Engineering Commons^™

An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Prescribed fires can lessen wildfire severity and control invasive species, but some terrains may be difficult, dangerous, or costly to burn with existing tools. This thesis presents the design of an unmanned aerial system that can ignite prescribed fires from the air, with less cost and risk than with aerial ignition from a manned aircraft. The prototype was evaluated in-lab and successfully used to ignite interior areas of two prescribed fires. Additionally, we introduce an approach that integrates a lightweight fire simulation to autonomously plan safe flight trajectories and suggest effective fire lines. Both components are unique in that they …

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

Analytical Modeling Of A Communication Channel Based On Subthreshold Stimulation Of Neurobiological Networks, Alireza Khodaei

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The emergence of wearable and implantable machines manufactured artificially or synthesized biologically opens up a new horizon for patient-centered health services such as medical treatment, health monitoring, and rehabilitation with minimized costs and maximized popularity when provided remotely via the Internet. In particular, a swarm of machines at the scale of a single cell down to the nanoscale can be deployed in the body by the non-invasive or minimally invasive operation (e.g., swallowing and injection respectively) to perform various tasks. However, an individual machine is only able to perform basic tasks so it needs to exchange data with the others …

Rate Based Impact Analysis, Nishant Sharma

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Impact Analysis (IA) identifies control and data dependencies to determine the system components that could be affected by a change. Changes to robotic systems as they are updated often alter the flow of control and sensor data. Changes to the rates at which data is published from sensors, controllers, and other parts of the system are particularly subtle and difficult to detect. These rate changes, even if minor (e.g. lowering the frame rate of a camera), can propagate throughout the system and have broad impacts. However, for robotic systems, these changes in flow rate cannot be precisely tracked by just …

Feature Extraction And Parallel Visualization For Large-Scale Scientific Data, Lina Yu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Advanced computing and sensing technologies enable scientists to study natural and physical phenomena with unprecedented precision, resulting in an explosive growth of data. The unprecedented amounts of data generated from large scientific simulations impose a grand challenge in data analytics and visualization due to the fact that data are too massive for transferring, storing, and processing.

This dissertation makes the first contribution to the design of novel transfer functions and application-aware data replacement policy to facilitate feature classification on highly parallel distributed systems. We design novel transfer functions that advance the classification of continuously changed volume data by combining the …

Study Of Comparison Of Ocs And Hybrid Switching In Fso Data Centers, Suraj Yadav

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

With the increase in big data applications, it has become the need of the hour to handle data efficiently to handle the growing traffic in the data centers. The popular mechanism is parallel processing using commodity hardware hence it is becoming an interesting research topic to explore new architectures which have high performance, but with an increase in data sizes the architecture has to expand which increases the cabling complexity. Hence the study of Free Space Optical (FSO) communication for the data centers is gaining more importance now than ever. We proposed square OWCELL topology which is a new free …

Exploring The Telecommunications Properties Of The Human Nervous System: Analytical Modeling And Experimental Validation Of Information Flow Through The Somatosensory System, Natalie Hanisch

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The growing field of Body Area Networks (BANs) is providing solutions to the wireless connectivity of wearable and implantable devices with applications in medicine, entertainment, fitness, and military, amongst others. While electromagnetic wave propagation has been the main BANs' enabling technology, the increasingly pervasive nature of these devices encourages novel solutions with added bio-compatibility and sustainability. In this thesis, a novel communication system is proposed for BANs based on the natural propagation of tactile stimuli through the nervous system. This system is composed of a tactile stimulator coupled to an ElectroEncephaloGraphy (EEG) system, and realizes the propagation of somatosensory signals …

Deep Learning And Transfer Learning In The Classification Of Eeg Signals, Jacob M. Williams

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Deep learning is seldom used in the classification of electroencephalography (EEG) signals, despite achieving state of the art classification accuracies in other spatial and time series data. Instead, most research has continued to use manual feature extraction followed by a traditional classifier, such as SVMs or logistic regression. This is largely due to the low number of samples per experiment, high-dimensional nature of the data, and the difficulty in finding appropriate deep learning architectures for classification of EEG signals. In this thesis, several deep learning architectures are compared to traditional techniques for the classification of visually evoked EEG signals. We …

Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Good querying and visualization of moving objects and their trajectories is still an open problem. This thesis investigates three types of moving objects. First, projectiles, whose parabolic motion is difficult to represent. Second, moving objects that slide down a slope. The representation of these objects is challenging because of their accelerating motion. Third, the motion of migrating animals. The motion of migrating animals is challenging because it also involves some spatio-temporal interpolation. The thesis shows a solution to these problems using ideas from physics and an implementation in the MLPQ constraint databases system. The MLPQ implementation enables several complex spatio-temporal …

Investigating Diversity In Open Multiagent Team Formation, Pooja Ahuja

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Team formation is the most rudimentary form of interactions in distributed AI and multiagent systems as it allows coherent collections of agents to work together in a beneficial manner towards a common goal of interest. Basically, individual expertise are assembled together in an additive fashion for accomplishing tasks together. A plethora of the related studies found in the literature often make several unrealistic assumptions such as coordination amongst the agents, or agents having knowledge of the whole environment, or agents and/or tasks are of the same kind, or a static environment setting. Against this background, we argue that there are …

Investigating Agent And Task Openness In Adhoc Team Formation, Bin Chen

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

When deciding which ad hoc team to join, agents are often required to consider rewards from accomplishing tasks as well as potential benefits from learning when working with others, when solving tasks. We argue that, in order to decide when to learn or when to solve task, agents have to consider the existing agents’ capabilities and tasks available in the environment, and thus agents have to consider agent and task openness—the rate of new, previously unknown agents (and tasks) that are introduced into the environment. We further assume that agents evolve their capabilities intrinsically through learning by observation or learning …

Detection Of Plant Emergence Based On Spatio Temporal Image Sequence Analysis, Bhushit Agarwal

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The phenome of a plant is the sum of all observable phenotypes for that plant. Phenotypes are observable characteristics or traits of a plant. These traits generally reflect a combination of influences from the genotype of the plant and the environment in which the plant has grown and developed. Collecting phenotypic data has traditionally been a slow and costly manual process, albeit one highly necessary for plant breeding and the development of improved agronomic practices. As a result automated methods for plant phenotyping analysis have become an active research field in recent years. Image-based plant phenotyping analysis facilitates extraction of …