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
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
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
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
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
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
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
面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题,在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上,通过组织多学科的协同技术攻关,突破了作物表型组...面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题,在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上,通过组织多学科的协同技术攻关,突破了作物表型组大数据高通量获取和智能化解析中的关键技术难题,设计了具有自主知识产权的轻小敏捷型多传感器阵列、通用化成像单元和适用于多生境的固定式、移动式高通量表型平台装备,以及配套算法和软件平台,构建了农作物表型组大数据工厂成套技术装备体系。该体系由大田和设施作物高通量自主作业表型平台、室内器官和显微表型平台、大田和设施环境自动化种植管控设备、作物模型系统、数字孪生智慧管控平台和大数据计算服务中心等构成,可实现多生境、自动化、高通量、高效率、高精度的多源作物表型-环境数据协同采集,涵盖农作物群体、个体、器官和显微多重尺度,能够重建农林作物的三维形态结构并精准解析株型、产品、品质、抗性等表型组指标,是发展数字育种和智慧栽培的新一代信息化基础设施。农作物表型组大数据工厂技术装备体系创新了作物表型组大数据的产生、处理和服务模式,可为作物表型组理论技术的发展、基于AI for Science的平台化科研和工厂化的作物种质资源表型鉴定等提供体系化的技术装备支撑。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.
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.
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.
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.
文摘面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题,在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上,通过组织多学科的协同技术攻关,突破了作物表型组大数据高通量获取和智能化解析中的关键技术难题,设计了具有自主知识产权的轻小敏捷型多传感器阵列、通用化成像单元和适用于多生境的固定式、移动式高通量表型平台装备,以及配套算法和软件平台,构建了农作物表型组大数据工厂成套技术装备体系。该体系由大田和设施作物高通量自主作业表型平台、室内器官和显微表型平台、大田和设施环境自动化种植管控设备、作物模型系统、数字孪生智慧管控平台和大数据计算服务中心等构成,可实现多生境、自动化、高通量、高效率、高精度的多源作物表型-环境数据协同采集,涵盖农作物群体、个体、器官和显微多重尺度,能够重建农林作物的三维形态结构并精准解析株型、产品、品质、抗性等表型组指标,是发展数字育种和智慧栽培的新一代信息化基础设施。农作物表型组大数据工厂技术装备体系创新了作物表型组大数据的产生、处理和服务模式,可为作物表型组理论技术的发展、基于AI for Science的平台化科研和工厂化的作物种质资源表型鉴定等提供体系化的技术装备支撑。
