Current Search: feature (x)
Pages
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Title
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HOPE FOR A THORN: THE MAKING OF A MICROBUDGET DIGITAL FEATURE FILM.
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Creator
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Kitzinger, Leslie, Stoeckl, Ula, University of Central Florida
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Abstract / Description
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This paper provides a look at the making of a microbudget feature film. It seeks to explain my growth as a filmmaker and an artist, through the challenges, both narrative and practical, that I encountered, as well as provide documentation following the process. Hope for a Thorn: The Making of a Microbudget Digital Feature Film includes elements from each phase of filmmaking, from script and preproduction to the marketing plan. This document shows the tremendous amount of preparation and...
Show moreThis paper provides a look at the making of a microbudget feature film. It seeks to explain my growth as a filmmaker and an artist, through the challenges, both narrative and practical, that I encountered, as well as provide documentation following the process. Hope for a Thorn: The Making of a Microbudget Digital Feature Film includes elements from each phase of filmmaking, from script and preproduction to the marketing plan. This document shows the tremendous amount of preparation and planning that goes into the making of a microbudget digital feature film.
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Date Issued
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2008
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Identifier
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CFE0002322, ucf:47880
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002322
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Title
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Analyses and comparisons of three lexical features in native and nonnative academic English writing.
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Creator
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Yu, Xiaoli, Folse, Keith, Fernandez-Rubiera, Francisco, Young, Beth, Boote, David, University of Central Florida
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Abstract / Description
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Built upon the Contrastive Interlanguage Analysis (CIA) framework, this corpus-based research analyzes three lexical features (lexical diversity, lexical sophistication, and cohesion) in native and nonnative English writers' academic writing and examines the potential differences in lexical performance 1) between native and nonnative English writers and 2) across all writers from various language backgrounds. The differences in lexical performance in academic writing between native and...
Show moreBuilt upon the Contrastive Interlanguage Analysis (CIA) framework, this corpus-based research analyzes three lexical features (lexical diversity, lexical sophistication, and cohesion) in native and nonnative English writers' academic writing and examines the potential differences in lexical performance 1) between native and nonnative English writers and 2) across all writers from various language backgrounds. The differences in lexical performance in academic writing between native and nonnative English writers and the unique characteristics of writers from different language backgrounds suggest the necessity of targeted academic writing instruction based upon learner needs. Using text length as the covariate, two Multivariate Analysis of Covariate (MANCOVA) were conducted with language background as the Independent Variable and the three lexical features as the Dependent Variables. The results revealed that nonnative English writers demonstrated significantly lower performance in lexical sophistication than did native English writers. In terms of the comparison between writers from different language backgrounds, the results suggested statistically significant differences in all three aspects of lexical features. Pedagogical implications for vocabulary instruction in academic writing for nonnative English writers include emphasizing the mastery of academic, low-frequency, and discipline-specific vocabulary. In addition, improving nonnative writers' vocabulary size and lexical diversity can offer these learners more options to build cohesion in academic writing at a deeper level. Moreover, the results of this study highlight the wide but often under-considered variability within any language group as individual learner differences come into play, thereby downplaying the idea that writers of any given language tend to perform homogenously. Instructors should acknowledge the unique writing characteristics of different nonnative writers and their varied learner needs. Thus, targeted instruction is essential to provide effective enhancement to nonnative English writers' lexical performance in academic writing.
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Date Issued
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2018
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Identifier
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CFE0007269, ucf:52206
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007269
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Title
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Methods for online feature selection for classification problems.
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Creator
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Razmjoo, Alaleh, Zheng, Qipeng, Rabelo, Luis, Boginski, Vladimir, Xanthopoulos, Petros, University of Central Florida
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Abstract / Description
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Online learning is a growing branch of machine learning which allows all traditional data miningtechniques to be applied on an online stream of data in real-time. In this dissertation, we presentthree efficient algorithms for feature ranking in online classification problems. Each of the methodsare tailored to work well with different types of classification tasks and have different advantages.The reason for this variety of algorithms is that like other machine learning solutions, there is...
Show moreOnline learning is a growing branch of machine learning which allows all traditional data miningtechniques to be applied on an online stream of data in real-time. In this dissertation, we presentthree efficient algorithms for feature ranking in online classification problems. Each of the methodsare tailored to work well with different types of classification tasks and have different advantages.The reason for this variety of algorithms is that like other machine learning solutions, there is usuallyno algorithm which works well for all types of tasks. The first method, is an online sensitivitybased feature ranking (SFR) which is updated incrementally, and is designed for classificationtasks with continuous features. We take advantage of the concept of global sensitivity and rankfeatures based on their impact on the outcome of the classification model. In the feature selectionpart, we use a two-stage filtering method in order to first eliminate highly correlated and redundantfeatures and then eliminate irrelevant features in the second stage. One important advantage of ouralgorithm is its generality, which means the method works for correlated feature spaces withoutpreprocessing. It can be implemented along with any single-pass online classification method withseparating hyperplane such as SVMs. In the second method, with help of probability theory wepropose an algorithm which measures the importance of the features by observing the changes inlabel prediction in case of feature substitution. A non-parametric version of the proposed methodis presented to eliminate the distribution type assumptions. These methods are application to alldata types including mixed feature spaces. At last, we present a class-based feature importanceranking method which evaluates the importance of each feature for each class, these sub-rankingsare further exploited to train an ensemble of classifiers. The proposed methods will be thoroughlytested using benchmark datasets and the results will be discussed in the last chapter.
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Date Issued
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2018
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Identifier
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CFE0007584, ucf:52567
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007584
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Title
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AN EXPERIMENTAL INVESTIGATION OF HEAT TRANSFER FOR ARRAYS OF IMPINGEMENT JETS ONTO THE FEATURED SURFACES WITH CYLINDRICAL AND ELLIPTICAL RAISED SURFACES.
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Creator
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Medina, Marc A, Kapat, Jayanta, University of Central Florida
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Abstract / Description
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This study focuses on multi-jet impingement for gas turbine geometries in which the objective is to understand the influence of the roughness elements on a target surface to the heat transfer. Current work has proven that implementing roughness elements for multi-jet impingement target surfaces has increased heat transfer ranging anywhere from 10-30%. This study has chosen to investigate three different roughness elements, elliptical in cross-section, to compare to smooth surface geometries...
Show moreThis study focuses on multi-jet impingement for gas turbine geometries in which the objective is to understand the influence of the roughness elements on a target surface to the heat transfer. Current work has proven that implementing roughness elements for multi-jet impingement target surfaces has increased heat transfer ranging anywhere from 10-30%. This study has chosen to investigate three different roughness elements, elliptical in cross-section, to compare to smooth surface geometries for multi-jet impingement. An experimental was taken for this study to extend the current knowledge of multi-jet impingement geometries and to further understand the heat transfer performance. A temperature sensitive paint (TSP) technique was used to measure the heat transfer on the target surface, in which the local temperature was measured to estimate area averaged heat transfer coefficient (HTC) and row averaged HTC. In order stay consistent with literature, non-dimensional parameters were used for geometry locations and boundaries. For this study, the Reynolds number range, based on jet diameter and mass flux, is 10-15k. The X/D (streamwise direction), Y/D (spanwise direction), Z/D (channel height direction), L/D (thickness of the jet plate) constraints for this study are 5, 6, 3, and 1 respectively. From the local heat transfer distributions of the different roughness elements, it is concluded that the inclusion of these elements increases heat transfer by 2-12% as compared to a flat/smooth target plate. It is therefore recommended from this study, that elements, elliptical in shape, provide favorability in heat transfer for gas turbine configurations.
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Date Issued
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2016
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Identifier
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CFH2000131, ucf:46021
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFH2000131
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Title
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HYBRID AND HIERARCHICAL IMAGE REGISTRATION TECHNIQUES.
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Creator
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Xu, Dongjiang, Kasparis, Takis, University of Central Florida
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Abstract / Description
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A large number of image registration techniques have been developed for various types of sensors and applications, with the aim to improve the accuracy, computational complexity, generality, and robustness. They can be broadly classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in scale, rotation, and translation. In addition,...
Show moreA large number of image registration techniques have been developed for various types of sensors and applications, with the aim to improve the accuracy, computational complexity, generality, and robustness. They can be broadly classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in scale, rotation, and translation. In addition, intensity-based methods lack the robustness in the presence of non-spatial distortions due to different imaging conditions between images. In this dissertation, the image registration is formulated as a two-stage hybrid approach combining both an initial matching and a final matching in a coarse-to-fine manner. In the proposed hybrid framework, the initial matching algorithm is applied at the coarsest scale of images, where the approximate transformation parameters could be first estimated. Subsequently, the robust gradient-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution scheme. Several novel and effective initial matching algorithms have been proposed for the first stage. The variations of the intensity characteristics between images may be large and non-uniform because of non-spatial distortions. Therefore, in order to effectively incorporate the gradient-based robust estimation into our proposed framework, one of the fundamental questions should be addressed: what is a good image representation to work with using gradient-based robust estimation under non-spatial distortions. With the initial matching algorithms applied at the highest level of decomposition, the proposed hybrid approach exhibits superior range of convergence. The gradient-based algorithms in the second stage yield a robust solution that precisely registers images with sub-pixel accuracy. A hierarchical iterative searching further enhances the convergence range and rate. The simulation results demonstrated that the proposed techniques provide significant benefits to the performance of image registration.
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Date Issued
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2004
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Identifier
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CFE0000317, ucf:46294
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0000317
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Title
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AN EXPLORATION INTO THE PSYCHOTIC SYMPTOMS ASSOCIATED WITH SCHIZOPHRENIA AND MAJOR DEPRESSIVE DISORDER.
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Creator
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Michael-Samaroo, Kyndester I, Sugaya, Kimonobu, University of Central Florida
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Abstract / Description
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This research focuses on examining the neurological similarities between schizophrenia and major depressive disorder with psychotic features in order to compare the manifestations of psychosis in each disorder. Both disorders often involve symptoms of psychosis, although the overall disorders are very different from each other. The hypothesis for this research is that the neurological similarities between schizophrenia and major depressive disorder with psychotic features will provide...
Show moreThis research focuses on examining the neurological similarities between schizophrenia and major depressive disorder with psychotic features in order to compare the manifestations of psychosis in each disorder. Both disorders often involve symptoms of psychosis, although the overall disorders are very different from each other. The hypothesis for this research is that the neurological similarities between schizophrenia and major depressive disorder with psychotic features will provide researchers with the strategies needed to develop a treatment for psychotic symptoms. In order to test this hypothesis, five related studies were gathered for each disorder, and three studies were gathered for psychosis. These studies were then analyzed to pinpoint any similarities among factors for psychosis, and this analysis allowed for the determination of whether or not the hypothesis would be rejected. The results indicated that a lot of the similarities between the two disorders cannot be verified because of the lack of substantial research.
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Date Issued
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2018
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Identifier
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CFH2000548, ucf:45669
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFH2000548
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Title
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PERCEIVED GENDER AND ITS EFFECT ON ATTRIBUTIONS TOWARD AVATARS IN THE VIDEO GAME SPORE.
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Creator
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Sweeney, Victoria, Sims, Valerie, University of Central Florida
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Abstract / Description
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In this study, 174 undergraduates from the University of Central Florida were asked to rate individual human and animal avatar features from the video game Spore on their level of femininity, masculinity, likability, and how well the feature represented them on a 7 point Likert scale of agreeability. Avatar features were presented on a neutral gray, quadruped body in two different views. It was expected that participants would show higher likability for avatar features that they perceived as...
Show moreIn this study, 174 undergraduates from the University of Central Florida were asked to rate individual human and animal avatar features from the video game Spore on their level of femininity, masculinity, likability, and how well the feature represented them on a 7 point Likert scale of agreeability. Avatar features were presented on a neutral gray, quadruped body in two different views. It was expected that participants would show higher likability for avatar features that they perceived as corresponding to their Personal Attribute Questionnaire (PAQ) gender. Males liked feminine features approximately the same as females, however, in many categories females liked the most masculine features more than the most feminine features. Males liked the most masculine body detail feature more than females, and females liked the most masculine body detail more than males. It also was anticipated that avatar features rated as having both low femininity and low masculinity would be the features rated lowest in likability overall. These features did not have the lowest likability, but were somewhat close to neutral in likability. These results have implications for likable avatar creation for businesses, the military, and education.
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Date Issued
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2011
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Identifier
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CFH0003815, ucf:44714
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFH0003815
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Title
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VARIABLE RESOLUTION & DIMENSIONAL MAPPING FOR 3D MODEL OPTIMIZATION.
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Creator
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Venezia, Joseph, Kasparis, Takis, University of Central Florida
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Abstract / Description
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Three-dimensional computer models, especially geospatial architectural data sets, can be visualized in the same way humans experience the world, providing a realistic, interactive experience. Scene familiarization, architectural analysis, scientific visualization, and many other applications would benefit from finely detailed, high resolution, 3D models. Automated methods to construct these 3D models traditionally has produced data sets that are often low fidelity or inaccurate; otherwise,...
Show moreThree-dimensional computer models, especially geospatial architectural data sets, can be visualized in the same way humans experience the world, providing a realistic, interactive experience. Scene familiarization, architectural analysis, scientific visualization, and many other applications would benefit from finely detailed, high resolution, 3D models. Automated methods to construct these 3D models traditionally has produced data sets that are often low fidelity or inaccurate; otherwise, they are initially highly detailed, but are very labor and time intensive to construct. Such data sets are often not practical for common real-time usage and are not easily updated. This thesis proposes Variable Resolution & Dimensional Mapping (VRDM), a methodology that has been developed to address some of the limitations of existing approaches to model construction from images. Key components of VRDM are texture palettes, which enable variable and ultra-high resolution images to be easily composited; texture features, which allow image features to integrated as image or geometry, and have the ability to modify the geometric model structure to add detail. These components support a primary VRDM objective of facilitating model refinement with additional data. This can be done until the desired fidelity is achieved as practical limits of infinite detail are approached. Texture Levels, the third component, enable real-time interaction with a very detailed model, along with the flexibility of having alternate pixel data for a given area of the model and this is achieved through extra dimensions. Together these techniques have been used to construct models that can contain GBs of imagery data.
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Date Issued
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2009
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Identifier
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CFE0002837, ucf:48081
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002837
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Title
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Characterization, Classification, and Genesis of Seismocardiographic Signals.
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Creator
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Taebi, Amirtaha, Mansy, Hansen, Kassab, Alain, Huang, Helen, Vosoughi, Azadeh, University of Central Florida
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Abstract / Description
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Seismocardiographic (SCG) signals are the acoustic and vibration induced by cardiac activity measured non-invasively at the chest surface. These signals may offer a method for diagnosing and monitoring heart function. Successful classification of SCG signals in health and disease depends on accurate signal characterization and feature extraction.In this study, SCG signal features were extracted in the time, frequency, and time-frequency domains. Different methods for estimating time-frequency...
Show moreSeismocardiographic (SCG) signals are the acoustic and vibration induced by cardiac activity measured non-invasively at the chest surface. These signals may offer a method for diagnosing and monitoring heart function. Successful classification of SCG signals in health and disease depends on accurate signal characterization and feature extraction.In this study, SCG signal features were extracted in the time, frequency, and time-frequency domains. Different methods for estimating time-frequency features of SCG were investigated. Results suggested that the polynomial chirplet transform outperformed wavelet and short time Fourier transforms.Many factors may contribute to increasing intrasubject SCG variability including subject posture and respiratory phase. In this study, the effect of respiration on SCG signal variability was investigated. Results suggested that SCG waveforms can vary with lung volume, respiratory flow direction, or a combination of these criteria. SCG events were classified into groups belonging to these different respiration phases using classifiers, including artificial neural networks, support vector machines, and random forest. Categorizing SCG events into different groups containing similar events allows more accurate estimation of SCG features.SCG feature points were also identified from simultaneous measurements of SCG and other well-known physiologic signals including electrocardiography, phonocardiography, and echocardiography. Future work may use this information to get more insights into the genesis of SCG.
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Date Issued
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2018
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Identifier
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CFE0007106, ucf:51944
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007106
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Title
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Training Neural Networks Through the Integration of Evolution and Gradient Descent.
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Creator
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Morse, Gregory, Stanley, Kenneth, Wu, Annie, Shah, Mubarak, Wiegand, Rudolf, University of Central Florida
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Abstract / Description
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Neural networks have achieved widespread adoption due to both their applicability to a wide range of problems and their success relative to other machine learning algorithms. The training of neural networks is achieved through any of several paradigms, most prominently gradient-based approaches (including deep learning), but also through up-and-coming approaches like neuroevolution. However, while both of these neural network training paradigms have seen major improvements over the past...
Show moreNeural networks have achieved widespread adoption due to both their applicability to a wide range of problems and their success relative to other machine learning algorithms. The training of neural networks is achieved through any of several paradigms, most prominently gradient-based approaches (including deep learning), but also through up-and-coming approaches like neuroevolution. However, while both of these neural network training paradigms have seen major improvements over the past decade, little work has been invested in developing algorithms that incorporate the advances from both deep learning and neuroevolution. This dissertation introduces two new algorithms that are steps towards the integration of gradient descent and neuroevolution for training neural networks. The first is (1) the Limited Evaluation Evolutionary Algorithm (LEEA), which implements a novel form of evolution where individuals are partially evaluated, allowing rapid learning and enabling the evolutionary algorithm to behave more like gradient descent. This conception provides a critical stepping stone to future algorithms that more tightly couple evolutionary and gradient descent components. The second major algorithm (2) is Divergent Discriminative Feature Accumulation (DDFA), which combines a neuroevolution phase, where features are collected in an unsupervised manner, with a gradient descent phase for fine tuning of the neural network weights. The neuroevolution phase of DDFA utilizes an indirect encoding and novelty search, which are sophisticated neuroevolution components rarely incorporated into gradient descent-based systems. Further contributions of this work that build on DDFA include (3) an empirical analysis to identify an effective distance function for novelty search in high dimensions and (4) the extension of DDFA for the purpose of discovering convolutional features. The results of these DDFA experiments together show that DDFA discovers features that are effective as a starting point for gradient descent, with significant improvement over gradient descent alone. Additionally, the method of collecting features in an unsupervised manner allows DDFA to be applied to domains with abundant unlabeled data and relatively sparse labeled data. This ability is highlighted in the STL-10 domain, where DDFA is shown to make effective use of unlabeled data.
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Date Issued
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2019
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Identifier
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CFE0007840, ucf:52819
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007840
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Title
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The Happiest Place on Earth - The Microbudget Model as a Means to an American National Cinema.
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Creator
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Goshorn, John, Stoeckl, Ula, Gay, Andrew, Harris, Christopher, Sandler, Barry, University of Central Florida
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Abstract / Description
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The Happiest Place on Earth is a feature-length film written, directed, and produced by John Goshorn as part of the requirements for earning a Master of Fine Arts in Film (&) Digital Media from the University of Central Florida. The project aims to challenge existing conventions of the American fiction film on multiple levels (-) aesthetic, narrative, technical, and industrial (-)while dealing with a distinctly American subject and target audience. These challenges were both facilitated and...
Show moreThe Happiest Place on Earth is a feature-length film written, directed, and produced by John Goshorn as part of the requirements for earning a Master of Fine Arts in Film (&) Digital Media from the University of Central Florida. The project aims to challenge existing conventions of the American fiction film on multiple levels (-) aesthetic, narrative, technical, and industrial (-)while dealing with a distinctly American subject and target audience. These challenges were both facilitated and necessitated by the limited resources available to the production team and the academic context of the production. This thesis is a record of the film, from concept to completion and preparation for delivery to an audience.
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Date Issued
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2012
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Identifier
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CFE0004325, ucf:49451
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0004325
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Title
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DATA MINING METHODS FOR MALWARE DETECTION.
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Creator
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Siddiqui, Muazzam, Wang, Morgan, University of Central Florida
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Abstract / Description
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This research investigates the use of data mining methods for malware (malicious programs) detection and proposed a framework as an alternative to the traditional signature detection methods. The traditional approaches using signatures to detect malicious programs fails for the new and unknown malwares case, where signatures are not available. We present a data mining framework to detect malicious programs. We collected, analyzed and processed several thousand malicious and clean programs to...
Show moreThis research investigates the use of data mining methods for malware (malicious programs) detection and proposed a framework as an alternative to the traditional signature detection methods. The traditional approaches using signatures to detect malicious programs fails for the new and unknown malwares case, where signatures are not available. We present a data mining framework to detect malicious programs. We collected, analyzed and processed several thousand malicious and clean programs to find out the best features and build models that can classify a given program into a malware or a clean class. Our research is closely related to information retrieval and classification techniques and borrows a number of ideas from the field. We used a vector space model to represent the programs in our collection. Our data mining framework includes two separate and distinct classes of experiments. The first are the supervised learning experiments that used a dataset, consisting of several thousand malicious and clean program samples to train, validate and test, an array of classifiers. In the second class of experiments, we proposed using sequential association analysis for feature selection and automatic signature extraction. With our experiments, we were able to achieve as high as 98.4% detection rate and as low as 1.9% false positive rate on novel malwares.
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Date Issued
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2008
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Identifier
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CFE0002303, ucf:47870
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002303
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Title
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GAME ON: THE IMPACT OF GAME FEATURES IN COMPUTER-BASED TRAINING.
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Creator
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DeRouin-Jessen, Renee, Fritzsche, Barbara, University of Central Florida
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Abstract / Description
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The term "serious games" became popularized in 2002 as a result of an initiative to promote the use of games for education, training, and other purposes. Today, many companies are using games for training and development, often with hefty price tags. For example, the development budget for the U.S. Army recruiting game, "America's Army" was estimated at $7 million. Given their increasing use and high costs, it is important to understand whether game-based learning systems perform as...
Show moreThe term "serious games" became popularized in 2002 as a result of an initiative to promote the use of games for education, training, and other purposes. Today, many companies are using games for training and development, often with hefty price tags. For example, the development budget for the U.S. Army recruiting game, "America's Army" was estimated at $7 million. Given their increasing use and high costs, it is important to understand whether game-based learning systems perform as billed. Research suggests that games do not always increase learning outcomes over conventional instruction. However, certain game features (e.g., rules/goals, fantasy, challenge) might be more beneficial for increasing learner motivation and learning outcomes than other game features. This study manipulated two specific game features: multimedia-based fantasy (vs. text-based fantasy) and reward (vs. no reward) in a computer-based training program on employment law. Participants (N=169) were randomly assigned to one of the four experimental conditions or to a traditional computer-based training condition. Contrary to hypotheses, the traditional PowerPoint-like version was found to lead to better declarative knowledge outcomes on the learning test than the most game-like version, although no differences were found between conditions on any of the other dependent variables. Participants in all conditions were equally motivated to learn, were equally satisfied with the learning experience, completed an equal number of practice exercises, performed equally well on the declarative knowledge and skill-based practice, and performed equally well on the skill-based learning test. This suggests that adding the "bells and whistles" of game features to a training program won't necessarily improve learner motivation and training outcomes.
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Date Issued
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2008
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Identifier
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CFE0002439, ucf:47714
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002439
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Title
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IDENTIFICATION OF SYSTEM DESIGN FEATURES THAT AFFECT SICKNESS IN VIRTUAL ENVIRONMENTS.
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Creator
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Drexler, Julie, Malone, Linda, University of Central Florida
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Abstract / Description
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The terms "simulator" and "VR" are typically used to refer to specific types of virtual environments (VEs) which differ in the technology used to display the simulated environment. While simulators and VR devices may offer advantages such as low cost training, numerous studies on the effects to humans of exposure to different VEs indicate that motion sickness-like symptoms are often produced during or after exposure to the simulated environment. These deleterious side effects have the...
Show moreThe terms "simulator" and "VR" are typically used to refer to specific types of virtual environments (VEs) which differ in the technology used to display the simulated environment. While simulators and VR devices may offer advantages such as low cost training, numerous studies on the effects to humans of exposure to different VEs indicate that motion sickness-like symptoms are often produced during or after exposure to the simulated environment. These deleterious side effects have the potential to limit the utilization of VE systems if they jeopardize the health and/or safety of the user and create liability issues for the manufacturer. The most widely used method for assessing the adverse symptoms of VE exposure is the Simulator Sickness Questionnaire (SSQ). The method of scoring the symptoms reported by VE users permits the different sickness symptoms to be clustered into three general types of effects or subscales and the distribution or pattern of the three SSQ subscales provides a profile for a given VE device. In the current research, several different statistical analyses were conducted on the SSQ data obtained from 21 different simulator studies and 16 different VR studies in order to identify an underlying symptom structure (i.e., SSQ profile) or severity difference for various types of VE systems. The results of the research showed statistically significant differences in the SSQ profiles and the overall severity of sickness between simulator and VR systems, which provide evidence that simulator sickness and VR sickness represent distinct forms of motion sickness. Analyses on three types of simulators (i.e., Fixed- and Rotary-Wing flight simulators and Driving simulators) also found significant differences in the sickness profiles as well as the overall severity of sickness within different types of simulator systems. Analyses on three types of VR systems (i.e., HMD, BOOM, and CAVE) revealed that BOOM and CAVE systems have similar sickness profiles, which are different than the HMD system profile. Moreover, the results showed that the overall severity of sickness was greater in HMD systems than in BOOM and CAVE systems. Recommendations for future research included additional psychophysical studies to evaluate the relationship between various engineering characteristics of VE systems and the specific types of sickness symptoms that are produced from exposure to them.
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Date Issued
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2006
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Identifier
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CFE0000989, ucf:46700
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0000989
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Title
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The Effects of Presence and Cognitive Load on Episodic Memory in Virtual Environments.
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Creator
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Barclay, Paul, Sims, Valerie, Bowers, Clint, Jentsch, Florian, Fiore, Stephen, University of Central Florida
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Abstract / Description
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Episodic memory refers to an individual's memory for events that they have experienced in the past along with the associated contextual details. In order to more closely reflect the way that episodic memory functions in the real world, researchers and clinicians test episodic memory using virtual environments. However, these virtual environments introduce new interfaces and task demands that are not present in traditional methodologies. This dissertation investigates these environments...
Show moreEpisodic memory refers to an individual's memory for events that they have experienced in the past along with the associated contextual details. In order to more closely reflect the way that episodic memory functions in the real world, researchers and clinicians test episodic memory using virtual environments. However, these virtual environments introduce new interfaces and task demands that are not present in traditional methodologies. This dissertation investigates these environments through the lenses of Presence and Cognitive Load theories in order to unravel the ways that basic technological and task differences may affect memory performance. Participants completed a virtual task under High and Low Immersion conditions intended to manipulate Presence and Single-Task, Ecological Dual-Task and Non-Ecological Dual-Task conditions intended to manipulate cognitive load. Afterward they completed a battery of memory tasks assessing spatial, object, and feature binding aspects of episodic memory. Analysis through 2x3 ANOVA showed that performance for spatial memory is greatly improved by manipulation of Presence, where performance for object memory is improved by germane cognitive load. Exploratory analyses also revealed significant gender differences in spatial memory performance, indicating that improving Presence may offset the higher levels in male performance traditionally seen on spatial tasks. These results have practical implications for clinical memory assessment, as well as training paradigms and may serve to highlight the differences in the ways that memory is studied in the laboratory versus the way that it is employed in day-to-day life. Future studies based on this research should focus on linking these differences in memory performance to visuospatial and verbal strategies of memorization and determining whether the effects observed in this study replicate using other manipulations of presence and cognitive load.
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Date Issued
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2019
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Identifier
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CFE0007601, ucf:52521
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007601
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Title
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Interior: A Micro-Budget Horror Feature.
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Creator
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Beckler, Zachary, Harris, Christopher, Sandler, Barry, Gay, Andrew, University of Central Florida
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Abstract / Description
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INTERIOR is a feature-length film written, directed, and produced by Zachary Beckler as part of the requirements for earning a Master of Fine Arts in Entrepreneurial Digital Cinema from the University of Central Florida. The project aims to challenge existing conventions of the horror film on multiple levels (-) aesthetic, narrative, technical, and industrial (-) while also examining growing importance of workflow throughout all aspects of production. These challenges were both facilitated...
Show moreINTERIOR is a feature-length film written, directed, and produced by Zachary Beckler as part of the requirements for earning a Master of Fine Arts in Entrepreneurial Digital Cinema from the University of Central Florida. The project aims to challenge existing conventions of the horror film on multiple levels (-) aesthetic, narrative, technical, and industrial (-) while also examining growing importance of workflow throughout all aspects of production. These challenges were both facilitated and necessitated by the limited resources available to the production team and the academic context of the production. This thesis is a record of the film, from concept to completion and preparation for delivery to an audience.
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Date Issued
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2014
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Identifier
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CFE0005130, ucf:50677
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0005130
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Title
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The Tailor's Apprentice Cinematic Experience Through The Micro-Budget Paradigm.
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Creator
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Lehman, Jeffrey, Stoeckl, Ula, Sandler, Barry, Schlow, Stephen, University of Central Florida
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Abstract / Description
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The Tailor's Apprentice is a feature-length, micro-budget, narrative digital motion picture, written, produced and directed by Jeffrey Lehman in partial fulfillment of the requirements of earning a Master of Fine Arts in Film from the University of Central Florida. The film is a result of applying specific monetary, logistical and creative limitations to the production process in order to contribute in defining the micro-budget aesthetic, resulting in a final shared cinematic audience...
Show moreThe Tailor's Apprentice is a feature-length, micro-budget, narrative digital motion picture, written, produced and directed by Jeffrey Lehman in partial fulfillment of the requirements of earning a Master of Fine Arts in Film from the University of Central Florida. The film is a result of applying specific monetary, logistical and creative limitations to the production process in order to contribute in defining the micro-budget aesthetic, resulting in a final shared cinematic audience experience. This thesis is a record of all stages from conception to completion of the executed, feature length film with-in the micro-budget production paradigm.
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Date Issued
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2013
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Identifier
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CFE0004877, ucf:49660
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0004877
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Title
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EDUCATIONAL HANDHELD VIDEO: EXAMINING SHOT COMPOSITION, GRAPHIC DESIGN, AND THEIR IMPACT ON LEARNING.
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Creator
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Hutchens, Jason, Taylor, Rosemarye, University of Central Florida
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Abstract / Description
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Formal features of video such as shot composition and graphic design can weigh heavily on the success or failure of educational videos. Many studies have assessed the proper use of these techniques given the psychological expectations that viewers have for video programming (Hawkins et al., 2002; Kenny, 2002; Lang, Zhou, Schwardtz, Bolls, & Potter, 2000; McCain, Chilberg, & Wakshlag, 1977; McCain & Repensky, 1972; Miller, 2005; Morris, 1984; Roe, 1998; Schmitt, Anderson, & Collins, 1999;...
Show moreFormal features of video such as shot composition and graphic design can weigh heavily on the success or failure of educational videos. Many studies have assessed the proper use of these techniques given the psychological expectations that viewers have for video programming (Hawkins et al., 2002; Kenny, 2002; Lang, Zhou, Schwardtz, Bolls, & Potter, 2000; McCain, Chilberg, & Wakshlag, 1977; McCain & Repensky, 1972; Miller, 2005; Morris, 1984; Roe, 1998; Schmitt, Anderson, & Collins, 1999; Sherman & Etling, 1991; Tannenbaum & Fosdick, 1960; Wagner, 1953). This study examined formal features within the context of the newly emerging distribution method of viewing video productions on mobile handheld devices. Shot composition and graphic design were examined in the context of an educational video to measure whether or not they had any influence on user perceptions of learning and learning outcomes. The two formal features were modified for display on 24 inch screens and on 3.5 inch or smaller screens. Participants were shown one of the four modified treatments, then presented with a test to measure whether or not the modified formal features had any impact or influence on learning outcomes from a sample of 132 undergraduate college students. No significant differences were found to occur as a result of manipulation of formal features between the treatment groups.
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Date Issued
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2008
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Identifier
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CFE0002371, ucf:47797
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0002371
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Title
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Learning to Grasp Unknown Objects using Weighted Random Forest Algorithm from Selective Image and Point Cloud Feature.
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Creator
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Iqbal, Md Shahriar, Behal, Aman, Boloni, Ladislau, Haralambous, Michael, University of Central Florida
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Abstract / Description
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This method demonstrates an approach to determine the best grasping location on an unknown object using Weighted Random Forest Algorithm. It used RGB-D value of an object as input to find a suitable rectangular grasping region as the output. To accomplish this task, it uses a subspace of most important features from a very high dimensional extensive feature space that contains both image and point cloud features. Usage of most important features in the grasping algorithm has enabled the...
Show moreThis method demonstrates an approach to determine the best grasping location on an unknown object using Weighted Random Forest Algorithm. It used RGB-D value of an object as input to find a suitable rectangular grasping region as the output. To accomplish this task, it uses a subspace of most important features from a very high dimensional extensive feature space that contains both image and point cloud features. Usage of most important features in the grasping algorithm has enabled the system to be computationally very fast while preserving maximum information gain. In this approach, the Random Forest operates using optimum parameters e.g. Number of Trees, Number of Features at each node, Information Gain Criteria etc. ensures optimization in learning, with highest possible accuracy in minimum time in an advanced practical setting. The Weighted Random Forest chosen over Support Vector Machine (SVM), Decision Tree and Adaboost for implementation of the grasping system outperforms the stated machine learning algorithms both in training and testing accuracy and other performance estimates. The Grasping System utilizing learning from a score function detects the rectangular grasping region after selecting the top rectangle that has the largest score. The system is implemented and tested in a Baxter Research Robot with Parallel Plate Gripper in action.
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Date Issued
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2014
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Identifier
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CFE0005509, ucf:50358
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0005509
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Title
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A Psychophysical Approach to Standardizing Texture Compression for Virtual Environments.
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Creator
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Flynn, Jeremy, Szalma, James, Fidopiastis, Cali, Jentsch, Florian, Shah, Mubarak, University of Central Florida
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Abstract / Description
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Image compression is a technique to reduce overall data size, but its effects on human perception have not been clearly established. The purpose of this effort was to determine the most effective psychophysical method for subjective image quality assessment, and to apply those findings to an objective algorithm. This algorithm was used to identify the minimum level of texture compression noticeable to the human, in order to determine whether compression-induced texture distortion impacted...
Show moreImage compression is a technique to reduce overall data size, but its effects on human perception have not been clearly established. The purpose of this effort was to determine the most effective psychophysical method for subjective image quality assessment, and to apply those findings to an objective algorithm. This algorithm was used to identify the minimum level of texture compression noticeable to the human, in order to determine whether compression-induced texture distortion impacted game-play outcomes. Four experiments tested several hypotheses. The first hypothesis evaluated which of three magnitude estimation (ME) methods (absolute ME, absolute ME plus, or ME with a standard) for image quality assessment was the most reliable. The just noticeable difference (JND) point for textures compression against the Feature Similarity Index for color was determined The second hypothesis tested whether human participants perceived the same amount of distortion differently when textures were presented in three ways: when textures were displayed as flat images; when textures were wrapped around a model; and when textures were wrapped around models and in a virtual environment. The last set of hypotheses examined whether compression affected both subjective (immersion, technology acceptance, usability) and objective (performance) gameplay outcomes. The results were: the absolute magnitude estimation method was the most reliable; no difference was observed in the JND threshold between flat textures and textures placed on models, but textured embedded within the virtual environment were more noticeable than in the other two presentation formats. There were no differences in subjective gameplay outcomes when textures were compressed to below the JND thresholds; and those who played a game with uncompressed textures performed better on in-game tasks than those with the textures compressed, but only on the first in-game day. Practitioners and researchers can use these findings to guide their approaches to texture compression and experimental design.
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Date Issued
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2018
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Identifier
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CFE0007178, ucf:52250
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007178
Pages