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产业经济 2024年第1期

作者：贺俊庞尧

每一轮通用技术革命都会引发产业发展范式的深刻变革，而那些能够更快适应产业发展新范式并进行有效制度供给的国家就能够引领科技革命和产业变革。数字技术的加速拓展将推动产品功能、生产技术、商业模式、消费形式的跨产业深度融合，... 详细信息

每一轮通用技术革命都会引发产业发展范式的深刻变革，而那些能够更快适应产业发展新范式并进行有效制度供给的国家就能够引领科技革命和产业变革。数字技术的加速拓展将推动产品功能、生产技术、商业模式、消费形式的跨产业深度融合，塑造产业融合发展新范式。在此背景下，我国传统面向边界清晰的特定产业所形成的产业政策体系、创新体系和监管体系，如特定产业发展规划、特定部门管理机构和特定行业研发机构等制度安排，已经不能完全适应新产业发展范式，甚至成为生产资源、知识要素和资本跨产业流动组合的障碍，亟须进行改革和调整。

关键词：技术革命数字技术产业融合政策体系 technological revolution digital technology industrial integration policy system

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Research on the Improvement and Innovation Paths of Teaching Quality in Private Universities in Zhejiang Province in the digital Era

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Journal of Contemporary Educational Research 2024年第3期8卷 227-231页

作者： Xiangjiang Li College of digital technology and Engineering Ningbo University of Finance and EconomicsNingbo 315175Zhejiang ProvinceChina

In the digital era,the education and teaching of private undergraduate universities in China are undergoing innovative *** article uses the literature review method to conduct a survey and research on the quality of teaching resources,teaching platforms,and literature reserves,and proposes a series of strategies and innovative paths to improve the teaching quality of private undergraduate *** research results show that the rational use of digital technology can improve the quality of education and teaching,and achieve innovative development in education and *** research results have certain theoretical value and guiding significance for the teaching reform of private undergraduate universities under the background of digital teaching.

关键词： Teaching quality digital technology Undergraduate universities Innovation path

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Education and the Fourth Industrial Revolution:Lessons from COVID-19

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Computers, Materials & Continua 2022年第1期70卷 951-962页

作者： Hussien Mohamad Alakrash Norizan Abdul Razak Faculty of Social Sciences and Humanities School of Language Studies and LinguisticsUniversiti KebangsaanMalaysia

The COVID-19 pandemic has prompted educators to rethink educational practices,especially with regard to *** COVID-19 pandemic is a huge challenge to education systems around the *** Viewpoint offers guidance to teachers,institutional heads,and officials on addressing the *** study investigated technology use in teaching during the COVID-19 lockdown inMalaysia,focusing on technology-based teaching methods,modifications necessitated by this new teaching style,and challenges teachers faced when using *** purposive sampling,a qualitative study was undertaken with a sample of 10 English language teachers from Arabic schools in *** results indicated that a digital leap occurred in education during the COVID-19 lockdown because teachers had to quickly adapt to a more technology-based teaching *** challenges teachers faced included managing virtual classes,ensuring reliable Internet connections,overcoming a lack of preparedness and low digital competence,and dealing with students’mental *** changes in teaching methods have created new roles for teachers while also increasing their acceptance of e-learning and remote *** contribution of this research is to provide a holistic picture of remote education activities during the pandemic period to establish a linkage between the online teaching-learning process during the COVID-19 outbreak as to ensure the resumption of teaching-learning education as a normal course of procedure in the education *** the human suffering brought by the pandemic,the new norms of education during COVID-19 generally have some pockets of excellence to drive the education into the Fourth Industrial Revolution.

关键词： COVID-19 digital technology English education fourth industrial revolution Education 4.0

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Methods and applications for Artificial Intelligence, Big Data, Internet of Things, and Blockchain in smart energy management

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能源与人工智能(英文) 2023年第1期11卷 161-178页

作者： Joey Li Munur Sacit Herdem Jatin Nathwani John Z.Wen Department of Mechanical&Mechatronics Engineering University of Waterloo200 University Avenue WestWaterlooN2L 3G1ONCanada Waterloo Institute for Sustainable Energy EVO Unit 100200 University Avenue WestWaterlooON CanadaN2L 3G1 Department of Management Science University of Waterloo200 University Avenue WestWaterlooN2L 3G1ONCanada Department of Mechanical Engineering Adiyaman University02040AdiyamanTurkey

Information technologies involving artificial Intelligence, big data, Internet of Things devices and blockchain have been developed and implemented in many engineering fields worldwide. Existing review articles focus on developments and characteristics of individual topics and the associated deployment in the energy sector. These technologies, all based on communication, information, and data analysis, are naturally coherent and integrable. This article reviews the literature and patents in four closely related fields and aims to provide a holistic view of how they are related and their integrability in relation to smart energy management strategies. Artificial intelligence models forecast energy use and load profiles as well as schedule resources to ensure reliable performance and effective utilization of energy resources. Training artificial intelligence models requires immense volumes of data. Utilizing big data systems and data mining enables the discovery of new functions and relationships, which determines the performance of artificial intelligence. Data mining also refines the information;thus, artificial intelligence is trained iteratively with more accurate data. Smart energy management can be further enhanced through advanced digital technologies like Internet of Things and blockchain. An Internet of Things platform containing edge, fog and cloud layers helps connect artificial intelligence to other hardware and software devices and systems. Furthermore, an Internet of Things platform efficiently transmits and stores data, improving access and availability to stakeholders for data mining. Emerging technologies such as blockchain and cryptocurrency facilitate energy trading and can be designed in the cloud layer of an Internet of Things platform to supplement data storage. Providing an efficient and seamless integration of artificial intelligence, big data, and advanced digital technologies will be an important factor in the emerging transition of the energ

关键词： Artificial Intelligence Big Data digital technology Smart grid IoT Blockchain

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Curriculum Development for FAIR Data Stewardship

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Data Intelligence 2022年第4期4卷 991-1012,1033页

作者： Francisca Oladipo Sakinat Folorunso Ezekiel Ogundepo Obinna Osigwe Akinyinka Tosin Akindele Directorate of Research InnovationsConsultancy and ExtensionKampala International University10102Uganda Virus Over Data Network(VODAN)-Africa and Asia Federal University Lokoja 260101Nigeria Department of Mathematical Sciences Olabisi Onabanjo UniversityP.M.B 2002Ago-IwoyeOgun State120005Nigeria Data Science Nigeria Lagos 105102Nigeria School of eLearning Projects Kampala International UniversityP.M.B 4000OgbomosoOyo stateNigeriaUganda

The FAIR Guidelines attempts to make digital data Findable, Accessible, Interoperable, and Reusable(FAIR). To prepare FAIR data, a new data science discipline known as data stewardship is emerging and, as the FAIR Guidelines gain more acceptance, an increase in the demand for data stewards is expected. Consequently, there is a need to develop curricula to foster professional skills in data stewardship through effective knowledge communication. There have been a number of initiatives aimed at bridging the gap in FAIR data management training through both formal and informal programmes. This article describes the experience of developing a digital initiative for FAIR data management training under the digital Innovations and Skills Hub(DISH) project. The FAIR Data Management course offers 6 short on-demand certificate modules over 12 weeks. The modules are divided into two sets: FAIR data and data science. The core subjects cover elementary topics in data science, regulatory frameworks, FAIR data management, intermediate to advanced topics in FAIR Data Point installation, and FAIR data in the management of healthcare and semantic data. Each week, participants are required to devote 7–8 hours of self-study to the modules, based on the resources provided. Once they have satisfied all requirements, students are certified as FAIR data scientists and qualified to serve as both FAIR data stewards and analysts. It is expected that in-depth and focused curricula development with diverse participants will build a core of FAIR data scientists for Data Competence Centres and encourage the rapid adoption of the FAIR Guidelines for research and development.

关键词： Data steward Data science FAIR Guidelines FAIR digital technology FDP installation FAIR Data Trains Semantic web Personal Health Train

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