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Articles 24031 - 24060 of 63515

Full-Text Articles in Computer Sciences

Using Cuda To Enhance Data Processing Of Variant Call Format Files For Statistical Genetic Analysis, Heather Mckinnon Jan 2020

Using Cuda To Enhance Data Processing Of Variant Call Format Files For Statistical Genetic Analysis, Heather Mckinnon

All Graduate Projects

Utilizing the power of GPU parallel processing with CUDA can speed up the processing of Variant Call Format (VCF) files and statistical analysis of genomic data. A software package designed toward this purpose would be beneficial to genetic researchers by saving them time which they could spend on other aspects of their research. A data set containing genetics from a study of trichome production in Mimulus guttatus, or yellow monkey flower, was used to develop a package to test the effectiveness of GPU parallel processing versus serial executions. After a serial version of the code was generated and benchmarked, OpenACC …

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Multi-Class Twitter Data Categorization And Geocoding With A Novel Computing Framework, Sakib Mahmud Khan, Mashrur Chowdhury, Linh B. Ngo, Amy Apon Jan 2020

Multi-Class Twitter Data Categorization And Geocoding With A Novel Computing Framework, Sakib Mahmud Khan, Mashrur Chowdhury, Linh B. Ngo, Amy Apon

Computer Science Faculty Publications

This study details the progress in transportation data analysis with a novel computing framework in keeping with the continuous evolution of the computing technology. The computing framework combines the Labeled Latent Dirichlet Allocation (L-LDA)-incorporated Support Vector Machine (SVM) classifier with the supporting computing strategy on publicly available Twitter data in determining transportation-related events to provide reliable information to travelers. The analytical approach includes analyzing tweets using text classification and geocoding locations based on string similarity. A case study conducted for the New York City and its surrounding areas demonstrates the feasibility of the analytical approach. Approximately 700,010 tweets are analyzed …

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Machine Learning Methods For The Analysis Of Metagenomes, Vito Adrian Cantu Alessio Robles Jan 2020

Machine Learning Methods For The Analysis Of Metagenomes, Vito Adrian Cantu Alessio Robles

CGU Theses & Dissertations

As of October 2020, there are 18.6 × 1015 DNA base pairs publicly available in the Sequence Read Archive and this number is growing at an exponential rate. As DNA sequencing prices continue to drop, many research groups around the world have incorporated high throughput sequencing in their research, giving us access to sequences from many distinct ecosystems. This has revolutionized the field of metagenomics, which aims to fully characterize all organisms and their interactions in a particular system. Nevertheless, the plethora of available data has made its analysis difficult as traditional techniques such as genome assembly or sequence alignment …

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Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh Jan 2020

Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi Khatchadourian, Yiming Tang, Mehdi Bagherzadeh

Publications and Research

Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages and platforms. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite, e.g., collections, and infinite data structures. However, using this API efficiently involves subtle considerations such as determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. ics-preserving fashion. The approach, based on a novel data ordering and typestate analysis, consists of preconditions and …

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Automatically Categorizing Software Technologies, Mathieu Nassif, Christoph Treude, Martin P. Robillard Jan 2020

Automatically Categorizing Software Technologies, Mathieu Nassif, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Informal language and the absence of a standard taxonomy for software technologies make it difficult to reliably analyze technology trends on discussion forums and other on-line venues. We propose an automated approach called Witt for the categorization of software technologies (an expanded version of the hypernym discovery problem). Witt takes as input a phrase describing a software technology or concept and returns a general category that describes it (e.g., integrated development environment), along with attributes that further qualify it (commercial, php, etc.). By extension, the approach enables the dynamic creation of lists of all technologies of a given type (e.g., …

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Deepdrawing: A Deep Learning Approach To Graph Drawing, Yong Wang, Zhihua Jin, Qianwen Wang, Weiwei Cui, Tengfei Ma, Huamin Qu Jan 2020

Deepdrawing: A Deep Learning Approach To Graph Drawing, Yong Wang, Zhihua Jin, Qianwen Wang, Weiwei Cui, Tengfei Ma, Huamin Qu

Research Collection School Of Computing and Information Systems

Node-link diagrams are widely used to facilitate network explorations. However, when using a graph drawing technique to visualize networks, users often need to tune different algorithm-specific parameters iteratively by comparing the corresponding drawing results in order to achieve a desired visual effect. This trial and error process is often tedious and time-consuming, especially for non-expert users. Inspired by the powerful data modelling and prediction capabilities of deep learning techniques, we explore the possibility of applying deep learning techniques to graph drawing. Specifically, we propose using a graph-LSTM-based approach to directly map network structures to graph drawings. Given a set of …

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Towards Automated Infographic Design: Deep Learning-Based Auto-Extraction Of Extensible Timeline, Zhutian Chen, Yun Wang, Qianwen Wang, Yong Wang, Huamin Qu Jan 2020

Towards Automated Infographic Design: Deep Learning-Based Auto-Extraction Of Extensible Timeline, Zhutian Chen, Yun Wang, Qianwen Wang, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Designers need to consider not only perceptual effectiveness but also visual styles when creating an infographic. This process can be difficult and time consuming for professional designers, not to mention non-expert users, leading to the demand for automated infographics design. As a first step, we focus on timeline infographics, which have been widely used for centuries. We contribute an end-to-end approach that automatically extracts an extensible timeline template from a bitmap image. Our approach adopts a deconstruction and reconstruction paradigm. At the deconstruction stage, we propose a multi-task deep neural network that simultaneously parses two kinds of information from a …

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A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria Jan 2020

A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Sentiment analysis consists in the identification of the sentiment polarity associated with a target object, such as a book, a movie or a phone. Sentiments reflect feelings and attitudes, while emotions provide a finer characterization of the sentiments involved. With the huge number of comments generated daily on the Internet, besides sentiment analysis, emotion identification has drawn keen interest from different researchers, businessmen and politicians for polling public opinions and attitudes. This paper reviews and discusses existing emotion categorization models for emotion analysis and proposes methods that enhance existing emotion research. We carried out emotion analysis by inviting experts from …

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Values Of Artificial Intelligence In Marketing, Yingrui Xi Jan 2020

Values Of Artificial Intelligence In Marketing, Yingrui Xi

Masters Theses

“Artificial Intelligence (AI) is causing radical changes in marketing and emerging as a competent assistant supporting all areas of the marketing field. The influences and impacts AI has created in various marketing segments have aroused much interest among marketing professionals and academic scholars. Comprehensive and systematic studies on the values of AI in marketing, however, are still lacking and the existing literature fragmented. This research provides a comprehensive review of the existing literature in the relevant fields as well as a series of systematic interviews using the Value-Focused Thinking approach to understand the values of AI in marketing. This research …

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Data And Artificial Intelligence: Mismatch Between Expectations And Uses, Diana Garcia Jan 2020

Data And Artificial Intelligence: Mismatch Between Expectations And Uses, Diana Garcia

Cybersecurity Undergraduate Research Showcase

People like to hide behind their phones when it comes to social media. Not every user has their real name or their own photo on display in their social media account. To obfuscate their identities, some users use unusual usernames and profile photos that are divorced from their true identity.

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Infrastructure For Performance Monitoring And Analysis Of Systems And Applications, Ramin Izadpanah Jan 2020

Infrastructure For Performance Monitoring And Analysis Of Systems And Applications, Ramin Izadpanah

Electronic Theses and Dissertations, 2020-2023

The growth of High Performance Computer (HPC) systems increases the complexity with respect to understanding resource utilization, system management, and performance issues. HPC performance monitoring tools need to collect information at both the application and system levels to yield a complete performance picture. Existing approaches limit the abilities of the users to do meaningful analysis on actionable timescale. Efficient infrastructures are required to support largescale systems performance data analysis for both run-time troubleshooting and post-run processing modes. In this dissertation, we present methods to fill these gaps in the infrastructure for HPC performance monitoring and analysis. First, we enhance the …

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Algorithms And Applications Of Novel Capsule Networks, Rodney Lalonde Jan 2020

Algorithms And Applications Of Novel Capsule Networks, Rodney Lalonde

Electronic Theses and Dissertations, 2020-2023

Convolutional neural networks, despite their profound impact in countless domains, suffer from significant shortcomings. Linearly-combined scalar feature representations and max pooling operations lead to spatial ambiguities and a lack of robustness to pose variations. Capsule networks can potentially alleviate these issues by storing and routing the pose information of extracted features through their architectures, seeking agreement between the lower-level predictions of higher-level poses at each layer. In this dissertation, we make several key contributions to advance the algorithms of capsule networks in segmentation and classification applications. We create the first ever capsule-based segmentation network in the literature, SegCaps, by introducing …

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Organization Global Software Development Challenges Of Software Product Quality, Patrick Enabudoso Jan 2020

Organization Global Software Development Challenges Of Software Product Quality, Patrick Enabudoso

Walden Dissertations and Doctoral Studies

Leaders of global software development (GSD) processes in organizations have been confronting low software product quality. Managers of these processes have faced challenges that have been affecting customer satisfaction and that have resulted in negative social impacts on public safety, business financial performance, and global economic stability. The purpose of this qualitative exploratory multiple case study was to discover a common understanding shared by managers in Canadian GSD organizations of how to meet software product quality goals and enhance customer satisfaction. The conceptual framework for the study was based on Deming's 14 principles of quality management. The purposeful sample included …

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Uncertainty-Aware Brain Lesion Visualization, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Karl T. Hoffman, Hans Hagen, Ross Maciejewski, Gerik Scheuermann Jan 2020

Uncertainty-Aware Brain Lesion Visualization, Christina Gillmann, Dorothee Saur, Thomas Wischgoll, Karl T. Hoffman, Hans Hagen, Ross Maciejewski, Gerik Scheuermann

Computer Science and Engineering Faculty Publications

A brain lesion is an area of tissue that has been damaged through injury or disease. Its analysis is an essential task for medical researchers to understand diseases and find proper treatments. In this context, visualization approaches became an important tool to locate, quantify, and analyze brain lesions. Unfortunately, image uncertainty highly effects the accuracy of the visualization output. These effects are not covered well in existing approaches, leading to miss-interpretation or a lack of trust in the analysis result. In this work, we present an uncertainty-aware visualization pipeline especially designed forbrain lesions. Our method is based on an uncertainty …

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The Cyberworld And Human Trafficking: A Double-Edged Sword, Bridget Dukes Jan 2020

The Cyberworld And Human Trafficking: A Double-Edged Sword, Bridget Dukes

Cybersecurity Undergraduate Research Showcase

This report examines the advantages and disadvantages associated with the growth of technology within the United States, specifically how technology, digital literacy, and cybersecurity can be used to both facilitate and combat sex trafficking and sexual exploitation on the Internet. The first part of the report addresses trafficking statistics in the United States, as well as legal intervention the country has taken against this epidemic, including an explanation of the Trafficking Victims Prevention Act and the FOSTA-SESTA bill. The second part of the report addresses the online recruitment of buyers and sellers, as well as how the use of open-source …

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Understanding The Use Of Malware And Encryption, Eva M. Castillo Jan 2020

Understanding The Use Of Malware And Encryption, Eva M. Castillo

OUR Journal: ODU Undergraduate Research Journal

The main objective of this research project is understanding malware and encryption.

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Topical Review Of Vulnerability Management For Local Hampton Roads Industry, Gregory W. Hubbard Jr., Matthew Eunice Jan 2020

Topical Review Of Vulnerability Management For Local Hampton Roads Industry, Gregory W. Hubbard Jr., Matthew Eunice

OUR Journal: ODU Undergraduate Research Journal

The progress towards an interconnected digital world offers an exciting level of advancement for humanity. Unfortunately, this “online” connection is not safe from the threats and dangers typically associated with physical operations. With the foundation of Cyber Command of DoD cyberspace, the United States Government is taking a prominent stance in cyberspace operations. Like the federal government, both industries and individuals are not immune and are oftentimes unknowingly at risk to cyberattack. This report hopes to bring awareness to common vulnerabilities in multi-user networks by describing a historical background on cyber security as well as outlining current methods of vulnerability …

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Automatic Distinction Between Twitter Bots And Humans, Jeremiah Stubbs Jan 2020

Automatic Distinction Between Twitter Bots And Humans, Jeremiah Stubbs

All Undergraduate Theses and Capstone Projects

Weak artificial intelligence uses encoded functions of rules to process information. This kind of intelligence is competent, but lacks consciousness, and therefore cannot comprehend what it is doing. In another view, strong artificial intelligence has a mind of its own that resembles a human mind. Many of the bots on Twitter are only following a set of encoded rules. Previous studies have created machine learning algorithms to determine whether a Twitter account was being run by a human or a bot. Twitter bots are improving and some are even fooling humans. Creating a machine learning algorithm that differentiates a bot …

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Gröbner Bases And Systems Of Polynomial Equations, Rachel Holmes Jan 2020

Gröbner Bases And Systems Of Polynomial Equations, Rachel Holmes

All Graduate Theses, Dissertations, and Other Capstone Projects

This paper will explore the use and construction of Gröbner bases through Buchberger's algorithm. Specifically, applications of such bases for solving systems of polynomial equations will be discussed. Furthermore, we relate many concepts in commutative algebra to ideas in computational algebraic geometry.

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Innovation And Market Leadership In A Technology Industry, Wilson Zehr Jan 2020

Innovation And Market Leadership In A Technology Industry, Wilson Zehr

Walden Dissertations and Doctoral Studies

According to the Abernathy-Utterback (A-U) model, firms focus on technological product innovation early in the product lifecycle and then shift to process innovation as markets mature. However, there is no consensus on the forms that non-technological innovation can take. In addition, the A-U model, which guides innovators, does not include forms of non-technological innovation that are generally accepted by experts. In this study, a hybrid e-Delphi technique with an AHP decision model was used to evaluate the forms of innovation used to establish market leadership over the historical lifecycle of the personal computer industry in the United States. In Phase …

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Factors Influencing Cloud Computing Adoption By Small Firms In The Payment Card Industry, Marie Njanje Tambe Jan 2020

Factors Influencing Cloud Computing Adoption By Small Firms In The Payment Card Industry, Marie Njanje Tambe

Walden Dissertations and Doctoral Studies

Technology acceptance is increasingly gaining attention in research considering the continuous exploits of innovation and various derived advantages. Cloud computing (CC) has shown to be the ideal solution for aligning information technology with business strategies. However, small to medium-sized enterprises (SMEs) in the payment card industry are reluctantly adopting this technology despite the benefits. This correlational study aims at investigating whether security, cost effectiveness, or regulatory compliance influence CC adoption by U.S. SMEs in the payment card sector. The study builds on the technology-organization-environment (TOE) framework and uses a previously validated instrument to assess CC adoption by decision-makers in U.S. …

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Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant Jan 2020

Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant

Walden Dissertations and Doctoral Studies

Spine and related disorders represent one of the most common causes of pain and disability in the United States. Imaging represents an important diagnostic procedure in spine care. Imaging studies contain actionable data and insights undetectable through routine visual analysis. Convergent advances in imaging, artificial intelligence (AI), and radiomic methods has revealed the potential of multiscale in vivo interrogation to improve the assessment and monitoring of pathology. AI offers various types of decision support through the analysis of structured and unstructured data. The primary purpose of this qualitative exploratory case study was to identify the potential impacts of AI solutions …

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Strategies Universities’ And Colleges’ It Leaders Use To Prevent Malware Attacks, Felix Agyei Jan 2020

Strategies Universities’ And Colleges’ It Leaders Use To Prevent Malware Attacks, Felix Agyei

Walden Dissertations and Doctoral Studies

Information systems at universities and colleges are not exempt from the threat of malware. Preventing and mitigating malware attacks is important to universities’ and colleges’ IT leaders to protect sensitive data confidentiality. Grounded in general system theory, the purpose of this exploratory multiple case study was to explore strategies universities’ and colleges’ information technology (IT) leaders use to prevent and mitigate malware attacks. Participants consisted of 6 IT leaders from 3 universities and colleges in Southern California responsible for preventing and mitigating malware attacks. Data were collected through semistructured video teleconferences and 7 organizational documents. Three significant themes emerged through …

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The Impact Of Technological Advances On Older Workers, Toni Mcintosh Jan 2020

The Impact Of Technological Advances On Older Workers, Toni Mcintosh

Walden Dissertations and Doctoral Studies

The general problem addressed in this study was the treatment of older workers in the information technology industry that contributes to age discrimination in the workplace. Age discrimination is against the law irrespective of whether it is aimed at older workers in the workforce or becoming job candidates at an advanced age. Although previous research has shown that age discrimination is prevalent in work environments, little has been suggested to eradicate the issue in the workplace. The purpose of this qualitative case study was to investigate the issue of age discrimination as it relates to workers over the age of …

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The Effects Of Gesture Presentation In Video Games, Jack Oakley Jan 2020

The Effects Of Gesture Presentation In Video Games, Jack Oakley

Electronic Theses and Dissertations, 2020-2023

As everyday and commonplace technology continues to move toward touch devices and virtual reality devices, more and more video games are using gestures as forms of gameplay. While there is much research focused on gestures as user interface navigation methods, we wanted to look into how gestures affect gameplay when used as a gameplay mechanic. In particular, we set out to determine how different ways of presenting gestures might affect the game's difficulty and flow. We designed two versions of a zombie game where the zombies are killed by drawing gestures. The first version of the game is a touchscreen-based …

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Action Recognition In Still Images: Confluence Of Multilinear Methods And Deep Learning, Marjaneh Safaei Jan 2020

Action Recognition In Still Images: Confluence Of Multilinear Methods And Deep Learning, Marjaneh Safaei

Electronic Theses and Dissertations, 2020-2023

Motion is a missing information in an image, however, it is a valuable cue for action recognition. Thus, lack of motion information in a single image makes action recognition for still images inherently a very challenging problem in computer vision. In this dissertation, we show that both spatial and temporal patterns provide crucial information for recognizing human actions. Therefore, action recognition depends not only on the spatially-salient pixels, but also on the temporal patterns of those pixels. To address the challenge caused by the absence of temporal information in a single image, we introduce five effective action classification methodologies along …

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An Ordinance-Tweet Mining App To Disseminate Urban Policy Knowledge For Smart Governance, Christina Varghese, Aparna S. Varde, Xu Du Jan 2020

An Ordinance-Tweet Mining App To Disseminate Urban Policy Knowledge For Smart Governance, Christina Varghese, Aparna S. Varde, Xu Du

Department of Computer Science Faculty Scholarship and Creative Works

This paper focuses on how populations by the use of technology, more specifically an app, can comprehend the enactment of ordinances (local laws) in an urban area along with their public reactions expressed as tweets. Furthermore, they can understand how well the area is developing and enhancing as a Smart City. The main goal of this research is to develop an Ordinance-Tweet Mining App that disseminates the results of analyzing ordinances and tweets about them, especially related to Smart City Characteristics such as Smart Environment, Smart Mobility etc. This app would be beneficial to various users such as environmental scientists, …

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I Am Guessing You Can't Recognize This: Generating Adversarial Images For Object Detection Using Spatial Commonsense, Anurag Garg, Niket Tandon, Aparna S. Varde Jan 2020

I Am Guessing You Can't Recognize This: Generating Adversarial Images For Object Detection Using Spatial Commonsense, Anurag Garg, Niket Tandon, Aparna S. Varde

Department of Computer Science Faculty Scholarship and Creative Works

Can we automatically predict failures of an object detection model on images from a target domain? We characterize errors of a state-of-the-art object detection model on the currently popular smart mobility domain, and find that a large number of errors can be identified using spatial commonsense. We propose CSK-SNIFFER, a system that automatically identifies a large number of such errors based on commonsense knowledge. Our system does not require any new annotations and can still find object detection errors with high accuracy (more than 80% when measured by humans). This work lays the foundation to answer exciting research questions on …

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Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery Jan 2020

Fault Identification On Electrical Transmission Lines Using Artificial Neural Networks, Christopher W. Asbery

Theses and Dissertations--Electrical and Computer Engineering

Transmission lines are designed to transport large amounts of electrical power from the point of generation to the point of consumption. Since transmission lines are built to span over long distances, they are frequently exposed to many different situations that can cause abnormal conditions known as electrical faults. Electrical faults, when isolated, can cripple the transmission system as power flows are directed around these faults therefore leading to other numerous potential issues such as thermal and voltage violations, customer interruptions, or cascading events. When faults occur, protection systems installed near the faulted transmission lines will isolate these faults from the …

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Machine Learning Based Rf Transmitter Characterization In The Presence Of Adversaries, Debashri Roy Jan 2020

Machine Learning Based Rf Transmitter Characterization In The Presence Of Adversaries, Debashri Roy

Electronic Theses and Dissertations, 2020-2023

The advances in wireless technologies have led to autonomous deployments of various wireless networks. As these networks must co-exist, it is important that all transmitters and receivers are aware of their radio frequency (RF) surroundings so that they can learn and adapt their transmission and reception parameters to best suit their needs. To this end, machine learning techniques have become popular as they can learn, analyze and even predict the RF signals and associated parameters that characterize the RF environment. In this dissertation, we address some of the fundamental challenges on how to effectively apply different learning techniques in the …

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