Engineering Commons^™

Video Stream Adaptation In Computer Vision Systems, Yousef Sharrab Sharrab

Wayne State University Dissertations

Computer Vision (CV) has been deployed recently in a wide range of applications, including surveillance and automotive industries. According to a recent report, the market for CV technologies will grow to $33.3 billion by 2019. Surveillance and automotive industries share over 20% of this market. This dissertation considers the design of real-time CV systems with live video streaming, especially those over wireless and mobile networks. Such systems include video cameras/sensors and monitoring stations. The cameras should adapt their captured videos based on the events and/or available resources and time requirement. The monitoring station receives video streams from all cameras and …

Integrative Pathway Analysis Pipeline For Mirna And Mrna Data, Diana Mabel Diaz Herrera

Wayne State University Theses

The identification of pathways that are involved in a particular phenotype helps us understand the underlying biological processes. Traditional pathway analysis techniques aim to infer the impact on individual pathways using only mRNA levels. However, recent studies showed that gene expression alone is unable to capture the whole picture of biological phenomena. At the same time, MicroRNAs (miRNAs) are newly discovered gene regulators that have shown to play an important role in diagnosis, and prognosis for different types of diseases. Current pathway analysis techniques do not take miRNAs into consideration. In this project, we investigate the effect of integrating miRNA …

Analysis Of Cross-Layer Optimization Of Facial Recognition In Automated Video Surveillance, Loren Garavaglia

Wayne State University Theses

Interest in automated video surveillance systems has grown dramatically and with that so too has research on the topic. Recent approaches have begun addressing the issues of scalability and cost. One method aimed to utilize cross-layer information for adjusting bandwidth allocated to each video source. Work on this topic focused on using distortion and accuracy for face detection as an adjustment metric, utilizing older, less efficient codecs. The framework was shown to increase accuracy in face detection by interpreting dynamic network conditions in order to manage application rates and transmission opportunities for video sources with the added benefit of reducing …

A Scalable Solution For Interactive Video Streaming, Kamal Kayed Nayfeh

Wayne State University Dissertations

This dissertation presents an overall solution for interactive Near Video On Demand (NVOD) systems, where limited server and network resources prevent the system from servicing all customers’ requests. The interactive nature of recent workloads complicates matters further. Interactive requests require additional resources to be handled. This dissertation analyzes the system performance under a realistic workload using different stream merging techniques and scheduling policies. It considers a wide range of system

parameters and studies their impact on the waiting and blocking metrics. In order to improve waiting customers experience, we propose a new scheduling policy for waiting customers that is fairer …

Data Placement And Task Mapping Optimization For Big Data Workflows In The Cloud, Mahdi Ebrahimi

Wayne State University Dissertations

Data-centric workflows naturally process and analyze a huge volume of datasets. In this new era of Big Data there is a growing need to enable data-centric workflows to perform computations at a scale far exceeding a single workstation's capabilities. Therefore, this type of applications can benefit from distributed high performance computing (HPC) infrastructures like cluster, grid or cloud computing.

Although data-centric workflows have been applied extensively to structure complex scientific data analysis processes, they fail to address the big data challenges as well as leverage the capability of dynamic resource provisioning in the Cloud. The concept of “big data workflows” …

Improving Usability And Scalability Of Big Data Workflows In The Cloud, Aravind Mohan

Wayne State University Dissertations

Big data workflows have recently emerged as the next generation of data-centric workflow technologies to address the five “V” challenges of big data: volume, variety, velocity, veracity, and value. More formally, a big data workflow is the computerized modeling and automation of a process consisting of a set of computational tasks and their data interdependencies to process and analyze data of ever increasing in scale, complexity, and rate of acquisition. The convergence of big data and workflows creates new challenges in workflow community.

First, the variety of big data results in a need for integrating large number of remote Web …