Matching Items (476)
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- All Subjects: Guitar music
ContributorsDaval, Charles (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-26
DescriptionThe purpose of this project is to explore the influence of folk music in guitar compositions by Manuel Ponce from 1923 to 1932. It focuses on his Tres canciones populares mexicanas and Tropico and Rumba.
ContributorsGarcia Santos, Arnoldo (Author) / Koonce, Frank (Thesis advisor) / Rogers, Rodney (Committee member) / Rotaru, Catalin (Committee member) / Arizona State University (Publisher)
Created2014
Description
Survey indicates a rise of 81% in mobile data usage in the year 2013. A fair share of this total data demand can be attributed to video streaming. The encoding structure of videos, introduces nuances that can be utilized to ensure a fair and optimal means of streaming the video data. This dissertation proposes a novel user and packet scheduling algorithm that guarantees a fair allocation of resources. MS-SSIM index
is used to calculate the mean opinion score (DMOS) to evaluate the quality of the received video. Simulations indicate that the proposed algorithm outperforms existing algorithms in the literature.
is used to calculate the mean opinion score (DMOS) to evaluate the quality of the received video. Simulations indicate that the proposed algorithm outperforms existing algorithms in the literature.
ContributorsChoudhuri, Sabarna (Author) / Ying, Lei (Thesis advisor) / Bliss, Dan (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2014
ContributorsKotronakis, Dimitris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-01
ContributorsDavin, Colin (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-05
Description
Video capture, storage, and distribution in wireless video sensor networks
(WVSNs) critically depends on the resources of the nodes forming the sensor
networks. In the era of big data, Internet of Things (IoT), and distributed
demand and solutions, there is a need for multi-dimensional data to be part of
the Sensor Network data that is easily accessible and consumable by humanity as
well as machinery. Images and video are expected to become as ubiquitous as is
the scalar data in traditional sensor networks. The inception of video-streaming
over the Internet, heralded a relentless research for effective ways of
distributing video in a scalable and cost effective way. There has been novel
implementation attempts across several network layers. Due to the inherent
complications of backward compatibility and need for standardization across
network layers, there has been a refocused attention to address most of the
video distribution over the application layer. As a result, a few video
streaming solutions over the Hypertext Transfer Protocol (HTTP) have been
proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion
Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These
frameworks, do not address the typical and future WVSN use cases. A highly
flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH)
are introduced. The platform's goal is to usher video as a data element that
can be integrated into traditional and non-Internet networks. A low cost,
scalable node is built from the ground up to be fully compatible with the
Internet of Things Machine to Machine (M2M) concept, as well as the ability to
be easily re-targeted to new applications in a short time. Flexi-WVSNP design
includes a multi-radio node, a middle-ware for sensor operation and
communication, a cross platform client facing data retriever/player framework,
scalable security as well as a cohesive but decoupled hardware and software
design.
(WVSNs) critically depends on the resources of the nodes forming the sensor
networks. In the era of big data, Internet of Things (IoT), and distributed
demand and solutions, there is a need for multi-dimensional data to be part of
the Sensor Network data that is easily accessible and consumable by humanity as
well as machinery. Images and video are expected to become as ubiquitous as is
the scalar data in traditional sensor networks. The inception of video-streaming
over the Internet, heralded a relentless research for effective ways of
distributing video in a scalable and cost effective way. There has been novel
implementation attempts across several network layers. Due to the inherent
complications of backward compatibility and need for standardization across
network layers, there has been a refocused attention to address most of the
video distribution over the application layer. As a result, a few video
streaming solutions over the Hypertext Transfer Protocol (HTTP) have been
proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion
Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These
frameworks, do not address the typical and future WVSN use cases. A highly
flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH)
are introduced. The platform's goal is to usher video as a data element that
can be integrated into traditional and non-Internet networks. A low cost,
scalable node is built from the ground up to be fully compatible with the
Internet of Things Machine to Machine (M2M) concept, as well as the ability to
be easily re-targeted to new applications in a short time. Flexi-WVSNP design
includes a multi-radio node, a middle-ware for sensor operation and
communication, a cross platform client facing data retriever/player framework,
scalable security as well as a cohesive but decoupled hardware and software
design.
ContributorsSeema, Adolph (Author) / Reisslein, Martin (Thesis advisor) / Kitchen, Jennifer (Committee member) / Seeling, Patrick (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2017
ContributorsSanchez, Armand (Performer) / Nordstrom, Nathan (Performer) / Roubison, Ryan (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-13
ContributorsChan, Robbie (Performer) / McCarrel, Kyla (Performer) / Sadownik, Stephanie (Performer) / ASU Library. Music Library (Contributor)
Created2018-04-18
ContributorsMayo, Joshua (Contributor) / Betts, Sarah (Performer) / Cericola, Marco (Performer) / Gonzalez, Nikolas (Performer) / ASU Library. Music Library (Publisher)
Created2021-04-28