Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network

Open Access. Powered by Scholars. Published by Universities.®

Western Michigan University

Theses/Dissertations

2018

Machine learning

Articles 1 - 4 of 4

Full-Text Articles in Entire DC Network

Efficacy Of Deep Learning In Support Of Smart Services, Basheer Mohammed Basheer Qolomany Dec 2018

Efficacy Of Deep Learning In Support Of Smart Services, Basheer Mohammed Basheer Qolomany

Dissertations

The massive amount of streaming data generated and captured by smart service appliances, sensors and devices needs to be analyzed by algorithms, transformed into information, and minted to extract knowledge to facilitate timely actions and better decision making. This can lead to new products and services that can dramatically transform our lives. Machine learning and data analytics will undoubtedly play a critical role in enabling the delivery of smart services. Within the machine-learning domain, Deep Learning (DL) is emerging as a superior new approach that is much more effective than any rule or formula used by traditional machine learning. Furthermore, …


Evaluating The Efficacy Of Convolution Neural Networks In Age At Deat Estimation Using 3d Scans Of The Pubic Symphyseal Face, Melissa A. Brown Aug 2018

Evaluating The Efficacy Of Convolution Neural Networks In Age At Deat Estimation Using 3d Scans Of The Pubic Symphyseal Face, Melissa A. Brown

Masters Theses

The research presented assesses the utility of machine learning approaches, specifically convolutional neural networks (CNNs), to the estimation of age at death in adult decedents by analysis of the pubic symphyseal face of the os coxa rendered as a 3D image. Age at death estimation is an important duty of forensic anthropologists working in medico-legal contexts, as well as bioarcheological researchers. The purpose of this study is to evaluate the accuracy of a CNN relative to the performance of human observers using traditional methods of age estimation. To accomplish this, a CNN created for this project and expert anthropologists were …


Exploring The Use Of Hierarchal Statistical Analysis And Deep Neural Networks To Detect And Mitigate Covert Timing Channels, Omar Darwish Apr 2018

Exploring The Use Of Hierarchal Statistical Analysis And Deep Neural Networks To Detect And Mitigate Covert Timing Channels, Omar Darwish

Dissertations

Covert timing channels provide a mechanism to transmit unauthorized information across different processes. It utilizes the inter-arrival times between the transmitted packets to hide the communicated data. It can be exploited in a variety of malevolent scenarios such as leaking military secrets, trade secrets, and other forms of Intellectual Property (IP). They can be also used as a vehicle to attack existing computing systems to disseminate software viruses or worms while bypassing firewalls, intrusion detection and protection systems, and application filters. Therefore, the detection and mitigation of covert channels is a key issue in modern Information Technology (IT) infrastructure. Many …


A Holistic Computational Approach To Boosting The Performance Of Protein Search Engines, Majdi Ahmad Mosa Maabreh Apr 2018

A Holistic Computational Approach To Boosting The Performance Of Protein Search Engines, Majdi Ahmad Mosa Maabreh

Dissertations

Despite availability of several proteins search engines, due to the increasing amounts of MS/MS data and database sizes, more efficient data analysis and reduction methods are important. Improving accuracy and performance of protein identification is a main goal in the community of proteomic research. In this research, a holistic solution for improvement in search performance is developed.

Most current search engines apply the SEQUEST style of searching protein databases to define MS/MS spectra. SEQUEST involves three main phases: (i) Indexing the protein databases, (ii) Matching and Ranking the MS/MS spectra and (iii) Filtering the matches and reporting the final proteins. …