Physical Sciences and Mathematics Commons^™

Automatic Classification Of Epilepsy Lesions, Junwei Sun

Electronic Thesis and Dissertation Repository

Epilepsy is a common and diverse set of chronic neurological disorders characterized by seizures. Epileptic seizures result from abnormal, excessive or hypersynchronous neuronal activity in the brain. Seizure types are organized firstly according to whether the source of the seizure within the brain is localized or distributed. In this work, our objective is to validate the use of MRI (Magnetic Resonance Imaging) for localizing seizure focus for improved surgical planning. We apply computer vision and machine learning techniques to tackle the problem of epilepsy lesion classification. First datasets of digitized histology images from brain cortexes of different patients are obtained …

Automatic Foreground Initialization For Binary Image Segmentation, Wei Li

Electronic Thesis and Dissertation Repository

Foreground segmentation is a fundamental problem in computer vision. A popular approach for foreground extraction is through graph cuts in energy minimization framework. Most existing graph cuts based image segmentation algorithms rely on user’s initialization. In this work, we aim to find an automatic initialization for graph cuts. Unlike many previous methods, no additional training dataset is needed. Collecting a training set is not only expensive and time consuming, but it also may bias the algorithm to the particular data distribution of the collected dataset. We assume that the foreground differs significantly from the background in some unknown feature space …

Math, Minds, Machines, Christopher V. Carlile

Chancellor’s Honors Program Projects

No abstract provided.

A New Web Search Engine With Learning Hierarchy, Da Kuang

Electronic Thesis and Dissertation Repository

Most of the existing web search engines (such as Google and Bing) are in the form of keyword-based search. Typically, after the user issues a query with the keywords, the search engine will return a flat list of results. When the query issued by the user is related to a topic, only the keyword matching may not accurately retrieve the whole set of webpages in that topic. On the other hand, there exists another type of search system, particularly in e-Commerce web- sites, where the user can search in the categories of different faceted hierarchies (e.g., product types and price …

Preoperative Planning Of Robotics-Assisted Minimally Invasive Cardiac Surgery Under Uncertainty, Hamidreza Azimian

Electronic Thesis and Dissertation Repository

In this thesis, a computational framework for patient-specific preoperative planning of Robotics-Assisted Minimally Invasive Cardiac Surgery (RAMICS) is developed. It is expected that preoperative planning of RAMICS will improve the rate of success by considering robot kinematics, patient-specific thoracic anatomy, and procedure-specific intraoperative conditions. Given the significant anatomical features localized in the preoperative computed tomography images of a patient's thorax, port locations and robot orientations (with respect to the patient's body coordinate frame) are determined to optimize characteristics such as dexterity, reachability, tool approach angles and maneuverability. In this thesis, two approaches for preoperative planning of RAMICS are proposed that …

Real-Time Mobile Stereo Vision, Bryan Hale Bodkin

Masters Theses

Computer stereo vision is used extract depth information from two aligned cameras and there are a number of hardware and software solutions to solve the stereo correspondence problem. However few solutions are available for inexpensive mobile platforms where power and hardware are major limitations. This Thesis will proposes a method that competes with an existing OpenCV stereo correspondence method in speed and quality, and is able to run on generic multi core CPU’s.

Incorporating Memory And Learning Mechanisms Into Meta-Raps, Arif Arin

Engineering Management & Systems Engineering Theses & Dissertations

Due to the rapid increase of dimensions and complexity of real life problems, it has become more difficult to find optimal solutions using only exact mathematical methods. The need to find near-optimal solutions in an acceptable amount of time is a challenge when developing more sophisticated approaches. A proper answer to this challenge can be through the implementation of metaheuristic approaches. However, a more powerful answer might be reached by incorporating intelligence into metaheuristics.

Meta-RaPS (Metaheuristic for Randomized Priority Search) is a metaheuristic that creates high quality solutions for discrete optimization problems. It is proposed that incorporating memory and learning …

A Location-Aware Architecture Supporting Intelligent Real-Time Mobile Applications, Sean J. Barbeau

USF Tampa Graduate Theses and Dissertations

This dissertation presents LAISYC, a modular location-aware architecture for intelligent real-time mobile applications that is fully-implementable by third party mobile app developers and supports high-precision and high-accuracy positioning systems such as GPS. LAISYC significantly improves device battery life, provides location data authenticity, ensures security of location data, and significantly reduces the amount of data transferred between the phone and server. The design, implementation, and evaluation of LAISYC using real mobile phones include the following modules: the GPS Auto-Sleep module saves battery energy when using GPS, maintaining acceptable movement tracking (approximately 89% accuracy) with an approximate average doubling of battery life. …

The Advanced Educational Robot, Calder Phillips-Grafflin

Honors Theses

Existing literature in the field of computer science education clearly demonstrates that robots can be ideal teaching tools for basic computer science concepts. Likewise, robots are an ideal platform for more complicated CS techniques such as evolutionary algorithms and neural networks. With these two distinct roles in mind, that of the teaching tool and that of the research tool, in collaboration with customers in the CS department we have developed a new robotics platform suitable for both roles that provides higher performance and improved ease-of-use in comparison to the robots currently in use at Union. We have successfully designed and …

The Interacting Multiple Models Algorithm With State-Dependent Value Assignment, Rastin Rastgoufard

University of New Orleans Theses and Dissertations

The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game's player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. …

A Location-Based Incentive Mechanism For Participatory Sensing Systems With Budget Constraints, Luis Gabriel Jaimes

USF Tampa Graduate Theses and Dissertations

Participatory Sensing (PS) systems rely on the willingness of mobile users to participate in the collection and reporting of data using a variety of sensors either embedded or integrated in their

cellular phones. Users agree to use their cellular phone resources to sense and transmit the data of interest because these data will be used to address a collective problem that otherwise would

be very difficult to assess and solve. However, this new data collection paradigm has not been very successful yet mainly because of the lack of incentives for participation and privacy concerns. Without adequate incentive and privacy guaranteeing …

Game Challenge: A Factorial Analysis Approach, Ian J. Fraser

Electronic Thesis and Dissertation Repository

Video games that customize to a player's experience level and abilities have the potential to allow a broader range of players to become engaged and maintain interest as they progress in experience level. A game that uniquely customizes the player's experience could attract additional demographics to gaming, which will result in a distinct edge in marketability and potential revenue. This thesis examines a subsection of adaptive gaming systems from the perspective of identifying game factors that alter the level of difficulty. Our focus is to provide a solution useful to both research and commercial gaming communities by developing a system …

3d Velocity Retrieval And Storm Tracking Using Multiple Radars, Yong Zhang

Electronic Thesis and Dissertation Repository

Severe weather forecasting is one of the most important and urgent tasks in the meteorology field. This thesis builds on previous work by Barron and Mercer and their graduate students, concerning the use of 3D optical flow to retrieve 3D wind velocity from 3D Doppler radial velocity datasets and tracking 3D severe weather storms using fuzzy points realized as ellipsoids to represent storms and a fuzzy algebra machinery in a relaxation labeling framework to track storms in Doppler precipitation datasets.

We first extend the original 3D optical flow (both least squares and regularization methods) for recovering 3D wind velocity from …

A Spatially Explicit Agent Based Model Of Muscovy Duck Home Range Behavior, James Howard Anderson

USF Tampa Graduate Theses and Dissertations

ABSTRACT

Research in GIScience has identified agent-based simulation methodologies as effective in the study of complex adaptive spatial systems (CASS). CASS are characterized by the emergent nature of their spatial expressions and by the changing relationships between their constituent variables and how those variables act on the system's spatial expression over time. Here, emergence refers to a CASS property where small-scale, individual action results in macroscopic or system-level patterns over time. This research develops and executes a spatially-explicit agent based model of Muscovy Duck home range behavior. Muscovy duck home range behavior is regarded as a complex adaptive spatial system …

Multi-Core Unit Propagation In Functional Languages, Jonathan Alexander Leaver

Electronic Thesis and Dissertation Repository

Answer Set Programming is a declarative modeling paradigm enabling specialists in diverse disciplines to describe and solve complicated problems. Growth in high performance computing is driving ever smarter and more scalable parallel answer set solvers. To improve on today's cutting-edge, researchers need to develop increasingly intelligent methods for analysis of a solver's runtime information. Reflecting on the solver's search state typically pauses its progress until the analysis is complete. This work introduces methods from the domain of parallel functional programming and immutable type theory to construct a representation of the search state that is both amenable to introspection and efficiently …

Predicting Disease Outbreaks Using A Support Vector Machine Model, Nicolae Dragu

Senior Theses and Projects

The purpose of this research is to create an efficient way of detecting disease outbreaks from news articles using Support Vector Machines (SVM). An SVM is a supervised machine learning method used for classification and regression problems. The role of the SVM in this project is to “learn” to distinguish between news articles that may indicate a disease outbreak and those that do not.

A series of health-related articles from the World Health Organization is parsed using a Java program in order to create vectors for the SVM. Each such article thus results in a vector. A basic negation detection …

What Do You Tweet? An Analysis Of Twitter Using Support Vector Machines, Richard Sung

Senior Theses and Projects

In the past few years, Twitter has become a major social networking service with over 200 million tweets made every day. With this newfound source of expanding information, can people stay up to date with what others are posting? Along with the increasing processing power of computers, is there a way computing can analyze tweets on a large scale? Moreover, can computers understand what people think based on what they post? This senior project explores this question by determining the positive or negative sentiment of twitter posts by using a machine learning algorithm called Support Vector Machines. Based on …

Online Path Planning And Control Solution For A Coordinated Attack Of Multiple Unmanned Aerial Vehicles In A Dynamic Environment, Juan Vega-Nevarez

Electronic Theses and Dissertations

The role of the unmanned aerial vehicle (UAV) has significantly expanded in the military sector during the last decades mainly due to their cost effectiveness and their ability to eliminate the human life risk. Current UAV technology supports a variety of missions and extensive research and development is being performed to further expand its capabilities. One particular field of interest is the area of the low cost expendable UAV since its small price tag makes it an attractive solution for target suppression. A swarm of these low cost UAVs can be utilized as guided munitions or kamikaze UAVs to attack …

Partial Orders For Representing Uncertainty, Causality And Decision Making: General Properties, Operations, And Algorithms, Francisco Adolfo Zapata

Open Access Theses & Dissertations

One of the main objectives of science and engineering is to help people select the most beneficial decisions. To make these decisions, we must know people's preferences, we must have the information about different possible consequences of different decisions. Since information is never absolutely accurate and precise, we must also have information about the degree of certainty of different parts on information. All these types of information naturally lead to partial orders:

- For preferences, a <= b means that b is preferable to a. This relation is used in decision theory.

- For events, a <= b means that a can influence b. This causality relation is one of the fundamental notions of physics, especially of physics of space-time.

* For uncertain statements, a <= b means that a is less certain than b. This relation is used in logics describing uncertainty, such as fuzzy logic.

In each of these areas, there is abundant research about studying the corresponding partial orders. …

Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System, Thaer W. Jayyousi

Wayne State University Dissertations

In this dissertation, agent-based models of emergent ancient urban centers were constructed through the use of techniques from computational intelligence, agent-based modeling, complex systems, and data-mining of existing archaeological data from the prehistoric urban center, Monte Albán. This real world application was selected because of its importance in understanding the emergence of modern economic and political systems. Specifically, Cultural Algorithms was used to evolve models of early Monte Alban, models that can then be compared with existing models of ancient and modern urban centers.

Features of a complex system were used to help interpret the archaeological data. The analysis went …

New Multi-Objective Evolutionary Game Theory Algorithm For Border Security, Franciso Oswaldo Aguirre

Open Access Theses & Dissertations

The complexity of border security relays on the diversity and volume of illegal activity that must be controlled, and the variety of resources that can be deployed to secure the border. A key operational problem encountered by those charged with the task of border security is the scheduling and deployment of patrols. Patrolling can be defined as the act of walking or traveling around an area - network-, at regular intervals, in order to protect or supervise it. The problem of optimizing schedules for patrolling open areas is one that arises in many contexts, and has attracted significant attention from …

Comparing Ai Archetypes And Hybrids Using Blackjack, Robert Edward Noonan

All Graduate Theses, Dissertations, and Other Capstone Projects

The discipline of artificial intelligence (AI) is a diverse field, with a vast variety of philosophies and implementations to consider. This work attempts to compare several of these paradigms as well as their variations and hybrids, using the card game of blackjack as the field of competition. This is done with an automated blackjack emulator, written in Java, which accepts computer-controlled players of various AI philosophies and their variants, training them and finally pitting them against each other in a series of tournaments with customizable rule sets. In order to avoid bias towards any particular implementation, the system treats each …

The Application Of Fuzzy Granular Computing For The Analysis Of Human Dynamic Behavior In 3d Space, Murad Mohammad Alaqtash

Open Access Theses & Dissertations

Human dynamic behavior in space is very complex in that it involves many physical, perceptual and motor aspects. It is tied together at a sensory level by linkages between vestibular, visual and somatosensory information that develop through experience of inertial and gravitational reaction forces. Coordinated movement emerges from the interplay among descending output from the central nervous system, sensory input from the body and environment, muscle dynamics, and the emergent dynamics of the whole neuromusculoskeletal system.

There have been many attempts to directly capture the activities of the neuronal system in human locomotion without the ability to clarify how the …

Scale Invariant Object Recognition Using Cortical Computational Models And A Robotic Platform, Danny Voils

Dissertations and Theses

This paper proposes an end-to-end, scale invariant, visual object recognition system, composed of computational components that mimic the cortex in the brain. The system uses a two stage process. The first stage is a filter that extracts scale invariant features from the visual field. The second stage uses inference based spacio-temporal analysis of these features to identify objects in the visual field. The proposed model combines Numenta's Hierarchical Temporal Memory (HTM), with HMAX developed by MIT's Brain and Cognitive Science Department. While these two biologically inspired paradigms are based on what is known about the visual cortex, HTM and HMAX …

Memristor-Based Reservoir Computing, Manjari S. Kulkarni

Dissertations and Theses

In today's nanoscale era, scaling down to even smaller feature sizes poses a significant challenge in the device fabrication, the circuit, and the system design and integration. On the other hand, nanoscale technology has also led to novel materials and devices with unique properties. The memristor is one such emergent nanoscale device that exhibits non-linear current-voltage characteristics and has an inherent memory property, i.e., its current state depends on the past. Both the non-linear and the memory property of memristors have the potential to enable solving spatial and temporal pattern recognition tasks in radically different ways from traditional binary transistor-based …