Current Issue : October - December Volume : 2020 Issue Number : 4 Articles : 5 Articles
Abstract: Video game live streaming is a kind of real-time video social media that integrates traditional\nbroadcasting and online gaming. With the rapid popularity of video game live streaming in the past\ndecade, researchers have started to investigate the relationship between the use of video game live\nstreaming and various psychological variables. In order to fully understand the factors that affected\nuser participation (streamers and audiences) in video game live streaming and provide a reference to\nthe mental health issues of Internet addiction, this paper summarizes the relevant literature on user\nbehavior in video game live streaming. First, we comprehensively searched literature in six social\nscience databases and thus obtained 24 papers that meet our inclusion criteria. Second, the above\nliterature was presented in table form for classification and we found that the effect factors of user\nbehavior in video game live streaming mainly include user demands and platform impact. Based on\nUse and Satisfaction theory, this paper reviewed the following four aspects: streamer demand,\naudience demand, interaction behavior and platform impact, then a relevant theoretical framework\nwas constructed. Finally, this paper looks forward to possible future research topics based on the\nresearch platform, research data and research content and so on, hoping to provide a foundation and\nnew ideas for future research....
In this research, the color system was analyzed according to the International Lighting Commission (CIE) standard by studying the\ntheoretical aspect of the general color system according to the latest communication theories of the visual image supported by\nmathematical equations and illustrations supporting the relevant hypotheses and then a comparison of evolution. There is an\nenormous use in color spaces and systems according to their own use, where the use of colors has become in various areas\nincluding television systems; computer systems; industry and product colors; printing of all kinds of black and white and color;\npaint colors for buildings, houses, and cities; and many other color-related uses. The development of color spaces and systems\nfrom 1931 to the present day has expanded a lot, and this led to the emergence of new areas of color systems characterized by\naccuracy and beauty and became the color of the subcolors according to the desire of the customer and the quality of use. The\ndevelopment of color systems has an impact on visual communication such as television broadcasting systems, medical image\nprocessing, and video signal processing, as well as in the field of computer such as graphic equipment and printing....
In this paper, we research a synthesis scheme for secure wireless communication in the broadcasting multiusers directional\nmodulation system, which consists of multiple legitimate users (LUs) receiving the same confidential messages and multiple\neavesdroppers (Eves) intercepting the confidential messages. We propose a new type of array antennas, termed random frequency\ndiverse arrays (RFDA), to enhance the security of confidential messages due to its angle-range dependent beam patterns. Based on\nRFDA, we put forward a synthesis scheme to achieve multiobjective secure wireless communication. First, with known locations\nof Eves, the beamforming vector is designed to minimize Evesâ?? receiving power of confidential message (Min-ERP) while\nsatisfying the power requirement of LUs. Furthermore, we research a more practical scenario, where locations of Eves are\nunknown. Unlike the scenario of known locations of Eves, the beamforming vector is designed to maximize the sum received\npower of LUs (Max-LRP) while satisfying a minimum received power constraint at each LU. Second, the artificial-noise projection\nmatrix (ANPM) is calculated to reduce artificial-noise (AN) impact on LUs and enhance the interference on Eves. Numerical\nresults verify the superior secure performance of the proposed schemes in the broadcasting multiusers system....
Video surveillance is an important data source of urban computing and intelligence. The low resolution of many existing video\nsurveillance devices affects the efficiency of urban computing and intelligence. Therefore, improving the resolution of video\nsurveillance is one of the important tasks of urban computing and intelligence. In this paper, the resolution of video is improved\nby superresolution reconstruction based on a learning method. Different from the superresolution reconstruction of static\nimages, the superresolution reconstruction of video is characterized by the application of motion information. However, there\nare few studies in this area so far. Aimed at fully exploring motion information to improve the superresolution of video, this\npaper proposes a superresolution reconstruction method based on an efficient subpixel convolutional neural network, where the\noptical flow is introduced in the deep learning network. Fusing the optical flow features between successive frames can\ncompensate for information in frames and generate high-quality superresolution results. In addition, in order to improve the\nsuperresolution, a superpixel convolution layer is added after the deep convolution network. Finally, experimental evaluations\ndemonstrate the satisfying performance of our method compared with previous methods and other deep learning networks; our\nmethod is more efficient....
With the rapid development of Internet technology, live broadcast industry has also flourished. However, in the public network\nlive broadcast platform, live broadcast security issues have become increasingly prominent. The detection of suspected pornographic\nvideos in live broadcast platforms is still in the manual detection stage, that is, through the supervision of administrators\nand user reports. At present, there are many online live broadcast platforms in China. In mainstream live streaming\nplatforms, the number of live broadcasters at the same time can reach more than 100,000 people/times. Only through manual\ndetection, there are a series of problems such as low efficiency, poor pertinence, and slow progress. This approach is obviously not\nup to the task requirements of real-time network supervision. For the identification of whether live broadcasts on the Internet\ncontain pornographic content, a deep neural network model based on residual networks (ResNet-50) is proposed to detect\npictures and videos in live broadcast platforms. The core idea of detection is to classify each image in the video into two categories:\n(1) pass and (2) violation. The experiments verify that the network proposed can heighten the efficiency of pornographic detection\nin webcasts. The detection method proposed in this article can improve the accuracy of detection on the one hand and can\nstandardize the detection indicators in the detection process on the other. These detection indicators have a certain promotion\neffect on the classification of pornographic videos....
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