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

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.

2021 ◽  
Vol 2074 (1) ◽  
pp. 012096
Author(s):  
Yuanyuan You

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.


2011 ◽  
Vol 204-210 ◽  
pp. 1880-1883
Author(s):  
Shuang Chen ◽  
Jun Wang

CBR(Case-based reasoning)is an important research direction of artificial intelligence field,which start a new way for it. The mine hoist spindle is the most critical equipment to hoisting equipment.It is the main part of the machine which relates to the upgrading of equipment life.With the platform of Visual C++,we analysised the design methods of the mine hoist spindle based on CBR in this experiment.It will combine computer-aided design technology with artificial intelligence factors.


Author(s):  
Wei Jia ◽  
Wei Xia ◽  
Yang Zhao ◽  
Hai Min ◽  
Yan-Xiang Chen

AbstractPalmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition and have achieved impressive results. In recent years, in the field of artificial intelligence, deep learning has gradually become the mainstream recognition technology because of its excellent recognition performance. Some researchers have tried to use convolutional neural networks (CNNs) for palmprint recognition and palm vein recognition. However, the architectures of these CNNs have mostly been developed manually by human experts, which is a time-consuming and error-prone process. In order to overcome some shortcomings of manually designed CNN, neural architecture search (NAS) technology has become an important research direction of deep learning. The significance of NAS is to solve the deep learning model’s parameter adjustment problem, which is a cross-study combining optimization and machine learning. NAS technology represents the future development direction of deep learning. However, up to now, NAS technology has not been well studied for palmprint recognition and palm vein recognition. In this paper, in order to investigate the problem of NAS-based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct a performance evaluation of twenty representative NAS methods on five 2D palmprint databases, two palm vein databases, and one 3D palmprint database. Experimental results show that some NAS methods can achieve promising recognition results. Remarkably, among different evaluated NAS methods, ProxylessNAS achieves the best recognition performance.


2020 ◽  
pp. 1-14
Author(s):  
Longjie Li ◽  
Lu Wang ◽  
Hongsheng Luo ◽  
Xiaoyun Chen

Link prediction is an important research direction in complex network analysis and has drawn increasing attention from researchers in various fields. So far, a plethora of structural similarity-based methods have been proposed to solve the link prediction problem. To achieve stable performance on different networks, this paper proposes a hybrid similarity model to conduct link prediction. In the proposed model, the Grey Relation Analysis (GRA) approach is employed to integrate four carefully selected similarity indexes, which are designed according to different structural features. In addition, to adaptively estimate the weight for each index based on the observed network structures, a new weight calculation method is presented by considering the distribution of similarity scores. Due to taking separate similarity indexes into account, the proposed method is applicable to multiple different types of network. Experimental results show that the proposed method outperforms other prediction methods in terms of accuracy and stableness on 10 benchmark networks.


Nanoscale ◽  
2021 ◽  
Author(s):  
Qiufan Wang ◽  
Jiaheng Liu ◽  
Guofu Tian ◽  
Daohong Zhang

The rapid development of human-machine interface and artificial intelligence is dependent on flexible and wearable soft devices such as sensors and energy storage systems. One of the key factors for...


2011 ◽  
Vol 335-336 ◽  
pp. 419-422 ◽  
Author(s):  
Yuan Lian ◽  
Jian Yi Wu ◽  
Da Peng Zhou ◽  
Hong Mei Wang ◽  
Dian Wu Huang ◽  
...  

Alginate fibre has attracted great attention in the area of biological medical materials due to its unique biological properties. But its low tenacity greatly hinders its application area. Therefore, the preparation technology of alginate fibre has been as an important research direction in this area in recent years. The purpose of this article is to prepare the calcium alginate fibre with good properties by wet spinning. The structure and properties of this fibre are analyzed by scanning electron microscope,infrared spectrometer,thermal gravimetric analyzer and DSC.


2021 ◽  
Vol 5 (9) ◽  
pp. RV1-RV5
Author(s):  
Sahrish Tariq ◽  
Nidhi Gupta ◽  
Preety Gupta ◽  
Aditi Sharma

The educational needs must drive the development of the appropriate technology”. They should not be viewed as toys for enthusiasts. Nevertheless, the human element must never be dismissed. Scientific research will continue to offer exciting technologies and effective treatments. For the profession and the patients, it serves to benefit fully from modern science, new knowledge and technologies must be incorporated into the mainstream of dental education. The technologies of modern science have astonished and intrigued our imagination. Correct diagnosis is the key to a successful clinical practice. In this regard, adequately trained neural networks can be a boon to diagnosticians, especially in conditions having multifactorial etiology.


2021 ◽  
Vol 3 (5) ◽  
pp. 130-134
Author(s):  
E. A. ULANOV ◽  

The scale of the tasks being solved has turned AI into a special area of modern science. AI is a branch of science that studies ways to train a computer, robotic technology, or analytical system to think intelligently. The article reveals the essence and concept of artificial intelligence. The main features, problems, trends and prospects of artificial intelligence development are analyzed.


2021 ◽  
Vol 6 (5) ◽  
pp. 10-15
Author(s):  
Ela Bhattacharya ◽  
D. Bhattacharya

COVID-19 has emerged as the latest worrisome pandemic, which is reported to have its outbreak in Wuhan, China. The infection spreads by means of human contact, as a result, it has caused massive infections across 200 countries around the world. Artificial intelligence has likewise contributed to managing the COVID-19 pandemic in various aspects within a short span of time. Deep Neural Networks that are explored in this paper have contributed to the detection of COVID-19 from imaging sources. The datasets, pre-processing, segmentation, feature extraction, classification and test results which can be useful for discovering future directions in the domain of automatic diagnosis of the disease, utilizing artificial intelligence-based frameworks, have been investigated in this paper.


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