This PDF file contains the front matter associated with SPIE Proceedings Volume 12160, including the Title Page, Copyright information and Table of Contents

Lost circulation is one of the common drilling accidents. Occurrence of such problem will lead to a lot of wastage of resources. This paper proposes research on the application of ensemble gradient boost decision tree (GBDT) to develop a robust model that can be used to predict the occurrence of lost circulation precisely. In the first step, we collect 1048550 wells drilling data from northwest of China. Then two artificial features, distance feature and aggregation feature, are constructed by visualization. Next, we use three GBDT algorithms, XGBoost, LightGBM and Catboost, to build prediction models. Finally, we take the mean and maximum probability, predicted by the above three algorithms, as the ultimate output result. The result of the analysis has revealed that the ensemble model we propose performance are better than a single model. Besides, the model incorporates artificial features can attain a higher predicting accuracy.

With the increasing demand of domestic oil and gas energy, China's oil and gas resources are more and more dependent on foreign countries. The development and utilization of unconventional oil and gas has gradually become a research hotspot. Tight reservoir is a typical unconventional reservoir, and dual-media seepage system is an important characteristic of tight reservoir. In order to study the flow law of reservoir fluid in dual media reservoir, the influencing factors of reservoir productivity in dual medium percolation system are analyzed, and the influence of various parameters on oil well productivity was calculated and analyzed by using numerical examples. The results show that the ratio of matrix fracture pressure difference to production pressure difference and the inter-porosity flow coefficient have obvious influence on the oil well productivity. It is concluded that the oil well productivity increases with the increase of the ratio of matrix fracture pressure difference to production pressure difference and the inter-porosity flow coefficient. The study of dual porosity and single permeability productivity model of oil in dual medium reservoir has certain reference significance for in-depth analysis of the development law of tight reservoir and establishment of development countermeasures.

Passenger flow forecast is the basis of rail transit operation Department, and it is an important reference for rail transit cloud data fusion and optimal passenger capacity deployment. Due to the randomness and uncertainty of urban rail transit passenger flow, the traditional forecasting technology has been unable to meet the operational needs. Therefore, we should use more accurate methods to predict the short-term passenger flow. Therefore, this paper proposes a short-term passenger flow forecasting method for rail transit based on cloud data fusion, using cloud distributed and virtual technology Combined with big data technology for passenger flow data collection and analysis, line data classification from two dimensions of real-time judgment and real-time prediction, combined with cloud data fusion technology for the synthesis of various algorithms, to achieve the accurate prediction of rail transit short-term passenger flow. Finally, through experiments, it is confirmed that the rail transit short-term passenger flow prediction based on cloud data fusion has high practical application value and fully meets the research requirements requirement.

After the 14th Five-Year Plan, with the overall planning of the country, provinces and cities have introduced their own plans and goals, and the ministries and departments of the construction industry have also landed relevant documents and policies to promote the development of digital city integration, gradually established the requirements of digital city construction for BIM technology. At present, in the construction industry, there is an increasing demand for lightweight BIM models, but the efficiency of rendering models on the web side is still to be improved. To address this pain point, this paper designs a lightweight platform for fast loading of BIM models on the Web side based on WebGL 3D engine and optimized processing through format conversion, which reduces the volume of models while retaining model information, improves the loading performance of models on the Web side, and provides a new solution for enterprises to build a lightweight platform for BIM.

With the development of the times, people will look toward the cold polar regions of exploration. Due to the extreme harsh environment, scientists had to develop a new type of protective clothing to meet the needs of people working outdoors. This paper establishes a mathematical model to study this new type of protective clothing. First, this article studies how to increase the thickness of the protective clothing under multiple constraints (funds, maximum bearing weight, thickness of the middle layer), so that the experimenter can stand outside for as long as possible. Secondly, this paper establishes a single-objective optimization model for this, taking the length of time the experimenter is standing outside as the optimization objective, and taking the amount of funds and the maximum bearing weight as the constraints. Finally, the optimal solution of the nonlinear optimization model is solved through programming, and the thickening scheme of the cryogenic protective clothing is obtained. As a result, to keep the thickness of the inner layer (fabric layer) unchanged, the thickness of the middle layer (functional layer) was increased to 0.45mm, and the thickness of the outermost layer (heat insulation layer) was increased to 1.2mm. Outdoors, the holding time with 15°C as the holding limit is 846.65s, and the holding time with 10°C as the holding limit is 870.23s.

Shear wave velocity (S-wave velocity) is the essential data for rock mechanics parameter prediction and reservoir compressibility evaluation in shale oil and gas sweet spot optimization. Owing to the extremely complex rock components and pore structure of shale reservoirs, it is usually difficult to represent the relationship between well logs and S-wave velocity accurately for theoretical petrophysical models and conventional empirical formulas. Within this context, a novel architecture of S-wave velocity estimation based on N-BEATS model was proposed. It can help improve the estimation accuracy by effectively incorporating sequence features of well logs. To illustrate its performance, a case study for shale reservoir in the Permian Fengcheng Formation in Mahu Sag of Junggar Basin, Xinjiang Oilfield, was performed. Seven kinds of conventional well logs were selected to establish the regression model. Compared with Xu-White model and eleven machine learning methods (MLs) and deep learning methods (DLs), the mean relative error (MRE) of N-BEATS has been reduced to 0.946%. The case study showed that N-BEATS model proposed can achieve better performance and generalization, which indicated its widespread application value to the other oil and gas exploration area.

Pipeline installation is one of the more critical aspects of offshore oilfield development and construction. Pipeline installation requires comprehensive consideration of the impact of installation methods, environmental conditions and ship movements on the structural safety of the pipeline. In this paper, a new calculation method is proposed to calculate the deformation degree of the pipeline and whether the deformation meets the ultimate stress check by combining the method of pipe coiling with matlab. The method used in this paper has the advantages of more accurate calculation results, faster calculation speed, stronger calculation accuracy and more intuitive calculation conclusion, which is of great significance for pipeline installation. For different types of submarine pipelines, it has universal applicability and can be applied to industrial practice.

In order to consider the influence of sedimentation and stress history on the settlement calculation and compression modulus, a formula for calculating the compression modulus and settlement of soil was derived based on the unified compression curve of the single logarithm model, and the applicability of the prediction formula was discussed by comparing the existing field monitoring data. Finally, a case study was conducted to explore the evolution of soil compression modulus and settlement under the conditions of sedimentation and stress history. The results show that: (1) For compression modulus, when the additional stress is small, the compression modulus depends on the early consolidation stress. With the increase of additional stress, the influence of the initial consolidation stress becomes less and less, making the compression modulus more and more affected by the additional stress. (2) With the increase of soil depth, the difference of sedimentation on settlement results becomes more obvious. Therefore, when calculating the settlement of deep soil layer, not only the influence of gravity stress, but also the influence of sedimentation on effective weight should be considered.

As a clean, safe and efficient energy, nuclear energy is one of the important solutions to realize clean energy heating in China. In this paper, the nuclear heating simulation model includes process system, control system, man-machine interface are established by using the modeling tool JADE. Through the simulation and analysis of steady-state and transient conditions, the rationality and correctness of the simulation model are verified. The model can be used for operating condition simulation, design optimization, and operator training, which can improve the digitalization level and enhance security and reliability of the nuclear heating units.

How to prevent and control the pollution of these construction wastes and keep the balance between urban development and ecological environment has become an important problem that we have to face. Based on the data research, this paper studies the prevention and Control of construction waste pollution in the construction of construction projects, standardize the behavior in the process of construction waste pollution prevention and control, and provide theoretical basis and support for the implementation of construction waste pollution prevention and control in China.

In engineering surveying, it is a common problem for geodetic height to convert to normal height, and the key is to calculate the abnormal value of elevation in a small range. Moreover, there are often errors in the observed value variables. Therefore, relevant mathematical models must be used to estimate parameter. Experimental Purpose: Taking the height abnormality fitting simulation data in engineering survey as an example, an application program is designed and implemented to obtain the optimal unbiased estimation of model parameters. Experimental Methods：With the help of the model parameter estimation theory (EIV model) and total least squares (TLS) with errors in variables, the data processing software is designed on the Visual Studio platform under the C# language environment to solve the cumbersome problem of model formulas in the data calculation process. Experimental results：It is completely feasible to apply the Visual Studio platform design to processing the height abnormality fitting calculation based on the EIV model. The internal coincidence accuracy of the traditional least square method is 5.216 mm, and the external coincidence accuracy is 6.948 mm; The inner coincidence accuracy of the total least square method is 5.216 mm, and the outer coincidence accuracy is 6.948 mm. The calculation results of the program show that the calculation results of the model parameters in the total least squares method are not significantly higher than that of the traditional least squares method under the same precision observation conditions.

Accurate prediction of the transition process of a pumped storage power station is an important issue in the design and operation of the power station.In this paper, based on the in-situ test of the super-high-head pumped storage power station, the numerical model of the hydraulic transition process of the water transmission and power generation system is first established, Then carried out the comparison calculation of the real machine load rejection test to verify the reliability of the numerical calculation and obtain the pressure pulsation and calculation error, Finally, the prediction and analysis of extreme control conditions are carried out, and the pressure pulsation and calculation error correction are carried out. The research results show that the prediction results of the control parameters under extreme conditions are all within the design standards, which guarantees the safety of the power station's operation. This analysis method can provide reference value in similar pumped storage power stations.

Chinese couplet is an art form with concise and strict antithesis. Given a sentence (namely an antecedent clause), people reply with another sentence (namely a subsequent clause) equal in length. It has made the machine-generated couplets readable and consistent for the result of existing deep learning methods. However, the generation process is character based which is different from the word-based use of Chinese. It is still a gap in semantic consistency between the results and the artificial creation. In this paper, a joint word segmentation of couplet is designed for the symmetry of couplet word segmentation results, and a word-based transformer couplet generation model is built to improve the semantic coherence of subsequent clauses generated. Moreover, word count information and part of speech information are added into the word vectors to provide the features of generating. Finally, the effectiveness of our model was confirmed in BLEU, Perplexity and human evaluation.

In the process of rapid urbanization, the spatial and temporal pattern of land use in Beijing has changed dramatically. How to realize the reasonable optimization of land use structure has become an important topic in land use management. Based on the results of structural optimization by using the multi-objective linear programming method (MOP model), the paper uses Future Land Use Simulation (FLUS model) to finish the spatial distribution optimization. The optimization of land use structure is mainly reflected in the following aspects: the urban spatial pattern has been optimized, and the ecological space area and the layout have improved; the concentration of construction land in the new urban area has increased; the quantity of water resources and other resources has been restored.

In order to solve the problems of large workload and relatively complex maintenance caused by the scripted input of power grid regulation documents, a knowledge modeling method of complex power grid regulation rules based on DMN is proposed. This method is based on the planning expression of power grid regulation and stability provisions based on DMN standard, so as to ensure the consistency and integrity of logic expression of power grid stability provisions. Practice has proved that, this method is applied to the provincial power grid regulation system and improves the intelligent level in the field of power grid regulation.

There exists many problems in the YaLong River Basin, such as the lacking of observational data, the large area of the basin, and the complex terrain. Wind resource assessment methods in traditional that based on observation data such as weather stations’ data are difficult to apply. The refined numerical simulation method is highly dependent on calculation resources, and it is difficult to apply wind resources assessment in the entire basin. As for the problems mentioned above, we proposed a method based on WRF/CALMET coupling. In this method, a multi-scale coupling is adopted to achieve hierarchical and progressive wind resource assessment in the YaLong River Basin. Lacking of data can be well overcame by the use of the mesoscale numerical models. The introduction of fluid dynamics simulation methods can simulate the impact mechanism of complex terrain on the wind field in detail. The proposed multi-scale coupled wind resource evaluation method can obtain balance between computing resources and evaluation results.

This paper compares the models trained on the different mortgage markets of different states in the USA. We use the measured performance (AUC) to generate a similarity matrix and then generate clusters. We regard AUC as a similarity between two models and use t-SNE method combined with k-means to construct clusters and visualize them. There are two main findings. One is that the model of MA (Massachusetts) is relatively similar to the model of CA (California) not NY (New York) although MA is next to NY and far from CA. The other is that the crisis in 2008 makes the differences between the model of OK (Oklahoma) and the model of TX (Texas) more obvious.

In view of the current contradiction between economic development and environmental restoration. We talk about the relevant information of ecological environment construction of specific regions and provinces and the Evaluation index system of Ecological civilization construction of China's provincial level (ECCI), and successfully build the investment model of ecological environment construction based on entropy weight method. The model is utilized to analyze and evaluate the GDP and ecological environment of each province and finally draw the conclusion of investment and construction of specific provinces and cities.

It is an important precondition for military Unmanned Aerial Vehicle (UAV) trajectory planning and mission deduction by modeling the threats faced by UAV in battlefield environment. We introduced the basic theory of Voronoi diagram for battlefield environment modeling and present Voronoi diagram based method of battlefield environment modeling for multirotor drones in three-dimensional space. In particularly, we propose a modeling process method by Voronoi diagram and calculate the trajectory cost of each path based on the threat level and energy consumption with flight altitude information.

In view of the current contradiction between economic development and environmental restoration. We talk about the relevant information of ecological environment construction of specific regions and provinces and the Evaluation index system of Ecological civilization construction of China's provincial level (ECCI), and successfully build the investment model of ecological environment construction based on entropy weight method. The model is utilized to analyze and evaluate the GDP and ecological environment of each province and finally draw the conclusion of investment and construction of specific provinces and cities.

C4 olefin is an important chemical industry raw material, but the traditional production method not only has a low output rate, but also produces many additional by-products, wasting valuable resources. Therefore, exploring the production of C4 olefins from ethanol to alleviate the status quo has become the mainstream direction of chemistry research. Aiming at practical problems, this paper establishes corresponding effective models based on experimental data at various temperatures under different catalysts, and obtains the specific relationships between C4 olefin selectivity and C4 olefin yield, catalyst combination and temperature, respectively, so as to obtain the optimal ethanol to C4 olefins plan.

In the traditional rocket launch and weapon test, in order to determine the space coordinates and speed of the flying target, the traditional two-station or multi-station theodolite rendezvous measurement method is used. Due to the accuracy of the theodolite angle measurement, the target positioning error increases linearly with the increase of distance. At present, the mainstream method for real-time high-precision calculation of exterior ballistics is the large triangle rendezvous measurement method, which has the advantages of flexible test stations, long operating distance, less accumulated data, and simple calculation method. It is a good solution for long-distance rendezvous measurement and other equipment real-time guidance. This paper optimizes and upgrades the intersection measurement method of the big triangle. When more than 3 fixed-site radars/USB devices are invested, a method based on Gauss-Markov trajectory estimation is designed. Ranging and speed measurement (nRR’, >3) for joint calculation. When there are more device, the ballistic accuracy obtained by calculation is higher, which is suitable for real-time data processing of rocket launch and weapon test.

The WF315A drum hot air conditioning cylinder is the main equipment for the process of tobacco silk production. The main problem at present is not stable enough of the outlet moisture content. The large lag and uncertainty of the leaf moisturizing process made it impossible to achieve closed-loop automatic controls of the conditioning cylinder. The methods of energy and material balance were used to analyze heat and water exchange between steam and leaves. And the dynamic prediction models of the opening of the film valve and the water/heat transfer were established. Through actual production verification, the relative error of the dynamic prediction model is within ∓0.17%, which meets the production requirements of ±0.50%. At the same time, two potential industrial applications were proposed, including the prediction of equipment operating status and the establishment of automatic control systems. This work can also provide a theoretical basis of system optimization to achieve energy and material savings.

Mobile Edge Computing (MEC) effectively improves user service quality by sinking the computing center to the edge of the neighboring terminal users. However, insufficient MEC cloud computing resources have created many obstacles to the promotion and application of edge cloud technology. Aiming at the problem of MEC computing offloading and resource allocation under the condition of limited computing resources, this paper builds a Stackelberg master-slave game model to conduct "cloud-side" interactive analysis on MEC revenue and user service quality, and uses differentiated pricing strategies to strengthen the constraints on offloading strategies. Obtain the largest MEC revenue unloading ratio. Finally, the optimal simulated annealing algorithm is used to iterate the optimal allocation strategy of MEC computing resources. Simulations show that the solution in this paper can effectively improve the MEC rate of return on the basis of optimizing the quality of user experience. This method has guiding significance for the study of unloading problems under resource-constrained conditions.

Online bidding has become more and more common in the market economy, but there still exists cheating phenomena, such as rent-seeking and bid-rigging. To study the characteristics of bidding behavior, we designed a bidding game model based on multi-agents to simulate the game between tendering and bidding agents, visualizing and collecting data from multi-rounds of multi-agent game process, quantifying the impact of the existence and non-existence of blockchain to suppress rent-seeking and bid-rigging. The data of the model support the theory that combining e-bidding platform with blockchain can effectively reduce the fraud costs in bidding process. The research provides theoretical and practical evidence for improving the bidding environment.

The combined guidance system based on inertial navigation is most widely used in the flying vehicle. In order to meet the demand of the rapid evaluation of the modern aircraft guidance system, this paper constructs a model-driven inertial navigation error index visual rapid evaluation platform. First of all, according to the typical error indicators and error transmission relations, the error transmission mathematical model of impact point error is established. Then, the initial visual software debugging interface is realized by C language. Finally, depending on Modelica language for optimized programming, a comprehensive platform for the rapid evaluation of the inertial navigation error index is established. Through real-time calculation of ballistic data, the analysis of impact point error under the combinations of different inertial navigation error indexes is quickly completed. The simulation results show that the design efficiency is greatly improved and the platform lays a good foundation for the development of aircraft.

When the radar is tracking an air target, there is a short-term interruption of the track. The accurate prediction of the target track can help improve the accuracy of the track association. In response to the problem of low calculation accuracy of traditional track prediction algorithms, this article introduces and adopts a long short-term memory algorithm (Long Short − Term Memory) track prediction method. Use data to train the model, and use the mean square error (MSE) as an evaluation indicator to predict the future location of the target. The final simulation test results show that the algorithm can use the changing law of the air target's movement state to predict the target's movement state in a certain time in the future, which demonstrates the feasibility of the proposed algorithm in the problem of interrupted track prediction.

This paper deeply analyzes the model-based development and test verification mechanism of SCADE development environment. In this paper, based on DSP embedded software development, the Model-Based Development (MBD) process of requirement modeling, functional modeling, model simulation and model test coverage (MTC) is practiced using SCADE. The above practice process verifies the feasibility and superiority of SCADE in embedded software development and improves the efficiency of embedded software development.

This paper analyzes the necessity of applying architecture pattern in complex information system modeling,and first puts forward the definition of architecture mining, based on the process of architecture mining and the method of architecture mining from the aspects of architecture design data mining; and second puts forward how to design architecture pattern template, in the end discusses the role of Architecture pattern in architecture modeling and optimization.

It is difficult to predict the oil and gas productivity when multiple production sections are used to produce multiple reservoirs at the same time. To solve this problem, a semi-analytical productivity prediction model of double-step horizontal wells is established. Reservoir anisotropy, properties, seepage interference, wellbore pressure drop are considered in this model. The discretization method is applied to divide the double-step horizontal well into several sections for the coupling of reservoir model and wellbore model based on some relevant theories of seepage mechanics, fluid mechanics and numerical analysis. Two double-step horizontal wells in the Minghuazhen Formation and Dongying Formation in Caofeidian Oilfield are used for instance verification to analyze the production of each micro-element in the wellbore and the distribution of cumulative production along the wellbore. The results show that the distribution of the micro-element sections of the upper and lower horizontal sections of the double-step horizontal well presents a typical "U"-shaped distribution. The heel and toe sections of the horizontal section have a larger production, while the middle section has a smaller production. Comparing the productivity predicted by the model of the double-step horizontal well built in this paper with the actual well productivity, it can be seen that the relative error of the well D is 4.47% and the relative error of the well F is 5.8%. The prediction error is controlled within 10%, the model established in this paper has good prediction accuracy. This paper proposes a wellbore-reservoir coupled double-step horizontal well productivity model. This model can effectively predict the prediction distribution, pressure distribution and cumulative production distribution along each micro-element section of the wellbore and the model has good applicability in the actual oil field.

High-speed railway construction has become a new driving force for the development of national economy. As an important equipment of modern railway, railway signal infrastructure plays an irreplaceable role in ensuring traffic safety and improving transportation efficiency. Based on the structure and principle of signal infrastructure equipment, this paper studies the training simulation system based on virtual reality technology. Combined with Unity3D engine, it realizes the guided teaching of signal infrastructure equipment's structure composition, 3D model demonstration of action process, maintenance operation process and fault treatment. Students can quickly understand the technical parameters ,the overall structure and operation principle of signal infrastructure equipment, and then improve the training effect.

The oil stored in oil depot storage tanks is flammable, explosive and easy to diffuse, once a fire and explosion accident occurs, it will cause heavy losses. In this paper, the fire and explosion accidents in oil storage tank area are simulated and analyzed. The oil steam cloud is formed due to the leakage of underground oil storage tank area and the evaporation of oil vapor. Firstly, for the underground oil storage tank area, TNT equivalent analysis method is used to analyze the influence range of the oil steam cloud explosion when encountering ignition source. Then，for the aboveground storage tank area, the pool fire mathematical model is used to determine the influence degree of fire. Finally, based on the above analysis, the corresponding risk control measures are put forward.

This paper studies the optimal operation of integrated energy system and the participation mechanism of demand side response, establishes the operation optimization model of integrated energy system, and puts forward the transaction strategy formulation process of participating in demand side response. Finally, an example is given to verify that the proposed transaction mechanism and operation optimization model can promote the integrated energy system to participate in demand response, improve the system new energy consumption level and reduce the system operation cost.

Based on big data simulation, three ventilation systems including mixing ventilation, displacement ventilation and diffuse ceiling ventilation are numerically simulated and compared in an office room. Ventilation performances of these three ventilation systems are obtained through analysing indoor air velocity distribution, temperature distribution, PMV, age of air and ventilation efficiency. Results show that the vertical temperature gradient of diffuse ceiling ventilation is 0.30 °C/m. Compared with displacement ventilation and mixing ventilation, the indoor vertical temperature gradient of diffuse ceiling ventilation is reduced by 3.95°C/m and 1.22°C/m, respectively. The indoor temperature distribution is relatively uniform, and there is no local thermal discomfort in the occupied zone. In addition, the indoor air velocity gradient of diffuse ceiling ventilation is very small, and there is no cold air draught even when the supplied air has high momentum. The indoor PMV is also within the requirement of regulations, and the thermal comfort can be greatly improved. The indoor air age of diffuse ceiling ventilation is 539 s, with the ventilation efficiency close to 1.0. Although it is less than that of displacement ventilation, the effects of ventilation and heat rejection are still excellent. This study can provide technical basis for the application of diffuse ceiling ventilation in practical projects.

Accurate characterisation of fracture detail is fundamental to the fine description of a reservoir's structure and the deeper understanding of the reservoir. As oil and gas reservoirs gradually enter the middle and late stages of development, there is an increasing demand for fine identification of small fractures. However, due to the influence of burial depth and surface conditions, the current seismic data is more difficult to identify small fractures in the middle and late stages of development, and the identification accuracy is low. Combined with current methods of artificial intelligence big data analysis, this paper proposes an unsupervised mode fracture identification technique under superiority frequency conditions. The frequency that can reflect different scales of fractures is preferentially selected, on the basis of which a variety of different types of geometric fracture attributes are extracted, and then unsupervised pattern recognition algorithms are applied to allow the computer to automatically set and classify certain fractures with common characteristics by learning to compare, and to portray the spreading characteristics of single-scale and full-scale fractures, so as to improve the lateral discrimination ability of fractures and effectively enhance fracture recognition Through the application in the Y area, it has achieved fine fracture mapping within the gas reservoir, saving the interpreters' effort and time in analysing data, and obtaining ideal fracture pattern results, deepening the understanding of oil and gas reservoirs, and effectively supporting the evaluation of oil and gas reservoir development potential and later well deployment.

A numerical simulation analysis based on Computational Fluid Dynamics (CFD) was used to study the leakage of ammonia storage tank in the Beijing Winter Olympics snowmobile sled stadium. The leak location and leak flow rate were varied to investigate their effects on the dispersion profile. Different positions of leakage points of ammonia storage tank led to different dangerous regions. With the same flow rate, the dangerous area caused by the leakage on the left side of the liquid ammonia storage tank is the largest. However, the leakage from the top of the storage tank has almost no effect on the ammonia concentration near the ground. When the bottom leaks, the high concentration of ammonia gas is mainly gather near the ground. The work in this paper can provide technical support for improving the safety of ammonia leakage accident.

With the continuous advancement of the protection process of intangible cultural heritage, the protection and inheritance of the Wind & Rain bridge of Dong Nationality in Sanjiang, Guangxi, as one of the key symbols of the intangible culture of construction technology of the Dong wooden architecture, has received corresponding attention, but it is facing many difficulties and challenges under the rapid social evolution of digital development. In this paper, BIM technology is integrated into the protection and inheritance of the Wind and Rain Bridges, through indepth research and coordination of data collection, building description, digital modeling, information integration and int eraction of Wind and Rain Bridges, it provides thoughts for the protection and inheritance of wooden construction cultur e of Dong minority in Sanjiang.

In order to solve the problem that it is difficult to accurately judge the rationality of clothing virtual simulation design, a clothing virtual simulation structure design method based on clothing comfort pressure threshold is proposed. By systematically combing the relevant clothing structure and location pressure threshold affecting clothing comfort, young female students who meet the size 160 / 84A standard are selected as the experimental objects; the data of key characteristic parts of the experimental human body are obtained by using the vertical white light three-dimensional human body scanning system; the construction of digital human model of CLO virtual simulation design system is completed; the slim basic women’s pants are used as the experimental samples; and 40 count plain 100% cotton fabric is used as the experimental fabric to complete the virtual fitting experiment of the experimental sample clothing. The location pressure data of the key structure of the experimental sample clothing are collected. The experimental pressure data with the clothing comfort pressure threshold data are compared and analyzedby using Excel software. The virtual simulation verification, optimization and correction of the rationality of the clothing structure are completed. The experimental results show that this method can quickly and accurately judge the rationality of virtual garment structure design, and effectively improve the accuracy of clothing structure virtual simulation design.

Using the latest world geomagnetic models WMM2020 and IGRF13, the spatial distribution characteristics of five geomagnetic elements such as the total magnetic field intensity F described by the two models are analyzed. Then, the annual variation rate of each element with an interval of one year is calculated and plotted for analysis. In this process, the differences between the two models in describing the main magnetic field in mainland China are analyzed. The results show that the two models can better describe the distribution characteristics of China's mainland.Total magnetic intensity F, horizontal component h, vertical component Z and magnetic inclination I are roughly distributed along the zonal direction in China, and the magnetic declination D is higher in the west and lower in the east around the northwest peak and northeast trough. The accuracy of the two models is close to each other, with similar distribution characteristics and slight difference in annual variation rate. The two models can only represent the approximate change of magnetic field to a certain extent, which cloud not meet the needs of practical application. Therefore, it is urgent for China to reconstruct high-precision regional model combined with long-term high-precision measured data.

In order to improve the ventilation efficiency of greenhouse under the condition of no wind or low wind speed and to ensure the supply of carbon dioxide to plants, a CFD greenhouse three-dimensional thermal pr roof vent height essure ventilation model was established to simulate with the background of Zhengzhou regional climate environment, and the changes of temperature distribution, pressure distribution, flow field and roof ventilation flow inside the greenhouse were studied by raising the roof vent height and changing the roof ventilation area. The results show: Increasing the roof ventilation area effectively increases the roof ventilation flow rate, and the roof ventilation flow rate increases when the ratio of roof ventilation area to greenhouse floor area reaches 2%-4%. The ratio of roof ventilation area to greenhouse area 2%-4% flow rate increase is higher, 4%-6% flow rate increase is significantly lower, when increased to 4%, the increase of roof ventilation flow rate will have a significant decrease. Because the thermal pressure ventilation relies on the heat source from the sun, the internal wind generated is more stable.

The integrated energy system connects various types of energy closely to form a complex multi-energy flow network to improve energy quality and support large-scale renewable energy access. To study the technologies of multi-energy flow modeling and simulation for the integrated energy system, the coupling characteristics and differences of mul-ti-energy flow are first summarized. Then three multi-energy flow unified modeling methods are introduced, i.e., en-ergy hub modeling method, unified energy path modeling method and energy network modeling method. In terms of model solving, the advantages and disadvantages of unified solution and decomposition solution are analyzed and compared. On this basis, the multi-period simulation process of a typical IES is expounded, and the difficulties and future of simulation technology are analyzed and prospected.

Visible light and thermal infrared (RGBT) data contain different levels of information about the target, and how to use them effectively plays a crucial role in the representation of the target appearance in RGBT tracking. Existing work has focused on the integration of information from modality-shared features and modality-specific features. These approaches effectively deploy modality-shared cues and modality-specific attributes, ignoring the potential value of multi-layer shared cues of different modalities. To this end, a new multi-feature extraction-based infrared and visible target tracking algorithm is proposed. The tracking algorithm consists of a multi-layer shared fusion network, modal complementary network and target regression network that performs multi-layer modality-sharing, modality-specific and target probability prediction feature learning. Extensive experiments are conducted on the RGBT tracking benchmark dataset to achieve real-time tracking in terms of tracking speed and also show superior performance in comparison with other advanced RGB and RGBT tracking algorithms.

To study the gait planning of a quadruped robot when walking on parallel ground, this paper takes a self-developed directdrive quadruped robot as the research object and conducts research from both structure and simulation. The method used here is the combination of SolidWorks and ADAMS. Simulation calculations such as geometric processing, setting constraints, and designing contact are performed on the quadruped robot. At the same time, we define the 8 motor drives and come up with the gait planning, a method for processing the working conditions of the quadruped robot on flat ground is proposed. The results show that the displacement curve of the robot presents a straight-up motion law, the maximum displacement reaches 900mm, the overall motion tends to be sinusoidal, and the motion speed is about 75mm/s. This indicates that the robot has good smooth movement performance.

In order to avoid battery damage under extreme working conditions such as vehicle collision, which leads to the safety problems of new energy vehicles, the mechanical properties of a battery module under extrusion condition were studied in this paper. Based on finite element method, the simulation platform of battery pack extruded by sphere and cylinder is established. Maximum strain of structure is obtained, from which the end plate, side plate and busbar are identified as the most deformed components. Excessive deformation reveals the risk of damage to the battery. Therefore, 5 proposals on structural optimization are summarized to enhance the mechanical performance of this battery module.

In this paper, a new simulation method for the transducer acoustics field in multilayer irregular media boundaries is presented. Based on the acoustic wave vibration equation, Snell's law, other physical models, and finite element methods, this study uses the method by overlapping the media space model and the boundary surface model to solve the problem of simulating the transducer acoustics field in multilayer irregular media boundaries and reduces the computational redundancy. The simulation software uses a point drawing algorithm and OpenGL to generate the 3D image of the media space model. The simulation system achieves the simulation of the transient state acoustic field at any moment and analysis the effect of any point source at the focal plane by saving the virtual point source's vibration equation at each sampling point. In addition, this study demonstrates the feasibility of the simulation method by comparing the simulation results with the real measurement result of acoustic pressure distribution.

In the force analysis of special vehicle leveling system, usually only the force change of leveling leg in the leveling process is analyzed, but the force analysis of leveling leg in the ultimate condition is less.Therefore, the mathematical model of force variation of special vehicle leveling leg was constructed, and the ultimate condition of force variation of special vehicle leveling leg was simulated by ADAMS software.The results show that the load variation of special vehicle leveling leg under the limit condition matches with the mathematical model, which can be used as the theoretical basis for the boundary condition of special vehicle leveling leg design.

This paper focuses on the construction influence of the foundation pit on the adjacent existing cable tunnel. And the retaining structure of the pit is soil nailing wall. Three-dimensional finite difference method is used to simulate the influence of the foundation pit excavation on the tunnel. And many influence factors are considered in analyzing disturbing deformation and safety of the tunnel, such as pit depth, spacing between pit and tunnel, and buried depth of the tunnel. The calculation results show that the horizontal displacement is the dominant deformation on the slope stability for the foundation pit with soil nailing wall. With the increase of the pit depth, the safety of tunnel structure is non-linearly weakened. While the spacing between pit and tunnel became large, the tunnel safety increases nonlinearly. But the safety of the tunnel increases firstly and then decreases with the increase of the tunnel buried depth. The research results can provide reference for the protection of the existing cable tunnels while adjacent foundation pit construction.

The purpose of this paper is to explore how to independently develop a three-dimensional solid modeling software for microwave tube through the research of OpenGL and computer graphics theory, and then realize a microwave tube threedimensional measurement and annotation system with perfect functions from the bottom. Using this system, the microwave tube modeling engineer can observe the built microwave tube model more intuitively and conveniently, and can measure and annotate the microwave tube model, and obtain the measurement results through human-computer interaction.

Based on the mathematical model of bank slope seepage under the distribution of atomized rain intensity, the relationship between the distribution of atomized rain intensity and the safety factor of slope stability under different geotechnical materials is discussed. The distribution of seepage field load under different distribution of atomized rain intensity is given.Based on the principle of limit equilibrium method, the calculation model of slope stability safety factor is established, and the corresponding stability safety factor is calculated.The relationship curve between the distribution of atomized rain intensity and the slope stability safety coefficient is given. The results show that the slope stability analysis method under the continuous distribution of atomized rain intensity can truly reflect the variation characteristics between the distribution of atomized rain intensity and the slope stability safety.

The calculation and solving are made on high temperature gas expanding in water for the later period of emergency gas jet blowing-off, the equations on mass, energy and gas state in that period are established and the calculation models are also built for the performance parameters such as the heat and water discharge flow during high temperature gas expanding for water discharging. Thus the engineering calculation methods are improved for the complex process of emergency gas blowing-off.

As the proportion of photovoltaic, wind power and other new energy in the power system gradually increases, the proportion of conventional power supply gradually decreases, therefore, the overall inertia of the system decreases，and the primary frequency modulation capability of the system gradually weakens. This paper mainly studies how to set the system control gain in the future low inertia system dominated by photovoltaic. Firstly, the proportion of photovoltaic, the inertia time constant of the system and the parameters of the saturation link should be considered, then the influence of changing the three factors on the frequency changing rate of the system is analyzed by simulation; then combined with the actual power system requirements, the best system control gain value can be obtained by taking the system frequency change rate as the objective function and using PSO optimization algorithm through simulation analysis.

Tire-soil relationship is an important research topic in terramechanics. In this paper, a tire-soil interaction model considering soil cohesion is established based on discrete element method (DEM). Through the coupling of EDEM and RecurDyn, the traction characteristics of tire under different slip ratio and the same load were studied, and the microscopic behavior of the particles was analyzed. The results show that with the slip ratio increasing from 0% to 75%, the value of the drawbar pull increase from about -1000N to about 2000N and the relative motion of particles becomes more and more violent.

In this paper, the finite element simulation method is used to conduct a numerical study on the characteristics of microwave plasma chemical vapor deposition (MPCVD) and hydrogen plasma discharge. The multi-physics coupling of electromagnetic field and plasma field in MPCVD chamber is established in COMSOL. And corresponding twodimensional model is also built combing finite element high-frequency Maxwell solver, drift diffusion solver and heat transfer solver. The characteristics of plasma deduced from different deposition platform designs are analyzed. Our simulations reveal that even minor structure modifications of the deposition platform greatly change the distribution of electron density, thereby affecting the growth of homoepitaxial and polycrystalline. And thus deposition platform design, including its shape and dimension, is fundamentally important in crystal growth process.

Radar Emitter Individual Identification is a technique to extract the radio fingerprint features of radar by means of external feature measurement of the radar signal, in order to identify radar emitter individuals. In the past few years, the related theories and practical applications of radar emitter individual identification technology had been continuously improved, and the research on radio frequency fingerprint extraction methods has made great progress. Based on domestic and foreign academic achievements, the current research status is classified by deep learning methods, which are specifically divided into two types of traditional SEI methods and deep learning SEI methods. Finally, several potential research directions for Radar Emitter Individual Identification are analyzed and explored.

Since Xinfengjiang Reservoir began to store water, earthquakes occurred frequently in the reservoir area. Even now, earthquakes are still frequently raging in that region. The fortification intensity of the reservoir dam was 6 degrees at the initial stage of construction, which was obviously low. After that, it has been reinforced twice, so it is necessary to analyze the seismic response of the reinforced dam. In this paper, the strong earthquake records of the dam and finite element simulation technology are used to analyze the seismic response of the dam. The results show that: under the action of small earthquakes, the acceleration response of the dam sections on both banks is larger along the dam direction, while the acceleration response of the middle dam section along the river direction and in the vertical direction is larger, and the dam amplification is obvious. Under the action of a fortification earthquake, the maximum displacement of the dam occurs at the top of the dam, and the major tensile stress is at the downstream outlet and dam heel, but they are all within the safe range.

In the middle and late stage of water flooding reservoir, the existence of high permeability channel of water flooding affects water flooding efficiency and thus affects oil recovery. Nitrogen foam flooding is one of the important ways to improve oil recovery after water flooding, but foam flooding only emphasizes the ability of foam to expand sweep volume, but recent studies show that it also needs to enhance its oil washing ability. To solve this problem, reservoir numerical simulation software CMG was used to simulate nitrogen foam flooding. The results show that the effect of injecting multiple nitrogen foam slug and surfactant slug alternately is better than that of injecting only nitrogen foam, and the effect of increasing oil and reducing water cut becomes better with the increase of nitrogen foam, surfactant slug size and gas liquid ratio.

The economic benefit of engineering is closely related to the schedule of the project. Nowadays, the progress of transmission line project still mainly depends on manual report and cannot reflect the real progress of the field. To strengthen schedule management, the progress recognition algorithm for the transmission line project based on YOLOv3 is designed, and the intelligent recognition rules of the transmission line project progress are established. By identifying concrete protection cap, tower head and insulator string, the progress intelligent recognition of transmission line project is realized. The precision rate of the algorithm is 100% and the recall rate is over 90%.

With the continuous improvement of China's comprehensive transportation system and tourism gradually becoming an important strategic pillar industry of the national economy, the integrated development of transportation and tourism has become a new trend in the development of traditional economic transformation. Based on the Qimen-Wuyuan Tourism Highway, this paper conducts research on the integration of traffic and travel big data and tourism resources, and uses traffic flow and regional tourism big data to propose a road traffic and travel fusion data service and resource architecture, so as to achieve the integration of traffic and tourism data. The service experience in the travel process, through cloud computing, proposes more optimized solutions in the integration of travel experience, radiation activation, and product planning, and builds a branded and shared transportation and travel integration development road industry chain.

Based on the research and analysis of data, this paper compares the carbon emission reduction basic legal systems of China and South Korea, and expounds the similarities and differences between the two countries. Moreover, this paper attempts to put forward constructive suggestions on the carbon market cooperation between the two countries by analyzing the feasibility, possible difficulties and obstacles of the current carbon market cohesion. Based on the above contents, this paper also discusses the space of climate cooperation in Northeast Asia.

In order to predict the compressive strength of blast furnace slag-fly ash concrete more accurately, a GA-BP model for compressive strength prediction was developed by improving the initial weights and thresholds of BP neural network through genetic algorithm on MATLAB platform. The prediction results of artificial neural network (BP), random forest (RF), support vector machine (SVM), extreme learning machine (ELM) and multiple nonlinear regression (MnLR) were compared and analyzed, and the GA-BP model has obvious advantages in terms of prediction accuracy and model stability. Thus, it provides guidance for the quality assessment of blast furnace slag-fly ash concrete, which has important practical value.

Based on China's coastal coal transportation market, this paper establishes ARMA model, and carries out data analysis and prediction by using China coastal coal transport price index (CBCFI). The analysis results show that the prediction accuracy of the model is high. With the increase of time, the prediction accuracy of ARMA model is also declining. Therefore, ARMA model is suitable for short-term prediction of cbcfi, so as to provide decision-making suggestions for shipping companies and shipping operators and avoid risks.

Potable water detection is an important issue in human society. Whether human have access to water with drinkable quality is crucial due to health concern. Before developing some techniques to ensure the water quality, it is important to understand some properties of the water, which can give a general view of how water quality is affected. Nowadays, machine learning is getting increasingly popular and it can be applied to many fields and solve plenty of problems in practice. Designing a machine learning predictor based on water properties can be drastically helpful to determine whether a water source is safe to consume. This article is based on the research which uses five common machine learning algorithms: k Nearest Neighbors, Decision Tree, Random Forest, Neural Network, and Support Vector Machine to train a model which predicts whether the water in the dataset is human consumable. By comparing the performance among these five models, as a conclusion, we find Random Forest and Support Vector Machine have the highest accuracy.

Aiming at the problems of low detection accuracy and poor generalization ability in multi-information fire detection, a fire detection method based on improved random forest algorithm was proposed. The method was considered comprehensively from the data, characteristics and model. Firstly, an improved random forest algorithm was designed to build a fire detection model. Secondly,feature selection was carried out through Pearson correlation coefficient feature extraction rule, and then the fire factor data were balanced. Finally, through the simulation experiment, the comparison with the results of the standard Random Forest algorithm showed that the overall accuracy of the improved random forest algorithm was 93.33%, 4.44% higher than the standard random forest algorithm.

This paper analyses the data of document examination, supplementary verification, found problems and experience feedback during the inspection of China’s imported civil nuclear safety equipment from 2011 to 2020, and analyses the problems that may be encountered in the follow-up inspection work. Based on the analysis of inspection data, suggestions are made in terms of personnel team building, supervision methods, examination methods, system construction, etc., to strengthen the construction of the inspection capacity of imported nuclear safety equipment and ensure the quality of imported nuclear safety equipment is under control.

Due to the long-term and future presupposition of urban planning, public participation has gradually become an indispensable link in urban planning. By analyzing the way big data intervenes in public participation, the importance and possibility of establishing a public participation system framework based on big data are clarified. Finally, by exploring how to build a two-way interactive public participation system between the government and the public, this paper puts forward some ideas on the public data platform built by using big data. We hope to promote the development of public participation in urban planning practice through the exploration of the system framework and big data platform.

With the continuous development of network technology and Internet technology, the current amount of network multimedia data is increasing, which affects the supervision of network public opinion to a certain extent. In order to ensure the extraction efficiency of the element information of network public opinion association subject, this paper deeply analyzes the mining methods of the public opinion association subject in the network multimedia data, that is, in the specific research, the relevant contents of the network public opinion association are taken as the starting point to analyze the data mining methods. Through research and exploration, the effective application of data mining methods of public opinion related topics can improve the mining efficiency and accuracy of network multimedia data, and provide effective data support for the supervision of network public opinion, that is, to support the public network with various opinions, which is conducive to supervision.

In order to compare and analyze the accuracy and applicability of Global Precipitation Measurement Mission (IMERG) satellite precipitation products in Nandu River Basin, the daily precipitation data of 51 ground observation stations in Nandu River Basin from 2014 to 2018 is collected in this paper, and the evaluation index such as Pearson correlation coefficient (CC), root mean square error (RMSE), relative bias (BIAS) and mean absolute error (MAE) are chosen to evaluate the accuracy and applicability of GPM IMERG satellite precipitation products, including Early Run, Late Run and Final Run, on daily and monthly scales. The results show that: (1) the correlation coefficient between the three types of GPM precipitation products and ground station observation dataset is significantly improved on the monthly scale compared with the daily scale. (2) It can be seen that the accuracy of the three types of GPM products is related to the number of data revisions. With the increase of the number of revisions, the accuracy of data continues to rise. In general, GPM precipitation products have high accuracy and applicability in Nandu River Basin. The results of this paper are expected to provide some support for the application of GPM IMERG satellite precipitation dataset in hydrological research and water resources management in Nandu River Basin, and have a certain reference value for the relevant research in other basins.

In order to effectively compensate the graph image drift problem generated in the photoelectric stabilized platform operational process, this paper uses a numerical control technology based on the Verilog language algorithm to perform speed command operations on the fast reflector, and operates the fast reflector to compensate the photoelectric stabilized platform image shift. The Verilog language algorithm used in the article is written in the field programmable gate array FPGA, and combined with RS422 to manipulate the fast mirror, which can effectively improve the control accuracy of the fast mirror. According to the simulation experiment, when setting the 3ms integration time, the Verilog language algorithm can make the fast mirror move more accurately than the single CPU, achieve better image shift compensation effect, and improve the performance of the photoelectric stabilized platform.

In the process of analysis and design of fire control system, we need to use firing table data with practical reference value, but such data is often not easy to obtain. In this paper, according to the rigid principle of gun firing process, based on the fitting function of the open firing table, the one-dimensional firing table which only contains the firing results of ground targets is extended to the two-dimensional firing table which contains the height by the method of digital simulation. The shooting table includes the basic shooting table under ideal conditions and the modified shooting table under different meteorological and ballistic conditions. The rationality of the modified shooting table is verified by the way of shooting table fitting and trajectory reconstruction. This method provides an effective method for the process of building gun firing table. With this method, firing table can be generated for further scientific research under the condition of less data.

The aim of the project is to predict and analyse broad trends across the US economy using stock data from mainstream companies in six industries on Forbes 2000 and data from COVID-19. A time series analysis approach was used to predict the daily increases in each company's share price. The following five supervised learning techniques (logistic regression, random forest, decision tree, neural network and XGBoost) were used. As the accuracy of the results predicted by the different models for each company varies considerably, only the results predicted by the most accurate model for each company have been selected for analysed. The results show that the Electronic Pleased Technology Industry and the Social Entertainment Internet Industry remain break-even for COVID-19; the E-Commerce Industry shows a significant increase; The Financial Services Industry shows a significant drop in share price, while the Insurance Industry and Pharmaceutical Industry show a small drop in share price.

Clipping is a very important function in two-dimensional sketches, and users can obtain the desired curve through clipping. This paper mainly studies the clipping problem of the second-order Bezier curve. First, solve the problem of intersection between Bezier curve and line segment, circle, Bezier curve, etc. Then, by traversing the intersection point, determine the intersection point on the two sides closest to the mouse point, and determine whether the cut is the middle section, the start or end section, or the entire curve. Get the clipping algorithm of Bezier curve. Finally, the cutting function was applied to the MTSS simulation software independently developed by the research group, and good results were obtained, which improved the modeling ability of MTSS two-dimensional sketches.

To study the influence of tire parameters on automotive ride comfort, the sensitivity of each parameter is calculated from a control variable method. Based on the tire test data, this paper establishes the CDTire simulation model. The virtual simulation of automotive ride comfort is conducted by combining multibody dynamics with virtual pavement technology. After comparing the results of test and simulation, the rationality and accuracy of the model are verified and the tire parameter variables are thus designed according to the control variable method. The sensitivity of the results is analyzed to obtain the influence degree of each tire parameter on the automotive ride comfort.

Target tracking is a technology that uses video or image sequence information to predict the motion state and position of a target through modeling. It is a critical basic problem of computer vision, with important theoretical research significance, and has a wide range of applications in autonomous driving, UAV navigation, video surveillance and other aspects. In recent years, with the continuous improvement of hardware facilities and the emergence of deep learning methods, target tracking technology has been rapidly developed. This paper first reviews the previous target tracking methods, and points out that deep learning provides new opportunities for the research of target tracking, then introduces the current target tracking method based on deep learning and explains its working mechanism in depth. After that, this article establishes the evaluation criteria suitable for deep learning target tracking. Finally, it analyzes the problems of deep learning methods in target tracking, and makes a prospect for the future development direction.

The new generation of information technology is gradually being applied to various fields. Information technology represented by the Internet of Things and blockchain is applied to traceability, which solves the problems of original traceability information distortion, high collection cost, and multi-link information interoperability, and injects new vitality into traceability research. This paper sorted out 1184 selected documents on the traceability topic in the new generation of information technology environment from 2010 to 2019. In order to interpret the connotation of the theme, calculate the information gain of 1609 keywords to 17 categories of themes, and select the top five keywords of each theme's information gain to analyze the theme connotation. The 17 topics are mainly divided into initial exploration topics, current hot topics, future trend topics, and stable topics through literature time series analysis. The research results are as follows: from the subject point of view, the research on "Traceability + Radio Frequency Identification" has been relatively mature; "Traceability + Blockchain", "Traceability + Internet of Things" and others are current research hotspots. Eight categories of themes such as "traceability + QR code", "source traceability + big data", "quality and safety" are in the initial exploration period, their subsequent evolutions are determined on social needs and the development of technology.

The spherical radio telescope uses a flexible cable net as the supporting structure. The main cable net is composed of a flexible main cable according to the short-range triangular mesh, and a reflection panel is installed on each triangular mesh. According to the adjustment method of spherical radio telescope reflection panel, this paper analyzes each reflection panel which constitutes a radio telescope. When the observation object is located just above the telescope, an ideal working parabolic optimization model considering the adjustment constraint of the reflection panel is established. The angle of the reflection panel is changed by adjusting the length of the cable under the main cable node, and then the shape of the panel plane is changed. The optimal working parabolic is obtained by using the golden section algorithm. When the position of the observation celestial body changes, the position of the working parabolic surface also changes with it. An optimization model of the optimal adjustment scheme of the main cable node is established to solve the optimal ideal working parabolic surface. For the morphological control problem of the main cable network, the telescopic amount of the actuator is planned and optimized, and the optimal control scheme is solved by using the improved butterfly optimization algorithm.

Frequency is a fundamental parameter in the field of Electronic technology. As a basic measuring instrument, the digital frequency meter is extensively applied for its features such as high precision, fast speed, digital display. This paper describes a very simple and data transmittable design of a Digital Frequency Meter using a PIC microcontroller with some simple functions. This digital frequency meter has a range of frequency measurement from 1Hz to 100kHz and a resolution of 1hz and accuracy less than 0.5%. Digital Frequency Meter measures the frequency and displays its data on 1602 LCD screen with a unit in thousands(kHz); the usage of microcontroller enables it to toggle measuring mode, pause the data display and transmit data to other microcontrollers for extra uses.

Assembly simulation plays a very important role in the assembly process of large and complex products.The design of the assembly tree structure is related to the flexibility and scalability of assembly module development.This paper uses the Reference Virtual Tree and Component Real Tree to design the assembly tree structure,Reference Virtual Tree to manage component data and rendering updates,and Component Real Tree management to obtain complete assembly tree structure information.Then,the feasibility and superiority of the design of the assembly tree structure are analyzed by analyzing the effect of the designed assembly tree structure on the support of assembly functions such as component price positioning,collision detection and constraint association.Finally,the assembly simulation module is embedded in the MTSS simulation software to expand the 3D modeling function and improve the modeling ability

A new method for polarization dependence analysis of periodic nanostructured SERS substrates was proposed. The method combines the Fourier transform and the wave vector matching model of surface plasmon polariton (SPP). The periodic nanostructured SERS substrate was sensitive to the polarization Angle of incident light, which seriously affected the application of the substrate in practical detection. In this paper, based on the Drude model, the wave vector matching conditions of metal surface plasmas excited by incident light are studied. The compensation wave vector deviation coefficient η which characterizes the weakening degree of surface electric field intensity under different polarization angles of incident light is defined. The finite-difference time-domain (FDTD) and η -value analysis of one-dimensional and two-dimensional sinusoidal gratings are carried out respectively. Compared with the relationship curve obtained by the two methods, there is a negative correlation between the η -value curve and the maximum electric field intensity E_max curve of the grating surface. Moreover, the difference between the theoretical value of E_max and the simulation result is very small ( Δ <0.2). FDTD simulation and calculation results show that η -value can well describe the attenuation law of E_max of periodic nanostructured SERS substrate when the polarization angle of incident light changes. The method has simple analysis process and less computation. This method provides a fast and simple polarization correlation analysis method for SERS substrate design.

Probabilistic graphical model (PGM) is a mainstream model for data publishing. Due to its structural characteristics, the higher the accuracy of important nodes in PGM, the higher the utility of published data. This paper proposes a datadependent differentially private publishing method for horizontally partitioned data, including a multi-party data publishing framework which can combine the existing data-dependent parameter learning method and a data-dependent structure learning method in the horizontally partitioned data setting. So that the whole learning process of PGM is datadependent. Thus, different privacy budgets can be allocated to different nodes when learning the PGM for different datasets. The experimental results show that the data published by our scheme has high utility.

Economic development and reform is a subject that has been explored by countries all over the world, and especially by my country, the largest developing country. In the context of our economic system, each place has its unique economic development model. In this paper, the economic growth model of Jingzhou is derived by studying the economic development data of Jingzhou during the period of fourteen years from 2006 to 2019, using the extended Cobb-Douglas production function to establish a multiple linear regression model empirical analysis simulation. The results show that the economic growth mode of Jingzhou is based on the crude - that is, the growth of the economy relies on a large number of inputs, the adjustment and optimization of industrial structure contributes more to the economic growth of Jingzhou, while other factors on the economic impact is not only inefficient, the contribution is also small, and there is still much room for improving labor productivity and production efficiency.

Through the rapid development of information technology, communication technology, and network technology, self media, as a new marketing method, has gradually appeared in the public’s field of vision. There is no powerful evidence for the success of We Media marketing to explain the characteristics and panorama of media marketing, and it is difficult to use data information as a method and means of discourse. This paper proposes countermeasures in accordance with the analysis of the current problems faced by self-media, and briefly analyzes the effect of big data analysis on self-media marketing, based on the understanding of big data analysis.

In the new era, big data, cloud computing and other technologies have penetrated into the power industry, providing strong support for power data collection and quality improvement. In this regard, this paper analyzes the application of power data acquisition based on big data cloud platform, and puts forward data acquisition methods and application measures in line loss management, load prediction, pollution prevention and control. Through the research of this paper, the power enterprises can dig out valuable information from the mass information and provide users with better electricity service.

The protection of user privacy is more and more important, which restricts the effective application of traditional methods in some fields. Federated learning is an effective method to solve such problems. The vertical federated learning method can be effectively applied to the joint analysis of multiple energy data. This paper discusses the application of this method in identifying group tenants in the research of urban energy big data, proposes an address based data matching method and corresponding coding rules, and implements an example based on SecureBoost. The results show that vertical federated learning has a good effect in the joint modeling of electricity and water data.

Volcanic rock formations, as an important oil and gas resource reservoir, have received the focus of the energy industry in recent years. Shear wave logging is essential geophysical data for the exploration and evaluation of volcanic rock oil and gas reservoirs. Due to the strong nonlinear relationship between reservoir logging parameters and S-wave velocity, the conventional point-to-point machine learning methods can not effectively construct the feature space. Deep learning adds neighborhood information to learn the depth features relationship, and builds the mapping of S-wave velocity and wireline logs with its powerful nonlinear solving capability, achieves S-wave velocity prediction. Taking the volcanic reservoir in Xujiaweizi area of Songliao Basin in Northeast China as an example, thirteen logging parameters sensitive to S-wave velocity are selected, and the S-wave velocity prediction models are based on deep learning methods (represented by CNN, ViT, and MLP-Mixer) are proposed. The research demonstrates that the proposed deep learning models are able to predict S-wave velocity with more precision, and the modeling method can give great significance for the exploration of the volcanic reservoir.

As an extremely important target for unconventional oil and gas resources exploration at present, shale reservoir differs significantly from conventional clastic and carbonate reservoirs due to their diverse mineral composition, complex pore characteristics, and severe heterogeneity, which makes the conventional theoretical petrophysical models not accurate enough to characterize shale reservoirs. For this reason, machine learning and deep learning methods are introduced to construct a more intelligent petrophysical modeling process, which uses a data-driven approach. And taking the shale reservoirs of the Permian Fengcheng Formation in Mahu Depression of Junggar Basin as an example, we achieve high accuracy Shear wave velocity prediction based on conventional well logs, and the mean relative error (MRE) of prediction is reduced by 2.78-3.88% and the method has good applicability and generalization compared with conventional petrophysical model.