scholarly journals Construction of Live Broadcast Training Platform Based on “Cloud Computing” and “Big Data” and “Wireless Communication Technology”

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhidong Sun ◽  
Xueqing Li

With the rapid development of information technology, a scientific theory is brought by the rapid progress of science and technology. The advancement of science and technology of the impact on every field, changing the mode of transmission of information, the advent of big data for promotion and dissemination of resources played their part, let more and more people benefit. In the context of cloud computing, big data ushered in another upsurge of development and growth. Given this, the live broadcast training platform, which focuses on enterprise staff training and network education, arises at the right moment. People favor its convenience, real-time performance, and high efficiency. However, the low-value density of big data and cloud computing’s security problem has difficulties constructing a live broadcast training platform. In this paper, the live broadcast training platform’s structure is improved by constructing three modules: the live training module based on cloud computing, the user recommendation module based on big data, and the security policy guarantee module. In addition, to ensure that the trainees can receive training anytime and anywhere, this paper uses wireless communication technology to ensure the quality and speed of all users’ live video sources.

Author(s):  
Chandu Thota ◽  
Gunasekaran Manogaran ◽  
Daphne Lopez ◽  
Vijayakumar V.

The rapid development of data generation sources such as digital sensors, networks, and smart devices along with their extensive use is leading to create huge database and coins the term Big Data. Cloud Computing enables computing resources such as hardware, storage space and computing tools to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. Cloud-based technologies with advantages over traditional platforms are rapidly utilized as potential hosts for big data. However, privacy and security is one of major issue in cloud computing due to its availability with very limited user-side control. This chapter proposes security architecture to prevent and secure the data and application being deployed in cloud environment with big data technology. This chapter discuss the security issues for big data in cloud computing and proposes Meta Cloud Data Storage architecture to protect big data in cloud computing environment.


Web Services ◽  
2019 ◽  
pp. 240-257
Author(s):  
Chandu Thota ◽  
Gunasekaran Manogaran ◽  
Daphne Lopez ◽  
Vijayakumar V.

The rapid development of data generation sources such as digital sensors, networks, and smart devices along with their extensive use is leading to create huge database and coins the term Big Data. Cloud Computing enables computing resources such as hardware, storage space and computing tools to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. Cloud-based technologies with advantages over traditional platforms are rapidly utilized as potential hosts for big data. However, privacy and security is one of major issue in cloud computing due to its availability with very limited user-side control. This chapter proposes security architecture to prevent and secure the data and application being deployed in cloud environment with big data technology. This chapter discuss the security issues for big data in cloud computing and proposes Meta Cloud Data Storage architecture to protect big data in cloud computing environment.


2018 ◽  
pp. 589-607 ◽  
Author(s):  
Chandu Thota ◽  
Gunasekaran Manogaran ◽  
Daphne Lopez ◽  
Vijayakumar V.

The rapid development of data generation sources such as digital sensors, networks, and smart devices along with their extensive use is leading to create huge database and coins the term Big Data. Cloud Computing enables computing resources such as hardware, storage space and computing tools to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. Cloud-based technologies with advantages over traditional platforms are rapidly utilized as potential hosts for big data. However, privacy and security is one of major issue in cloud computing due to its availability with very limited user-side control. This chapter proposes security architecture to prevent and secure the data and application being deployed in cloud environment with big data technology. This chapter discuss the security issues for big data in cloud computing and proposes Meta Cloud Data Storage architecture to protect big data in cloud computing environment.


2013 ◽  
Vol 662 ◽  
pp. 896-901
Author(s):  
Zong Jin Liu ◽  
Yang Yang ◽  
Zheng Fang ◽  
Yan Yan Xu

Because of rapid development of wireless communication technology, there is an increasing adoption of mobile advertising, such as location based advertising (LBA). To what extent can LBA improve advertising effectiveness is an important topic in the field of wireless communication technology research. Most researches quantify long term impacts of advertisings by VAR (Vector Autoregressive) model. However, compared to VAR model, VECM (Vector Error Correction Model) is a better method in that it allows one to estimate both a long-term equilibrium relationship and a short-term dynamic error correction process. In this study, we employ VECM to explore LBA’s (Location Based Advertising) and PUA’s (Pop-up Advertising) sales impact in both short and long terms. The developed VECM reveals that LBA’s sales impact is about more than2 times as big as PUA’s in short dynamic term and nearly 6 times bigger than PUA’s in long equilibrium term. These findings add to advertising and VECM literatures. These results can give managers more confident to apply wireless communication technology to advertising.


2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>


2014 ◽  
Vol 945-949 ◽  
pp. 2301-2305
Author(s):  
Yi Peng ◽  
Yan Jun Wang

With the rapid development of wireless communication technology, the shortage of spectrum resources is becoming more and more serious, and may even become a bottleneck restricting of the development wireless communication technology in the future. Now, Spectrum sensing technology, spectrum sharing technology and spectrum management technology is the three core technologies of cognitive radio spectrum,and sensing technology is to implement the follow-up of spectrum sharing and the premise of spectrum management.So mainly to the current model of the cognitive radio spectrum sensing technology,to make a classification and comparison, finally it is concluded that cognitive users under the environment of higher signal-to-noise ratio, the better results of the perceived performance.


2020 ◽  
Vol 12 (14) ◽  
pp. 5605
Author(s):  
Yi-Zeng Hsieh ◽  
Shih-Syun Lin ◽  
Yu-Cin Luo ◽  
Yu-Lin Jeng ◽  
Shih-Wei Tan ◽  
...  

Under the vigorous development of global anticipatory computing in recent years, there have been numerous applications of artificial intelligence (AI) in people’s daily lives. Learning analytics of big data can assist students, teachers, and school administrators to gain new knowledge and estimate learning information; in turn, the enhanced education contributes to the rapid development of science and technology. Education is sustainable life learning, as well as the most important promoter of science and technology worldwide. In recent years, a large number of anticipatory computing applications based on AI have promoted the training professional AI talent. As a result, this study aims to design a set of interactive robot-assisted teaching for classroom setting to help students overcoming academic difficulties. Teachers, students, and robots in the classroom can interact with each other through the ARCS motivation model in programming. The proposed method can help students to develop the motivation, relevance, and confidence in learning, thus enhancing their learning effectiveness. The robot, like a teaching assistant, can help students solving problems in the classroom by answering questions and evaluating students’ answers in natural and responsive interactions. The natural interactive responses of the robot are achieved through the use of a database of emotional big data (Google facial expression comparison dataset). The robot is loaded with an emotion recognition system to assess the moods of the students through their expressions and sounds, and then offer corresponding emotional responses. The robot is able to communicate naturally with the students, thereby attracting their attention, triggering their learning motivation, and improving their learning effectiveness.


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