research on effects of urban residents' income growth caused by city scale's expansion. The results show that city scale's expansion plays a significant role in income growth of urban residents from different industries, especially in labor-intensive industry, highly monopolized industry, non-tradable industry, as well as urban residents from secondary industry. In consideration of these findings, this thesis holds that China's urbanization process should be further accelerated, and the development strategy and policies of the large cities should continue to be adhered to in the current and future years.
Combining with the supervision practice of Yijing river Bridge at Yangquan,the paper indicates the quality control in the construction process of the prestressed reinforced concrete box beam,illustrates the control,the process,the tension,the grouting,and the hanging shift of the materials,so as to let supervision personnel have the full recognition of the relative steps and the quality safety supervision.
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