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
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
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
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
Northeast Asia is a key area for Earth system studies, global change frontier science research and regional sustainable development research. It has a complex ecological environment, a variety of climatic zones and ty...Northeast Asia is a key area for Earth system studies, global change frontier science research and regional sustainable development research. It has a complex ecological environment, a variety of climatic zones and typical human-Earth relationships. This paper outlines a data resources integration system fulfilling the data accumulation and management requirements of the Northeast Asia Resources and Environment Scientific Expedition. The data resources integration system has three subsystems：（i） data resources collection and management standards and specifications system, （ii） data classification system and （iii） a data management and publication software platform. The data resources collection and management standard and specification system has 23 specifications,divided into three types. They are： （i） data collection and processing specification type,（ii） data analysis and archiving specification and （iii） data management and sharing specification. The data resources classification system has four classes, 25 sub classes and 128 data elements. The data management and publication software platform has five function models：（i） data catalogue search model, （ii） metadata management model, （iii） data publication and virtualization model, （iv） data view model and （v） data download model. Based on the designed data integration system a prototype system has been developed and is supported by computer and Web GIS technologies. So far 144 datasets have been integrated into this data system. As more data are accumulated and integrated, it will play an important role in future scientific expedition data application and analysis.展开更多
China Unicorn, the largest WCDMA 3G operator in China, meets the requirements of the historical Mobile Internet Explosion, or the surging of Mobile Internet Traffic from mobile terminals. According to the internal sta...China Unicorn, the largest WCDMA 3G operator in China, meets the requirements of the historical Mobile Internet Explosion, or the surging of Mobile Internet Traffic from mobile terminals. According to the internal statistics of China Unicom, mobile user traffic has increased rapidly with a Compound Annual Growth Rate （CAGR） of 135%. Currently China Unicorn monthly stores more than 2 trillion records, data volume is over 525 TB, and the highest data volume has reached a peak of 5 PB. Since October 2009, China Unicom has been developing a home-brewed big data storage and analysis platform based on the open source Hadoop Distributed File System （HDFS） as it has a long-term strategy to make full use of this Big Data. All Mobile Internet Traffic is well served using this big data platform. Currently, the writing speed has reached 1 390 000 records per second, and the record retrieval time in the table that contains trillions of records is less than 100 ms. To take advantage of this opportunity to be a Big Data Operator, China Unicom has developed new functions and has multiple innovations to solve space and time constraint challenges presented in data processing. In this paper, we will introduce our big data platform in detail. Based on this big data platform, China Unicom is building an industry ecosystem based on Mobile Internet Big Data, and considers that a telecom operator centric ecosystem can be formed that is critical to reach prosperity in the modern communications business.展开更多
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
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
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
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
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
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
"Data Structure and Algorithm",which is an important major subject in computer science,has a lot of problems in teaching activity.This paper introduces and analyzes the situation and problems in this course ..."Data Structure and Algorithm",which is an important major subject in computer science,has a lot of problems in teaching activity.This paper introduces and analyzes the situation and problems in this course study.A "programming factory" method is then brought out which is indeed a practice-oriented platform of the teachingstudy process.Good results are obtained by this creative method.展开更多
Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a sof...Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3];however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.展开更多
Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespre...Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.展开更多
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.
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.
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%.
基金National Scientific & Technology Basic Work Program of China(2007FY110300,2011FY110400)National Nature Science Foundation of China(40801180)
文摘Northeast Asia is a key area for Earth system studies, global change frontier science research and regional sustainable development research. It has a complex ecological environment, a variety of climatic zones and typical human-Earth relationships. This paper outlines a data resources integration system fulfilling the data accumulation and management requirements of the Northeast Asia Resources and Environment Scientific Expedition. The data resources integration system has three subsystems：（i） data resources collection and management standards and specifications system, （ii） data classification system and （iii） a data management and publication software platform. The data resources collection and management standard and specification system has 23 specifications,divided into three types. They are： （i） data collection and processing specification type,（ii） data analysis and archiving specification and （iii） data management and sharing specification. The data resources classification system has four classes, 25 sub classes and 128 data elements. The data management and publication software platform has five function models：（i） data catalogue search model, （ii） metadata management model, （iii） data publication and virtualization model, （iv） data view model and （v） data download model. Based on the designed data integration system a prototype system has been developed and is supported by computer and Web GIS technologies. So far 144 datasets have been integrated into this data system. As more data are accumulated and integrated, it will play an important role in future scientific expedition data application and analysis.
基金supported in part by the National Key Basic Research and Development(973)Program of China(Nos.2013CB228206 and 2012CB315801)the National Natural Science Foundation of China(Nos.61233016 and 61140320)supported by the Intel Research Council under the title of"Security Vulnerability Analysis Based on Cloud Platform with Intel IA Architecture"
文摘China Unicorn, the largest WCDMA 3G operator in China, meets the requirements of the historical Mobile Internet Explosion, or the surging of Mobile Internet Traffic from mobile terminals. According to the internal statistics of China Unicom, mobile user traffic has increased rapidly with a Compound Annual Growth Rate （CAGR） of 135%. Currently China Unicorn monthly stores more than 2 trillion records, data volume is over 525 TB, and the highest data volume has reached a peak of 5 PB. Since October 2009, China Unicom has been developing a home-brewed big data storage and analysis platform based on the open source Hadoop Distributed File System （HDFS） as it has a long-term strategy to make full use of this Big Data. All Mobile Internet Traffic is well served using this big data platform. Currently, the writing speed has reached 1 390 000 records per second, and the record retrieval time in the table that contains trillions of records is less than 100 ms. To take advantage of this opportunity to be a Big Data Operator, China Unicom has developed new functions and has multiple innovations to solve space and time constraint challenges presented in data processing. In this paper, we will introduce our big data platform in detail. Based on this big data platform, China Unicom is building an industry ecosystem based on Mobile Internet Big Data, and considers that a telecom operator centric ecosystem can be formed that is critical to reach prosperity in the modern communications business.
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.
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 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.
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.
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.
基金supported by NSF B55101680,NTIF B2090571,B2110140,SCUT x2rjD2116860,Y1080170,Y1090160,Y1100030,Y1100050,Y1110020 and S1010561121,G101056137
文摘"Data Structure and Algorithm",which is an important major subject in computer science,has a lot of problems in teaching activity.This paper introduces and analyzes the situation and problems in this course study.A "programming factory" method is then brought out which is indeed a practice-oriented platform of the teachingstudy process.Good results are obtained by this creative method.
文摘Various code development platforms, such as the ATHENA Framework [1] of the ATLAS [2] experiment encounter lengthy compilation/linking times. To augment this situation, the IRIS Development Platform was built as a software development framework acting as compiler, cross-project linker and data fetcher, which allow hot-swaps in order to compare various versions of software under test. The flexibility fostered by IRIS allowed modular exchange of software libraries among developers, making it a powerful development tool. The IRIS platform used input data ROOT-ntuples [3];however a new data model is sought, in line with the facilities offered by IRIS. The schematic of a possible new data structuring—as a user implemented object oriented data base, is presented.
文摘Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.
