Advances in Engineering Technology Research

Lane-line Detection based on Inverse Perspective Mapping and Kalman Filter

2024-04-19T10:45:29+08:00

In real-time vision-based autonomous driving, lane-lines are difficult to identify due to shadows, road disrepair, reflection or other disturbances, as well as obstacles dynamic occlusion. In this paper, region of interest (ROI) is selected first. An algorithm based on inverse perspective mapping (IPM) is proposed to transform graphic images into flat images, after the operation of gray processing and image enhancement, binarization processing and secondary image enhancement are carried out for these images. Through the pixel statistics of image columns, The characteristic curves are extracted and lane-lines are fitted. At the same time, Kalman filter algorithm is proposed to predict the lane-line which are discontinuity, this improves the robustness and stability of the lane-line detection effectively. Finally, Experiments have been conducted on different scenes, the results show that the proposed algorithm own good detection efficiency.

Improved Autuoformer Electricity load forecasting based on model fusion

2024-05-08T16:38:10+08:00

The development of the power system is undergoing rapid changes. The future direction of power system development is inevitably smart grids. This paper proposes an optimization of the Autoformer model based on model fusion to improve the accuracy of electricity load forecasting. By incorporating the predictive results of traditional statistical multivariate linear regression (MLR) and machine learning method LightGBM into the Autoformer model, we aim to fully leverage the strengths of both traditional statistical and machine learning approaches to enhance the predictive accuracy of the Autoformer model. Experimental results, using mean MAE and MSE as the evaluation metrics, demonstrate that the algorithm proposed in this paper exhibits better performance in the prediction results.

Optimization research on short-term load forecasting method for electric vehicles based on SSA-SVM

2024-05-08T16:42:14+08:00

In order to improve the accuracy of short-term electric vehicle load forecasting, a combined forecasting model based on Sparrow Search Algorithm (SSA) and Support Vector Machine (SVM) is constructed. Using SVM model to predict electric vehicle load, accelerating the convergence speed of the prediction model through sparrow search algorithm, conducting global optimization in the solution space, expressing the impact of calculated parameters on the model through fitness, searching for the optimal model parameter data, and improving the overall accuracy of the prediction model. Through simulation experiments, comparing the prediction results of SVM models, and SSA-SVM shows better performance in electric vehicle load prediction.

Research on the motor control system of electric driven air suction seed dispenser

2024-05-08T16:55:01+08:00

In order to improve the characteristics of the motor control system of the electric drive type pneumatic PLANTING device, some pneumatic PLANTING devices made by American PrecisionPlanting Company were used to design the motor control system and the drive gear of the motor. On the basis of analyzing the dynamics of brushless DC motor, hysteresis control and sliding mode control strategy are used to control the speed of the motor, and the control system simulation model of the drive motor is established on MATLAB/Simulink software. The simulation results show that the waveform is consistent with the theoretical analysis. When the load is suddenly applied, the speed can respond quickly and become stable quickly. The torque response can follow the change of current well, and the system can run smoothly.

An Electrochemical Sensor Based on Au/rGO/GaN Porous Layer for Dopamine Determination

2024-05-08T17:00:26+08:00

Dopamine (DA) is a biomarker that plays an important regulatory role in human body. In this paper, a Au/rGO/PGaN electrochemical sensor was fabricated by electrodeposition of reduced graphene oxide (rGO)and gold nanoparticles on GaN porous layer（PGaN）, which was grown by metal organic chemical vapor deposition (MOCVD). The composition and structure of the Au/rGO/PGaN electrode was characterized by scanning electron microscopy (SEM)．The sensing performance of the Au/rGO/PGaN electrode on DA was investigated using cyclic voltammetry and chronoamperometry. The sensor can detect dopamine in the range of 0.5-400μmol/L, and the detection limit of DA is 0.15μmol/L. In addition, the Au/rGO/PGaN electrode has good stability and repeatability, high sensitivity and wide detection range.

Study on cuttings removal effect of Effective HydroClean Drill Pipe under different deviation conditions of drill pipe

2024-05-08T17:05:33+08:00

In order to solve the problem of cuttings bed in the drilling process of highly deviated sections in directional wells, horizontal wells and extended reach wells, an Effective HydroClean Drill Pipe(EHCDP) was designed, using computational fluid dynamics (CFD) simulation techniques, the flow characteristics of the annular flow field under the action of EHCDP were analyzed, the cuttings removal efficiency of this kind of EHCDP under different deviation conditions is studied, thus providing the relevant basis for using this EHCDP to remove cuttings more efficiently. The results show that the EHCDP can effectively remove cuttings under different deviation conditions. However, the larger the inclination angle of the well, the more likely the cuttings is to accumulate on the lower edge of the wellbore due to gravity, forming cuttings bed. In highly inclined wellbore above 60°, EHCDP can be combined with traditional cuttings removal methods to more effectively remove cuttings near the low side of the wellbore.

Design and Implementation of Process Rollback Mechanism Based On Activiti For Power

2024-05-08T17:14:38+08:00

With the development of power system business, the complexity of business processes and the frequency of interaction between processes are getting higher and higher. The complexity of interaction between processes is not only limited to the functions of starting, sending and returning to the main process after the end of the sub-process, but also needs the support of the rollback mechanism of the main sub-process. Because the main sub-process can be nested in multiple layers, the rollback mechanism of the main sub-process is relatively complex.

Study on the Definition Principle of Reasonable Well Spacing in Tight Sandstone Gas Reservoirs

2024-05-08T17:23:46+08:00

The reasonable well spacing of tight sandstone gas reservoir not only affects the production effect of a single well, but also directly determines the reserve utilization and economic benefit of the whole gas reservoir. At present, the rational well spacing of tight sandstone gas reservoirs is determined by multiple methods. There are many calculation methods of well spacing and the calculation results are very different, and there is no definite definition principle of reasonable well spacing, the definition of reasonable well spacing obtained by comprehensive method is fuzzy and artificial. In order to standardize the calculation and effective definition of reasonable well spacing for tight sandstone gas reservoirs, this paper puts forward the definition principle of reasonable well spacing for tight sandstone gas reservoirs on the basis of in-depth investigation and classification of well spacing calculation methods, and takes Shan2 gas reservoir of Zizhou gas field as an example to evaluate reasonable well spacing. The main conclusion is that: ①The calculation methods of well spacing in tight sandstone gas reservoirs can be divided into three categories: the method based on economic benefit, the method based on production response and the method based on production demand. Based on the method of economic benefit, the economic well spacing is determined from the balance between cost and income. Based on the production response method, the technical well spacing is determined from the perspective of effectively avoiding the waste of reserves and inter-well interference. Based on the method of production demand, the proposed well spacing is determined from the reasonable production rate scheme of gas field. ②The study of reasonable well spacing in tight sandstone gas reservoirs should focus on economic well spacing and technical well spacing, and the study of scheme well spacing is not necessary; The reasonable well spacing of gas reservoir should meet the principle of "economy and technology", both of which are indispensable.③The economic well spacing of Shan2 gas reservoir in Zizhou Gas field is 816m, the technical well spacing is 1097m, and the reasonable well spacing is 1097m; At present, the well spacing of gas reservoir is 1965m, and the well pattern is not perfect. In order to avoid the waste of reserves and interference between Wells and improve the recovery rate of gas reservoir, it is recommended to adjust the well pattern according to the 1097m well spacing in subsequent development. The research results can provide reference for the calculation and effective definition of reasonable well spacing in standard tight sandstone gas reservoirs.

Stability Analysis of Yebatan Underground Cavern Surrounding Rock based on Crack Evolution Theory

2024-05-08T17:35:56+08:00

The deformation properties of rock are closely related to the effect of crack closure, generation and expansion in the rock. In this paper, the stress-crack strain evolution constitutive model is used to determine the relaxation damage zone of the surrounding rock based on the change regulation of the crack closure ratio during the whole process of surrounding rock damage, and the model is embedded into FLAC3D software, and then the stability evaluation of the surrounding rock of the cavern group under unsupported and supported conditions is carried out for the underground plant of Yebatan hydropower station. The excavation simulation shows that the displacement of the cavern surrounding rock increases with the excavation step, and the influence of the fault on the displacement of the surrounding rock is very significant. The high stress concentration area is distributed in the arch top of the plant, the tailwater connection hole, the arch top and the bottom of the tail chamber, and the tensile stress area is mainly distributed in the high side wall of the underground plant and the tail chamber. The crack closure ratio index was used to quantitatively evaluate the degree of relaxation damage of the surrounding rock, indicating that the relaxation damage area is influenced by the fault, and the volume of the surrounding rock damage area under the system support is significantly reduced compared with the unsupported working condition, showing the effectiveness of the support measures.

Research on Temperature Field Characteristics of Lithium Battery Vacuum Drying Furnace

2024-05-31T16:48:03+08:00

The temperature distribution of the vacuum contact drying oven fixture is a crucial factor that affects the moisture characteristics of the electric core. This paper presents a study on the temperature characteristics of the vacuum oven fixture, which combines theoretical analysis, numerical calculation, and experimental research. The results indicate that during the temperature rise process, the fixture temperature center intersects elliptically with the surrounding diffusion, while the temperature center of the insulation process is circular to the surrounding diffusion. Additionally, the temperature increase at each test point during the PID control process first increases and then decreases with time, gradually reaching stability. The temperature difference between the test points meets the process requirements. The research results obtained for the design of the vacuum oven fixture provide theoretical reference for addressing temperature control issues and practical guidance for production.

Characteristics of Hazardous Rock Avalanche Disasters on High and Steep Slopes and Countermeasures for Prevention and Control in Wuling Mountain Area of Chongqing

2024-05-31T16:54:31+08:00

Chongqing Wuling Mountain area has complex geological conditions and frequent geologic disasters, which bring severe challenges to the construction of highways along the route, especially affected by the topography and meteorological conditions in the Chongqing region, the distribution of disaster points is dense, and the disaster management is difficult. This paper takes a highway in Chongqing Wuling Mountain area as an example, fully analyzes the development characteristics of geologic disasters along the route, and concludes that dangerous rock collapse is a typical geologic disaster on the slope in Chongqing Wuling Mountain area. The influencing factors of dangerous rock failure on the slope are divided into three categories: geological conditions, meteorology and hydrology, and slope design pattern, and their influencing mechanisms are elaborated respectively. Finally, 16 high and steep slopes along the route are analyzed in depth, divided into four grades according to the degree of influence on slope safety, and targeted prevention and control measures are proposed. It can provide certain reference for the construction of highway along the Wuling Mountain area in Chongqing.

Identifying the temporal variation of nonlinear seismic site response by Artificial Neural Network

2024-05-31T16:58:33+08:00

3135 strong motion records at 50 KiK-net stations in northeastern Japan are collected. The soil site response to strong motions is classified as linear, transition between linearity and nonlinearity, and nonlinear, by the dynamic soil parameters PGA_rotD50 and I_γ. 326 records in the nonlinear set are divided into the training set (200 records) and the test set (126 records) for an artificial neural network (ANN). This ANN is constructed to identify the temporal variation of nonlinear seismic site response automatically, by combining with the soil dynamic parameters PGA_rotD50 and I_γ in moving time window. The accuracy of soil nonlinearity identified using this network reaches 98%, which is higher than the result of visual identification, and there is no overfitting.

Research on the influence of diverse tea varieties on disease and exercise regulation

2024-05-31T17:03:08+08:00

Tea and tea beverages are popular around the world due to their unique flavors, and tea is rich in a variety of bioactive compounds such as catechins, alkaloids, and polysaccharides, which are the main contributors to its health benefits. In recent years, an increasing body of research has indicated that incorporating tea consumption into daily life exerts positive effects in combating oxidation, cardiovascular diseases, inflammation, aiding in exercise recovery, and potentially mitigating cancer risks. The relevant mechanisms of the signaling pathways involved have been extensively studied. Clinical trials have also demonstrated the potential of tea products as dietary supplements and natural medicines. In this paper, we review the health effects of tea, the steroid metabolic diseases modulated by different teas and the effects of related substances on health campaigns.

Comparative Analysis of Grain Size Parameters in Gonghe Loess Utilizing Various Calculation Methods

2024-05-31T17:07:51+08:00

Grain size is a key physical property of sediments, critical for reflecting their origin, transport, and depositional environments. However, the methods to calculate sediment grain size parameters are not standardized, affecting data integration and application. This study addresses the gap in comparative analysis between the graphical and moment methods in Gonghe Basin. By analyzing the YQ loess profile in Gonghe Basin, it establishes a conversion relationship between these methods and identifies the more suitable method for Gonghe loess based on their principle differences and sediment characteristics. Key findings include: (1) the moment method, aligning with Gonghe loess's sedimentary features, provides better-suited grain size parameter results due to its principle and the loess's properties; (2) the moment method shows Gonghe loess has moderate kurtosis and positive skewness, typical of aeolian sediments, affected by diverse sources and dynamic forces, with variations in transport and kinetic energy, especially during phases of high aeolian activity.

Low-frequency Acoustic Collimation Modulation Based on Monopole Mie Resonance Acoustic Metamaterials

2024-05-31T17:23:01+08:00

Acoustic metamaterials show great flexibility in manipulating acoustic waves and exhibit important applications. However, an increasing number of applications are suitable for the low-frequency range, which makes it challenging to design acoustic metamaterials for low-frequency modulation. Here, we propose a subwavelength monopole Mie resonance acoustic metamaterial that can flexibly control the propagation route of acoustic waves. Compared to the background medium, the designed Mie unit has a higher refractive index and can achieve directional manipulation of low-frequency acoustic waves based on monopole Mie resonance. Furthermore, an array formed by multiple Mie units in a specific arrangement can achieve the acoustic collimation phenomenon. The designed monopole Mie resonance acoustic metamaterial has potential application prospects in fields such as low-frequency filtering, noise suppression, and nondestructive testing.

Research on Safety Assessment Indicators of Gas Extinguishing System for Urban Railway Transportation

2024-06-20T11:39:17+08:00

Gas fire extinguishing system as a more widely used system in urban rail transit, its safety is related to the safety of passengers, lives and property. At present, there are few studies on the safety of gas fire extinguishing system, and there is no special standard to guide. In order to improve the safety of the subway gas fire extinguishing system, through a number of operating companies and manufacturers to conduct on-site research, and the use of theory and data analysis and other methods of gas fire extinguishing system safety indicators have been studied. Reliability analysis is carried out by using Fault Tree Analysis, and on this basis, the safety evaluation of the system is further quantified by identifying and analyzing the hazards of the gas extinguishing system and rating the risk of the system by using semi-quantitative method. The results show that the average working time index of the gas extinguishing system before hazardous failure is 173 years, and the average non-hazardous failure time is 173 years.

Application Research of Integrated Geophysical Methods in Hydrogeological Survey in Extremely Arid Desert Areas

2024-06-20T11:52:24+08:00

The research area is located in the Wuyi Mountain area of Dunhuang, Gansu Province, belonging to an extremely arid desert region. Previous hydrogeological surveys in the area had not conducted geophysical exploration work, and most of the hydrological boreholes previously drilled had either low water yield or almost no water yield. In this study, based on a comprehensive analysis of existing regional geological and hydrogeological data, the researchers conducted Controlled Source Audio-frequency Magnetotellurics (CSAMT) measurements and high-density electrical resistivity tomography (ERT) measurements. This work essentially identified the hydrogeological characteristics such as buried fracture water in the structural zones of the research area and water-rich properties. Hydrogeological boreholes were then deployed, and subsequent drilling confirmed a relatively high water yield.

A modeling method for the Earth's interior structure based on the principles of 2n geometry and the resulting Earth's tectonic model

2024-06-20T13:43:01+08:00

A non-seismic wave detection method based on 2ⁿ geometry principle is proposed to deduce the vertical structure of the earth. By using this method, a new earth structure model can be derived by pure theory, avoiding the traditional earth modeling method that mainly relies on seismic wave imaging. The traditional method is to fill in the new findings and refine the model by studying the detection results of seismic waves, gravity and magnetic field. The deduction method proposed in this paper does not depend on seismic waves, gravity and magnetic field. Using pure geometry theory, it can derive results highly similar to the PREM model (more than 90%), and predict some new structures that can not be actively derived by PREM and other models.

Development Level of Digital Government: A Qualitative Comparative Analysis of Fuzzy Sets Based on 31 Provincial Capital Cities in China

2024-06-20T13:47:49+08:00

The onset of the information era has accelerated the transformation of digital governance, establishing it as a critical component in the modernization of governance frameworks and capabilities worldwide. Despite considerable advancements in the field of digital government, regional disparities in development remain pronounced, emphasizing the necessity for a coordinated and effective approach. This study employs a qualitative comparative analysis (QCA) of fuzzy sets to assess 31 provincial capitals in China, aiming to discern the digital governance ecosystems that promote the development of digital governments. It is grounded in the TOE framework, which examines the dynamics among technological, organizational, and environmental factors. The results provide empirical insights into the architecture of digital governance, offering a detailed comprehension of performance levels and recommending specific policy directions to enhance digital government progression.

Dual-site catalysts for water oxidation: A detailed study

2024-06-20T13:56:56+08:00

Water oxidation stands as a pivotal half-reaction in the complete water-splitting equation, essential for green hydrogen production. Dual-site catalysts, recognized for their active sites, emerge as a potential solution in this domain. Non-noble metal materials, employed in such catalysts, present an auspicious research frontier. However, the underlying mechanisms warrant further clarity. This review concentrates on the fundamental mechanisms and performance of classical dual-site catalysts in water oxidation, aiming to offer newcomers a lucid conceptual framework.

Lap Length of Steel Bars Between Novel Prefabricated Wall and Foundation Floor Structures: Full-Scale Experiment

2024-06-20T13:59:51+08:00

In the context of promoting environmentally friendly practices, prefabricated components are increasingly utilized in civil engineering design and construction. Prefabricated shear walls, in particular, have become prevalent in contemporary residential and office buildings. Following an economic analysis of the construction steps for prefabricated walls, Shanghai Hengxu Energy Conservation Company developed a novel type of prefabricated wall for use in building basements. This innovative wall consists of two thin plates joined by distributed tie pieces, with an internal steel bar cage positioned between them. The core concrete is cast in place between the plates. The wall is designed to withstand water and soil pressures from underground and connects to the basement floor through overlapping steel bars. The effectiveness of the wall's integration with the foundation floor depends on the lap length of the steel bars, a critical factor in structural design and construction. To optimize the lap length, three full-scale specimens were tested, differentiated by varying steel bar lap lengths: 0.8 lae, 1.0 lae, and 1.2 lae, where lae represents the basic anchorage length. The specimens were subjected to horizontal loading to assess failure modes, crack propagation, load-displacement behaviors, and stress-strain responses of the reinforcements. The experimental results revealed that increasing the lap length of the steel bars beyond 0.8 lae does not significantly enhance the bearing capacity or deformation potential of the specimens.

Analyzing EV Charging Patterns: Towards Efficient Infrastructure Deployment

2024-06-20T14:11:35+08:00

This paper analyzes real-world EV charging data, covering station distribution, volume, duration probability, and utilization efficiency. Future infrastructure developments and improvement recommendations are discussed. Based on diverse station data, including probability distributions and regression analysis, findings reveal disparities in infrastructure availability and charging patterns. Strategic planning and investment are emphasized to meet growing EV charging demands, along with exploring opportunities in renewable energy integration and smart charging technologies. Overall, this study provides insights for promoting widespread EV adoption and sustainable transportation.

Study on numerical analysis method of abnormal pressure formation in annulus A of CO2 injection well

2024-06-26T14:43:04+08:00

With the gradual development of CO₂ drive in oilfield, the existing CO₂ injection wells have A annulus pressure anomalies, and the A annulus pressure anomalies are very likely to cause damage to the wellbore integrity, and there is a greater safety risk to production and the environment. To address the problem of annulus pressure in CO₂ injection wells, a model of pressure equilibrium between tubing and A annulus and a model of mass conservation in the process of A annulus pressure relief have been established, and the effects of different oil jacket differential pressures, annulus liquid levels, leakage hole locations, equivalent diameter of leakage holes, and pressure relief time on the pressure in A annulus have been investigated, so as to form a method of evaluating the degree of leakage in A annulus. This method can provide theoretical guidance for the preliminary diagnosis of annulus with pressure in CO₂ injection wells, and has certain engineering reference significance for the control of annulus pressure in CO₂ injection wells.

Evaluation method of residual life of casing with corrosion defect in CO2 injection Wells

2024-06-26T14:49:01+08:00

With the hot development of CCUS project in major oil fields, CO₂ flooding technology is also developing continuously. CO₂ flooding needs to transform old oil field Wells into CO₂ Wells, and the residual life of casing with corrosion defects in old oil Wells needs to be evaluated. To solve this problem, the residual strength of casing with corrosion defects under the combined force is analyzed, and a finite element analysis model is established considering the material nonlinearity. It is found that the temperature difference and axial force will significantly reduce the residual strength of casing. The influence of corrosion rate and pitting pit radius on the residual life of CO₂ injection well is discussed. It is found that well H can continue to serve for 13 years after CO₂ injection. The research results can provide a theoretical basis for predicting the residual life of CO₂ injection Wells in old wells, and ensure the normal production and operation of CO₂ injection flooding development.

Electric Field Analysis and Shielding Optimization of 15kV DC Switchgear Wall Bushing

2024-06-26T14:54:35+08:00

Aiming at the 15kV direct current (DC) switchgear busbar wall bushing is prone to local aging resulting in insufficient insulation capacity.In this paper, according to the response surface parameter optimisation method, Maxwell-Workbench joint simulation is established to carry out numerical calculations of electric field on the parameterised model of shielding ring of wall bushing, and to study the influence of the structural parameters of the shielding ring on the distribution of electric field and the optimal combination of structural parameters of the shielding ring. The results show that the maximum electric field intensity without the shielding ring appears at the position of the connection between the fixing plate and the wall bushing and at the position where the inside diameter of the casing is closest to the busbar.The high potential shielding ring mainly affects the electric field strength of the air region inside the wall bushing, and the ground potential shielding ring mainly affects the electric field strength of the air region outside the wall bushing;The ground potential shielding ring should be as far as possible beyond the location where the fixing plate is connected to the wall bushing;The high ground potential shielding ring is closer, the electric field between the shielding rings is drum-shaped, and the electric field strength inside the casing is higher;The high ground voltage shielding ring is farther away, the electric field is funnel-shaped, and the electric field intensity is small at the connection position between the wall bushing and the fixing plate, which is favourable to the insulation life of the wall bushing and the partial discharge;Analysing and obtaining 4 groups of shielding ring structure parameter combinations that meet the insulation requirements can effectively improve the electric field distribution and reduce the electric field intensity.

Tibetan food customization mini-program study

2024-06-26T14:58:59+08:00

One of China's distinctive culinary traditions, Tibetan cuisine is currently beset by a number of issues, including a disconnect between traditional catering and contemporary lifestyle, a low penetration rate, and the relative backwardness of traditional ordering practices with respect to informationization and intelligence. We create and implement a personalised Tibetan food system called "Intelligent Tibetan Food" as a small programme to address these issues. The system aims to enhance user satisfaction and convenience by offering personalised recommendations, online ordering, dish introduction, and other features through extensive research and analysis of Tibetan food culture, mobile Internet technology, and artificial intelligence algorithms.

Evolution and zoning of the "production-living- ecological" spatial pattern in the coastal urban agglomeration of Guangdong, Fujian and Zhejiang

2024-06-26T15:03:49+08:00

Clarifying the spatial differentiation patterns and evolutionary characteristics of urban territories is the basis and prerequisite for enhancing regional spatial governance capacity and realizing sustainable urban development patterns. In order to make up for the inadequacy of the existing coastal urban agglomerations of Guangdong, Fujian and Zhejiang in the exploration of regional evolutionary characteristics and zoning. Based on the theory of production-life-ecology space, the land use data from 2010 to 2020 are used to analyze the land space pattern and evolution characteristics of urban agglomeration by applying the methods of transfer matrix, kernel density analysis, and comparative advantage index. The results show that: (1) the ecological space continued to decrease and the area of production space and ecological space continued to increase. (2) The high-value areas of production space show multinuclear diffusion, the high-value areas of ecological space are mainly distributed in a faceted manner, and the living space are distributed in a band along the coastline. (3) The entire urban agglomeration was categorized into six types of land function zones based on the comparative advantage indices of the three spaces at the county scale.

Seismic Damage Analysis of Zamora Bridge in Ecuador

2024-06-26T15:07:08+08:00

The Zamora Bridge, located in the Zamora-Chinchipe Province in the southeastern part of Ecuador, on the Pacific Rim seismic belt, serves as the sole river-crossing channel from the Mirador Copper Mine area to the exterior. Constructed and opened for traffic in 2013, this bridge is designed as a low-pier continuous girder bridge, featuring a three-span prestressed concrete continuous box girder for the main beam, with a span arrangement of 45.5+140+45.5 meters, and utilizes basin-type rubber bearings throughout. On May 6, 2019, and November 28, 2021, the Zamora Bridge experienced two significant seismic events. The initial seismic damage investigation revealed that the piers and foundation maintained their load-bearing capacity largely intact; the basin-type rubber bearings predominantly suffered shear failure and displacement, losing their horizontal limit capacity. Additionally, abutment blocks sheared, padstones cracked locally, and the main girder exhibited residual displacement. Following the first earthquake, repair work was undertaken based on the damage results, switching to friction pendulum seismic isolation bearings to enhance the seismic resilience of bridge. The subsequent seismic damage assessment indicated the overall stable condition of the bridge, with no observable damage, deformation, or settling to the main structure, thus maintaining basic traffic functionality. However, shear and deformation occurred to the bolts and pins fixing the direction of the friction pendulum isolation bearings, along with residual displacements after the activation of the seismic isolation function, and cracks developed in the abutment padstones and mortar layers. To delve into the performance and damage probability of vulnerable components of low-pier continuous girder bridges under various seismic intensities, numerical models of the Zamora Bridge equipped with basin rubber bearings and friction pendulum bearings were separately established using OpenSees finite element software. An analysis of the bearings' longitudinal seismic susceptibility was conducted by integrating the demand-capacity ratio and IDA method. The findings indicate that bearings, padstones, and anchor bolts are the vulnerable components necessitating reinforcement for such bridges. Compared to the basin rubber bearings, friction pendulum bearings significantly reduce the probability of bearing damage and demonstrate an excellent seismic isolation effect.

Data analysis method for power big data

2024-07-18T09:53:22+08:00

This paper discusses a data quality analysis and evaluation mode based on power big data. Its basic content is to use the analysis platform template to conduct acquisition control and process rule analysis, and then use the data quality management module to call out the platform database system that realizes the inspection and analysis function, and retrieve and generate inspection data from the entity base. The analysis program will classify, count, sort, and sort the data, The final generated quantitative indicator data reflecting the project implementation status and data quality will be saved in the analysis result table. The analysis result report called from the middle platform can obtain a more detailed data quality analysis and evaluation report reflecting the data quality of various quantitative projects. This paper has improved the intelligent degree of information quality management and evaluation, realized the intelligent control of information service quality, adapted to the needs of large-scale information service management, and completed the quantitative research and evaluation of information completeness, timeliness, accuracy, accuracy and other important parameters.

Communication method of distribution network geographic information system

2024-07-18T10:19:47+08:00

A communication method and system between the distribution network planning system and the grid geographic information system. After the change of the grid structure, the grid equipment change information is generated with the grid equipment as the unit. The production control region information structure is used to encapsulate the grid equipment change information, obtain the equipment change bus message, and send the equipment change bus message to the production control region service bus, This enables the distribution network planning system to receive equipment change bus messages from the production control area service bus, so that the distribution network planning system can directly communicate with the grid geographic information system.

Simulation of Optimization Decision Model for Low-carbon Economy Schemes Based on Machine Learning Algorithms

2024-07-18T10:41:06+08:00

Low-carbon economy (LCE) is a shift from high-carbon intensive industries and activities to low-emission or zero-emission industries and activities, which requires a lot of investment in new technologies and infrastructure, as well as changes in policies and regulations to promote sustainability and reduce emissions. In this article, the back propagation neural network (BPNN) algorithm in machine learning (ML) is applied to the construction of low-carbon economic scheme optimization decision model, and the performance of the model is simulated and tested. The results show that BPNN algorithm has higher accuracy and reliability in predicting the development level of LCE, which is 23.8% higher than Support Vector Machine (SVM) algorithm. Through the comparative study of BPNN algorithm and SVM algorithm in forecasting the development level of LCE, the advantages of BPNN algorithm in forecasting accuracy and application value are verified. BPNN algorithm can better adapt to and deal with the complex data patterns in the field of LCE, improve the accuracy and reliability of prediction, and provide strong technical support and guarantee for the growth of LCE.

Applicants and Prospects of Uplink/Downlink Decoupled Access Cellular Vehicle-to-Everything (C-V2X) in B5G/6G

2024-07-18T10:48:29+08:00

The cellular vehicle-to-everything (C-V2X) is an important information technology solution to address the low-latency and high-reliability communication demands of current vehicle users in beyond 5th generation (B5G) and 6th generation (6G) wireless communications. However, existing C-V2X frameworks suffer from frequent handovers, insufficient data rates, and imbalanced base station loads due to the smaller coverage range of base stations. To address these challenges, it becomes imperative to introduce uplink/downlink decoupled access (DUDe) into the preexisting coupled access framework. This article analyzes the core challenges of C-V2X, summarizes the development background and advantages of DUDe, examines the feasibility of applying DUDe in C-V2X, explores various application directions related to uplink/downlink decoupled access C-V2X, and finally concludes with the development of uplink/downlink decoupled access C-V2X.

Vanishing Gradient Problem: An Activation Function that Seeks to Improve VGP

2024-07-18T11:33:26+08:00

The performance of deep learning networks can easily be affected by the phenomenon of vanishing gradients. With this in mind, this paper mainly discusses an activation function different from ReLU and other functions that improve the vanishing gradient problem (VGP). Influenced by parameterized functions and equations, we can set an activation function that allows for manual parameter changes. In this way, we can avoid the vanishing gradient situation when the input received by backpropagation is close to 0. With such an activation function, we can manually avoid vanishing gradients; in the experimental part, this paper uses the MNIST dataset to verify the effectiveness of the proposed method. The experiments demonstrate that the proposed method can alleviate the vanishing gradient phenomenon to a certain extent.

An Exploration of Factors Influencing the Passing of Mainland Chinese Students' Study Abroad Applications Based on Logistic Regression Modeling--Example of Applying for Master's Degree in Hong Kong

2024-07-18T11:38:56+08:00

In order to explore the admission factors of mainland Chinese students applying for master's degree in Hong Kong, the article collected about 240 data by visiting and researching professional study abroad application agencies and students in colleges and universities. It collected undergraduate institution background, major grades, target institution ranking, language scores and undergraduate grades of the applicants and analyzed and explored them based on the logistic regression model. We found that undergraduate institutional rank, undergraduate GPA, target institution rank, and major match were significantly different across admissions outcomes and were able to conclude, that undergraduate institutional rank, GPA, and target institution rank had the most significant effect on admissions outcomes, and that language scores and major match did not significantly affect admissions outcomes. We hypothesize that there may be a survivor bias in the data collected, and that some unquantifiable factors of soft backgrounds such as research competitions, internships, and patents and journals may have an impact on the admissions outcomes. We also provide strategies to improve the success rate of the application.

A survey of Autoencoder and Convolutional Neural Network Based Methods for Fault Diagnosis

2024-07-18T11:43:25+08:00

Deep learning technology, with its exceptional nonlinear feature extraction capability, has been gradually accepted and widely adopted by the industry. This paper reviews the fault diagnosis techniques utilizing deep learning, emphasizing an in-depth analysis of two main deep learning models that are extensively applied in the current fault diagnosis domain: Autoencoder (AE) and Convolutional Neural Network(CNN). In addition, we also discuss the specific application cases of both algorithms, and introduce their specific principles of implementation. Through these in-depth analysis, it is intended to provide readers with the application overview and technical progress of deep learning technology in the field of fault diagnosis, so as to offer reference and enlightenment for related research.

Self-correcting gripping robotic arm for QR code based on hand-eye calibrationv

2024-07-18T11:47:44+08:00

During the operation of a robotic arm, the inaccuracy of the end-effector position can seriously affect the overall performance of the robot. In order to significantly reduce the positional error of the actuator with minimal cost, we adopt a 2D code-assisted positioning method based on the principle of hand-eye calibration to negatively feedback correct the coordinates of the end-effector. This method establishes a robotic arm-camera system, which improves the performance and accuracy of the robotic arm.

Unleashing the Power of Momentum: Analyzing Tennis Match Flow through Data Analysis

2024-07-18T11:51:16+08:00

This paper aims to analyze the impact of momentum in the Wimbledon Men's Singles Final, uncovering its influence on the game's trajectory and providing strategic advice. To analyze player performance and game pace in tennis, we identified key variables within the dimensions of Consumption, Serving, Accuracy, and Difference. Initially, we developed a momentum prediction model in tennis using logistic regression, with an accuracy of over 73%. In line with the actual match, our visualizations provide valuable insights into the flow of play and momentum shifts in tennis matches. Secondly, we conducted a randomness analysis using the Run test on two metrics: CW (swings in play) and DPW (runs of success by one player), indicated that neither CW nor DPW occurs randomly. Furthermore, we employed Vector Auto-regressive Models (VAR) and found that momentum significantly affects the states of players and their winning streaks. Thirdly, we created the Momentum Swing Prediction Model using the Random Forest approach, introducing a dependent variable, TP, to capture the swings in momentum during a match. By analyzing the variable, we have identified four key factors: win/loss of the serve, rally length, serve speed, and distance. Moreover, we offer three practical recommendations for players entering a new match. Finally, we tested the Momentum Swings Prediction model on matches that were not included in the 2023 Wimbledon Men's model, and proposed incorporating player strength and injury information into future models to enhance the model's performance in different scenarios. Through testing on the 2022 Wimbledon Women's matches, we conclude that our model exhibits generalization across various types of matches. In conclusion, these findings highlight the significance of momentum and how it can impact the flow of play. By understanding these dynamics, coaches can better prepare players to respond to events that impact the match's trajectory.

Digital Twin System of Substation Equipment

2024-07-18T11:54:51+08:00

This paper adopts the following technical solutions to achieve: a digital twin system for substation, including: database, database configuration module, data warehousing module, background data processing module and front-end browsing module; The front-end browsing module is used to display the data sent by the background data processing module in the corresponding form according to the user's selection; The form includes building the three-dimensional model of the substation based on BIM technology, and displaying the corresponding real-time data and status in the three-dimensional components of the three-dimensional model. Compared with the existing technology, it organically integrates the three-dimensional model and panoramic monitoring data of the substation, realizes the three-dimensional panoramic display of substation assets and the acquisition of substation monitoring data, improves the spatial experience of daily operation and maintenance comprehensive monitoring, and provides a solid data platform for the subsequent in-depth mining and intelligent analysis of multidimensional data of the substation.

Review of Research Progress in Computer Vision

2024-07-18T12:00:27+08:00

Computer vision, being a pivotal element of artificial intelligence, has witnessed significant advancements in theoretical methodologies, key technologies, and practical applications after years of development, which has shown great application prospects in medical, industrial, transportation, military, public safety, and other fields. Therefore, it is necessary to review the current development and application of computer vision technology to comprehensively evaluate its future development trend and potential. Firstly, this paper reviews the development history of computer technology. Then, aiming at the specific tasks of computer vision, the typical methods and models based on depth learning in recent years are summarized, including image classification, target detection, image segmentation, etc. Then, the application and research progress of computer vision technology in various vital fields are introduced respectively. Finally, the current challenges and critical research problems in computer vision technology are analyzed.

Research and Implementation of FPGA Image Compression Parallel Algorithm Based on CCSDS

2024-07-18T12:07:04+08:00

High-pixel, high-resolution spectral images are an important source of key graphical information obtained from space remote sensing, however, with the dramatically expanding amount of graphical information, the limited transmission bandwidth and hardware resources are difficult to meet the demand for massive data, which makes real-time image lossless compression and transmission technology an important solution. For this reason, this paper is based on the CCSDS image lossless compression algorithm, using FPGA for the construction of image compression system, and proposes a method strategy based on parallel acceleration algorithm to realize the real time processing of large-capacity hyperspectral images. The simulation results show that hyperspectral river and mountain range images can be compressed with greatly improved compression efficiency while maintaining real time performance and accuracy.

The impact of resolution and flipping on image classification

2024-07-18T13:42:12+08:00

The initial stage of image classification involves image preprocessing, which includes considerations such as the object's position within the image, the background, ambient lighting, and the viewing angle. These factors can introduce variations in the original pixel data, and consequently, applying diverse preprocessing methods can yield varying levels of accuracy in the collected data. This study explores the relationship between preprocessing techniques and the performance of deep learning models. In this paper, images are processed by both reducing and increasing their resolution and by applying 180° horizontal and vertical flips. Subsequently, the Edge Impulse platform (https://edgeimpulse.com/) is employed for image classification. The objective of this paper is to assess the impact of resolution adjustments and flipping on image classification accuracy through a series of repeated experimental analyses.

A Brief Review of Classic IoT security Protocols

2024-07-18T13:48:06+08:00

Recent years have witnessed that Internet of Things (IoT) became more and more popular in many technical fields. Due to its high utility, IoT is closely linked with a number of domains in people’s daily life; hence, it is really crucial and necessary to reinforce and maintain the security of IoT. In fact, there are numerous protocols proposed to protect it, and these researches aim to find an effective way to resist attacks from hackers. In order to improve safety index of the existing models and build a nearly brilliant model. This paper analyzes and compares three published studies which are relevant to this topic through several factors. This paper describes these protocols from an understandable and explicit perspective which makes readers easy to catch the main idea of each protocol. After detailed explanation of the algorithm and analysis of several safety indicators, according to several comparison tables and bar charts, we finally figure out the best protocol among these three studies, and specific results are showed in the paper. Furthermore, we also give some available and useful suggestions about the future work to optimize the protocol in this industry.

Research on the influence of AI on social labor force composition

2024-07-18T13:49:33+08:00

This paper focuses on the impact of AI technology on the workforce structure. As AI technology permeates our lives, one of the most important questions is whether it revolutionizes the composition of the workforce. Deep learning technology, combined with AI's increasingly powerful arithmetic chip, has significant advantages over the human brain and other mechanical devices in terms of logical operations and information capture. The change of labor force structure not only involves the problem of technology replacing human resources, but also is related to the long-term development of social economy. Although the popularization of AI provides opportunities for many people to improve themselves, how to balance technology and manpower to ensure the smooth transition and sustainable development of the economy is an urgent problem to be solved. Especially in terms of economic equality, how to ensure that the popularization and application of AI technology will not aggravate social inequality is also a question for us to think deeply. Therefore, it is of great practical significance for the research and discussion of labor force structure.

Utilizing Metasurfaces for Directional Control of LED Emission

2024-07-18T13:58:47+08:00

This study provides a detailed modeling and analysis of four different three-dimensional GaN-based LED structures. The results reveal that incorporating DBRs effectively focuses light and enhances the light extraction efficiency (LEE). Additionally, the integration of Metasurface in the Micro-LED+DBRs+M structure allows for precise control of light emission direction and further radiation focusing. Furthermore, in the Micro-LED+DBRs+M2 structure with improved periodic nanocolumns, the light beam can be deflected simultaneously in multiple directions. These findings offer new possibilities for the advancement of LED technology.

Utilizing Silhouette and Head Information for Improved Cloth-changing Person Re-Identification

2024-07-18T14:06:39+08:00

In recent years, significant progress has been made in person re-identification (ReID). However, as the time span increases, the phenomenon of changing clothes often occur, and the performance of methods based on person re-identification may decrease in this case. In this article, we focus on solving the problem of cloth-changing person re-identification from a single RGB image, which is more challenging, and improving the accuracy and robustness of traditional methods for recognition. We propose a cloth-changing Feature Regularization learning framework by fusing Silhouette and Head information (SHFR), a two-stream framework which transfers the silhouette information and head information learned by auxiliary stream to the main stream and supplements features unrelated to clothing. Specifically, the main stream approach we adopt is the traditional cloth-changing person re-identification network. In the auxiliary stream, we use the DeepLabV3 semantic segmentation model to extract person silhouette features, and the FCHD fully convolutional head detection model to extract head information with advanced semantic information. We concatenate the head information and background information into the silhouette as input for BackBone to continue training the network. In order to utilize silhouette information and head information, we regularize the cloth-changing features on both main stream and auxiliary stream, allowing main stream model to pay more attention to features unrelated to clothing and improve the accuracy of model recognition. We conduct extensive experiments on our model on the PRCC dataset, and the results show that our method has highly competitive performance.

Predicting Lead Changes in Tennis Matches based on Machine Learning Models

2024-07-18T14:12:41+08:00

Based on men's singles data from the 2023 Wimbledon Tennis Championships, this study applies advanced statistical and machine learning techniques (including Principal Component Analysis PCA, Uniform Streaming Approximation and Projection UMAP, Random Forests, and Extreme Random Trees Extra-Trees) to explore the dynamics of lead changes during matches. By constructing mathematical models, the study predicts lead changes at key moments of the race that have a decisive impact on the race strategy and outcome. The experimental results show that the Extreme Random Trees model performs well on all evaluation metrics, especially in terms of accuracy, recall and F1 score, demonstrating its ability to handle complex interactions and variations in the data. In addition, the CatBoost model performed well in identifying actual leading changes, but with lower accuracy, possibly due to overfitting certain data patterns. The hybrid model, on the other hand, demonstrated a balanced performance, although it failed to outperform the extreme random tree model in terms of overall effectiveness.

Design of PID control model for reducer based on Simulink simulation

2024-07-18T14:21:19+08:00

At present, modern industry is developing rapidly, and the level of industrial automation is gradually improving. Many production lines use a large number of mechanical equipment and robots, and reducers play a key role in these equipment, helping to control and adjust the speed and torque of various moving parts, achieving efficient production. At the same time, in high-speed railway trains and airplanes, reducers improve the efficiency of engines and turbines, reduce fuel consumption, and ensure safe and reliable operation. However, traditional reducers have drawbacks such as low accuracy and long adjustment time in controlling speed. This article adopts the method of PID control of the reducer, and uses the Simulink platform of Matlab to build a control model of the reducer. At the same time, negative feedback control is applied to the speed and current, forming two PID closed-loop controls: current loop and speed loop. The speed waveform and current waveform are displayed on an oscilloscope, and the simulation control results are analyzed. The simulation results show that by using a PID controller to control the speed of the reducer, the maximum overshoot can be reduced, the adjustment time can be shortened, the adjustment process can be smoother, and the set value can be reached quickly.

Survey for Detecting AI-generated Content

2024-07-18T14:31:28+08:00

In large language models (LLMs) field, the rapid advancements have significantly improved text generation, which has blured the distinction between AI-generated and human-written texts. These developments have sparked concerns about potential risks, such as disseminating fake information or engaging in academic cheating. As the responsible use of LLMs becomes imperative, the detection of AI-generated content has become a crucial task. Most existing surveys on AI-generated text (AIGT) Detection have analysed the detection approaches from a computational perspective, with less attention to linguistic aspects. This survey seeks to provide a fresh perspective to drive progress in the area of LLM-generated text detection. Futhermore, in order to make the assessment more explainable, we emphasize the great importence of leveraging specific parameters or metrics to linguistically evaluate the candidate text.

Bike Sharing Demand Forecasting Based on the Informer Model

2024-07-18T15:07:35+08:00

Advancements in machine learning and artificial intelligence have been instrumental in enhancing demand forecasting for shared transportation modes, significantly benefiting urban traffic management and promoting a balanced supply-demand dynamic. This study harnesses the deep learning Informer model to forecast bike-sharing demand, integrating multiple factors to provide an empirical foundation for transport scheduling and redeployment, thereby contributing to the advancement of the field. Our experimental analysis reveals that the Informer model outperforms LSTM in predictive accuracy, as evidenced by improved R² scores and MSE values, reflecting gains in training efficiency and predictive precision. Despite these advances, predictions for extreme demand values, particularly during peak usage periods, indicate potential areas for refinement. Future research directions are oriented towards optimizing model accuracy by leveraging multimodal data for a comprehensive analysis and enhancement of traffic management strategies. This approach aims not only to better predict demand and alleviate congestion but also to deliver more optimized solutions for businesses and convenience for users. Furthermore, the model's application extends beyond bike-sharing to other forms of shared mobility, such as electric scooters, potentially aiding in reducing carbon emissions and furthering the development of the sharing economy and environmental sustainability.

Analysis of Factors Causing Urban Road Traffic Accidents Based on XGboost Algorithm

2024-07-18T15:10:27+08:00

To further strengthen road traffic safety management and improve the accuracy of early warning systems for road traffic safety, a model for factors causing urban road traffic accidents based on the XGBoost algorithm is proposed. Firstly, SMOTE is used to process the unbalanced data, including supplementing the missing values, deleting the duplicate values, and visualizing the data. Then the prediction model is built by the XGBoost algorithm. By comparing and analyzing the results with the LR model, linear SVM model, DT model and Lightgbm model, the average accuracy rate of the XGBoost model reaches 0.979. Based on the XGBoost algorithm, the analysis of the factors causing urban road traffic accidents has better prediction performance, which can provide a reliable reference for preventing traffic accidents.

Summary of MEMS Capacitive Accelerometer

2024-07-18T15:18:09+08:00

Micro-Electro-Mechanical System (MEMS) accelerometer (MEMS accelerometer), as an important MEMS device, has been widely used in the field of high-precision electronic technology and consumer electronic products. At present, the technology of MEMS accelerometer has been mature, and the sensor based on capacitance principle, piezoelectric effect, piezoresistive effect and other principles has been widely used in many aspects of national life and production and sustainable development. Combined with and according to all kinds of references, this paper briefly describes the shape composition and sensing principle of the MEMS capacitive accelerometer, enumerates the design and error optimization research of each research group for the sensor, and explains it with the relevant research data.

Optimal Representation of (123) from the Symmetric Group S3 in terms of Quantum Circuits

2024-07-18T15:19:33+08:00

The symmetric group plays a vital role in abstract algebra, impacting mathematics and physics. Quantum circuits, especially in communication, utilize strategies like the CNOT gate and local unitary gates, influencing quantum cost. Minimizing this cost is crucial by using the fewest non-local unitary gates. The existing works proves that representing the element (12) in S₂ requires at least three CNOT gates, however, the representation of CNOT gates with the minimal quantum cost is still unexplored. This study focuses on the element (123) in S₃, aiming to reduce quantum costs. Using the Strassen tensor, we find the Schmidt rank for (123) is 7. With this, we prove that achieving (123) with only 2 CNOT gates is impractical. Exhaustive enumeration rules out 3 or 4 CNOT gates. We analyze circuit states after each CNOT gate application to eliminate non-equivalent configurations. Finally, we propose a construction using 6 CNOT gates for (123). We introduce theorems for cataloging non-equivalent circuits, tracking states pre- and post-CNOT gate operations, and computing outputs. Whether 5 CNOT gates suffice for (123) remains open. These theorems can extend to optimal circuit representations for other symmetric group elements, like (1234) and (12345).

Research on the Influencing Factors of Slow Traffic on Campuses Based on Data Analysis: A Case Study of the South Campus of Henan Polytechnic University

2024-07-18T15:28:35+08:00

With the continuous development of campus construction, university faculty and students have higher requirements for the quality of the campus commuting environment. However, the supply situation of most of the campus spatial configurations in China still cannot meet the slow traffic needs. Therefore, taking the South Campus of Henan Polytechnic University as the object, this paper adopts a quantitative research method with data through field research and questionnaire distribution, and uses machine learning Apriori algorithm to analyze the data association rules. A selection model of factors affecting the slow traffic was constructed to excavate factors related to the slow traffic in campus. Meanwhile, significantly related road spatial environment factors and the specific conditions of the campus were combined to propose improvement, so as to encourage faculty and students to participate in slow traffic which is good for health.

Development and Application of Modern Intelligent Control Theory

2024-07-18T15:30:48+08:00

Modern intelligent control theory has experienced multi-stage development from classical control to fuzzy control, neural networks, and model predictive control, which not only improves the flexibility and adaptability of control systems but also promotes interdisciplinary research. With the advancement of science and technology and social development, intelligent control theory will be further combined with machine learning, big data, and other fields in the future to promote industrial automation and technological innovation. This article reviews the development history of modern intelligent control theory, its main theories, and its applications in robot manufacturing, power electronics, and other fields. It also discusses the current challenges and future development trends in the field of intelligent control.

Break Out of the Sea Surface: Genetic Algorithm based Search Path Planning Model for Locating and Searching Submersible Lost in Deep Sea

2024-07-18T15:33:02+08:00

Deep-sea tourism and exploration, which require regulatory approval due to safety concerns, are burgeoning entertainment activities. Our study introduces a probabilistic model for locating missing submersibles to facilitate these approvals. The model predicts the submersible's location based on Newton's second law, analyzing three potential malfunction scenarios. It incorporates dynamics to account for variations in water flow and terrain, using a normal distribution to handle random location fluctuations. To address the complexities of deep-sea search and rescue, we propose a method that integrates detailed equipment selection, suited to the extreme conditions. Furthermore, we develop a discrete grid-based model for search path planning. This model simplifies path planning into a sorting optimization problem by connecting grid centers and calculating the probability integral for each grid. Our research also discusses the scalability of our positioning and search models, crucial for adapting to various deep-sea environments. We demonstrate the efficacy of our model through simulations and calculations, proving its potential to enhance safety and efficiency in deep-sea tourism projects. This comprehensive approach ensures that our probabilistic model not only predicts the submersible's location but also optimizes the search process, addressing both regulatory and practical challenges in the field of underwater exploration.

Research on momentum conversion in sports

2024-07-18T15:39:03+08:00

Momentum, traditionally examined in sports, is an ability to increase or develop continuously, impacting mental and physical performance in a pattern akin to human preferences, which are complex and non-linear. This research explores momentum in sports, particularly tennis, integrating it with the economic concept of diminishing marginal utility to analyze momentum shifts. Using data from the 2023 Wimbledon men's singles, the study dissects momentum into absolute and relative measures, revealing server advantage and precise models with an R-square value of 0.877. It employs macro and micro perspectives to link momentum with success, affirming its significant impact on win rates and performance dimensions. A GARCH model identifies influential factors in momentum transitions, informing strategies for game control. Applying the model to basketball, specifically a 2024 Clippers-Celtics NBA game, maintains strong predictive capabilities, indicating its broader applicability. Practical recommendations for tennis coaches and players, grounded in empirical findings, conclude the study, emphasizing strategic momentum utilization.

Generalized Frames in Finite Space and Applications

2024-07-18T15:41:06+08:00

In the field of signal and imaging processing, the Frame Theory is a practical-mathematical tool for analysis. Moreover, generalized frames such as K-frame and g-frame are also hot research topics in the field of analytics. We apply the conclusions of the frames in infinite-dimensional to the finite-dimensional space, which makes it easier for us to apply the conclusions in actual scenarios.

Grasp the Momentum: Define and Prediction Models for Accurate Trend

2024-07-18T15:48:31+08:00

In tennis, the concept of momentum is used to describe the reversal of a player's big lead. However, motivation in sports is subjective and difficult to quantify. To address this challenge, the study aims to build models that can predict momentum and successful streaks. We accomplished three main tasks. Task one involves assessing player motivation using a variety of metrics and analytic hierarchy process (AHP). Task two includes proving strong autocorrelation and testing fringes using run tests. The results show significant autocorrelation, which is suitable for momentum regression prediction. In Mission three, the random forest method is used to calculate the importance of features to provide suggestions for the player's next game. The long short-term memory (LSTM) model is used to predict the trend of the next game and the momentum of the players, showing good reliability and accuracy. The sensitivity analysis and robustness verification show that it is consistent with the actual situation and the error range is acceptable. Finally, the advantages and disadvantages of the model are summarized, and suggestions for further improvement are put forward.

Multi-Objective Parameter Optimization Strategy of Rheological Instability and Power Dissipation for Molybdenum Alloy Based on Genetic Algorithm

2024-07-18T15:51:48+08:00

Because of the limited performance of the core material of heat pipe reactor, the cooling effect of nuclear power source is restricted. Molybdenum alloy with excellent comprehensive performance has been a popular core material. To improve the performance of the molybdenum alloy hot forming process, the rheological instability and power dissipation of recrystallized molybdenum alloys are studied by orthogonal arrays L16 with three factors and four levels in this paper. Considering the experimental temperature, strain rate and true strain, the rheological instability and power dissipation are optimized based on a genetic algorithm (GA), with optimal process parameters of recrystallized molybdenum alloys obtained as follows by taking the rheological instability and power dissipation as the objectives. The experimental temperature is 792.424 ℃, the strain rate is 0.01 s-1, the true strain is 0.1N, the rheological instability is 0.23336, and the power dissipation is 0.6832. The rheological instability is increased by 21.79% and the power dissipation is decreased by 64.95% compared with that in the experiment (the experimental temperature is 650 ℃, the strain rate is 0.01 s-1, and the true strain is 0.1N in the experiment with similar parameters in the orthogonal arrays).

A Brief Survey for GPT Series

2024-07-18T15:54:28+08:00

Since the invention of GPT, the GPT language model has become an increasingly popular topic. ChatGPT as a recent hit point is built on the basis of GPT models, but so far there has been no comprehensive survey for GPT series. In this paper, we would like to present a brief survey of the GPT series and expound on the principle of GPT. Moreover, based on the development history and application scenarios of GPT, we report on the future prospects and applications of the GPT series.

Research on Personal Medical Information Protection Based on Big Data

2024-07-18T15:57:28+08:00

The rapid development of big data, cloud computing, and artificial intelligence has brought new opportunities to the development of the medical field. The emergence of electronic medical records and medical information systems has provided great convenience for people's medical treatment. However, the arrival of the big data era also poses new challenges to the protection of human medical privacy. The development and application of medical big data have led to explosive growth of data in the medical field, putting pressure on the management of medical institutions. The sharing of medical data between medical institutions and between medical institutions and third parties also poses significant security risks. Moreover, medical data leakage incidents have been continuously exposed in recent years, seriously infringing on the identity and privacy rights of patients. This article aims to explore the research on personal medical information protection based on big data. Firstly, the importance and necessity of protecting personal medical information were analyzed, as well as the current application status and existing problems of big data in medical information management. Secondly, a comparative analysis of domestic and international research on medical privacy protection was elaborated, including the analysis of medical information privacy protection standards in the United States, Europe, and Asia, and the differences and commonalities of international medical information privacy protection standards were compared and analyzed. Then, the theoretical basis of medical information privacy protection was summarized. Then, the application methods and technologies of big data in personal medical information protection were discussed. Finally, relevant countermeasures and suggestions for the protection of personal medical information in big data were discussed, including privacy protection technologies and policy recommendations, as well as ethical issues and norms for the protection of medical information privacy. Through this study, it is hoped that it can provide reference and inspiration for the protection of personal medical information in big data, and provide ideas and suggestions for future development directions.

The Security Threat and Precautionary Measures of QR Code of Internet of Things Technology

2024-07-18T15:59:37+08:00

The Internet of Things (IoT) is the expansion and extension of the traditional network. It is a network that connects goods and objects, which has been widely used in today's social development process. It occupies an important position in various industries. The emergence of the Internet of Things has greatly improved the refinement level of human management. The QR code (Quick Response Code) is a part of the perception layer of the IoT, which belongs to the perception and recognition technology of the IoT. The QR code not only brings convenience to users but also becomes the carrier and disseminator of malware, phishing, and other attacks. Therefore, it is of great significance for the security of the IoT to understand the potential threats of the QR code, analyze its potential attack methods, and put forward defense plans. This paper briefly introduces the basic characteristics of the QR code, as well as some attack methods and potential threats against the QR code, and put forward some preventive measures from both technical and non-technical aspects. The technical aspect includes the combination of cryptography and the introduction of third-party management. The non-technical aspects are discussed at the national and individual user levels.

Deep Learning-Based Fine-Grained Image Recognition

2024-07-18T16:03:24+08:00

Fine-grained image recognition (FGIR) is an important part of today's vision field. Unlike basic image classification, FGIR aims at recognizing multiple different dependent categories of meta-category objects. However, early FGIR faced many challenges, such as the fact that the differences between fine-grained images are subtle and the background is often noisy, which greatly affects the accuracy of the recognition performance. Now, with the cconstant development of deep learning in the field of optical recognition, FGIR has made large accomplishments and progress. In this paper, we make a more broad survey of deep learning-based FGIR methods in recent years and categorize these new methods. Then they are comparatively analyzed through recognized datasets in recent years to summarize the contribution of different methods to the current challenges. Eventually, the current state of research is analyzed and several directions for future research are put forward.

Coverage Probability Analysis for Uplink/Downlink Decoupled Access in Heterogeneous Cellular Networks

2024-07-18T16:05:37+08:00

Cellular networks are evolving into wireless heterogeneous networks with various types of base stations (BSs) including macro base stations and femto base stations. Since the traditional coupled access method is not able to meet the communication needs of the current users, uplink (UL) and downlink (DL) decoupled access is proposed, which refers that the BS selected in UL is unnecessarily the same as in DL. We commence by deriving the association probabilities for UL and DL decoupled access. Subsequently, we derive explicit analytical expressions for the joint distance distribution. Leveraging the tools of stochastic geometry, we obtain precise formulas for the coverage probabilities. Furthermore, we investigate the influence of the path loss exponent on the network performance. To validate the efficacy of our proposed analytical framework, we conduct extensive Monte Carlo simulations

A Survey of Deep Learning-Based Object Detection

2024-07-18T16:12:14+08:00

Object detection is a fundamental task in computer vision that plays a crucial role in various applications, such as autonomous driving, surveillance, and augmented reality. In recent years, deep learning techniques have revolutionized the field of object detection, achieving remarkable performance improvements. This paper presents a retrospective review of the field of object detection from a technological evolution perspective, covering various topics. It analyzes representative detection algorithms, including two-stage and one-stage detectors, as well as transformer-based detectors. It also describes datasets and evaluation metrics used in object detection. Additionally, the latest advances in object detection, such as multi-scale detection, lightweight detection, and rotation-invariant detection, are reviewed. Finally, the paper concludes by discussing the most promising future research directions in the field.

Intelligent Discrimination of Fruit Variety Quality Based on Bp Neural Network

2024-07-18T16:14:04+08:00

In recent years, thanks to the development of computer vision technology and digital image technology, traditional agriculture and information technology have been deeply integrated. This study uses image recognition and bp neural network technology to identify the types of fruits and selects apples as objects for quality evaluation. First, 150 images of apples, bananas, peaches, avocados, and cherries were selected from the fruit database Fruit360 after grayscale processing as a data set. After the images were grayscaled, image denoising, edge detection, and other feature processing in MATLAB, The classification of five kinds of fruits has been successfully realized, and the correct rate of evaluation reached 94.8%. Then divide the data sets for apples of different varieties and qualities, and input them into the bp neural network for training. After testing, the 6-layer bp network has the highest accuracy rate, and can effectively classify and score apple images.

Road surface crack detection and classification based on YOLOv5

2024-07-18T16:16:15+08:00

The burgeoning need for sustainable urban transportation has magnified the importance of effective road infrastructure maintenance, particularly road crack detection. This study addresses the challenge of accurately detecting road surface cracks through automated methods. To accurately identify road surface cracks, we used the YOLOv5 image recognition algorithm, enhanced by comprehensive data augmentation and meticulous training strategies. The YOLOv5 proved superior to traditional methods in accuracy and recall while maintaining high computational speed and a smaller model size in experimental outcomes. The findings affirm that YOLOv5-based detection technologies significantly improve maintenance efficiency and traffic safety, with future work poised to further refine these approaches for greater robustness and integration into intelligent transportation systems.

A study on graduation diversion of college students based on LDA model

2024-07-18T16:18:40+08:00

The significance of college students' graduation diversion is to effectively adjust the talent structure and improve the efficiency of social resource allocation. In this paper, firstly, through text mining, the diversion direction is divided into three parts, namely,taking Postgraduate Entrance Examination,get postgraduate recommendation and employment, and python is used to crawl the relevant comments on microblogging about graduation diversion. Then, the crawled text is applied the jieba library to split words. Then, the LDA topic model was applied to model the participle results, and a total of 11, 21 and 23 numbers were obtained for employment, postgraduate recommendation and Postgraduate Entrance Examination respectively. From the results of the model, it can be seen that college students choose to take Postgraduate Entrance Examination in the current graduation stream, and the number of getting postgraduate recommendation and employment is small. This suggests that the government should intervene in the employment environment, and it also suggests that college students should multitask simultaneously.

Study on the Influence of Step-by-step Excavation of Foundation Pit on Supporting Structure

2024-07-22T17:13:34+08:00

Aiming at the influence of step-by-step excavation of foundation pit on the internal force and deformation of supporting structure, this paper summarizes the research status of domestic and foreign scholars on this issue, introduces the calculation method of internal force of supporting structure, and uses GEO5 software and ABAQUS finite element analysis software to solve the internal force and deformation of supporting structure in the process of step-by-step excavation, and compares it with the measured results.

Study of flood protection water levels for railway projects in the plains river network area

2024-07-22T17:17:44+08:00

The Taihu Lake basin is characterised by a developed water system and a longitudinal river network, which is prone to flooding during the flood season. This poses a threat to the construction and operation of river-related railways, bridges, and other infrastructures, and therefore the design value of the water level of the river channel must be provided prior to the construction of roads and bridges in the basin. The Yanyi Railway traverses numerous river systems without the benefit of measured hydrological data. In order to address this deficiency, two methods were constructed using the Taihu Lake basin model: the historical water level frequency analysis method and the typical design storm method of the basin. These methods were employed to calculate the flood protection water level of each river under different design schemes and to analyze the reasons for the differences in the results. The results indicate that the water level results of the historical water level frequency analysis method are also applicable to the construction of the Yanyi Railway, provided that an economic perspective is taken.

Refined Identification and Spatiotemporal Characteristics of Drought and Flood Abrupt Alternation Events in the Poyang Lake Basin from 1965 to 2023

2024-07-22T17:23:54+08:00

This paper utilizes actual observation data from 75 precipitation stations in the Poyang Lake Basin (PLB), combined with the daily scale drought and flood abrupt alternation (DFAA) index, to analyze the occurrences of DFAA in the basin from 1965 to 2023. This includes the frequency and spatiotemporal variation of events, as well as the spatial variation in the intensity of DFAA events. The results indicate that there is no apparent temporal pattern in the frequency and intensity of events in the PLB, with spatial concentration mainly in the Fuhe, Xinjiang, and Raohe river basins. The analysis of a typical drought-to-flood event (DTF) in 1994 and a typical flood-to-drought event (FTD) in 2022 shows that the 1994 event progressed from the northeast to the south, and the prolonged drought following the 2022 event exacerbated the losses caused by the DFAA.

Study on energy dissipation and scour downstream of differential flip bucket in a spillway project

2024-07-22T17:28:45+08:00

The differential flip bucket has efficient energy dissipation capacity, but its impact on downstream erosion cannot be ignored. In this paper, the physical model test is used to analyze the water surface line of the spillway, the flow pattern and velocity distribution of the downstream river channel, and the erosion of the downstream river channel in the form of a differential flip bucket. The influence of the discharge flow on the project is studied, and the rationality of the engineering design is verified. It is found that the flip bucket tongue of the spillway falls into the plunge pool of the downstream river channel, and the flow pattern of the downstream main river channel is gradually stable after a certain distance adjustment. The depth of the stilling basin meets the requirements of energy dissipation and erosion prevention, but local protection is required at the end of the excavation of the downstream left bank slope, or the excavation type of the left bank of the stilling basin is optimized.

Lawyer Recommendation System Based On User Profiles And Collaborative Filtering

2024-07-22T17:34:33+08:00

This study discusses the difficulties that ordinary citizens face when dealing with legal problems in the process of China's rule of law, including high lawyer fees, lengthy litigation processes, the shortcomings of existing lawyer recommendation methods, and the lack of channels for efficient matching between user needs and lawyers. Currently, when seeking legal rights protection, citizens usually rely on referrals from acquaintances or search engines to find lawyers, but these methods have some issues. Lawyer recommendation platforms are still in the early stages of development in China, with problems such as data gaps, opaque information sources, and quality issues. To address these problems, this study proposes a user profile-based lawyer recommendation system, aiming to provide citizens with more accurate and centralized legal aid services, as well as establish an efficient user-lawyer matching channel.

Comprehensive Study of Load Characteristics of O-type Rotor Car Dumper Based on Measurements

2024-07-22T17:38:48+08:00

The car dumper, an essential apparatus for unloading bulk materials, is increasingly critical across various sectors such as electricity generation, metallurgy, and operations at port terminals. This significance stems from its continuous operational capacity, which significantly boosts the efficiency of bulk material handling and optimizes the overall processes at industrial sites. This research paper delves into the power quality problems associated with car dumper applications, particularly focusing on the harmonic disturbances caused by inverters used within these systems. Such disturbances can degrade the quality of power within the industrial grid, potentially leading to inefficiencies and safety hazards. To address these issues, the paper proposes the use of parallel active power filters (APF). These filters are renowned for their efficiency in controlling and mitigating harmonic disruptions in electrical systems. The implementation of APFs has shown promising potential to stabilize power quality by filtering unwanted harmonic frequencies and allowing for a smoother power flow. Through detailed measurements conducted on an O-type rotor quad car dumper, the study systematically analyzes the operational characteristics of the dumper, thereby forming a comprehensive database. This database aids in the optimization of electrical control strategies and operational methodologies for car dumpers.The primary objectives of this research are to enhance the operational efficiency of car dumpers, minimize their energy consumption, and improve overall safety measures. By integrating advanced harmonic control technologies such as APF, this study not only addresses the immediate issues of power quality but also contributes to the broader goal of sustainable and efficient industrial practices. The findings are expected to influence future designs and operations of car dumpers, making them more energy-efficient and less prone to electrical disturbances, thereby ensuring a safer working environment in industries dependent on heavy machinery for bulk material handling.

A Review of Studies on the Brewing Process of Italian Grape Ale

2024-07-22T17:42:14+08:00

Beer is one of the most consumed alcoholic beverages in the world, and in order to satisfy people's attraction to novel smells and tastes, the variety of beer is constantly enriched. Fruit beer has a unique flavor and taste brought by the use of fruit varieties, which can bring a good experience to consumers. Italian Grape Ale (IGA) is a new kind of fruit-flavored beer produced by adding grape matrix, which is more and more popular among people. This paper firstly describes the brewing process of Italian Grape Ale, the selection of raw materials, the selection of grape varieties, the addition method and the amount of addition. It is hoped that this review will provide the reader with an in-depth understanding of Italian grape ale and trigger further developments in this field.

Evaluation of the degree of satisfaction of river ecological flow —Taking the Kushui River in Ningxia as an example

2024-07-22T17:46:01+08:00

In order to comprehensively evaluate the degree of satisfaction of ecological flow in rivers, an evaluation system was constructed based on the daily average flow, monthly average flow, and the lowest monthly flow data of the Kushui River in Ningxia from 2017 to 2019, including indicators such as flow changes, flow satisfaction at different levels, ecological water demand guarantee, and monthly average ecological water demand suitability, to assess the health status of the Kushui River. The results showed that the minimum runoff of the Guojiaqiao hydrological station in the Kushui River during the dry season was relatively small, with a large gap compared to the annual average daily flow, but the degree of ecological flow guarantee was high, reflecting the seasonal and uneven distribution characteristics of the Kushui River. It is recommended to strengthen the research on the dispatching of water storage reservoirs, rationally allocate water, and gradually improve and improve the sustainable guarantee degree of ecological flow in the Kushui River.

Multi-levels Long-Narrow Lake Flood Routing Modeling

2024-07-23T17:17:48+08:00

Nansi Lake,as a long-narrow lake,has the same features as those of rivers during flood routing.According to topographical and hydrological conditions of Nansi Lake,aided by DEM and remote sensing images of the study areas,combining field investigation and survey,several factors are generalized including boundaries of lake region,river centerlines,river trunk lines,flow pathway lines,no-effective flow regions and river cross section lines.The regions with fish ponds and densely covered by water plants are considered as no-effective flow regions.A coupled method to divide computed unit is adopted by topological generalization method under the multi-levels topological conditions.Flood routing models are built separately for the upper lake and the lower lake divided by the second-level dam constructed at the middle part of Nansi Lake,with individual topological relations,applying the method of comprehensive roughness.The models are tested and simulated by three actual floods in the past,the results manifest that it is feasible and effective to consider Nansi Lake as a river to build 1-D flood routing models.

The clinical application and experience of acupuncture in the treatment of asthma assisted by intelligent technology

2024-07-23T17:23:32+08:00

Asthma, a prevalent chronic respiratory disease, impacts patients' quality of life. Traditional acupuncture therapy is effective but lacks personalization. This paper introduces AI technology into acupuncture treatment, proposing an intelligent assistance system. The system uses patients' physiological and imaging data to construct an intelligent diagnostic model, accurately identifying conditions and symptom types. Through reinforcement learning optimization algorithms, personalized acupuncture plans are tailored for each patient. Clinical trials show that AI-assisted acupuncture significantly improves symptom scores, lung function, and reduces attack frequency, enhancing clinical efficacy and serving as a valuable tool for traditional Chinese medicine acupuncture training.

Effect of three alkaline impurities on the pressure of 1,2, 4-triazole pyrolysis gas

2024-07-23T17:27:00+08:00

1,2,4-triazole is now widely used in the production of pesticides and medicine, and progress has been made in the application of materials. The structural characteristics of 1,2,4-triazole with high nitrogen content will cause it to the release of a large amount of gas when it occurs pyrolysis, which may have a certain impact on industrial production safety. In the industrial process, there will be some other impurities mixed into it, so the influence of these impurities on the 1,2,4-triazole pyrolysis gas is worth exploring. In this study, the adiabatic acceleration calorimeter was used to simulate the adiabatic conditions to study the pressure value of the gas generated by the pyrolysis of 1,2,4-triazole itself, and the influence of the addition of three basic impurities on the overall pyrolysis pressure value. Experiments show that these three impurities can affect the pressure value of pyrolysis gas in different degrees. The results can provide reference for the loss prevention and control of 1,2,4-triazole in industrial production.

A DPD Algorithm of Maximum Likelihood Based on DOAs and Doppler

2024-07-23T17:39:02+08:00

Direct position determination (DPD) is a single step method that estimates the position of target by received signals. Localization in 3D scene is a complicated problem, because the signal propagation channel is complex, and it has many kinds of interference and noise. This paper establishes the Over-the-horizon (OTH) shortwave signals and line-of-sight propagation of ultra short wave model, and proposes a joint localization algorithm. We compare the Cramér-Rao Bound(CRB) and the root mean square error (RMSE) between the proposed algorithm and DPD used single information like DOA and Doppler. The simulation results verify the superiority of the proposed algorithm, and prove it has higher accuracy.

Landscape Architecture Carbon Emission Lifecycle Management Tool Based on Artificial Intelligence

2024-07-24T16:26:05+08:00

In the contemporary discourse, carbon emissions have emerged as a focal point of global concern due to their role in inducing climate warming and precipitating ecological collapse. The establishment of a comprehensive carbon emission management system, coupled with effective measures, holds the potential to mitigate climate change, safeguard ecological integrity, improve health conditions, and promote global sustainable development. The Carbon Lifecycle AI Project Management Tool (CLA) proposed in this paper makes use of Large Language Model (LLM) and image processing model to intelligently analyze and manage the carbon emission of landscape architecture throughout its life cycle, and focuses on solving the carbon emission problem in landscape architecture. By gathering, integrating, and analyzing data related to landscape architecture, including information on material selection, plant configuration, and energy utilization, comprehensive monitoring and management of carbon emissions from landscape architecture are achieved. CLA not only offers real-time monitoring and analytical capabilities for carbon emissions but also identifies emission reduction opportunities and provides corresponding optimization recommendations, thus offering crucial support for the sustainable development of the landscape architecture industry.

Simplified Assessment of Deterioration in Old Industrial Buildings: A Case Study of Jiaxing Metallurgical Machinery Factory

2024-07-24T16:30:23+08:00

Under the background of the national policy of revitalizing old industrial areas by shutting down two-thirds of outdated factories, a significant number of aged industrial facilities are poised for adaptive reuse. Determining whether these old industrial buildings and their ancillary structures need to be "retained, renovated, or demolished" before reuse is a critical step in heritage conservation. The assessment of structural integrity is a prerequisite for evaluating whether to retain or demolish old buildings, which typically involves considerable time, effort, and high costs. In order to save costs and enhance the efficiency of inspections for each building, a simplified assessment method is employed to evaluate the integrity of buildings. Fuzzy evaluation method is utilized to assess the structural integrity of entire buildings, while the Analytic Hierarchy Process (AHP) is applied to determine the weights of the main load-bearing structures (slabs, beams, columns) and enclosing structures (exterior walls). Taking the Jiaxing Metallurgical Machinery Factory as a case study, the degree of deterioration of 61 buildings within the factory area is evaluated and ranked to provide technical support for subsequent demolition or preservation.

Static and dynamic load test on concrete hollow-core slab bridge

2024-07-24T16:36:31+08:00

In this paper, dynamic and static load test were carried out on a multi-span reinforced concrete simply supported hollow core slab bridge in Shenyang, Liaoning Province. Through the static load test, the quality and reliability of the project are evaluated, and the results show that under the action of 0.88 times of highway-classⅠload, the deflection and strain check coefficients of the control section of the tested condition are less than 1, which meets the specification requirements, and the measured relative residual deformation and relative residual strain are less than 20%, and the bridge structure is basically in the elastic working state. And combined with the finite element analysis model, the comparison between measured data and calculated data is carried out. Through the dynamic load test, the self-oscillation frequency and damping ratio of the superstructure were tested, and the results showed that the measured damping ratio was 0.690%, the first-order measured vibration pattern conformed to the variation rule of the vibration pattern of the simply supported girder bridge, and the measured self-oscillation frequency was 13.594 Hz, and the measured self-oscillation frequency (fundamental frequency) was greater than the calculated frequency, and the structural actual stiffness was greater than the theoretical stiffness, and the working condition was good. This study is of great significance for the assessment of bearing capacity and quality control of concrete hollow core slab bridge, and provides a useful reference for bridge design and operation.

Urban Climate Change Resilience and Adaptation Assessment in Semi-arid Region Based on TOPSIS Analysis Method

2024-07-24T16:42:28+08:00

This research delves into the assessment framework and progress of urban climate resilience and adaptability in semi-arid areas, using Gansu Province as a case study. An assessment of the overall climate resilience and adaptability of Gansu Province was conducted by establishing a comprehensive evaluation index system and utilizing the TOPSIS method for integrated analysis. Among the prefecture-level cities and autonomous prefectures, Lanzhou exhibited a high level of resilience, whereas Baiyin displayed lower resilience. The results highlight significant variations in urban resilience levels across Gansu Province, influenced by diverse factors. Therefore, it is imperative to develop climate adaptation plans tailored to different cities' specific conditions to enhance urban climate resilience and achieve sustainable development objectives.

Comparative Analyses of Electro-Palatoraphic Features in Uighur and Chinese Fricative /s/

2024-07-24T16:47:22+08:00

This article examines the Uighur and Chinese fricative /s/ with specific vowels by using Electropalatograph. By investigating similarities and differences in the alveolar region, blocking segments, and synergistic articulation, it proves that Uighur and Chinese fricatives /s/ are both lingual anterior consonants due to the same or similar articulatory places. During articulation, they share some commonality. Firstly, the contact between tongue and palate in the target frame is reduced when fricative /s/ is pronounced in both languages. Secondly, the tongue-palate contact primarily occurs in the gingival area. However, it has a larger Anterior Contact than Posterior Contact. Additionally, without complete obstructions between the tongue and palate, there is a gap between the tip of the tongue and the gingiva, allowing an airflow to articulate the fricative. Most important of all, a comparative analysis reveals distinctions between Uighur and Chinese fricatives /s/ from the aspect of synergistic articulation. The Uighur /s/ has tongue-palate contact with the soft palate in the hard palate region, which is not obvious in Chinese fricative /s/.

Erosion Pits Distribution Characteristics of Nanosecond Pulse Gas Spark Switches at Different Repetition Rates

2024-07-24T16:53:13+08:00

Gas spark switches are widely used in the field of nanosecond pulses. Lifetime is one of the key parameters of a gas spark switch, which is closely related to the distribution of erosion pits A repetition rate nanosecond pulsed discharge experimental platform is set up to investigate the distribution characteristics of erosion pits on the electrodes of nanosecond pulsed gas spark switch under different repetition rates. The distribution of erosion pits on the electrodes at different repetition rates has been analyzed statistically through a metallographic microscope. The results indicate that the range of erosion pits on the surface of electrodes is linearly related to the repetition rate. As the switch repetition rate increases, the range of erosion pits expands. The range of erosion pits on the cathode surface is slightly larger than that on the anode. When the repetition frequency increases from 1 Hz to 100 Hz, the radius of the anode pit range increases from 7.27 mm to 9.2 mm, and the cathode pit range increases from 8 mm to 9.73 mm. The density of erosion pits is related to the normalized electric field intensity in power function. With the increase in repetition rate, the tendency for erosion pits to concentrate at the geometric center of the electrode weakens. This research is of significant importance for the design of long-life gas spark switches.

Analysis on the stability of a coal mine's dumping slope and its influence on oil pipeline

2024-07-24T16:57:28+08:00

There is cross-interference between an-yu-meng line of Yunnan product oil pipeline about 920m and NO.1 dump of a coal mine. In order to analyze the stability of the dump slope under heavy rain and other working conditions, and the influence of the dump continued dumping on the pipeline safety, combined with the geological environment conditions, quantitative calculation of stability and numerical simulation in the study area, a comprehensive analysis is carried out. The results show that the south section of the dump is about 200m long and unstable under heavy rain, and the other sections are in a stable state, because the pipeline in the south section of the dump is located at the foot of the dump slope, the soil has the possibility of squeezing and shearing the pipeline, and the cross-interference pipeline in the north section of the dump is about 490m long, the northern section of the dump has a good stability. Most of the pipelines are buried at a depth of 1.5 m ~ 2 m, and the local depth is 7.5 m. the buried depth of the pipelines is in strongly weathered basalt, which is beneficial to the safety of the pipelines, the slope of the pipeline is inclined to the west, the slope of the pipeline is inclined in the opposite direction to the lateral compression of the dump, and the possibility of the pipeline forming lateral shear is small, the main hazards of the north slope instability to pipelines are burial and impact. The research results provide basis for safety evaluation and later treatment design of pipeline in cross-interference section of dump slope.

A Semi-smooth Newton Method for Diffuse Optical Tomography with L1-Norm and Total Variation Regularization

2024-07-24T17:05:14+08:00

This study introduces a novel multi-measurement Diffuse Optical Tomography reconstruction method that employs both L1-norm and Total Variation regularization, solved by the semi-smooth Newton method. By integrating L1-norm regularization to address sparsity and TV regularization to preserve edges and structural details, our approach effectively combats the ill-posed nature of DOT reconstructions. The results demonstrate that our approach reduces the required iterations while simultaneously maintaining or enhancing reconstruction accuracy and robustness to noise.

Isolation and identification of postharvest pathogenic bacteria of nectarine and antibacterial test of essential oils

2024-07-24T17:24:03+08:00

With 'Rose Red' nectarine as the test subject，postharvest pathogenic bacteria were isolated，purified，and identified. Their pathogenicity was determined using Koch's postulates，and the antibacterial activity of 28 types of plant essential oils against highly pathogenic bacteria was assessed.The results showed that a highly pathogenic pathogenic fungus TBZ1-9 was isolated and identified from peach fruits and had a high genetic relationship with Fusarium oxysporum. Among the 28 essential oils, mustard and Achyranthes essential oil (1000 μl/L) had the most significant antibacterial effect on strain TBZ1-9, with an antibacterial rate of 100%.500 μl/L Achyranthes essential oil had the best inhibitory effect on the TBZ1-9 strain, and the antibacterial rate was still >85% after 12 days of treatment. In summary, it was determined that the pathogen causing postharvest diseases of nectarines is Fusarium oxysporum, which is highly pathogenic. 500 μl/L Achyranthes essential oil has the best inhibitory effect on F. oxysporum.

Isolation and identification of postharvest pathogenic bacteria of Syzygium samarangense and antibacterial test of essential oils

2024-07-24T17:29:59+08:00

With Syzygium samarangense as the test subject，postharvest pathogenic bacteria were isolated，purified，and identified. Their pathogenicity was determined using Koch's postulates，and the antibacterial activity of 36 types of plant essential oils against highly pathogenic bacteria was assessed. The findings indicated that a highly pathogenic fungus was isolated and identified from naturally existing S. samarangense, labeled LW3-1. The pathogenicity rate of strain LW3-1 reached 100% within 2 days of inoculation, and molecular biology identified it as Colletotrichum gloeosporioides. Among the 36 essential oils, clove, geranium, myrrh, rose and sophora flavescens essential oils (1000 μl/L) had the most significant antibacterial effect on the LW3-1 strain, with an antibacterial rate of 100%. The antibacterial rate of 500 μl/L clove essential oil against the LW3-1 strain was still >85% after 12 days of treatment. In summary, it is determined that the pathogenic bacteria causing postharvest diseases of l S. samarangense is C. gloeosporioides, which is highly pathogenic. 500 μl/L clove essential oil has the best inhibitory effect on C. gloeosporioides.

Temperature control technology on construction of large volume concrete

2024-07-24T17:37:12+08:00

After the pouring of large volume concrete, the internal hydration heat is accumulated and not easy to send out. However, the surface heat sending is faster, and then the temperature difference between inside and outside is bigger, so the compressive stress is generated in the interior of the concrete and In the concrete external tensile stress is occurred, which eventually led to temperature cracks in the concrete surface. In the north latitude of 45 degrees, Harbin, in order to avoid unfavourable factors during the large volume concrete pool construction, the appropriate and effective temperature control measures must be taken to prevent the temperature cracks harm to the safety and durability of the structure.

Opportunities and Challenges in Hospital Financial Management Digitization Transformation: A Summary

2024-07-24T17:40:35+08:00

The rapid development of information technology has created opportunities for the digitization of hospital financial management. This article examines the opportunities and challenges from the perspectives of technology, human resources, and data, and proposes implementation strategies.New technologies like big data and AI support the transformation but also present challenges such as integration and data security. In human resources, the influx of young employees and talent cultivation drive transformation, yet issues like the shortage of compound talents and integration of old and new staff persist. Improving data quality is crucial, but data fragmentation and privacy concerns need urgent attention.The article suggests strategies such as developing a clear transformation roadmap, enhancing human resource training, and improving data governance and security to guide the digitization of hospital financial management.

High Frequency Breakdown Characteristics of Alumina Filler Content Epoxy Resin

2024-07-24T17:44:39+08:00

Power electronic transformers have high insulation frequency and compact insulation structure, and insulation performance is one of the main factors restricting their further development. Epoxy resin is an important insulating material in the electrical industry, its thermal conductivity and mechanical properties can not meet the needs of high-frequency transformers, usually metal oxide (Al2O3, etc.) is added to form composite insulation material. It is of great reference value for the insulation design of power electronic transformer to study the insulation performance of composite insulation materials with different filler content ratio under high-frequency AC. The effects of power supply frequency and alumina filler content on the breakdown performance of the composite were investigated experimentally. The results show that the breakdown voltage of pure epoxy resin decreases exponentially with frequency. At any filler content, the breakdown voltage of epoxy resin decreases with the increase of frequency, and the decreasing trend gradually slows down when the frequency increases from 50Hz to 1000Hz, and the decreasing trend gradually increases when the frequency increases to 2000Hz. The breakdown voltage of epoxy resin showed a down-rise-down trend with the increase of filler content, and the effect of filler content on breakdown voltage gradually weakened with the increase of frequency.

Research on the influencing factors of evolution of oil trade network based on TERGM model

2024-07-25T11:36:48+08:00

This paper constructs a trade network using global oil trade data from 2001 to 2021, and uses TERGM model to explore the factors influencing the evolution of oil trade network. We found that the structures mutual, transitive closure, 3-outstars and 3-instars all boost the evolution of the oil trade network while cycle closure structure impede the evolution of the oil trade network. In addition, the level of national economic development inhibits the change of oil trade relations. Finally, geographical distance has little effect on the evolution of oil trade network, and the national border and common language have positive effect on the evolution of oil trade network.

A method for allocating demand response benefits considering contribution degree

2024-07-25T11:48:33+08:00

To enhance the operational level of demand response transactions in the new power system and meet the requirements for refined management of demand response transactions, this paper proposes a novel method for allocation of demand response benefits. This method introduces the concept of contribution degree, and based on considering the contribution degree of agent users, it achieves a refined allocation of demand response benefits. This approach enables precise evaluation of agent users' participation in demand response, effectively enhancing their enthusiasm to engage in demand response, and promoting the level of market-oriented transactions in demand response. Practical applications have demonstrated the accuracy and effectiveness of this scheme in market-oriented demand response transactions.

Solidification microstructure and properties of Ni(60-y)Fe20Co10Cr10Aly high-entropy alloys

2024-07-25T11:53:30+08:00

A series of eutectic high-entropy alloys Ni_(60-y)Fe₂₀Co₁₀Cr₁₀Al_y (y = 0, 5, 10, 15, 20, 25) were synthesized via non-consumable vacuum melting, followed by investigation into their solidification microstructures and compression properties. The research results reveal that the solidification microstructures transition from a well-distributed FCC phase (y-0, y-5) to a coarse FCC+B2 isometric crystal structure (y-10), subsequently to a primary FCC phase with a (FCC+B2) eutectic structure (y-15), succeeded by a predominant B2 phase with a (FCC+B2) eutectic microstructure (y-20), and ultimately to a BCC+B2 biphasic structure characterized by periodic braided sheets (y-25). The FCC phase demonstrates a substantial concentration of Ni and Fe, the BCC phase shows substantial enrichment primarily in Fe and Cr, while the B2 phase exhibits significant enrichment in Ni and Al. As the Al content increases, the alloys exhibit higher strength but reduced plasticity. Specifically, alloys with y values of 20 and 25 exhibit yield strengths of 1012 MPa and 1477 MPa, respectively, coupled with remarkable plasticity of 41 and 23%, thereby demonstrating robust mechanical properties.

The Nearshore Marine of ShenZhen Environmental Risk Assessment Method Based on the DPSIR Framework

2024-07-25T14:03:20+08:00

The nearshore marine areas are the most intensely concentrated regions for human economic activities and serve as vital carriers for the development of the marine economy. Accurately assessing the environmental risks in these areas is of significant importance for the sustainable development of the marine economy. This study constructs an environmental risk assessment system for the nearshore marine areas of Shenzhen City based on the DPSIR framework and evaluates it using the comprehensive index method. Specifically, the study begins by selecting 27 indicators related to the marine environment to construct the evaluation index system. It employs the grey relational analysis and entropy weight method to weight the indicators and finally assesses the environmental risks of Shenzhen's nearshore marine areas from 2013 to 2020 using the comprehensive index method. The study finds that the environmental risks of Shenzhen's nearshore marine areas from 2013 to 2020 are generally low, with the risk score increasing from 0.3277 to 0.7308 year by year, shifting from a more dangerous to a safe risk level. The research indicates that the marine environment of the nearshore areas in Shenzhen is greatly influenced by local human economic activities and the industrial structure of Shenzhen. The study suggests that the environmental safety level of Shenzhen's nearshore marine areas could be improved by leveraging policy guidance, optimizing the industrial structure, and perfecting tourism management methods.

Establishment and application of real-time monitoring system for mine ventilation resistance

2024-07-25T14:11:06+08:00

The monitoring of ventilation resistance in domestic coal mines is generally faced with two problems: huge workload and lagging monitoring data behind production, which is due to the backward monitoring technology. In recent years, with the progress of technology and equipment in the coal industry, ventilation resistance monitoring products have appeared in the market one after another, but they still face the following main problems: (1) the sensor measurement error needs to be further improved; (2) The monitoring scheme is relatively simple, and the use of absolute pressure multi-parameter monitoring faces two problems: measurement error and construction cost; (3) There is a lack of successful application cases of ventilation resistance monitoring in the industry, and the analysis and application of ventilation resistance monitoring data by the upper computer is insufficient. In view of the above problems, this paper studies the principle, monitoring scheme, system framework and practical application of ventilation resistance monitoring, aiming to solve the problem of real-time online monitoring and analysis of ventilation resistance.

Analysis and Research on Vibration of Hydraulic System at the Three Gorges Ship Lift Chamber

2024-07-25T14:15:05+08:00

The hydraulic pump station at the lower head of the Three Gorges ship lift chamber primarily controls the opening and locking of the chamber gate, the lifting and locking of the anti-collision truss, the tensioning and release of the anti-collision buffer cylinder, and the extension and retraction of the sealing frame. The chamber gate is influenced by external forces such as water flow during the opening and closing process. The anti-collision truss, being in a single-arm suspended state, is affected by external wind forces during its lifting and lowering process. The operation of these mechanisms induces significant vibrations in the hydraulic system, which can lead to oil leakage at joints and other points. Leakage in the hydraulic system can affect the operation of the chamber gate, anti-collision truss, and sealing frame, and severe leakage can directly lead to the malfunction of these mechanisms. This paper utilizes accelerometers, data acquisition systems, and handheld spectrum analyzers to analyze the vibration of the hydraulic system, aiming to reduce system vibrations and decrease oil leakage occurrences.

Functional Study of Anticoagulant Ice Asphalt Mixture with Slow-release Agent

2024-07-25T14:18:45+08:00

Based on the difference in freezing points of various chlorides, a multi-component synthesis method is employed to produce mixed chlorides with desired freezing points. To address the issue of chloride dissolution time, a sustained-release agent is used to encapsulate the mixed chlorides, creating an anti-coagulant ice modifier that controls release time. Indoor testing is conducted to verify its functionality and durability.

Study on Variation Law of Ground Pressure before and after Hard Roof Fracturing

2024-07-25T14:22:30+08:00

Hard roof has the characteristics of small fracture development, good structural integrity and strong integrity, and the hanging roof area is large during mining, which seriously threatens the safety production of working face.Based on the characteristics of hard roof such as high strength, large thickness and difficulty in self-caving, directional drilling hydraulic fracturing is adopted to destroy the structural stability of hard roof and make it reach an ideal fracture form. At the same time, the variation law of strata behavior in working face before and after fracturing of hard roof is explored.The results show that:①During the normal weighting period of hard roof working face, the support pressure of working face is generally small, but when the hard roof is broken, it will cause the phenomenon of strong weighting in working face, which threatens safe production;②Hydraulic fracturing leads to secondary development of primary fractures in hard roof and continuous diffusion in the form of fracture network, which destroys the original bearing structure of hard roof and forces hard roof to collapse ahead of time;③Thirdly, comparing the weighting law of working face before and after fracturing, it is found that after pressure relief, the initial weighting step of working face decreases by 50.8 m, which is 56.4% year-on-year, and the average periodic weighting step decreases by 3.7 m, which is 21.4% year-on-year. After pressure relief, there is no strong strata behavior in working face, and hydraulic fracturing achieves the expected effect.