To accurately capture the complex relationship between PM2.5 and predictive factors, and to obtain spatially continuous PM2.5 pollution distribution with higher resolution and prediction accuracy, a regional PM2.5 pollution early warning mechanism is constructed.In this study, the firefly algorithm-support vector machine (FA-SVM) is used to optimize the land use regression (LUR) model, estimating the PM2.5 mass concentrations in the Fenwei Plain in 2019 at a spatial resolution of 1 km.The results indicate that, compared to conventional LUR and SVM models, FA-SVM demonstrates superior predictive performance.The ten-fold cross-validation coefficient of determination for FA-SVM is as high as 0.90, with a root mean square error and mean absolute error of 12.29 μg/m3 and 8.99 μg/m3, respectively.In contrast, the validation coefficient of determination for LUR and SVM are 0.75 and 0.85, respectively, with root mean square error values of 19.57 μg/m3 and 14.37 μg/m3, and mean absolute error values of 14.84 μg/m3 and 9.62 μg/m3, respectively.PM2.5 pollution in the Fenwei Plain in 2019 exhibits significant spatiotemporal heterogeneity.Temporally, PM2.5 pollution is most severe in winter, gradually decreasing in spring, autumn, and summer.Spatially, areas with relatively higher economic levels show higher PM2.5 mass concentration, forming high-value aggregation zones, while the Qinling Mountains region represents low-value aggregation zones.Overall, PM2.5 exhibits a spatial pattern of higher concentrations in the central region and lower concentrations in the surrounding areas.
In response to the motion blur and visual interference problems resulting from the high-speed movement of unmanned aerial vehicles(UAVs),this paper presents a quality optimi-zation method based on dynamic interpolation and adaptive image enhancement.First,a dynamic blur kernel is constructed in accordance with the target trajectory and image feature point track-ing.By integrating interpolation techniques,a dynamic image interpolation method is developed to restore the crucial details of the image.Subsequently,by incorporating three image enhance-ment techniques such as histogram equalization,an adaptive image re-processing strategy is pro-posed to comprehensively optimize the image quality.Finally,this paper simulates the image deg-radation scenarios of UAVs,creates a corresponding dataset,and conducts comparisons of image quality improvement and verification of the enhancement of its application effects.The experi-mental results indicate that,compared with traditional de-blurring techniques like Wiener filte-ring,the method proposed in this paper minimally improves three metrics,namely the peak sig-nal-to-noise ratio,by 19.3%,55.1%,and 8.7%respectively.In applications based on the YOLO model,it enhances the recognition accuracy by more than 13.4%,thereby strengthening the target identification ability of high-speed UAVs.
User access behavior changes over time and in the environment,making it difficult to accurately capture data features and affecting the effectiveness of user access data mining.There-fore,a new user access data mining method was proposed in the article.Firstly,Z-score and mean imputation methods were used to process user access data.Secondly,for the processed user access data,a relative positional self-attention mechanism was used to capture the relative positional re-lationship,mine the connections between these scattered related access behaviors in a long se-quence,and complete the feature extraction of user access data.Finally,the extracted features were used as clustering centroids to complete user access data mining through K-means cluste-ring.The experimental results show that the method proposed in this paper performs well in data mining accuracy,with normalized mutual information(NMI)values and adjusted rand index(ARI)values both exceeding 0.95,and area under curve(AUC)values close to 1.At the same time,this method also has significant advantages in terms of memory occupancy,with a memory occupancy rate of less than 2%,effectively reducing memory overhead and improving resource u-tilization efficiency.This method has broad application prospects in fields such as user behavior a-nalysis and personalized recommendation.
Aiming at the issue of the shape of Han women's wedding dresses in the Qing dynasty,The existing portraits of women's dress in the Qing dynasty and the old wedding photos retained from the late Qing dynasty were made as research objects in this study.By integrating textual research with visual analysis,an in-depth exploration of the evolution of Han women's wedding dress shapes were conducted during the Qing dynasty.The research shows that the Han women's wedding dress is usually a combina-tion of phoenix coronet,jacket,horse-face skirts and small shoes.In the middle and late Qing dynasty,the cloud shoulder gradually became popular with the embrroidered cape combination,the phoenix coro-net shape evolved into a semi-crown type,and the embrroidered cape evolved into a"vest-like".The jacket gradually integrated into the Manchu costume elements,and the horse-face skirts evolved into skirts such as pleated skirts,Langan skirts,phoenix-tailed skirts,and Yuehua skirts.The research con-clusion has reference significance for the study of traditional wedding dress shape in China.
Solar photocatalytic natural ventilation has attracted wide attention because of its pas-sive ventilation and indoor pollutant purification effect,but it has low ventilation and purification efficiency.Using mechanical ventilation to assist in the construction of photocatalytic multiple ventilation can effectively overcome the lack of passive ventilation,and improve the purification efficiency of indoor pollutants.A pollutant flow diffusion model coupled between photocatalytic multiple ventilation wall and indoor environment was constructed.Secondly,the connection be-tween the structural optimization of the ventilation wall and the indoor air flow distribution was analyzed.Finally,the influence of mechanical ventilation assistance on indoor pollutant ventilation and purification energy efficiency of the model system was analyzed to verify the practicability and indoor comfort of the model.The results show that the average indoor concentration of the me-chanically assisted solar photocatalytic natural ventilation model can be reduced by 1 step com-pared with the traditional model,and the purification rate can be up to 29％.When the inclination height of the model is 0.15 m,the ventilation performance is optimal and the ventilation volume can reach 0.349 m3/s.The thermal performance of the system model is optimized and can be re-duced by up to 11 J,which can effectively avoid the indoor overheating problem of the traditional ventilation wall model in summer.The research fully considers the optimization of building ener-gy saving and indoor comfort and reduces the seasonal limitation impact of traditional solar natu-ral ventilation wall,so as to provide reference and basis for improving the performance of solar ventilation wall and the indoor environment.
To investigate the control effectiveness of different ventilation modes on major indoor pollutants, focuse on formaldehyde, CO2, and indoor/outdoor PM2.5 concentrations. Field measurements were conducted in 19 residential households in Xi'an across typical seasons over a oneyear period, while 31 households were continuously monitored online for two and a half years. The study further identifies the optimal ventilation modes for different pollutants.The results show that the mass concentration of indoor formaldehyde is highest in summer and lowest in winter.Under natural ventilation for 1 hour, the removal effect is the best, reducing the formaldehyde concentration from 200 μg/m3 to below 80 μg/m3.The volumetric concentration distribution of indoor CO2 is negatively correlated with the variation of outdoor temperature.The optimal strategy is to primarily use natural ventilation, supplemented by air purifiers.The mass concentration range of indoor and outdoor PM2.5 is strongly correlated with outdoor temperature.The optimal mode is to close windows and operate a fresh air unit, which can effectively reduce the indoor PM2.5 mass concentration.
The human body is an open thermal system.Many scholars put forward human body energy balance model to analyze the heat exchange process between the human body and the indoor thermal environment.However, due to the loss in the heat exchange process, some scholars established human body exergy balance model and conducted related research.Exergy emphasizes the ability to do work, while entransy emphasizes the ability to transfer heat; therefore entransy is more suitable for studying the heat transfer or exchange between human body and thermal environment.Based on Gagge's two-node human thermal balance model and the definition of entransy, this paper establishes the human entransy balance model, deduces the calculation formula of human entransy dissipation, and analyzes the influence of indoor thermal environment parameters on human entransy dissipation.The results show that when the air relative humidity is 30%～70%, the human entransy dissipation first decreases and then increases with the increase of air temperature and average radiation temperature, and air temperature and average radiation temperature have great influence on the entransy dissipation of human body.When the air temperature and average radiation temperature are 20～30 ℃, the human body entransy dissipation decreases with the increase of air relative humidity.When the air temperature and the average radiation temperature are both less than 25 ℃, the change of air relative humidity has little influence on the entransy dissipation of human body.
Photovoltaic power generation is influenced by weather factors,which results in strong insta-bility and intermittency,so accurate prediction of it faces great challenge.To improve the accuracy of pho-tovoltaic power prediction,we proposed a short-term photovoltaic power prediction method that com-bines empirical mode decomposition(EMD),wavelet threshold denoising,and sparrow search algorithm(SSA)optimized Informer model.First,to reduce the impact of noise on model prediction,EMD was ap-plied to decompose the input features,obtaining multiple intrinsic mode functions(IMF).Then,the wavelet threshold denoising method was applied to each IMF to remove the noise components,and final-ly,the denoised IMFs were reconstructed into a one-dimensional signal.This process significantly im-proved the data quality,providing cleaner and more accurate input for the subsequent model.To enable the Informer model to better adapt to the data characteristics,SSA was introduced to optimize the hyper-parameters of the Informer model.Through the global search ability of SSA,it effectively avoided the lo-cal optimum problem,thus enhancing the model's prediction accuracy and generalization ability.Compared with traditional single prediction models,experimental results show that the proposed prediction model not only effectively improves prediction accuracy but also significantly reduces errors under different weather conditions.For complex weather,in particular,the mean absolute error(MAE)and mean-square error(MSE)have notably decreased,verifying the superiority of this method in photovoltaic power prediction.
In Qing dynasty theatrical costumes,the girdle is an important component,serving both a practical function and symbolizing social status.The method of multiple evidence and compara-tive research were adopted to explore the hierarchy of girdles in Qing dynasty opera costumes,and analyzed the shape,pattern,and evolution of leather girdles in Qing dynasty palace clothing.By collecting and sorting out the objects and documents related to Qing dynasty opera costume gir-dles from different museums.The results show that the types of Qing dynasty opera costume gir-dle can be summarized into four types as a whole,among which leather girdle are the highest-level and most unique type,mostly used for roles such as emperors,generals,gods,queens,princesses and ladies.The shape and pattern of the leather girdle change with the change of palace clothing style,and it experiences an evolution process from simplicity to complexity and then to extreme decoration.This evolution not only reflects the development of opera art,but is also closely relat-ed to the aesthetic concepts and social and cultural background of the rulers at that time.The transformation of leather girdles in imperial robes—from simplicity to complexity,and from fru-gality to extravagance—represents not only an artistic change on the surface of Qing material cul-ture but also serves as historical evidence of the societal shift from prosperity to decline.
To investigate the diffusion characteristics of pollutants in single and multi-street val-leys under the effect of thermal pressure,as well as the influence law of the peak position of the street valley on the flow field within the street valley,the simulation of the radiation situation of the sunlit side of the building in actual circumstances was carried out.Through fitting the temper-ature change curve of the transition zone between the sun radiation area and the shadow area,the flow field,temperature,and pollutant distribution within the street valley under the action of ther-mal pressure were analyzed.The results show that with the temperature difference rising from 5 K to 30 K,the concentration of pollutants in the center of the single street valley gradually de-creased by about 30%.The distribution of pollutants in multi street valleys is affected by conver-gent flow.When the number of street valleys increased from 3 to 10,the pollutant concentration in the left street valley significantly increased,with the maximum increase approaching 40%,while the pollutant concentration in the right street valley decreased.The position of valley peak has a guiding effect on convergent flow,thus affecting the diffusion performance of pollutants in street valleys.
In the planning and design of new energy generation systems,optimizing the configura-tion of energy storage capacity and power is the key to ensuring the safe and stable operation of the power system.In response to the current lack of rigorous mathematical foundations and com-plex calculation processes in energy storage planning,this paper proposes an energy storage capac-ity optimization configuration method based on system balance mechanism.This method was based on the statistical characteristics of new energy output,considering the efficiency loss during the charging and discharging process of energy storage systems.It improved the traditional power electricity balance model,derived the analytical expression of energy storage capacity,and con-structed the collaborative configuration relationship between new energy penetration rate,conven-tional power penetration rate,and energy storage capacity.The calculation example based on actu-al data from the Northwest Power Grid shows that applying this method can determine a penetra-tion rate of 200%for new energy and 80%for conventional power sources,requiring 70.4 GW×3.2h(approximately 2.25×108kW·h)of energy storage.Compared with traditional methods,conventional power generation capacity is reduced by about 31 GW while meeting the same sup-ply-demand balance conditions,and the simultaneous rate of renewable energy is increased by 28%.
Patients with complete lower limb immobility or those requiring periodic rehabilitation exercises due to muscle weakness typically use lower limb rehabilitation robots for passive reha-bilitation treatment.This paper addresses the issue of joint friction in a distributed variable-struc-ture rehabilitation robot during passive rehabilitation mode.A friction compensation trajectory tracking control method for the robot joints was designed.Firstly,based on the mechanical struc-ture of the distributed variable-structure lower limb rehabilitation robot,a mathematical model of the rehabilitation robot was established according to the armature circuit balance relationship and the electromechanical coupling relationship.Then,the LuGre model was adopted and modified to characterize joint friction.To counteract nonlinear effects induced by frictional forces,a particle swarm optimization(PSO)-based proportional-integral-derivative(PID)controller was designed,achieving compensation and suppression of nonlinear friction force and ensuring the control effect of the trajectory tracking controller.Finally,a simulation experiment platform was constructed and a prototype was developed to verify the effectiveness of the proposed control method.Experi-ments shown that for the expected signals of different joint angle motion trajectories,PID control-lers based on PSO algorithm can stably track the expected signals,with error values controlled within±1.87×10-4rad and fitness values iterated to 1.06,while conventional controllers exhibit significant fluctuations.At the same time,the prototype completed two passive rehabilitation modes of motion actions,verifying the control effect of the controller and the effectiveness of the control method.
In order to analyze the application performance of compound bacteria in agricultural produc-tion,the application effect of Bacillus subtilis SL-44 and Enterobacter hormaechei Rs-5 in the field was investigated by tomato field weight loss and effect enhancement experiment and tomato straw in-situ field return experiment.By analyzing soil physicochemical parameters,fruit quality and soil bacterial commu-nity structure,the application efficiency of compound bactericide combined with chemical fertilizer was investigated.The results showed that the biomass of tomato plants,the processing quality of tomato fruits,the nutritional quality of tomato fruits and the yield of tomato fruits all decreased with the reduc-tion of fertilizer dosage,but the contents of the corresponding treatment indexes increased after the addi-tion of complex bacterial agent,among which the effect of 30％reduction of fertilizer treatment was more obvious,and there was no difference between the treatment and no reduction of fertilizer applica-tion.Applying 30％less chemical fertilizer combined with compound bacteria can achieve the effect of re-ducing weight and increasing efficiency.In situ returning experiment,the content of soil physicochemical indexes significantly increased after 30 d of decomposition of tomato straw combined with compound bac-terial agent,and the diversity of soil bacteria was promoted.
In order to prepare superhydrophobic cotton fabrics with good self-healing properties, SA@PDA microspheres with core-shell structure were prepared by using stearic acid SA as core material and PDA as shell material.Then, the microspheres and PDMS were dip-coated on the surface of cotton fabric to prepare SA@PDA superhydrophobic cotton fabric.The SA@PDA coreshell microspheres and cotton fabrics were characterized by SEM, FT-IR and XPS.The photothermal conversion performance, self-healing performance and friction resistance of SA@PDA super hydrophobic cotton fabrics under simulated sunlight were studied, and the repair mechanism was discussed.The results show that the superhydrophobic cotton fabric coated with SA@PDA coreshell microspheres has good photothermal conversion performance, and the temperature rise is 40.9 ℃ after simulated sunlight irradiation.After losing superhydrophobicity, the cotton fabric can restore the superhydrophobic state after 30 min of light repair, and can be recycled for 6 times.The fabric also has good friction resistance, and loses superhydrophobicity after rubbing with sandpaper for 3 200 cm.The self-healing mechanism of SA@PDA superhydrophobic self-repairing cotton fabric is the rapid migration of stearic acid in SA@PDA core-shell microspheres under photothermal action.
In order to further improve the effectiveness of phosphorus bacteria agents,phosphate solubi-lizing bacteria(PSB)biochar-based microbial agents were prepared by adding different amounts of corn stover biochar(CSB)in PSB solution.The preparation conditions of the biochar-based microbial agents were analyzed using OD600 and effective viable bacterial count as indicators.Through pot experiments,the effect of biochar-based microbial agent on wheat growth performance and soil physicochemical properties were investigated.The results showed that when the addition amount of biochar was 0.16％,the OD600 of the prepared biochar-based microbial agent significantly increased,and the effective viable cell count reached 8.37 CFU/pL,which was 3.3 times higher than the CK1(without CSB)group.Biochar-based microbial agent T group(CSB+PSB)could effectively promote the growth of wheat after four weeks of application,the plant height,chlorophyll content,and root activity increased by(10.25±0.62)％,(67.69±4.21)％,and(49.58±3.73)％,respectively,compared to the CK1 group.At the same time,biochar-based microbial agents effectively improved soil properties,with soil available nitrogen,soil available phosphorus,soil catalase,and urease activities increasing by(31.81±2.25)％,(50.71±4.58)％,(30.89±1.43)％,and(44.26±3.84)％,respectively,compared to the CK1 group.The CK2(with CSB)group treated with biochar alone showed slightly higher indicators than the CK1 group.Adding a certain a-mount of biochar had a certain effect on improving wheat growth and soil properties,but the phosphorus solubilizing bacteria biochar-based microbial agent prepared with biochar as a carrier could more effective-ly improve soil fertility and enhance wheat growth promotion performance,providing a theoretical basis for further research and development of microbial agents.
In order to solve the problem of low control precision and poor anti-interference ability due to the input and output limitation,the unknown external interference and the uncertainty of its own dynamic parameters,an adaptive backstepping sliding mode control method based on the time-varying tangent barrier Lyapunov function was proposed.Firstly,the issue of input constraint was addressed by designing a saturation compensation system to enhance the stability of the control system.Secondly,external un-known disturbances and uncertainties in the dynamic parameters were treated as composite disturbances,and a feedback adaptive law was designed to accurately estimate them.Simultaneously,a time-varying tangent-type barrier Lyapunov function was employed to confine the position error and velocity error within time-varying bounds.Finally,the closed-loop control system was proven to be bounded stable through Lyapunov theory analysis.The simulation results show that the proposed control method reduces the tracking error of joint 1 and joint 2 by 58%and 33%,respectively,compared with the control method based on the time-varying log-obstacle Lyapunov function.Compared with the method without input con-straint,the proposed control method improves the response speed of joint 1 and joint 2 by 69%and 50%.
When mobile robots use monocular vision sensors for simultaneous localization and mapping(SLAM),they encounter numerous challenges in complex environments characterized by frequent lighting changes and sparse environmental textures,leading to inaccuracies in positio-ning.Therefore,this article focuses on improving the front-end and positioning components of the ORB-SLAM3 system to enhance the accuracy and robustness of monocular vision mobile robots.Firstly,we proposed a regional dynamic feature probability threshold adjustment algorithm to en-hance the SuperPoint network,replacing the original ORB algorithm for image feature extraction.This step was aimed to acquire more robust and evenly distributed visual feature points.Second-ly,we introduced a common view matching strategy and dynamic window matching strategy,opti-mizing the feature matching and tracking algorithm of the visual front-end.This optimization sig-nificantly improved visual tracking performance in scenes with sparse textures.Finally,by combi-ning the proposed improved algorithm with multi-sensor information fusion technology,a com-plete positioning system framework was constructed.An experiment was conducted using this system.The results demonstrate that the improved algorithm reduces the absolute trajectory er-ror on the EuRoc dataset by 8.6%compared to ORB-SLAM3.In a real-world environment,the error of the robot is reduced by 33.59%compared to that before the improvement.
Understanding and mastering the traveling wave propagation characteristics of high-voltage cables is a prerequisite for cable fault location,and existing research on traveling wave propagation characteristics mainly focuses on overhead lines,and its conclusions can not be di-rectly applied to cable lines.In order to accurately describe the propagation characteristics of trav-eling waves,a calculation method for the time-domain decoupling matrix of transient signals is proposed,and modulus parameters that can reflect the propagation characteristics of traveling waves are extracted.Firstly,by solving the phase mode transformation decoupling matrix of the cable line at different frequencies,the magnitude of the modulus parameters at each frequency point was calculated.Secondly,the propagation characteristics of cable traveling waves were ana-lyzed from the perspectives of frequency characteristics of modulus parameters and modulus transmission paths.Thirdly,the impact of using phase mode transformation at a fixed frequency were evaluated from two aspects:changes in modulus properties and calculation errors of modulus parameters.Finally,a frequency dependent parameter model for high-voltage power cables was established in PSCAD/EMTDC and conduct fault simulation.The analysis results of fault current traveling waves show that at the phase mode transformation frequencies of 100 k Hz and 200 k Hz,the waveform characteristics of each modulus conform to the propagation law of traveling waves,and the wave velocity error of the line mode component does not exceed 1.8%,and the wave ve-locity error of the ground mode component does not exceed 6%,the correctness of the analysis of traveling wave propagation characteristics is verified.By systematically explaining the propagation characteristics of traveling waves in high-voltage power cables,a theoretical basis is provided for achieving precise fault location in cable lines.
In order to reveal the summer thermal environment and users' thermal comfort characteristics of slide spaces in urban children's parks in Guangzhou, this study conducted physical environment measurement and subjective questionnaire survey on six groups of slide spaces in three children's parks, and conducted regression analysis and comparative analysis on thermal comfort indicators.Some major conclusions can be drawn:The spatial temperature and humidity levels of the slide in Guangzhou in summer are higher, and the maximum values are 40.4 ℃ and 77.4%, respectively.The solar radiation is notably intense, peaking at 981.7 W/m2 during the testing period.Simultaneously, it was recorded that within unshielded slide areas, the ambient black globe temperature can soar to 60.2 ℃, while the surface temperature of the slides may reach as high as 71.8 ℃, posing a significant risk for thermal burns.Although wind speeds are generally active, averaging above 0.5 m/s, some areas experience reduced airflow due to tree enclosure.Both children and their guardians predominantly perceive the thermal environment of all slide spaces as "hot" or "very hot", yet there exist variations in their evaluations regarding thermal comfort and acceptability.The neutral temperature of children and guardians was 23.3 ℃ and 26.8 ℃ respectively.The important factors affecting the thermal comfort of children's slide games in Guangzhou summer are solar radiation and wind speed.In view of the fact that children's thermal sensitivity is higher than that of guardians, the use and design of children's parks need to pay special attention to children's thermal comfort.
In response to the high energy and water consumption of data centers,hollow fiber membrane chillers were used to produce chilled water for the system in order to improve the air conditioning system performance and reduce water consumption.The response surface methodology(RSM)was used to de-sign the experimental program.Air temperature,relative humidity,air flow rate,inlet water temperature and water flow rate were selected as impact factors.And a cooling system experimental bench based on fork flow hollow fiber membrane cooler was built.The data were collated and analyzed to assess the po-tential impact of each impact factor on the response values,including outlet water temperature,cooling ef-ficiency,coefficient of performance(COP)and water consumption,and their magnitude.The results show that there is a significant positive correlation between inlet water temperature and outlet water tem-perature.And the cooling performance of the system is optimized when the inlet water temperature is 34 ℃.In addition,increased air flow helps to increase cooling efficiency and COP,and can effectively re-duce water consumption.While increasing the water flow rate can further increase COP,it can lead to an increase in outlet water temperature and an increase in water consumption.This study provides scientific basis and theoretical support for the optimal design of air conditioning cooling system in data centers.
