International Journal of Mobile Computing and Multimedia Communications

Mobile edge computing (MEC) can provide computing services for mobile users (MUs) by offloading computing tasks to edge clouds through wireless access networks. Unmanned aerial vehicles (UAVs) are deployed as supplementary edge clouds to provide effective MEC services for MUs with poor wireless communication condition. In this paper, a joint task offloading and power allocation (TOPA) optimization problem is investigated in UAV-assisted MEC system. Since the joint TOPA problem has a strong non-convex characteristic, a method based on deep reinforcement learning is proposed. Specifically, the joint TOPA problem is modeled as Markov decision process. Then, considering the large state space and continuous action space, a twin delayed deep deterministic policy gradient algorithm is proposed. Simulation results show that the proposed scheme has lower smoothing training cost than other optimization methods.

Nan Zhao

Fan Ren

Wei Du

Zhiyang Ye

Deep Reinforcement Learning for Task Offloading and Power Allocation in UAV-Assisted MEC System

无人机辅助移动边缘计算系统中的任务卸载与功率分配深度强化学习

In recent years, Android became the first target for hackers and malware developers due to its inefficient permission model. In this article, the authors introduce a tool called PerUpSecure to manage permissions requested by Android applications, calculate the risk rates, and display the results to the user in order to help him to make a better decision. Thanks to our PerUpSecure, the user will be able to install only the trusted applications. As far as the authors know, the other existing tools focus only on measuring app risk after being installed and not before as this tool does. Therefore, to evaluate the tool, they selected two different applications sets. The results show that the tool can produce the most trustworthy risk rate to prevent and detect potential malicious activities performed by malware.

Latifa Er-Rajy

My Ahmed El Kiram

Mohamed El Ghazouani

Estimate Risks Eate for Android Applications Using Android Permissions

使用Android权限估计Android应用程序的风险

Music is a widely used data format in the explosion of Internet information. Automatically identifying the style of online music in the Internet is an important and hot topic in the field of music information retrieval and music production. Recently, automatic music style recognition has been used in many real life scenes. Due to the emerging of machine learning, it provides a good foundation for automatic music style recognition. This paper adopts machine learning technology to establish an automatic music style recognition system. First, the online music is process by waveform analysis to remove the noises. Second, the denoised music signals are represented as sample entropy features by using empirical model decomposition. Lastly, the extracted features are used to learn a relative margin support vector machine model to predict future music style. The experimental results demonstrate the effectiveness of the proposed framework.

Lizhu Yuan

Yue Zhang

Online Music Style Recognition via Mobile Computing

基于移动计算的在线音乐风格识别

With the rapidly developing of the scientific research in the field of sports, big data analytics and information science are used to carry out technical and tactical statistical analysis of competition or training videos. The table tennis is a skill oriented sport. The technique and tactics in table tennis are the core factors to win the game. With the endlessly emerging innovative playing techniques and tactics, the players have their own competition styles. According to the competition events among athletes, the athletes’ competition relationship network is constructed and the players’ ranking is established. The ranking can be used to help table tennis players improve daily training and understand their ability. In this paper, the table tennis players’ ranking is established their competition videos and their prestige scores in the table tennis players’ competition relationship network.

Xiaoni Wei

Video Sequence Analysis for On-Table Tennis Player Ranking and Analysis

视频序列分析用于台球选手排名与分析

With the rapid development of mobile Internet technology, mobile network data traffic presents an explosive growth trend. Especially, the proportion of mobile video business has become a large proportion in mobile Internet business. Mobile video business is considered as a typical business in the 5G network, such as in online education. The growth of video traffic poses a great challenge to mobile network. In order to provide users with better quality of experience (QoE), it requires mobile network to provide higher data transmission rate and lower network delay. This paper adopts a combined optimization to minimize total cost and maximize QoE simultaneously. The optimization problem is solved by ant colony algorithm. The effectiveness is verified on experiment.

Dan Wang

Jian Zhao

Mobile Edge Computing to Assist the Online Ideological and Political Education

移动边缘计算助力在线思想政治教育

With the deployment of internet of things-based monitoring terminals, massive electric measurement data are transmitted and shared among different grid company sectors. Consortium blockchain based consensus process has been adopted to enhance data traceability. However, previous studies face challenges including single-dimensional indication and lack of dynamic trustworthy degree update mechanism. Therefore, this paper proposes a node trust evaluation and selection algorithm based on improved fuzzy Petri network (IFPN). Firstly, the multi-dimensional node trust evaluation and selection framework for practical Byzantine fault tolerance (PBFT)-empowered electric measurement data sharing is constructed. On this basis, IFPN is proposed to dynamically evaluate measurement data node trust, and nodes participating in the PBFT consensus process are selected based on the Top-N algorithm. Further, the trustworthy degree of IFPN is dynamically updated based on the fuzzy deviation to improve the accuracy. Finally, the superiority of the proposed algorithm has been verified through simulation.

Xianbo Du

Shuyun Wang

Chunyang Li

Mingtao Cui

Zheng Xiong

Haodong Liu

Multi-Dimensional Consensus Node Trust Evaluation and Selection for Blockchain-Empowered Electric Measurement Data Traceability

区块链赋能的电力测量数据溯源的多维共识节点信任评估与选择

With the maturity of AR technology, AR is more and more used in various industries. from the perspective of the application of AR technology at this stage, the emergence of AR technology improves the visual effect in image animation, simulates the real scene in the viewing process, and makes the computer advanced human-machine interface with the basic characteristics of equipment interactivity and conceptualization, spread to the scope of film and television. As a creative emerging industry, influence animation has huge development space and prospects, and it also carries the functions and tasks of inheriting traditional culture. Combined with the specific situation of Lingnan culture, this paper introduces the combination of AR technology and Lingnan culture in visual, sound and interactive design, and extracts its creative elements. Compared with the simple data recording method, the difference between the two is 41.22%. Through specific ideas and programs, it provides a new digital method and idea for the protection and research of Lingnan culture.

Zhengzhong Shen

Wei Zhang

Peijuan Song

Integration and Application of AR Technology in Augmented Reality Image Animation Within the Context of Lingnan Culture

岭南文化背景下AR技术在增强现实图像动画中的融合与应用

This paper combines the dance 3D space simulation sequence diagram with video motion recognition technology, filters, denoises, grays and background removal the collected dance video images, analyzes the motion characteristics of people in the sequence diagram, uses support vector machine to learn and train 3D space models, classifies and recognizes people's dance movements, and extracts 3D-SIFT and optical flow characteristics of various areas of human body. Form a three-dimensional space simulation sequence diagram, reduce and normalize the extracted features, get the feature vectors of various characters, and input them into the classifier to realize the recognition of dance movements. The results show that the combination of 3D-SIFT and optical flow can realize the dynamic change of human static information, the illumination invariance of SIFT features can make up for the illumination sensitivity of optical flow features, and the optical flow features can solve the instability problem of determining the key points of SIFT features.

Hua Wei

Vinh Chau

The Role of the Combination of 3D Simulation Sequence Diagram and Video Motion Recognition Technology in Evaluating and Correcting Dancers' Dance Moves

3D模拟序列图与视频运动识别技术组合在评估和纠正舞者舞姿中的作用

With the circulation of massive electric measurement data, data anomaly caused by security attacks imposes security risks on reliable operation of smart grid. Long short-term memory (LSTM) based data circulation monitoring and security risk anomaly evaluation has been intensively studied. However, some issues remain unsolved, including learning overfitting and large prediction error. In this paper, we investigate fuzzy learning to infer the abnormal level of security risk. In particular, an adaptive grey wolf optimization-LSTM-fuzzy petri network (AGWO-LSTM-FPN) based electrical measurement data circulation monitoring and security risk anomaly evaluation algorithm is proposed. Specifically, AGWO is utilized to optimize LSTM parameter updating and improve traffic prediction accuracy. Furthermore, FPN is combined with multi-dimensional monitoring indicators to enhance anomaly level evaluation. Simulation results illustrate the excellent performance of AGWO-LSTM-FPN.

Xinjia Li

Yahong Li

Lei Fang

Liwei Liu

Ke Wang

Fuzzy Learning-Based Electric Measurement Data Circulation Monitoring and Security Risk Anomaly Evaluation

基于模糊学习的电力测量数据循环监测与安全风险异常评估

Coronavirus disease 2019 (COVID-19) pandemic has produced a global health crisis that has had a deep impact on the way we perceive our world and everyday lives. Not only the spread rate of contagion and patterns of transmission endangered our sense of security, but the safety measures put in place to contain the spread of the virus also require social distancing. In this context of physical threat, social and physical distancing, the role of the different mass media channels and social media in lives of individual, social and societal levels cannot be underestimated.

None Badreya Al-jenaibi (536d4bda-1d8b-42f0-94b7-3346c14bc901

Youth Sources of News During the COVID-19 Period

COVID-19期间青年的新闻来源

短名	Int. J. Mob. Comput. Multimedia Commun.
Journal Impact	0.48
国际分区	TELECOMMUNICATIONS(Q4)

ISSN	1937-9404, 1937-9412
h-index	12

涉及主题	计算机科学操作系统工程类计算机网络数学电信计算机安全人工智能万维网物理程序设计语言无线统计生物电气工程
出版信息	出版商: IGI Global Publishing，出版周期: ，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 2016，原创研究文献占比: 100.00%，自引率:0.00%， Gold OA占比: 70.00%

International Journal of Mobile Computing and Multimedia Communications

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