3,519 research outputs found

    Survey of Transportation of Adaptive Multimedia Streaming service in Internet

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    [DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; GarcĂ­a-GarcĂ­a, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

    The Triple-S framework: ensuring scalable, sustainable, and serviceable practices in educational technology

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    Educational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational landscape constantly evolves, where tertiary institutions are incorporating new modes of content delivery, hybrid-style learning, and interactive technologies. Investments into digital expansions must be taken with caution, particularly prior to the procurement of technology, with a need for the proposed interventions’ scalability, sustainability, and serviceability to be considered. This article presents the Triple-S framework for educators, administrators, and educational institutions, and outlines examples of its application within curricula. The paper synthesises research evidence to provide the foundation underlying the key principles of the Triple-S framework, presenting a useful model to use when evaluating digital interventions. Utilising the framework for decisions regarding the acquisition of educational technology, devices, software, applications, and online resources can assist in the assurance of viable and appropriate investments

    Organizational Strategies for Developing New STEM Talent

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    U.S. business leaders are experiencing a deficiency within STEM skill sets in newly hired employees, resulting in challenges to business sustainability. The purpose of this case study was to identify strategies used to develop new STEM employees for business sustainability. Participants included 5 IT business leaders who had experience developing new STEM employees in a technology organization in New York. The 3-part theory of knowledge management, knowledge creation, and knowledge transfer was the conceptual framework for this study. Data collection included face-to-face interviews and analyses of company training plans, videos, and internal websites. Methodological triangulation of the analysis technique included organizing, collecting, and comparing data. Data analysis included a generic coding process to identify 3 themes: (a) strategies for organizational effectiveness, (b) strategies for new IT employee enrichment, and (c) strategies for improving business productivity. The results of the study indicated strategies to deliver employee training and development systems leveraging internal knowledge management and transfer could provide business leaders with effective ways to increase productivity and maintain organizational effectiveness. The social implications of the study include the potential to improve the economic strength of the local community because new insights on the development of STEM employees may lead to increased hiring and business sustainability

    WING/WORLD: An Open Experimental Toolkit for the Design and Deployment of IEEE 802.11-Based Wireless Mesh Networks Testbeds

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    Wireless Mesh Networks represent an interesting instance of light-infrastructure wireless networks. Due to their flexibility and resiliency to network failures, wireless mesh networks are particularly suitable for incremental and rapid deployments of wireless access networks in both metropolitan and rural areas. This paper illustrates the design and development of an open toolkit aimed at supporting the design of different solutions for wireless mesh networking by enabling real evaluation, validation, and demonstration. The resulting testbed is based on off-the-shelf hardware components and open-source software and is focused on IEEE 802.11 commodity devices. The software toolkit is based on an "open" philosophy and aims at providing the scientific community with a tool for effective and reproducible performance analysis of WMNs. The paper describes the architecture of the toolkit, and its core functionalities, as well as its potential evolutions

    From Social Data Mining to Forecasting Socio-Economic Crisis

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    Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

    Widening Access to Applied Machine Learning with TinyML

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    Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this paper, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML both leverages low-cost and globally accessible hardware, and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia (Harvard University) and industry (Google) produced a four-part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for learners from a global variety of backgrounds. It introduces pupils to real-world applications, ML algorithms, data-set engineering, and the ethical considerations of these technologies via hands-on programming and deployment of TinyML applications in both the cloud and their own microcontrollers. To facilitate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project competition. We also released the course materials publicly, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies.Comment: Understanding the underpinnings of the TinyML edX course series: https://www.edx.org/professional-certificate/harvardx-tiny-machine-learnin

    Mashup Ecosystems: Integrating Web Resources on Desktop and Mobile Devices

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    The Web is increasingly used as an application platform, and recent development of it has introduced software ecosystems where different actors collaborate. This collaboration is international from day one, and it evolves and grows rapidly. In web ecosystems applications are provided as services, and interdependencies between ecosystem parts can vary from very strong and obvious to loose and recondite. Mashups -- web application hybrids that combine resources from different services into an integrated system that has increased value from user perspective -- are exploiting services of the Web and creating ecosystems where end-users, mashup authors, and service providers collaborate. The term "resources" is used here in a broad sense, and it can refer to user's local data, infinite content of the Web, and even executable code. This dissertation presents mashups as a new breed of web applications that are intended for parsing the web content into an easily accessed form on both regular desktop computers as well as on mobile devices. Constantly evolving web technologies and new web services open up unforeseen possibilities for mashup development. However, developing mashups with current methods and tools for existing deployment environments is challenging. First, the Web as an application platform faces numerous shortcomings, second, web application development practices in general are still immature, and third, development of mashups has additional requirements that need to be addressed. In addition, mobility sets even more challenges for mashup authoring. This dissertation describes and addresses numerous issues regarding mashup ecosystems and client-side mashup development. To achieve this, we have implemented technical research artifacts including mashup ecosystems and different kinds of mashup compositions. The artifacts are developed with numerous runtime environments and tools and targeted at different end-user platforms. This has allowed us to evaluate methods, tools, and practises used during the implementation. As result, this dissertation identifies the fundamental challenges of mashup ecosystems and describes how service providers and mashup ecosystem authors can address these challenges in practice. In addition, example implementation of a specialized multimedia mashup ecosystem for mobile devices is described. To address mashup development issues, this dissertation introduces practical guidelines and a reference architecture that can be applied when mashups are created with traditional web development tools. Moreover, environments that can be used on mobile devices to create mashups that have access to both web and local resources are introduced. Finally, a novel approach to web software development -- creating software as a mashup -- is introduced, and a realization of such concept is described
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