scholarly journals Construction of New Intelligent Teaching Scene Based on Multimodal Wireless Sensing Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Lin Zhou
Keyword(s):  
Recognition Performance ◽  
Wireless Sensing ◽  
Practical Application ◽  
User Interest ◽  
Technology Application ◽  
Sensing Technology ◽  
Wireless Signal ◽  
Actual Environment ◽  
User Interest Model ◽  
Information Technology Application

With the continuous development of computer technology and the gradual popularization of information technology application, the construction of intelligent teaching scene based on wireless sensing technology plays a more and more important role in modern information education. Taking a primary school as an example, this paper introduces multimodal wireless sensing technology into the construction of intelligent teaching system. The purpose of this paper is to explore the construction of a new teaching scene. Firstly, this paper deeply analyzes the sensing mechanism of wireless signal and optimizes the sensing mode, deployment structure, and signal processing in practical application, so that the system can run more effectively in the actual environment. Then, based on multimodal wireless sensing technology, this paper designs and optimizes the basic architecture and functions of intelligent teaching scene. The results show that combining the characteristic information of each mode to get the information conducive to identity confirmation, which can get better recognition performance and improve the accuracy. Combining the information of multiple modes can greatly improve the recognition performance. The user interest model combined with dynamic and static is used to optimize the system recommended resources, so that students can obtain high-quality and highly matched learning resources more quickly and accurately, so as to improve students’ learning efficiency in resource acquisition.

MANAGING INFORMATION TECHNOLOGY APPLICATION IN TEACHING AT HIGH SCHOOLS IN VINH YEN CITY, VINH PHUC PROVINCE MEETS INDUSTRIAL REVOLUTION 4.0

2018 ◽  
Author(s):  
Vu Kha Thap
Keyword(s):  
Information Technology ◽  
Social Life ◽  
Industrial Revolution ◽  
Strong Impact ◽  
Surface Strength ◽  
Technology Application ◽  
Management Measures ◽  
The World ◽  
The Status ◽  
Information Technology Application

Entering the XXI century and especially in the period of the industrial revolution has entered the era of IT with the knowledge economy in the trend of globalization. The 4.0 mankind development of ICT, especially the Internet has had a strong impact and make changes to all activities profound social life of every country in the world. Through surveys in six high School, interviewed 85 managers and teachers on the status of the management of information technology application in teaching, author of the article used the SWOT method to distribute surface strength, weaknesses, opportunities and challenges from which to export 7 management measures consistent with reality. 7 measures have been conducting trials and the results showed that 07 measures of necessary and feasible.

An Energy-efficient Street Lighting Approach Based on Traffic Parameters Measured by Wireless Sensing Technology

2021 ◽  
pp. 1-1
Author(s):  
Yuxi Jiang ◽  
Yinghong Shuai ◽  
Xiaoliang He ◽  
Xing Wen ◽  
Liangliang Lou
Keyword(s):  
Energy Efficient ◽  
Wireless Sensing ◽  
Street Lighting ◽  
Sensing Technology

scholarly journals A novel user-interest model based on mixed measure

2017 ◽  
Vol 887 ◽  
pp. 012061
Author(s):  
Junkai Yi ◽  
Yacong Zhang ◽  
Mingyong Yin ◽  
Xianghui Zhao
Keyword(s):  
User Interest ◽  
Model Based ◽  
Mixed Measure ◽  
Interest Model ◽  
User Interest Model

A Webpage Ranking Algorithm Based on Collaborative Recommendation

2013 ◽  
Vol 765-767 ◽  
pp. 998-1002
Author(s):  
Shao Xuan Zhang ◽  
Tian Liu
Keyword(s):  
Sorting Algorithm ◽  
User Interest ◽  
Recommendation Algorithm ◽  
Search Results ◽  
Collaborative Recommendation ◽  
Interest Model ◽  
Sorting Efficiency ◽  
User Interest Model ◽  
Relevant Calculation ◽  
Personalized Ranking

In view of the present personalized ranking of search results user interest model construction difficult, relevant calculation imprecise problems, proposes a combination of user interest model and collaborative recommendation algorithm for personalized ranking method. The method from the user search history, including the submit query, click the relevant webpage information to train users interest model, then using collaborative recommendation algorithm to obtain with common interests and neighbor users, on the basis of these neighbors on the webpage and webpage recommendation level associated with the users to sort the search results. Experimental results show that: the algorithm the average minimum precision than general sorting algorithm was increased by about 0.1, with an increase in the number of neighbors of the user, minimum accuracy increased. Compared with other ranking algorithms, using collaborative recommendation algorithm is helpful for improving webpage with the user interest relevance precision, thereby improving the sorting efficiency, help to improve the search experience of the user.

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