Fishing the Electronic River: Disruptive Technologies, the Unlibrary, and the Ecology of Information

Author(s):  
Dennis Dillon
2018 ◽  
Vol 20 (6) ◽  
pp. 64 ◽  
Author(s):  
Yongjie Li ◽  
Juntao Yang ◽  
Jian Du

2018 ◽  
Vol 20 (6) ◽  
pp. 57 ◽  
Author(s):  
Wang Dong ◽  
Chen Yuanquan ◽  
Li Daoliang ◽  
Zhu Wanbin ◽  
Tan Weiming ◽  
...  

2020 ◽  
Vol 26 (2) ◽  
pp. 288-293
Author(s):  
Codrin-Leonard Herţanu

AbstractOur contemporary world is on the verge of crucial changes of an unparalleled pace. The ‘technological changeover’ is the new paradigm caused by the unprecedented evolution of the disruptive technologies. The present world has the tendency to evolve at least exponential, therefore future educational environment is fairly different than its present layout. An entire array of nowadays studies widely recognizes that the progress of the disruptive technologies will pose a meaningful impact over the educational system evolution. Among the most spectacular technologies with disruptive features we should encounter Artificial Intelligence, Blockchain Technology, Cloud Computing, and the like. In an era of technological disruption the education is seen as the new currency. With the help of Artificial Intelligence, for instance, the education system could track how people learn from kindergarten to retirement. Besides, the technology domain will move the centre of gravity from the institutional area to that of the education’s beneficiaries, as we might expect that they will recruit and employ the needed teacher staff, not the institutions. Moreover, the education’s recipients will be the main creators of tomorrow’s professions and within their community the overarching events will happen and the main decisions will be taken in the educational domain.


Author(s):  
Da-Yin Liao

Contemporary 300mm semiconductor manufacturing systems have highly automated and digitalized cyber-physical integration. They suffer from the profound problems of integrating large, centralized legacy systems with small islands of automation. With the recent advances in disruptive technologies, semiconductor manufacturing has faced dramatic pressures to reengineer its automation and computer integrated systems. This paper proposes a Distributed-Ledger, Edge-Computing Architecture (DLECA) for automation and computer integration in semiconductor manufacturing. Based on distributed ledger and edge computing technologies, DLECA establishes a decentralized software framework where manufacturing data are stored in distributed ledgers and processed locally by executing smart contracts at the edge nodes. We adopt an important topic of automation and computer integration for semiconductor research &development (R&D) operations as the study vehicle to illustrate the operational structure and functionality, applications, and feasibility of the proposed DLECA software framework.


2019 ◽  
Vol 56 (Special) ◽  
pp. 143-155
Author(s):  
SD Mohapatra ◽  
R Tripathi ◽  
Anjani Kumar ◽  
Suchismita Kar ◽  
Minati Mohapatra ◽  
...  

The insect problem is accentuated in intensive rice cropping where the insects occur throughout the year in overlapping generations. Over 800 insect species damaging rice in one way or another, although the majority of them do very little damage. In India, about a dozen of insect species are of major importance but the economic damage caused by these species varies greatly from field to field and from year to year. Insect pests cause about 10-15 per cent yield losses. Farmers lose an estimated average of 37% of their rice crop to insect pests and diseases every year. This review focuses on precision farming tools being used in rice pest and diseases management viz., forecasting model for real-time pest-advisory services, hyper-spectral remote sensing in pest damage assessment, computer-based decision support system, disruptive technologies (mobile apps).


Author(s):  
Dhruvil Shah ◽  
Devarsh Patel ◽  
Jainish Adesara ◽  
Pruthvi Hingu ◽  
Manan Shah

AbstractAlthough the education sector is improving more quickly than ever with the help of advancing technologies, there are still many areas yet to be discovered, and there will always be room for further enhancements. Two of the most disruptive technologies, machine learning (ML) and blockchain, have helped replace conventional approaches used in the education sector with highly technical and effective methods. In this study, a system is proposed that combines these two radiant technologies and helps resolve problems such as forgeries of educational records and fake degrees. The idea here is that if these technologies can be merged and a system can be developed that uses blockchain to store student data and ML to accurately predict the future job roles for students after graduation, the problems of further counterfeiting and insecurity in the student achievements can be avoided. Further, ML models will be used to train and predict valid data. This system will provide the university with an official decentralized database of student records who have graduated from there. In addition, this system provides employers with a platform where the educational records of the employees can be verified. Students can share their educational information in their e-portfolios on platforms such as LinkedIn, which is a platform for managing professional profiles. This allows students, companies, and other industries to find approval for student data more easily.


Engineering ◽  
2021 ◽  
Author(s):  
Yueguang Lyu ◽  
Yaxin Zhang ◽  
Yang Liu ◽  
Weifang Chen ◽  
Xilin Zhang ◽  
...  

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