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(1 - 7 of 7)
- Title
- DECREASING ALCOHOL USE AMONG HIGH SCHOOL STUDENTS BY CHALLENGING ALCOHOL EXPECTANCIES.
- Creator
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Cruz, Iris, Dunn, Michael, University of Central Florida
- Abstract / Description
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Altering alcohol expectancies has reduced alcohol use among college students and may lead to successful prevention of alcohol use among high school students. We randomly assigned 379 12th-grade students to an expectancy challenge, traditional alcohol information, or control condition, and used Individual Differences Scaling to map expectancies into memory network format with Preference Mapping to model likely paths of association. After expectancy and traditional alcohol interventions, higher...
Show moreAltering alcohol expectancies has reduced alcohol use among college students and may lead to successful prevention of alcohol use among high school students. We randomly assigned 379 12th-grade students to an expectancy challenge, traditional alcohol information, or control condition, and used Individual Differences Scaling to map expectancies into memory network format with Preference Mapping to model likely paths of association. After expectancy and traditional alcohol interventions, higher drinking male participants exhibited a greater likelihood to associate alcohol use with negative and sedating consequences and a decreased likelihood to associate alcohol with positive and arousing consequences. Drinking decreases paralleled the magnitude of changes in their likely path of expectancy activation. Children and adults who emphasize negative and sedating effects have been found to be less likely to use alcohol. Therefore, expectancy challenge interventions that have been successful at modifying expectancies and subsequently decreasing alcohol consumption among heavy drinking college students may be useful in the development of prevention curricula for high school students.
Show less - Date Issued
- 2006
- Identifier
- CFE0001232, ucf:46887
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001232
- Title
- THE MEMORY OF FORGOTTEN THINGS.
- Creator
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Metz, Brittany, Poindexter, Carla, University of Central Florida
- Abstract / Description
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This thesis investigates my lack of childhood memories and documents how my artwork stands in as a substitute for that lost memory. The first part of the thesis analyzes my early life and influences; the second part analyzes my art making and process. The narrative style of writing is intentionally autobiographical to mimic the narrative style and structure of the thesis installation. My upbringing, interests, creative process, access to materials, and inspiration are fully explored. The...
Show moreThis thesis investigates my lack of childhood memories and documents how my artwork stands in as a substitute for that lost memory. The first part of the thesis analyzes my early life and influences; the second part analyzes my art making and process. The narrative style of writing is intentionally autobiographical to mimic the narrative style and structure of the thesis installation. My upbringing, interests, creative process, access to materials, and inspiration are fully explored. The impact my early life has on my current work is evident. Real memory is combined with created memory in the thesis multi-media installation. I wish to transport the viewer into the dreamlike space I have constructed with found objects and multi-media materials by offering an immersive experience into my world.
Show less - Date Issued
- 2011
- Identifier
- CFE0003649, ucf:48814
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003649
- Title
- Phonological Working Memory Deficits in ADHD Revisited: The Role of Lower-Level Information Processing Deficits in Impaired Working Memory Performance.
- Creator
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Raiker, Joseph, Rapport, Mark, Beidel, Deborah, Mouloua, Mustapha, Vasquez, Eleazar, University of Central Florida
- Abstract / Description
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Working memory deficits in children with ADHD are well established; however, insufficient evidence exists concerning the degree to which lower-level cognitive processes contribute to these deficits. The current study dissociates lower level information processing abilities (i.e., visual registration, orthographic conversion, and response output) in children with ADHD and typically developing children and examines the unique contribution of these processes to their phonological working memory...
Show moreWorking memory deficits in children with ADHD are well established; however, insufficient evidence exists concerning the degree to which lower-level cognitive processes contribute to these deficits. The current study dissociates lower level information processing abilities (i.e., visual registration, orthographic conversion, and response output) in children with ADHD and typically developing children and examines the unique contribution of these processes to their phonological working memory performance. Thirty-four boys between 8 and 12 years of age (20 ADHD, 14 typically developing) were administered novel information processing and phonological working memory tasks. Between-group differences were examined and bootstrap mediation analysis was used to evaluate the mediating effect of information processing deficits on phonological working memory performance. Results revealed moderate to large magnitude deficits in visual registration and encoding, orthographic to phonological conversion, and phonological working memory in children with ADHD. Subsequent mediation analyses, however, revealed that visual registration/encoding alone mediated the diagnostic group status/phonological working memory relationship and accounted for approximately 32% of the variance in children's phonological working memory performance. Diagnostic and treatment implications for understanding the complex interplay among multiple cognitive deficits in children with ADHD are discussed.
Show less - Date Issued
- 2014
- Identifier
- CFE0005694, ucf:50141
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005694
- Title
- Automated Synthesis of Unconventional Computing Systems.
- Creator
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Hassen, Amad Ul, Jha, Sumit Kumar, Sundaram, Kalpathy, Fan, Deliang, Ewetz, Rickard, Rahman, Talat, University of Central Florida
- Abstract / Description
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Despite decades of advancements, modern computing systems which are based on the von Neumann architecture still carry its shortcomings. Moore's law, which had substantially masked the effects of the inherent memory-processor bottleneck of the von Neumann architecture, has slowed down due to transistor dimensions nearing atomic sizes. On the other hand, modern computational requirements, driven by machine learning, pattern recognition, artificial intelligence, data mining, and IoT, are growing...
Show moreDespite decades of advancements, modern computing systems which are based on the von Neumann architecture still carry its shortcomings. Moore's law, which had substantially masked the effects of the inherent memory-processor bottleneck of the von Neumann architecture, has slowed down due to transistor dimensions nearing atomic sizes. On the other hand, modern computational requirements, driven by machine learning, pattern recognition, artificial intelligence, data mining, and IoT, are growing at the fastest pace ever. By their inherent nature, these applications are particularly affected by communication-bottlenecks, because processing them requires a large number of simple operations involving data retrieval and storage. The need to address the problems associated with conventional computing systems at the fundamental level has given rise to several unconventional computing paradigms. In this dissertation, we have made advancements for automated syntheses of two types of unconventional computing paradigms: in-memory computing and stochastic computing. In-memory computing circumvents the problem of limited communication bandwidth by unifying processing and storage at the same physical locations. The advent of nanoelectronic devices in the last decade has made in-memory computing an energy-, area-, and cost-effective alternative to conventional computing. We have used Binary Decision Diagrams (BDDs) for in-memory computing on memristor crossbars. Specifically, we have used Free-BDDs, a special class of binary decision diagrams, for synthesizing crossbars for flow-based in-memory computing. Stochastic computing is a re-emerging discipline with several times smaller area/power requirements as compared to conventional computing systems. It is especially suited for fault-tolerant applications like image processing, artificial intelligence, pattern recognition, etc. We have proposed a decision procedures-based iterative algorithm to synthesize Linear Finite State Machines (LFSM) for stochastically computing non-linear functions such as polynomials, exponentials, and hyperbolic functions.
Show less - Date Issued
- 2019
- Identifier
- CFE0007648, ucf:52462
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007648
- Title
- COMMISSIONING OF AN ARC-MELTING / VACUUM QUENCH FURNACE FACILITY FOR FABRICATION OF NI-TI-FE SHAPE MEMORY ALLOYS, AND THEIR CHARACTERIZATION.
- Creator
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Singh, Jagat, Vaidyanathan, Raj, University of Central Florida
- Abstract / Description
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Shape memory alloys when deformed can produce strains as high as 8%. Heating results in a phase transformation and associated recovery of all the accumulated strain, a phenomenon known as shape memory. This strain recovery can occur against large forces, resulting in their use as actuators. The goal of this project is to lower the operating temperature range of shape memory alloys in order for them to be used in cryogenic switches, seals, valves, fluid-line repair and self-healing gaskets for...
Show moreShape memory alloys when deformed can produce strains as high as 8%. Heating results in a phase transformation and associated recovery of all the accumulated strain, a phenomenon known as shape memory. This strain recovery can occur against large forces, resulting in their use as actuators. The goal of this project is to lower the operating temperature range of shape memory alloys in order for them to be used in cryogenic switches, seals, valves, fluid-line repair and self-healing gaskets for space related technologies. The Ni-Ti-Fe alloy system, previously used in Grumman F-14 aircrafts and activated at 120 K, is further developed through arc-melting a range of compositions and subsequent thermo-mechanical processing. A controlled atmosphere arc-melting facility and vertical vacuum quench furnace facility was commissioned to fabricate these alloys. The facility can create a vacuum of 10-7 Torr and heat treat samples up to 977 °C. High purity powders of Ni, Ti and Fe in varying ratios were mixed and arc-melted into small buttons weighing 0.010 kg to 0.025 kg. The alloys were subjected to solutionizing and aging treatments. A combination of rolling, electro-discharge machining and low-speed cutting techniques were used to produce strips. Successful rolling experiments highlighted the workability of these alloys. The shape memory effect was successfully demonstrated at liquid nitrogen temperatures through a constrained recovery experiment that generated stresses of over 40 MPa. Differential scanning calorimetry (DSC) and a dilatometry setup was used to characterize the fabricated materials and determine relationships between composition, thermo-mechanical processing parameters and transformation temperatures.
Show less - Date Issued
- 2004
- Identifier
- CFE0000308, ucf:46320
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000308
- Title
- Automatically Acquiring a Semantic Network of Related Concepts.
- Creator
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Szumlanski, Sean, Gomez, Fernando, Wu, Annie, Hughes, Charles, Sims, Valerie, University of Central Florida
- Abstract / Description
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We describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to...
Show moreWe describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to automatically disambiguate them to their corresponding WordNet noun senses (i.e., concepts). The resultant concept-to-concept associations, stemming from 7,593 target nouns, with 17,104 distinct senses among them, constitute a large-scale semantic network with 208,832 undirected edges between related concepts. Our work can thus be conceived of as augmenting the WordNet noun ontology with RelatedTo links.The network, which we refer to as the Szumlanski-Gomez Network (SGN), has been subjected to a variety of evaluative measures, including manual inspection by human judges and quantitative comparison to gold standard data for semantic relatedness measurements. We have also evaluated the network's performance in an applied setting on a word sense disambiguation (WSD) task in which the network served as a knowledge source for established graph-based spreading activation algorithms, and have shown: a) the network is competitive with WordNet when used as a stand-alone knowledge source for WSD, b) combining our network with WordNet achieves disambiguation results that exceed the performance of either resource individually, and c) our network outperforms a similar resource, WordNet++ (Ponzetto (&) Navigli, 2010), that has been automatically derived from annotations in the Wikipedia corpus.Finally, we present a study on human perceptions of relatedness. In our study, we elicited quantitative evaluations of semantic relatedness from human subjects using a variation of the classical methodology that Rubenstein and Goodenough (1965) employed to investigate human perceptions of semantic similarity. Judgments from individual subjects in our study exhibit high average correlation to the elicited relatedness means using leave-one-out sampling (r = 0.77, ? = 0.09, N = 73), although not as high as average human correlation in previous studies of similarity judgments, for which Resnik (1995) established an upper bound of r = 0.90 (? = 0.07, N = 10). These results suggest that human perceptions of relatedness are less strictly constrained than evaluations of similarity, and establish a clearer expectation for what constitutes human-like performance by a computational measure of semantic relatedness. We also contrast the performance of a variety of similarity and relatedness measures on our dataset to their performance on similarity norms and introduce our own dataset as a supplementary evaluative standard for relatedness measures.
Show less - Date Issued
- 2013
- Identifier
- CFE0004759, ucf:49767
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004759
- Title
- Facilitating Information Retrieval in Social Media User Interfaces.
- Creator
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Costello, Anthony, Tang, Yubo, Fiore, Stephen, Goldiez, Brian, University of Central Florida
- Abstract / Description
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As the amount of computer mediated information (e.g., emails, documents, multi-media) we need to process grows, our need to rapidly sort, organize and store electronic information likewise increases. In order to store information effectively, we must find ways to sort through it and organize it in a manner that facilitates efficient retrieval. The instantaneous and emergent nature of communications across networks like Twitter makes them suitable for discussing events (e.g., natural disasters...
Show moreAs the amount of computer mediated information (e.g., emails, documents, multi-media) we need to process grows, our need to rapidly sort, organize and store electronic information likewise increases. In order to store information effectively, we must find ways to sort through it and organize it in a manner that facilitates efficient retrieval. The instantaneous and emergent nature of communications across networks like Twitter makes them suitable for discussing events (e.g., natural disasters) that are amorphous and prone to rapid changes. It can be difficult for an individual human to filter through and organize the large amounts of information that can pass through these types of social networks when events are unfolding rapidly. A common feature of social networks is the images (e.g., human faces, inanimate objects) that are often used by those who send messages across these networks. Humans have a particularly strong ability to recognize and differentiate between human Faces. This effect may also extend to recalling information associated with each human Face. This study investigated the difference between human Face images, non-human Face images and alphanumeric labels as retrieval cues under different levels of Task Load. Participants were required to recall key pieces of event information as they emerged from a Twitter-style message feed during a simulated natural disaster. A counter-balanced within-subjects design was used for this experiment. Participants were exposed to low, medium and high Task Load while responding to five different types of recall cues: (1) Nickname, (2) Non-Face, (3) Non-Face (&) Nickname, (4) Face and (5) Face (&) Nickname. The task required participants to organize information regarding emergencies (e.g., car accidents) from a Twitter-style message feed. The messages reported various events such as fires occurring around a fictional city. Each message was associated with a different recall cue type, depending on the experimental condition. Following the task, participants were asked to recall the information associated with one of the cues they worked with during the task. Results indicate that under medium and high Task Load, both Non-Face and Face retrieval cues increased recall performance over Nickname alone with Non-Faces resulting in the highest mean recall scores. When comparing medium to high Task Load: Face (&) Nickname and Non-Face significantly outperformed the Face condition. The performance in Non-Face (&) Nickname was significantly better than Face (&) Nickname. No significant difference was found between Non-Faces and Non-Faces (&) Nickname. Subjective Task Load scores indicate that participants experienced lower mental workload when using Non-Face cues than using Nickname or Face cues. Generally, these results indicate that under medium and high Task Load levels, images outperformed alphanumeric nicknames, Non-Face images outperformed Face images, and combining alphanumeric nicknames with images may have offered a significant performance advantage only when the image is that of a Face. Both theoretical and practical design implications are provided from these findings.
Show less - Date Issued
- 2014
- Identifier
- CFE0005318, ucf:50524
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005318
