The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data,leading to a demand for effective data management solutions.This...The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data,leading to a demand for effective data management solutions.This is further catalysed through the need for society to make informed policies and decisions that can properly support their emerging growth.While data systems and platforms exist,they are often proprietary,being only compatible to the products that they are designed for.Given the products and services generate energy and spatial-temporal data that can often correlate,a lack of interoperability between these systems would impede decision making,as data from each system must be considered independently.By studying currently available data platforms and frameworks,this paper weighs the problems that these products address,and identifies necessary gaps for a more cohesive platform to exist.This is performed through a top-down approach,whereby broader vehicle-toeverything approaches are first studied,before moving to the components that could comprise a data platform to integrate and ingest these various data feeds.Finally,potential design considerations for a data platform is presented,along with examples of application bene.展开更多
Currently, big data platforms are widely applied across various industries. These platforms are characterized by large scale, diverse forms, high update frequency, and rapid data flow, making it challenging to directl...Currently, big data platforms are widely applied across various industries. These platforms are characterized by large scale, diverse forms, high update frequency, and rapid data flow, making it challenging to directly apply existing risk quantification methods to them. Additionally, the composition of big data platforms varies among enterprises due to factors such as industry, economic capability, and technical proficiency. To address this, we first developed a risk quantification assessment process tailored to different types of big data platforms, taking into account relevant laws, regulations, and standards. Subsequently,we developed RiskTree, a risk quantification system for big data platforms, which supports automated detection of configuration files, traffic, and vulnerabilities. For situations where automated detection is not feasible or permitted, we provide a customized questionnaire system to collect assets and data processing procedures. We utilize a knowledge graph(KG)to integrate and analyze the collected data. Finally, we apply a random forest algorithm to compute risk index weights, risk values, and risk levels, enabling the quantification of risks on big data platforms. To validate the proposed process, we conducted experiments on an educational big data platform. The results demonstrate that the risk index system presented in this paper objectively and comprehensively reflects the risks faced by big data platforms. Furthermore, the proposed risk assessment process not only effectively identifies and quantifies risks but also provides highly interpretable evaluation results.展开更多
As China’s first new energy comprehensive demonstration zone,Ningxia’s solar photovoltaic(PV)industry has developed rapidly,but it still faces shortcomings in terms of intelligence and digitalization.This study focu...As China’s first new energy comprehensive demonstration zone,Ningxia’s solar photovoltaic(PV)industry has developed rapidly,but it still faces shortcomings in terms of intelligence and digitalization.This study focuses on the application and construction of an intelligent big data platform based on Narrowband Internet of Things(NB-IoT)technology within Ningxia’s solar PV industry.It explores the application trends of digital technology in the energy sector,particularly in the PV industry under the backdrop of energy reform,analyzes the technological development status of the smart energy field both domestically and internationally,and details the research methods and design components of the platform(including the photovoltaic base data platform,outdoor mobile application,remote data system,and back-office management system).The study discusses the opportunities and challenges Ningxia’s PV industry faces and proposes a construction pathway.It provides a theoretical foundation and technical support for the digital transformation of Ningxia’s PV industry,facilitating industrial upgrading and sustainable development.Although the current research is limited to the proposed design scheme,it establishes a basis for future empirical research and platform development.展开更多
Pelvic floor dysfunction(PFD),including conditions such as stress urinary incontinence,pelvic organ prolapse,and fecal incontinence,significantly affects women's quality of life and their physical and mental healt...Pelvic floor dysfunction(PFD),including conditions such as stress urinary incontinence,pelvic organ prolapse,and fecal incontinence,significantly affects women's quality of life and their physical and mental health.With advancement of digital medicine,the systematic collection of data and the high-quality development of database platforms have increasingly become central pillars of PFD research and management.We systematically review the developmental stages of PFDrelated databases.We then conduct a comparative analysis of representative international and domestic platforms,examining key aspects including organizational structures and construction models,data sources and integration strategies,core functionalities,data quality control and standardization,data security and access management,and research applications.Finally,based on the current status of PFD database development both globally and in China,we offer recommendations to strengthen data infrastructure and guide future directions.The findings may serve as a valuable reference for the optimization of PFD databases worldwide.展开更多
5G-R is the main type of next-generation mobile communication system for railways,offering highly reliable broadband data transmission services for intelligent railway operations.In the light of meeting the bearing de...5G-R is the main type of next-generation mobile communication system for railways,offering highly reliable broadband data transmission services for intelligent railway operations.In the light of meeting the bearing demands of the 5G-R network,a comprehensive data transmission platform is proposed.This platform enables unified accession for various data service systems and applies Software Defined Network(SDN)technology for dynamic routing selection and high-effective data forwarding.Based on shared key lightweight access authentication technology,two-way identity authentication is performed for mobile terminals and network-side devices,ensuring the legitimacy verification of heterogeneous terminals within the application domain.展开更多
With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heter...With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.展开更多
In view of the problems such as frequent fluctuation of garlic price, lack ofefficient forecasting means and difficulty in realizing the steady development of garlicindustry, combined with the current situation of gar...In view of the problems such as frequent fluctuation of garlic price, lack ofefficient forecasting means and difficulty in realizing the steady development of garlicindustry, combined with the current situation of garlic industry and the collected datainformation. Taking Big Data platform of garlic industry chain as the core, using themethods of correlation analysis, smoothness test, co-integration test, and Grangercausality test, this paper analyzes the correlation, dynamic, and causality between garlicprice and young garlic shoot price. According to the current situation of garlic industry,the garlic industry service based on Big Data is put forward. It is concluded that there is apositive correlation between garlic price and young garlic shoot price, and there is a longtermstable dynamic equilibrium relationship between young garlic shoot price and garlicprice fluctuation, and young garlic shoot price can affect garlic price. Finally, it isproposed to strengthen the infrastructure construction of garlic Big Data, increase thetechnological innovation and application of garlic Big Data technology, and promote thesafety and security ability of the whole industry to promote the development of garlicindustry.展开更多
This paper makes astudy on the interactive digital gener-alization,where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure,which are done by human andcomputer,respectiv...This paper makes astudy on the interactive digital gener-alization,where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure,which are done by human andcomputer,respectively.And an inter-active map generalization environmentfor large scale topographic map is thendesigned and realized.This researchfocuses on:①the significance of re-searching an interactive map generali-zation environment,②the features oflarge scale topographic map and inter-active map generalization,③the con-struction of map generalization-orien-ted database platform.展开更多
The Data Platform of Resource and Environment—whose data mainly come from field observation stations,spatial observations,and internet service institutions—is the base of data analysis and model simulation in geosci...The Data Platform of Resource and Environment—whose data mainly come from field observation stations,spatial observations,and internet service institutions—is the base of data analysis and model simulation in geoscience research in China.Among this integrated data platform,the tasks of the data platform of field observation stations are principally data collection,management,assimilation,and share service.Taking into consideration the distributing characteristics of the data sources and the service objects,the authors formulated the framework of the field observation stations' data platform based on the grid technology and designed its operating processes.The authors have further defined and analyzed the key functions and implementing techniques for each module.In a Linux operating system,validation tests for the data platform's function on data replication,data synchronization,and unified data service have been conducted under an environment that of the simulating field stations.展开更多
The calculation results of the rolling force and torque model based on Orowan's differential equation numerical solution method do not fit with the industrial measurements very well.In particular,a quite large dev...The calculation results of the rolling force and torque model based on Orowan's differential equation numerical solution method do not fit with the industrial measurements very well.In particular,a quite large deviation on the torque model was found.On the basis of analyzing the shortcomings of the existing method,an improved rolling force and torque model algorithm aided by the Process Integrated Data Application System platform is proposed.Accordingly,the calculation accuracy of the rolling torque model is improved.The improved models are verified by 1711136 records of a data platform.The improved models are also based on Orowan's differential equation.Two coefficients,namely,friction factor and forward slip,are recognized as the crucial factors to be determined from industrial measurements to improve the accuracy.Therefore,the proposed method is a hybrid method that can be used to deeply understand the rolling process and improve the model's accuracy by combining traditional plastic mechanics and data-driving global optimization algorithms.This paper proposes a new approach to studying theoretical rolling deformation models powered by the industrial data platform.展开更多
To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex mult...To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.展开更多
In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning method.We demonstrated that the training dataset has a significant impact on the trainin...In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning method.We demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model structure.However,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial obstacle.This issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data security.To address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.展开更多
Remote data monitoring system which adopts virtual instrument usually applies data sharing, acquisition and remote transmission technology via internet. It is able to finish concurrent data acquisition and processing ...Remote data monitoring system which adopts virtual instrument usually applies data sharing, acquisition and remote transmission technology via internet. It is able to finish concurrent data acquisition and processing for multi-user and multi-task and also build a personalized virtual testing environment for more people but with fewer instruments. In this paper, we＇ 11 elaborate on the design and implementation of information sharing platform through a typical example of how to build multi-user concurrent virtual testing environment based on the virtnal software LabVIEW.展开更多
Objective To introduce the relevant big data platforms of FDA regulatory sciences and to provide reference for the construction of big data platform for China’s regulatory science under the“14th five-year plan”to d...Objective To introduce the relevant big data platforms of FDA regulatory sciences and to provide reference for the construction of big data platform for China’s regulatory science under the“14th five-year plan”to deepen the reform of medical and health system.Methods A comparative analysis was made on China’s big data for regulatory science after studying the development process,operation mode,practical significance and characteristics of the big data platform for FDA regulatory science,which would help China to establish a perfect big database.Results and Conclusion The construction of big data platform for China’s regulatory science is not comprehensive compared with that in the United States.It is necessary to build data platforms in line with China’s national conditions through efforts in law,talents,standards,and other aspects.展开更多
Big data cloud platforms provide users with on-demand configurable computing,storage resources to users,thus involving a large amount of user data.However,most of the data is processed and stored in plaintext,resultin...Big data cloud platforms provide users with on-demand configurable computing,storage resources to users,thus involving a large amount of user data.However,most of the data is processed and stored in plaintext,resulting in data leakage.At the same time,simple encrypted storage ensures the confidentiality of the cloud data,but has the following problems:if the encrypted data is downloaded to the client and then decrypted,the search efficiency will be low.If the encrypted data is decrypted and searched on the server side,the security will be reduced.Data availability is finally reduced,and indiscriminate protection measures make the risk of data leakage uncontrollable.To solve the problems,based on searchable encryption and key derivation,a cipher search system is designed in this paper considering both data security and availability,and the use of a search encryption algorithm that supports dynamic update is listed.Moreover,the system structure has the advantage of adapting different searchable encryption algorithm.In particular,a user-centered key derivation mechanism is designed to realize file-level fine-grained encryption.Finally,extensive experiment and analysis show that the scheme greatly improves the data security of big data platform.展开更多
Offshore engineering projects require the management of a huge amount of heterogeneous georeferenced data-among others metocean,geophysical,geotechnical,and environmental,which need a Data Model,data visualization and...Offshore engineering projects require the management of a huge amount of heterogeneous georeferenced data-among others metocean,geophysical,geotechnical,and environmental,which need a Data Model,data visualization and data analytics features on a common geographic basis.A Digital Data Platform(DDP)has been developed on a GIS ambient with the aim to speed up the engineering design process(i.e.minimization of routine operations),and also prevent misalignment of the data originating from different sources from Owner to Suppliers and any potential loss of information.The proposed GIS architecture is composed by two main components:i)the Data Model geodatabase,and ii)the GIS-Model Toolbar add-in.The proposed development represents a step forward on the definition of a common specification and dictionary for offshore project execution overcoming the current bottlenecking and inefficiency on the design phases between the project owner and the engineering contractor.The paper illustrates“what”and“how”,and in particular:i)the geodatabase and Data Model framework,ii)the required parameters to be organized and stored for offshore engineering design,and iii)the widgets implementation(i.e.GIS-based tools).Its application on a case study project with practical examples is presented.展开更多
A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat...A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat-form suitable for the Jining No.3 coal mine is presented. This network is an information superhighway intended to inte-grate all existing and new automation subsystems. Its standard interface can be used with future subsystems. The net-work,data structure and management decision-making all employ this uniform hardware and software. This effectively avoids the problems of system and information islands seen in traditional mine-automation systems. The construction of the network provides a stable foundation for digital communication in the Jining No.3 coal mine.展开更多
Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logi...Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.展开更多
This paper introduces the high-speed electrical multiple unit （EMO） life cycle, including the design, manufacturing, testing, and maintenance stages. It also presents the train control and monitoring system （TCMS）...This paper introduces the high-speed electrical multiple unit （EMO） life cycle, including the design, manufacturing, testing, and maintenance stages. It also presents the train control and monitoring system （TCMS） software development platform, the TCMS testing and verification bench, the EMU driving simulation platform, and the EMU remote data transmittal and maintenance platform. All these platforms and benches combined together make up the EMU life cycle cost （LCC） system. Each platform facilitates EMU LCC management and is an important part of the system.展开更多
文摘The continuing expansion of connected and electro-mobility products and services has led to their ability to rapidly generate very large amounts of data,leading to a demand for effective data management solutions.This is further catalysed through the need for society to make informed policies and decisions that can properly support their emerging growth.While data systems and platforms exist,they are often proprietary,being only compatible to the products that they are designed for.Given the products and services generate energy and spatial-temporal data that can often correlate,a lack of interoperability between these systems would impede decision making,as data from each system must be considered independently.By studying currently available data platforms and frameworks,this paper weighs the problems that these products address,and identifies necessary gaps for a more cohesive platform to exist.This is performed through a top-down approach,whereby broader vehicle-toeverything approaches are first studied,before moving to the components that could comprise a data platform to integrate and ingest these various data feeds.Finally,potential design considerations for a data platform is presented,along with examples of application bene.
基金supported by the National Key R&D Program of China(No.2022YFB3103401)the National Natural Science Foundation of China(No.62172317,U23B2024)
文摘Currently, big data platforms are widely applied across various industries. These platforms are characterized by large scale, diverse forms, high update frequency, and rapid data flow, making it challenging to directly apply existing risk quantification methods to them. Additionally, the composition of big data platforms varies among enterprises due to factors such as industry, economic capability, and technical proficiency. To address this, we first developed a risk quantification assessment process tailored to different types of big data platforms, taking into account relevant laws, regulations, and standards. Subsequently,we developed RiskTree, a risk quantification system for big data platforms, which supports automated detection of configuration files, traffic, and vulnerabilities. For situations where automated detection is not feasible or permitted, we provide a customized questionnaire system to collect assets and data processing procedures. We utilize a knowledge graph(KG)to integrate and analyze the collected data. Finally, we apply a random forest algorithm to compute risk index weights, risk values, and risk levels, enabling the quantification of risks on big data platforms. To validate the proposed process, we conducted experiments on an educational big data platform. The results demonstrate that the risk index system presented in this paper objectively and comprehensively reflects the risks faced by big data platforms. Furthermore, the proposed risk assessment process not only effectively identifies and quantifies risks but also provides highly interpretable evaluation results.
基金supported by the Scientific Research Foundation of Xinhua College,Ningxia University,ChinaProject name:Preliminary Exploration of Ningxia Solar Photovoltaic Industry Intelligent Big Data Platform Construction Based on NB-IoT(Project No.23XHKY07).
文摘As China’s first new energy comprehensive demonstration zone,Ningxia’s solar photovoltaic(PV)industry has developed rapidly,but it still faces shortcomings in terms of intelligence and digitalization.This study focuses on the application and construction of an intelligent big data platform based on Narrowband Internet of Things(NB-IoT)technology within Ningxia’s solar PV industry.It explores the application trends of digital technology in the energy sector,particularly in the PV industry under the backdrop of energy reform,analyzes the technological development status of the smart energy field both domestically and internationally,and details the research methods and design components of the platform(including the photovoltaic base data platform,outdoor mobile application,remote data system,and back-office management system).The study discusses the opportunities and challenges Ningxia’s PV industry faces and proposes a construction pathway.It provides a theoretical foundation and technical support for the digital transformation of Ningxia’s PV industry,facilitating industrial upgrading and sustainable development.Although the current research is limited to the proposed design scheme,it establishes a basis for future empirical research and platform development.
文摘Pelvic floor dysfunction(PFD),including conditions such as stress urinary incontinence,pelvic organ prolapse,and fecal incontinence,significantly affects women's quality of life and their physical and mental health.With advancement of digital medicine,the systematic collection of data and the high-quality development of database platforms have increasingly become central pillars of PFD research and management.We systematically review the developmental stages of PFDrelated databases.We then conduct a comparative analysis of representative international and domestic platforms,examining key aspects including organizational structures and construction models,data sources and integration strategies,core functionalities,data quality control and standardization,data security and access management,and research applications.Finally,based on the current status of PFD database development both globally and in China,we offer recommendations to strengthen data infrastructure and guide future directions.The findings may serve as a valuable reference for the optimization of PFD databases worldwide.
文摘5G-R is the main type of next-generation mobile communication system for railways,offering highly reliable broadband data transmission services for intelligent railway operations.In the light of meeting the bearing demands of the 5G-R network,a comprehensive data transmission platform is proposed.This platform enables unified accession for various data service systems and applies Software Defined Network(SDN)technology for dynamic routing selection and high-effective data forwarding.Based on shared key lightweight access authentication technology,two-way identity authentication is performed for mobile terminals and network-side devices,ensuring the legitimacy verification of heterogeneous terminals within the application domain.
文摘With the acceleration of intelligent transformation of energy system,the monitoring of equipment operation status and optimization of production process in thermal power plants face the challenge of multi-source heterogeneous data integration.In view of the heterogeneous characteristics of physical sensor data,including temperature,vibration and pressure that generated by boilers,steam turbines and other key equipment and real-time working condition data of SCADA system,this paper proposes a multi-source heterogeneous data fusion and analysis platform for thermal power plants based on edge computing and deep learning.By constructing a multi-level fusion architecture,the platform adopts dynamic weight allocation strategy and 5D digital twin model to realize the collaborative analysis of physical sensor data,simulation calculation results and expert knowledge.The data fusion module combines Kalman filter,wavelet transform and Bayesian estimation method to solve the problem of data time series alignment and dimension difference.Simulation results show that the data fusion accuracy can be improved to more than 98%,and the calculation delay can be controlled within 500 ms.The data analysis module integrates Dymola simulation model and AERMOD pollutant diffusion model,supports the cascade analysis of boiler combustion efficiency prediction and flue gas emission monitoring,system response time is less than 2 seconds,and data consistency verification accuracy reaches 99.5%.
文摘In view of the problems such as frequent fluctuation of garlic price, lack ofefficient forecasting means and difficulty in realizing the steady development of garlicindustry, combined with the current situation of garlic industry and the collected datainformation. Taking Big Data platform of garlic industry chain as the core, using themethods of correlation analysis, smoothness test, co-integration test, and Grangercausality test, this paper analyzes the correlation, dynamic, and causality between garlicprice and young garlic shoot price. According to the current situation of garlic industry,the garlic industry service based on Big Data is put forward. It is concluded that there is apositive correlation between garlic price and young garlic shoot price, and there is a longtermstable dynamic equilibrium relationship between young garlic shoot price and garlicprice fluctuation, and young garlic shoot price can affect garlic price. Finally, it isproposed to strengthen the infrastructure construction of garlic Big Data, increase thetechnological innovation and application of garlic Big Data technology, and promote thesafety and security ability of the whole industry to promote the development of garlicindustry.
文摘This paper makes astudy on the interactive digital gener-alization,where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure,which are done by human andcomputer,respectively.And an inter-active map generalization environmentfor large scale topographic map is thendesigned and realized.This researchfocuses on:①the significance of re-searching an interactive map generali-zation environment,②the features oflarge scale topographic map and inter-active map generalization,③the con-struction of map generalization-orien-ted database platform.
基金supported by the Incubation Foundation for Special Disciplines of National Science Foundation of China (NSFC) (grant number: J0630966)Chinese Research Network on Special Environment and Disaster (CRENSED) of Ministry of Science and Technology of the People’s Republic of China (grant number:1Z2005DKA10600)the Knowledge Innovation Important Program of Chinese Academy of Sciences (Grant Number:NF105-SDB-1-21)
文摘The Data Platform of Resource and Environment—whose data mainly come from field observation stations,spatial observations,and internet service institutions—is the base of data analysis and model simulation in geoscience research in China.Among this integrated data platform,the tasks of the data platform of field observation stations are principally data collection,management,assimilation,and share service.Taking into consideration the distributing characteristics of the data sources and the service objects,the authors formulated the framework of the field observation stations' data platform based on the grid technology and designed its operating processes.The authors have further defined and analyzed the key functions and implementing techniques for each module.In a Linux operating system,validation tests for the data platform's function on data replication,data synchronization,and unified data service have been conducted under an environment that of the simulating field stations.
文摘The calculation results of the rolling force and torque model based on Orowan's differential equation numerical solution method do not fit with the industrial measurements very well.In particular,a quite large deviation on the torque model was found.On the basis of analyzing the shortcomings of the existing method,an improved rolling force and torque model algorithm aided by the Process Integrated Data Application System platform is proposed.Accordingly,the calculation accuracy of the rolling torque model is improved.The improved models are verified by 1711136 records of a data platform.The improved models are also based on Orowan's differential equation.Two coefficients,namely,friction factor and forward slip,are recognized as the crucial factors to be determined from industrial measurements to improve the accuracy.Therefore,the proposed method is a hybrid method that can be used to deeply understand the rolling process and improve the model's accuracy by combining traditional plastic mechanics and data-driving global optimization algorithms.This paper proposes a new approach to studying theoretical rolling deformation models powered by the industrial data platform.
文摘To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.
基金National Key Research and Development Program of China(2021ZD0113704).
文摘In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning method.We demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model structure.However,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial obstacle.This issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data security.To address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.
文摘Remote data monitoring system which adopts virtual instrument usually applies data sharing, acquisition and remote transmission technology via internet. It is able to finish concurrent data acquisition and processing for multi-user and multi-task and also build a personalized virtual testing environment for more people but with fewer instruments. In this paper, we＇ 11 elaborate on the design and implementation of information sharing platform through a typical example of how to build multi-user concurrent virtual testing environment based on the virtnal software LabVIEW.
文摘Objective To introduce the relevant big data platforms of FDA regulatory sciences and to provide reference for the construction of big data platform for China’s regulatory science under the“14th five-year plan”to deepen the reform of medical and health system.Methods A comparative analysis was made on China’s big data for regulatory science after studying the development process,operation mode,practical significance and characteristics of the big data platform for FDA regulatory science,which would help China to establish a perfect big database.Results and Conclusion The construction of big data platform for China’s regulatory science is not comprehensive compared with that in the United States.It is necessary to build data platforms in line with China’s national conditions through efforts in law,talents,standards,and other aspects.
基金the Sichuan Science and Technology Program(2021JDRC0077)the Sichuan Province’s Key Research and Development Plan.“Distributed Secure StorageTechnology for Massive Sensitive Data”Project(2020YFG0298)Applied Basic Research Project of Sichuan Province(No.2018JY0370).
文摘Big data cloud platforms provide users with on-demand configurable computing,storage resources to users,thus involving a large amount of user data.However,most of the data is processed and stored in plaintext,resulting in data leakage.At the same time,simple encrypted storage ensures the confidentiality of the cloud data,but has the following problems:if the encrypted data is downloaded to the client and then decrypted,the search efficiency will be low.If the encrypted data is decrypted and searched on the server side,the security will be reduced.Data availability is finally reduced,and indiscriminate protection measures make the risk of data leakage uncontrollable.To solve the problems,based on searchable encryption and key derivation,a cipher search system is designed in this paper considering both data security and availability,and the use of a search encryption algorithm that supports dynamic update is listed.Moreover,the system structure has the advantage of adapting different searchable encryption algorithm.In particular,a user-centered key derivation mechanism is designed to realize file-level fine-grained encryption.Finally,extensive experiment and analysis show that the scheme greatly improves the data security of big data platform.
文摘Offshore engineering projects require the management of a huge amount of heterogeneous georeferenced data-among others metocean,geophysical,geotechnical,and environmental,which need a Data Model,data visualization and data analytics features on a common geographic basis.A Digital Data Platform(DDP)has been developed on a GIS ambient with the aim to speed up the engineering design process(i.e.minimization of routine operations),and also prevent misalignment of the data originating from different sources from Owner to Suppliers and any potential loss of information.The proposed GIS architecture is composed by two main components:i)the Data Model geodatabase,and ii)the GIS-Model Toolbar add-in.The proposed development represents a step forward on the definition of a common specification and dictionary for offshore project execution overcoming the current bottlenecking and inefficiency on the design phases between the project owner and the engineering contractor.The paper illustrates“what”and“how”,and in particular:i)the geodatabase and Data Model framework,ii)the required parameters to be organized and stored for offshore engineering design,and iii)the widgets implementation(i.e.GIS-based tools).Its application on a case study project with practical examples is presented.
基金Project 50574094 supported by the National Natural Science Foundation of China
文摘A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat-form suitable for the Jining No.3 coal mine is presented. This network is an information superhighway intended to inte-grate all existing and new automation subsystems. Its standard interface can be used with future subsystems. The net-work,data structure and management decision-making all employ this uniform hardware and software. This effectively avoids the problems of system and information islands seen in traditional mine-automation systems. The construction of the network provides a stable foundation for digital communication in the Jining No.3 coal mine.
基金supported in part by National Key Research and Development Program under Grant No. 2016YFC0803206China Postdoctoral Science Foundation under Grant No.2016M600972
文摘Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.
文摘This paper introduces the high-speed electrical multiple unit （EMO） life cycle, including the design, manufacturing, testing, and maintenance stages. It also presents the train control and monitoring system （TCMS） software development platform, the TCMS testing and verification bench, the EMU driving simulation platform, and the EMU remote data transmittal and maintenance platform. All these platforms and benches combined together make up the EMU life cycle cost （LCC） system. Each platform facilitates EMU LCC management and is an important part of the system.
