Received: 5 November 2020 Accepted: 28 January 2021 Artificial intelligence and fifth generation (5G) technology are widely adopted to evaluate the classroom poses of college students, with the help of campus video surveillance equipment. To ensure the effective learning in class, it is important to detect and intervene in abnormal behaviors like sleeping and using cellphones in time. Based on spatiotemporal representation learning, this paper presents a deep learning algorithm to evaluate classroom poses of college students. Firstly, feature engineering was adopted to mine the moving trajectories of college students, which were used to determine student distribution and establish a classroom prewarning system. Then, k-means clustering (KMC) was employed for cluster analysis on different student groups, and identify the features of each group. For a specific student group, the classroom surveillance video was decomposed into several frames; the edge of each frame was extracted by edge detection algorithm, and imported to the proposed convolutional neural network (CNN). Experimental results show that our algorithm is 5% more accurate than the benchmark three-dimensional CNN (C3D), making it an effective tool to recognize abnormal behaviors of college students in class.

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Abnormal Behavior Recognition in Classroom Pose Estimation of College Students Based on Spatiotemporal Representation Learning

Mobility in cluster based wireless sensor networks is reminder of a new challenge that is not considered as an important issue is traditional protocols designed for static environments. This new challenge is packet delivery. When nodes leave their cluster zone, they no longer can send data to the cluster head, and they have to find as soon as possible a new cluster head. By increasing mobility in the network, this situation becomes worse. To address this issue an adaptive protocol needed to reduce the packet loss by selecting better cluster heads and assign a new cluster head to mobile nodes in order to avoid more packet loss. In this paper we proposed MACP-FL, a mobility adaptive clustering protocol proposed for mobile wireless sensor networks. In setup phase of our protocol, we used FCM algorithm to divide the network into several clusters. The candidate cluster heads are selected based on three measures, residual energy, and membership function. When candidate cluster heads have been selected, by considering maximum radio range, suitable cluster head for each individual node selected based on estimated connection time between node and corresponding cluster heads. If a node is going to leave its cluster in transmission phase, it selects the new cluster head based on estimated connection time. Simulation results show that our method outperforms LEACH-M, LEACH-ME and MBC in terms of data delivery rate and energy consumption.

A fuzzy clustering based mobility-adaptive routing protocol for wireless sensor networks

The significance and value of literature itself determine the importance of literary communication, and literary text communication contains the communication of literary value and significance. Communication is the carrier of transmitting literary works and the bridge between literature and audience. At present, the network new media has become the most frequently used media platform for the public, providing an independent space for individual information production, accumulation, sharing and dissemination. In this paper, literature communication is defined as "the communication of literary text", taking the literature communication caused by "Wang Guozhen's death" as the research object, through the analysis of the content of relevant information and the questionnaire survey of the audience, the statistics show that the people who get the information through wechat circle of friends are the most, accounting for 33%, and the influence of network new media on literature communication and the reasons for its influence are analyzed.

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Influence of Network New Media on the Digital Dissemination of Chinese Literature

The optimum use of energy in wireless sensor networks WSNs is very important. The recent researches show that organising the network nodes in some clusters leads to higher efficiency of energy and ...

MasdariMohammad

Papers

A new approach for decreasing energy in wireless sensor networks with hybrid LEACH protocol and fuzzy C-means algorithm