Thanks to the technical integration of radio frequency (RF) communication technology, digital electronic technology and micro electro mechanical systems (MEMS), micro, cheap, low-power and multifunctional wireless sensor nodes can be realized, and wireless sensor networks (WSN s) have been developed rapidly and widely used [1]. Sensor nodes in wireless sensor networks have the ability of environment awareness, data processing and communication. Wireless networks are formed between nodes through multi hop, and complete large-scale and complex monitoring tasks in a cooperative way. Wireless sensor networks connect people with rich and real information in the real world more directly and closely, and provide sufficient development space and effective solutions for the increasing application scenarios and requirements in the current era of Internet of things [2]. At present, wireless sensor networks have been widely used in national defense support, environmental monitoring, health care, smart home and smart city, and have played a positive role in social construction, nature protection and personal development. In order to realize the perception and acquisition of multimedia information, sensor nodes in WMSN s are generally equipped with CMOS cameras and micro microphones in addition to scalar sensors with simple environmental data acquisition function [3]. WMSN s integrates technologies in many fields such as digital signal processing, communication, network, control and statistics. It can realize the retrieval of video stream, audio stream and still image and the real-time transmission of information, and store, process, correlate and fuse the information from different services. Due to the introduction of multimedia processing technology, WMSN s can realize higher precision monitoring, so that end users can obtain more objective and comprehensive information, and then complete complex advanced monitoring tasks [4]. At present, there are two common methods: machine vision detection and manual detection. Among them, the former is greatly affected by experience and subjective factors, so machine vision detection has gradually become the mainstream. However, because there are dense parallel grid lines on the surface of solar cells, and the defects are subtle and hidden, the algorithm has become a key factor in the field of machine vision to identify the surface defects of solar cells [5]. In addition, the image acquisition of battery is greatly affected by light, which makes it difficult to identify defects. In order to remove these effects, the commonly used detection methods in time domain, frequency domain and wavelet domain need to introduce preprocessing technologies, such as LBP algorithm, Hough transform, normalization and frequency domain filtering. However, these technologies set the empirical threshold on the data after image transformation to remove the influence of illumination and parallel grid, which inevitably increases the complexity of the algorithm, and it is easy to eliminate slight scratches as the background and increase the false detection rate. In addition, considering the differences of parallel grids of battery chips from different manufacturers, the empirical threshold needs to be estimated accordingly, which brings inconvenience to use [6]. Aiming at this research problem, Huang B and others fused the color, direction and gray features of the image, which is the most typical method for significance detection of fused low-level features [7]. Ambareesh S and others first used the face detection algorithm to construct the face features reflecting the image face region, and then combined them with low-level features to improve the accuracy of significance detection. The above methods all use the linear fusion method with equal weight for feature fusion, and the fusion parameters of the model are constructed manually [8]. Kim B S and others used the model to quote the features used in other significance detection related work, calculated the low-level, medium-level and high-level features of 33 images, and then combined with the information in the eye movement database to construct training samples, and regarded the process of fusing features and predicting significant areas as a binary classification problem, a nonlinear feature fusion model is trained by SVM method [9]. Xiao D and others characterized the detection results of some other significance detection models [10]. Sharma R P and others' models are used to learn the model parameters with the methods of expression, SVM and boosting. The detection results are better than most other models. This kind of feature fusion model constructed with the idea of statistical modeling can automatically learn feature fusion parameters and avoid too much human intervention in the process of model construction [11].

Based on the current research, aiming at the problem of low reliability of image sensor quality detection results, this paper establishes an image recognition model based on Laplacian operator image recognition technology and MATLAB software to realize the functions of image acquisition, image edge intelligent recognition, image feature information intelligent extraction and analysis. The number of samples in this experiment is 50. The products are numbered and grouped. Since the base of the product warpagetest needs to be removed from the surface of the product image sensor after the base installation process, the whole product will be scrapped and cannot flow to the next process for production. Referring to the existing production materials, it is found that the existing production processes that may have a great impact on the flatness of the image sensor are false hardening, heating hardening, base installation, calibration and bonding, soldering and testing, so each group shall set the measurement. Among them, No. 22, No. 39 and No. 40 products are poor due to changes in physical properties in subsequent production, and cannot flow to the next process for production. Therefore, the data of No. 22, No. 39 and No. 40 are missing in the test data. A total of 133 groups of experimental data were obtained in this experimental test. The results showed that the standard deviations of group 1, group 2, group 3 and group 4 were 0.172, 0.125 and 0.304 respectively. That is, after the same product is treated by false hardening, heating hardening and base installation processes, the false hardening and heating hardening processes have relatively little impact on the surface flatness of the image sensor. After the base opening and installation process, the surface flatness of the image sensor begins to change. The standard deviations of the measurement results of group 1 and groups 4, 5, 6 and 7 were 0.304, 0.381, 0.391 and 0.514 respectively. That is, after the base installation, calibration, bonding, soldering and testing of the product, the surface flatness of the image sensor and the initial surface flatness have changed greatly. Therefore, production technicians can focus on the process that starts to change, that is, the base installation process. The improved method has the advantages of automatic operation, low error, low error rate and so on.

The time interval is set as Δt; The space step size is 1.(I, j) represents the discrete points in the image, and the iterative formula after the dispersion of the model in this paper is as follows:

The camera quality is the most important part of the camera quality of the mobile phone. The case studied in this paper is model h mobile phone camera, and the first pass rate of good products is only 80%. In order to meet the 95% pass rate of good products required by customers, it is necessary to comprehensively improve the processes that have a great impact on product quality, so as to improve the first pass rate of products, achieve quality objectives and reduce manufacturing failure costs [14].

According to the requirements of the existing quality control system, when the first batch of each equipment is produced in each shift, process and process, after a certain number of products are trial produced, stop the equipment and randomly select three products for quality inspection. If all three random products are qualified, the equipment in this shift and process can be mass produced; If there are unqualified products among the three products, the equipment shall be debugged, and after a certain number of products are produced again, three products shall be randomly selected for quality inspection. Until three products are randomly selected as qualified products.

The main quality inspection item studied in this paper is WarpageTest, which measures the surface flatness of image sensor. In the production process of mobile phone camera, if the surface flatness of image sensor exceeds 5

Select the photosensitive area of the image sensor as the reference plane, automatically calculate the average height of the reference plane as the 0 degree reference line of the whole area, and set the display height color information.

In the selected area, draw two straight lines from top left to bottom right and from bottom left to top right respectively, with a line width of 30, that is, draw 30 straight lines with an average width at the same time to obtain the height line of the area through which the 30 straight lines pass, and calculate the average value as the height line of the straight lines drawn from top left to bottom right and from bottom left to top right.

Manually select the midpoint of the drawn line as the reference point, and manually select the starting point, 1 / 4 point, 3 / 4 point and end point of the drawn line in turn. Finally, the software can automatically obtain the height difference between the reference point and the last 4 points. Repeat for another line.

The operator shall check the final height difference data, and if the maximum value does not exceed 5

Through communication with on-site operators and quality supervisors, we use brainstorming and other methods to summarize many shortcomings of existing measurement methods, and sort out the existing problems based on man-machine material method, environmental measurement and fishbone diagram analysis method.

The existing image measurement methods are not scientific enough and human subjectivity is strong. Image recognition is mainly based on photosensitive areas, and there is a lack of scientific extraction methods. The existing detection adopts manual marking and setting center points to obtain the detection interval, which can not fully and accurately reflect the overall plane image characteristics, and it is easy to miss detection [15].

The detection link is not scientific enough. Due to the limitation of the existing production process, the base installation process cannot be tested directly on the premise of keeping the surface flatness of the image sensor unchanged. The War page Test only after the patch process can not ensure the reliability of the detection quality.

The 3D profilometer can obtain the maximum height height_{max} and minimum height height_{min} in the measurement area, in which red indicates the area with higher height min and dark blue indicates the area with lower height. For the height feature information extraction of the whole plane, we only need to find out the maximum color value (red value) and the minimum color value (blue value) in the HSL color model matrix [h, s, l] after image digitization. The value difference between the two is the height feature information gap in the whole plane. Therefore, the height matrix component value of the whole measurement area is:

After extracting the height feature information of the measurement area of the image sensor and obtaining the plane height matrix, the original two-dimensional plane image can be transformed into a three-dimensional image, and the data of the plane height feature information can be analyzed by using the statistical principle.

After extracting the height information of the main measurement area of the collected image, the height information is analyzed, and the flatness evaluation of the measurement area is obtained by using the standard deviation tool in the principle of data statistics. The calculation formula is:

To find the threshold of height information measured by the improved method, judge whether the product is good or not, and identify the process that significantly affects the surface smoothness of the image sensor. Custom. The number of samples for this test is 50. Products are numbered and grouped. After the installation process, the base needs to be removed from the surface of the product image sensor, so that the product is completely scrapped and cannot flow into the next production process. Existing production materials include existing production processes such as forging hardening, thermal hardening, base mounting, adjusting connections, welding and testing, which can significantly affect the smoothness of the image sensor. Therefore, the measurement Settings for each group are shown in Table 1. The first four groups of tests are war Page tests of single product after different processes, and the last three groups of tests are WAR Page tests of different products. Through various processes. At the beginning of production, due to the uneven surface of the image sensor, 9 reserved products were used as a reference.

Experimental settings

Group number | Number | Variable setting | Naming method |
---|---|---|---|

1 | 1–51 | Conduct War page |
1–51.1 |

2 | 1–18 | Conduct War page |
1–17.23 |

3 | 1–18 | After the heating and hardening process, | 1–17.29 |

4 | 1–11 | Conduct War page |
1–10.39 |

5 | 18–27 | Conduct War page |
18–28.49 |

6 | 29–37 | Conduct War page |
29–38.59 |

7 | 39–51 | Conduct War page |
39–50.69 |

8 | 51–58 | It is found that the flatness of the image sensor is poor | 51–59.79 |

The improved war page test method was used to measure the products of each experimental group. Among them, No. 22, No. 39 and No. 40 products are poor due to changes in physical properties in subsequent production, and cannot flow to the next process for production. Therefore, the data of No. 22, No. 39 and No. 40 are missing in the test data. A total of 133 groups of experimental data were obtained in this experimental test.

Based on the patch process in production, the war page test was inspected as good, but after the final assembly of the product, the test link found that the product had a poor quality accident of the whole product due to the change of the surface flatness of the image sensor. The defective product is No. 51–59 in the experiment.

Therefore, in order to completely avoid the recurrence of such quality accidents, production technicians need to determine the processes that have a great impact on the surface flatness of the image sensor in each process after the die bonding process, so as to narrow the spot inspection range and find out the root cause of the impact on the surface flatness of the image sensor.

After improving the measurement method of War page Test, we can extract the height information and analyze the data of the whole plane of the image sensor, that is, we can find out the processes that have a great impact on the surface flatness of the image sensor. Compare the measurement results of War page Test between group 1 and other groups before and after assembly in each process, and compare the measurement results. The difference significance test is carried out, and the results are shown in Table 2.

Paired t-test of measured results

Pair | Mean value | Standard deviation | T value | p |
---|---|---|---|---|

Groups 1 and 2 | 0.108 | 0.172 | 2.610 | 0.030 |

Groups 1 and 3 | 0.047 | 0.125 | 1.595 | 0.081 |

Groups 1 and 4 | −0.176 | 0.304 | −1.920 | 0.002 |

Groups 1 and 5 | −0.196 | 0.381 | −1.631 | 0.036 |

Groups 1 and 6 | −0.125 | 0.391 | −1.025 | 0.018 |

Groups 1 and 7 | −0.263 | 0.514 | −1.621 | 0.041 |

The significant difference between the paired groups was reflected by the paired t-test of each group. The test results showed that there was a very significant difference between group 1 and group 4 (P = 0.003 < 0.01), and there was a significant difference between group 1 and group 2, group 5, group 6 and group 7 (P = 0.030 < 0.05, P = 0.036 < 0.05, P = 0.018 < 0.05, P = 0.041 < 0.05), but there was no significant difference between group 1 and group 3 (P = 0.081 > 0.05). The following experimental conclusions can be drawn by comparing the measurement results of the last 6 groups with the measurement results of the first group.

The standard deviations of group 1, group 2, group 3 and group 4 were 0.172, 0.125 and 0.304 respectively. Taking the measurement results of group 1, group 2 and group 4 as an example, the comparison diagram is shown in Figure 1 and Figure 2. That is, after the same product is treated by false hardening, heating hardening and base installation processes, the false hardening and heating hardening processes have relatively little impact on the surface flatness of the image sensor. After the base opening and installation process, the surface flatness of the image sensor begins to change.

Compared with the measurement results of group 1 and group 2, the data of group 2 is generally less than that of group 1, that is, the surface flatness of the image sensor gradually becomes stable after the false hardening process of the same product, which shows that the false hardening process helps the surface of the image sensor become flat. Since the false hardening process is a short-term low-temperature heating of the product, which has no impact on other properties of the product, in order to flatten the surface of the image sensor, the false hardening process can be added after individual processes that have a great impact on the surface flatness of the image sensor.

The standard deviations of the measurement results of group 1 and groups 4, 5, 6 and 7 were 0.304, 0.381, 0.391 and 0.514 respectively. That is, after the base installation, calibration, bonding, soldering and testing of the product, the surface flatness of the image sensor and the initial surface flatness have changed greatly. Therefore, production technicians can focus on the process that starts to change, that is, the base installation process.

The improved method has the advantages of automatic operation, low error, low error rate and so on. Compared with the original measurement method, the advantages after improvement are summarized as follows.

Without the participation of operators, the program algorithm can automatically carry out image recognition, analysis and processing, output results and other processes, completely avoiding the quality control problems caused by the operator's operation errors and the interference of human subjective factors in the detection process.

Compared with the original measurement method, the improved method can output the height feature information of the whole plane, rather than just manually drawing the straight line area, and can more comprehensively reflect the surface flatness feature of the whole image sensor.

The time of the whole test process is greatly shortened. The whole analysis process can realize the self operation of the computer. The time of the whole war page test mainly depends on the image acquisition time of the 3D profilometer, and the test time is shortened from 5.1min to 2min.

After improvement, the products after each process shall be subject to war page test, and the surface flatness shall be compared and analyzed longitudinally through multiple groups of data to make up for the deficiency of war page test measurement method before improvement.

In this paper, multimedia sensor image detection based on constrained underdetermined equation is proposed. Aiming at the problem of low reliability of image sensor quality detection results, based on Laplacian operator image recognition technology and Matlab software, an image recognition model is established to realize the functions of image acquisition, image edge intelligent recognition, image feature information intelligent extraction and analysis. The number of samples in this experiment is 50. The products are numbered and grouped. Because the base on the surface of the product image sensor needs to be removed after the base installation process, the whole product will be scrapped and cannot flow to the next process for production. Referring to the existing production materials, it is found that the existing production processes that may have a great impact on the flatness of the image sensor are false hardening, heating hardening, base installation, calibration and bonding, soldering and testing, so each group shall set the measurement. After improving the measurement method of War page Test, we can extract the height information and analyze the data of the whole plane of the image sensor, that is, we can find out the processes that have a great impact on the surface flatness of the image sensor. Compare the measurement results of War page Test between group 1 and other groups before and after assembly in each process, and compare the measurement results. The significance of difference was tested. Through experimental comparison, it is proved that the improved detection method can more accurately reflect the quality characteristics of products. However, the image recognition algorithm proposed in this paper is currently an independent detection program, and the operator still needs to operate the 3D contour measuring instrument to collect the product image. The next improvement direction is to connect the detection program with the image acquisition program to realize the intellectualization of the whole detection link.

#### Paired t-test of measured results

Pair | Mean value | Standard deviation | T value | p |
---|---|---|---|---|

Groups 1 and 2 | 0.108 | 0.172 | 2.610 | 0.030 |

Groups 1 and 3 | 0.047 | 0.125 | 1.595 | 0.081 |

Groups 1 and 4 | −0.176 | 0.304 | −1.920 | 0.002 |

Groups 1 and 5 | −0.196 | 0.381 | −1.631 | 0.036 |

Groups 1 and 6 | −0.125 | 0.391 | −1.025 | 0.018 |

Groups 1 and 7 | −0.263 | 0.514 | −1.621 | 0.041 |

#### Experimental settings

Group number | Number | Variable setting | Naming method |
---|---|---|---|

1 | 1–51 | Conduct War page |
1–51.1 |

2 | 1–18 | Conduct War page |
1–17.23 |

3 | 1–18 | After the heating and hardening process, | 1–17.29 |

4 | 1–11 | Conduct War page |
1–10.39 |

5 | 18–27 | Conduct War page |
18–28.49 |

6 | 29–37 | Conduct War page |
29–38.59 |

7 | 39–51 | Conduct War page |
39–50.69 |

8 | 51–58 | It is found that the flatness of the image sensor is poor | 51–59.79 |

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An empirical study on factors influencing smooth trade along the Belt and Road Research on the processing method of multi-source heterogeneous data in the intelligent agriculture cloud platform Internal control index and enterprise growth: An empirical study of Chinese listed-companies in the automobile manufacturing industry Research on design of customer portrait system for E-commerce Research on rule extraction method based on concept lattice of intuitionistic fuzzy language Fed-UserPro: A user profile construction method based on federated learning A multi-factor Regression Equation-based Test of Fitness Maximal Aerobic Capacity in Athletes Design and evaluation of intelligent teaching system on basic movements in PE Garment Image Retrieval based on Grab Cut Auto Segmentation and Dominate Color Method Financial Risk Prediction and Analysis Based on Nonlinear Differential Equations Constructivist Learning Method of Ordinary Differential Equations in College Mathematics Teaching Multiple Effects Analysis of Hangzhou Issuing Digital Consumer Coupons Based on Simultaneous Equations of CDM Model Response Model of Teachers’ Psychological Education in Colleges and Universities Based on Nonlinear Finite Element Equations A Hybrid Computational Intelligence Method of Newton's Method and Genetic Algorithm for Solving Compatible Nonlinear Equations Pressure Image Recognition of Lying Positions Based on Multi-feature value Regularized Extreme Learning Algorithm English Intelligent Question Answering System Based on elliptic fitting equation Precision Machining Technology of Jewelry on CNC Machine Tool Based on Mathematical Modeling Application Research of Mathematica Software in Calculus Teaching Computer Vision Communication Technology in Mathematical Modeling Skills of Music Creation Based on Homogeneous First-Order Linear Partial Differential Equations Mathematical Statistics Technology in the Educational Grading System of Preschool Students Music Recommendation Index Evaluation Based on Logistic Distribution Fitting Transition Probability Function Children's Educational Curriculum Evaluation Management System in Mathematical Equation Model Query Translation Optimization and Mathematical Modeling for English-Chinese Cross-Language Information Retrieval The Effect of Children’s Innovative Education Courses Based on Fractional Differential Equations Fractional Differential Equations in the Standard Construction Model of the Educational Application of the Internet of Things Optimization research on prefabricated concrete frame buildings based on the dynamic equation of eccentric structure and horizontal-torsional coupling Optimization in Mathematics Modeling and Processing of New Type Silicate Glass Ceramics Green building considering image processing technology combined with CFD numerical simulation Research on identifying psychological health problems of college students by logistic regression model based on data mining Abnormal Behavior of Fractional Differential Equations in Processing Computer Big Data Mathematical Modeling Thoughts and Methods Based on Fractional Differential Equations in Teaching Research on evaluation system of cross-border E-commerce platform based on the combined model A mathematical model of PCNN for image fusion with non-sampled contourlet transform Nonlinear Differential Equations in Computer-Aided Modeling of Big Data Technology The Uniqueness of Solutions of Fractional Differential Equations in University Mathematics Teaching Based on the Principle of Compression Mapping Financial customer classification by combined model Influence of displacement ventilation on the distribution of pollutant concentrations in livestock housing Recognition of Electrical Control System of Flexible Manipulator Based on Transfer Function Estimation Method Automatic Knowledge Integration Method of English Translation Corpus Based on Kmeans Algorithm Real Estate Economic Development Based on Logarithmic Growth Function Model Design of Tennis Mobile Teaching Assistant System Based on Ordinary Differential Equations Financial Crisis Early Warning Model of Listed Companies Based on Fisher Linear Discriminant Analysis High Simulation Reconstruction of Crowd Animation Based on Optical Flow Constraint Equation Construction of Intelligent Search Engine for Big Data Multimedia Resource Subjects Based on Partial Least Squares Structural Equation 3D Animation Simulation of Computer Fractal and Fractal Technology Combined with Diamond-Square Algorithm Analysis of the Teaching Quality of Physical Education Class by Using the Method of Gradient Difference The Summation of Series Based on the Laplace Transformation Method in Mathematics Teaching Optimal Solution of the Fractional Differential Equation to Solve the Bending Performance Test of Corroded Reinforced Concrete Beams under Prestressed Fatigue Load Animation VR scene mosaic modeling based on generalized Laplacian equation Radial Basis Function Neural Network in Vibration Control of Civil Engineering Structure Optimal Model Combination of Cross-border E-commerce Platform Operation Based on Fractional Differential Equations The influence of accounting computer information processing technology on enterprise internal control under panel data simultaneous equation Research on Stability of Time-delay Force Feedback Teleoperation System Based on Scattering Matrix BIM Building HVAC Energy Saving Technology Based on Fractional Differential Equation Construction of comprehensive evaluation index system of water-saving irrigation project integrating penman Montei the quation Human Resource Management Model of Large Companies Based on Mathematical Statistics Equations Data Forecasting of Air-Conditioning Load in Large Shopping Malls Based on Multiple Nonlinear Regression Analysis of technical statistical indexes of college tennis players under the win-lose regression function equation Automatic extraction and discrimination of vocal main melody based on quadratic wave equation Analysis of wireless English multimedia communication based on spatial state model equation Optimization of Linear Algebra Core Function Framework on Multicore Processors Application of hybrid kernel function in economic benefit analysis and evaluation of enterprises Research on classification of e-commerce customers based on BP neural network The Control Relationship Between the Enterprise's Electrical Equipment and Mechanical Equipment Based on Graph Theory Mathematical Modeling and Forecasting of Economic Variables Based on Linear Regression Statistics Nonlinear Differential Equations in Cross-border E-commerce Controlling Return Rate 3D Mathematical Modeling Technology in Visualized Aerobics Dance Rehearsal System Fractional Differential Equations in Electronic Information Models BIM Engineering Management Oriented to Curve Equation Model Leakage control of urban water supply network and mathematical analysis and location of leakage points based on machine learning Analysis of higher education management strategy based on entropy and dissipative structure theory Prediction of corporate financial distress based on digital signal processing and multiple regression analysis Mathematical Method to Construct the Linear Programming of Football Training Multimedia sensor image detection based on constrained underdetermined equation The Size of Children's Strollers of Different Ages Based on Ergonomic Mathematics Design Application of Numerical Computation of Partial Differential Equations in Interactive Design of Virtual Reality Media Stiffness Calculation of Gear Hydraulic System Based on the Modeling of Nonlinear Dynamics Differential Equations in the Progressive Method Knowledge Analysis of Charged Particle Motion in Uniform Electromagnetic Field Based on Maxwell Equation Relationship Between Enterprise Talent Management and Performance Based on the Structural Equation Model Method Term structure of economic management rate based on parameter analysis of estimation model of ordinary differential equation Influence analysis of piano music immersion virtual reality cooperation based on mapping equation Chinese painting and calligraphy image recognition technology based on pseudo linear directional diffusion equation Label big data compression in Internet of things based on piecewise linear regression Animation character recognition and character intelligence analysis based on semantic ontology and Poisson equation Design of language assisted learning model and online learning system under the background of artificial intelligence Study on the influence of adolescent smoking on physical training vital capacity in eastern coastal areas Application of machine learning in stock selection Comparative analysis of CR of ideological and political education in different regions based on improved fuzzy clustering Action of Aut( G ) on the set of maximal subgroups ofp -groupsThe internal mechanism of corporate social responsibility fulfillment affecting debt risk in China: analysis of intermediary transmission effect based on degree of debt concentration and product market competitive advantage Study on transmission characteristics in three kinds of deformed finlines based on edge-based finite element method Asymptotic stability problem of predator–prey system with linear diffusion Research on loyalty prediction of e-commerce customer based on data mining Algebraic Equations in Educational Model of College Physical Education Course Education Professional English Translation Corpus Under the Binomial Theorem Coefficient Geometric Tolerance Control Method for Precision Machinery Based on Image Modeling and Novel Saturation Function Retrieval and Characteristic Analysis of Multimedia Tester Based on Bragg Equation Semiparametric Spatial Econometric Analysis of Household Consumption Based on Ordinary Linear Regression Model Video adaptive watermark embedding and detection algorithm based on phase function equation English Learning Motivation of College Students Based on probability Distribution Scientific Model of Vocational Education Teaching Method in Differential Nonlinearity Research on mobile Awareness service and data privacy Protection based on Linear Equations computing protocol Vocal Music Teaching Model Based on Finite Element Differential Mathematical Equations Studying a matching method combining distance proximity and buffer constraints The trend and influence of media information Propagation based on nonlinear Differential equation Research on the construction of early warning model of customer churn on e-commerce platform Evaluation and prediction of regional human capital based on optimised BP neural network Study on inefficient land use determination method for cities and towns from a city examination perspective A sentiment analysis method based on bidirectional long short-term memory networks A study of local smoothness-informed convolutional neural network models for image inpainting Mathematical Calculus Modeling in Improving the Teaching Performance of Shot Put Application of Nonlinear Differential Equation in Electric Automation Control System Higher Mathematics Teaching Curriculum Model Based on Lagrangian Mathematical Model Computational Algorithm to Solve Two–Body Problem Using Power Series in Geocentric System Decisions of competing supply chain with altruistic retailer under risk aversion Optimization of Color Matching Technology in Cultural Industry by Fractional Differential Equations The Marketing of Cross-border E-commerce Enterprises in Foreign Trade Based on the Statistics of Mathematical Probability Theory Application of Linear Partial Differential Equation Theory in Guiding Football Scientific Training Nonlinear Channel Estimation for Internet of Vehicles Some Necessary Conditions for Feedback Functions of de Bruijn Sequences The Evolution Model of Regional Tourism Economic Development Difference Based on Spatial Variation Function System Model of Shipping Enterprise Safety Culture Based on Dynamic Calculation Matrix Model An empirical research on economic growth from industrial structure optimisation in the Three Gorges Reservoir area The Inner Relationship between Students' Psychological Factors and Physical Exercise Based on Structural Equation Model (SEM) Analysis and Research on Influencing Factors of Ideological and Political Education Teaching Effectiveness Based on Linear Equation Study of agricultural finance policy information extraction based on ELECTRA-BiLSTM-CRF Fractional Differential Equations in Sports Training in Universities Examination and Countermeasures of Network Education in Colleges and Universities Based on Ordinary Differential Equation Model Innovative research of vertical video creation under the background of mobile communication Higher Education Agglomeration Promoting Innovation and Entrepreneurship Based on Spatial Dubin Model Chinese-English Contrastive Translation System Based on Lagrangian Search Mathematical Algorithm Model Genetic algorithm-based congestion control optimisation for mobile data network