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Description
Recent trends in big data storage systems show a shift from disk centric models to memory centric models. The primary challenges faced by these systems are speed, scalability, and fault tolerance. It is interesting to investigate the performance of these two models with respect to some big data applications. This

Recent trends in big data storage systems show a shift from disk centric models to memory centric models. The primary challenges faced by these systems are speed, scalability, and fault tolerance. It is interesting to investigate the performance of these two models with respect to some big data applications. This thesis studies the performance of Ceph (a disk centric model) and Alluxio (a memory centric model) and evaluates whether a hybrid model provides any performance benefits with respect to big data applications. To this end, an application TechTalk is created that uses Ceph to store data and Alluxio to perform data analytics. The functionalities of the application include offline lecture storage, live recording of classes, content analysis and reference generation. The knowledge base of videos is constructed by analyzing the offline data using machine learning techniques. This training dataset provides knowledge to construct the index of an online stream. The indexed metadata enables the students to search, view and access the relevant content. The performance of the application is benchmarked in different use cases to demonstrate the benefits of the hybrid model.
ContributorsNAGENDRA, SHILPA (Author) / Huang, Dijiang (Thesis advisor) / Zhao, Ming (Committee member) / Maciejewski, Ross (Committee member) / Chung, Chun-Jen (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Speech recognition in games is rarely seen. This work presents a project, a 2D computer game named "The Emblems" which utilizes speech recognition as input. The game itself is a two person strategy game whose goal is to defeat the opposing player's army. This report focuses on the speech-recognition aspect

Speech recognition in games is rarely seen. This work presents a project, a 2D computer game named "The Emblems" which utilizes speech recognition as input. The game itself is a two person strategy game whose goal is to defeat the opposing player's army. This report focuses on the speech-recognition aspect of the project. The players interact on a turn-by-turn basis by speaking commands into the computer's microphone. When the computer recognizes a command, it will respond accordingly by having the player's unit perform an action on screen.
ContributorsNguyen, Jordan Ngoc (Author) / Kobayashi, Yoshihiro (Thesis director) / Maciejewski, Ross (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-05
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Description
The project, "The Emblems: OpenGL" is a 2D strategy game that incorporates Speech Recognition for control and OpenGL for computer graphics. Players control their own army by voice commands and try to eliminate the opponent's army. This report focuses on the 2D art and visual aspects of the project. There

The project, "The Emblems: OpenGL" is a 2D strategy game that incorporates Speech Recognition for control and OpenGL for computer graphics. Players control their own army by voice commands and try to eliminate the opponent's army. This report focuses on the 2D art and visual aspects of the project. There are different sprites for the player's army units and icons within the game. The game also has a grid for easy unit placement.
ContributorsHsia, Allen (Author) / Kobayashi, Yoshihiro (Thesis director) / Maciejewski, Ross (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-05