Physical Sciences and Mathematics Commons^™

Rhetsec_ | Rhetorical Security, Jennifer Mead

Culminating Projects in English

Rhetsec_ examines the rhetorical situation, the rhetorical appeals, and how phishing emails simulate "real" emails in five categories of phishing emails. While the first focus of cybersecurity is security, you must also understand the language of computers to know how to secure them. Phishing is one way to compromise security using computers, and so the computer becomes a tool for malicious language (phishing emails and malware) to be transmitted. Therefore to be concerned with securing computers, then you must also be concerned with language. Language is rhetoric's domain, and the various rhetorical elements which create an identity of the phisher …

Towards Location Free Movement Recognition With Channel State Information, Chunhai Feng

Computer Science and Engineering Dissertations

Channel state information based movement recognition has gathered immense attention over recent years. Different from traditional systems which usually require wearable sensors or surveillance cameras, many existing works achieved desirable performance with only wireless signals in various applications, including healthcare, security and Internet of Things, with different machine learning algorithms. However, it still remains many challenges to be solved. Particularly, the location dependent nature of channel state information is one of the most significant challenges remaining. Firstly, many previous researchers deploy and evaluate their systems with employing machine learning or deep neural networks. Because of the aforementioned challenge, the models …

Deduplication-Aware Page Cache In Linux Kernel For Improved Read Performance, Venkata Satya Ravi Kiran Boggavarapu

Computer Science and Engineering Theses

The amount of data being produced and consumed is increasing every day. As a result, there can be a large amount of redundant data in the storage system. Storing and accessing these duplicate data unnecessarily consumes disk space and I/O bandwidth. Deduplication techniques are widely deployed to remove the redundancy. In particular, the deduplication solutions that work at the block level are proven to be effective. These solutions aim to effectively use disk space and write bandwidth by avoiding duplicate data writes to the storage. However, such a design might not help in improving the read performance, which is critical …

Detect Traffic Signs From Large Street View Images With Deep Learning, Zhifei Deng

Computer Science and Engineering Theses

Autonomous driving is about to shaping the future of our life. Self-driving vehicles produced by Waymo or many other companies have demonstrated excellent driving capabilities on the road. However, accidents still happen. Correctly recognising the traffic signs, such as stop signs, is critical for a self-driving vehicle. Failing to recognise the traffic signs could lead to fatal accidents. Meanwhile, computer vision technology has made huge progress since the advent of deep learning, for example, image classification, object detection, and instance segmentation. Efforts have been made in developing faster and more accurate object detection methods. Faster R-CNN stands out as one …

Deep Representation Learning For Clustering And Domain Adaptation, Mohsen Kheirandishfard

Computer Science and Engineering Dissertations

Representation learning is a fundamental task in the area of machine learning which can significantly influence the performance of the algorithms used in various applications. The main goal of this task is to capture the relationships between the input data and learn feature representations that contain the most useful information of the original data. Such representations can be further leveraged in many machine learning applications such as clustering, natural language analysis, recommender systems, etc. In this dissertation, we first present a theoretical framework for solving a broad class of non-convex optimization problems. The proposed method is applicable to various tasks …

Using Property-Based Testing, Weighted Grammar-Based Generators, And A Consensus Oracle To Test Browser Rendering Engines And To Reproduce Minimized Versions Of Existing Test Cases, Joel David Martin

Computer Science and Engineering Theses

Verifying that a web browser rendering engine correctly renders all valid web pages is challenging due to the size of the input space (valid web pages), the difficulty of determining correct rendering for any given web page (the test oracle problem), and the degree to which normal variation in browser rendering behavior can obscure other differences (fonts, bor- ders, input controls, etc). These challenges lead to manual human involvement during the testing process. We propose a new Property-Based Testing (PBT) approach that addresses these challenges in order to enable automated web browser render testing. Our approach is composed of the …

Use Of Word Embedding To Generate Similar Words And Misspellings For Training Purpose In Chatbot Development, Sanjay Thapa

Computer Science and Engineering Theses

The advancement in the field of Natural Language Processing and Machine Learning has played a significant role in the huge improvement of conversational Artificial Intelligence (AI). The use of text-based conversation AI such as chatbots have increased significantly for the everyday purpose to communicate with real people for a variety of tasks. Chatbots are deployed in almost all popular messaging platforms and channels. The rise of chatbot development frameworks based on machine learning is helping to deploy chatbot easily and promptly. These chatbot development frameworks use machine learning and natural language understanding (NLU) to understand users' messages and intents and …

Spatial Similarity Measures With Applications To Map Integration And Improving Accuracy Of Map Data Sets, Mousa Alhajlah Almotairi

Computer Science and Engineering Dissertations

These days we live in a digital era where most societies rely on applications that depend on digital data. One popular type of digital data that is the basis many of applications is spatial data. Road network maps are one of the spatial data sets that are available for many important applications. However, acquisition of Road Network maps is an expensive task in terms of cost and time, not to mention the maintenance and the updating costs on these spatial data sets. In addition, each Road network map is captured for specific applications such as: road navigation, topographic cartography for …

Feature Extraction In Noise-Diverse Environments For Human Activities Recognition Using Wi-Fi, Sheheryar Arshad

Computer Science and Engineering Dissertations

With the rapid development of 802.11 standard and Internet of Things (IoT) applications, Wi-Fi (IEEE 802.11) has emerged as the most widely used wireless communication technology. Wi-Fi based sensing has found widespread use cases involving activity recognition, indoor localization, design of smart spaces and in healthcare applications. This dissertation presents the study of human activities’ sensing and recognition using channel state information (CSI) of Wi-Fi. We highlight the limitations of existing methods and consequently design the frameworks for collecting stable CSI and monitoring different indoor and outdoor environments for human activities. Specifically, this dissertation provide means to define and extract …

Hiding In Plain Sight? The Impact Of Face Recognition Services On Privacy, James Richard Ortega

Computer Science and Engineering Theses

The public at large is increasingly concerned with privacy online. While the focus is on the data privately collected by platforms, there are also privacy concerns in the realm of public data. Seemingly innocuous information shared in public, on online platforms, can be pieced together to detrimentally affect one's privacy in unexpected ways. On YouTube there exists a rich public dataset for adversaries to analyze for the purposes of breaching privacy; particularly due to the intersection of location and facial data. The goal of this work is to characterize the privacy risks that exists on YouTube, and explore the viability …

The Impact Of Toxic Replies On Twitter Conversations, Nazanin Salehabadi

Computer Science and Engineering Theses

Social media has become an empowering agent for individual voices and freedom of expression. Yet, it can also serve as a breeding ground for hate speech. According to a Pew Research Center study, 41% of Americans have been personally subjected to harassing behavior online, 66% have witnessed these behaviors directed at others, and 18% have been subjected to particularly severe forms of harassment online, such as physical threats, harassment over a sustained period, sexual harassment, or stalking. Recently, many research studies have tried to understand online hate speech and its implications, focusing on detecting and characterizing hate speech. One limitation …

Using Property-Based Testing, Weighted Grammar-Based Generators, And A Consensus Oracle To Test Browser Rendering Engines And To Reproduce Minimized Versions Of Existing Test Cases, Joel David Martin

Computer Science and Engineering Dissertations

Verifying that a web browser rendering engine correctly renders all valid web pages is challenging due to the size of the input space (valid web pages), the difficulty of determining correct rendering for any given web page (the test oracle problem), and the degree to which normal variation in browser rendering behavior can obscure other differences (fonts, bor- ders, input controls, etc). These challenges lead to manual human involvement during the testing process. We propose a new Property-Based Testing (PBT) approach that addresses these challenges in order to enable automated web browser render testing. Our approach is composed of the …

Performance Modeling And Resource Provisioning For Data-Intensive Applications, Zhongwei Li

Computer Science and Engineering Theses

Performance evaluation and resource provisioning are two most critical factors to be considered for designers of distributed systems at modern warehouse data centers. The ever-increasing volumes of data in recent years have pushed many businesses to move their computing tasks to the Cloud, which offers many benefits including the low system management and maintenance costs and better scalability. As a result, most recent prominently emerging workloads are data-intensive, calling for scaling out the workload to a large number of servers for parallel processing. Questions can be asked as what factors impact the system scaling performance, and how to efficiently schedule …

Distributed Deep Neural Networks Training For Brain Imaging Applications, Sudheer Raja

Computer Science and Engineering Theses

Over the recent years, Deep Neural Networks (DNNs) have surpassed human-level intelligence in recognizing and interpreting complex patterns in data. Ever since the ImageNet competition in 2012, Deep Learning (DL) has become a promising approach for solving numerous problems in the field of Computer Science. However, the neuroscience community is not able to utilize the DL algorithms effectively because the brain imaging datasets are huge in terms of size, and the current sequential training techniques do not scale up well for such big datasets. Without the proper amount of training data, training DNN models to competitive accuracies is quite challenging. …

Comprehensive Study Of Generative Methods On Drug Discovery, Siyu Xiu

Computer Science and Engineering Theses

Observing the recent success of the deep learning (DL) technology in multiple life-changing application areas, e.g., autonomous driving, image/video search and discovery, natural language processing, etc., many new opportunities have presented themselves. One of the biggest ones lies in applying DL in accelerating the drug discovery, where millions of human lives could potentially be saved. However, applying DL into the drug discovery task turns out to be non-trivial. The most successful DL methods take fix-sized tensors/matrices, e.g., images, or sequences of tokens, e.g., sentences with variant numbers of words, as their inputs. However, none of these registers with the inputs …

Performance Modeling And Resource Provisioning For Data-Intensive Applications, Zhongwei Li

Computer Science and Engineering Dissertations

Performance evaluation and resource provisioning are two most critical factors to be considered for designers of distributed systems at modern warehouse data centers. The ever-increasing volumes of data in recent years have pushed many businesses to move their computing tasks to the Cloud, which offers many benefits including the low system management and maintenance costs and better scalability. As a result, most recent prominently emerging workloads are data-intensive, calling for scaling out the workload to a large number of servers for parallel processing. Questions can be asked as what factors impact the system scaling performance, and how to efficiently schedule …

Parsing Code-Switched Taglish Language By Creating Constituents, Fadiah Qudah

Computer Science and Engineering Theses

When extracting meaning from language, a common first step is to break down language into constituents, or words that work together as a unit. This task, known as parsing, typically follows a specific grammar in order decompose the language into its underlying structure composed of constituents. Difficulties with this grammar-based parsing occur, however, with real-world natural language due to its unstructured nature. Code-switching, the phenomenon of alternating between languages while communicating, further complicates this task by requiring us to parse based on two (or more) languages instead of one. In this thesis, a data-driven method to parse code-switched language into …

Social Media Text Analysis Using Multi-Kernel Convolutional Neural Network, Anna Philips

Computer Science and Engineering Theses

Transportation planners and ride hailing platforms such as Uber and Lyft use their riders feedback to assess their services and monitor customer satisfaction. Social media websites such as Facebook, Instagram, LinkedIn and in particular Twitter provides a large dataset of micro-texts by users who regularly post to their social media accounts about their grievances with their ride experience. This data is often unorganized and intractable to process because of it’s extremely large size which is continuously increasing daily. In this project, we collected ride hailing service relevant text data from Twitter around New York and developed a novel Convolutional Neural …

Think2act: Using Multimodal Data To Assess Human Cognitive And Physical Performance, Maher Abujelala

Computer Science and Engineering Dissertations

As computers become more advanced, affordable, and smaller in size, we start to use them in almost every aspect of our daily life. Nowadays, the use of computers is not just limited to accomplish work-related tasks. Instead, we use computers for education, entertainment, healthcare, and in many other areas to facilitate our daily life activities. From here, the Human-Computer Interaction (HCI) field emerged. HCI is a multidisciplinary field of study that focuses on utilizing computers and technology to interact with humans, improve their quality of life, and enhance their performance. The rapid advancements in other related research fields, such as …

Approxml: Efficient Approximate Ad-Hoc Ml Models Through Materialization And Reuse, Faezeh Ghaderi

Computer Science and Engineering Theses

Machine Learning (ML) has become an essential tool in answering complex predictive analytic queries. Model building for large scale datasets is one of the most time-consuming parts of the data science pipeline. Often data scientists are willing to sacrifice some accuracy in order to speed up this process during the exploratory phase. In this report, we aim to demonstrate ApproxML, a system that efficiently constructs approximate ML models for new queries from previously constructed ML models using the concepts of model materialization and reuse. ApproxML supports a wide variety of ML models such as generalized linear models for supervised learning …

Automated Testing Of A Commercial Cyber-Physical System Development Tool Chain, Shafiul Azam Chowdhury

Computer Science and Engineering Dissertations

Rigorous validation of commercial cyber-physical system (CPS) tool chains (e.g., MATLAB/Simulink) through automated testing is of utmost importance since tool-chain generated artifacts are often deployed in safety-critical embedded hardware. Although automated differential testing through random program generation and equivalence modulo input (EMI)-based mutation has been well studied for procedural compiler testing, applying these techniques for Simulink, the widely used commercial CPS development tool pose unique challenges, which we explore in this series of work for the very first time. To better understand real-world CPS modeling and to automatically generate Simulink models similar to those crafted by engineers and researchers, we …

Learning Robot Manipulation Tasks Via Observation, Michail Theofanidis

Computer Science and Engineering Dissertations

The coexistence of humans and robots has been the aspiration of many scientific endeavors in the past century. Most anthropomorphic or industrial robots are highly articulated and complex machines, which are designed to carry out tasks that often involve the manipulation of physical objects. Traditionally, robots learn how to perform such tasks with the aid of a human programmer or operator. In this regard, the human acts as a teacher who provides a demonstration of a task. From the data of the demonstration, the robot must learn a state-action mapping that accomplishes the task. This state-action mapping is often addressed …

Data Set For An Empirical Analysis Of Search Engines’ Response To Web Search Queries Associated With The Classroom Setting, Oghenemaro Anuyah, Ashlee Milton, Michael Green, Maria Soledad Pera

Computer Science Faculty Scripts and Data

This archive contains queries that capture information in different search contexts. The first file includes those written by children between the 3rd - 6th grade levels, while performing search tasks. We collected and archived this data between the April 2017 -- December 2018, based on Boise State University's IRB approval. We also include simulated queries we extracted from children's reviews. Additional columns in this dataset are children's grade levels, the query source, and the query type (i.e., if it is a keyword, phrase, or question query). The other files are comprised of queries that are meant to lead to the …

Python Practice Assignments For Computer Science I, Hyrum Carroll, Hillary Fleenor

Computer Science and Information Technology Ancillary Materials

This set of practice assignments for Computer Science 1 were created under a Round Twelve Mini-Grant for Ancillary Materials Creation and Revision.

The assignments use the Python coding language and the repl.it coding platform and cover the following topics:

• Modules;
• Functions;
• Selections;
• Loops;
• Strings;
• Lists;
• Files;
• Dictionaries.

Internet Of Things (Open Course), Rebecca Rutherfoord, Susan Vandeven, Guangzhi Zheng, Hossain Shahriar, Xin Tian

Computer Science and Information Technology Ancillary Materials

This open course for Internet of Things was created through a Round 13 Affordable Materials Grant.

Cloud Computing (Ksu), Yong Shi, Dan Lo, Selena He, Mingon Kang, Sarah North

Computer Science and Information Technology Grants Collections

This Grants Collection for Cloud Computing was created under a Round Twelve ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

User Interface Engineering (Ksu), Yong Shi, Dan Lo, Selena He, Mingon Kang, Sarah North

Computer Science and Information Technology Grants Collections

This Grants Collection for User Interface Engineering was created under a Round Twelve ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Mobile Software Development (Ksu), Yong Shi, Dan Lo, Selena He, Sarah North, Mingon Kang

Computer Science and Information Technology Grants Collections

This Grants Collection for Mobile Software Development was created under a Round Twelve ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Computer Organization And Architecture (Ksu), Yong Shi, Dan Lo, Selena He, Mingon Kang, Sarah North

Computer Science and Information Technology Grants Collections

This Grants Collection for Computer Organization and Architecture was created under a Round Twelve ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Advanced Web Development (Ksu), Meng Han, Jack Zheng

Computer Science and Information Technology Grants Collections

This Grants Collection for Advanced Web Development was created under a Round Twelve ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report