scholarly journals Design of Double-effect Propulsion System for News Broadcast Based on Artificial Intelligence and Virtual Host Technology

2021 ◽  
Vol 2074 (1) ◽  
pp. 012096
Author(s):  
Yuanyuan You
Keyword(s):  
Artificial Intelligence ◽  
Sign Language ◽  
Double Effect ◽  
Propulsion System ◽  
Switching Function ◽  
Test Results ◽  
Channel Switching ◽  
Intelligent Algorithm ◽  
Artificial Intelligence Technology ◽  
Live Broadcast

Abstract A virtual host refers to a host who uses an avatar to submit contributions on a video website. The virtual host is a powerful combination of artificial intelligence technology and live broadcast. In recent years, virtual video hosts have sprung up on major video websites, and their popularity is growing rapidly. Virtual host technology has been applied to many areas of society. Based on this background, this article designs a news broadcast double-effect propulsion system based on artificial intelligence and virtual host technology. This article applies the virtual host technology to the field of news broadcasting, and realizes the double-effect advancement of virtual host technology and news broadcasting. The virtual host designed in this article mainly uses sign language to broadcast news, so this article first conducts a quick and brief knowledge of sign language, and then conducts a detailed analysis of the current research status of virtual host technology and artificial intelligence technology, and uses artificial intelligence. The technology realizes the motion control of the virtual host; then the intelligent algorithm is used to realize the superimposition and synthesis of videos, and a news broadcast double-effect propulsion system of artificial intelligence and virtual host technology is designed. Finally, this article carried out an experimental test on the system’s simultaneous broadcast function and channel switching function. The test results surface excluded subjective human factors. After the improvement, the system can achieve simultaneous broadcast and successful channel switching.

scholarly journals Image Search System Based on Machine Learning

2022 ◽  
Vol 2146 (1) ◽  
pp. 012026
Author(s):  
HongLin Wang
Keyword(s):  
Artificial Intelligence ◽  
Network Communication ◽  
Test Results ◽  
Search System ◽  
Communication Platform ◽  
Face To Face ◽  
Teacher Student ◽  
Artificial Intelligence Technology ◽  
And Performance

Abstract Since the 21st century, with the continuous maturity of network technology and its integration with the education field, traditional face-to-face communication has gradually expanded to the virtual network environment. In the online learning environment, students can use the online platform to communicate directly with teachers, no longer limited by time and region. The time and space breakthrough of teacher-student interaction has brought development opportunities for teachers to constantly contact students with a long-term management mechanism. Based on this situation, this article uses artificial intelligence technology to build a network communication platform. This article first analyzes the application status of artificial intelligence technology in the network communication platform, and then introduces the artificial intelligence technology applied in this article. Then, this article uses artificial intelligence technology to design a network communication platform, and test the function and performance of the platform. The test results show that the function of the system is very accurate and reliable, and the performance of the system is sufficient to support nearly 10,000 users at the same time.

scholarly journals Exploration of Artificial Intelligence Security in Multi Unmanned System Cooperation

2022 ◽  
Vol 2146 (1) ◽  
pp. 012021
Author(s):  
Shanshan Li ◽  
Liang Zhang ◽  
Zongpu Li
Keyword(s):  
Artificial Intelligence ◽  
Modern Science ◽  
Research Direction ◽  
Unmanned Systems ◽  
Test Results ◽  
Intelligent Algorithm ◽  
Multiple Uavs ◽  
Machine Interface ◽  
Unmanned System ◽  
Important Research Direction

Abstract In modern science and technology, artificial intelligence has become one of the most important and promising technologies in today’s society and plays a very important role in people’s life. In artificial intelligence, cooperation is a very important research direction, which includes the cooperation between sensors, coordinated man-machine interface and actuators on multiple UAVs. Therefore, based on the exploration of artificial intelligence security, this paper studies artificial intelligence in multi unmanned system cooperation. Firstly, this paper expounds the development of cooperative system, and then describes the purpose of multi unmanned system cooperation. Then, this paper studies the intelligent algorithm applied to the cooperation of multiple unmanned systems in the field of artificial intelligence. Finally, aiming at the existing security problems of artificial intelligence, this paper tests the functions of multiple unmanned systems. The test results show that when multiple unmanned systems work together, the accuracy of artificial intelligence in dealing with things is basically more than 90%. At the same time, it can be nearly 100% scientific, and can budget a variety of treatment schemes. This shows that in the multi unmanned system cooperation, artificial intelligence can almost meet its needs, but it still needs to be further improved.

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

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