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- Title
- Ralph Waldo Emerson and Jorge Luis Borges: Harbingers of Human Rights.
- Creator
- Gillespie Elizabeth Joy, Poulson, Nancy Kason, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Languages, Linguistics and Comparative Literature
- Abstract/Description
-
This dissertation comparatively analyzes the works of Ralph Waldo Emerson, a nineteenth century American, and Jorge Luis Borges, a twentieth-century Argentinian, within the context of human rights. Through their writings, both Emerson and Borges provided a voice to the voiceless by addressing the most egregious violations of human rights during their respective days: For Emerson, the most virulent social ill was slavery; for Borges, it was fascism. While Emerson and Borges differ in several...
Show moreThis dissertation comparatively analyzes the works of Ralph Waldo Emerson, a nineteenth century American, and Jorge Luis Borges, a twentieth-century Argentinian, within the context of human rights. Through their writings, both Emerson and Borges provided a voice to the voiceless by addressing the most egregious violations of human rights during their respective days: For Emerson, the most virulent social ill was slavery; for Borges, it was fascism. While Emerson and Borges differ in several ways, they are remarkably similar in their emphasis of natural laws and natural rights, notably egalitarianism and liberty, which underpin humanity and comprise an integral aspect of civilization. By counteracting the antithesis of civilization, barbarism, the works of Emerson and Borges ultimately embody the tenets that would ultimately constitute The Universal Declaration of Human Rights. Thus, Emerson and Borges are indelibly linked through serving as harbingers of human rights.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013207
- Subject Headings
- Emerson, Ralph Waldo, 1803-1882--Criticism and interpretation, Borges, Jorge Luis, 1899-1986--Criticism and interpretation, Human rights
- Format
- Document (PDF)
- Title
- Punctuated Identities In Contemporary Italian Cinema.
- Creator
- Iadevaia, Vincenza, Serra, Haria, Guneratne, Anthony, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Languages, Linguistic and Comparative Literature
- Abstract/Description
-
At a time of major political disruption in Italy, this dissertation aims to explore the landscape of contemporary Italian Cinema in connection with the nation’s new demographic trends and social configurations. Focusing on a selected, inherently representative group of filmmakers, the current study proposes a new form of film theory that sees the emergence and recognition of multi-ethnic filmmaking in a hitherto largely monocultural context as an indicator of a profound cultural...
Show moreAt a time of major political disruption in Italy, this dissertation aims to explore the landscape of contemporary Italian Cinema in connection with the nation’s new demographic trends and social configurations. Focusing on a selected, inherently representative group of filmmakers, the current study proposes a new form of film theory that sees the emergence and recognition of multi-ethnic filmmaking in a hitherto largely monocultural context as an indicator of a profound cultural transformation rather than a mere aesthetic tendency. The critical terminology I propose, “punctuated identitties,” document the characteristics of contemporary filmmakers, since they cannot be easily defined under the categories established by previous critical vocabularies. While these multi-ethnic filmmakers are part of a larger trend in European filmmaking as a whole, and hence constitute a case study of the evolution of a particular trend within individual national cinemas, my aim is to show how their punctuated identities complicate and color the Italian mediascape, and perhaps add a pluralistic dimension to the most recent chapter in the story of one of the most influential national cinemas. The filmmakers analyzed are selected according to specific elements and not on any categorization as first-and-second-generation immigrants. The present analysis includes two immigrants who have consciously chosen Italy as their homeland (Ferzan Özpetek and Jonas Carpignano), a migrant other who rejects nationality (Laura Halilovic), a political exile who relishes a certain sense of freedom in his Italian sojourn (Fariborz Kamkari), and a naturalized son of immigrants (Suranga Katugampala). All move in a fluid and conceptual space that creates a new path inside the traditional domain of national cinema, establishing the validity of others’s points of views and proving that coexistence can enrich even established and influential art forms.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013219
- Subject Headings
- Cinema, Motion pictures, Italian, Contemporary filmmakers, Motion picture producers and directors--Italy
- Format
- Document (PDF)
- Title
- Reimagining Climate Change: Visualizing the Future of Sustainability.
- Creator
- Dowis, Kaitlin, Afanador-Llach, Camila, Florida Atlantic University, Department of Visual Arts and Art History, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
-
The world’s path to climate change is inevitable. Activists and legislators, all around the world, are actively working to slow down this process or stop changes. Technology is moving toward a sustainable future of renewable energy and resources to lighten the impact that the human population has on the climate. Whether or not these efforts will slow down the changing climate is unknown, but the world’s scientists, engineers, and designers are preparing for any scenario that comes our way....
Show moreThe world’s path to climate change is inevitable. Activists and legislators, all around the world, are actively working to slow down this process or stop changes. Technology is moving toward a sustainable future of renewable energy and resources to lighten the impact that the human population has on the climate. Whether or not these efforts will slow down the changing climate is unknown, but the world’s scientists, engineers, and designers are preparing for any scenario that comes our way. This thesis uses graphic design to visualize the future of humanity adapting to climate change. Topics that are explored include controlled-environment agriculture, vertical farming, sustainable food production, advancements in the medical industry, advancements in transportation, and sustainable energy production. These elements will come together, in my projects, to visualize one possible future of living in Arizona, where living conditions have become inhospitable for life as we know today.
Show less - Date Issued
- 2020
- PURL
- http://purl.flvc.org/fau/fd/FA00013557
- Subject Headings
- Climate Change, Sustainability, Visualization
- Format
- Document (PDF)
- Title
- Reclaiming Wonder.
- Creator
- Barreneche, Ingrid M., Broderick, Amy S., Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Visual Arts and Art History
- Abstract/Description
-
I believe art can offer an antidote to our numbness and rekindle a sense of childlike wonder. Reclaiming Wonder is an installation in which I aim to explore the possibility of evoking the curiosity of childhood in the viewer’s mind and transporting him or her into a dreamlike atmosphere to wander about in wonder through the use of the senses of sight, touch, and hearing.
- Date Issued
- 2017
- PURL
- http://purl.flvc.org/fau/fd/FA00004863, http://purl.flvc.org/fau/fd/FA00004863
- Subject Headings
- Semiotics and literature., Wonder in children., Philosophy of nature., Nature study., Discourse analysis., Symbolism in literature., Spiritual life.
- Format
- Document (PDF)
- Title
- Real-time traffic incidents prediction in vehicular networks using big data analytics.
- Creator
- Al-Najada, Hamzah, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The United States has been going through a road accident crisis for many years. The National Safety Council estimates 40,000 people were killed and 4.57 million injured on U.S. roads in 2017. Direct and indirect loss from tra c congestion only is more than $140 billion every year. Vehicular Ad-hoc Networks (VANETs) are envisioned as the future of Intelligent Transportation Systems (ITSs). They have a great potential to enable all kinds of applications that will enhance road safety and...
Show moreThe United States has been going through a road accident crisis for many years. The National Safety Council estimates 40,000 people were killed and 4.57 million injured on U.S. roads in 2017. Direct and indirect loss from tra c congestion only is more than $140 billion every year. Vehicular Ad-hoc Networks (VANETs) are envisioned as the future of Intelligent Transportation Systems (ITSs). They have a great potential to enable all kinds of applications that will enhance road safety and transportation efficiency. In this dissertation, we have aggregated seven years of real-life tra c and incidents data, obtained from the Florida Department of Transportation District 4. We have studied and investigated the causes of road incidents by applying machine learning approaches to this aggregated big dataset. A scalable, reliable, and automatic system for predicting road incidents is an integral part of any e ective ITS. For this purpose, we propose a cloud-based system for VANET that aims at preventing or at least decreasing tra c congestions as well as crashes in real-time. We have created, tested, and validated a VANET traffic dataset by applying the connected vehicle behavioral changes to our aggregated dataset. To achieve the scalability, speed, and fault-tolerance in our developed system, we built our system in a lambda architecture fashion using Apache Spark and Spark Streaming with Kafka. We used our system in creating optimal and safe trajectories for autonomous vehicles based on the user preferences. We extended the use of our developed system in predicting the clearance time on the highway in real-time, as an important component of the traffic incident management system. We implemented the time series analysis and forecasting in our real-time system as a component for predicting traffic flow. Our system can be applied to use dedicated short communication (DSRC), cellular, or hybrid communication schema to receive streaming data and send back the safety messages. The performance of the proposed system has been extensively tested on the FAUs High Performance Computing Cluster (HPCC), as well as on a single node virtual machine. Results and findings confirm the applicability of the proposed system in predicting traffic incidents with low processing latency.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013114
- Subject Headings
- Vehicular ad hoc networks (Computer networks), Big data, Intelligent transportation systems, Prediction, traffic incidents
- Format
- Document (PDF)
- Title
- Reckoning.
- Creator
- LeVan, Jason, Ward, Julie Anne, Florida Atlantic University, Department of Visual Arts and Art History, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
-
Reckoning is a body of sculptural work that explores the emotional resonance contained within memory through a combination of personal ephemera and handcrafted objects. The physical presence of this work underscores the importance of its materiality, in both the handmade and collected objects, in emphasizing their ability to conjure a memory. Reckoning evokes the intangible emotions and overwhelming sensations that accompany the act of remembering, and an inability to forget.
- Date Issued
- 2020
- PURL
- http://purl.flvc.org/fau/fd/FA00013480
- Subject Headings
- Art, Sculpture, Ephemera, Handicraft
- Format
- Document (PDF)
- Title
- SPATIAL NETWORK BIG DATA APPROACHES TO EMERGENCY MANAGEMENT INFORMATION SYSTEMS.
- Creator
- Herschelman, Roxana M., Yang, KwangSoo, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
Emergency Management Information Systems (EMIS) are defined as a set of tools that aid decision-makers in risk assessment and response for significant multi-hazard threats and disasters. Over the past three decades, EMIS have grown in importance as a major component for understanding, managing, and governing transportation-related systems. To increase resilience against potential threats, the main goal of EMIS is to timely utilize spatial and network datasets about (1) locations of hazard...
Show moreEmergency Management Information Systems (EMIS) are defined as a set of tools that aid decision-makers in risk assessment and response for significant multi-hazard threats and disasters. Over the past three decades, EMIS have grown in importance as a major component for understanding, managing, and governing transportation-related systems. To increase resilience against potential threats, the main goal of EMIS is to timely utilize spatial and network datasets about (1) locations of hazard areas (2) shelters and resources, (3) and how to respond to emergencies. The main concern about these datasets has always been the very large size, variety, and update rate required to ensure the timely delivery of useful emergency information and response for disastrous events. Another key issue is that the information should be concise and easy to understand, but at the same time very descriptive and useful in the case of emergency or disaster. Advancement in EMIS is urgently needed to develop fundamental data processing components for advanced spatial network queries that clearly and succinctly deliver critical information in emergencies. To address these challenges, we investigate Spatial Network Database Systems and study three challenging Transportation Resilience problems: producing large scale evacuation plans, identifying major traffic patterns during emergency evacuations, and identifying the highest areas in need of resources.
Show less - Date Issued
- 2020
- PURL
- http://purl.flvc.org/fau/fd/FA00013576
- Subject Headings
- Emergency management, Big data, Emergency management--Information technology
- Format
- Document (PDF)
- Title
- Remote Labs: A Method to Implement a Portable Logic Design Laboratory Infrastructure and to Provide Access to Modern Test Equipment.
- Creator
- Weinthal, Charles Perry, Petrie, Maria Mercedes Larrondo, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This Thesis explores building low cost and reliable portable laboratory infrastructure platform for Logic Design, methods for allowing access to modern test equipment via the internet, and issues related to academic integrity. A comprehensive engineering education, per ABET, requires an equal emphasis on both lecture and laboratory components. The laboratory experience builds and establishes a foundation of skills and experiences that the student cannot obtain through any other means. The...
Show moreThis Thesis explores building low cost and reliable portable laboratory infrastructure platform for Logic Design, methods for allowing access to modern test equipment via the internet, and issues related to academic integrity. A comprehensive engineering education, per ABET, requires an equal emphasis on both lecture and laboratory components. The laboratory experience builds and establishes a foundation of skills and experiences that the student cannot obtain through any other means. The laboratory must use modern, pertinent methods and techniques including the use of appropriate tools. This is especially true when it comes to test equipment. Engineering students require and deserve training on and access to modern test equipment in order to obtain better career opportunities. However, providing access to modern and relevant labs requires a significant budget commitment. One way to extend current budgets is to adopt the growing concept of “remote labs.” This approach allows higher utilization of existing (and costly) equipment, it improves an institution’s Return on Investment (ROI), and also can be used to meet the needs of students’ complicated schedules, especially in the case of a “commuter campus,” where a majority of students live off campus. By developing remote labs, both the institution and the students benefit: Institutions increase equipment utilization, and utilize space, budgets and support personnel more efficiently. Students can access a lab whenever and wherever they have internet access. Finally, academic integrity must be protected to ensure the potential of remote laboratories in education. This Thesis presents a design and implementation plan for a low cost Logic Design laboratory infrastructure built and tested over 3 years by over 1,500 Logic Design students; a design and implementation of the infrastructure to include the ability to measure using remote test equipment; and the design of a case (3d printed or laser cut) to encapsulate a USB enabled micro-controller; and a scheme to ensure the academic integrity is maintained for in-person, hybrid and fully online classes.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013177
- Subject Headings
- Logic design, Engineering laboratories, Logic design--Computer-assisted instruction
- Format
- Document (PDF)
- Title
- PERFORMATIVE ACTIVISM AND POLITICS: A REPRESENTATIONAL ANALYSIS OF THE 2020 RESURGENCE OF THE BLACK LIVES MATTER MOVEMENT.
- Creator
- McCalla-Johnson, Alexa G., Robé, Christopher, Florida Atlantic University, School of Communication and Multimedia Studies, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
-
This study seeks to analyze the performative activism and political performance that took place during the Black Lives Matter protests between May and November of the year 2020. Various points of view perceive such acts as merely reductive or otherwise worthy of disdain, however, this study seeks to analyze these acts to identify different components within each performance. The primary focus is to further understand the advantages and disadvantages of performative activism and political...
Show moreThis study seeks to analyze the performative activism and political performance that took place during the Black Lives Matter protests between May and November of the year 2020. Various points of view perceive such acts as merely reductive or otherwise worthy of disdain, however, this study seeks to analyze these acts to identify different components within each performance. The primary focus is to further understand the advantages and disadvantages of performative activism and political performance. This research concentrates on examining the significant social and political impacts of these performances and their symbolic nature. This study also evaluates how discourse related to marginalized communities enters the public sphere and influences it. This study will include the analysis of performance via social media platforms, such as Instagram and Twitter during the 2020 resurgence of Black Lives Matter, including performances carried out by political leaders along the 2020 U.S. presidential campaign trail.
Show less - Date Issued
- 2021
- PURL
- http://purl.flvc.org/fau/fd/FA00013804
- Subject Headings
- Performative (Philosophy), Black lives matter movement--2020
- Format
- Document (PDF)
- Title
- PREDICTING MELANOMA RISK FROM ELECTRONIC HEALTH RECORDS WITH MACHINE LEARNING TECHNIQUES.
- Creator
- Richter, Aaron N., Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Melanoma is one of the fastest growing cancers in the world, and can affect patients earlier in life than most other cancers. Therefore, it is imperative to be able to identify patients at high risk for melanoma and enroll them in screening programs to detect the cancer early. Electronic health records collect an enormous amount of data about real-world patient encounters, treatments, and outcomes. This data can be mined to increase our understanding of melanoma as well as build personalized...
Show moreMelanoma is one of the fastest growing cancers in the world, and can affect patients earlier in life than most other cancers. Therefore, it is imperative to be able to identify patients at high risk for melanoma and enroll them in screening programs to detect the cancer early. Electronic health records collect an enormous amount of data about real-world patient encounters, treatments, and outcomes. This data can be mined to increase our understanding of melanoma as well as build personalized models to predict risk of developing the cancer. Cancer risk models built from structured clinical data are limited in current research, with most studies involving just a few variables from institutional databases or registries. This dissertation presents data processing and machine learning approaches to build melanoma risk models from a large database of de-identified electronic health records. The database contains consistently captured structured data, enabling the extraction of hundreds of thousands of data points each from millions of patient records. Several experiments are performed to build effective models, particularly to predict sentinel lymph node metastasis in known melanoma patients and to predict individual risk of developing melanoma. Data for these models suffer from high dimensionality and class imbalance. Thus, classifiers such as logistic regression, support vector machines, random forest, and XGBoost are combined with advanced modeling techniques such as feature selection and data sampling. Risk factors are evaluated using regression model weights and decision trees, while personalized predictions are provided through random forest decomposition and Shapley additive explanations. Random undersampling on the melanoma risk dataset shows that many majority samples can be removed without a decrease in model performance. To determine how much data is truly needed, we explore learning curve approximation methods on the melanoma data and three publicly-available large-scale biomedical datasets. We apply an inverse power law model as well as introduce a novel semi-supervised curve creation method that utilizes a small amount of labeled data.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013342
- Subject Headings
- Melanoma, Electronic Health Records, Machine learning--Technique, Big Data
- Format
- Document (PDF)
- Title
- Optimization of an Ocean Current Turbine Design and Prediction of Wake Propagation in an Array.
- Creator
- Kawssarani, Ali, VanZwieten, James H., Seiffert, Betsy, Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
- Abstract/Description
-
This research focused on maximizing the power generated by an array of ocean current turbines. To achieve this objective, the produced shaft power of an ocean current turbine (OCT) has been quantified using CFD without adding a duct, as well as over a range of duct geometries. For an upstream duct, having a diameter 1.6 times the rotor diameter, the power increased by 8.35% for a duct that extends 1 diameter upstream. This research also focused on turbine array optimization, providing a...
Show moreThis research focused on maximizing the power generated by an array of ocean current turbines. To achieve this objective, the produced shaft power of an ocean current turbine (OCT) has been quantified using CFD without adding a duct, as well as over a range of duct geometries. For an upstream duct, having a diameter 1.6 times the rotor diameter, the power increased by 8.35% for a duct that extends 1 diameter upstream. This research also focused on turbine array optimization, providing a mathematical basis for calculating the water velocity within an array of OCTs. After developing this wake model, it was validated using experimental data. As the downstream distance behind the turbine increases, the analytic results become closer to the experimental results, with a difference of 3% for TI = 3% and difference of 4% for TI = 15%, both at a downstream distance of 4 rotor diameters.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013077
- Subject Headings
- Turbines--Design and construction., Marine turbines., Ocean current energy, Ocean wave power
- Format
- Document (PDF)
- Title
- Oral History as a Means of Moral Repair: Jim Crow Racism and the Mexican Americans of San Antonio, Texas.
- Creator
- Dominguez-Karimi, Rebecca, Norman, Sandra, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Languages, Linguistics and Comparative Literature
- Abstract/Description
-
Oral history’s purposes have metamorphosed from a record of lifeways and stories of the elite to a means of healing for minority communities oppressed by trauma. This dissertation focuses on the power of oral history to catalyze the restorative justice process of moral repair for victims—in this case the Mexican Americans of Texas—who were traumatized by the Jim Crow laws and practices prior to 1965. I researched the racial, socio-cultural history of Texas from its colonial days up to the Jim...
Show moreOral history’s purposes have metamorphosed from a record of lifeways and stories of the elite to a means of healing for minority communities oppressed by trauma. This dissertation focuses on the power of oral history to catalyze the restorative justice process of moral repair for victims—in this case the Mexican Americans of Texas—who were traumatized by the Jim Crow laws and practices prior to 1965. I researched the racial, socio-cultural history of Texas from its colonial days up to the Jim Crow historical era of 1876-1965 and utilized archival, legal, and historical sources for my study. Additionally, I explore theories and frameworks of trauma, structural violence, and restorative justice, and analyze twenty-eight oral histories from the Voces Oral History Collection (University of Texas, Austin). Lastly, I apply oral history methodology to collect seventeen oral histories for my own project, Project Aztlan. My findings reveal a community suffering from structural violence—a theory that argues unjust laws harm individuals as much as physical violence. The oral histories unearth several issues: first, both groups of narrators were victims of structural violence as a result of traumatic racism. I anticipated finding traumatic racism, but not on such a broad scale. The results reveal it occurred in all four corners of Texas. Second, these Jim Crow laws and practices targeted members individually and collectively through racially restrictive housing covenants, segregation of schools/public facilities, job discrimination, and disfranchisement or poll taxes. Thirdly, the oral histories demonstrate and legitimize the fact that the Mexican American community deserves atonement, apology and reparation from historically guilty institutions. The State of Texas battered them with mass lynchings, disfranchisement, racially restrictive housing covenants, school segregation, and discrimination, oppressing them for over 100 years. My dissertation concludes that the oral history process helps victims attain moral repair because, similar to moral repair, it also allows them the space to voice their stories of injustice. In turn, the oral historian validates their claims and reconciliation occurs when narrators received vindication through this reparatory process. This acknowledgment fuses broken moral bonds by equalizing members of society.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00005963
- Subject Headings
- Mexican Americans--Texas--San Antonio, Oral histories, Jim Crowism, Racism
- Format
- Document (PDF)
- Title
- People counting and density estimation using public cameras.
- Creator
- Escudero Huedo, Antonio Eliseo, Kalva, Hari, Raviv, Daniel, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Many times we decide to go to a place depending on how crowded the place is. Our decisions are made based on different aspects that are only known in real time. A system that provides users or agencies information about the actual number of people in the scene over the time will allow them to make a decision or have information about a given location. This thesis presents a low complexity system for human counting and human detection using public cameras which usually do not have good quality...
Show moreMany times we decide to go to a place depending on how crowded the place is. Our decisions are made based on different aspects that are only known in real time. A system that provides users or agencies information about the actual number of people in the scene over the time will allow them to make a decision or have information about a given location. This thesis presents a low complexity system for human counting and human detection using public cameras which usually do not have good quality. The use of computer vision techniques makes it possible to have a system that allows the user to have an estimate number of people. Different videos were studied with different resolutions and camera positions. The best video result shows an error of 0.269%, while the worst one is 8.054 %. The results show that relatively inexpensive cameras streaming video at a low bitrate can be used to develop large scale people counting applications.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004104
- Format
- Document (PDF)
- Title
- Parallel Distributed Deep Learning on Cluster Computers.
- Creator
- Kennedy, Robert Kwan Lee, Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Deep Learning is an increasingly important subdomain of arti cial intelligence. Deep Learning architectures, arti cial neural networks characterized by having both a large breadth of neurons and a large depth of layers, bene ts from training on Big Data. The size and complexity of the model combined with the size of the training data makes the training procedure very computationally and temporally expensive. Accelerating the training procedure of Deep Learning using cluster computers faces...
Show moreDeep Learning is an increasingly important subdomain of arti cial intelligence. Deep Learning architectures, arti cial neural networks characterized by having both a large breadth of neurons and a large depth of layers, bene ts from training on Big Data. The size and complexity of the model combined with the size of the training data makes the training procedure very computationally and temporally expensive. Accelerating the training procedure of Deep Learning using cluster computers faces many challenges ranging from distributed optimizers to the large communication overhead speci c to a system with o the shelf networking components. In this thesis, we present a novel synchronous data parallel distributed Deep Learning implementation on HPCC Systems, a cluster computer system. We discuss research that has been conducted on the distribution and parallelization of Deep Learning, as well as the concerns relating to cluster environments. Additionally, we provide case studies that evaluate and validate our implementation.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013080
- Subject Headings
- Deep learning., Neural networks (Computer science)., Artificial intelligence., Machine learning.
- Format
- Document (PDF)
- Title
- Only sound remains.
- Creator
- Filsoofi, Raheleh T., McConnell, Brian E., Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Visual Arts and Art History
- Abstract/Description
-
We each experience the world through the prism of our upbringing, our traditions and the familiar sights and sounds embedded deep within our soul. Only Sound Remains is an installation in which I explore and share those experiences through objects, sounds and video. Ceramic vessels inspired by the traditions of my ancestors hide and shape sounds that narrate simple and complex experiences, which are the stories of my life. The sounds relate to the world that I came from and that still can be...
Show moreWe each experience the world through the prism of our upbringing, our traditions and the familiar sights and sounds embedded deep within our soul. Only Sound Remains is an installation in which I explore and share those experiences through objects, sounds and video. Ceramic vessels inspired by the traditions of my ancestors hide and shape sounds that narrate simple and complex experiences, which are the stories of my life. The sounds relate to the world that I came from and that still can be heard now. The sounds are not clear until one gets close to the vessels and lifts the lid-- a bazaar, praying, marching, an explosion, a woman telling a story, traditional Iranian music. The installation is a metaphor for the way in which we experience the world. The vessels represent a selection of personal and cultural experiences through sounds that may or may not be fully understood.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004108, http://purl.flvc.org/fau/fd/FA00004108
- Subject Headings
- Iran -- Social life and customs, Memory -- Social aspects, Music -- Philosophy and aesthetics, Symbolism in literature
- Format
- Document (PDF)
- Title
- Male Bonding: A Queer Analysis of the James Bond Canon.
- Creator
- Hester, Grant C., Caputi, Jane, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Center for Women, Gender, and Sexuality Studies, Communication, and Multimedia
- Abstract/Description
-
The character of James Bond which was first introduced in Ian Fleming’s first novel Casino Royale in 1953 and was then featured in 11 subsequent novels, 2 volumes of short stories, and 24 film adaptations has long been considered to be the ultimate man’s man. There is no feat he cannot conquer, villain he cannot best, or lady he cannot bed. However, in an examination of both the novels and the film, clues exist to Bond’s deeper psyche—most notably his repressed homosexuality. While much...
Show moreThe character of James Bond which was first introduced in Ian Fleming’s first novel Casino Royale in 1953 and was then featured in 11 subsequent novels, 2 volumes of short stories, and 24 film adaptations has long been considered to be the ultimate man’s man. There is no feat he cannot conquer, villain he cannot best, or lady he cannot bed. However, in an examination of both the novels and the film, clues exist to Bond’s deeper psyche—most notably his repressed homosexuality. While much discussion has been had of Bond’s misogyny, in many ways it masks his true identity possibly even from himself. Utilizing a framework of theoretical analysis drawing upon Sigmund Freud, Jack Hallberstam, Judith Butler, Susan Sontag, Laura Mulvey, and Charles Klosterman (among many others), this dissertation will fully explore the character Fleming created. Additionally, by examining how the male gaze and camp elements have been utilized by the filmmakers in the Bond films, analysis will be conducted how those elements contribute to a “queerness” of the character’s film incarnations.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013216
- Subject Headings
- James Bond 007, Fictitious characters, Homosexuality, Queer
- Format
- Document (PDF)
- Title
- MODELING AND SECURITY IN CLOUD AND RELATED ECOSYSTEMS.
- Creator
- Syed, Madiha Haider, Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Software systems increasingly interact with each other, forming ecosystems. Cloud is one such ecosystem that has evolved and enabled other technologies like IoT and containers. Such systems are very complex and heterogeneous because their components can have diverse origins, functions, security policies, and communication protocols, which makes it difficult to comprehend, utilize and consequently secure them. Abstract architectural models can be used to handle this complexity and...
Show moreSoftware systems increasingly interact with each other, forming ecosystems. Cloud is one such ecosystem that has evolved and enabled other technologies like IoT and containers. Such systems are very complex and heterogeneous because their components can have diverse origins, functions, security policies, and communication protocols, which makes it difficult to comprehend, utilize and consequently secure them. Abstract architectural models can be used to handle this complexity and heterogeneity but there is lack of work on precise, implementation/vendor neutral and holistic models which represent ecosystem components and their mutual interactions. We attempted to find similarities in systems and generalize to create abstract models for adding security. We represented the ecosystem as a Reference architecture (RA) and the ecosystem units as patterns. We started with a pattern diagram which showed all the components involved along with their mutual interactions and dependencies. We added components to the already existent Cloud security RA (SRA). Containers, being relatively new virtualization technology, did not have a precise and holistic reference architecture. We have built a partial RA for containers by identifying and modeling components of the ecosystem. Container security issues were identified from the literature as well as analysis of our patterns. We added corresponding security countermeasures to container RA as security patterns to build a container SRA. Finally, using container SRA as an example, we demonstrated an approach for RA validation. We have also built a composite pattern for fog computing that is an intermediate platform between Cloud and IoT devices. We represented an attack, Distributed Denial of Service (DDoS) using IoT devices, in the form of a misuse pattern which explains it from the attacker’s perspective. We found this modelbased approach useful to build RAs in a flexible and incremental way as components can be identified and added as the ecosystems expand. This provided us better insight to analyze security issues across boundaries of individual ecosystems. A unified, precise and holistic view of the system is not just useful for adding or evaluating security, this approach can also be used to ensure compliance, privacy, safety, reliability and/or governance for cloud and related ecosystems. This is the first work we know of where patterns and RAs are used to represent ecosystems and analyze their security.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013345
- Subject Headings
- Software ecosystems, Cloud computing--Security measures, Internet of things, Software architecture--Security measures, Computer modeling
- Format
- Document (PDF)
- Title
- Libertinage et feminisme dans les lettres du colonel talbert de francoise-albine puzin de la martiniere benoist.
- Creator
- Montonen, Jane M., Munson, Marcella L., Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Languages, Lingustics and Comparative Literature
- Abstract/Description
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In 1767, Mme Benoist published an epistolary libertine novel entitled Lettres du Colonel Talbert. Although she has received little critical attention to date, she was a prolific author who appeared with great regularity at minor literary salons. Her presence at these salons is well-established in personal memoirs and correspondences, and actively remarked upon by other authors—men and women—of the period, including Mme Roland and Choderlos de Laclos. Mme Benoist’s preferred genre was the...
Show moreIn 1767, Mme Benoist published an epistolary libertine novel entitled Lettres du Colonel Talbert. Although she has received little critical attention to date, she was a prolific author who appeared with great regularity at minor literary salons. Her presence at these salons is well-established in personal memoirs and correspondences, and actively remarked upon by other authors—men and women—of the period, including Mme Roland and Choderlos de Laclos. Mme Benoist’s preferred genre was the novel with its explicit blend of high and low literary cultures, its melding of the philosophical and the sentimental, its pursuit of formal innovation, and its deliberate marketing in multiple formats and for multiple audiences, including publication through the mainstream book market, and serial publication in revues and journals with a large female readership, such as the Journal des Dames. This study focuses on Lettres du Colonel Talbert (1767) as both a paradigmatic and privileged text inside Mme Benoist’s larger corpus, and one which explicitly engages many of the most pressing moral and philosophical debates of the period, including the legal status of women. To do so, Mme Benoist appropriates the libertine novel as specific novelistic subtype. In Les Lettres du Colonel Talbert, Mme Benoist parodies the libertine novel and in doing so, converts the libertine textual economy to one in which well-established narrative codes of femininity and masculinity are inverted. Although her depiction of the heroine, Hélène—an exceptional and courageous young woman who resists the predatory advances of a man through sheer strength of moral character—is not in itself unusual, Mme Benoist’s choice to frame her heroine’s moral struggle in a narrative epistolary exchange between two diametrically opposed male “types” in enlightenment thought—the libertine and the honnête homme— Mme Benoist effectively subverts masculine textual dynamics at the level of plot and character. More importantly, she also subverts the libertine novel’s traditional identification with masculine authorship.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004141, http://purl.flvc.org/fau/fd/FA00004141
- Subject Headings
- Benoist, Françoise Albine Puzin de La Martinière -- 1724-1809 -- Lettres du Colonel Talbert -- Criticism and interpretation, Feminism in literature, Libertinism in literature, Revolutionary literature, French -- 18th century -- Criticism and interpretation, Women and literature -- France -- 18th century
- Format
- Document (PDF)
- Title
- Machine Learning Algorithms with Big Medicare Fraud Data.
- Creator
- Bauder, Richard Andrew, Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Healthcare is an integral component in peoples lives, especially for the rising elderly population, and must be affordable. The United States Medicare program is vital in serving the needs of the elderly. The growing number of people enrolled in the Medicare program, along with the enormous volume of money involved, increases the appeal for, and risk of, fraudulent activities. For many real-world applications, including Medicare fraud, the interesting observations tend to be less frequent...
Show moreHealthcare is an integral component in peoples lives, especially for the rising elderly population, and must be affordable. The United States Medicare program is vital in serving the needs of the elderly. The growing number of people enrolled in the Medicare program, along with the enormous volume of money involved, increases the appeal for, and risk of, fraudulent activities. For many real-world applications, including Medicare fraud, the interesting observations tend to be less frequent than the normative observations. This difference between the normal observations and those observations of interest can create highly imbalanced datasets. The problem of class imbalance, to include the classification of rare cases indicating extreme class imbalance, is an important and well-studied area in machine learning. The effects of class imbalance with big data in the real-world Medicare fraud application domain, however, is limited. In particular, the impact of detecting fraud in Medicare claims is critical in lessening the financial and personal impacts of these transgressions. Fortunately, the healthcare domain is one such area where the successful detection of fraud can garner meaningful positive results. The application of machine learning techniques, plus methods to mitigate the adverse effects of class imbalance and rarity, can be used to detect fraud and lessen the impacts for all Medicare beneficiaries. This dissertation presents the application of machine learning approaches to detect Medicare provider claims fraud in the United States. We discuss novel techniques to process three big Medicare datasets and create a new, combined dataset, which includes mapping fraud labels associated with known excluded providers. We investigate the ability of machine learning techniques, unsupervised and supervised, to detect Medicare claims fraud and leverage data sampling methods to lessen the impact of class imbalance and increase fraud detection performance. Additionally, we extend the study of class imbalance to assess the impacts of rare cases in big data for Medicare fraud detection.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013108
- Subject Headings
- Medicare fraud, Big data, Machine learning, Algorithms
- Format
- Document (PDF)
- Title
- Machine learning algorithms for the analysis and detection of network attacks.
- Creator
- Najafabadi, Maryam Mousaarab, Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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The Internet and computer networks have become an important part of our organizations and everyday life. With the increase in our dependence on computers and communication networks, malicious activities have become increasingly prevalent. Network attacks are an important problem in today’s communication environments. The network traffic must be monitored and analyzed to detect malicious activities and attacks to ensure reliable functionality of the networks and security of users’ information....
Show moreThe Internet and computer networks have become an important part of our organizations and everyday life. With the increase in our dependence on computers and communication networks, malicious activities have become increasingly prevalent. Network attacks are an important problem in today’s communication environments. The network traffic must be monitored and analyzed to detect malicious activities and attacks to ensure reliable functionality of the networks and security of users’ information. Recently, machine learning techniques have been applied toward the detection of network attacks. Machine learning models are able to extract similarities and patterns in the network traffic. Unlike signature based methods, there is no need for manual analyses to extract attack patterns. Applying machine learning algorithms can automatically build predictive models for the detection of network attacks. This dissertation reports an empirical analysis of the usage of machine learning methods for the detection of network attacks. For this purpose, we study the detection of three common attacks in computer networks: SSH brute force, Man In The Middle (MITM) and application layer Distributed Denial of Service (DDoS) attacks. Using outdated and non-representative benchmark data, such as the DARPA dataset, in the intrusion detection domain, has caused a practical gap between building detection models and their actual deployment in a real computer network. To alleviate this limitation, we collect representative network data from a real production network for each attack type. Our analysis of each attack includes a detailed study of the usage of machine learning methods for its detection. This includes the motivation behind the proposed machine learning based detection approach, the data collection process, feature engineering, building predictive models and evaluating their performance. We also investigate the application of feature selection in building detection models for network attacks. Overall, this dissertation presents a thorough analysis on how machine learning techniques can be used to detect network attacks. We not only study a broad range of network attacks, but also study the application of different machine learning methods including classification, anomaly detection and feature selection for their detection at the host level and the network level.
Show less - Date Issued
- 2017
- PURL
- http://purl.flvc.org/fau/fd/FA00004882, http://purl.flvc.org/fau/fd/FA00004882
- Subject Headings
- Machine learning., Computer security., Data protection., Computer networks--Security measures.
- Format
- Document (PDF)