The modified Poisson-Boltzmann(MPB)equations are often used to describe the equilibrium particle distribution of ionic systems.In this paper,we propose a fast algorithm to solve the MPB equations with the self Green’...The modified Poisson-Boltzmann(MPB)equations are often used to describe the equilibrium particle distribution of ionic systems.In this paper,we propose a fast algorithm to solve the MPB equations with the self Green’s function as the self-energy in three dimensions,where the solution of the self Green’s function poses a computational bottleneck due to the requirement of solving a high-dimensional partial differential equation.Our algorithm combines the selected inversion with hierarchical interpolative factorization for the self Green’s function,building upon our previous result of two dimensions.This approach yields an algorithm with a complexity of O(N log N)by strategically leveraging the locality and low-rank characteristics of the corresponding operators.Additionally,the theoretical O(N)complexity is obtained by applying cubic edge skeletonization at each level for thorough dimensionality reduction.Extensive numerical results are conducted to demonstrate the accuracy and efficiency of the proposed algorithm for problems in three dimensions.展开更多
Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design o...Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.展开更多
In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accurac...In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.展开更多
Given the swift proliferation of structural health monitoring(SHM)technology within tunnel engineering,there is a demand on proficiently and precisely imputing the missing monitoring data to uphold the precision of di...Given the swift proliferation of structural health monitoring(SHM)technology within tunnel engineering,there is a demand on proficiently and precisely imputing the missing monitoring data to uphold the precision of disaster prediction.In contrast to other SHM datasets,the monitoring data specific to tunnel engineering exhibits pronounced spatiotemporal correlations.Nevertheless,most methodologies fail to adequately combine these types of correlations.Hence,the objective of this study is to develop spatiotemporal recurrent neural network(ST-RNN)model,which exploits spatiotemporal information to effectively impute missing data within tunnel monitoring systems.ST-RNN consists of two moduli:a temporal module employing recurrent neural network(RNN)to capture temporal dependencies,and a spatial module employing multilayer perceptron(MLP)to capture spatial correlations.To confirm the efficacy of the model,several commonly utilized methods are chosen as baselines for conducting comparative analyses.Furthermore,parametric validity experiments are conducted to illustrate the efficacy of the parameter selection process.The experimentation is conducted using original raw datasets wherein various degrees of continuous missing data are deliberately introduced.The experimental findings indicate that the ST-RNN model,incorporating both spatiotemporal modules,exhibits superior interpolation performance compared to other baseline methods across varying degrees of missing data.This affirms the reliability of the proposed model.展开更多
This work’s aim is to participate in local materials (raw or fiber improved), which can be used in sustainable and accessible buildings to every Senegalese. To do this, studied materials are respectively collected fr...This work’s aim is to participate in local materials (raw or fiber improved), which can be used in sustainable and accessible buildings to every Senegalese. To do this, studied materials are respectively collected from a laterite clay pit in Ndouloumadjie Dembe (Matam, Northern Senegal) and another from a termite mound in Tattaguine (Fatick, Central Senegal). These samples are first subjected to Geotechnical identification tests. Mud bricks are then made with raw or sifted millet involucre improved to 1%, 2%, and 3% at 5 mm sieve samples. These briquettes are subjected to compression tests and thermal evaluations. Lagrange and Newton methods of numeric modelling are used to test the whole mixture points between 1% and 3% millet involucre for a better correlation between mechanical and thermal parameters. The results show that in Matam, as well as in Tattaguine, these muds, raw or improved, are of good thermomechanical quality when they are used in bricks making. And the thermomechanical coupling quality reaches a maximum situated at 2.125% for Ndouloumadjie and 2.05% for Tattaguine. These briquettes’ building quality depends on the mud content used in iron, aluminum, silica and clay. Thus, same natural materials can be used in the establishment of habitats according to their geotechnical, chemical, mechanical and thermal characteristics.展开更多
Indian Railways have been the largest people moving transport infrastructure in India.Over the years the systems and trains have been upgraded resulting in both better passenger amenities and reduction in travel time....Indian Railways have been the largest people moving transport infrastructure in India.Over the years the systems and trains have been upgraded resulting in both better passenger amenities and reduction in travel time.The newest addition is the Vande Bharat Express,a semi-high-speed train that was introduced in India in 2019.The train currently runs between 10 routes and has brought significant changes to India’s railway network.This article explores the introduction of Vande Bharat Express trains in India and its effects on the country’s interstation time-space shrinkage using cartographic techniques.The cartographic techniques like stepwise multidimensional scaling and interpolation using the distance cartogram plugin in QGIS are mainly used for generating the time-space maps for various speeds.The limitations of these techniques and the methods to overcome those limitations are also explored in this article.展开更多
With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multi...With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction.Audio,as a vital medium in communication,entertainment,and information sharing,demands the same level of security as images.However,embedding data in encrypted audio poses unique challenges due to the trade-offs between security,data integrity,and embedding capacity.This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity.By increasing sample density through interpolation,embedding opportunities are significantly enhanced while maintaining encryption throughout the process.The method further integrates multiple most significant bit(multi-MSB)prediction and Huffman coding to optimize compression and embedding efficiency.Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity,while preserving full reversibility.These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio.This work advances reversible data hiding in encrypted audio by offering a secure,efficient,and fully reversible data hiding framework.展开更多
Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribut...Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribution along railway routes,thereby achieving graded post-earthquake response measures.Design/methodology/approach–The seismic intensity monitoring system for railways adopts a two-level architecture,namely the seismic intensity monitoring equipment and the seismic intensity rapid reporting information center processing platform.The platform obtains measured instrumental intensity through the seismic intensity monitoring equipment deployed along railways and combines it with the National Seismic Network Earthquake Catalog to generate real-time railway seismic intensity distribution maps using the Kriging interpolation algorithm.A calculation method for railway seismic impact intervals is designed to calculate the mileage intervals where the intensity area corresponding to each contour line in the seismic intensity distribution map intersects with the railway line.Findings–The system was deployed for practical earthquake monitoring demonstration applications on the Nanjiang Railway Line in Xinjiang.During the operational period,the seismic intensity monitoring equipment calculated and uploaded instrumental intensity values to the seismic intensity rapid reporting information center processing platform a total of nine times.Among these,earthquakes triggering the Kriging interpolation algorithm occurred twice.The system operated stably throughout the application period and successfully visualized relevant seismic impact data,such as earthquake intensity distribution maps and affected railway mileage sections.These results validate the system’s practicality and effectiveness.Originality/value–The seismic intensity monitoring for the railway system designed in this study can integrate the measured instrumental intensity data along railways and the earthquake catalog of the National Seismic Network.It uses the Kriging interpolation method to calculate the intensity distribution and determine the seismic impact scope,thereby addressing the issue that the seismic intensity distribution calculated by traditional attenuation formulas deviates from reality.The system can provide clear graded interval recommendations for post-earthquake disposal,effectively improve the efficiency of post-earthquake recovery and inspection and offer a decision-making basis for restoring railway operations quickly.展开更多
Gear flank modification is essential to reduce the noise generated in the gear meshing process,improve the gear transmission performance,and reduce the meshing impact.Aiming at the problem of solving the additional mo...Gear flank modification is essential to reduce the noise generated in the gear meshing process,improve the gear transmission performance,and reduce the meshing impact.Aiming at the problem of solving the additional motions of each axis in the higher-order topology modification technique and how to accurately add the different movements expressed in the form of higher-order polynomials to the corresponding motion axes of the machine tool,a flexible higher-order gear topology modification technique based on an electronic gearbox is proposed.Firstly,a two-parameter topology gear surface equation and a grinding model of wheel grinding gears are established,and the axial feed and tangential feed are expressed in a fifth-order polynomial formula.Secondly,the polynomial coefficients are solved according to the characteristics of the point contact when grinding gears.Finally,an improved electronic gearbox model is constructed by combining the polynomial interpolation function to achieve gear topology modification.The validity and feasibility of the modification method based on the electronic gearbox are verified by experimental examples,which is of great significance for the machining of modification gears based on the continuous generative grinding method of the worm grinding wheel.展开更多
Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduce...Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduced and then enlarged through interpolation,followed by the embedding of secret data into the newly generated pixels.A general improving approach for embedding secret messages is proposed.The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods.This enhancement is achieved by expanding the range of pixel values available for embedding secret messages,removing the limitations of many existing methods,where the range is restricted to powers of two to facilitate the direct embedding of bit-based messages.This improvement is accomplished through the application of multiple-based number conversion to the secret message data.The method converts the message bits into a multiple-based number and uses an algorithm to embed each digit of this number into an individual pixel,thereby enhancing the message embedding efficiency,as proved by a theorem derived in this study.The proposed improvement method has been tested through experiments on three well-known image interpolation-based data hiding methods.The results show that the proposed method can enhance the three data embedding rates by approximately 14%,13%,and 10%,respectively,create stego-images with good quality,and resist RS steganalysis attacks.These experimental results indicate that the use of the multiple-based number conversion technique to improve the three interpolation-based methods for embedding secret messages increases the number of message bits embedded in the images.For many image interpolation-based data hiding methods,which use power-of-two pixel-value ranges for message embedding,other than the three tested ones,the proposed improvement method is also expected to be effective for enhancing their data embedding capabilities.展开更多
With the rapid development of the nuclear power industry on a global scale,the discharge of radioactive e uents from nuclear power plants and their impact on the environment have become important issues in radioactive...With the rapid development of the nuclear power industry on a global scale,the discharge of radioactive e uents from nuclear power plants and their impact on the environment have become important issues in radioactive waste management,radiation protection,and environmental impact assessments.-detection of nuclides requires tedious processes,such as waiting for the radioactive balance of the sample and pretreatment separation,and there is an urgent need for a method specifically designed for mixing rapid energy spectrum measurement method for nuclide samples.The analysis of hybrid-energy spectrum is proposed in this study as a new algorithm,which takes advantage of the spectral analysis of-logarithmic energy spectrum and fitting ability of Fourier series.The logarithmic energy spectrum is obtained by logarithmic conversion of the hybrid linear energy spectrum.The Fourier fitting interpolation method is used to fit the logarithmic energy spectrum numerically.Next,the interpolation points for the‘e ective high-energy window’and‘e ective low-energy window’corresponding to the highest E_(m)nuclide in the hybrid logarithmic fitted energy spectrum are set,and spline interpolation is performed three times to obtain the logarithmic fitted energy spectrum of the highest E_(m)nuclide.Finally,the logarithmic fitted spectrum of the highest E_(m)nuclide is subtracted from the hybrid logarithmic fitted spectrum to obtain a logarithmic fitted spectrum comprised of the remaining lower E_(m)nuclides.The aforementioned process is iterated in a loop to resolve the logarithmic spectra of each nuclide in the original hybrid logarithmic spectra.Then,the radioactivity of E_(m)nuclides to be measured is calculated.In the experimental tests,^(14)C,^(90)Sr,and ^(90)Y spectra,which are obtained using the Fourier fitting interpolation method are compared with the original simulated ^(14)C,^(90)Sr,and ^(90)Y spectra of GEANT4.The measured liquid scintillator data of ^(90)Sr∕^(90)Y sample source and simulated data from GEANT4 are then analyzed.Analysis of the experimental results indicates that the Fourier fitting interpolation method accurately solves ^(14)C,^(90)Sr,and ^(90)Y energy spectra,which is in good agreement with the original GEANT4 simulation.The error in ^(90)Y activity,calculated using the actual detection e ciency,is less than 10%and less than 5%when using the simulated full-spectrum detection e ciency,satisfying the experimental expectations.展开更多
Blended acquisition offers efficiency improvements over conventional seismic data acquisition, at the cost of introducing blending noise effects. Besides, seismic data often suffers from irregularly missing shots caus...Blended acquisition offers efficiency improvements over conventional seismic data acquisition, at the cost of introducing blending noise effects. Besides, seismic data often suffers from irregularly missing shots caused by artificial or natural effects during blended acquisition. Therefore, blending noise attenuation and missing shots reconstruction are essential for providing high-quality seismic data for further seismic processing and interpretation. The iterative shrinkage thresholding algorithm can help obtain deblended data based on sparsity assumptions of complete unblended data, and it characterizes seismic data linearly. Supervised learning algorithms can effectively capture the nonlinear relationship between incomplete pseudo-deblended data and complete unblended data. However, the dependence on complete unblended labels limits their practicality in field applications. Consequently, a self-supervised algorithm is presented for simultaneous deblending and interpolation of incomplete blended data, which minimizes the difference between simulated and observed incomplete pseudo-deblended data. The used blind-trace U-Net (BTU-Net) prevents identity mapping during complete unblended data estimation. Furthermore, a multistep process with blending noise simulation-subtraction and missing traces reconstruction-insertion is used in each step to improve the deblending and interpolation performance. Experiments with synthetic and field incomplete blended data demonstrate the effectiveness of the multistep self-supervised BTU-Net algorithm.展开更多
In this paper,a meshfree Jacobi point interpolation(MJPI)approach for the dynamic analysis of sandwich laminated conical and cylindrical shells with varying thickness is presented.The theoretical formulations for sand...In this paper,a meshfree Jacobi point interpolation(MJPI)approach for the dynamic analysis of sandwich laminated conical and cylindrical shells with varying thickness is presented.The theoretical formulations for sandwich laminated shells with varying thickness are established using the modified variational principle within the framework of first-order shear deformation theory(FSDT).The displacement components of the sandwich shell are expanded using the MJPI shape function and Fourier series in the meridional and circumferential directions,respectively.The accuracy and reliability of the proposed MJPI shape function are validated against numerical results from published literature and the commercial simulation tool Abaqus.Finally,the effects of different parameters such as thickness gradient,thickness power index and boundary condition on the free vibration and dynamic response of the sandwich laminated shell are investigated.展开更多
This paper focuses on applying the barycentric Lagrange interpolation collocation method(BLICM)for solving 2D time-fractional diffusion-wave equation(TFDWE).In order to obtain the discrete format of the equation,we co...This paper focuses on applying the barycentric Lagrange interpolation collocation method(BLICM)for solving 2D time-fractional diffusion-wave equation(TFDWE).In order to obtain the discrete format of the equation,we construct the multivariate barycentric Lagrange interpolation approximation function and process the integral terms by using the Gauss-Legendre quadrature formula.We provide a detailed error analysis of the discrete format on the second kind of Chebyshev nodes.The efficacy of the proposed method is substantiated by some numerical experiments.The results of these experiments demonstrate that our method can obtain high-precision numerical solutions for fractional partial differential equations.Additionally,the method's capability to achieve high precision with a reduced number of nodes is confirmed.展开更多
Ocean remote sensing satellites provide observations with high spatiotemporal resolution.However,the influence of clouds,fog,and haze frequently leads to significant data gaps.Accurate and effective estimation of thes...Ocean remote sensing satellites provide observations with high spatiotemporal resolution.However,the influence of clouds,fog,and haze frequently leads to significant data gaps.Accurate and effective estimation of these missing data is highly valuable for engineering and scientific research.In this study,the radial basis function(RBF)method is used to estimate the spatial distribution of total suspended matter(TSM)concentration in Hangzhou Bay using remote sensing data with severe data gaps.The estimation precision is validated by comparing the results with those of other commonly used interpolation methods,such as the Kriging method and the basic spline(B-spline)method.In addition,the applicability of the RBF method is explored.Results show that the estimation of the RBF method is significantly close to the observation in Hangzhou Bay.The average of the mean absolute error,mean relative error,and root mean square error in all the experiments is evidently smaller than those of the Kriging and B-spline interpolations,indicating that the proposed method is more appropriate for estimating the spatial distribution of the TSM in Hangzhou Bay.Finally,the TSM distribution in the blank observational area is predicted.This study can provide some reference values for handling watercolor remote sensing data.展开更多
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.展开更多
To conduct a comprehensive analysis of the current status of water environment quality in Yilong Lake,a systematic study was undertaken to characterize the evolution of water quality.This study utilized monthly data o...To conduct a comprehensive analysis of the current status of water environment quality in Yilong Lake,a systematic study was undertaken to characterize the evolution of water quality.This study utilized monthly data on water quality indicators collected from three monitoring sections of Yilong Lake between 2016 and 2023,employing the Mann-Kendall trend test and ArcGIS spatial interpolation technique.The results indicated that the five-day biochemical oxygen demand(BOD5),total nitrogen(TN),and chlorophyll a(Chla)exhibited an overall increasing trend,whereas other indicators demonstrated a decreasing trend.The permanganate index(PI),chemical oxygen demand(COD),TN,and Chla were observed in the following order:east of the lake>middle of the lake>west of the lake.In contrast,the BOD5 and total phosphorus(TP)were ranked as west of the lake>east of the lake>middle of the lake.Additionally,ammonia nitrogen(NH3-N)was found to be in the order of east of the lake>west of the lake>middle of the lake,while transparency was ranked as west of the lake>middle of the lake>east of the lake.Urban domestic sewage,effluent from industrial parks,domestic waste generated by rural residents’production and daily activities,agricultural waste,wastewater from decentralized farming,domestic sewage,and point source discharges from the soybean processing industry are the primary contributors to the exceedance of water quality standards.The enhancement of a precise pollution control system,along with the regulation of pollution sources and the interception of pollutants,can significantly diminish the pollution load entering the lake.This approach is essential for the protection and restoration of river and lake ecosystems,thereby facilitating the gradual recovery of their ecological functions.Additionally,the implementation of ecological water replenishment and the recycling of water resources can improve the capacity of the water environment.Furthermore,bolstering scientific and technological support,as well as comprehensive supervision and assurance measures,is crucial to ensuring that water quality remains stable and adheres to established standards.展开更多
We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresp...We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresponding extended ab initio data set,we construct interpolation formulas covering the range from low-density,high-temperature to high-density,low-temperature plasmas.Our conductivity model repro-duces the well-known limits of the Spitzer and Ziman theory.We compare with available experimental data andfind very good agreement.The new conductivity model can be applied,for example,in dynamo simulations for magneticfield generation in gas giant planets,brown dwarfs,and stellar envelopes.展开更多
Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility o...Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility of EMS has received considerable attention in health and transport geography studies.^([3])One of the optimal gauges for evaluating the accessibility of EMS is the response time,which is defined as the time from receiving an emergency call to the arrival of an ambulance.^([4])Beijing has already reduced the response time to approximately12 min,and the next goal is to ensure that the response time across Beijing does not exceed 12 min (the information comes from the Beijing Emergency Medical Center).展开更多
Although the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)model has been widely applied in water quality assessment by numerous studies,several common limitations remain unresolved.Specificall...Although the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)model has been widely applied in water quality assessment by numerous studies,several common limitations remain unresolved.Specifically:1)Subjective elements in methods such as fuzzy theory and the analytic hierarchy process(AHP)may distort evaluation outcomes;2)The utilization of raw sample data is in‐sufficient when constructing evaluation matrices;3)The traditional entropy weight method in TOPSIS merely reflects statistical character‐istics of the final matrix while neglecting richer information embedded in raw datasets.To address these issues,we proximate probability distribution function of various indicators by using cubic spline interpolation and fully exploit information in the existing massive sample data.In this paper,the entropy weight method is enhanced based on the concept mentioned above and integrated with TOPSIS model to construct a novel evaluation model.Furthermore,the experimental analysis using wastewater monitoring data from Guizhou Province,China,verifies its practicality,and its results provide valuable references for local water environmental management.展开更多
基金support from the National Natural Science Foundation of China(Grant Nos.12071288 and 12325113)the Science and Technology Commission of Shanghai Municipality of China(Grant No.21JC1403700)+1 种基金Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA25010403)support of the US National Science Foundation under awards DMS-2244988 and DMS-2206333.
文摘The modified Poisson-Boltzmann(MPB)equations are often used to describe the equilibrium particle distribution of ionic systems.In this paper,we propose a fast algorithm to solve the MPB equations with the self Green’s function as the self-energy in three dimensions,where the solution of the self Green’s function poses a computational bottleneck due to the requirement of solving a high-dimensional partial differential equation.Our algorithm combines the selected inversion with hierarchical interpolative factorization for the self Green’s function,building upon our previous result of two dimensions.This approach yields an algorithm with a complexity of O(N log N)by strategically leveraging the locality and low-rank characteristics of the corresponding operators.Additionally,the theoretical O(N)complexity is obtained by applying cubic edge skeletonization at each level for thorough dimensionality reduction.Extensive numerical results are conducted to demonstrate the accuracy and efficiency of the proposed algorithm for problems in three dimensions.
基金supports for this research were provided by the National Natural Science Foundation of China(No.12272301,12002278,U1906233)the Guangdong Basic and Applied Basic Research Foundation,China(Nos.2023A1515011970,2024A1515010256)+1 种基金the Dalian City Supports Innovation and Entrepreneurship Projects for High-Level Talents,China(2021RD16)the Key R&D Project of CSCEC,China(No.CSCEC-2020-Z-4).
文摘Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.
基金supported by the National Natural Science Foundation of China(62272049,62236006,62172045)the Key Projects of Beijing Union University(ZKZD202301).
文摘In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.51991395 and 42293355)geological survey project of China Geological Survey:Support for Geo-hazard monitoring,early warning and prevention(Grant No.DD20230085).
文摘Given the swift proliferation of structural health monitoring(SHM)technology within tunnel engineering,there is a demand on proficiently and precisely imputing the missing monitoring data to uphold the precision of disaster prediction.In contrast to other SHM datasets,the monitoring data specific to tunnel engineering exhibits pronounced spatiotemporal correlations.Nevertheless,most methodologies fail to adequately combine these types of correlations.Hence,the objective of this study is to develop spatiotemporal recurrent neural network(ST-RNN)model,which exploits spatiotemporal information to effectively impute missing data within tunnel monitoring systems.ST-RNN consists of two moduli:a temporal module employing recurrent neural network(RNN)to capture temporal dependencies,and a spatial module employing multilayer perceptron(MLP)to capture spatial correlations.To confirm the efficacy of the model,several commonly utilized methods are chosen as baselines for conducting comparative analyses.Furthermore,parametric validity experiments are conducted to illustrate the efficacy of the parameter selection process.The experimentation is conducted using original raw datasets wherein various degrees of continuous missing data are deliberately introduced.The experimental findings indicate that the ST-RNN model,incorporating both spatiotemporal modules,exhibits superior interpolation performance compared to other baseline methods across varying degrees of missing data.This affirms the reliability of the proposed model.
文摘This work’s aim is to participate in local materials (raw or fiber improved), which can be used in sustainable and accessible buildings to every Senegalese. To do this, studied materials are respectively collected from a laterite clay pit in Ndouloumadjie Dembe (Matam, Northern Senegal) and another from a termite mound in Tattaguine (Fatick, Central Senegal). These samples are first subjected to Geotechnical identification tests. Mud bricks are then made with raw or sifted millet involucre improved to 1%, 2%, and 3% at 5 mm sieve samples. These briquettes are subjected to compression tests and thermal evaluations. Lagrange and Newton methods of numeric modelling are used to test the whole mixture points between 1% and 3% millet involucre for a better correlation between mechanical and thermal parameters. The results show that in Matam, as well as in Tattaguine, these muds, raw or improved, are of good thermomechanical quality when they are used in bricks making. And the thermomechanical coupling quality reaches a maximum situated at 2.125% for Ndouloumadjie and 2.05% for Tattaguine. These briquettes’ building quality depends on the mud content used in iron, aluminum, silica and clay. Thus, same natural materials can be used in the establishment of habitats according to their geotechnical, chemical, mechanical and thermal characteristics.
文摘Indian Railways have been the largest people moving transport infrastructure in India.Over the years the systems and trains have been upgraded resulting in both better passenger amenities and reduction in travel time.The newest addition is the Vande Bharat Express,a semi-high-speed train that was introduced in India in 2019.The train currently runs between 10 routes and has brought significant changes to India’s railway network.This article explores the introduction of Vande Bharat Express trains in India and its effects on the country’s interstation time-space shrinkage using cartographic techniques.The cartographic techniques like stepwise multidimensional scaling and interpolation using the distance cartogram plugin in QGIS are mainly used for generating the time-space maps for various speeds.The limitations of these techniques and the methods to overcome those limitations are also explored in this article.
基金funded by theNational Science and Technology Council of Taiwan under the grant number NSTC 113-2221-E-035-058.
文摘With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction.Audio,as a vital medium in communication,entertainment,and information sharing,demands the same level of security as images.However,embedding data in encrypted audio poses unique challenges due to the trade-offs between security,data integrity,and embedding capacity.This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity.By increasing sample density through interpolation,embedding opportunities are significantly enhanced while maintaining encryption throughout the process.The method further integrates multiple most significant bit(multi-MSB)prediction and Huffman coding to optimize compression and embedding efficiency.Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity,while preserving full reversibility.These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio.This work advances reversible data hiding in encrypted audio by offering a secure,efficient,and fully reversible data hiding framework.
基金funded by the Research and Development Fund Project of China Academy of Railway Science Group Co.,Ltd.,(No:2023YJ259)the Science and Technology Research and Development Program Project of China State Railway Group Co.,Ltd.(No:J2024G008).
文摘Purpose–This research aims to monitor seismic intensity along railway lines,study methods for calculating the extent of earthquake impact on railways and address practical challenges in estimating intensity distribution along railway routes,thereby achieving graded post-earthquake response measures.Design/methodology/approach–The seismic intensity monitoring system for railways adopts a two-level architecture,namely the seismic intensity monitoring equipment and the seismic intensity rapid reporting information center processing platform.The platform obtains measured instrumental intensity through the seismic intensity monitoring equipment deployed along railways and combines it with the National Seismic Network Earthquake Catalog to generate real-time railway seismic intensity distribution maps using the Kriging interpolation algorithm.A calculation method for railway seismic impact intervals is designed to calculate the mileage intervals where the intensity area corresponding to each contour line in the seismic intensity distribution map intersects with the railway line.Findings–The system was deployed for practical earthquake monitoring demonstration applications on the Nanjiang Railway Line in Xinjiang.During the operational period,the seismic intensity monitoring equipment calculated and uploaded instrumental intensity values to the seismic intensity rapid reporting information center processing platform a total of nine times.Among these,earthquakes triggering the Kriging interpolation algorithm occurred twice.The system operated stably throughout the application period and successfully visualized relevant seismic impact data,such as earthquake intensity distribution maps and affected railway mileage sections.These results validate the system’s practicality and effectiveness.Originality/value–The seismic intensity monitoring for the railway system designed in this study can integrate the measured instrumental intensity data along railways and the earthquake catalog of the National Seismic Network.It uses the Kriging interpolation method to calculate the intensity distribution and determine the seismic impact scope,thereby addressing the issue that the seismic intensity distribution calculated by traditional attenuation formulas deviates from reality.The system can provide clear graded interval recommendations for post-earthquake disposal,effectively improve the efficiency of post-earthquake recovery and inspection and offer a decision-making basis for restoring railway operations quickly.
基金Projects(52275483,52075142,U22B2084)supported by the National Natural Science Foundation of ChinaProject(JZ2023HGPA0292)supported by the Fundamental Research Funds for the Central Universities of China。
文摘Gear flank modification is essential to reduce the noise generated in the gear meshing process,improve the gear transmission performance,and reduce the meshing impact.Aiming at the problem of solving the additional motions of each axis in the higher-order topology modification technique and how to accurately add the different movements expressed in the form of higher-order polynomials to the corresponding motion axes of the machine tool,a flexible higher-order gear topology modification technique based on an electronic gearbox is proposed.Firstly,a two-parameter topology gear surface equation and a grinding model of wheel grinding gears are established,and the axial feed and tangential feed are expressed in a fifth-order polynomial formula.Secondly,the polynomial coefficients are solved according to the characteristics of the point contact when grinding gears.Finally,an improved electronic gearbox model is constructed by combining the polynomial interpolation function to achieve gear topology modification.The validity and feasibility of the modification method based on the electronic gearbox are verified by experimental examples,which is of great significance for the machining of modification gears based on the continuous generative grinding method of the worm grinding wheel.
文摘Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduced and then enlarged through interpolation,followed by the embedding of secret data into the newly generated pixels.A general improving approach for embedding secret messages is proposed.The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods.This enhancement is achieved by expanding the range of pixel values available for embedding secret messages,removing the limitations of many existing methods,where the range is restricted to powers of two to facilitate the direct embedding of bit-based messages.This improvement is accomplished through the application of multiple-based number conversion to the secret message data.The method converts the message bits into a multiple-based number and uses an algorithm to embed each digit of this number into an individual pixel,thereby enhancing the message embedding efficiency,as proved by a theorem derived in this study.The proposed improvement method has been tested through experiments on three well-known image interpolation-based data hiding methods.The results show that the proposed method can enhance the three data embedding rates by approximately 14%,13%,and 10%,respectively,create stego-images with good quality,and resist RS steganalysis attacks.These experimental results indicate that the use of the multiple-based number conversion technique to improve the three interpolation-based methods for embedding secret messages increases the number of message bits embedded in the images.For many image interpolation-based data hiding methods,which use power-of-two pixel-value ranges for message embedding,other than the three tested ones,the proposed improvement method is also expected to be effective for enhancing their data embedding capabilities.
基金supported by the National Natural Science Foundation of China(No.12005026)。
文摘With the rapid development of the nuclear power industry on a global scale,the discharge of radioactive e uents from nuclear power plants and their impact on the environment have become important issues in radioactive waste management,radiation protection,and environmental impact assessments.-detection of nuclides requires tedious processes,such as waiting for the radioactive balance of the sample and pretreatment separation,and there is an urgent need for a method specifically designed for mixing rapid energy spectrum measurement method for nuclide samples.The analysis of hybrid-energy spectrum is proposed in this study as a new algorithm,which takes advantage of the spectral analysis of-logarithmic energy spectrum and fitting ability of Fourier series.The logarithmic energy spectrum is obtained by logarithmic conversion of the hybrid linear energy spectrum.The Fourier fitting interpolation method is used to fit the logarithmic energy spectrum numerically.Next,the interpolation points for the‘e ective high-energy window’and‘e ective low-energy window’corresponding to the highest E_(m)nuclide in the hybrid logarithmic fitted energy spectrum are set,and spline interpolation is performed three times to obtain the logarithmic fitted energy spectrum of the highest E_(m)nuclide.Finally,the logarithmic fitted spectrum of the highest E_(m)nuclide is subtracted from the hybrid logarithmic fitted spectrum to obtain a logarithmic fitted spectrum comprised of the remaining lower E_(m)nuclides.The aforementioned process is iterated in a loop to resolve the logarithmic spectra of each nuclide in the original hybrid logarithmic spectra.Then,the radioactivity of E_(m)nuclides to be measured is calculated.In the experimental tests,^(14)C,^(90)Sr,and ^(90)Y spectra,which are obtained using the Fourier fitting interpolation method are compared with the original simulated ^(14)C,^(90)Sr,and ^(90)Y spectra of GEANT4.The measured liquid scintillator data of ^(90)Sr∕^(90)Y sample source and simulated data from GEANT4 are then analyzed.Analysis of the experimental results indicates that the Fourier fitting interpolation method accurately solves ^(14)C,^(90)Sr,and ^(90)Y energy spectra,which is in good agreement with the original GEANT4 simulation.The error in ^(90)Y activity,calculated using the actual detection e ciency,is less than 10%and less than 5%when using the simulated full-spectrum detection e ciency,satisfying the experimental expectations.
基金supported by the National Natural Science Foundation of China(42374134,42304125,U20B6005)the Science and Technology Commission of Shanghai Municipality(23JC1400502)the Fundamental Research Funds for the Central Universities.
文摘Blended acquisition offers efficiency improvements over conventional seismic data acquisition, at the cost of introducing blending noise effects. Besides, seismic data often suffers from irregularly missing shots caused by artificial or natural effects during blended acquisition. Therefore, blending noise attenuation and missing shots reconstruction are essential for providing high-quality seismic data for further seismic processing and interpretation. The iterative shrinkage thresholding algorithm can help obtain deblended data based on sparsity assumptions of complete unblended data, and it characterizes seismic data linearly. Supervised learning algorithms can effectively capture the nonlinear relationship between incomplete pseudo-deblended data and complete unblended data. However, the dependence on complete unblended labels limits their practicality in field applications. Consequently, a self-supervised algorithm is presented for simultaneous deblending and interpolation of incomplete blended data, which minimizes the difference between simulated and observed incomplete pseudo-deblended data. The used blind-trace U-Net (BTU-Net) prevents identity mapping during complete unblended data estimation. Furthermore, a multistep process with blending noise simulation-subtraction and missing traces reconstruction-insertion is used in each step to improve the deblending and interpolation performance. Experiments with synthetic and field incomplete blended data demonstrate the effectiveness of the multistep self-supervised BTU-Net algorithm.
文摘In this paper,a meshfree Jacobi point interpolation(MJPI)approach for the dynamic analysis of sandwich laminated conical and cylindrical shells with varying thickness is presented.The theoretical formulations for sandwich laminated shells with varying thickness are established using the modified variational principle within the framework of first-order shear deformation theory(FSDT).The displacement components of the sandwich shell are expanded using the MJPI shape function and Fourier series in the meridional and circumferential directions,respectively.The accuracy and reliability of the proposed MJPI shape function are validated against numerical results from published literature and the commercial simulation tool Abaqus.Finally,the effects of different parameters such as thickness gradient,thickness power index and boundary condition on the free vibration and dynamic response of the sandwich laminated shell are investigated.
基金Supported by the Scientific Research Foundation for Talents Introduced of Guizhou University of Finance and Economics(Grant No.2023YJ16)the Institute of Complexity Science,Henan University of Technology(Grant No.CSKFJJ-2025-33)the International Science and Technology Cooperation Project of Henan Province(Grant No.252102520007).
文摘This paper focuses on applying the barycentric Lagrange interpolation collocation method(BLICM)for solving 2D time-fractional diffusion-wave equation(TFDWE).In order to obtain the discrete format of the equation,we construct the multivariate barycentric Lagrange interpolation approximation function and process the integral terms by using the Gauss-Legendre quadrature formula.We provide a detailed error analysis of the discrete format on the second kind of Chebyshev nodes.The efficacy of the proposed method is substantiated by some numerical experiments.The results of these experiments demonstrate that our method can obtain high-precision numerical solutions for fractional partial differential equations.Additionally,the method's capability to achieve high precision with a reduced number of nodes is confirmed.
基金supported by the Open Funds for Hubei Key Laboratory of Marine Geological Resources,China University of Geosciences(No.MGR202308)the Natural Science Foundation of Shandong Province(No.ZR2020MD085)+3 种基金the National Natural Science Foundation of China(No.41821004)the Taishan Scholar Program(No.tstp2022114)the Shandong Provincial Natural Science Foundation(No.DKXZZ202206)the National Key Research and Development Program of China(No.2016YFC1402404).
文摘Ocean remote sensing satellites provide observations with high spatiotemporal resolution.However,the influence of clouds,fog,and haze frequently leads to significant data gaps.Accurate and effective estimation of these missing data is highly valuable for engineering and scientific research.In this study,the radial basis function(RBF)method is used to estimate the spatial distribution of total suspended matter(TSM)concentration in Hangzhou Bay using remote sensing data with severe data gaps.The estimation precision is validated by comparing the results with those of other commonly used interpolation methods,such as the Kriging method and the basic spline(B-spline)method.In addition,the applicability of the RBF method is explored.Results show that the estimation of the RBF method is significantly close to the observation in Hangzhou Bay.The average of the mean absolute error,mean relative error,and root mean square error in all the experiments is evidently smaller than those of the Kriging and B-spline interpolations,indicating that the proposed method is more appropriate for estimating the spatial distribution of the TSM in Hangzhou Bay.Finally,the TSM distribution in the blank observational area is predicted.This study can provide some reference values for handling watercolor remote sensing data.
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
文摘To conduct a comprehensive analysis of the current status of water environment quality in Yilong Lake,a systematic study was undertaken to characterize the evolution of water quality.This study utilized monthly data on water quality indicators collected from three monitoring sections of Yilong Lake between 2016 and 2023,employing the Mann-Kendall trend test and ArcGIS spatial interpolation technique.The results indicated that the five-day biochemical oxygen demand(BOD5),total nitrogen(TN),and chlorophyll a(Chla)exhibited an overall increasing trend,whereas other indicators demonstrated a decreasing trend.The permanganate index(PI),chemical oxygen demand(COD),TN,and Chla were observed in the following order:east of the lake>middle of the lake>west of the lake.In contrast,the BOD5 and total phosphorus(TP)were ranked as west of the lake>east of the lake>middle of the lake.Additionally,ammonia nitrogen(NH3-N)was found to be in the order of east of the lake>west of the lake>middle of the lake,while transparency was ranked as west of the lake>middle of the lake>east of the lake.Urban domestic sewage,effluent from industrial parks,domestic waste generated by rural residents’production and daily activities,agricultural waste,wastewater from decentralized farming,domestic sewage,and point source discharges from the soybean processing industry are the primary contributors to the exceedance of water quality standards.The enhancement of a precise pollution control system,along with the regulation of pollution sources and the interception of pollutants,can significantly diminish the pollution load entering the lake.This approach is essential for the protection and restoration of river and lake ecosystems,thereby facilitating the gradual recovery of their ecological functions.Additionally,the implementation of ecological water replenishment and the recycling of water resources can improve the capacity of the water environment.Furthermore,bolstering scientific and technological support,as well as comprehensive supervision and assurance measures,is crucial to ensuring that water quality remains stable and adheres to established standards.
基金supported by the Priority Program SPP 1992 of the German Science Foundation(DFG)The Diversity of Exoplanets under project number 362460292.
文摘We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresponding extended ab initio data set,we construct interpolation formulas covering the range from low-density,high-temperature to high-density,low-temperature plasmas.Our conductivity model repro-duces the well-known limits of the Spitzer and Ziman theory.We compare with available experimental data andfind very good agreement.The new conductivity model can be applied,for example,in dynamo simulations for magneticfield generation in gas giant planets,brown dwarfs,and stellar envelopes.
基金supported by National Key Research & Development Program of China (2022YFC3006201)。
文摘Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility of EMS has received considerable attention in health and transport geography studies.^([3])One of the optimal gauges for evaluating the accessibility of EMS is the response time,which is defined as the time from receiving an emergency call to the arrival of an ambulance.^([4])Beijing has already reduced the response time to approximately12 min,and the next goal is to ensure that the response time across Beijing does not exceed 12 min (the information comes from the Beijing Emergency Medical Center).
文摘Although the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)model has been widely applied in water quality assessment by numerous studies,several common limitations remain unresolved.Specifically:1)Subjective elements in methods such as fuzzy theory and the analytic hierarchy process(AHP)may distort evaluation outcomes;2)The utilization of raw sample data is in‐sufficient when constructing evaluation matrices;3)The traditional entropy weight method in TOPSIS merely reflects statistical character‐istics of the final matrix while neglecting richer information embedded in raw datasets.To address these issues,we proximate probability distribution function of various indicators by using cubic spline interpolation and fully exploit information in the existing massive sample data.In this paper,the entropy weight method is enhanced based on the concept mentioned above and integrated with TOPSIS model to construct a novel evaluation model.Furthermore,the experimental analysis using wastewater monitoring data from Guizhou Province,China,verifies its practicality,and its results provide valuable references for local water environmental management.
