Real-time steganalysis for streaming media based on multi-channel convolutional sliding windows

2021 ◽  
pp. 107561
Author(s):  
Zhongliang Yang ◽  
Hao Yang ◽  
Ching-Chun Chang ◽  
Yongfeng Huang ◽  
Chin-Chen Chang
2014 ◽  
Vol 701-702 ◽  
pp. 943-946
Author(s):  
Nian Fang Hong

In the wireless network environment, a large number of applications based on cell phone have emerged. But it has appeared some problems such as large amount of data and limited bandwidth and higher quality transmission in the mobile streaming media data transmission. To solve these problems, this paper designs a bandwidth adaptive streaming media real-time synchronization algorithm. Algorithm firstly analysis the state of the network, and then through real-time increase or decrease the factor method to effectively adjust the code flow rate, thus improve the QoS of streaming in transmission; to meet the learners' online learning, for subsequent teaching and interaction provides a good technical support.


2014 ◽  
Vol 543-547 ◽  
pp. 1972-1976
Author(s):  
Huai Lin Dong ◽  
Ming Yuan He ◽  
Qing Feng Wu ◽  
Sheng Hang Wu

When membership queries are evaluated in a set, the performance can be improved by a Bloom filter which is a space-efficient probabilistic data structure. According to its space-efficient character, Bloom Filter presented to address the load balancing problem for streaming media information in Storm system which is free and open source distributed real time computation system. This method increases the server cluster availability by balancing the workloads among the servers within a cluster. Additionally, it improves real time system Storm efficiently in saving the data transmission time and reducing the calculation complexity.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kuiqun Wang

Network and related network technology limit the traditional online teaching activities, making teaching activities only limited to asynchronous teaching, limiting the advantages of real-time, interactive, and vivid online teaching. As a new online teaching network technology, streaming media technology can realize flexible and efficient two-way communication between teachers and students, simulate virtual face-to-face teaching environment, and produce enough emotional resonance for both sides in the corresponding time and space. In view of the poor communication quality and flexibility of current streaming media technology, this paper will build a selective streaming media online teaching architecture based on animation media service platform. The system innovatively uses DXSDK filtering technology to realize real-time audio acquisition and filtering processing and solves the communication quality problem of streaming media online teaching. Aiming at the flexibility of streaming media online teaching, the system adds online auxiliary teaching function, which can realize online text communication, file information management, and learning tracking interaction between teaching and learning. The experimental part is applied to the online teaching activities of a training institution. From the experimental results, the stability and flexibility of the system are greatly improved within a certain range of users, which has obvious practical value. It has high stability and application value.


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