This PDF file contains the front matter associated with SPIE Proceedings Volume 12153 including the Title Page, Copyright information, and Table of Contents.

With the development of quality education and information technology, new computer technology is continuously added in the field of music education. Computer technology assists students in music teaching, which can cultivate students' independent learning ability and strengthen students' enthusiasm for learning music. This paper studies the interactive teaching music intelligence system based on artificial intelligence, and proposes a music learning model based on RBF algorithm. The addition of artificial intelligence to music teaching can improve students' inquiry ability, give play to the leading role of teachers, and make music teaching in the music classroom complementary and let students become the subject of teaching. Artificial intelligence technology combined with music teaching, building a neuron model and RBF algorithm, makes the music classroom interesting and vivid. Artificial intelligence technology provides a better teaching method for music teaching, which has far-reaching significance for music teaching.

Object detection is a hot topic in the field of computer vision and pattern recognition. The task of object detection is to accurately and efficiently identify and locate many object instances of predefined categories from images. With the wide application of deep learning, the accuracy and efficiency of object detection have been greatly improved. However, object detection based on deep learning still faces challenges such as improving the performance of mainstream object detection algorithms and the detection accuracy of small target objects. In this paper, based on extensive literature research, we survey the mainstream algorithms of object detection from the angle of improving and optimizing the two-stage and onestage object detection algorithms. We also analyze the promotion method of small object detection accuracy combined with the backbone network, the visual receptive field, and the model's training. In addition, the common data sets of object detection are introduced in detail, while the performance of representative algorithms is compared from two aspects. The problems to be solved in object detection and the future research direction are predicted and prospected. More high precision and efficient algorithms are proposed, and more research directions will be developed in the future.

The 500m aperture spherical radio telescope (FAST) independently developed by China is the largest single aperture radio telescope with the highest sensitivity in the world. How to adjust its reflector to a working paraboloid is very important. In this paper, the ideal paraboloid model is established based on the coordinate transformation and geometric optics law, so as to solve the optimal design problem of the adjustment scheme of the reflection panel in the working state.

With the rise of living standards, more and more people pay attention to the grade of ceramic products. The beautiful appearance of two different ceramic products of the same type can bring a price difference of more than 1,000 times. Because the structure of ceramic products is simple, easy to imitate, and difficult to identify, many imitation products have infringed on the rights of customers and original product enterprises. Therefore, copyright protection becomes particularly important. However, traditional methods of copyright registration fail to satisfy the requirements due to their long cycle, non-transferable, and cumbersome in rights confirmation, etc. In this paper, we combine the appearance and structural features of ceramic products, investigate an approach for rights confirmation and infringement tracking with the digital features of ceramic products. As another contribution, we propose to establish a copyright transaction model based on smart contracts. To identify the infringement acts, we invoke smart contracts to extract the rights. Through the computer vision algorithms to compare the similarity between physical products and digital resources. Combined with this research, the registration, confirmation, traceability, and transaction of ceramic product copyright can be well realized.

The planning model often pursues the minimization of investment and operating costs, and does not consider the economic issues of the planning scheme under the full time sequence condition in the traditional power grid planning process. The key factors affecting the cost and benefit of the full time sequence of the power grid is analyzed, and the concept of full time sequence is integrated into the development plan of the power grid with the support of panoramic simulation technology. The full-time sequence cost and benefit calculation model is established on the basis of consideration of construction, operating, and reliability, combined with the impact of the planning scheme on the safety, reliability and operating conditions of the power grid. Finally, the optimal construction sequence of the power grid planning scheme is determined through the economic analysis of the planning scheme. An empirical analysis is carried out through a typical power grid, and the results show that the model and algorithm proposed in this paper are effective and feasible.

Marine pollution has become a global environmental problem, and the negative impact of marine garbage on marine life and human beings cannot be ignored, especially the pollution of plastic products. However, there are still many problems in the recycling and treatment of ocean plastic waste. In order to solve these problems, this project designed an intelligent unmanned offshore plastic waste efficient recovery and cracking oil refining platform. An innovative design was carried out to address the disadvantages of plastic waste at sea, such as great harm, existing fishing devices that cannot be handled on site (waste caught at sea needs to be transported to land for treatment), high recovery cost, low collection efficiency, limited application scenarios, and inability to be used in real offshore "garbage islands" and garbage patches.

This paper selects Chinese second largest bay area—the Hangzhou Bay area as the research area. Based on the three phases of land use data in 2000, 2010 and 2018, the InVEST model is used to calculate the spatial differentiation and temporal changes of habitat quality in the study area from 2000 to 2018. Combined with spatial autocorrelation and socio-economic data, the impact of land use changes in the study area on the changes in the spatial and temporal patterns of habitat quality is analyzed. The results show that:(1) The land use type conversion in the study area is significant, which is mainly manifested by the rapid expansion of construction land to squeeze the area of cultivated land;(2) The average habitat quality index in 2000, 2010 and 2018 are 0.5675, 0.5540, and 0.5534, respectively, showing a ‘high in the southwest and low in the northeast’. In the spatial pattern of ‘Habitat Quality’, the area of poor habitat quality is almost half of the total area. The reason for the decline is mainly due to the conversion of fair-grade areas into poorgrade areas. The phased comparison shows that the improvement of habitat quality is concentrated in In woodland and grassland areas, the quality of most habitats has slightly declined, and urban construction and regional policies are important influencing factors; (3) The spatial autocorrelation analysis shows that the quality of habitats shows a certain spatial agglomeration and is getting closer and closer, and cold spots are concentrated in areas For woodland and grassland areas, hotspots are mainly distributed in cities, towns and Qiandao Lake area; while habitat degradation hotspots are mainly distributed in the northern areas of Shanghai, Huzhou, Hangzhou, Ningbo and most parts of Shaoxing. How to make scientific preventions against rapid urbanization Policies need urgent attention.

With the rise of neural networks, Echo state network (ESN) is also added to the queue of the neural network. ESN is a powerful form of reservoir computation, is a new type of recurrent neural network and only need to train the output weights. ESN overcomes the problems of the traditional recursive neural network such as too complicated training algorithm, slow convergence speed and easy to fall into local minimum.In order to reflect different learning tasks need different status updating methods and appropriate reservoir are constructed for a given task, an improved leaky integrator echo state network is proposed. The improved model, named Double Echo State Network with Multiple Reservoir(DMESN) for Time-Series Prediction. It uses multiple sub-reservoir to build a total reservoir and extends it in depth. Then the batch gradient descent method is utilized to optimize the DM-ESN parameters. Finally, the proposed method is applied to the time-series prediction. Simulation results show that the DM-ESN model can greatly improve the accuracy and stability.

In terms of security detection, security personnel often need to find potential dangerous events in time, although there are many monitoring equipment that can monitor behavior at any time. However, the real-time performance of monitoring equipment is not strong enough. Therefore, this paper proposes a novel action detection method suitable for violent action detection. In this method, the common camera is used as the data acquisition equipment, and the human skeleton structure is obtained by using the algorithm of object detection and pose estimation. Finally, it is recognized by graph convolution neural network. In addition, TensorRT acceleration technology is used in object detection and pose estimation algorithm, which further improves the real-time performance of action recognition and detection algorithm. Through the detection of the actual environment, it shows that the algorithm has good real-time performance and can be widely used in security monitoring.

In recent years, speaker recognition technology can achieve more than 90% accuracy in quiet environment, but it is not accurate in noise environment. In order to solve the problem of speaker recognition in noisy environment, a speaker recognition method based on deep residual network and improved Power Normalized Cepstral Coefficients (PNCC) features is proposed in the study. The PNCC features extraction algorithm is improved to be suitable for PNCC features parameter extraction in noisy environment. In order to further improve the training effect of the model, the deep residual network is adopted in this study to train the model, which effectively improves the model accuracy. In the recognition stage, in order to effectively suppress the influence of noise, this study proposes a VMD algorithm based on wavelet threshold denoising to improve the accuracy of speaker recognition. The experimental results show that compared with MFCC and PNCC features parameter extraction methods, the improved PNCC features extraction method is more conducive to feature extraction of speech signal under noise environment. Compared with other speaker recognition methods, the proposed speaker recognition method based on deep residual network and improved PNCC features has higher recognition accuracy.

SOBEK is an integrated model for river, urban or rural water management and it can be used to simulate complex flows and the water related processes in almost any system. SOBEK can simulate both 1D and 2D flow. 1D network system is applied for the river, and 2D horizontal grids are applied for the floodplain and connecting these through a channel with a weir. It is widely used in river management. This paper studies the middle reach of Huaihe River from Lutaizi to Bengbu City based on a 1D2D SOBEK model, as well as eight retention areas along this reach. In order to reduce the water level of downstream, several scenarios were designed. Different performances also exist depending on the different scenarios, which can be good references for decision-makers.

At present, after radar target detection, radar target recognition mainly depends on manual judgment. Manual identification relies too much on the operator's personal experience and subjective consciousness, which takes a long time and has a large error. To solve this problem, a radar target recognition method based on deep learning is proposed. By analyzing the differential characteristics of radar echoes of different targets, taking the range profile of radar echo sequence as the data set, a deep residual network classifier model is designed to classify and identify the types of radar targets. In order to improve the generalization ability of the network and avoid the over-fitting problem, the deep convolutional generative adversarial network is used to expand the range profile data set of radar echo sequence. In order to ensure the quality of the generated samples during data set expansion, the expanded samples are screened with the peak signal-to-noise ratio as the index. The experimental results of radar measured data show that this method has a good effect on radar target recognition.

With the continuous expansion of the power industry, insulators, as one of the important power transmission equipment, have been exposed for a long time, causing wear, string loss and other problems, which threaten the safe operation of the power system. In this paper,yolov4 target detection algorithm based on deep learning is used. Based on CSPDarknet-53 and adding SPP Net, the receptive field is greatly increased. PANet is introduced to strengthen the feature extraction network，and focal loss is used as a function to calculate the loss.Then the models trained using RetinaNet and yolov4 are compared.The experimental data show that the defect detection accuracy can reach 96.2% and the recall rate can reach 97.7%.

With many previous works being done in the field of analyzing traffic accidents using machine learning, classification of victims and their sex seems to be a missing field. We aim to train a model to classify the types of victims and their sex in a traffic accident using various classification models and a dataset containing traffic accident data in France in 2019. We experimented with the variables involved using ablation study and gave the factors that are most relevant in determining the types of victims.

With the rapid development of China's economy, people's lives are prosperous, and the number of private cars is rising rapidly. The transportation system is facing more and more serious operating pressures, and traffic jams and traffic accidents are endless. Therefore, the state has issued a strategy to strengthen the country in transportation and put forward the concept of "smart transportation". It has given strong support to the transportation industry in terms of transportation policies and investment funds, especially in the construction of transportation infrastructure and transportation operation system, and emphasized Smart transportation will run through the whole process of transportation construction, aiming to provide people with efficient, safe and convenient travel services.

At present, cooperative vehicle-infrastructure system and automatic driving technology are developing rapidly. The automatic driving technology route based on cooperative vehicle-infrastructure system has become the industry consensus for the development of automatic driving. This paper makes a detailed analysis on the technical route and application scenario of automatic driving based on cooperative vehicle-infrastructure system, and puts forward the classification method and technical requirements of networking automatic driving. It discusses the technical route and overall technical architecture of automatic driving based on cooperative vehicle-infrastructure system, and analyzes the key technologies used to realize automatic driving through vehicle-infrastructure cooperation. The future development of automatic driving based on cooperative vehicle-infrastructure system is prospected.

Based on the requirements of intelligent transformation in electronic component manufacturing enterprises, this paper focuses on the application of artificial intelligence technology in the field of electronic component manufacturing based on the analysis of the connotation of intelligent manufacturing. The application status of four key technologies of machine vision, information system, Internet of Things (IOT) and big data in quality detection, manufacturing informationization, interactive perception and decision analysis is studied, and the existing problems are analysed. Finally, the future development trend of intelligent manufacturing of electronic components is prospected, which can provide reference for intelligent manufacturing research.

The application of virtual reality technology in industrial heritage protection has always been an important part of industrial heritage protection. Virtual reality technology mainly starts with the systematicness and professionalism of industrial protection. This paper mainly studies the specific application of virtual reality technology in industrial heritage. Through the analysis of the characteristics and development of virtual reality technology and the latest industrial heritage protection cases, an industrial heritage protection data model based on virtual reality technology is constructed. This model reconstructs the industrial heritage protection system supported by virtual reality technology from four aspects: data support, system support, algorithm level and storage level. Provide a new system framework for the application of new technologies for industrial heritage protection, and promote the development and improvement of its industrial heritage protection industry. At the same time, by using the public information model as the data verification technology between systems, many advanced multi-source data are used to screen high-quality industrial data, and the protection scheme is further adjusted according to the actual industrial heritage data. Compared with the traditional industrial heritage protection scheme, the new data quality optimization method not only improves the data automation of industrial heritage, but also saves the maintenance time of industrial protection system.

Due to the slow innovation time of traditional art design, this paper focuses on the innovative design of visual art in virtual reality (Virtual Reality,VR) technology. Ensure the safety of system operation by the development of teaching resource management protocol. Art design finally completes the innovative design of visual art by establishing three-dimensional model based on virtual reality technology and virtual scene mode, and the establishment of teaching. Thus to promote the further development of art design innovation, so that art design innovation to keep up with the development of The Times

In the VR social game - VRChat, VR motion sickness, as known as Cybersickness(CS), becomes a serious negative factor that degrades user experiences in VRChat. Current solutions that have been utilized to solve CS either degrade user experience in game or contain risk factors. Therefore, better CS solving methods should be applied in this field. The paper first investigates the influencing factors and inducement mechanisms of CS; analyze two classical theories - Postural instability theory and Sensory conflict theory, which explains motion sickness problems, and settle the exact inducement of CS in VRChat. Then the paper analyzes the better CS solutions according to the inadequacy of current solutions. Three promising solutions found are tricking vestibular organs, infinite space and the BCI system. After research, each of the three better solutions presented by the paper is considered to also contain disadvantages. The side effect of tricking vestibular organs requires further study; large omnidirectional treadmills are too expensive; BCI systems and EEG algorithms need improvements in accuracy. In conclusion, current solutions are not perfect and require further study in allusion to the VRChat. In the plateau of the productivity of VR technology, as technology and market size advance, there will certainly be more satisfying solutions to solve CS problems. The author also believes that peripheral devices such as VR treadmills will have better development prospects due to auxiliary features.

Aiming at the problems of uncontrollable factors such as many steps, long firing cycle, high cost and great danger in the ceramic kiln firing process of the shuttle kiln, the traditional theoretical explanation, physical operation and other unidirectional teaching methods have poor effects. This article is based on the real three-dimensional model and space layout of the shuttle kiln scene in Jingdezhen, and the teaching content is planned according to the syllabus and assessment requirements. Based on the Unity 3D software, the simulation teaching of shuttle kiln ceramic firing with high simulation and full scale physical equipment is developed. The platform expounds the functional innovation design of the simulation system, and introduces the development process and key technical points of the simulation system. The results show that using VR technology training, students repeatedly perform virtual operations, multiple people participate, low equipment loss, and reduce teaching costs. At the same time, it provides learners with a self-supporting learning platform, and also provides convenience for the teaching of experimenting with "interactive" lessons.

Using virtual reality (VR)/mixed reality (MR) virtual hoisting training system is a low-cost and low-risk skill training method. However, the research on the performance of VR/MR virtual hoisting training is still relatively scarce. The article comprehensively evaluates the performance of VR/MR virtual hoisting training by integrating three evaluation indicators: objective performance, visual characteristics and subjective experience. The results show that the effect of the MR virtual hoisting training system is better, and the simulation reduction degree is higher. However, the VR virtual hoisting training system has good operability and is easy to master. Long-term use of the VR/MR virtual training system will cause recoverable vision loss, and there is a problem that the user's ability to actively explore the virtual environment using touch is weak. The research results have a positive effect on optimizing the allocation of training resources and improving training effectiveness.

With the progress of science and instrument quality, piano performance and color are more varied. The piano performance, receiving and skills also developed with the development of piano art. Virtual Reality technology will also have a certain auxiliary role in the mentality adjustment of piano performance. In terms of such application, Oculus Rift DK2 will become an important auxiliary tool to help piano players achieve good adjustment of mentality. In this paper, the auxiliary role of VR technique in the regulation of the piano mentality.

Take the instant replay system as an example, the role of AI technology in sports competition is very important. The fact that the technical principle of the instant playback system is not complicated, it is also very precise to separate the stereo space of the field into several units of measurement computed in millimeters. Using high-speed cameras to capture tennis flight tracks, you can generate three-dimensional images through the computer, and finally use real-time imaging technology to make the ball drop points of the network clearly presented on the big screen. The application of artificial intelligence technology in sports competitions is not only stopped in tennis competitions, but also whether the electronic generator and piezoelectric sensing technology can effectively reduce the misjudgment in sports competitions, and make the competition results more objective and fair.

This paper introduces the concept and characteristics of VR reality in the field of preschool education.The aim is to analyze the problems and role of VR technology in the application of preschool education.The application of virtual reality technology in the field of preschool education can make up for the shortcomings of traditional preschool education, greatly break through the teaching difficulties of preschool education, and promote children's learning initiative.greatly change the traditional way of childhood teaching, through virtual reality technology simulation suitable for childhood learning virtual environment, the knowledge on the book into a real scene through this teaching mode, make the content of books become vivid and interesting, more in line with the age characteristics of children, improve children's participation in learning, let its experience after knowledge experience.

In view of the current situation of poor and inefficient cross-platform information interaction in the three-dimensional building model under the C/S architecture, in order to intuitively and efficiently manage the static data and dynamic data generated in the building operation and maintenance phase, the management method based on BIM and IoT technology is studied. Through the IFC file conversion plug-in, the BIM model data is converted into a file format suitable for Web technology, and the Three.js framework is used to realize the display of the lightweight building model based on the B/S architecture; the data is collected by the IoT devices based on the Zigbee protocol. Integrating the building dynamic data with the BIM model data to realize data management applications in the building operation and maintenance phase. The practical results verify the practicability of this method.

Fire-fighting robot plays an important role in the construction of unmanned substations and guaranteeing the fire safety of substations. In order to provide various fire-extinguishing mediums such as dry powder, firewater and foam for substation firefighting robots, supply scheme of firefighting medium is designed in this paper. A standard dry powder tank is installed on the robot body to store dry powder, which is convenient for quick replacement, so the efficiency can be increased. A supply equipment of fire medium is designed to provide firefighting water and foam for substation firefighting robot by connecting with the robot. The mixing proportion of foaming agent and firewater can be adjusted to several ratios. Supercharging of firewater and foam can be realized by booster pump to increase the injection distance of robot. The robot was indicated to have powerful fire-fighting capacity by the fire tests. The firefighting ability of substation firefighting robot can be greatly improved by the design of fire medium supply scheme for power station firefighting robot. It is of great significance to safety and stably operating of the power grid.

Digital media technology contributes to the realization of the innovation of the graphic design of Chinese characters. From the two aspects of the artistic expression characteristics of virtual reality and the image design of virtual interactive Chinese characters, this paper discusses the forms and methods of image design of Chinese characters in virtual reality, and discusses the multi-dimensional, animated and flowing image design of Chinese characters, which includes light, color, time and movement, sound and virtual interactive elements. In this work, the virtual world constructed by digital media technology is summarized, which provides a virtual Chinese character image scene for Chinese character design. In addition, Chinese character strokes are broken up and grafted into a new virtual space effect, which enables designers and viewers to resonate through game interaction.

Virtual Reality (VR), a scientific method and technology created by the human being during the process of exploring nature, help human understand nature, and then better adapt and utilize the natural resource. Brain-Computer Interface (BCI), a direct connection between the brain of a human or animal and an external device, provides a straightforward communication pathway, which might be used as a potential input solution for VR technology. In recent years, with the maturity of VR technology and the breakthrough of BCI technology, combing these two technologies is becoming more and more possible. Moreover, many companies and scientists have started their research and develop new technology using BCI with VR or AR system. Once the new technology comes out, there will be a huge change in the world. People can realize virtual social, virtual office, and even live in a virtual world. This paper will further discuss the research objectives and future application of VR/AR technology combined with invasive and non-invasive BCI. Discussing separately BCI used as perceptual devices and interaction devices of VR/AR systems. This study found that various types of brain-computer interfaces are potential auxiliary tools for future XR products such as VR/AR glasses.

Robots are superior to human workers in the manufacturing industry, but cannot fully supplant humans for several reasons. It is no coincidence that industrial robots are mostly robotic arms on assembly lines. This article analyzes why robots are playing a more and more important role in manufacturing, and whether soft robotics are able to make amendments to the flaws of rigid robotics, to achieve a higher level of automation. The robots are more precise, more productive, and able to reduce the risk of human injury. But at the same time, they may be too large or too small for the product, or unable to carry out duties due to design constraints. Soft robots possess a new level of adaptability and flexibility, thanks to biomimicry, but current development of soft robotics is slow because of the difficulty in kinematic control. However, this article only discusses its application, namely in the production of communication modules, aircraft assembly and vehicle inspection, assuming kinematic control is feasible in the future. And it is concluded that soft robotics could be applicable in manufacturing industries to make amendments of robotic arms’ drawbacks, but it takes time before soft robotic can be mass-produced.

It is proposed to adopt a research method combining the successful cases of modern virtual reality technology in the restoring of ancient ceramics and the comprehensive analysis of the literature. This article first puts forward the irritating gas generated in the offline restoration of ancient ceramics and the irreversibility of the ceramics restoration process. Secondly, the virtual reality technology itself has the characteristics of immersion, interactivity, and intuitiveness. Through the combination of virtual reality technology and ancient ceramic restoration, we can build an ancient ceramic restoration platform to solve the actual problems in ancient ceramic restoration.

In China, millions of houses need to be renovated every year. However, many problems exist in the current renovation process, especially in the interior design process. With the development of virtual reality, some of these problems can be solved. In this article, the author analyzed the people’s needs and problems in the current interior design process based on previous research. Then research and products of virtual reality for interior design were discussed to see how do current virtual reality applications solve these problems and limits of current virtual reality application in this field. Finally, based on the analysis, a prototype of virtual reality implementation in interior design was designed.

Virtual Reality (VR) reveals more possibilities to different fields in many regards. However, few research and studies were complemented in medicine to find an innovational way to treat the patients. In this paper, a comprehensive design and experiments about how to build a simulated system for the disabled and patients after the surgeries will be stated. In addition, some features that could use to improve the feasibility of the system are also proposed. Basically, the system is embedded in simulated virtual environment that generated by computer. The methodology of updating the system is to synchronize the map of the real world, which means this simulation world is dynamic. Recommended devices are also mentioned to accomplish the system, except to conventional headsets and controllers, advanced control pattern for example voice control and breath control are included as well [2]. This paper improves and re-proposes a design based on existing experiments. The basic functions of the system could be realized with the support of current technology. With the support of existing technology, the author also reported some obstacles in order to ensure safety and feasibility. This paper proposes a new design of virtual environment system for every disabled users. New control approaches such as voice control and breath control are mentioned. For some key problem like synchronization and AI technique, proper solutions are provided to meet current requirements. However, there are still some difficulties in the future, such as high-definition instant synchronization and how to decrease the dependence of AI technology on people.

Post-traumatic stress disorder has become a common mental illness in modern society, with up to 800 million patients worldwide. Usually, therapists use talk therapy and medication to relieve PTSD symptoms, but those traditional methods have many limitations. For example, its expensive treatment fee, lack of professionals, a considerable amount of time taken of the treatment. Currently, the application of VR in the field of PTSD has received attention, but most of the literature and cases are based on case analysis. This study aims to make an objective evaluation of the effect of virtual reality technology in the treatment of PTSD patients by studying different types of patients with PTSD, to better play the application of VR in the field of PTSD. In this study, qualitative analysis was carried out mainly by collecting published literature and typical cases. The results showed that VRET had a positive effect on symptom improvement in PTSD patients. However, the effects of VRET were different in different patients with a different mechanism of trauma and different tolerance of trauma. Simultaneously, PTSD adjuvant therapy also has many limitations. Suppose researchers combine psychology and use artificial intelligence algorithms to create a personalized VR scene reality that makes the ideal effect close to individual needs. In that case, they can get the most effective adjuvant therapy. After a certain extent of development, it is predictable that the VR therapy would have fewer side effects, simple operations, and low cost that can be used to build a healthier family and community environment.

Public sculpture has become an indispensable carrier of spiritual civilization in a modern city, which reflects the cultural connotation and unique taste of a city. Today's city develops rapidly, market demand is increasing, the traditional production system can not meet the development of modern society, under the requirements of efficiency, personality, diversification and other factors, use new technical means to modernization has become the main content of this article, the article through the virtual reality printing technology and 3D printing analysis, and for comparative analysis of modern technology, combined with specific cases shows the rationality of new technology in public sculpture design and production.

This paper uses vegprime to design the virtual reality of 3D animation display system of cultural and creative products, so as to improve the digital display ability of 3D animation of cultural and creative products. A design scheme combining virtual reality technology and animation design is proposed. Based on virtual reality technology, the virtual reality design of three-dimensional animation system is carried out, and the scene simulation of cultural and creative product system is carried out through visual simulation technology. 3D animation system mainly includes data information collection, database model construction, virtual reality technology, visual reconstruction template, virtual technology and so on. VR program is used for comprehensive virtual design and packaging of 3D animation of cultural and creative products, and MAX software system is used to build 3D virtual model and overall effect rendering of 3D animation of cultural and creative products. Therefore, the application of VR technology in the optimal design of 3D animation system of cultural and creative products can make obvious progress.

With the rapid development of modern technology, intelligence has become the mainstream of people chasing fashion and personality, among which wearable devices as a high degree of intelligence, convenience and comfort, high degree of personalization of electronic products have been widely used in various fields. Wearable smart products are designed with human perception, using virtual reality technology to make comprehensive use of people's own senses of feeling and touch. This paper explores the design and implementation of a virtual glasses fitting system based on virtual reality technology, taking the virtual fitting of glasses as an example.

At present, BIM is increasingly mature in the design and construction stage of engineering projects in China. However, the application of BIM model in FM operation and maintenance stage has not been well popularized and developed. Based on the general situation of Baishan Wanda's reconstruction project and the experience of operation and maintenance management of BIM+FM comprehensive application, this project builds a "BIM+FM" intelligent operation and maintenance management system as the core. Through the CAD drawings of Baishan Wanda Plaza, modeling was carried out by using Revit software, and the model was checked and optimized for collision, which was imported into FM system for operation and maintenance management to achieve standardized, refined management, to improve management efficiency and to reduce the costs of labor and operation management.

Based on the full analysis of user functional requirements, this paper designs and implements the technical management system of dangerous goods transportation vehicles based on SSM framework, which can meet the management requirements of atmospheric liquid dangerous goods tank vehicles. Users of the system include road transportation management institutions, road transportation enterprises of dangerous goods, tank inspection institutions and the public. The system can meet the requirements that enterprises submit basic information of new tank cars and in use vehicles, tank inspection agencies upload tank inspection reports, transportation management agencies carry out annual inspection of tank cars, and provide query functions for the public.

Face recognition system includes face detection, face positioning, and face identification. ith the advent of the information age, identity authentication has become more and more important, and face recognition has become the mainstream method of identity verification due to its non-invasiveness, easy availability, and high reliability. With the current rapid development of artificial intelligence, it is of practical significance to introduce deep learning methods into face recognition. My work uses the caffe framework to design an 18-layer network model. At the same time, 448,808 pictures of 1,583 objects in the YouTube Face data set were used as training set, and 111,403 pictures of 1583 objects were used as verification sets. After preprocessing. These images, we entered them into the network for training our model. The facerecognition accuracy of the final model reached 99.7%. Next, my work did a forward-looking work for 3D face verification: single-view 3D face reconstruction. At present, the lack of open source 3D face database can be said to be the biggest obstacle to 3D face verification if you want to use deep learning algorithms. In order to solve this problem, my work will focus on the reconstruction of 3D human faces. Traditional 3D face reconstruction methods are either unstable or over-regularized. So I tried to apply the deep learning method to the 3D face reconstruction. First of all, in order to solve the problem of lacking 3D model data, we improved the current Multi-view 3D face reconstruction methods, using the 3D Morphable Models (3DMM) to generate huge numbers of labeled examples. Next, design the network and train it, the network finally implemented the function of constructing a 3D model of the object from a 2D picture of itself.

The installation of a spacer damper is a very complicated and dangerous task. Based on the analysis of existing spacer damper installation tools, this article demonstrated how to install a robot through a quad spacer damper. Based on the application scenario of the existing quad spacer damper, a robot was designed to carry the required number of spacers between two towers at a time. At the same time, we also analyzed the fluctuation of conductors, designed a riding mechanism that can adjust the sitting posture, and made a kinematic analysis, mainly for the reliability of key components, of the quad-spacer-damper-installed robot. In addition, advanced control systems and positioning techniques were adopted to achieve precise measurement and improve the efficiency of the installation, which has a broad market prospect and can bring huge economic benefits.

Spatio-temporal field data is one of the primary forms of digital representation of geographic objects, characterized by massive, multidimensional, complex evolution and analysis-oriented, etc. The organization, management, and analysis of the above data have become important bottlenecks of existing information systems. Moreover, the analysis of dynamic evolution behavior of Spatio-temporal field data is less studied. The correlation between attributes and time is not studied enough, making it difficult to carry out smooth and accurate dynamic simulation and expression in the scene. Therefore, this paper proposes a dynamic organization and description scheme of Spatio-temporal field data based on tensor Tucker decomposition. Firstly, the Spatio-temporal field data is organized based on tensor Tucker decomposition, and the original Spatio-temporal field data is chunked according to time. The Spatio-temporal field data sub-packaging mechanism and dynamic evolution description scheme are designed based on the description document and the field data structure itself; Design time-space field data attributes and the expression relationship of time attributes. Finally, the Spatio-temporal deformation field data model in ground subsidence monitoring is used for applied research. The experimental results show that the dynamic evolution method of Spatio-temporal field data based on tensor decomposition proposed in this paper can achieve accurate dynamic simulation representation of Spatio-temporal field data in geographic scenes.

In order to clarify the context of the research progress of ecological restoration in mines, the Citespace bibliometric software was used to analyze the literature data related to this field in the CNKI database in the past 20 years. At the same time, it reveals the development direction and trend in the field of ecological restoration of mines through visual analysis of the amount of articles issued, the organization of the article, the author of the article, and the keywords. The results show that the period from 2001 to 2014 belongs to the low-speed development stage of this field, and the period from 2015 to 2020 belongs to the high-speed development stage; the cooperation relationship between relevant scientific research personnel and institutions is not close enough, and large-scale research has not been formed. The exchanges and cooperation between scientific research institutions and scientific researchers need to be further strengthened; mine ecology, geological environment management, open-pit abandoned mines, mine parks, etc. belong to the hotspots in the field of mine ecological restoration research; whether from the knowledge field or the technical level, the research in this field and policy measures are constantly improving.

This article is based on the literature in the CNKI database, mainly using CNKI visualization analysis, and takes the literature in the research field of "Song of the Wanderer" from 1983 to 2021 in the CNKI academic journal as the research object. Research data shows: (1) Since 1983, the number of documents studying "Song of the Wanderer" has shown a tortuous upward trend. The research has gone through three stages: The initial stage of slow growth (1983-1998)；The mid-term development of tortuous growth (2000-2009)；The rapid growth of the late stage of development (2010-2021); (2) The core authors of "Song of the Wanderer" are mainly 7 scholars, including Tian Guo, Bu Xiaomei, and Zhang You, whose literature has certain reference significance; (3) The core institutions of "Song of the Wanderers" are concentrated in normal schools and conservatories, mostly in universities in more economically developed areas such as Liaoning and Jilin, and relatively few universities in the western region;（4） "Violin", "Violin Performance", "Trilogy Style", are the research hotspots in the research field of "Song of the Wanderer". Based on the above analysis, the future research direction of "Song of the Wanderer" can be considered from the following aspects: Innovate research ideas; conduct interdisciplinary research, combining digital analysis technology with traditional music research; focus on field hotspots and conduct in-depth research, etc.

Visualization technology is one of the important channels to broaden music research. Black keys Etude (op.10 no.5) is one of the most classic and distinctive works in Chopin's Etudes. It is a bold innovation in Etudes genre, with its right hand running all over the black keys, and using pentatonic style skillfully. In this paper, taking interdisciplinary thinking as the center, combined with visual analysis technology of audio, the music data image is integrated with the artistic features and spectral details of black keys Etude, and the recorded audio of four piano players is selected as the research content. With the help of visual technology, the sound content is converted into corresponding data and image files, and then the overall speed of the work, the detailed processing of excerpts and the inherent speed elasticity deviation are specifically analyzed.

Aiming at the difficulty of sentence analysis caused by the fuzziness of words, this paper uses attribute reduction algorithm to generate emotion judgment rules based on rough set theory. Firstly, we extract features of the corpus sample that is the emotional words in the corpus, then through attribute reduction to reduce the extracted emotion feature words for text training and to generate rules for judging the emotion of the text. Secondly, we also extract the features of emotion words from the test corpus and compare with the trained rule text to achieve the classification of their emotions. Through experimental verification we know that different dimensions eigenvalues and boundary values have an important influence on the accuracy and recall rate of classification.

This paper studies the process of raw material ordering and transportation based on comprehensive evaluation and objective programming model. The VIKOR model based on entropy weight method was established to quantitatively evaluate the supply characteristics of suppliers, and fuzzy mathematics comprehensive evaluation was introduced to improve the evaluation system, so as to determine the 50 most important suppliers. Taking the minimum number of suppliers and the minimum inventory fluctuation as the objective function, a dual-objective dynamic programming model was established, which was converted into a single objective programming based on the golden section idea. According to the evaluation score, the greedy algorithm is used to get the minimum selection number of suppliers. Two single objective programming models with minimum total cost and minimum consumption as objective function are established to determine the most economical ordering scheme in the next cycle. Finally, error analysis is carried out to verify the rationality and accuracy of the model.

This paper studies the solution of FAST ideal paraboloid equation. Firstly, the problem is simplified from threedimensional to two-dimensional, and the problem is transformed into the solution of ideal parabolic equation; Considering the adjustment of reflective panel, the difference method and variable step iterative method are used to solve the model. For the ideal paraboloid equation obtained by different objective functions, the radial expansion amount, meridional variation and edge smoothness of main cable nodes with different ideal paraboloids are calculated. The three indexes are analyzed. When the average displacement of meridian main cable nodes is minimized as the objective function, the effect of the ideal parabola is the best. Then, the coordinate system is established to simplify the form of ideal paraboloid equation, and the ideal paraboloid equation is transformed into a global coordinate system by coordinate transformation. The distance between the main cable node and the parabola vertex is used to classify the nodes, and the main cable node in the lighting area is selected. Finally, a follow-up coordinate system is established to make the main cable node move to the ideal paraboloid in the lighting area, calculate the distance from the main cable node to the spherical center of the reference ball after adjustment, and then obtain the expansion and contraction of the corresponding actuator, and check whether the change range of the distance between adjacent nodes exceeds 0.07%.

This paper uses facial motion capture technology to extract the dynamic trajectory of the lip shape change of a person during pronunciation. According to the MPEG-4 standard, the face marking points of the speaker are defined. While analyzing the method of extracting parameters of upper lip protrusion and outer lip width, it focuses on the extraction method of lower lip protrusion and the process of data processing. The data obtained by this method is more accurate, which has a high reference value for analyzing lip features in the research of pronunciation phonetics. This method can also be used for research in various languages.

In recent years, with the continuous development of power grids, more power marketing data is generated, and the traditional EXCEL tables can no longer effectively mine the information in big data. In order to solve these problems, for the grid marketing data, an evaluation system with the collection of support as the main indicator was established, and the information was visualized through interactive visualization technology. This can greatly improve the work efficiency of the power marketing department. In this paper, the power marketing data of 4 league cities and 48 counties in eastern Inner Mongolia is visualized by using the pyecharts module in python, and visual report is generated to evaluate the business level of power companies in each region. The results show that the visual report can analyze and evaluate the business level of various regions intuitively and efficiently, which improve work efficiency. Meanwhile, the weak links in the entire marketing process of various regions and counties can also be found in time, which greatly improving the power marketing department management efficiency and level.