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Статті в журналах з теми "STREAMING SITES"
Chowdhury, Sugnik Roy. "Twitter Data Analysis by Live Streaming." Journal of Computational and Theoretical Nanoscience 16, no. 8 (August 1, 2019): 3178–82. http://dx.doi.org/10.1166/jctn.2019.8156.
Повний текст джерелаAlmatarneh, Feras Mohammed. "Investigating the Network Characteristics of Two Popular Web-Based Video Streaming Sites." European Scientific Journal, ESJ 13, no. 33 (November 30, 2017): 305. http://dx.doi.org/10.19044/esj.2017.v13n33p305.
Повний текст джерелаKitamura, Masahiko, Daisuke Shirai, Kunitake Kaneko, Takahiro Murooka, Tomoko Sawabe, Tatsuya Fujii, and Atsushi Takahara. "Beyond 4K: 8K 60p live video streaming to multiple sites." Future Generation Computer Systems 27, no. 7 (July 2011): 952–59. http://dx.doi.org/10.1016/j.future.2010.11.025.
Повний текст джерелаMai, Thoai Diem Phuong, Anh Tho To, Thi Hong Minh Trinh, Thi Thoa Nguyen, and Thi Thanh Trang Le. "Para-Social Interaction and Trust in Live-Streaming Sellers." Emerging Science Journal 7, no. 3 (May 3, 2023): 744–54. http://dx.doi.org/10.28991/esj-2023-07-03-06.
Повний текст джерелаHamilton, Robert. "YouTube For Two: Online Video Resources In A Student-Centered, Task-Based ESL/EFL Environment." Contemporary Issues in Education Research (CIER) 3, no. 8 (November 9, 2010): 27. http://dx.doi.org/10.19030/cier.v3i8.224.
Повний текст джерелаBlacklock, J. Bob, Donald C. Wright, Robert L. Dedrick, Ronald G. Blasberg, Robert J. Lutz, John L. Doppman, and Edward H. Oldfield. "Drug streaming during intra-arterial chemotherapy." Journal of Neurosurgery 64, no. 2 (February 1986): 284–91. http://dx.doi.org/10.3171/jns.1986.64.2.0284.
Повний текст джерелаDruschke, Maik, Anna T. P. Schauer, Simon C. O. Glover, and Ralf S. Klessen. "Shape and spin of minihaloes – II. The effect of streaming velocities." Monthly Notices of the Royal Astronomical Society 498, no. 4 (August 29, 2020): 4839–52. http://dx.doi.org/10.1093/mnras/staa2605.
Повний текст джерелаMoreno-García, María N. "Information Retrieval and Social Media Mining." Information 11, no. 12 (December 11, 2020): 578. http://dx.doi.org/10.3390/info11120578.
Повний текст джерелаGondara, Lovedeep, and Ke Wang. "PubSub-ML: A Model Streaming Alternative to Federated Learning." Proceedings on Privacy Enhancing Technologies 2023, no. 2 (April 2023): 464–79. http://dx.doi.org/10.56553/popets-2023-0063.
Повний текст джерелаNair, Lekha R., Sujala D. Shetty, and Siddhant Deepak Shetty. "Streaming Big Data Analysis for Real-Time Sentiment based Targeted Advertising." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (February 1, 2017): 402. http://dx.doi.org/10.11591/ijece.v7i1.pp402-407.
Повний текст джерелаДисертації з теми "STREAMING SITES"
Shuai, Yongtao [Verfasser], and Thorsten [Akademischer Betreuer] Herfet. "Dynamic adaptive video streaming with minimal buffer sizes / Yongtao Shuai ; Betreuer: Thorsten Herfet." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/1169132545/34.
Повний текст джерелаKhokhar, Muhammad Jawad. "Modélisation de la qualité d'expérience de la vidéo streaming dans l'internet par expérimentation contrôlée et apprentissage machine." Thesis, Université Côte d'Azur (ComUE), 2019. http://www.theses.fr/2019AZUR4067.
Повний текст джерелаVideo streaming is the dominant contributor of today's Internet traffic. Consequently, estimating Quality of Experience (QoE) for video streaming is of paramount importance for network operators. The QoE of video streaming is directly dependent on the network conditions (e.g., bandwidth, delay, packet loss rate) referred to as the network Quality of Service (QoS). This inherent relationship between the QoS and the QoE motivates the use of supervised Machine Learning (ML) to build models that map the network QoS to the video QoE. In most ML works on QoE modeling, the training data is usually gathered in the wild by crowdsourcing or generated inside the service provider networks. However, such data is not easily accessible to the general research community. Consequently, the training data if not available beforehand, needs to be built up by controlled experimentation. Here, the target application is run under emulated network environments to build models that predict video QoE from network QoS. The network QoS can be actively measured outside the data plane of the application (outband), or measured passively from the video traffic (inband). These two distinct types of QoS correspond to the use cases of QoE forecasting (from end user devices) and QoE monitoring (from within the networks). In this thesis, we consider the challenges associated with network QoS-QoE modeling, which are 1) the large training cost of QoE modeling by controlled experimentation, and 2) the accurate prediction of QoE considering the large diversity of video contents and the encryption deployed by today's content providers. Firstly, QoE modeling by controlled experimentation is challenging due to the high training cost involved as each experiment usually consumes some non-negligible time to complete and the experimental space to cover is large (power the number of QoS features). The conventional approach is to experiment with QoS samples uniformly sampled in the entire experimental space. However, uniform sampling can result in significant similarity in the output labels, which increases the training cost while not providing much gain in the model accuracy. To tackle this problem, we advocate the use of active learning to reduce the number of experiments while not impacting accuracy. We consider the case of YouTube QoE modeling and show that active sampling provides a significant gain over uniform sampling in terms of achieving higher modeling accuracy with fewer experiments. We further evaluate our approach with synthetic datasets and show that the gain is dependent on the complexity of the experimental space. Overall, we present a sampling approach that is general and can be used in any QoSQoE modeling scenario provided that the input QoS features are fully controllable. Secondly, accurate prediction of QoE of video streaming can be challenging as videos offered by today's content providers vary significantly from fast motion sports videos to static lectures. On top of that, today's video traffic is encrypted, which means that network operators have little visibility into the video traffic making QoE monitoring difficult. Considering these challenges, we devise models that aim at accurate forecasting and monitoring of video QoE. For the scenario of QoE forecasting, we build a QoE indicator called YouScore that quantifies the percentage of videos in the catalog of a content provider that may play out smoothly (without interruptions) for a given outband network QoS. For the QoE monitoring scenario, we estimate the QoE using the inband QoS features obtained from the encrypted video traffic. Overall, for both scenarios (forecasting and monitoring), we highlight the importance of using features that characterize the video content to improve the accuracy of QoE modeling
PRAGYA. "ASSESSING THE POTENTIAL OF OTT PLATFORMS DURING THE PANDEMIC." Thesis, 2022. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19696.
Повний текст джерелаCaetano, Miguel Afonso. "Cultura P2P: uma análise sociológica comparativa das redes e dos sites de partilha online de músicas, filmes e livros eletrónicos em Portugal e no Brasil." Doctoral thesis, 2016. http://hdl.handle.net/10071/12456.
Повний текст джерелаThis thesis has for its main goal to help fill the gap of theoretical and empirical research originating from Portuguese-speaking countries concerning the apparent clash between the rights of Internet users and the enforcement of intellectual property laws. By way of an interdisciplinary lens gathering contributions from communication science, sociology, economics and law, it intends to shed light on the new role of users of cultural works as distributors – a role amplified by informal platforms parallel to formal distribution circuits. The first part, of a theoretical nature, starts with a historical genealogy of concepts such as piracy, copyright, droit d’auteur and intellectual property, followed by a presentation of the technological and commercial evolution of file sharing over the past decade and a half. Next comes an overview of the most relevant literature on the relationship between sales and unauthorized copies of information goods, as well as a synthesis of the main results of hundreds of quantitative studies covering the behaviors of filesharers and their motives for downloading copyrighted works. Finally, this part ends with a comparative analysis of a set of statistical indicators regarding the penetration levels of ICTs in Portugal and Brazil as well as on the most popular online activities of Internet users in both countries. The second part comprises an empirical analysis of the behaviors and perceptions of Portuguese and Brazilian users of peer-to-peer (P2P) networks and sites enabling the unauthorized copying of copyrighted works. The analysis will be based on the answers of 301 individuals of both nationalities to an online survey, as well as on the subsequent statements made by 16 of these respondents in the context of a series of online interviews. With this research, it is my aim to show that, rather than being only a market failure, sharing is instead a fundamental dimension of culture (Aigrain 2011) Seen in this light, the constraints of an economic perspective exclusively aimed at measuring any possible losses become evident.
Книги з теми "STREAMING SITES"
Alvear, Jose. Web developer.com guide to streaming multimedia. New York: Wiley, 1998.
Знайти повний текст джерелаUnited States. Congress. House. Committee on the Judiciary. Subcommittee on Intellectual Property, Competition, and the Internet. Promoting investment and protecting commerce online: Legitimate sites v. parasites. Washington: U.S. G.P.O., 2013.
Знайти повний текст джерелаHTML5 multimedia: Develop and design. Berkeley, Calif: Peachpit Press, 2012.
Знайти повний текст джерелаUnited States. Environmental Protection Agency. Office of Solid Waste and Emergency Response and Brownfields Technology Support Center (U.S.), eds. Using the triad approach to streamline brownfields site assessment and cleanup. Washington, DC: U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, Brownfields Technology Support Center, 2003.
Знайти повний текст джерелаUnited States. Environmental Protection Agency. Office of Solid Waste and Emergency Response. and Brownfields Technology Support Center (U.S.), eds. Using the triad approach to streamline brownfields site assessment and cleanup. Washington, DC: U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, Brownfields Technology Support Center, 2003.
Знайти повний текст джерелаMastering internet video: A guide to streaming and on-demand video. Boston: Addison-Wesley, 2005.
Знайти повний текст джерелаStreaming and digital media: Understanding the business and technology. Burlington, MA, USA: Focal Press, 2007.
Знайти повний текст джерелаDepartment of Energy: Additional opportunities exist to streamline support functions at NNSA and Office of Science sites : report to congressional requesters. Washington, D.C.]: U.S. Govt. Accountability Office, 2012.
Знайти повний текст джерелаFerrate, Andres. Building web apps for Google TV. Sebastopol, CA: O'Reilly Media, 2011.
Знайти повний текст джерелаScalable video on demand: Adaptive Internet-based distribution. Hoboken, NJ: J. Wiley & Sons, 2005.
Знайти повний текст джерелаЧастини книг з теми "STREAMING SITES"
Furukawa, Gavin. "The Widening Road: Constructions of Gay Japanese Men on YouTube." In Gender in Japanese Popular Culture, 151–74. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-12942-1_6.
Повний текст джерелаLiu, Chuang, Sujie Shao, Shaoyong Guo, and Xuesong Qiu. "WebRTC-Based On-Site Operation and Maintenance Adaptive Video Streaming Rate Control Strategy." In Security with Intelligent Computing and Big-data Services, 292–303. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16946-6_23.
Повний текст джерелаZhang, Chi, and Xiaojie Wang. "On-Site Dance Teaching Live Broadcast System Based on Internet Streaming Media Technology." In Cyber Security Intelligence and Analytics, 457–63. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97874-7_59.
Повний текст джерелаNawaz, Shahid, Asad Waqar Malik, and Raihan ur Rasool. "Ceaseless Virtual Appliance Streaming." In Advances in Data Mining and Database Management, 70–84. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9767-6.ch005.
Повний текст джерелаSendhilvel, Lavanya, Kush Diwakar Desai, Simran Adake, Rachit Bisaria, and Hemang Ghanshyambhai Vekariya. "Twitter Data Analysis Using Apache Streaming." In Convergence of Big Data Technologies and Computational Intelligent Techniques, 61–75. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5264-6.ch002.
Повний текст джерелаStewart, Jennifer. "Could Television Streaming Sites Lead the Charge for Film-Induced Tourism Post COVID?" In Global Perspectives on Literary Tourism and Film-Induced Tourism, 217–39. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8262-6.ch012.
Повний текст джерелаSkondras, Emmanouil, Konstantina Siountri, Angelos Michalas, and Dimitrios D. Vergados. "Personalized Real-Time Virtual Tours in Places With Cultural Interest." In Destination Management and Marketing, 802–20. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2469-5.ch044.
Повний текст джерелаEbara, Yasuo. "Tele-Immersive Collaborative Environment with Tiled Display Wall." In E-Activity and Intelligent Web Construction, 75–84. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61520-871-5.ch007.
Повний текст джерелаAkgun, Ozgur. "The Role of New Media in Contemporary Entertainment Culture." In Advances in Media, Entertainment, and the Arts, 542–57. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6190-5.ch029.
Повний текст джерелаSharma, Sunil, and Minakshi Sharma. "Applications of Deep Learning-Based Product Recommendation Systems." In Advances in Web Technologies and Engineering, 89–104. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-8306-0.ch006.
Повний текст джерелаТези доповідей конференцій з теми "STREAMING SITES"
Utami, Paramita Retno, Riyanto Fitri Setiyono, Dina Fitria Murad, and Sunardi. "User Experience and Service Quality (SERVQUAL) Influence on Customer Loyalty of Video Streaming Sites Visitors." In 2023 8th International Conference on Business and Industrial Research (ICBIR). IEEE, 2023. http://dx.doi.org/10.1109/icbir57571.2023.10147446.
Повний текст джерелаLučić, Sonja. "VIDEO STRIMING USLUGE I AUTORSKO PRAVO." In XIX majsko savetovanje. University of Kragujevac, Faculty of Law, 2023. http://dx.doi.org/10.46793/xixmajsko.375l.
Повний текст джерелаBabaei, Hadi, and Kamran Siddiqui. "Investigation of Streaming Flow Patterns in a Thermoacoustic Device Using PIV." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30798.
Повний текст джерелаGroppe, Sven, Jinghua Groppe, Dirk Kukulenz, and Volker Linnemann. "A SPARQL Engine for Streaming RDF Data." In 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System SITIS. IEEE, 2007. http://dx.doi.org/10.1109/sitis.2007.22.
Повний текст джерелаPaya, A., and D. C. Marinescu. "A Cloud Service for Adaptive Digital Music Streaming." In 2012 Eighth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2012). IEEE, 2012. http://dx.doi.org/10.1109/sitis.2012.135.
Повний текст джерелаIchibane, Yacine, Youssef Gahi, Zouhair Guennoun, and Mouhcine Guennoun. "Private Video Streaming Service Using Leveled Somewhat Homomorphic Encryption." In 2014 Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). IEEE, 2014. http://dx.doi.org/10.1109/sitis.2014.61.
Повний текст джерелаOrlando, Dominick, and Claudia M. Craig. "Status of the NRC Decommissioning Program." In ASME 2003 9th International Conference on Radioactive Waste Management and Environmental Remediation. ASMEDC, 2003. http://dx.doi.org/10.1115/icem2003-4671.
Повний текст джерелаCorallo, Angelo, Annamaria Crespino, Carla Dibiccari, Mariangela Lazoi, and Marianna Lezzi. "Processing Big Data in Streaming for Fault Prediction: An Industrial Application." In 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). IEEE, 2018. http://dx.doi.org/10.1109/sitis.2018.00117.
Повний текст джерелаShrivastava, Amit, Anand Rajavat, and Rahul Deshmukh. "Predicting Number of Connections on Video Streaming Server with Machine Learning Approach." In 2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). IEEE, 2017. http://dx.doi.org/10.1109/sitis.2017.26.
Повний текст джерелаTaraghi, Babak, Selina Zoë Haack, and Christian Timmerer. "Towards Better Quality of Experience in HTTP Adaptive Streaming." In 2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). IEEE, 2022. http://dx.doi.org/10.1109/sitis57111.2022.00096.
Повний текст джерелаЗвіти організацій з теми "STREAMING SITES"
Whitaker, Stephen. Rocky intertidal community monitoring at Channel Islands National Park: 2018–19 annual report. National Park Service, August 2023. http://dx.doi.org/10.36967/2299674.
Повний текст джерела