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Yulianto, Agus, Sisworo Sisworo, and Erry Hidayanto. "Pembelajaran Matematika Berbantuan Video Pembelajaran untuk Meningkatkan Motivasi dan Hasil Belajar Peserta Didik." Mosharafa: Jurnal Pendidikan Matematika 11, no. 3 (September 30, 2022): 403–14. http://dx.doi.org/10.31980/mosharafa.v11i3.1396.
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Kemampuan guru memilih media dan mengemas proses belajar mengajar sangat menentukan keberhasilan belajar. Sebab, minat siswa dalam menggunakan buku teks masih kurang. Penelitian bertujuan menerpakan video pembelajaran guna meningkatkan motivasi dan hasil belajar. Video pembelajaran dibuat untuk mendampingi LKPD. Subyek penelitian adalah 36 siswa kelas X Akuntansi salah satu SMKN di Trenggalek. Data hasil penelitian di olah dan dianalisis secara deskriptif. Siswa pada awalnya diberikan Vidio pembelajaran dan LKPD melalui WAG, selanjutnya sesuai jadwal masuk ke googlemeet yang sudah disediakan untuk pembahasan apa saja yang kurang jelas dari video pembelajaran. Hasil penelitian menunjukkan peningkatan motivasi belajar dan hasil belajar siswa, meliputi: Siswa aktif dalam mengikuti kegiatan pembelajaran daring, menyelesaikan LKPD yang diberikan tepat waktu sesuai dengan petunjuk yang diberikan, dan prestasi siswa meningkat dengan bantuan Vidio Pembelajaran. Pada siklus 1 tingkat ketuntasan peserta didik mencapai 77,8 % dan pada siklus II mencapai 92%. Video pembelajaran terbukti bermanfaat dalam meningkatkan motivasi belajar.The teacher's ability to choose the media and package the teaching and learning process will determine success in learning. That was because students' interest to use textbooks is still lacking. This study aims to apply a learning video to increase motivation and learning outcomes. Learning videos made to accompany LKPD. The research subjects were 36 X student's Accounting at one of the Vocational High Schools in Trenggalek. Data from the research were processed and analyzed descriptively. Students are initially given learning videos and LKPD through WAG, then, according to the schedule enter the google meet that has been provided to discuss anything that is not clear from the learning video. The results showed an increase in motivation and student learning outcomes, including students being active in participating in online learning activities, students completing the LKPD given on time according to the instructions given, and student achievement increased with the help of learning videos. In cycle 1, the level of completeness of students reached 77.8%, and in cycle II, it reached 92%. Learning videos are proven to be useful in increasing learning motivation.
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Yulianto, Agus, Sisworo Yulianto, and Erry Hidayanto. "Pembelajaran Matematika Berbantuan Video Pembelajaran untuk Meningkatkan Motivasi dan Hasil Belajar Peserta Didik." Mosharafa: Jurnal Pendidikan Matematika 11, no. 3 (September 30, 2022): 403–14. http://dx.doi.org/10.31980/mosharafa.v11i3.731.
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Kemampuan guru memilih media dan mengemas proses belajar mengajar sangat menentukan keberhasilan belajar. Sebab, minat siswa dalam menggunakan buku teks masih kurang. Penelitian bertujuan menerpakan video pembelajaran guna meningkatkan motivasi dan hasil belajar. Video pembelajaran dibuat untuk mendampingi LKPD. Subyek penelitian adalah 36 siswa kelas X Akuntansi salah satu SMKN di Trenggalek. Data hasil penelitian di olah dan dianalisis secara deskriptif. Siswa pada awalnya diberikan Vidio pembelajaran dan LKPD melalui WAG, selanjutnya sesuai jadwal masuk ke googlemeet yang sudah disediakan untuk pembahasan apa saja yang kurang jelas dari video pembelajaran. Hasil penelitian menunjukkan peningkatan motivasi belajar dan hasil belajar siswa, meliputi: Siswa aktif dalam mengikuti kegiatan pembelajaran daring, menyelesaikan LKPD yang diberikan tepat waktu sesuai dengan petunjuk yang diberikan, dan prestasi siswa meningkat dengan bantuan Vidio Pembelajaran. Pada siklus 1 tingkat ketuntasan peserta didik mencapai 77,8 % dan pada siklus II mencapai 92%. Video pembelajaran terbukti bermanfaat dalam meningkatkan motivasi belajar. The teacher's ability to choose the media and package the teaching and learning process will determine success in learning. That was because students' interest to use textbooks is still lacking. This study aims to apply a learning video to increase motivation and learning outcomes. Learning videos made to accompany LKPD. The research subjects were 36 X student's Accounting at one of the Vocational High Schools in Trenggalek. Data from the research were processed and analyzed descriptively. Students are initially given learning videos and LKPD through WAG, then, according to the schedule enter the google meet that has been provided to discuss anything that is not clear from the learning video. The results showed an increase in motivation and student learning outcomes, including students being active in participating in online learning activities, students completing the LKPD given on time according to the instructions given, and student achievement increased with the help of learning videos. In cycle 1, the level of completeness of students reached 77.8%, and in cycle II, it reached 92%. Learning videos are proven to be useful in increasing learning motivation.
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S., Sankirti, and P. M. Kamade. "Video OCR for Video Indexing." International Journal of Engineering and Technology 3, no. 3 (2011): 287–89. http://dx.doi.org/10.7763/ijet.2011.v3.239.
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Tafesse, Wondwesen. "YouTube marketing: how marketers' video optimization practices influence video views." Internet Research 30, no. 6 (July 3, 2020): 1689–707. http://dx.doi.org/10.1108/intr-10-2019-0406.
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PurposeYouTube's vast and engaged user base makes it central to firms' digital marketing effort. With extant studies focusing on viewers' post-view engagement behavior, however, research into what motivates viewers to click on and watch YouTube videos is scarce. This study investigates the implications of marketers' video optimization practices for video views on YouTube.Design/methodology/approachThe study employed a data set of videos (N = 4,398) gathered by scraping YouTube's trending list. Using a combination of text and sentiment analysis, the study measured four video optimization practices: information content of video titles, emotional intensity of video titles, information content of video descriptions and volume of video tags. It then analyzed the effect of these video optimization practices on video views.FindingsThe study finds that greater availability of information in video titles is negatively associated with video views, whereas intensity of negative emotional sentiment in video titles is positively associated with video views. Further, greater availability of information in video descriptions is positively associated with video views. Finally, an inverted U-shaped relationship is found between volume of video tags and video views. Up to 17 video tags can contribute to more video views; however, beyond 17 tags, the relationship turns negative.Originality/valueThis study investigates the effect of marketers' video optimization practices on video views. While extant studies mainly focus on viewers' post-view engagement behavior, such as liking, commenting on and sharing videos, this study examines video views. Similarly, extant studies investigate videos' internal content, while this study investigates elements of the video metadata.
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Song, Yaguang, Junyu Gao, Xiaoshan Yang, and Changsheng Xu. "Learning Hierarchical Video Graph Networks for One-Stop Video Delivery." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 1 (January 31, 2022): 1–23. http://dx.doi.org/10.1145/3466886.
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The explosive growth of video data has brought great challenges to video retrieval, which aims to find out related videos from a video collection. Most users are usually not interested in all the content of retrieved videos but have a more fine-grained need. In the meantime, most existing methods can only return a ranked list of retrieved videos lacking a proper way to present the video content. In this paper, we introduce a distinctively new task, namely One-Stop Video Delivery (OSVD) aiming to realize a comprehensive retrieval system with the following merits: it not only retrieves the relevant videos but also filters out irrelevant information and presents compact video content to users, given a natural language query and video collection. To solve this task, we propose an end-to-end Hierarchical Video Graph Reasoning framework (HVGR) , which considers relations of different video levels and jointly accomplishes the one-stop delivery task. Specifically, we decompose the video into three levels, namely the video-level, moment-level, and the clip-level in a coarse-to-fine manner, and apply Graph Neural Networks (GNNs) on the hierarchical graph to model the relations. Furthermore, a pairwise ranking loss named Progressively Refined Loss is proposed based on prior knowledge that there is a relative order of the similarity of query-video, query-moment, and query-clip due to the different granularity of matched information. Extensive experimental results on benchmark datasets demonstrate that the proposed method achieves superior performance compared with baseline methods.
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Lin, Meihan. "Impacts of Short Video to Long Video and the Corresponding Countermeasures: Taking Tencent Video as an Example." Highlights in Science, Engineering and Technology 92 (April 10, 2024): 194–98. http://dx.doi.org/10.54097/rnxg6e63.
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The video industry is a comprehensive field that integrates multiple attributes such as culture, technology, and economy. It uses artificial intelligence and high-tech means as a communication medium, with film and television entertainment content as its core, and has become an important part of the tertiary industry. At the same time, the video industry has a profound impact on people's living conditions and spiritual world. With the rapid rise and prosperity of short videos in recent years, the traditional video industry has been greatly impacted. Taking Tencent Video as an example, this article deeply analyzes the impact of short videos on long videos in terms of copyright and profit and proposes feasible measures to promote Tencent Video to adjust its profit structure and development layout, and further promote the new development of the long video field.
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Handiani, Riana Ezra Savitry Is, and Surya Bintarti. "Pengaruh Conversation Dan Co-Creation Terhadap Customer Loyalty Dengan Mediasi Experience Quality Dan Moderasi Currency Pada Pengguna Layanan Vod Vidio Di Kabupaten Bekasi." Journal of Economic, Bussines and Accounting (COSTING) 7, no. 4 (June 24, 2024): 9159–70. http://dx.doi.org/10.31539/costing.v7i4.10365.
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Since the Covid-19 pandemic arrived in Indonesia, all people have become accustomed to carrying out their activities from inside the house, one of which is watching films. Vidio is an online streaming service platform that provides various online videos such as films, sports broadcasts, original series and many more. The aim of this research is to test the effect customer loyalty to conversation, co-creation, currency and experience quality on the Vidio VoD application service. This research was conducted within the boundaries of the Bekasi Regency community area with a total of 114 respondents, namely users who have used Vidio. The sampling technique used isNonprobability sampling namely by method purposive sampling. This research tests correlation and regression with the help ofsoftware SmartPLS 3.0 is used to test validity and reliability. This research shows that: 1) Activities Conversation carried out by the serviceVideo on Demand Vidio is able to push the level Experience Quality consumer; 2) Co-Creation which is set by the serviceVideo on Demand Vidio is able to push the level Experience Quality consumer; 3) Activities Conversation What is done is able to moderate Currency on serviceVideo on Demand Vidio against the level Experience Quality consumer; 4) Co-Creation determined can moderate Currency on Vidio's Video on Demand service Experience Quality consumer; 5) Experience Quality what consumers feel about the service Video on Demand Vidio is able to push the level Customer Loyalty; 6) Activities Conversation that can be done to mediate Experience Quality on service Video on Demand Vidio against Customer Loyalty; 7) Co-Creation determined to be able to mediate Experience Quality on service Video on Demand Vidio against the level Customer Loyalty.
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Rachmaniar, Rachmaniar, and Renata Anisa. "Video Inovasi Bisnis Kuliner di Youtube (Studi Etnografi Virtual tentang Keberadaan Video-video Inovasi Bisnis Kuliner di Youtube)." Proceeding of Community Development 1 (April 4, 2018): 89. http://dx.doi.org/10.30874/comdev.2017.14.
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The purpose of this study is to analyze the presence of culinary business innovation videos on YouTube, viewed from videos that have high views and video content uploaded by YouTuber related to culinary business innovation videos. The method used in this study is a qualitative method with a virtual ethnography approach to knowing the existence of culinary business innovation videos on YouTube. The main object of this research is the videos related to culinary business innovation on YouTube.Teknik data collection conducted through participatory observation and study of literature. The results of this study indicate that the videos related to culinary business innovation on YouTube that has high views are the videos that many show bananas as the basic ingredients of processed foods made innovatively and can be used as a source of business for anyone. While video content uploaded a lot by YouTuber related to culinary business innovation videos is a food processing video that can be used as a source of business.
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Ji, Wanting, and Ruili Wang. "A Multi-instance Multi-label Dual Learning Approach for Video Captioning." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 2s (June 10, 2021): 1–18. http://dx.doi.org/10.1145/3446792.
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Video captioning is a challenging task in the field of multimedia processing, which aims to generate informative natural language descriptions/captions to describe video contents. Previous video captioning approaches mainly focused on capturing visual information in videos using an encoder-decoder structure to generate video captions. Recently, a new encoder-decoder-reconstructor structure was proposed for video captioning, which captured the information in both videos and captions. Based on this, this article proposes a novel multi-instance multi-label dual learning approach (MIMLDL) to generate video captions based on the encoder-decoder-reconstructor structure. Specifically, MIMLDL contains two modules: caption generation and video reconstruction modules. The caption generation module utilizes a lexical fully convolutional neural network (Lexical FCN) with a weakly supervised multi-instance multi-label learning mechanism to learn a translatable mapping between video regions and lexical labels to generate video captions. Then the video reconstruction module synthesizes visual sequences to reproduce raw videos using the outputs of the caption generation module. A dual learning mechanism fine-tunes the two modules according to the gap between the raw and the reproduced videos. Thus, our approach can minimize the semantic gap between raw videos and the generated captions by minimizing the differences between the reproduced and the raw visual sequences. Experimental results on a benchmark dataset demonstrate that MIMLDL can improve the accuracy of video captioning.
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Nuratika, Sikin, Safra Apriani Zahraa, and M. I. Gunawan. "THE MAKING OF PROFILE VIDEO ABOUT TOURISM IN SIAK REGENCY." INOVISH JOURNAL 4, no. 1 (June 29, 2019): 102. http://dx.doi.org/10.35314/inovish.v4i1.958.
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Tourism is very important in Indonesia. However, there are many ways to promote tourism. One of the ways is through video. In promoting tourism in Siak Regency, many people have made tourism video but only in short videos. They are advertisement videos. The duration of the videos was limited and the dubber explained the exposure of the video used Bahasa Indonesia. Therefore, this profile video about tourism in Siak Regency will help Siak Regency in promoting tourism destinations. The main purpose of this final project is to explain the processes of making a profile video about tourism in Siak Regency. The method of this study is descriptive method. There are several steps in making this video such as collecting data, providing materials recording the video, giving the subtitles, continuing proceed with the process of dubbing, and the last was editing process. This video contains of ten places and a tourism event. This video can be used in order to help students, Tourism Office of Siak Regency, local community, and especially International community get information about the history and the tourism destinations in Siak Regency easily. Tourism is very important in Indonesia. However, there are many ways to promote tourism. One of the ways is through video. In promoting tourism in Siak Regency, many people have made tourism video but only in short videos. They are advertisement videos. The duration of the videos was limited and the dubber explained the exposure of the video used Bahasa Indonesia. Therefore, this profile video about tourism in Siak Regency will help Siak Regency in promoting tourism destinations. The main purpose of this final project is to explain the processes of making a profile video about tourism in Siak Regency. The method of this study is descriptive method. There are several steps in making this video such as collecting data, providing materials,iirecording the video, giving the subtitles, continuing proceed with the process of dubbing, and the last was editing process. This video contains of ten places and a tourism event. This video can be used in order to help students, Tourism Office of Siak Regency, local community, and especially International community get information about the history and the tourism destinations in Siak Regency easily.
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He, Wenjia, Ibrahim Sabek, Yuze Lou, and Michael Cafarella. "PAINE Demo: Optimizing Video Selection Queries with Commonsense Knowledge." Proceedings of the VLDB Endowment 16, no. 12 (August 2023): 3902–5. http://dx.doi.org/10.14778/3611540.3611581.
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Because video is becoming more popular and constitutes a major part of data collection, we have the need to process video selection queries --- selecting videos that contain target objects. However, a naïve scan of a video corpus without optimization would be extremely inefficient due to applying complex detectors to irrelevant videos. This demo presents Paine; a video query system that employs a novel index mechanism to optimize video selection queries via commonsense knowledge. Paine samples video frames to build an inexpensive lossy index, then leverages probabilistic models based on existing commonsense knowledge sources to capture the semantic-level correlation among video frames, thereby allowing Paine to predict the content of unindexed video. These models can predict which videos are likely to satisfy selection predicates so as to avoid Paine from processing irrelevant videos. We will demonstrate a system prototype of Paine for accelerating the processing of video selection queries, allowing VLDB'23 participants to use the Paine interface to run queries. Users can compare Paine with the baseline, the SCAN method.
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Wang, Han, Shangyu Xie, and Yuan Hong. "VideoDP: A Flexible Platform for Video Analytics with Differential Privacy." Proceedings on Privacy Enhancing Technologies 2020, no. 4 (October 1, 2020): 277–96. http://dx.doi.org/10.2478/popets-2020-0073.
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AbstractMassive amounts of videos are ubiquitously generated in personal devices and dedicated video recording facilities. Analyzing such data would be extremely beneficial in real world (e.g., urban traffic analysis). However, videos contain considerable sensitive information, such as human faces, identities and activities. Most of the existing video sanitization techniques simply obfuscate the video by detecting and blurring the region of interests (e.g., faces, vehicle plates, locations and timestamps). Unfortunately, privacy leakage in the blurred video cannot be effectively bounded, especially against unknown background knowledge. In this paper, to our best knowledge, we propose the first differentially private video analytics platform (VideoDP) which flexibly supports different video analyses with rigorous privacy guarantee. Given the input video, VideoDP randomly generates a utility-driven private video in which adding or removing any sensitive visual element (e.g., human, and object) does not significantly affect the output video. Then, different video analyses requested by untrusted video analysts can be flexibly performed over the sanitized video with differential privacy. Finally, we conduct experiments on real videos, and the experimental results demonstrate that VideoDP can generate accurate results for video analytics.
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Delti Kurnia, Septika Rudiamon, and Ramesh Prasad Adhikary. "Utilizing the Inshot Application as A Distance Learning Video." Journal International Inspire Education Technology 1, no. 1 (May 31, 2022): 11–20. http://dx.doi.org/10.55849/jiiet.v1i1.28.
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Distance learning at this time results in low delivery of learning materials and learning objectives are not achieved optimally, because teachers only give assignments without learning video learning media, so students do not really understand the learning material, teachers must make learning media at the same time. distance learning by utilizing advanced technology such as using inshot editing applications in learning videos. The goal is for teachers to better know, understand, and increase knowledge about the use of the inshot video editing application as a learning video editing application during the pandemic, because by knowing how to activate learning videos in the inshot application, teachers or it will be easy to make easy, interesting learning videos. , simple, simple. This inshot application has enough features, various features that can be tried for free without paying, this application can be downloaded via the Google Play store on smartphones. And there are several existing features of the inshot application that can be used such as video, split video in two parts or on several clips, adjust video speed, can speed up or slow down video editing, feature to add live audio recording, can control video volume, can rotate videos, Export video files with HD quality, and can crop or remove watermarks on videos. the advantage of the inshot application in video is that it is easy to find information, many interesting features, and can also set the size of the canvas or video size, can share to social media, the inshot application is very suitable for beginners or make simple videos without being complicated and will not interfere when uploading videos.
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Alpert, Frank, and Chris S. Hodkinson. "Video use in lecture classes: current practices, student perceptions and preferences." Education + Training 61, no. 1 (January 14, 2019): 31–45. http://dx.doi.org/10.1108/et-12-2017-0185.
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Purpose Despite the expansion of e-learning, higher education still involves live lectures, which students often see as “boring”. Lecture classes can be made more engaging and effective by including videos. However, empirical research is yet to report on current video use in lectures, or on student perceptions of and preferences for videos. The purpose of this paper is to fill that knowledge gap. Design/methodology/approach A two-stage mixed-method study used focus groups to gain a rich understanding of student’s video experiences, preferences and the types of videos they are shown. These understandings were utilised in a detailed on-line survey questionnaire, which was completed by a diverse sample of 773 university students, who responded about their recent in-class video experiences. Findings Students report that about 87 per cent of lecture classes included one or more videos. This paper reports on instructor practices, develops a video typology and reports on students’ preferred frequency, type of video, video source, video length and existing vs preferred video integration methods. Practical implications The results provide useful information for educational administrators. Recommendations are made for effective use of videos in lectures by instructors. Originality/value This is the first qualitative and survey research investigating current practice and student perceptions of video use during lecture classes. The authors also conduct the first survey with a broad sample across universities and academic disciplines using the unit of analysis of videos seen per course last week. Typologies of sources of videos, instructional functions, video facilitation techniques and types of videos used during lectures are proposed and then measured.
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Jennefer K Shanthini. "Video Audio Hosting (Internet video, YouTube, Vimeo, Wistia marketing & training strategies)." Recent Research Reviews Journal 2, no. 1 (June 2023): 153–59. http://dx.doi.org/10.36548/rrrj.2023.1.13.
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The objective of this study is to investigate the reasons for making online videos on platforms like Wistia, Twitch and YouTube. The available technologies and tools offered by the video sharing platforms have made the private online activities more professionalized. Even the practice of creating video content is becoming increasingly professionalized and commercialized. The motivations from outsides, which are frequently linked with work, i.e., the external factors are still more important for content creation than intrinsic motivations, which are connected to recreational work. This study illustrates how social impact affects the ideal subscription model for online video platforms. Paid, free, and trial strategies play the major role in choosing the strategy. Positive social influence and negative social influence are two cases provided by revenue models. This study summarizes the different video websites, relationship among the creators, and the online video which are analyzed in terms of its economics.
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Feng, Jinrui. "Review of Research on E-commerce Short Videos." Frontiers in Humanities and Social Sciences 4, no. 4 (April 27, 2024): 235–42. http://dx.doi.org/10.54691/at122k44.
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Short videos are innovative video content created through simple and quick shooting and post-production using smart devices, allowing for instant publication and sharing on social media platforms. Although there are various definitions, short videos are typically considered to be limited to a few minutes in length, easily watchable, diverse in content form, and highly engaging for users. The short video e-commerce model revolves around consumers, utilizing the creation of short video content embedded with product information to synchronize the circulation of products and content, making it one of the primary business models. Its development can be divided into three stages, covering the processes of mutual integration between short video platforms and e-commerce platforms, rapid development, and deep integration. The operational models of short video e-commerce mainly include three forms: "short video + e-commerce," "e-commerce + short video," and "short video e-commerce platform," each with its own characteristics. E-commerce short videos use short videos as carriers to promote product information through content marketing. Users participate in purchase decisions by watching videos, liking, commenting, and other behaviors, representing a specific manifestation of the "short video + e-commerce" model. During the marketing process, users experience sequential transitions from the "viewing" scene to other scenes, with the characteristics of short video content playing an important role in influencing user purchasing decisions.
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Qin, Yi, Ou Ye, and Yan Fu. "An Automatic Near-Duplicate Video Data Cleaning Method Based on a Consistent Feature Hash Ring." Electronics 13, no. 8 (April 17, 2024): 1522. http://dx.doi.org/10.3390/electronics13081522.
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In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issues caused by near-duplicate videos are becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can help uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which makes it difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and initial clustering centers under a condition that prior distribution is unknown, which seriously affects the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-head attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to the results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing studies, simulation results demonstrate the performance of the proposed method.
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Gong, Xiaohui. "A Personalized Recommendation Method for Short Drama Videos Based on External Index Features." Advances in Meteorology 2022 (April 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/3601956.
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Dramatic short videos have quickly gained a huge number of user views in the current short video boom. The information presentation dimension of short videos is higher, and it is easier to be accepted and spread by people. At present, there are a large number of drama short video messages on the Internet. These short video messages have brought serious information overload to users and also brought great challenges to short video operators and video editors. Therefore, how to process short videos quickly has become a research hotspot. The traditional episode recommendation process often adopts collaborative filtering recommendation or content-based recommendation to users, but these methods have certain limitations. Short videos have fast dissemination speed, strong timeliness, and fast hot search speed. These have become the characteristics of short video dissemination. Traditional recommendation methods cannot recommend short videos with high attention and high popularity. To this end, this paper adds external index features to extract short video features and proposes a short video recommendation method based on index features. Using external features to classify and recommend TV series videos, this method can quickly and accurately make recommendations to target customers. Through the experimental analysis, it can be seen that the method in this paper has a good effect.
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Puthumana, Joseph S., Christopher D. Lopez, Alisa Girard, Isabel V. Lake, Ainsley L. Taylor, Kimberly H. Khoo, Alex Rottgers, Robin Yang, and Jordan Halsey. "Evaluating YouTube Video Quality in Orthognathic Surgery Patient Education." FACE 3, no. 1 (February 20, 2022): 80–86. http://dx.doi.org/10.1177/27325016211072899.
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Background: Patients are increasingly accessing consumer-style health information from a variety of web-based platforms. This study aims to assess a popular audio-visual platform for its quality of information in orthognathic procedures. Methods: We queried YouTube on August 12th, 2021 for 20 videos, by both relevance and view count, under each of 3 search terms: (1) “orthognathic surgery,” (2) “LeFort I osteotomy,” and (3) “sagittal split osteotomy.” Each video was characterized by date of upload, time since upload, video duration, video type, and video author. Videos were further characterized by type of video (1) creator and (2) category. The provider-validated instrument DISCERN was applied to each video to assess content quality and bias. Results: Of 60 videos marked for review, 46 were included for analysis. The most common category of video was operative ( n = 18, 36.1%), while the most common creator type was non-physician medical professional ( n = 14, 30.4%). Hospital or physician advertisement videos had the greatest video power index (26 297 ± 44 556), while medical education videos had the least (13 ± 9). Significant differences were found across both video type and video creator in viewership ( P = .008 and .003, respectively) and video power index ( P = .010 and .007), but not duration ( P = .796 and .059). DISCERN scores ranged from 16 to 80 and were subdivided into 5 categories: very poor (16-28), poor (29-41), fair (42-54), good (55-67), and excellent (68-80). Average DISCERN scores for all 46 videos were 17.9 ± 4.9 for reliability, 14.2 ± 4.0 for quality, and 34.3 ± 9.0 for overall. Conclusions: YouTube videos on orthognathic surgery were of overall poor quality. These videos were rated best in relevance to the search parameter and description of treatment but were least helpful in describing alternatives to the treatment and uncertainties about the procedure. Videos created by patients and about patient experiences were rated best for content that was reliable, high quality, and low bias.
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Wen, Hao. "Research on the Advantages of Short Video and the Way to Revive Long Video." Communications in Humanities Research 26, no. 1 (January 3, 2024): 17–20. http://dx.doi.org/10.54254/2753-7064/26/20232005.
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Short video is one of the fastest growing industries at present, and the spread of short video on social media is very large. Long videos not only provide more selectivity, but also change the way humans watch videos. However, in the face of massive content competition, it becomes more difficult to attract viewers, leading to more people choosing to watch short videos. This paper explores the advantages of short video in modern communication, and proposes the revival of long video. Short videos are popular for their concise and clear features, which grab viewers' attention in a fast-paced society. They are easily shared and disseminated across various platforms, expanding the reach of information. Moreover, short videos provide a rich audio-visual experience, making communication more lively and interesting. On the other hand, long videos face challenges such as the dominance of short video platforms, rising membership fees, and copyright restrictions. To revive long videos, platforms can open up copyrights, reduce fees, and improve member benefits. Creators should focus on producing premium content with appealing themes, while the government can promote the import of foreign films to enrich viewing options. Viewers can use their free time to watch long-form videos in theaters or on TV. By addressing these challenges and promoting quality content, long-form videos can thrive alongside short-form videos in the modern media landscape.
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Jacob, Jaimon, M. Sudheep Elayidom, and V. P. Devassia. "Video content analysis and retrieval system using video storytelling and indexing techniques." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (December 1, 2020): 6019. http://dx.doi.org/10.11591/ijece.v10i6.pp6019-6025.
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Videos are used often for communicating ideas, concepts, experience, and situations, because of the significant advances made in video communication technology. The social media platforms enhanced the video usage expeditiously. At, present, recognition of a video is done, using the metadata like video title, video descriptions, and video thumbnails. There are situations like video searcher requires only a video clip on a specific topic from a long video. This paper proposes a novel methodology for the analysis of video content and using video storytelling and indexing techniques for the retrieval of the intended video clip from a long duration video. Video storytelling technique is used for video content analysis and to produce a description of the video. The video description thus created is used for preparation of an index using wormhole algorithm, guarantying the search of a keyword of definite length L, within the minimum worst-case time. This video index can be used by video searching algorithm to retrieve the relevant part of the video by virtue of the frequency of the word in the keyword search of the video index. Instead of downloading and transferring a whole video, the user can download or transfer the specifically necessary video clip. The network constraints associated with the transfer of videos are considerably addressed.
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Jia, Shijie, Tianyin Wang, Xiaoyan Su, and Liuke Liang. "A Novel Video Propagation Strategy Fusing User Interests and Social Influences Based on Assistance of Key Nodes in Social Networks." Electronics 12, no. 3 (January 19, 2023): 532. http://dx.doi.org/10.3390/electronics12030532.
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Accurate video launching and propagation is significant for promotion and distribution of videos. In this paper, we propose a novel video propagation strategy that fuses user interests and social influences based on the assistance of key nodes in social networks (VPII). VPII constructs an estimation model for video distribution capacities in the process of video propagation by investigating interest preference and influence of social users: (1) An estimation method of user preferences for video content is designed by integrating a comparative analysis between current popular videos and historical popular videos. (2) An estimation method to determine the distribution capacities of videos is designed according to scale and importance of neighbor nodes covered. VPII further designs a multi-round video propagation strategy with the assistance of the selected key nodes, which enables these nodes to implement accurate video launching by estimating weighted levels based on available bandwidth and node degree centrality. The video propagation can effectively promote the scale and speed of video sharing and efficiently utilize network resources. Simulations-based testing shows how VPII outperforms other state-of-the-art solutions in terms of startup delay, caching hit ratio, caching cost and higher control overhead.
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Li, Eric. "AI in Video Recommendation System." Highlights in Science, Engineering and Technology 35 (April 11, 2023): 280–85. http://dx.doi.org/10.54097/hset.v35i.7214.
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Short videos are very popular all over the world. Video recommendation system is an essential part in it. It can help people to watch the video that they are interested in. This paper is written for study the specific principle of the video recommendation system. The result was getting through relative literatures and actual test. Short video recommendation systems typically use collaborative filtering and deep learning techniques to achieve this. Collaborative filtering comes in two types: user-based and content-based. User-based collaborative filtering recommends videos to new users based on the viewing behavior of similar users. Content-based collaborative filtering uses video features and similarity to recommend similar videos. Finally, this paper shows how the video web set can learn what is the user’s interest.
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Ma, Zirui, and Bin Gu. "The influence of firm-Generated video on user-Generated video: Evidence from China." International Journal of Engineering Business Management 14 (January 2022): 184797902211186. http://dx.doi.org/10.1177/18479790221118628.
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We examined the impact of firm-generated content on firm-related user-generated content. Researches have proven that firm-related user-generated content impacts firm revenue. Therefore, it is necessary to determine what factors stimulate the creation of firm-related user-generated content. Creating user-generated videos related to companies (e.g. E-sports) on Chinese online video platforms often includes the use of firm-generated videos as material. It may suggest that firm-generated content may play an essential role in influencing Internet users to create firm-related user-generated content. We collected a unique dataset using a Python web crawler and used the LSDV model for empirical analysis, including 2977 firm-generated videos and 49860 user-generated videos, to explore the impact of firm-generated video attributes on user-generated videos. The results show that some attributes of firm-generated video have a significant impact on user-generated video. The number of comments and coins on firm-generated videos positively affects user-generated videos, while the number of favorite on firm-generated videos negatively affects user-generated videos. We also found that the difference in how users feel about firm-generated videos affects the likelihood of users creating their original videos. User engagement and user brand identity in FGV positively impact stimulating user-generated videos. The authors suggest that companies can maximize the impact on user-generated content by targeting the creation of firm-generated content based on these video attributes. The authors also suggest that firms further investigate theories related to motivational factors, such as the impact of consumer engagement, brand identity, and perceived usefulness on user-generated content.
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Liu, Xiulei, Shoulu Hou, Qiang Tong, Xuhong Liu, Zhihui Qin, and Junyang Yu. "A Prediction Approach for Video Hits in Mobile Edge Computing Environment." Security and Communication Networks 2020 (November 17, 2020): 1–6. http://dx.doi.org/10.1155/2020/8857564.
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Smart device users spend most of the fragmentation time in the entertainment applications such as videos and films. The migration and reconstruction of video copies can improve the storage efficiency in distributed mobile edge computing, and the prediction of video hits is the premise for migrating video copies. This paper proposes a new prediction approach for video hits based on the combination of correlation analysis and wavelet neural network (WNN). This is achieved by establishing a video index quantification system and analyzing the correlation between the video to be predicted and already online videos. Then, the similar videos are selected as the influencing factors of video hits. Compared with the autoregressive integrated moving average (ARIMA) and gray prediction, the proposed approach has a higher prediction accuracy and a broader application scope.
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Umar, Rusydi, Abdu Fadlil, and Alfiansyah Imanda Putra. "Analisis Forensics Untuk Mendeteksi Pemalsuan Video." J-SAKTI (Jurnal Sains Komputer dan Informatika) 3, no. 2 (September 13, 2019): 193. http://dx.doi.org/10.30645/j-sakti.v3i2.140.
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The current technology is proving that the ease with which crimes occur using computer science in the field of video editing, in addition from time to time more and more video editing software and increasingly eassy to use, but the development of this technology is widely misused by video creators to manipulate video hoaxes that cause disputes, so many video cases are spread which cannot be trusted by the public. Counterfeiting is an act of modifying documents, products, images or videos, among other media. Forensic video is one of the scientific methods in research that aims to obtain evidence and facts in determining the authenticity of a video. This makes the basis of research to detect video falsification. This study uses analysis with 2 forensic tools, forevid and VideoCleaner. The result of this study is the detection of differences in metadata, hash and contrast of original videos and manipulated videos.
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Park, Jounsup. "Multi-Session Multicasting for 360-Degree Video Multicast over OFDMA Systems." International Journal of Digital Multimedia Broadcasting 2021 (June 16, 2021): 1–19. http://dx.doi.org/10.1155/2021/5560312.
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360-degree video content provides a rich and immersive multimedia experience to viewers by allowing viewers to the video from any angle. However, 360-degree videos require much higher bandwidth to be delivered over mobile networks compared to conventional videos. Multicasting of the videos is one of the solutions to efficiently utilize the limited bandwidth since many viewers share the wireless spectrum resource for popular videos, such as sports events or musical concerts. LTE eMBMS assigns the videos to the video sessions, and multiple viewers can subscribe to the same video allocated to the video sessions. Moreover, the tiling of the 360-degree video makes it possible to control the regional quality of the video. The tiles that are likely to be seen by many viewers should have higher quality than other tiles to satisfy more viewers. In this paper, we proposed the Multi-Session Multicast (MSM) system to optimally allocate the wireless resources to tiles with different qualities to maximize the expected user experience. The experimental results show that the proposed MSM system provides higher quality videos to viewers using limited wireless resources.
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Lin, Ming, Michael Chau, Jinwei Cao, and Jay F. Nunamaker Jr. "Automated Video Segmentation for Lecture Videos." International Journal of Technology and Human Interaction 1, no. 2 (April 2005): 27–45. http://dx.doi.org/10.4018/jthi.2005040102.
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C, Chanjal. "Feature Re-Learning for Video Recommendation." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 3143–49. http://dx.doi.org/10.22214/ijraset.2021.35350.
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Predicting the relevance between two given videos with respect to their visual content is a key component for content-based video recommendation and retrieval. The application is in video recommendation, video annotation, Category or near-duplicate video retrieval, video copy detection and so on. In order to estimate video relevance previous works utilize textual content of videos and lead to poor performance. The proposed method is feature re-learning for video relevance prediction. This work focus on the visual contents to predict the relevance between two videos. A given feature is projected into a new space by an affine transformation. Different from previous works this use a standard triplet ranking loss that optimize the projection process by a novel negative-enhanced triplet ranking loss. In order to generate more training data, propose a data augmentation strategy which works directly on video features. The multi-level augmentation strategy works for video features, which benefits the feature relearning. The proposed augmentation strategy can be flexibly used for frame-level or video-level features. The loss function that consider the absolute similarity of positive pairs and supervise the feature re-learning process and a new formula for video relevance computation.
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Retnani, Ajeng Dwi, Titin Sutini, and Suhendar Sulaeman. "Video Kartun dan Video Animasi dapat Menurunkan Tingkat Kecemasan Pre Operasi pada Anak Usia Pra Sekolah." Jurnal Keperawatan Silampari 3, no. 1 (November 8, 2019): 332–41. http://dx.doi.org/10.31539/jks.v3i1.837.
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The purpose of this study was to analyze the effect of cartoon videos and animated videos on reducing preoperative anxiety levels in pre-school age children. This research method uses quasi-experimental with a pre and post-test approach with out control. The results showed that the reduction in preoperative anxiety levels in pre-school children after being given a cartoon video intervention by 4.20, after being given an animated video intervention by 4.70 and after being given a combination intervention between cartoon videos + animated videos by 7.20. Based on this, the level of preoperative anxiety using a cartoon video + animated video combination intervention showed the greatest decrease. The results of the study also obtained p value> 0,000. Conclusions, the influence of cartoon videos and animated videos on the reduction of preoperative anxiety levels in pre-school age children.
Keywords: Animation, Anxiety, Pre Operation, Cartoon Video
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Li, Hao, Zhaoquan Gu, Lianbing Deng, Yi Han, Cheng Yang, and Zhihong Tian. "A Fine-Grained Video Encryption Service Based on the Cloud-Fog-Local Architecture for Public and Private Videos." Sensors 19, no. 24 (December 5, 2019): 5366. http://dx.doi.org/10.3390/s19245366.
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With the advancement of cloud computing and fog computing, more and more services and data are being moved from local servers to the fog and cloud for processing and storage. Videos are an important part of this movement. However, security issues involved in video moving have drawn wide attention. Although many video-encryption algorithms have been developed to protect local videos, these algorithms fail to solve the new problems faced on the media cloud, such as how to provide a video encryption service to devices with low computing power, how to meet the different encryption requirements for different type of videos, and how to ensure massive video encryption efficiency. To solve these three problems, we propose a cloud-fog-local video encryption framework which consists of a three-layer service model and corresponding key management strategies, a fine-grain video encryption algorithm based on the network abstract layer unit (NALU), and a massive video encryption framework based on Spark. The experiment proves that our proposed solution can meet the different encryption requirements for public videos and private videos. Moreover, in the experiment environment, our encryption algorithm for public videos reaches a speed of 1708 Mbps, and can provide a real-time encryption service for at least 42 channels of 4K-resolution videos.
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Cheng, Tian. "Analysis of Video Media Management Mode from Pear Video." Communication, Society and Media 7, no. 2 (July 24, 2024): p29. http://dx.doi.org/10.22158/csm.v7n2p29.
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Nowadays, the way of video communication has undergone great changes, the public has rarely watched videos through traditional TV, and the market users have been constantly divided. Tiktok, Kuaishou, micro-vision quickly occupied the short video market, B station occupied the video hegemon seat, “Love Youteng” three long-term in the long video industry top position. In this context, major TV stations and video media production teams have tried to transform and upgrade video media. Pear video is a short video platform in China so far, focusing on short information video and doing very successful in the field. From the current model of Pear video, we can study and analyze the trend of video media management.
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Gernsbacher, Morton Ann. "Video Captions Benefit Everyone." Policy Insights from the Behavioral and Brain Sciences 2, no. 1 (October 2015): 195–202. http://dx.doi.org/10.1177/2372732215602130.
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Video captions, also known as same-language subtitles, benefit everyone who watches videos (children, adolescents, college students, and adults). More than 100 empirical studies document that captioning a video improves comprehension of, attention to, and memory for the video. Captions are particularly beneficial for persons watching videos in their non-native language, for children and adults learning to read, and for persons who are D/deaf or hard of hearing. However, despite U.S. laws, which require captioning in most workplace and educational contexts, many video audiences and video creators are naïve about the legal mandate to caption, much less the empirical benefit of captions.
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Mardhiyana, Dewi, Ariesma Setyarum, and Amalia Fitri. "Penggunaan Video Interaktif Edpuzzle dalam Pembelajaran Matematika dan Bahasa pada Era Merdeka Belajar di SMP Al Fusha Kedungwuni." Bubungan Tinggi: Jurnal Pengabdian Masyarakat 4, no. 4 (December 30, 2022): 1671. http://dx.doi.org/10.20527/btjpm.v4i4.6139.
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Salah satu pembelajaran yang inovatif dan kreatif bisa dilakukan dengan menggunakan media pembelajaran yang menarik, seperti video interaktif. Edpuzzle adalah salah satu platform yang bisa membantu guru dalam melaksanakan pembelajaran melalui video yang bersifat interaktif antara guru dan siswa. Tujuan dari kegiatan pengabdian ini adalah pemanfaatan video interaktif edpuzzle dalam pembelajaran Matematika dan Bahasa sebagai inovasi pembelajaran untuk mengatasi rendahnya minat belajar siswa dan kurangnya literasi teknologi guru. Metode yang digunakan dalam pengabdian ini dengan memberikan pelatihan dan pendampingan. Kegiatan pengabdian ini diberikan kepada guru SMP Al Fusha Kedungwuni selama bulan Agustus 2021. Kegiatan pengabdian ini dirancang dalam beberapa tahap, yaitu perencanaan, pelaksanaan pelatihan, follow up hasil pelatihan, dan evaluasi. Pada perencanaan dilakukan penyusunan bahan sosialisasi, bahan pelatihan, dan soal pretest. Pada pelaksanaan pelatihan, kegiatan dimulai dengan pemberian soal pre-test, sosialisasi video interaktif edpuzzle, pelatihan penyusunan konten video pembelajaran, dan pelatihan pembuatan video interaktif edpuzzle. Hasil pre-test menunjukkan bahwa sebanyak 67% peserta sudah mengetahui video interaktif dan manfaat video interaktif. Namun, belum ada peserta yang pernah mendengar istilah edpuzzle. Oleh karena itu diperlukan pelatihan pembuatan video interaktif edpuzzle. Tahap selanjutnya, yaitu follow up hasil pelatihan, yang dilakukan dengan pendampingan penyusunan konten video pembelajaran dan pembuatan video pembelajaran serta pengeditan video dengan menggunakan edpuzzle. Tahap terakhir, yaitu evaluasi yang dilakukan denan pemberian post-test kepada peserta pelatihan. Hasil post-test menunjukkan bahwa 83% peserta mengetahui video interaktif dan manfaat video interaktif. Selain itu, 67% peserta juga bisa menjelaskan tentang edpuzzle, serta kegunaan dan fitur-fitur yang ada di dalam edpuzzle. Setelah kegiatan ini peserta sudah memiliki kemampuan untuk menyusun video interaktif dengan menggunakan edpuzzle.One innovative and creative learning can be done using interesting learning media, such as interactive videos. Edpuzzle is a platform that can help teachers carry out learning through interactive videos between teachers and students. This service activity's purpose is to use interactive edpuzzle videos in Mathematics and Language learning as a learning innovation to overcome the low interest in student learning and the lack of teacher technological literacy. The method used in this service is to provide training and mentoring. This service activity was given to teachers of SMP Al Fusha Kedungwuni in August 2021. This service activity was designed in several stages: planning, implementing training, following up on training results, and evaluating. In planning, the preparation of socialization materials, training materials, and pretest questions was carried out. In the implementation of the training, the activities began with giving pretest questions, socialization of interactive edpuzzle videos, training in the preparation of learning video content, and training on making interactive edpuzzle videos. The pretest results showed that as many as 67% of the participants already knew about interactive videos and the benefits of interactive videos. However, the participants had yet to hear of the term edpuzzle. Therefore, training in making interactive edpuzzle videos is needed. The next stage is the follow-up of the training results, which is carried out by preparing learning video content, making learning videos, and editing videos using edpuzzles. The last stage, namely the evaluation conducted by giving a post-test to the training participants. The post-test results showed that 83% of the participants knew about interactive videos and the benefits of interactive videos. In addition, 67% of participants were also able to explain the edpuzzle, as well as the uses and features of edpuzzle. After this activity, the participants can already compile interactive videos using edpuzzle.
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Luo, Yong, Guochang Zhou, Jianping Li, and Xiao Xiao. "A MOOC Video Viewing Behavior Analysis Algorithm." Mathematical Problems in Engineering 2018 (October 16, 2018): 1–7. http://dx.doi.org/10.1155/2018/7560805.
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MOOCs (massive open online courses) are developing rapidly, but they also face many problems. As the MOOC’s most important resource, the course videos have a very important influence on the learning. This article defines the ratio R (R=Average viewing duration/Video length), which reflects the popularity of the video. By analyzing the relationship between the video length, release time, and R, we found a significant negative linear correlation between video length and R and video release time and R. However, when the number of videos is less than the threshold, the release time has less influence on R. This paper presents a video viewing behavior analysis algorithm based on multiple linear regression. The residual independence test proved that the algorithm has a good approximation to the data. It can predict the popularity of similar course videos to help producers optimize video design.
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Fu, Hailin. "The Impact of Short videos on People's Consumption Habits." Journal of Education, Humanities and Social Sciences 23 (December 13, 2023): 348–52. http://dx.doi.org/10.54097/ehss.v23i.12918.
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This article aims to analyze and summarize the changes in consumption habits caused by short video users due to the influence of short video through the literature review and the research of short video software. At the same time, the different age groups of users are affected by short videos. This article analyzes the different marketing strategies and methods of introducing products between different short video platforms. And the influencing factors of short videos and users' personal responses are studied. In addition, this paper combines short video audiences and consumers' personal factors to analyze the impact of short videos on people's consumption behavior. While focusing on the analysis of the short video platform- -TikTok, it is also compared with other platforms. At the same time, the advantages and disadvantages of short video marketing are analyzed, because of the risks brought by false propaganda.
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Luo, Lei, Rong Xin Jiang, Xiang Tian, and Yao Wu Chen. "Reference Viewpoints Selection for Multi-View Video Plus Depth Coding Based on the Network Bandwidth Constraint." Applied Mechanics and Materials 303-306 (February 2013): 2134–38. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2134.
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In multi-view video plus depth (MVD) coding based free viewpoint video applications, a few reference viewpoints’ texture and depth videos should be compressed and transmitted at the server side. At the terminal side, the display view videos could be the decoded reference view videos or the virtual viewpoints’ videos which are synthesized by DIBR technology. The entire video quality of all display views are decided by the number of reference viewpoints and the compression distortion of each reference viewpoint’s texture and depth videos. This paper studies the impact of the reference viewpoints selection on the entire video quality of all display views. The results show that depending on the available network bandwidth, the MVD coding requires different selections of reference viewpoints to maximize the entire video quality of all display views.
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Kumar, Anil, and Umesh Chandra Jaiswal. "Comparative Analysis of Sentiments in Children with Neurodevelopmental Disorders." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 12 (December 29, 2023): e31469. http://dx.doi.org/10.14201/adcaij.31469.
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In-group favoritism is the tendency of people where, individuals tend to punish transgressors with varying intensity based on whether they belong to their own group or not. In this cross-sectional analytical study, we examine matched samples of children with developmental disorders, observing their perspectives on punishment after watching two videos in which rules are broken. Data (video 1) shows a football player from the viewer’s country scoring a handball goal, while in data (video 2), a foreign player replicates the same action against the host nation. Every contestant viewed both videos, and their responses were then compared. Our proposed methods compare and analyze the data to determine player’s opinions using artificial intelligence-based machine learning such as text analysis and opinion, extract on- favorable, unfavorable, neutral feelings, or emotions. In both sets of data, the autism spectrum disorder (ASD) group displayed negative emotions for both video 1 (M = −.1; CI 90% −.41 to .21) and video 2 (t (7) = 1.54, p =.12; M = -.42; CI 90% 76 to -.08). On the contrary, the groups with attention deficit hyperactivity disorder (ADHD), learning disabilities (LD), and intellectual disability (ID) had a favorable reaction to video1 but an unfavorable reaction to video 2. Children diagnosed with ASD typically display a consistent adherence to rules, even when those breaking the rules are not part of their group. This behavior may be linked to lower levels of empathy.
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Laghari, Asif Ali, Hui He, Shahid Karim, Himat Ali Shah, and Nabin Kumar Karn. "Quality of Experience Assessment of Video Quality in Social Clouds." Wireless Communications and Mobile Computing 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/8313942.
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Video sharing on social clouds is popular among the users around the world. High-Definition (HD) videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS). Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE) level of end users. To assess the QoE of video compression, we conducted subjective (QoE) experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.
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Nguyen, Cuong, Wu-chi Feng, and Feng Liu. "Hotspot: Making computer vision more effective for human video surveillance." Information Visualization 15, no. 4 (July 25, 2016): 273–85. http://dx.doi.org/10.1177/1473871616630015.
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Studies have shown that the human capability of monitoring multiple surveillance videos is limited. Computer vision techniques have been developed to detect abnormal events to support human video surveillance; however, their results are often unreliable, thus distracting surveillance operators and making them miss important events. This article presents Hotspot as a surveillance video visualization system that can effectively leverage noisy computer vision techniques to support human video surveillance. Hotspot consists of two views: a designated focus view to summarize videos with detected events and a video-bank view surrounding the focus view to display source surveillance videos. The focus view allows an operator to quickly dismiss false alarms and focus on true alarms. The video-bank view allows for extended human video analysis after an important event is detected. Hotspot further provides visual links to assist quick attention switch from the focus view to the video-bank view. Our experiments show that Hotspot can effectively integrate noisy, automatic computer vision detection results and better support human video surveillance tasks than the baseline video surveillance with no or only basic computer vision support.
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Desai, T. S., and D. C. Kulkarni. "Assessment of Interactive Video to Enhance Learning Experience: A Case Study." Journal of Engineering Education Transformations 35, S1 (January 1, 2022): 74–80. http://dx.doi.org/10.16920/jeet/2022/v35is1/22011.
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In modern STEM classrooms, video learning holds an important place, since it offers flexibility of time, place and content. But a lot of improvement is needed to enhance the learning experience because conventional video lecture lacks interaction that is indispensable component of teaching – learning process. Interactive video is highly recommended to resolve this issue as it allows proactive and random access to video content and promotes learner – content interactivity by inserting interactive elements. Interactive kind of video facilitates students’ engagement and active learning through incorporated interactive components. Present study employed two settings: learning using demonstrative video and learning using interactive video. It is observed that, students’ performance enhanced significantly in the post video quiz of interactive video and thus interactive video leads to better learners’ satisfaction. A study was carried out with 240 number of first year Engineering students for the course of Applied Physics. We collected data from post- video quiz performance and feedback from the students. The grades obtained by the students in post-video quiz for demonstrative and interactive videos were compared. For the interactive type of videos, the average marks scored were 82.79% and for demonstrative type of videos, average marks obtained were of 64.41%. This study brings forth superiority of interactive video over linear, demonstrative video as it offers enhancement of the level of conceptual understanding and attainment of desired learning outcomes through the management of cognitive and germane load by enhancing students’ engagement through active learning. Keywords—cognitive load; demonstrative video; germane load; interactive video; Learning Design; learning outcomes.
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Christodoulou, Vasiliki, Vaggelis Saprikis, Louiza Kythreotou, Monogios Christodoulos, Ece Calikus, and Jared Joselowitz. "Video features predicting engagement in climate change education." E3S Web of Conferences 436 (2023): 06009. http://dx.doi.org/10.1051/e3sconf/202343606009.
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Climate change is a substantial threat. Awareness-raising and education are key goals. Social media provide an opportune context for the delivery of science education content. However, little research has examined which video features elicit engagement on climate change. This project focused on YouTube and aimed to identify the most predictive factors of video engagement on the topic of climate change. Video engagement was defined as an algorithmic composite of outcomes derived through YouTube API such as the number of views and number of comments, among other measures. A search of YouTube videos revealed an original list of 183 videos on climate change. A random selection of 90 videos was manually coded on engagement predictor variables (i.e., video type, presenter type, audio-visual elements, video content, and other features). Results indicated that most YouTube videos are consistent with a widely accepted scientific viewpoint on the topic although their scientific quality and video argumentation content do not appear to affect video engagement. Rather, presenter and video characteristics associated with entertainment emerge as more specific predictors influencing video engagement. Social media can be used as a fruitful avenue for imparting education on pertinent issues such as climate change although it is important to consider ways of balancing quality education with entertainment features.
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Wicaksana, Inovensius Hugo Bima. "Application of Video Mapping Technique in Kotak Band Video Music." Business Economic, Communication, and Social Sciences (BECOSS) Journal 4, no. 2 (June 4, 2022): 89–96. http://dx.doi.org/10.21512/becossjournal.v4i2.7963.
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In the current development of visual videography technology, especially in the creation of music video content, new media are developing very rapidly, one of which is video projection (Projection Mapping). apart from the screen. Video Mapping is one of the newest video projection techniques used to convert almost any surface into a dynamic video display. The purpose of video mapping is to create the physical illusion of an image by combining visual elements. Most of the mapping projects are used in fashion shows, corporate events, concerts, and theater performances and can be an asset in artistic music videos. This research explains how to implement video projection into an artistic asset. Then displayed in public spaces to reach a wider audience. This paper will focus on the aspect of video mapping with the technical aspects of developing the concept of the Musik Video Kotak Band project entitled Wings of Garuda by using visual elements of applying visual video mapping in music videos to convey visual messages in video projections on the faces of the band members of the Kotak band. visual delivery in projection mapping creates artistic innovation in music video visuals to minimize the number of production teams in music video projects and messages in video projection visuals can convey their messages, the visuals will be perfected in the editing process to achieve the desired contrast so that video projections on the face more visible detail.
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Hanson, Anne M. ""Video after Video"." English Journal 81, no. 4 (April 1992): 97. http://dx.doi.org/10.2307/819953.
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Wu, Yihong, Mingli Lin, and Wenlong Yao. "The Influence of Titles on YouTube Trending Videos." Communications in Humanities Research 29, no. 1 (April 19, 2024): 285–94. http://dx.doi.org/10.54254/2753-7064/29/20230835.
Full textAbstract:
The global video platform market has been growing in a remarkable way in recent years. As a part of a video, title can compel people to view. However, few scholars have studied the relationship between video trendiness and title at present. This work studies the influence of sentiment polarity of videos using Valence Aware Dictionary Sentiment Reasoner (VADER) and investigated the feasibility of the application of video titles text on YouTube trending videos research using Doc2Vec. It is found that the text in YouTube trend video titles possesses predictive value for video trendiness, but it requires advanced techniques such as deep learning for full exploitation. The sentiment polawrity in titles impacts the video views and this impact varies across video categories.
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Hazra, Debapriya, and Yung-Cheol Byun. "Upsampling Real-Time, Low-Resolution CCTV Videos Using Generative Adversarial Networks." Electronics 9, no. 8 (August 14, 2020): 1312. http://dx.doi.org/10.3390/electronics9081312.
Full textAbstract:
Video super-resolution has become an emerging topic in the field of machine learning. The generative adversarial network is a framework that is widely used to develop solutions for low-resolution videos. Video surveillance using closed-circuit television (CCTV) is significant in every field, all over the world. A common problem with CCTV videos is sudden video loss or poor quality. In this paper, we propose a generative adversarial network that implements spatio-temporal generators and discriminators to enhance real-time low-resolution CCTV videos to high-resolution. The proposed model considers both foreground and background motion of a CCTV video and effectively models the spatial and temporal consistency from low-resolution video frames to generate high-resolution videos. Quantitative and qualitative experiments on benchmark datasets, including Kinetics-700, UCF101, HMDB51 and IITH_Helmet2, showed that our model outperforms the existing GAN models for video super-resolution.
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Rachmatullah, Muhammad Naufal, Sutarno Sutarno, and Rahmat Fadli Isnanto. "Video Annomaly Classification Using Convolutional Neural Network." Computer Engineering and Applications Journal 13, no. 1 (February 1, 2024): 74–82. http://dx.doi.org/10.18495/comengapp.v13i1.468.
Full textAbstract:
The use of surveillance videos is increasingly popular in city monitoring systems. Generally, the analysis process in surveillance videos still relies on conventional methods. This method requires professional personnel to constantly monitor and analyze videos to identify abnormal events. Consequently, the conventional approach is time-consuming, resource-intensive, and costly. Therefore, a system is needed to automatically detect video anomalies, reducing the massive human resource utilization for video monitoring. This research employs deep learning methods to classify anomalies in videos. The video anomaly detection process involves transforming the video into image format by extracting each frame present in the video. Subsequently, a Convolutional Neural Network (CNN) model is utilized to classify anomalous events within the video. Testing results using the CNN architectures DenseNet121 and EfficientNet V2 yielded performance accuracies of 87% and 75%, respectively. The testing results indicate that the DenseNet121 architecture outperforms the EfficientNetV2 architecture in terms of performance.
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Luo, Dezhao, Yu Zhou, Bo Fang, Yucan Zhou, Dayan Wu, and Weiping Wang. "Exploring Relations in Untrimmed Videos for Self-Supervised Learning." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 1s (February 28, 2022): 1–21. http://dx.doi.org/10.1145/3473342.
Full textAbstract:
Existing video self-supervised learning methods mainly rely on trimmed videos for model training. They apply their methods and verify the effectiveness on trimmed video datasets including UCF101 and Kinetics-400, among others. However, trimmed datasets are manually annotated from untrimmed videos. In this sense, these methods are not truly unsupervised. In this article, we propose a novel self-supervised method, referred to as Exploring Relations in Untrimmed Videos (ERUV), which can be straightforwardly applied to untrimmed videos (real unlabeled) to learn spatio-temporal features. ERUV first generates single-shot videos by shot change detection. After that, some designed sampling strategies are used to model relations for video clips. The strategies are saved as our self-supervision signals. Finally, the network learns representations by predicting the category of relations between the video clips. ERUV is able to compare the differences and similarities of video clips, which is also an essential procedure for video-related tasks. We validate our learned models with action recognition, video retrieval, and action similarity labeling tasks with four kinds of 3D convolutional neural networks. Experimental results show that ERUV is able to learn richer representations with untrimmed videos, and it outperforms state-of-the-art self-supervised methods with significant margins.
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Pan, Tung-Ming, Kuo-Chin Fan, and Yuan-Kai Wang. "Object-Based Approach for Adaptive Source Coding of Surveillance Video." Applied Sciences 9, no. 10 (May 16, 2019): 2003. http://dx.doi.org/10.3390/app9102003.
Full textAbstract:
Intelligent analysis of surveillance videos over networks requires high recognition accuracy by analyzing good-quality videos that however introduce significant bandwidth requirement. Degraded video quality because of high object dynamics under wireless video transmission induces more critical issues to the success of smart video surveillance. In this paper, an object-based source coding method is proposed to preserve constant quality of video streaming over wireless networks. The inverse relationship between video quality and object dynamics (i.e., decreasing video quality due to the occurrence of large and fast-moving objects) is characterized statistically as a linear model. A regression algorithm that uses robust M-estimator statistics is proposed to construct the linear model with respect to different bitrates. The linear model is applied to predict the bitrate increment required to enhance video quality. A simulated wireless environment is set up to verify the proposed method under different wireless situations. Experiments with real surveillance videos of a variety of object dynamics are conducted to evaluate the performance of the method. Experimental results demonstrate significant improvement of streaming videos relative to both visual and quantitative aspects.
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Lo, Shi Wei. "Video Matching by One-Dimensional PSNR Profile." Applied Mechanics and Materials 479-480 (December 2013): 174–78. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.174.
Full textAbstract:
This paper addresses a compact framework to matching video sequences through a PSNR-based profile. This simplify video profile is suitable to matching process when apply in disordered undersea videos. As opposed to using color and motion feature across the video sequence, we use the image quality of successive frames to be a feature of videos. We employ the PSNR quality feature to be a video profile rather than the complex contend-based analysis. The experimental results show that the proposed approach permits accurate of matching video. The performance is satisfactory on determine correct video from undersea dataset.