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Pages
- Title
- Vision-Based Sensing and Optimal Control for Low-Cost and Small Satellite Platforms.
- Creator
-
Sease, Bradley, Xu, Yunjun, Lin, Kuo-Chi, Bradley, Eric, University of Central Florida
- Abstract / Description
-
Current trends in spacecraft are leading to smaller, more inexpensive options whenever possible. This shift has been primarily pursued for the opportunity to open a new frontier for technologies with a small financial obligation. Limited power, processing, pointing, and communication capabilities are all common issues which must be considered when miniaturizing systems and implementing low-cost components. This thesis addresses some of these concerns by applying two methods, in attitude...
Show moreCurrent trends in spacecraft are leading to smaller, more inexpensive options whenever possible. This shift has been primarily pursued for the opportunity to open a new frontier for technologies with a small financial obligation. Limited power, processing, pointing, and communication capabilities are all common issues which must be considered when miniaturizing systems and implementing low-cost components. This thesis addresses some of these concerns by applying two methods, in attitude estimation and control. Additionally, these methods are not restricted to only small, inexpensive satellites, but offer a benefit to large-scale spacecraft as well.First, star cameras are examined for the tendency to generate streaked star images during maneuvers. This issue also comes into play when pointing capabilities and camera hardware quality are low, as is often the case in small, budget-constrained spacecraft. When pointing capabilities are low, small residual velocities can cause movement of the stars in the focal plane during an exposure, causing them to streak across the image. Additionally, if the camera quality is low, longer exposures may be required to gather sufficient light from a star, further contributing to streaking. Rather than improving the pointing or hardware directly, an algorithm is presented to retrieve and utilize the endpoints of streaked stars to provide feedback where traditional methods do not. This allows precise attitude and angular rate estimates to be derived from an image which, with traditional methods, would return large attitude and rate error. Simulation results are presented which demonstrate endpoint error of approximately half a pixel and rate estimates within 2% of the true angular velocity. Three methods are also considered to remove overlapping star streaks and resident space objects from images to improve performance of both attitude and rate estimates. Results from a large-scale Monte Carlo simulation are presented in order to characterize the performance of the method.Additionally, a rapid optimal attitude guidance method is experimentally validated in a ground-based, pico-scale satellite test bed. Fast slewing performance is demonstrated for an incremental step maneuver with low average power consumption. Though the focus of this thesis is primarily on increasing the capabilities of small, inexpensive spacecraft, the methods discussed have the potential to increase the capabilities of current and future large-scale missions as well.
Show less - Date Issued
- 2013
- Identifier
- CFE0005249, ucf:50603
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005249
- Title
- PSYCHOLOGICAL SENSE OF COMMUNITY AND RETENTION: RETHINKING THE FIRST-YEAR EXPERIENCE OF STUDENTS IN STEM.
- Creator
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Dagley Falls, Melissa, Cintron-Delgado, Rosa, University of Central Florida
- Abstract / Description
-
This investigation looks at the relationship between a STEM learning community's co-curricular activities and students' perceived sense of community (SOC)to determine which activities most influence SOC and, in turn, retention. This investigation shows that SOC can be impacted by a multitude of factors found within the college environment. The most influential of these factors are open acceptance, student academic support services, and residential experiences. Most importantly there...
Show moreThis investigation looks at the relationship between a STEM learning community's co-curricular activities and students' perceived sense of community (SOC)to determine which activities most influence SOC and, in turn, retention. This investigation shows that SOC can be impacted by a multitude of factors found within the college environment. The most influential of these factors are open acceptance, student academic support services, and residential experiences. Most importantly there were significant differences for African American students participating in the STEM learning community on the measures of SOC, retention, and being on-track in mathematics. Additional data suggested higher levels of being on-track in mathematics for male students and differences in retention and being on-track for Hispanic students participating in a STEM learning community.
Show less - Date Issued
- 2009
- Identifier
- CFE0002841, ucf:48058
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002841
- Title
- REALIZATION OF POWER FACTOR CORRECTION AND MAXIMUM POWER POINT TRACKING FOR LOW POWER WIND TURBINES.
- Creator
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Gamboa, Gustavo, Batarseh, Issa, University of Central Florida
- Abstract / Description
-
In recent years, wind energy technology has become one of the top areas of interest for energy harvesting in the power electronics world. This interest has especially peaked recently due to the increasing demand for a reliable source of renewable energy. In a recent study, the American Wind Energy Association (AWEA) ranked the U.S as the leading competitor in wind energy harvesting followed by Germany and Spain. Although the United States is the leading competitor in this area, no one has...
Show moreIn recent years, wind energy technology has become one of the top areas of interest for energy harvesting in the power electronics world. This interest has especially peaked recently due to the increasing demand for a reliable source of renewable energy. In a recent study, the American Wind Energy Association (AWEA) ranked the U.S as the leading competitor in wind energy harvesting followed by Germany and Spain. Although the United States is the leading competitor in this area, no one has been able successfully develop an efficient, low-cost AC/DC convertor for low power turbines to be used by the average American consumer. There has been very little research in low power AC/DC converters for low to medium power wind energy turbines for battery charging applications. Due to the low power coefficient of wind turbines, power converters are required to transfer the maximum available power at the highest efficiency. Power factor correction (PFC) and maximum power point tracking (MPPT) algorithms have been proposed for high power wind turbines. These turbines are out of the price range of what a common household can afford. They also occupy a large amount of space, which is not practical for use in one's home. A low cost AC/DC converter with efficient power transfer is needed in order to promote the use of cheaper low power wind turbines. Only MPPT is implemented in most of these low power wind turbine power converters. The concept of power factor correction with MPPT has not been completely adapted just yet. The research conducted involved analyzing the effect of power factor correction and maximum power point tracking algorithm in AC/DC converters for wind turbine applications. Although maximum power to the load is always desired, most converters only take electrical efficiency into consideration. However, not only the electrical efficiency must be considered, but the mechanical energy as well. If the converter is designed to look like a purely resistive load and not a switched load, a wind turbine is able to supply the maximum power with lower conduction loss at the input side due to high current spikes. Two power converters, VIENNA with buck converter and a Buck-boost converter, were designed and experimentally analyzed. A unique approach of controlling the MPPT algorithm through a conductance G for PFC is proposed and applied in the VIENNA topology. On the other hand, the Buck-boost only operates MPPT. With the same wind profile applied for both converters, an increase in power drawn from the input increased when PFC was used even when the power level was low. Both topologies present their own unique advantages. The main advantage for the VIENNA converter is that PFC allowed more power extraction from the turbine, increasing both electrical and mechanical efficiency. The buck-boost converter, on the other hand, presents a very low component count which decreases the overall cost and volume. Therefore, a small, cost-effective converter that maximizes the power transfer from a small power wind turbine to a DC load, can motivate consumers to utilize the power available from the wind.
Show less - Date Issued
- 2009
- Identifier
- CFE0002730, ucf:48158
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002730
- Title
- Synthesis and Characterization of New Probes for use in Fluorescence and X-ray CT Bioimaging.
- Creator
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Tang, Simon, Belfield, Kevin, Miles, Delbert, Campiglia, Andres, Zou, Shengli, Cheng, Zixi, University of Central Florida
- Abstract / Description
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The pursuit of more suitable drugs intended for possible biological applications are a continuously growing topic of research within the scientific community. One of these suitable qualities includes the need for hydrophilicity and or some appropriate delivery system for the drug to enter into biological systems. A system of analyzing and following these compounds would then, however, be necessary to conduct any kind of mechanistic or interaction studies for he said drug within the biological...
Show moreThe pursuit of more suitable drugs intended for possible biological applications are a continuously growing topic of research within the scientific community. One of these suitable qualities includes the need for hydrophilicity and or some appropriate delivery system for the drug to enter into biological systems. A system of analyzing and following these compounds would then, however, be necessary to conduct any kind of mechanistic or interaction studies for he said drug within the biological system. Just to name a few, fluorescence and X-ray computed tomography (CT) methods allow for imaging of biological systems but require the need of compounds with specific qualities. Finally, even with a means of entering and following a oaded drug, it would not be complete without a way of targeting its intended location. Herein, the first chapter reports the synthesis and characterization of a fluorene-based pyridil bis-?-diketone compound with suitable one- and two-photon fluorescent properties and its encapsulation into Pluronic F127 micelles for the possible application of tracking lysosomes. Next the synthesis and characterization of a BODIPY-based fluorophore with excellent fluorescence ability is reported. This compound was conjugated to two triphenylphosphine (TPP) groups and is shown as a potential mitochondria probe within HCT-116 cells. Finally, the synthesis and characterization of diatrizoic acid (DA) based derivatives conjugated to silica nanoparticles, as well as unconjugated, are reported as potential CT contrast agents. The derivatives were also functionalized with maleimide moieties facilitating subsequent potential bioconjugation of a targeting protein via a thiol group.
Show less - Date Issued
- 2015
- Identifier
- CFE0006056, ucf:50961
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006056
- Title
- Detecting, Tracking, and Recognizing Activities in Aerial Video.
- Creator
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Reilly, Vladimir, Shah, Mubarak, Georgiopoulos, Michael, Stanley, Kenneth, Dogariu, Aristide, University of Central Florida
- Abstract / Description
-
In this dissertation we address the problem of detecting humans and vehicles, tracking their identities in crowded scenes, and finally determining human activities. First, we tackle the problem of detecting moving as well as stationary objects in scenes that contain parallax and shadows. We constrain the search of pedestrians and vehicles by representing them as shadow casting out of plane or (SCOOP) objects.Next, we propose a novel method for tracking a large number of densely moving objects...
Show moreIn this dissertation we address the problem of detecting humans and vehicles, tracking their identities in crowded scenes, and finally determining human activities. First, we tackle the problem of detecting moving as well as stationary objects in scenes that contain parallax and shadows. We constrain the search of pedestrians and vehicles by representing them as shadow casting out of plane or (SCOOP) objects.Next, we propose a novel method for tracking a large number of densely moving objects in aerial video. We divide the scene into grid cells to define a set of local scene constraints which we use as part of the matching cost function to solve the tracking problem which allows us to track fast-moving objects in low frame rate videos.Finally, we propose a method for recognizing human actions from few examples. We use the bag of words action representation, assume that most of the classes have many examples, and construct Support Vector Machine models for each class. We then use Support Vector Machines for classes with many examples to improve the decision function of the Support Vector Machine that was trained using few examples via late fusion of weighted decision values.
Show less - Date Issued
- 2012
- Identifier
- CFE0004627, ucf:49935
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004627
- Title
- On RADAR DECEPTION, AS MOTIVATION FOR CONTROL OF CONSTRAINED SYSTEMS.
- Creator
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Hajieghrary, Hadi, Jayasuriya, Suhada, Xu, Yunjun, Das, Tuhin, University of Central Florida
- Abstract / Description
-
This thesis studies the control algorithms used by a team of ECAVs (Electronic Combat Air Vehicle) to deceive a network of radars to detect a phantom track. Each ECAV has the electronic capability of intercepting the radar waves, and introducing an appropriate time delay before transmitting it back, and deceiving the radar into seeing a spurious target beyond its actual position. On the other hand, to avoid the errors and increase the reliability, have a complete coverage in various...
Show moreThis thesis studies the control algorithms used by a team of ECAVs (Electronic Combat Air Vehicle) to deceive a network of radars to detect a phantom track. Each ECAV has the electronic capability of intercepting the radar waves, and introducing an appropriate time delay before transmitting it back, and deceiving the radar into seeing a spurious target beyond its actual position. On the other hand, to avoid the errors and increase the reliability, have a complete coverage in various atmosphere conditions, and confronting the effort of the belligerent intruders to delude the sentinel and enter the area usually a network of radars are deployed to guard the region. However, a team of cooperating ECAVs could exploit this arrangement and plans their trajectories in a way all the radars in the network vouch for seeing a single and coherent spurious track of a phantom. Since each station in the network confirms the other, the phantom track is considered valid. This problem serves as a motivating example in trajectory planning for the multi-agent system in highly constrained operation conditions. The given control command to each agent should be a viable one in the agent limited capabilities, and also drives it in a cumulative action to keep the formation.In this thesis, three different approaches to devise a trajectory for each agent is studied, and the difficulties for deploying each one are addressed. In the first one, a command center has all information about the state of the agents, and in every step decides about the control each agent should apply. This method is very effective and robust, but needs a reliable communication. In the second method, each agent decides on its own control, and the members of the group just communicate and agree on the range of control they like to apply on the phantom. Although in this method much less data needs to communicate between the agents, it is very sensitive to the disturbances and miscalculations, and could be easily fell apart or come to a state with no feasible solution to continue. In the third method a differential geometric approach to the problem is studied. This method has a very strong backbone, and minimizes the communication needed to a binary one. However, less data provided to the agents about the system, more sensitive and infirm the system is when it faced with imperfectionalities. In this thesis, an object oriented program is developed in the Matlab software area to simulate all these three control strategies in a scalable fashion. Object oriented programming is a naturally suitable method to simulate a multi-agent system. It gives the flexibility to make the code more close to a real scenario with defining each agent as a separated and independent identity. The main objective is to understand the nature of the constrained dynamic problems, and examine various solutions in different situations. Using the flexibility of this code, we could simulate several scenarios, and incorporate various conditions on the system. Also, we could have a close look at each agent to observe its behavior in these situations. In this way we will gain a good insight of the system which could be used in designing of the agents for specific missions.
Show less - Date Issued
- 2013
- Identifier
- CFE0004857, ucf:49683
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004857
- Title
- MAXIMUM ENERGY HARVESTING CONTROL FOROSCILLATING ENERGY HARVESTING SYSTEMS.
- Creator
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Elmes, John, Batarseh, Issa, University of Central Florida
- Abstract / Description
-
This thesis presents an optimal method of designing and controlling an oscillating energy harvesting system. Many new and emerging energy harvesting systems, such as the energy harvesting backpack and ocean wave energy harvesting, capture energy normally expelled through mechanical interactions. Often the nature of the system indicates slow system time constants and unsteady AC voltages. This paper reveals a method for achieving maximum energy harvesting from such sources with fast...
Show moreThis thesis presents an optimal method of designing and controlling an oscillating energy harvesting system. Many new and emerging energy harvesting systems, such as the energy harvesting backpack and ocean wave energy harvesting, capture energy normally expelled through mechanical interactions. Often the nature of the system indicates slow system time constants and unsteady AC voltages. This paper reveals a method for achieving maximum energy harvesting from such sources with fast determination of the optimal operating condition. An energy harvesting backpack, which captures energy from the interaction between the user and the spring decoupled load, is presented in this paper. The new control strategy, maximum energy harvesting control (MEHC), is developed and applied to the energy harvesting backpack system to evaluate the improvement of the MEHC over the basic maximum power point tracking algorithm.
Show less - Date Issued
- 2007
- Identifier
- CFE0001822, ucf:47345
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001822
- Title
- MODELING SCENES AND HUMAN ACTIVITIES IN VIDEOS.
- Creator
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Basharat, Arslan, Shah, Mubarak, University of Central Florida
- Abstract / Description
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In this dissertation, we address the problem of understanding human activities in videos by developing a two-pronged approach: coarse level modeling of scene activities and fine level modeling of individual activities. At the coarse level, where the resolution of the video is low, we rely on person tracks. At the fine level, richer features are available to identify different parts of the human body, therefore we rely on the body joint tracks. There are three main goals of this dissertation: ...
Show moreIn this dissertation, we address the problem of understanding human activities in videos by developing a two-pronged approach: coarse level modeling of scene activities and fine level modeling of individual activities. At the coarse level, where the resolution of the video is low, we rely on person tracks. At the fine level, richer features are available to identify different parts of the human body, therefore we rely on the body joint tracks. There are three main goals of this dissertation: (1) identify unusual activities at the coarse level, (2) recognize different activities at the fine level, and (3) predict the behavior for synthesizing and tracking activities at the fine level. The first goal is addressed by modeling activities at the coarse level through two novel and complementing approaches. The first approach learns the behavior of individuals by capturing the patterns of motion and size of objects in a compact model. Probability density function (pdf) at each pixel is modeled as a multivariate Gaussian Mixture Model (GMM), which is learnt using unsupervised expectation maximization (EM). In contrast, the second approach learns the interaction of object pairs concurrently present in the scene. This can be useful in detecting more complex activities than those modeled by the first approach. We use a 14-dimensional Kernel Density Estimation (KDE) that captures motion and size of concurrently tracked objects. The proposed models have been successfully used to automatically detect activities like unusual person drop-off and pickup, jaywalking, etc. The second and third goals of modeling human activities at the fine level are addressed by employing concepts from theory of chaos and non-linear dynamical systems. We show that the proposed model is useful for recognition and prediction of the underlying dynamics of human activities. We treat the trajectories of human body joints as the observed time series generated from an underlying dynamical system. The observed data is used to reconstruct a phase (or state) space of appropriate dimension by employing the delay-embedding technique. This transformation is performed without assuming an exact model of the underlying dynamics and provides a characteristic representation that will prove to be vital for recognition and prediction tasks. For recognition, properties of phase space are captured in terms of dynamical and metric invariants, which include the Lyapunov exponent, correlation integral, and correlation dimension. A composite feature vector containing these invariants represents the action and will be used for classification. For prediction, kernel regression is used in the phase space to compute predictions with a specified initial condition. This approach has the advantage of modeling dynamics without making any assumptions about the exact form (polynomial, radial basis, etc.) of the mapping function. We demonstrate the utility of these predictions for human activity synthesis and tracking.
Show less - Date Issued
- 2009
- Identifier
- CFE0002897, ucf:48042
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002897
- Title
- CONTROL STRATEGY FOR MAXIMIZING POWER CONVERSION EFFICIENCY AND EFFECTIVENESS OF THREE PORT SOLAR CHARGING STATION FOR ELECTRIC VEHICLES.
- Creator
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Hamilton, Christopher, Batarseh, Issa, University of Central Florida
- Abstract / Description
-
Recent trends in the energy sector have provided opportunities in the research of alternative energy sources and optimization of systems that harness these energy sources. With the rising cost of fossil fuel and rising concern about detrimental effects that fossil fuel consumption has on the environment, electric vehicles are becoming more prevalent. A study put out in 2009 gives a prediction that in the year 2025, 20% of new vehicles will be PHEVs. As energy providers become more concerned...
Show moreRecent trends in the energy sector have provided opportunities in the research of alternative energy sources and optimization of systems that harness these energy sources. With the rising cost of fossil fuel and rising concern about detrimental effects that fossil fuel consumption has on the environment, electric vehicles are becoming more prevalent. A study put out in 2009 gives a prediction that in the year 2025, 20% of new vehicles will be PHEVs. As energy providers become more concerned about a growing population and diminishing energy source, they are looking into alternative energy sources such as wind and solar power. Much of this is done on a large scale with vast amounts of land used for solar or wind farms to provide energy to the grid. However, as population grows, requirements of the physical components of a power transmission system will become more demanding and the need for remote micro-grids will become more prevalent. Micro-grids are essentially smaller subsystems of a distribution system that provide power to a confined group of loads, or households. Using the idea of micro grid technology, a solar charging station can be used as a source to provide energy for the immediate surroundings, or also to electric vehicles that are demanding energy from the panels. Solar charging stations are becoming very popular, however the need for improvement and optimization of these systems is needed. This thesis will present a method for redesigning the overall architecture of the controls and power electronics of typical carports so that efficiency, reliability and modularity are achieved. Specifically, a typical carport, as seen commonly today, has been built on the University of Central Florida campus in Orlando. This carport was designed in such a way that shifting from conventional charging methods is made easy while preserving the fundamental requirements of a practical solar carport.
Show less - Date Issued
- 2010
- Identifier
- CFE0003490, ucf:48954
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003490
- Title
- Computational Fluid Dynamics Study of Thromboembolism as a Function of Shunt Size and Placement in the Hybrid Norwood Palliative Treatment of Hypoplastic Left Heart Syndrome.
- Creator
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Seligson, John, Kassab, Alain, DeCampli, William, Mansy, Hansen, University of Central Florida
- Abstract / Description
-
The Hybrid Norwood procedure has emerged as a promising alternative palliative first stage treatment for infants with Hypoplastic Left Heart Syndrome (HLHS). The procedure is done to provide necessary blood flow to the pulmonary and systemic regions of the body. The procedure can affect hemodynamic conditions to be pro-thrombotic, and thrombus particles can form and release from the vessel walls and enter the flow. Assuming these particles are formed and released from the shunt surface, a...
Show moreThe Hybrid Norwood procedure has emerged as a promising alternative palliative first stage treatment for infants with Hypoplastic Left Heart Syndrome (HLHS). The procedure is done to provide necessary blood flow to the pulmonary and systemic regions of the body. The procedure can affect hemodynamic conditions to be pro-thrombotic, and thrombus particles can form and release from the vessel walls and enter the flow. Assuming these particles are formed and released from the shunt surface, a Computational Fluid Dynamics (CFD) model can be used to mimic the patient's vasculature geometry and predict the occurrence of embolization to the carotid or coronary arteries, as well as the other major arteries surrounding the heart. This study used a time dependent, multi-scale CFD analysis on patient-specific geometry to determine the statistical probability of thrombus particles exiting each major artery. The geometries explored were of a nominal and patient specific nature. Cases of 90% and 0% stenosis at the aortic arch were analyzed, including shunt diameters of 3mm, 3.5mm, and 4mm. Three different placements of the shunt were explored as well. The intent of this study was to suggest best methods of surgical planning in the Hybrid Norwood procedure by providing supporting data for optimal stroke and myocardial infarction prevention.
Show less - Date Issued
- 2017
- Identifier
- CFE0006655, ucf:51232
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006655
- Title
- An investigation of physiological measures in a marketing decision task.
- Creator
-
Lerma, Nelson, Karwowski, Waldemar, Elshennawy, Ahmad, Xanthopoulos, Petros, Reinerman, Lauren, University of Central Florida
- Abstract / Description
-
The objective of the present study was to understand the use of physiological measures as an alternative to traditional market research tools, such as self-reporting measures and focus groups. For centuries, corporations and researchers have relied almost exclusively on traditional measures to gain insights into consumer behavior. Oftentimes, traditional methods have failed to accurately predict consumer demand, and this has prompted corporations to explore alternative methods that will...
Show moreThe objective of the present study was to understand the use of physiological measures as an alternative to traditional market research tools, such as self-reporting measures and focus groups. For centuries, corporations and researchers have relied almost exclusively on traditional measures to gain insights into consumer behavior. Oftentimes, traditional methods have failed to accurately predict consumer demand, and this has prompted corporations to explore alternative methods that will accurately forecast future sales. One the most promising alternative methods currently being investigated is the use of physiological measures as an indication of consumer preference. This field, also referred to as neuromarketing, has blended the principles of psychology, neuroscience, and market research to explore consumer behavior from a physiological perspective. The goal of neuromarketing is to capture consumer behavior through the use of physiological sensors. This study investigated the extent to which physiological measures where correlated to consumer preferences by utilizing five physiological sensors which included two neurological sensors (EEG and ECG) two hemodynamic sensors (TCD and fNIR) and one optic sensor (eye-tracking). All five physiological sensors were used simultaneously to capture and record physiological changes during four distinct marketing tasks. The results showed that only one physiological sensor, EEG, was indicative of concept type and intent to purchase. The remaining four physiological sensors did not show any significant differences for concept type or intent to purchase.Furthermore, Machine Learning Algorithms (MLAs) were used to determine the extent to which MLAs (Na(&)#239;ve Bayes, Multilayer Perceptron, K-Nearest Neighbor, and Logistic Regression) could classify physiological responses to self-reporting measures obtained during a marketing task. The results demonstrated that Multilayer Perceptron, on average, performed better than the other MLAs for intent to purchase and concept type. It was also evident that the models faired best with the most popular concept when categorizing the data based on intent to purchase or final selection. Overall, the four models performed well at categorizing the most popular concept and gave some indication to the extent to which physiological measures are capable of capturing intent to purchase. The research study was intended to help better understand the possibilities and limitations of physiological measures in the field of market research. Based on the results obtained, this study demonstrated that certain physiological sensors are capable of capturing emotional changes, but only when the emotional response between two concepts is significantly different. Overall, physiological measures hold great promise in the study of consumer behavior, providing great insight on the relationship between emotions and intentions in market research.
Show less - Date Issued
- 2015
- Identifier
- CFE0006345, ucf:51563
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006345
- Title
- Exploring 3D User Interface Technologies for Improving the Gaming Experience.
- Creator
-
Kulshreshth, Arun, Laviola II, Joseph, Hughes, Charles, Da Vitoria Lobo, Niels, Masuch, Maic, University of Central Florida
- Abstract / Description
-
3D user interface technologies have the potential to make games more immersive (&) engaging and thus potentially provide a better user experience to gamers. Although 3D user interface technologies are available for games, it is still unclear how their usage affects game play and if there are any user performance benefits. A systematic study of these technologies in game environments is required to understand how game play is affected and how we can optimize the usage in order to achieve...
Show more3D user interface technologies have the potential to make games more immersive (&) engaging and thus potentially provide a better user experience to gamers. Although 3D user interface technologies are available for games, it is still unclear how their usage affects game play and if there are any user performance benefits. A systematic study of these technologies in game environments is required to understand how game play is affected and how we can optimize the usage in order to achieve better game play experience.This dissertation seeks to improve the gaming experience by exploring several 3DUI technologies. In this work, we focused on stereoscopic 3D viewing (to improve viewing experience) coupled with motion based control, head tracking (to make games more engaging), and faster gesture based menu selection (to reduce cognitive burden associated with menu interaction while playing). We first studied each of these technologies in isolation to understand their benefits for games. We present the results of our experiments to evaluate benefits of stereoscopic 3D (when coupled with motion based control) and head tracking in games. We discuss the reasons behind these findings and provide recommendations for game designers who want to make use of these technologies to enhance gaming experiences. We also present the results of our experiments with finger-based menu selection techniques with an aim to find out the fastest technique. Based on these findings, we custom designed an air-combat game prototype which simultaneously uses stereoscopic 3D, head tracking, and finger-count shortcuts to prove that these technologies could be useful for games if the game is designed with these technologies in mind. Additionally, to enhance depth discrimination and minimize visual discomfort, the game dynamically optimizes stereoscopic 3D parameters (convergence and separation) based on the user's look direction. We conducted a within subjects experiment where we examined performance data and self-reported data on users perception of the game. Our results indicate that participants performed significantly better when all the 3DUI technologies (stereoscopic 3D, head-tracking and finger-count gestures) were available simultaneously with head tracking as a dominant factor. We explore the individual contribution of each of these technologies to the overall gaming experience and discuss the reasons behind our findings.Our experiments indicate that 3D user interface technologies could make gaming experience better if used effectively. The games must be designed to make use of the 3D user interface technologies available in order to provide a better gaming experience to the user. We explored a few technologies as part of this work and obtained some design guidelines for future game designers. We hope that our work will serve as the framework for the future explorations of making games better using 3D user interface technologies.
Show less - Date Issued
- 2015
- Identifier
- CFE0005643, ucf:50190
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005643
- Title
- An Investigation of the Academic Impact of the Freshman Transition Course at One Urban Central Florida High School.
- Creator
-
Flynn, Timothy, Taylor, Rosemarye, Baldwin, Lee, Doherty, Walter, Bradshaw, Leigh, University of Central Florida
- Abstract / Description
-
The purpose of this research was to identify the extent to which a high school freshman transition program aligned with research based recommendations and to determine the extent to which the intervention impacted persistence to the tenth grade, on-track-to-graduation status, and academic success. Documents relevant to the program were collected and analyzed for research based themes. Students in the program at the target school were compared to students in a similar high school and a...
Show moreThe purpose of this research was to identify the extent to which a high school freshman transition program aligned with research based recommendations and to determine the extent to which the intervention impacted persistence to the tenth grade, on-track-to-graduation status, and academic success. Documents relevant to the program were collected and analyzed for research based themes. Students in the program at the target school were compared to students in a similar high school and a historical cohort of students who attended the target school. The impact of the course was statistically significant for persistence to the tenth grade, on-track to graduation status, and academic success; however ANOVA found statistical significance favored Algebra 1 EOC and not FCAT Reading. Effect size statistics revealed little to no effect among Freshman Experience and the dependent variables. These findings will help school-level and district administrators design research-based transition interventions which encourage academic success and graduation.
Show less - Date Issued
- 2016
- Identifier
- CFE0006684, ucf:51902
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006684
- Title
- Physiological Reactions to Uncanny Stimuli: Substantiation of Self-Assessment and Individual Perception in User Enjoyment and Comfort.
- Creator
-
Ballion, Tatiana, Sims, Valerie, Chin, Matthew, Jones, Donald, University of Central Florida
- Abstract / Description
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There is abundant anecdotal evidence substantiating Mori's initial observation of the "uncanny valley", a point at which human response to non-human entities drops sharply with respect to comfort (Mori, 1970), and the construct itself has a long-standing history in both Robotics and Psychology. Currently, many fields such as design, training, entertainment, and education make use of heuristic approaches to accommodate the anticipated needs of the user/consumer/audience in certain important...
Show moreThere is abundant anecdotal evidence substantiating Mori's initial observation of the "uncanny valley", a point at which human response to non-human entities drops sharply with respect to comfort (Mori, 1970), and the construct itself has a long-standing history in both Robotics and Psychology. Currently, many fields such as design, training, entertainment, and education make use of heuristic approaches to accommodate the anticipated needs of the user/consumer/audience in certain important aspects. This is due to the lack of empirical substantiation or, in some cases, the impossibility of rigorous quantification; one such area is with respect to the user's experience of uncanniness, a feeling of "eeriness" or "wrongness" when interacting with artefacts or environments. Uncanniness, however, continues to be defined and measured in a largely subjective way, and often after the fact; an experience or product's uncanny features are pointed out after the item has been markedly avoided or complained about by the general public. These studies are among the first seeking to determine a constellation of personality traits and physiological responses that incline the user to have a more frequent or profound (")uncanny" reaction when presented with stimuli meeting the criteria for a level of "eeriness". In study 1, 395 adults were asked to categorize 200 images as uncanny, neutral, pleasant, or other. In Study 2, physiological and eye-tracking data was collected from twenty two adults as they viewed uncanny, neutral and pleasant images culled from study 1. This research identifies components of the uncanny valley related to subjective assessment, personality factors (using the HEXACO and Anthropomorphic Tendencies Scale), and biophysical measures, and found that traits unique to Emotionality on the HEXACO inventory, compounded with a form of anthropomorphism demonstrates a level of relationship to the subjective experience of uncanny stimuli. There is evidence that HEXACO type and forms of anthropomorphic perception mediates the biophysical expression and the subjective perception of the stimuli. In keeping with psychological hypotheses, stimuli to which the participants had greatest response centered on death, the threat of death, or mismatched/absent facial features.
Show less - Date Issued
- 2012
- Identifier
- CFE0004354, ucf:49454
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004354
- Title
- PATTERNS OF MOTION: DISCOVERY AND GENERALIZED REPRESENTATION.
- Creator
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Saleemi, Imran, Shah, Mubarak, University of Central Florida
- Abstract / Description
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In this dissertation, we address the problem of discovery and representation of motion patterns in a variety of scenarios, commonly encountered in vision applications. The overarching goal is to devise a generic representation, that captures any kind of object motion observable in video sequences. Such motion is a significant source of information typically employed for diverse applications such as tracking, anomaly detection, and action and event recognition. We present statistical...
Show moreIn this dissertation, we address the problem of discovery and representation of motion patterns in a variety of scenarios, commonly encountered in vision applications. The overarching goal is to devise a generic representation, that captures any kind of object motion observable in video sequences. Such motion is a significant source of information typically employed for diverse applications such as tracking, anomaly detection, and action and event recognition. We present statistical frameworks for representation of motion characteristics of objects, learned from tracks or optical flow, for static as well as moving cameras, and propose algorithms for their application to a variety of problems. The proposed motion pattern models and learning methods are general enough to be employed in a variety of problems as we demonstrate experimentally. We first propose a novel method to model and learn the scene activity, observed by a static camera. The motion patterns of objects in the scene are modeled in the form of a multivariate non-parametric probability density function of spatiotemporal variables (object locations and transition times between them). Kernel Density Estimation (KDE) is used to learn this model in a completely unsupervised fashion. Learning is accomplished by observing the trajectories of objects by a static camera over extended periods of time. The model encodes the probabilistic nature of the behavior of moving objects in the scene and is useful for activity analysis applications, such as persistent tracking and anomalous motion detection. In addition, the model also captures salient scene features, such as, the areas of occlusion and most likely paths. Once the model is learned, we use a unified Markov Chain Monte-Carlo (MCMC) based framework for generating the most likely paths in the scene, improving foreground detection, persistent labelling of objects during tracking and deciding whether a given trajectory represents an anomaly to the observed motion patterns. Experiments with real world videos are reported which validate the proposed approach. The representation and estimation framework proposed above, however, has a few limitations. This algorithm proposes to use a single global statistical distribution to represent all kinds of motion observed in a particular scene. It therefore, does not find a separation between multiple semantically distinct motion patterns in the scene. Instead, the learned model is a joint distribution over all possible patterns followed by objects. To overcome this limitation, we then propose a superior method for the discovery and statistical representation of motion patterns in a scene. The advantages of this approach over the first one are two-fold: first, this model is applicable to scenes of dense crowded motion where tracking may not be feasible, and second, it distinguishes between motion patterns that are distinct at a semantic level of abstraction. We propose a mixture model representation of salient patterns of optical flow, and present an algorithm for learning these patterns from dense optical flow in a hierarchical, unsupervised fashion. Using low level cues of noisy optical flow, K-means is employed to initialize a Gaussian mixture model for temporally segmented clips of video. The components of this mixture are then filtered and instances of motion patterns are computed using a simple motion model, by linking components across space and time. Motion patterns are then initialized and membership of instances in different motion patterns is established by using KL divergence between mixture distributions of pattern instances. Finally, a pixel level representation of motion patterns is proposed by deriving conditional expectation of optical flow. Results of extensive experiments are presented for multiple surveillance sequences containing numerous patterns involving both pedestrian and vehicular traffic. The proposed method exploits optical flow as the low level feature and performs a hierarchical clustering to obtain motion patterns; and we observe that the use of optical flow is also an integral part of a variety of other vision applications, for example, as features based representation of human actions. We, therefore, propose a new representation for articulated human actions using the motion patterns. The representation is based on hierarchical clustering of observed optical flow in four dimensional, spatial and motion flow space. The automatically discovered motion patterns, are the primitive actions, representative of flow at salient regions on the human body, much like trajectories of body joints, which are notoriously difficult to obtain automatically. The proposed method works in a completely unsupervised fashion, and in sharp contrast to state of the art representations like bag of video words, provides a truly semantically meaningful representation. Each primitive action depicts the most atomic sub-action, like left arm moving upwards, or right leg moving downward and leftward, and is represented by a mixture of four dimensional Gaussian distributions. A sequence of primitive actions are discovered in the test video, and labelled by computing the KL divergence between mixtures. The entire video sequence containing the human action, is thus reduced to a simple string, which is matched against similar strings of training videos to classify the action. The string matching is performed by global alignment, using the well-known Needleman-Wunsch algorithm. Experiments reported on multiple human actions data sets, confirm the validity, simplicity, and semantically meaningful nature of the proposed representation. Results obtained are encouraging and comparable to the state of the art.
Show less - Date Issued
- 2011
- Identifier
- CFE0003646, ucf:48836
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003646
- Title
- Investigating the universality and comprehensive ability of measures to assess the state of workload.
- Creator
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Abich, Julian, Reinerman, Lauren, Lackey, Stephanie, Szalma, James, Taylor, Grant, University of Central Florida
- Abstract / Description
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Measures of workload have been developed on the basis of the various definitions, some are designed to capture the multi-dimensional aspects of a unitary resource pool (Kahneman, 1973) while others are developed on the basis of multiple resource theory (Wickens, 2002). Although many theory based workload measures exist, others have often been constructed to serve the purpose of specific experimental tasks. As a result, it is likely that not every workload measure is reliable and valid for all...
Show moreMeasures of workload have been developed on the basis of the various definitions, some are designed to capture the multi-dimensional aspects of a unitary resource pool (Kahneman, 1973) while others are developed on the basis of multiple resource theory (Wickens, 2002). Although many theory based workload measures exist, others have often been constructed to serve the purpose of specific experimental tasks. As a result, it is likely that not every workload measure is reliable and valid for all tasks, much less each domain. To date, no single measure, systematically tested across experimental tasks, domains, and other measures is considered a universal measure of workload. Most researchers would argue that multiple measures from various categories should be applied to a given task to comprehensively assess workload. The goal for Study 1 to establish task load manipulations for two theoretically different tasks that induce distinct levels of workload assessed by both subjective and performance measures was successful. The results of the subjective responses support standardization and validation of the tasks and demands of that task for investigating workload. After investigating the use of subjective and objective measures of workload to identify a universal and comprehensive measure or set of measures, based on Study 2, it can only be concluded that not one or a set of measures exists. Arguably, it is not to say that one will never be conceived and developed, but at this time, one does not reside in the psychometric catalog. Instead, it appears that a more suitable approach is to customize a set of workload measures based on the task. The novel approach of assessing the sensitivity and comprehensive ability of conjointly utilizing subjective, performance, and physiological workload measures for theoretically different tasks within the same domain contributes to the theory by laying the foundation for improving methodology for researching workload. The applicable contribution of this project is a stepping-stone towards developing complex profiles of workload for use in closed-loop systems, such as human-robot team interaction. Identifying the best combination of workload measures enables human factors practitioners, trainers, and task designers to improve methodology and evaluation of system designs, training requirements, and personnel selection.
Show less - Date Issued
- 2013
- Identifier
- CFE0005119, ucf:50675
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005119
