Computer Sciences Commons^™

A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang

Dissertations

OBJECTIVES. Coronary artery disease (CAD) is the most common type of heart disease and kills over 360,000 people a year in the United States. Myocardial revascularization (MR) is a standard interventional treatment for patients with stable CAD. Fluoroscopy angiography is real-time anatomical imaging and routinely used to guide MR by visually estimating the percent stenosis of coronary arteries. However, a lot of patients do not benefit from the anatomical information-guided MR without functional testing. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a widely used functional testing for CAD evaluation but limits to the absence of anatomical information. …

Need For Diversity In Elected Decision-Making Bodies: Economics-Related Analysis, Nguyen Ngoc Thach, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

On a qualitative level, everyone understands the need to have diversity in elected decision-making bodies, so that the viewpoint of each group be properly taken into account. However, when only the usual economic criteria are used in this election -- e.g., in the election of company's board -- the resulting bodies often under-represent some groups (e.g., women). A frequent way to remedy this situation is to artificially enforce diversity instead of strictly following purely economic criteria. In this paper, we show the current seeming contradiction between economics and diversity is caused by the imperfection of the use economic models: in …

Falcon: Framework For Anomaly Detection In Industrial Control Systems, Subin Sapkota, A.K.M. Nuhil Mehdy, Stephen Reese, Hoda Mehrpouyan

Computer Science Faculty Publications and Presentations

Industrial Control Systems (ICS) are used to control physical processes in critical infrastructure. These systems are used in a wide variety of operations such as water treatment, power generation and distribution, and manufacturing. While the safety and security of these systems are of serious concern, recent reports have shown an increase in targeted attacks aimed at manipulating physical processes to cause catastrophic consequences. This trend emphasizes the need for algorithms and tools that provide resilient and smart attack detection mechanisms to protect ICS. In this paper, we propose an anomaly detection framework for ICS based on a deep neural network. …

The Megaprocessor As An Educational Tool Making The Abstract Concrete, Jonathon Beauregard Ii

Master's Theses

Computer architecture courses can be difficult for students to engage with and learn from. This is because, unlike most core courses for a computer science student, learning architecture is an abstract process. To address this, universities have implemented methods for teaching course material other than purely descriptive methods. This typically means using simulations to model some aspect of a CPU or FPGA (fieldprogrammable gate array) boards for hands-on experimentation in CPU design. However, there are issues with these tools. Simulations can only cover a few topics well, are prone to being abandoned, and introduce additional abstraction layers. FPGAs, while great …

Evaluating The Accuracy Of Gaze Detection For Moving Character, Sanath Narasimhan

Computer Science and Engineering Theses - Archive

Joint attention, where a caregiver and an infant follow each other’s eye gaze plays an important role in the learning of language for new-born infants. To study joint attention, it is required to record and analyze the joint attention in a naturalistic environment. For this, we can use the head-mounted eye tracker. However, natural interaction involves the body movement which a?ects the accuracy of the measurement. In this work, I evaluated the accuracy of the eye-tracking system in the three di?erent scenarios: when the subject is sitting still in front of the target when the subject looks at the target …

"How Good Are They?" - A State Of The Effectiveness Of Anti-Phishing Tools On Twitter, Sayak Saha Roy

Computer Science and Engineering Theses - Archive

Phishing websites are one of the most pervasive online attack vectors, with nearly 1.5 million such attacks created every month. Social media is the primary ground for phishing attacks, with 86% of these attacks originating from Twitter, Facebook, LinkedIn, etc. Prevalent approaches against these attacks includes URL scanners, anti-phishing blacklists and social media's own detection systems. In this work, we focus on Twitter, and through a combination of data-driven methods and emulations, we evaluate the verdicts provided by URL scanners, and Twitter’s detection system. We show that these sources provide a good amount of misinformation, which not only can lead …

In Situ Sensor Calibration Using Noise Consistency, Shriiesh Var Sharma

Computer Science and Engineering Theses - Archive

Robots rely on sensors to map their surroundings. As a result, the accuracy of the map depends heavily on the sensor noise and in particular on accurate knowledge of it. The common way to minimize the impact of sensor noise is to use filtering algorithms. Accuracy of these filtering algorithms (like the Kalman filter) relies on the accuracy of the user supplied measurement noise model. Inaccurate noise models lead to higher residual noise in state estimates and errors in the estimate of the precision of the state estimate. It is therefore important to have precise noise models and thus accurately …

Classification Of Factual And Non-Factual Statements Using Adversarially Trained Lstm Networks, Daniel Obembe

Computer Science and Engineering Theses - Archive

Being able to determine which statements are factual and therefore likely candidates for further verification is a key value-add in any automated fact-checking system. For this task, it has been shown that LSTMs outperform regular machine learning models, such as SVMs. However, the complexity of LSTMs can also result in over fitting (Gal and Ghahramani,1997), leading to poorer performance as models fail to generalize. To resolve this issue, we set out to utilize adversarial training as away to improve the performance of LSTMs for the task of classifying statements as factual or non-factual. In our experiment, we implement the adversarial …

Activity Recognition To Mimic Human Perception, Alankrit Gupta

Computer Science and Engineering Theses - Archive

The recognition of activities from video is a capability that is important for a wide range of applications, ranging from basic scene understanding to the successful prediction of behavior in autonomous vehicle applications. At this time, human capabilities in this task by far outperform computer applications and thus the idea to mimic human perception should be promising. In this thesis we are proposing an architecture that processes videos to extract important action instances that describe the essential behaviors contained in any video and help us map the information from the video to a machine-understandable form. This is an important research …

Person Identification And Tinetti Score Assessment Using Balance Parameters To Determine Fall Risk, Varsha Rani Chawan

Computer Science and Engineering Theses - Archive

This thesis is aimed at a substantial health problem among the elderly population that is “Fall”, a major cause of accidental home deaths. Studies show approximately one-third of community-dwelling people over 65 years of age will experience one or more falls each year. The balance and walking pattern are useful to determine the risk of fall in an individual and is highly influenced by several parameters and conditions. The deterioration in the balance and walking stability of an individual can occur because of the natural processes related to aging or as a result of various underlying health conditions, fatigue, muscle …

Preparing Students For Digital Era Careers, Melissa Stange

Inquiry: The Journal of the Virginia Community Colleges

This paper will discuss why technical skills alone will not be enough for students to have successful careers in the digital age. Much of their success will hinge on critical soft skills, such as adaptability, inner strength, holistic thinking, and a collaborative spirit. Examples will be provided for inclusion with a computer science program, but in a way that is easily adaptable to other disciplines.

Snitch Application: Addressing Cyber Trust In Future Living Spaces, Russell Moore

Cybersecurity Undergraduate Research Showcase

The future of smart homes is filled with excitement and ample opportunity to live in an environment that features extraordinary convenience and energy efficiency. Devices such as Amazon Alexa and Roku Smart TV’s feature voice interaction options that provide the user with enhanced functionality. While voice-activated devices are accommodating, it is imperative to acknowledge how they work on the backend. The problem is that these devices collect and share a large amount of data from users who are oftentimes unaware that it’s even happening. The Snitch App is being developed in order to inform the user of what exactly is …

Statistical And Deep Learning Models For Software Engineering Corpora, Van Duc Thong Hoang

Dissertations and Theses Collection (Open Access)

This dissertation focuses on proposing statistical and deep learning models for software engineering corpora to detect bugs in software system. The dissertation aims to solve three main software engineering problems, i.e., bug localization (locating the potential buggy source files in a software project given a bug report or failing test cases), just-in-time defect prediction (identifying the potential defective commits as they are introduced into a version control system), and bug fixing patch identification (identifying commits repairing bugs for their propagation to parallelly maintained versions) to save developers’ time and e↵ort in improving software system quality. Moreover, I also propose a …

Learning Embeddings For Wearable-Based Human Activity Analysis, Taoran Sheng

Computer Science and Engineering Dissertations - Archive

The embedded sensors in widely used smartphones, wearable devices and smart environments make the sensor data stream of human activity more accessible. With the development of deep neural networks, extensive studies have been conducted using deep learning methods to extract useful information from the sensor data to recognize the human activity, identify the person, or monitor the health condition of the person. However, applying deep neural networks to the sensor based human activity analysis task remains a challenging research problem in ubiquitous computing. Some of the reasons are: (i) The majority of the acquired data has no labels; (ii) Most …

Tail Latency Prediction For Fork-Join Structures, Sami Marzook Alesawi

Computer Science and Engineering Dissertations - Archive

The workflows of the predominant user-facing datacenter services, including web searching and social networking, are underlaid by various Fork-Join structures. Due to the lack of understanding the performance of Fork-Join structures in general, today’s datacenters often resort to resource overprovisioning, operating under low resource utilization, to meet stringent tail-latency service level objectives (SLOs) for such services. Hence, to achieve high resource utilization, while meeting stringent tail-latency SLOs, it is of paramount importance to be able to accurately predict the tail latency for a broad range of Fork-Join structures of practical interests. In this dissertation, we propose and conduct a comprehensive …

Efficient Construction And Explanation Of Machine Learning Models Through Database Techniques, Sona Hasani

Computer Science and Engineering Dissertations - Archive

Machine learning (ML) has been widely adopted in the last few years and it has had an undeniable impact on the ways many organizations make decisions. While great advances have been made in developing new ML algorithms and applications, there is a major need for scalable ML solutions in order to meet the demands of the Big data era. In this dissertation, we focus on improving the efficiency of two main machine learning solutions through database techniques: i) efficient construction of machine learning models, and ii) efficient explanation of machine learning models for multiple predictions. First, we introduce application of …

Analysis Of Complex Data Sets Using Multilayer Networks: A Decoupling-Based Framework, Abhishek Santra

Computer Science and Engineering Dissertations - Archive

We are on the cusp of analyzing a variety of data being collected in every walk of life - social, biological, health-care, corporate, climate, to name a few. The data sets are becoming diverse and complex in addition to increased size. Some of the complexity comes from interacting entities that arise in diverse disciplines, such as epidemiology, marketing strategy, social sciences, cybersecurity and drug design. Data sets becoming diverse and complex entails search for appropriate models and concomitant analytical techniques that are also efficient. Our ability to analyze large, complex, and disparate data for a broad set of analysis objectives …

Computer Vision Methods For Sign Language And Cognitive Evaluation Through Physical Tasks, Alex J. Dillhoff

Computer Science and Engineering Dissertations - Archive

Analyzing human motion is vital for a multitude of tasks including human-computer interaction, sign language recognition, and the assessment of cognitive disorders. Providing automatic assessments for cognitive disorders increases the accessibility and affordability of life-changing tests and treatments. For sign language recognition, automated translation systems bridge the gap between native and non-native signers. Additionally, dictionary look-up systems are helpful for native signers learning a new language. Common to both of these tasks is the reliance of fine motor function in the hands. Hand Pose Estimation methods are used to drive applications that rely on hand shape. These tasks present unique …

Arkitektura E Mikroshërbimeve Duke Perdorur .Net Core Dhe Reactjs, Arbër Kadriu

Theses and Dissertations

Koncepti i dizajnimit të arkitekturës së një sistemi ka evoluar, nga njëri dizajn në tjetrin, ku secili nga ta plotëson kërkesa të ndryshe kualitetit. Ditëve të sotme, qëllimi kryesor është që të plotësohen të gjitha kërkesat e përdoruesit, të zvogëlohet koha e përgjigjes së serverit, të sigurohet integriteti i komponentëve të sistemit dhe të njëjtën kohë të bëhen bashkëpunuese, në mënyrë që të arrihet një karakteristike plotësisht funksionale e sistemit. Arkitektura e mikro-shërbimeve ka aftësi të plotësoj të gjitha ato kërkesa, duke u zhvilluar me anë të teknologjive me bashkëkohore, siç janë .Net Core dhe ReactJS. në mënyrë që të …

Cyber Security – Penetration Test, Veton Bejtullahu

Theses and Dissertations

Si pjesë e rritjes së vazhdueshme të një bote të ndërlidhur mes veti në internet, shteti, infrastrukturat, bizneset dhe të gjithë njerëzit varen nga funksionimi i besueshëm i teknologjisë së informacionit dhe komunikimit. Liria dhe vlera e njerëzve në botën kibernetike duhet mbrojtur ashtu sikur në botën e jashtme. Me numrin e përdoruesve në internet gjithmonë në rritje dhe me teknologjitë e reja, numri i mundësive për sulm së bashku me kompleksitetin e sulmit, po rritet gjithashtu. Rreziku kryesor mbetet krimi kibernetik dhe rritja e tij reflektohet nga zhvillimi i shkathtësive të kriminelëve kibernetik dhe aftësia e tyre për të …

Learning Health Information From Floor Sensor Data Within A Pervasive Smart Home Environment, Nicholas Brent Burns

Computer Science and Engineering Dissertations - Archive

Spatial and temporal gait analysis can provide useful measures for determining a person’s state of health while also identifying deviations in day-to-day activity. The SmartCare project is a multi-discipline health technologies project that aims to provide an unobtrusive and pervasive system that provides in-home health monitoring for the elderly. This research work focuses on the pressure-sensitive smart floor of the SmartCare project by using an experimental floor to develop methods for future use on a floor deployed within a home. This work presents a procedure to automatically calibrate a smart floor’s pressure sensors without specialized physical effort. The calibration algorithm …

Novel Deep Learning Methods Combined With Static Analysis For Source Code Processing, Duy Quoc Nghi Bui

Dissertations and Theses Collection (Open Access)

It is desirable to combine machine learning and program analysis so that one can leverage the best of both to increase the performance of software analytics. On one side, machine learning can analyze the source code of thousands of well-written software projects that can uncover patterns that partially characterize software that is reliable, easy to read, and easy to maintain. On the other side, the program analysis can be used to define rigorous and unique rules that are only available in programming languages, which enrich the representation of source code and help the machine learning to capture the patterns better. …

Social Participation Performance Of Wheelchair Users Using Clustering And Geolocational Sensor's Data, Yukun Yin, Kar Way Tan

Research Collection School Of Computing and Information Systems

For wheelchair users, social participation and physical mobility play a significant part in determining their mental health and quality of life outcomes. However, little is known about how wheelchair users move about and engage in social interactions within their life-spaces. In this project, we investigate the social participation performance of the wheelchair users based on a combination of geolocational and lifestyle survey data collected over a period of three months. This paper adopts a multi-variate approach combining geolocational travel patterns and various factors such as independence, willingness and self-perception to provide multi-faceted analysis to their lifestyles. We provide profiles of …

Load Forecasting Analysis Using Contextual Data And Integration With Microgrids Used For Off Grid Ev Charging Stations, Ashit Neema

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Electricity is an essential component of the smooth working of every sector. If a successful prediction of how much electricity will be required for say the next 24 hours or 48 hours can be made, it will not only help in efficiently planning the activities and operations but also help in minimizing the cost incurred. In this thesis the same is being attempted, first, a model is created that can predict the energy consumption of households using various tools available. To achieve this, historical data of the past 5 years that has been recorded in London has been used. Secondly, …

A Framework For Verifying The Fixity Of Archived Web Resources, Mohamed Aturban

Computer Science Theses & Dissertations

The number of public and private web archives has increased, and we implicitly trust content delivered by these archives. Fixity is checked to ensure that an archived resource has remained unaltered (i.e., fixed) since the time it was captured. Currently, end users do not have the ability to easily verify the fixity of content preserved in web archives. For instance, if a web page is archived in 1999 and replayed in 2019, how do we know that it has not been tampered with during those 20 years? In order for the users of web archives to verify that archived web …

Secure Mobile Computing By Using Convolutional And Capsule Deep Neural Networks, Rui Ning

Electrical & Computer Engineering Theses & Dissertations

Mobile devices are becoming smarter to satisfy modern user's increasing needs better, which is achieved by equipping divers of sensors and integrating the most cutting-edge Deep Learning (DL) techniques. As a sophisticated system, it is often vulnerable to multiple attacks (side-channel attacks, neural backdoor, etc.). This dissertation proposes solutions to maintain the cyber-hygiene of the DL-Based smartphone system by exploring possible vulnerabilities and developing countermeasures.

First, I actively explore possible vulnerabilities on the DL-Based smartphone system to develop proactive defense mechanisms. I discover a new side-channel attack on smartphones using the unrestricted magnetic sensor data. I demonstrate that attackers can …

Automatic Linear And Curvilinear Mesh Generation Driven By Validity Fidelity And Topological Guarantees, Jing Xu

Computer Science Theses & Dissertations

Image-based geometric modeling and mesh generation play a critical role in computational biology and medicine. In this dissertation, a comprehensive computational framework for both guaranteed quality linear and high-order automatic mesh generation is presented. Starting from segmented images, a quality 2D/3D linear mesh is constructed. The boundary of the constructed mesh is proved to be homeomorphic to the object surface. In addition, a guaranteed dihedral angle bound of up to 19:47^o for the output tetrahedra is provided. Moreover, user-specified guaranteed bounds on the distance between the boundaries of the mesh and the boundaries of the materials are allowed. The …

Cyber-Assets At Risk (Car): Monetary Impact Of Personally Identifiable Information Data Breaches On Companies, Omer Ilker Poyraz

Engineering Management & Systems Engineering Theses & Dissertations

Cyber-systems provide convenience, ubiquity, economic advantage, and higher efficiency to both individuals and organizations. However, vulnerabilities of the cyber domain also offer malicious actors with the opportunities to compromise the most sensitive information. Recent cybersecurity incidents show that a group of hackers can cause a massive data breach, resulting in companies losing competitive advantage, reputation, and money. Governments have since taken some actions in protecting individuals and companies from such crime by authorizing federal agencies and developing regulations. To protect the public from losing their most sensitive records, governments have also been compelling companies to follow cybersecurity regulations. If companies …

A Visual Analytics Tool For Personalized Competency Feedback, Joelle Elmaleh, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

In this paper we report our study on the design and implementation of a visual analytics tool, Competency Analytics System (CAS), which provides feedback to instructors on both the cohort and individual student’s competency acquisition rate, as well as provide personalized dashboard to each student on his or her competency acquisition for a specific course. We present the key functionalities of CAS and describe a case study on the implementation of CAS in a first-year programming course. Data from a student survey indicates that the personalized dashboard provided by CAS contributed to enhancing their ability to clearly identify the extent …

Using Natural Language Processing And Sentiment Analysis To Augment Traditional User-Centered Design: Development And Usability Study, Curtis L. Petersen, Ryan Halter, David Kotz, Lorie Loeb, Summer B. Cook, Dawna M. Pidgeon, Brock Christensen, John A. Batsis

Dartmouth Scholarship

Background: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process.

Objective: This study aims …