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.
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 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 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.
To address the issues of high computational cost and the inability to accurately capture multi-scale dynamic nonlinear processes in wind-sand particle flow simulation based on the dis-crete element method,a genetic algorithm-improved BP neural network method for predicting particle positions was proposed.A neural network data set was constructed by extracting the physical characteristics of the particle stacking simulation,and then a particle position prediction model based on the GA-BP neural network was proposed.The results show that the network takes 13.02 s and 25.79 s to predict the positions in the x and y directions,respectively,both of which are significantly lower than the DEM simulation time of 9 361 s.The network achieves RRMSEvalues of 0.003 2 and 0.004 3,and RMAPE values of 1.208 6%and 0.848 0%,outperfor-ming the original BP neural network.The differences between the predicted porosity and DEM simulated by GA-BP neural network are 4.47%,0.08 and 1.26%,the slope prediction difference is 1.53%,and the RMAE is 1.83%,which verifies the accuracy of the model.Therefore,the GA-BP prediction model reduces time cost and captures the nonlinear and multi-scale processes of dy-namic particle flow.
To address the common issues of structural deformation and misalignment in unsuper-vised image stitching,a dimension-aware images stitching network(DAISNet)based on dimen-sion aware attention was proposed.This network consists of two sub networks:homography esti-mation and reconstruction.The reconstruction sub network was further composed of two bran-ches:a low-resolution optimization branch and a high-resolution dual channel branch.We intro-duced the hollow space pyramid pooling module and dimension aware attention module to con-struct a low-resolution optimization branch,enhancing the perception ability of key areas such as structural features and stitching boundaries.Drawing on the idea of heterogeneous architecture,a high-resolution dual branch was constructed by adding lower-level subnetworks to extract more complementary structural information and improve local details in stitched images.The experi-mental results show that compared with advanced image stitching methods such as UDIS,the proposed DAISNet method effectively improves the structural deformation and misalignment phe-nomena in stitched images on the UDIS-D dataset,increases structural similarity by more than 0.63%,and improves peak signal-to-noise ratio by more than 0.30%.
To investigate the effect of nitrogen flow rate on the microstructure and corrosion re-sistance of CrFeCoNiCu high-entropy alloy films,(CrFeCoNiCu)Nx films were prepared using reactive direct current magnetron sputtering.The phase structure,microstructure,and corrosion resistance of the films were analyzed using X-ray diffraction(XRD),scanning electron microscopy(SEM),atomic force microscopy(AFM),energy dispersive spectroscopy(EDS),and electro-chemical experiments.The results show that the films prepared under different nitrogen flow rates exhibit dense structures,a simple FCC structure,and preferred orientation of(111).The hardness of the films increases with rising nitrogen flow rate,reaching 322.1 HV at a flow rate of 20 sccm.As the nitrogen flow rate increases,the corrosion resistance of the films first improves and then declines.At a nitrogen flow rate of 10 sccm,the self-corrosion potential is higher at-724 mV,and the self-corrosion current density is lower at 3.77 μA·cm-2,the smooth surface and fewer defects of the films effectively hinder corrosion reactions.
Aimed at the environmental pollution problems of toxic solvents(DMF/DMSO)and a-cidic modulators in the traditional synthesis system of Zr-MOFs,a green synthesis strategy based on choline-based deep eutectic solvent(DES)was developed in this study.The UiO-66-Ser carrier material was successfully constructed by introducing the biocompatible modulator molecule L-ser-ine in place of the conventional acidic medium,and the synergistic snailase and β-glucosidase were covalently crosslinked to the carrier,synthesizing the biocomposite Sna@UiO-66-Ser@β-G for the targeted catalytic conversion of ginsenoside Rb1 into the rare ginsenoside CK.Through the one-way experiments,the preparation conditions of UiO-66-Ser and Sna@UiO-66-Ser@β-G biocom-posites were optimized:L-Ser addition 1.5 g,reaction temperature 140℃,cross-linking time 4 h,snailase:40 mg,and β-glucosidase:150 μL.Optimization of the catalytic reaction conditions indica-ted that under the conversion time of 48 h,pH 4.0 and the optimal process conditions of enzyme-substrate ratio of 1∶2,the conversion of ginsenoside Rb1 into the rare ginsenoside CK was a-chieved,and the yield of the target product rare ginsenoside CK reached 87%.This study provides a novel catalytic system and process technology solution for the efficient conversion of natural product active ingredients.
This study adopts Charles Morris's triadic model of semiotics to conduct a systematic analysis of the traditional wave cliff patterns,exploring their derivation pathways and logic of vis-ual reassembling within the context of contemporary design.Structured around the three dimen-sions of semantics,syntactics,and pragmatics,the research investigates how this culturally em-bedded motif can be reinterpreted and revitalized in modern design practices.At the semantic lev-el,the study deciphers the symbolic meanings of elements,aiming to expand their expressive po-tential within a contemporary visual language.At the syntactics level,it applies the derivation and reasoning method along with random reassembling techniques to examine the motif's formal evo-lution and aesthetic transformation in terms of morphology,color,and compositional structure.At the pragmatic level,the focus is placed on the interactive relationship between traditional symbols and contemporary users,proposing a"user-oriented"path of innovation.The findings reveal that through compositional strategies such as horizontal and vertical displacement,mirroring,and deri-vation,wave cliff patterns achieve enhanced spatial layering and visual dynamism,increasing their adaptability to contemporary fashion design and commercial viability.The incorporation of the Munsell color system enables a modern reconstruction of traditional chromatics,enhancing their expressive value across diverse aesthetic systems.In practical application,the reconstructed pat-terns is effectively integrated into garment silhouettes and detail design,achieving an organic translation from traditional imagery to a contemporary design language.More importantly,the study,through a semiotic lens,identifies the patterns latent potential in fostering cultural-emo-tional resonance,interactive user engagement,and digital dissemination.This process establishes a sustainable design logic and communication mechanism for its continued development.According-ly,this research provides a sustainable design strategy and semiotic foundation for the contempo-rary transformation and symbolic transmission of traditional patterns.
