41,801 research outputs found

    Effect of oil palm empty fruit bunches (OPEFB) fibers to the compressive strength and water absorption of concrete

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    Growing popularity based on environmentally-friendly, low cost and lightweight building materials in the construction industry has led to a need to examine how these characteristics can be achieved and at the same time giving the benefit to the environment and maintain the material requirements based on the standards required. Recycling of waste generated from industrial and agricultural activities as measures of building materials is not only a viable solution to the problem of pollution but also to produce an economic design of building

    On an evaluation of transformation languages in a fully XML-driven framework for video content adaptation

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    Bitstream Structure Descriptions (BSDs) allow taking the complexity of transforming scalable bitstreams from the compressed domain to the semantic domain. These descriptions are an essential part of an XUL-driven video adaptation framework. The performance of a BSD transformation engine is very important in such an architecture. This paper evaluates the efficiency of XML-based transformation languages in our video adaptation framework. XSLT, STX, and a hybrid solution are compared to each other in terms of execution times, memory consumption, and user-friendliness. Our experiments show that STX is the preferred solution when speed and low-memory are important. The hybrid solution is competitive in terms of memory consumption and is more user-friendly than STX. Although XSLT is relative fast, its memory consumption is very high

    A machine learning-based framework for preventing video freezes in HTTP adaptive streaming

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    HTTP Adaptive Streaming (HAS) represents the dominant technology to deliver videos over the Internet, due to its ability to adapt the video quality to the available bandwidth. Despite that, HAS clients can still suffer from freezes in the video playout, the main factor influencing users' Quality of Experience (QoE). To reduce video freezes, we propose a network-based framework, where a network controller prioritizes the delivery of particular video segments to prevent freezes at the clients. This framework is based on OpenFlow, a widely adopted protocol to implement the software-defined networking principle. The main element of the controller is a Machine Learning (ML) engine based on the random undersampling boosting algorithm and fuzzy logic, which can detect when a client is close to a freeze and drive the network prioritization to avoid it. This decision is based on measurements collected from the network nodes only, without any knowledge on the streamed videos or on the clients' characteristics. In this paper, we detail the design of the proposed ML-based framework and compare its performance with other benchmarking HAS solutions, under various video streaming scenarios. Particularly, we show through extensive experimentation that the proposed approach can reduce video freezes and freeze time with about 65% and 45% respectively, when compared to benchmarking algorithms. These results represent a major improvement for the QoE of the users watching multimedia content online

    Semantic media decision taking using N3Logic

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    Power-Constrained Fuzzy Logic Control of Video Streaming over a Wireless Interconnect

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    Wireless communication of video, with Bluetooth as an example, represents a compromise between channel conditions, display and decode deadlines, and energy constraints. This paper proposes fuzzy logic control (FLC) of automatic repeat request (ARQ) as a way of reconciling these factors, with a 40% saving in power in the worst channel conditions from economizing on transmissions when channel errors occur. Whatever the channel conditions are, FLC is shown to outperform the default Bluetooth scheme and an alternative Bluetooth-adaptive ARQ scheme in terms of reduced packet loss and delay, as well as improved video quality
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