As mobile internet and Internet of Things technologies continue to advance,the application scenarios of peer-to-peer Internet of Drones(IoD)are becoming increasingly diverse.However,the development of IoD also faces s...As mobile internet and Internet of Things technologies continue to advance,the application scenarios of peer-to-peer Internet of Drones(IoD)are becoming increasingly diverse.However,the development of IoD also faces signifcant challenges,such as security,privacy protection,and limited computing power,which require technological innova-tion to overcome.For group secure communication,it is necessary to provide two basic services,user authentication and group key agreement.Due to the limited storage of IoD devices,group key negotiation requires lightweight calculations,and conventional schemes cannot satisfy the requirements of group communication in the IoD.To this end,a new lightweight communication scheme based on ring neighbors is presented in this paper for IoD,which not only realizes the identity verifcation of user and group key negotiation,but also improves computational ef-ciency on each group member side.A detailed security analysis substantiates that the designed scheme is capable of withstanding attacks from both internal and external adversaries while satisfying all defned security requirements.More importantly,in our proposal,the computational cost on the user side remains unafected by the variability of the number of members participating in group communication,as members communicate in a non-interactive manner through broadcasting.As a result,the protocol proposed in this article demonstrates lower computational and communication costs in comparison to other cryptographic schemes.Hence,this proposal presents a more appealing approach to lightweight group key agreement protocol with user authentication for application in the IoD.展开更多
In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the couplin...In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.展开更多
A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical dis...A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical distribution of the two variables may show multimodal characteristics.In this work,a finite mixture bivariate statistical model was designed to describe the statistical properties,which is composed of several components,each with a Weibull distribution and a normal distribution for wind speed and wind shear,respectively,with a Gaussian copula to describe the dependency structure between the two variables.To confirm the developed model,reanalysis data from six positions in the coastal sea areas of China were used.Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions,giving acceptable predictions of the joint probability distributions.Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics.Importantly,unlike traditional methods that are limited to specific hub heights,the model developed here can estimate wind energy potential across different hub heights,enhancing the economic viability assessment of wind power projects.展开更多
In this paper, we introduce and study some new classes of biconvex functions with respect to an arbitrary function and a bifunction, which are called the higher order strongly biconvex functions. These functions are n...In this paper, we introduce and study some new classes of biconvex functions with respect to an arbitrary function and a bifunction, which are called the higher order strongly biconvex functions. These functions are nonconvex functions and include the biconvex function, convex functions, and <i>k</i>-convex as special cases. We study some properties of the higher order strongly biconvex functions. Several parallelogram laws for inner product spaces are obtained as novel applications of the higher order strongly biconvex affine functions. It is shown that the minimum of generalized biconvex functions on the <i>k</i>-biconvex sets can be characterized by a class of equilibrium problems, which is called the higher order strongly biequilibrium problems. Using the auxiliary technique involving the Bregman functions, several new inertial type methods for solving the higher order strongly biequilibrium problem are suggested and investigated. Convergence analysis of the proposed methods is considered under suitable conditions. Several important special cases are obtained as novel applications of the derived results. Some open problems are also suggested for future research.展开更多
In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar re...In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping.展开更多
基金supported by the National Natural Science Founda-tion of China(Grants Nos.62172181,62272189,62072133)the Fundamental Research Funds for the Central Universities(No.CCNU19TS019)+1 种基金the Research Planning Project of National Language Committee(No.YB135-40)the Research Initiation Project of Zhejiang Lab(No.2022PD0AC02).
文摘As mobile internet and Internet of Things technologies continue to advance,the application scenarios of peer-to-peer Internet of Drones(IoD)are becoming increasingly diverse.However,the development of IoD also faces signifcant challenges,such as security,privacy protection,and limited computing power,which require technological innova-tion to overcome.For group secure communication,it is necessary to provide two basic services,user authentication and group key agreement.Due to the limited storage of IoD devices,group key negotiation requires lightweight calculations,and conventional schemes cannot satisfy the requirements of group communication in the IoD.To this end,a new lightweight communication scheme based on ring neighbors is presented in this paper for IoD,which not only realizes the identity verifcation of user and group key negotiation,but also improves computational ef-ciency on each group member side.A detailed security analysis substantiates that the designed scheme is capable of withstanding attacks from both internal and external adversaries while satisfying all defned security requirements.More importantly,in our proposal,the computational cost on the user side remains unafected by the variability of the number of members participating in group communication,as members communicate in a non-interactive manner through broadcasting.As a result,the protocol proposed in this article demonstrates lower computational and communication costs in comparison to other cryptographic schemes.Hence,this proposal presents a more appealing approach to lightweight group key agreement protocol with user authentication for application in the IoD.
基金supported by the Natural Science Foundation of Shanxi Province(Grant No.20210302124437)the Graduate Student Research and Innovation Project of Shanxi Province(Grant No.2023KY551).
文摘In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.
基金supported by the Key R&D Program of Shandong Province,China(No.2021ZLGX04)the National Natural Science Foundation of China(No.52171284)。
文摘A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis.However,given the different atmospheric conditions that may be involved,the statistical distribution of the two variables may show multimodal characteristics.In this work,a finite mixture bivariate statistical model was designed to describe the statistical properties,which is composed of several components,each with a Weibull distribution and a normal distribution for wind speed and wind shear,respectively,with a Gaussian copula to describe the dependency structure between the two variables.To confirm the developed model,reanalysis data from six positions in the coastal sea areas of China were used.Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions,giving acceptable predictions of the joint probability distributions.Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics.Importantly,unlike traditional methods that are limited to specific hub heights,the model developed here can estimate wind energy potential across different hub heights,enhancing the economic viability assessment of wind power projects.
文摘In this paper, we introduce and study some new classes of biconvex functions with respect to an arbitrary function and a bifunction, which are called the higher order strongly biconvex functions. These functions are nonconvex functions and include the biconvex function, convex functions, and <i>k</i>-convex as special cases. We study some properties of the higher order strongly biconvex functions. Several parallelogram laws for inner product spaces are obtained as novel applications of the higher order strongly biconvex affine functions. It is shown that the minimum of generalized biconvex functions on the <i>k</i>-biconvex sets can be characterized by a class of equilibrium problems, which is called the higher order strongly biequilibrium problems. Using the auxiliary technique involving the Bregman functions, several new inertial type methods for solving the higher order strongly biequilibrium problem are suggested and investigated. Convergence analysis of the proposed methods is considered under suitable conditions. Several important special cases are obtained as novel applications of the derived results. Some open problems are also suggested for future research.
基金supported by the Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),UTS under grant numbers 321740.2232335,323930,and 321740.2232357
文摘In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping.
