Physical Sciences and Mathematics Commons^™

Autonomous Eco-Driving With Traffic Light And Lead Vehicle Constraints: An Application Of Best Constrained Interpolation, Yara Hazem Mohamed Mahmoud

Masters Theses

Eco-Driving is a critical technology for improving automotive transportation efficiency. It is achieved by modifying the driving trajectory over a particular route to minimize required propulsion energy. Eco-Driving can be approached as an optimal control problem subject to driving constraints such as traffic lights and positions of other vehicles. Best interpolation in a strip is a problem in approximation theory and optimal control. The solution to this problem is a cubic spline. In this research we demonstrate the connection between Eco-Driving and best interpolation in the strip. By exploiting this connection, we are able to generate optimal Eco-Driving trajectories that …

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. …

Artificial Immune Systems: Applications, Multi-Class Classification, Optimizations, And Analysis, Brian Haroldo Schmidt

Dissertations

The focus of this research is the application of the Artificial Immune System (AIS) paradigm to a new research area along with the modifications necessary to adapt it to a new problem. In the past 10 years, there has been much research into the use of various Machine Learning (ML) algorithms in Network Flow Traffic Classification. AIS algorithms have thus far not been applied to this problem. Because AIS algorithms have been used extensively for Network Intrusion Detection applications, which is a similar area of research, the motivation to extend them to the network flow classification problem is clear.

This …

An Integral Framework For Sustainable Building Design, Bushra Asfari

Masters Theses

Selection of materials for building design is a delicate process hinged of a number of factors which can be cost or environmental related, depending on the objectives of the design. This process becomes more difficult when designers are faced with several material options for each building component. This thesis presents the design and development of a framework that enables designers understand the trade-off between cost and environmental related factors when selecting materials for building design. The framework is based on the integration of Autodesk Revit, Microsoft access, and modeling modified Harmony search multi-objective optimization tool adapted to account for material …

Artificial Immune Systems And Particle Swarm Optimization For Solutions To The General Adversarial Agents Problem, Jeremy Mange

Dissertations

The general adversarial agents problem is an abstract problem description touching on the fields of Artificial Intelligence, machine learning, decision theory, and game theory. The goal of the problem is, given one or more mobile agents, each identified as either “friendly" or “enemy", along with a specified environment state, to choose an action or series of actions from all possible valid choices for the next “timestep" or series thereof, in order to lead toward a specified outcome or set of outcomes. This dissertation explores approaches to this problem utilizing Artificial Immune Systems, Particle Swarm Optimization, and hybrid approaches, along with …