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Abstract: Given the phenomenon those left-behind children are prone to learning disabilities and psychological problems because their parents work outside for a long time. This paper puts forward a design scheme for an educational intervention system for left-behind children with learning disabilities. The plan is to collect and analyze the data on left-behind children's learning status. According to the results of data analysis, it can predict the learning behavior, knowledge, and emotion of left-behind children. Early warning indicators and implementation rules of intervention strategies are designed in advance for the system. When the diagnosis result of left-behind children exceeds the warning index, corresponding intervention measures should be taken to solve the learning disabilities of left-behind children. Through the study of the educational intervention system for left-behind children with learning disabilities, the data on left-behind children's learning situation are collected, analyzed, and designed, and a new educational intervention system of intelligent and interactive learning is constructed.Abstract: Given the phenomenon those left-behind children are prone to learning disabilities and psychological problems because their parents work outside for a long time. This paper puts forward a design scheme for an educational intervention system for left-behind children with learning disabilities. The plan is to collect and analyze the data on left-behi...Learn More
Abstract: Robots can replace people to complete many complex, and repetitive tasks, and can also replace people to work in dangerous and toxic and harmful environments. At present, most of the car cleaning methods are manual cleaning, which is time-consuming and laborious. It is also easy to damage the car surface and dirt will endanger the health of staff. The car cleaning robot can replace people to clean. The structure and cleaning path of the cleaning manipulator have an important impact on the cleaning efficiency. The paper designs the structure of the cleaning manipulator and plans its cleaning path. Firstly, the functions of the studied manipulator are analyzed through investigation; Determine the overall structure of the cleaning manipulator according to the required functions to ensure that the car can be cleaned in all directions; Secondly, carry out detailed structural design for the 6-DOF manipulator, complete the clamping of rags and other cleaning tools through the connecting rod structure, and assemble rollers on both sides of the connecting rod to ensure that the robot can effectively complete the cleaning of the car, and carry out digital 3D modeling; Finally, the cleaning path of the manipulator is planned in the MATLAB environment to ensure the smooth motion of the robot. The digital motion simulation of the manipulator is completed by solving the forward.Abstract: Robots can replace people to complete many complex, and repetitive tasks, and can also replace people to work in dangerous and toxic and harmful environments. At present, most of the car cleaning methods are manual cleaning, which is time-consuming and laborious. It is also easy to damage the car surface and dirt will endanger the health of staff. ...Learn More
Abstract: The performance of human pose estimation network model is gradually improved, and the over-deep network structure brings a large number of parameters and complex calculation. To solve these problems, the FastPose-Lite lightweight human pose estimation network is proposed, which is composed of GSE-ResNet feature extraction network, up-sampling DUC module and CBAM module. The basic GBNK module of GSE-ResNet feature extraction network is composed of Ghost module and SE module. On the one hand, Ghost module is proposed to replace the traditional convolutional module in order to reduce the number of parameters and calculation. On the other hand, in order to keep the performance of the network model unchanged, SE attention mechanism module is introduced. In order to enhance the processing ability of the network model to the feature information in both spatial and channel aspects, CBAM module is introduced into the up-sampling DUC module to reduce the loss in the up-sampling process. The experimental results on the COCO dataset show that the proposed FastPose-Lite reduce the number of parameters and calculation by 51.4% and 50.8% respectively compared with the FastPose network model. Compared with the common popular network models such as SHN, CPN, and SimpleBaseline, the FastPose-Lite network model not only has fewer parameters and computations, but also has higher prediction accuracy.Abstract: The performance of human pose estimation network model is gradually improved, and the over-deep network structure brings a large number of parameters and complex calculation. To solve these problems, the FastPose-Lite lightweight human pose estimation network is proposed, which is composed of GSE-ResNet feature extraction network, up-sampling DUC m...Learn More
Abstract: Three-dimensional spatial geo-fencing is a new application based on location-based services (LBS, Location Based Services), which can provide real-time, three-dimensional location change-based related services to fence associates, and its core is to judge the location relationship between target points and fence area, which can be abstracted as point and space figure location relationship discrimination in geometry and mathematics, i.e., point inclusion problem. At present, the mainstream ray method has singularity problem in boundary judgment, and although many improved algorithms have been proposed, most of them are limited to two-dimensional form, which cannot meet the demand of high-precision position discrimination for complex spatial three-dimensional environment. Therefore, this paper starts from the idea of solving a system of linear equations, transforms the judgment of the position relationship between points and polyhedral fences into the judgment of the position relationship between points and planes, and proposes a new algorithm of 3D geo-fencing based on linear equations, which can quickly and accurately complete the judgment of the position relationship between target points and fences. Firstly, the complex polyhedral fence is pre-processed and formed into a binary tree by combining the idea of convex dissection and BSP tree technology; secondly, the target point is recursively queried to be located in the binary tree and the sub-convex polyhedral fence data is obtained; finally, the linear equation algorithm is used to judge the point inclusion between the target point and the sub-convex polyhedron. Experimental results show that the new linear equation algorithm is 40%-48.49% more efficient in convex polyhedral fence position discrimination and 12.5%-20% more efficient in simple nonconvex polyhedral fences compared with the improved ray method.Abstract: Three-dimensional spatial geo-fencing is a new application based on location-based services (LBS, Location Based Services), which can provide real-time, three-dimensional location change-based related services to fence associates, and its core is to judge the location relationship between target points and fence area, which can be abstracted as poi...Learn More
Abstract: NAT (Network Address Translator) technology solves the problem of IP address shortage, but this technology can prevent P2P (Peer-to-Peer) communication between hosts. NAT penetration is the technical means to find a way to allow external datagrams to pass through the NAT device according to the mapping rules of the device, thus establishing a stable P2P connection. In order to ensure that the nodes in a P2P network complete high-quality communication, this paper investigates the entire P2P communication process and proposes an optimisation strategy based on STUN (Simple Traversal of UDP Through NATs) protocol penetration to address the problems of complex and tedious NAT type detection process and low success rate of the penetration process. By reclassifying NAT types, improving NAT type detection methods, introducing network state detection algorithms and optimising the communication flow, the strategy ensures smooth and high-quality communication between nodes in a P2P network. The experimental results show that the STUN protocol-based NAT penetration strategy proposed in this paper has lower resource consumption, stronger anti-interference capability and higher penetration success rate, avoiding performance bottlenecks in the server and providing high-quality network services for the whole communication process.Abstract: NAT (Network Address Translator) technology solves the problem of IP address shortage, but this technology can prevent P2P (Peer-to-Peer) communication between hosts. NAT penetration is the technical means to find a way to allow external datagrams to pass through the NAT device according to the mapping rules of the device, thus establishing a stabl...Learn More
Abstract: Object detection is a crucial problem in computer vision that involves accurately locating objects in images or videos to identify instances to be detected. It has various applications, including facial detection, intelligent driving assistance, and satellite remote sensing detection. This review aims to aid researchers in quickly comprehending object detection. It covers the concept of object detection algorithms, analyzes the development history of object detection algorithms, and elaborates on the evolution process of object detection algorithms from independent development to combination with deep learning technology. The article divides object detection based on whether anchor boxes are generated during the detection process. It discusses the types of anchor boxes and non-anchor boxes and analyzes the current research status of single-stage and two-stage object detection algorithms. It also summarizes classic model structures in the development process of object detection algorithms and introduces difficulties in object detection. The article aims to solve the problem of object detection with a small number of samples and without detailed annotations during the training process. It summarizes and compares the advantages and disadvantages of various classic models, mainstream datasets, and evaluation indicators. Additionally, it looks forward to current challenges and future development directions in the field of object detection.Abstract: Object detection is a crucial problem in computer vision that involves accurately locating objects in images or videos to identify instances to be detected. It has various applications, including facial detection, intelligent driving assistance, and satellite remote sensing detection. This review aims to aid researchers in quickly comprehending obj...Learn More
