Accurate prediction of main-engine rotational speed(RPM)is pivotal for en-ergy-efficient ship operation and compliance with emerging carbon-intensity regulations.Existing approaches either rely on computationally inte...Accurate prediction of main-engine rotational speed(RPM)is pivotal for en-ergy-efficient ship operation and compliance with emerging carbon-intensity regulations.Existing approaches either rely on computationally intensive phys-ics-based models or data-driven methods that neglect hydrodynamic con-straints and suffer from label noise in mandatory reporting data.We propose a physics-informed LightGBM framework that fuses high-resolution AIS tra-jectories,meteorological re-analyses and EU MRV logs through a temporally anchored,multi-source alignment protocol.A dual LightGBM ensemble(L1/L2)predicts RPM under laden and ballast conditions.Validation on a Panamax tanker(366 days)yields−1.52 rpm(−3%)error;ballast accuracy surpasses laden by 1.7%.展开更多
Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electron...Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.展开更多
Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from...Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.展开更多
The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initiall...The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.展开更多
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau a...On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,marked the largest earthquake in the region in recent years.The Shenzha-Dingjie fault zone,situated at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,is a key tectonic feature in the India-Eurasia collision process,exhibiting both thrust and strike-slip faulting.This study analyzed the disaster characteristics induced by the earthquake using Differential Synthetic Aperture Radar Interferometry(DIn SAR)to process Sentinel-1 satellite data and derive pre-and post-earthquake surface deformation information.Additionally,high-resolution optical remote sensing data,UAV(unmanned aerial vehicle)imagery,and airborne Li DAR(light detection and ranging)data were employed to analyze the spatial distribution of the surface rupture zone,with field investigations validating the findings.Key results include:(1)Field verification confirmed that potential landslide hazard points identified via optical image interpretation did not exhibit secondary landslide activity;(2)D-In SAR revealed the co-seismic surface deformation pattern,providing detailed deformation information for the Dingri region;(3)Integration of Li DAR and optical imagery further refined and validated surface rupture characteristics identified by optical-In SAR,indicating a predominantly north-south rupture zone.Additionally,surface fracture features extending in a near east-west direction were observed on the southeast side of the epicenter,accompanied by some infrastructure damage;(4)Surface fracture was most severe in high-intensity seismic areas near the epicenter,with the maximum surface displacement approximately 28 km from the epicenter.The earthquake-induced surface deformation zone spanned approximately 6 km by 46 km,with deformation concentrated primarily on the western side of the Dingmucuo Fault,where maximum subsidence of 0.65 m was detected.On the eastern side,uplift was dominant,reaching a maximum of 0.75 m.This earthquake poses significant threats to local communities and infrastructure,underscoring the urgent need for continued monitoring in affected areas.The findings highlight the effectiveness of multi-source data fusion(space-air-ground based observation)in seismic disaster assessment,offering a methodological framework for rapid post-earthquake disaster response.providing a valuable scientific foundation for mitigating secondary disasters in the region.展开更多
For all-sky infrared radiance assimilation,the heteroscedasticity and non-Gaussian behavior of observation-minusbackground(OMB)departures are two major difficulties.The Geer–Bauer observation error inflation(GBOEI)sc...For all-sky infrared radiance assimilation,the heteroscedasticity and non-Gaussian behavior of observation-minusbackground(OMB)departures are two major difficulties.The Geer–Bauer observation error inflation(GBOEI)scheme is a universal way to handle the issues.However,it fails to take into account the consistency between model and observation,resulting in unreasonably large observation errors where the simulations agree with the observations.Thus,this study modifies the GBOEI scheme to rationalize the observation errors in such areas.With Advanced Himawari Imager water vapor channel data,the test results show that the normalized OMB with the new observation error approach leads to more Gaussian form than the GBOEI method and constant observation errors.Hence,the assimilation experiments with the new scheme produce better brightness temperature analysis than other methods,and also improve temperature and humidity analysis.Furthermore,a real case experiment of Typhoon Lekima(2019)with the new observation error scheme exhibits more accuracy,especially in track prediction,and substantial error reductions in wind,temperature,and humidity forecasts are also obtained.Meanwhile,5-day 6-hour cycling experiments in the real case of Typhoon Lekima(2019)with the new observation error scheme confirm that the new method does not introduce extra imbalance compared to the experiment with constant observation errors;plus,more accurate typhoon forecasts can also be obtained in both the analysis and forecast,especially in track prediction.展开更多
Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to pred...Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.展开更多
Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with ...Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS （AMSR-E） and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System （IMS）. AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as ＂virtual＂ in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model （DEM） but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method.展开更多
Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of ble...Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.展开更多
Currently,China has 32 Earth observation satellites in orbit.The satellites can provide various data such as optical,multispectral,infrared,and radar.The spatial resolution of China Earth observation satellites ranges...Currently,China has 32 Earth observation satellites in orbit.The satellites can provide various data such as optical,multispectral,infrared,and radar.The spatial resolution of China Earth observation satellites ranges from low to medium to high.The satellites possess the capability to observe across multiple spectral bands,under all weather conditions,and at all times.The data of China Earth observation satellites has been widely used in fields such as natural resource detection,environmental monitoring and protection,disaster prevention and reduction,urban planning and mapping,agricultural and forestry surveys,land survey and geological prospecting,and ocean forecasting,achieving huge social benefits.This article introduces the recent progress of Earth observation satellites in China since 2022,especially the satellite operation,data archiving,data distribution and data coverage.展开更多
This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The ...This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones （typhoons）, ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finaliy, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.展开更多
The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of G...The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.展开更多
Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and...Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.展开更多
Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation...Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation with the variation of the tide.Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points,with 0.15℃/h considered a suitable threshold for detecting abnormal values.The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter.The diurnal variation of SST has bimodal structure on most days,i.e.,SST has a significant semidiurnal cycle.Moreover,the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August,but positively correlated with the tidal data from October to January.Little correlation is detected in the remaining months because of the weak coastal offshore SST gradients.The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellite-derived data.展开更多
For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for...For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for the ensemble-based data assimilation methods.In this paper,we propose a multi-source information fused generative adversarial network(MSIGAN)model,which is used for parameterization of the complex geologies.In MSIGAN,various information such as facies distribution,microseismic,and inter-well connectivity,can be integrated to learn the geological features.And two major generative models in deep learning,variational autoencoder(VAE)and generative adversarial network(GAN)are combined in our model.Then the proposed MSIGAN model is integrated into the ensemble smoother with multiple data assimilation(ESMDA)method to conduct history matching.We tested the proposed method on two reservoir models with fluvial facies.The experimental results show that the proposed MSIGAN model can effectively learn the complex geological features,which can promote the accuracy of history matching.展开更多
In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors,the urban surface temperature patterns of Changsha in 2000,2009 and 2016 are retrieved b...In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors,the urban surface temperature patterns of Changsha in 2000,2009 and 2016 are retrieved based on multi-source spatial data(Landsat 5 and Landsat 8 satellite image data,POI spatial big data,digital elevation model,etc.),and 12 natural and human factors closely related to urban thermal environment are quickly obtained.The standard deviation ellipse and spatial principal component analysis(PCA)methods are used to analyze the effect of urban human residential thermal environment and its influencing factors.The results showed that the heat island area increased by 547 km~2 and the maximum surface temperature difference reached 10.1℃during the period 2000–2016.The spatial distribution of urban heat island was mainly concentrated in urban built-up areas,such as industrial and commercial agglomerations and densely populated urban centers.The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs.There were multiple high-temperature centers,such as Wuyi square business circle,Xingsha economic and technological development zone in Changsha County,Wangcheng industrial zone,Yuelu industrial agglomeration,and Tianxin industrial zone.From 2000 to 2016,the main axis of spatial development of heat island remained in the northeast-southwest direction.The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9°in 2000–2009.The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9°in 2009–2016.On the whole,the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity.Through the PCA method,it was concluded that landscape pattern,urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha.The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors.The temperature would rise by 0.293℃under the synthetic effect of human and natural factors.Due to the complexity of factors influencing the urban thermal environment of human settlements,the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment,deepen the understanding of the causes of urban heat island effect,and clarify the correlation between human and natural factors,so as to provide scientific supports for the improvement of the quality of urban human settlements.展开更多
Multi-Source data plays an important role in the evolution of media convergence.Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemin...Multi-Source data plays an important role in the evolution of media convergence.Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data.However,it also faces serious problems in terms of protecting user and data privacy.Many privacy protectionmethods have been proposed to solve the problemof privacy leakage during the process of data sharing,but they suffer fromtwo flaws:1)the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain;2)the inability to solve the problem of the high computational complexity of ciphertext in multi-source data privacy protection,resulting in long encryption and decryption times.In this paper,we propose a multi-source data privacy protection method based on homomorphic encryption and blockchain technology,which solves the privacy protection problem ofmulti-source heterogeneous data in the dissemination ofmedia and reduces ciphertext processing time.We deployed the proposedmethod on theHyperledger platformfor testing and compared it with the privacy protection schemes based on k-anonymity and differential privacy.The experimental results showthat the key generation,encryption,and decryption times of the proposedmethod are lower than those in data privacy protection methods based on k-anonymity technology and differential privacy technology.This significantly reduces the processing time ofmulti-source data,which gives it potential for use in many applications.展开更多
Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of ...Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.展开更多
Due to the complex nature of multi-source geological data, it is difficult to rebuild every geological structure through a single 3D modeling method. The multi-source data interpretation method put forward in this ana...Due to the complex nature of multi-source geological data, it is difficult to rebuild every geological structure through a single 3D modeling method. The multi-source data interpretation method put forward in this analysis is based on a database-driven pattern and focuses on the discrete and irregular features of geological data. The geological data from a variety of sources covering a range of accuracy, resolution, quantity and quality are classified and integrated according to their reliability and consistency for 3D modeling. The new interpolation-approximation fitting construction algorithm of geological surfaces with the non-uniform rational B-spline(NURBS) technique is then presented. The NURBS technique can retain the balance among the requirements for accuracy, surface continuity and data storage of geological structures. Finally, four alternative 3D modeling approaches are demonstrated with reference to some examples, which are selected according to the data quantity and accuracy specification. The proposed approaches offer flexible modeling patterns for different practical engineering demands.展开更多
基金support from the“Ocean-going Vessel Meteorological Navigation System”project funded under the Key Core Technology Breakthrough Program for Transportation Equipment(GJ-2025-01)COSCO Shipping Group’s Third Batch of Scientific Research Projects from the 14th Five-Year Plan.
文摘Accurate prediction of main-engine rotational speed(RPM)is pivotal for en-ergy-efficient ship operation and compliance with emerging carbon-intensity regulations.Existing approaches either rely on computationally intensive phys-ics-based models or data-driven methods that neglect hydrodynamic con-straints and suffer from label noise in mandatory reporting data.We propose a physics-informed LightGBM framework that fuses high-resolution AIS tra-jectories,meteorological re-analyses and EU MRV logs through a temporally anchored,multi-source alignment protocol.A dual LightGBM ensemble(L1/L2)predicts RPM under laden and ballast conditions.Validation on a Panamax tanker(366 days)yields−1.52 rpm(−3%)error;ballast accuracy surpasses laden by 1.7%.
基金Under the auspices of the Key Program of National Natural Science Foundation of China(No.42030409)。
文摘Multi-source data fusion provides high-precision spatial situational awareness essential for analyzing granular urban social activities.This study used Shanghai’s catering industry as a case study,leveraging electronic reviews and consumer data sourced from third-party restaurant platforms collected in 2021.By performing weighted processing on two-dimensional point-of-interest(POI)data,clustering hotspots of high-dimensional restaurant data were identified.A hierarchical network of restaurant hotspots was constructed following the Central Place Theory(CPT)framework,while the Geo-Informatic Tupu method was employed to resolve the challenges posed by network deformation in multi-scale processes.These findings suggest the necessity of enhancing the spatial balance of Shanghai’s urban centers by moderately increasing the number and service capacity of suburban centers at the urban periphery.Such measures would contribute to a more optimized urban structure and facilitate the outward dispersion of comfort-oriented facilities such as the restaurant industry.At a finer spatial scale,the distribution of restaurant hotspots demonstrates a polycentric and symmetric spatial pattern,with a developmental trend radiating outward along the city’s ring roads.This trend can be attributed to the efforts of restaurants to establish connections with other urban functional spaces,leading to the reconfiguration of urban spaces,expansion of restaurant-dedicated land use,and the reorganization of associated commercial activities.The results validate the existence of a polycentric urban structure in Shanghai but also highlight the instability of the restaurant hotspot network during cross-scale transitions.
基金Sponsored by Beijing Youth Innovation Talent Support Program for Urban Greening and Landscaping——The 2024 Special Project for Promoting High-Quality Development of Beijing’s Landscaping through Scientific and Technological Innovation(KJCXQT202410).
文摘Taking the Ming Tombs Forest Farm in Beijing as the research object,this research applied multi-source data fusion and GIS heat-map overlay analysis techniques,systematically collected bird observation point data from the Global Biodiversity Information Facility(GBIF),population distribution data from the Oak Ridge National Laboratory(ORNL)in the United States,as well as information on the composition of tree species in suitable forest areas for birds and the forest geographical information of the Ming Tombs Forest Farm,which is based on literature research and field investigations.By using GIS technology,spatial processing was carried out on bird observation points and population distribution data to identify suitable bird-watching areas in different seasons.Then,according to the suitability value range,these areas were classified into different grades(from unsuitable to highly suitable).The research findings indicated that there was significant spatial heterogeneity in the bird-watching suitability of the Ming Tombs Forest Farm.The north side of the reservoir was generally a core area with high suitability in all seasons.The deep-aged broad-leaved mixed forests supported the overlapping co-existence of the ecological niches of various bird species,such as the Zosterops simplex and Urocissa erythrorhyncha.In contrast,the shallow forest-edge coniferous pure forests and mixed forests were more suitable for specialized species like Carduelis sinica.The southern urban area and the core area of the mausoleums had relatively low suitability due to ecological fragmentation or human interference.Based on these results,this paper proposed a three-level protection framework of“core area conservation—buffer zone management—isolation zone construction”and a spatio-temporal coordinated human-bird co-existence strategy.It was also suggested that the human-bird co-existence space could be optimized through measures such as constructing sound and light buffer interfaces,restoring ecological corridors,and integrating cultural heritage elements.This research provided an operational technical approach and decision-making support for the scientific planning of bird-watching sites and the coordination of ecological protection and tourism development.
基金supported by the National Key Research and Development Program of China(grant number 2019YFE0123600)。
文摘The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
基金supported by the National Natural Science Foundation of China(No.42477170)the Major Project of the National Natural Science Foundation of China(No.42090054)+1 种基金the Research Fund Program of Hubei Key Laboratory of Resources and Eco-Environment Geology(No.HBREGKFJJ-202411)Innovative Group Project of Natural Science Foundation of Hubei Province(No.2024AFA015)。
文摘On January 7,2025,an Ms6.8 earthquake struck Dingri County,XigazêCity,in the Xizang Autonomous Region.The epicenter,located near the Shenzha-Dingjie fault zone at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,marked the largest earthquake in the region in recent years.The Shenzha-Dingjie fault zone,situated at the boundary between the Qinghai-Xizang Plateau and the Indian Plate,is a key tectonic feature in the India-Eurasia collision process,exhibiting both thrust and strike-slip faulting.This study analyzed the disaster characteristics induced by the earthquake using Differential Synthetic Aperture Radar Interferometry(DIn SAR)to process Sentinel-1 satellite data and derive pre-and post-earthquake surface deformation information.Additionally,high-resolution optical remote sensing data,UAV(unmanned aerial vehicle)imagery,and airborne Li DAR(light detection and ranging)data were employed to analyze the spatial distribution of the surface rupture zone,with field investigations validating the findings.Key results include:(1)Field verification confirmed that potential landslide hazard points identified via optical image interpretation did not exhibit secondary landslide activity;(2)D-In SAR revealed the co-seismic surface deformation pattern,providing detailed deformation information for the Dingri region;(3)Integration of Li DAR and optical imagery further refined and validated surface rupture characteristics identified by optical-In SAR,indicating a predominantly north-south rupture zone.Additionally,surface fracture features extending in a near east-west direction were observed on the southeast side of the epicenter,accompanied by some infrastructure damage;(4)Surface fracture was most severe in high-intensity seismic areas near the epicenter,with the maximum surface displacement approximately 28 km from the epicenter.The earthquake-induced surface deformation zone spanned approximately 6 km by 46 km,with deformation concentrated primarily on the western side of the Dingmucuo Fault,where maximum subsidence of 0.65 m was detected.On the eastern side,uplift was dominant,reaching a maximum of 0.75 m.This earthquake poses significant threats to local communities and infrastructure,underscoring the urgent need for continued monitoring in affected areas.The findings highlight the effectiveness of multi-source data fusion(space-air-ground based observation)in seismic disaster assessment,offering a methodological framework for rapid post-earthquake disaster response.providing a valuable scientific foundation for mitigating secondary disasters in the region.
基金funded by the National Natural Science Foundation of China(Grant Nos.42192553 and 41805071)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_1413)the High Performance Computing Center of Nanjing University of Information Science&Technology for their support of this work。
文摘For all-sky infrared radiance assimilation,the heteroscedasticity and non-Gaussian behavior of observation-minusbackground(OMB)departures are two major difficulties.The Geer–Bauer observation error inflation(GBOEI)scheme is a universal way to handle the issues.However,it fails to take into account the consistency between model and observation,resulting in unreasonably large observation errors where the simulations agree with the observations.Thus,this study modifies the GBOEI scheme to rationalize the observation errors in such areas.With Advanced Himawari Imager water vapor channel data,the test results show that the normalized OMB with the new observation error approach leads to more Gaussian form than the GBOEI method and constant observation errors.Hence,the assimilation experiments with the new scheme produce better brightness temperature analysis than other methods,and also improve temperature and humidity analysis.Furthermore,a real case experiment of Typhoon Lekima(2019)with the new observation error scheme exhibits more accuracy,especially in track prediction,and substantial error reductions in wind,temperature,and humidity forecasts are also obtained.Meanwhile,5-day 6-hour cycling experiments in the real case of Typhoon Lekima(2019)with the new observation error scheme confirm that the new method does not introduce extra imbalance compared to the experiment with constant observation errors;plus,more accurate typhoon forecasts can also be obtained in both the analysis and forecast,especially in track prediction.
基金supported by the National Natural Science Foundation of China(41977215)。
文摘Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.
基金Meteorological Research in the Public Interest,No.GYHY201106014Beijing Nova Program,No.2010B037China Special Fund for the National High Technology Research and Development Program of China(863 Program),No.412230
文摘Snow depth （SD） is a key parameter for research into global climate changes and land surface processes. A method was developed to obtain daily SD images at a higher 4 km spatial resolution and higher precision with SD measurements from in situ observations and passive microwave remote sensing of Advanced Microwave Scanning Radiometer-EOS （AMSR-E） and snow cover measurements of the Interactive Multisensor Snow and Ice Mapping System （IMS）. AMSR-E SD at 25 km spatial resolution was retrieved from AMSR-E products of snow density and snow water equivalent and then corrected using the SD from in situ observations and IMS snow cover. Corrected AMSR-E SD images were then resampled to act as ＂virtual＂ in situ observations to combine with the real in situ observations to interpolate at 4 km spatial resolution SD using the Cressman method. Finally, daily SD data generation for several regions of China demonstrated that the method is well suited to the generation of higher spatial resolution SD data in regions with a lower Digital Elevation Model （DEM） but not so well suited to regions at high altitude and with an undulating terrain, such as the Tibetan Plateau. Analysis of the longer time period SD data generation for January between 2003 and 2010 in northern Xinjiang also demonstrated the feasibility of the method.
文摘Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.
文摘Currently,China has 32 Earth observation satellites in orbit.The satellites can provide various data such as optical,multispectral,infrared,and radar.The spatial resolution of China Earth observation satellites ranges from low to medium to high.The satellites possess the capability to observe across multiple spectral bands,under all weather conditions,and at all times.The data of China Earth observation satellites has been widely used in fields such as natural resource detection,environmental monitoring and protection,disaster prevention and reduction,urban planning and mapping,agricultural and forestry surveys,land survey and geological prospecting,and ocean forecasting,achieving huge social benefits.This article introduces the recent progress of Earth observation satellites in China since 2022,especially the satellite operation,data archiving,data distribution and data coverage.
基金The National Natural Science Foundation under contract No.41621064the Science and Technology Basic Work of the Ministry of Science and Technology of China under contract No.2012FY112300the Public Science and Technology Research Funds Projects of Ocean under contract No.201005033
文摘This paper reviews the current achievements of the China Argo project. It considers aspects of both the construction of the Argo observing array, float technology, and the quality control and sharing of its data. The developments of associated data products and data applications for use in the fields of ocean, atmosphere, and climate research are discussed, particularly those related to tropical cyclones （typhoons）, ocean circulation, mesoscale eddies, turbulence, oceanic heat/salt storage and transportation, water masses, and operational oceanic/atmospheric/climatic forecasts and predictions. Finaliy, the challenges and opportunities involved in the long-term maintenance and sustained development of the China Argo ocean observation network are outlined. Discussion also focuses on the necessity for increasing the number of floats in the Indian Ocean and for expanding the regional Argo observation network in the South China Sea, together with the importance of promoting the use of Argo data by the maritime countries of Southeast Asia and India.
基金the National Key R&D Program of China(Grant No.2022YFF0503702)the National Natural Science Foundation of China(Grant Nos.42074186,41831071,42004136,and 42274195)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20211036)the Specialized Research Fund for State Key Laboratories,and the University of Science and Technology of China Research Funds of the Double First-Class Initiative(Grant No.YD2080002013).
文摘The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.
基金funded by the International Cooperation and Exchanges National Natural Science Foundation of China (41120114001)
文摘Earth observation technology has provided highly useful information in global climate change research over the past few decades and greatly promoted its development,especially through providing biological,physical,and chemical parameters on a global scale.Earth observation data has the 4V features(volume,variety,veracity,and velocity) of big data that are suitable for climate change research.Moreover,the large amount of data available from scientific satellites plays an important role.This study reviews the advances of climate change studies based on Earth observation big data and provides examples of case studies that utilize Earth observation big data in climate change research,such as synchronous satelliteeaerialeground observation experiments,which provide extremely large and abundant datasets; Earth observational sensitive factors(e.g.,glaciers,lakes,vegetation,radiation,and urbanization); and global environmental change information and simulation systems.With the era of global environment change dawning,Earth observation big data will underpin the Future Earth program with a huge volume of various types of data and will play an important role in academia and decisionmaking.Inevitably,Earth observation big data will encounter opportunities and challenges brought about by global climate change.
基金The Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics under contract No.SOED1402the Youth Science and Technology Foundation of East China Sea Branch,SOA under contract No.201624
文摘Sea surface temperature(SST)data obtained from coastal stations in Jiangsu,China during 20102014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles,including the correlation with the variation of the tide.Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points,with 0.15℃/h considered a suitable threshold for detecting abnormal values.The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter.The diurnal variation of SST has bimodal structure on most days,i.e.,SST has a significant semidiurnal cycle.Moreover,the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August,but positively correlated with the tidal data from October to January.Little correlation is detected in the remaining months because of the weak coastal offshore SST gradients.The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellite-derived data.
基金supported by the National Natural Science Foundation of China under Grant 51722406,52074340,and 51874335the Shandong Provincial Natural Science Foundation under Grant JQ201808+5 种基金The Fundamental Research Funds for the Central Universities under Grant 18CX02097Athe Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008the Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002the National Research Council of Science and Technology Major Project of China under Grant 2016ZX05025001-006111 Project under Grant B08028Sinopec Science and Technology Project under Grant P20050-1
文摘For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for the ensemble-based data assimilation methods.In this paper,we propose a multi-source information fused generative adversarial network(MSIGAN)model,which is used for parameterization of the complex geologies.In MSIGAN,various information such as facies distribution,microseismic,and inter-well connectivity,can be integrated to learn the geological features.And two major generative models in deep learning,variational autoencoder(VAE)and generative adversarial network(GAN)are combined in our model.Then the proposed MSIGAN model is integrated into the ensemble smoother with multiple data assimilation(ESMDA)method to conduct history matching.We tested the proposed method on two reservoir models with fluvial facies.The experimental results show that the proposed MSIGAN model can effectively learn the complex geological features,which can promote the accuracy of history matching.
基金National Social Science Foundation of China,No.15BJY051Open Topic of Hunan Key Laboratory of Land Resources Evaluation and Utilization,No.SYS-ZX-202002Research Project of Appraisement Committee of Social Sciences Research Achievements of Hunan Province,No.XSP18ZDI031。
文摘In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors,the urban surface temperature patterns of Changsha in 2000,2009 and 2016 are retrieved based on multi-source spatial data(Landsat 5 and Landsat 8 satellite image data,POI spatial big data,digital elevation model,etc.),and 12 natural and human factors closely related to urban thermal environment are quickly obtained.The standard deviation ellipse and spatial principal component analysis(PCA)methods are used to analyze the effect of urban human residential thermal environment and its influencing factors.The results showed that the heat island area increased by 547 km~2 and the maximum surface temperature difference reached 10.1℃during the period 2000–2016.The spatial distribution of urban heat island was mainly concentrated in urban built-up areas,such as industrial and commercial agglomerations and densely populated urban centers.The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs.There were multiple high-temperature centers,such as Wuyi square business circle,Xingsha economic and technological development zone in Changsha County,Wangcheng industrial zone,Yuelu industrial agglomeration,and Tianxin industrial zone.From 2000 to 2016,the main axis of spatial development of heat island remained in the northeast-southwest direction.The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9°in 2000–2009.The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9°in 2009–2016.On the whole,the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity.Through the PCA method,it was concluded that landscape pattern,urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha.The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors.The temperature would rise by 0.293℃under the synthetic effect of human and natural factors.Due to the complexity of factors influencing the urban thermal environment of human settlements,the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment,deepen the understanding of the causes of urban heat island effect,and clarify the correlation between human and natural factors,so as to provide scientific supports for the improvement of the quality of urban human settlements.
基金funded by the High-Quality and Cutting-Edge Discipline Construction Project for Universities in Beijing (Internet Information,Communication University of China).
文摘Multi-Source data plays an important role in the evolution of media convergence.Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data.However,it also faces serious problems in terms of protecting user and data privacy.Many privacy protectionmethods have been proposed to solve the problemof privacy leakage during the process of data sharing,but they suffer fromtwo flaws:1)the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain;2)the inability to solve the problem of the high computational complexity of ciphertext in multi-source data privacy protection,resulting in long encryption and decryption times.In this paper,we propose a multi-source data privacy protection method based on homomorphic encryption and blockchain technology,which solves the privacy protection problem ofmulti-source heterogeneous data in the dissemination ofmedia and reduces ciphertext processing time.We deployed the proposedmethod on theHyperledger platformfor testing and compared it with the privacy protection schemes based on k-anonymity and differential privacy.The experimental results showthat the key generation,encryption,and decryption times of the proposedmethod are lower than those in data privacy protection methods based on k-anonymity technology and differential privacy technology.This significantly reduces the processing time ofmulti-source data,which gives it potential for use in many applications.
基金Under the auspices of Natural Science Foundation of China(No.41971166)。
文摘Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.
基金Supported by the National Natural Science Foundation of China(No.51379006 and No.51009106)the Program for New Century Excellent Talents in University of Ministry of Education of China(No.NCET-12-0404)the National Basic Research Program of China("973"Program,No.2013CB035903)
文摘Due to the complex nature of multi-source geological data, it is difficult to rebuild every geological structure through a single 3D modeling method. The multi-source data interpretation method put forward in this analysis is based on a database-driven pattern and focuses on the discrete and irregular features of geological data. The geological data from a variety of sources covering a range of accuracy, resolution, quantity and quality are classified and integrated according to their reliability and consistency for 3D modeling. The new interpolation-approximation fitting construction algorithm of geological surfaces with the non-uniform rational B-spline(NURBS) technique is then presented. The NURBS technique can retain the balance among the requirements for accuracy, surface continuity and data storage of geological structures. Finally, four alternative 3D modeling approaches are demonstrated with reference to some examples, which are selected according to the data quantity and accuracy specification. The proposed approaches offer flexible modeling patterns for different practical engineering demands.
