Edition Visualization Technology Project

2021 ◽  
Vol 10 (2) ◽  
pp. 340-342
Author(s):  
Hannelore Segers
Keyword(s):  
Technology Project ◽  
Visualization Technology

Advanced visualization technology project (AVTP): an architecture for visualization using remote parallel/distributed computing

1995 ◽  
Author(s):  
Ernest A. Franke ◽  
Stephen D. Huffman ◽  
William M. Carter ◽  
Joseph P. Baumgartner ◽  
Dennis J. Wenzel
Keyword(s):  
Distributed Computing ◽  
Technology Project ◽  
Visualization Technology ◽  
Advanced Visualization

Risk Control Study Based on the Digital Recording Technology Industry Investment Projects in "Internet +"

2020 ◽  
Vol 14 ◽  
Author(s):  
Yan Zhou
Keyword(s):  
Venture Capital ◽  
Digital Technology ◽  
Risk Control ◽  
Investment Risk ◽  
Digital Recording ◽  
Project Investment ◽  
Recording Technology ◽  
Technology Project ◽  
Investment Evaluation ◽  
Risk Investment

Background: The reform and innovation of recording technology has resulted in recording becoming an exciting, developing project. Against the background of Internet +, traditional analogue technology has developed into digital recording technology, playing an important role in various fields. Venture capital in digital recording technology projects has also attracted attention from all circles. Objective: This paper aims to, by sorting out literature on venture capital, analyze the measurement method of project investment risk, and then, after analyzing the risk factors existing in the investment of digital recording technology under the “Internet +”, propose measures to control these risk factors. At the same time, taking CY company as an example, the investment risk prevention strategy of digital recording technology project is applied to the risk investment evaluation practice of CY company. Methods: This paper reviews and comments the literature on venture capital, and sorts out the evaluation methods of project investment risk. After studying the project investment risk of digital recording technology, this paper finds out the preventive strategies to deal with these risks, and applies them to risk investment evaluation of CY. This paper proposes investment suggestions basing on various factors, and makes an overall evaluation of the value of digital recording technology project, which hopefully will act as a reference for venture capital institutions when investing in digital recording technology in the future. Results: The countermeasures against investment risks in digital recording technology projects are: 1. Identification of countermeasures against investment risks in digital recording technology projects. 2. Encouragement and promotion of joint-stock cooperation and reduction of operational risks 3. Establishment and improvement of financial risk control. Conclusion: Digital technology, which is continuously improving, has penetrated recording technology. With mindful awareness of investment risks and careful investment in recording technology projects, digital technology can improve living standards while making the flexibility and form of recording work more artistic and enabling recording technology to reach new heights.

A Year 7 technology project

1993 ◽  
Vol 1993 (1) ◽  
pp. 28-29
Author(s):  
T. Duffill ◽  
D.A. Snashall
Keyword(s):  
Technology Project

Research on the university intelligent learning analysis system based on AI

2021 ◽  
pp. 1-10
Author(s):  
Meng Huang ◽  
Shuai Liu ◽  
Yahao Zhang ◽  
Kewei Cui ◽  
Yana Wen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Academic Performance ◽  
Clustering Algorithm ◽  
Back Propagation ◽  
Three Dimensional ◽  
Training Model ◽  
Future Trend ◽  
Artificial Intelligence Technology ◽  
Visualization Technology

The integration of Artificial Intelligence technology and school education had become a future trend, and became an important driving force for the development of education. With the advent of the era of big data, although the relationship between students’ learning status data was closer to nonlinear relationship, combined with the application analysis of artificial intelligence technology, it could be found that students’ living habits were closely related to their academic performance. In this paper, through the investigation and analysis of the living habits and learning conditions of more than 2000 students in the past 10 grades in Information College of Institute of Disaster Prevention, we used the hierarchical clustering algorithm to classify the nearly 180000 records collected, and used the big data visualization technology of Echarts + iView + GIS and the JavaScript development method to dynamically display the students’ life track and learning information based on the map, then apply Three Dimensional ArcGIS for JS API technology showed the network infrastructure of the campus. Finally, a training model was established based on the historical learning achievements, life trajectory, graduates’ salary, school infrastructure and other information combined with the artificial intelligence Back Propagation neural network algorithm. Through the analysis of the training resulted, it was found that the students’ academic performance was related to the reasonable laboratory study time, dormitory stay time, physical exercise time and social entertainment time. Finally, the system could intelligently predict students’ academic performance and give reasonable suggestions according to the established prediction model. The realization of this project could provide technical support for university educators.

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