Computer Sciences Commons^™

Factors Affecting Customers’ Decision To Share Personal Data With Mobile Operators, Ammar Ali Qaffaf

CCAC Theses and Dissertations

Companies that personalize their services based on users’ specific needs have increased sales and customer satisfaction. Personalization requires analyzing the user’s behavior and correlating the action with other pieces of information. The information available for cellular service providers has grown substantially as connectivity becomes ubiquitous. Customers are unknowingly sharing their locations, habits, activities, and preferences in real-time with their service providers. Although cellular service providers state that they share personal data with external entities in their publicly available privacy policies, users have limited control over who can access their personal information. Users have no, or suboptimal, control to manage their …

Modified Structured Domain Randomization In A Synthetic Environment For Learning Algorithms, Bryan L. Croft

CCAC Theses and Dissertations

Deep Reinforcement Learning (DRL) has the capability to solve many complex tasks in robotics, self-driving cars, smart grids, finance, healthcare, and intelligent autonomous systems. During training, DRL agents interact freely with the environment to arrive at an inference model. Under real-world conditions this training creates difficulties of safety, cost, and time considerations. Training in synthetic environments helps overcome these difficulties, however, this only approximates real-world conditions resulting in a ‘reality gap’. The synthetic training of agents has proven advantageous but requires methods to bridge this reality gap. This work addressed this through a methodology which supports agent learning. A framework …

Information Systems Security Countermeasures: An Assessment Of Older Workers In Indonesian Small And Medium-Sized Businesses, Hari Samudra Roosman

CCAC Theses and Dissertations

Information Systems (IS) misuse can result in cyberattacks such as denial-of-service, phishing, malware, and business email compromise. The study of factors that contribute to the misuse of IS resources is well-documented and empirical research has supported the value of approaches that can be used to deter IS misuse among employees; however, age and cultural nuances exist. Research focusing on older workers and how they can help to deter IS misuse among employees and support cybersecurity countermeasures within developing countries is in its nascent stages. The goal of this study was two-fold. The first goal was to assess what older workers …

Experimental Study To Assess The Role Of Environment And Device Type On The Success Of Social Engineering Attacks: The Case Of Judgment Errors, Tommy Pollock

CCAC Theses and Dissertations

Phishing continues to be an invasive threat to computer and mobile device users. Cybercriminals continuously develop new phishing schemes using e-mail and malicious search engine links to gather the personal information of unsuspecting users. This information is used for financial gains through identity theft schemes or draining victims' financial accounts. Many users of varying demographic backgrounds fall victim to phishing schemes at one time or another. Users are often distracted and fail to process the phishing attempts fully, then unknowingly fall victim to the scam until much later. Users operating mobile phones and computers are likely to make judgment errors …

Impact Of Knowledge Management Processes Upon Job Satisfaction And Job Performance, George Reid Cooper

CCAC Theses and Dissertations

While we might know anecdotally that the implementation of knowledge management in an organization improves job satisfaction and job performance, there are limited empirical studies that assess this assumption. There have been studies done in this area but the results vary in terms of which knowledge management processes have an impact upon job satisfaction and which do not. Similarly, many studies make assumptions that job satisfaction leads to improved job performance without testing for that variable. The goal of this dissertation is to assess whether the knowledge management processes have a positive impact upon job satisfaction and job performance and …

An Approach For Efficient Robust Adversarial Training In Deep Neural Networks, Cesar Zalzalah

CCAC Theses and Dissertations

With advancements in computer hardware, deep neural networks outperform other methods for many applications, such as image and voice recognition. Unfortunately, existing deep neural networks are fragile at test time against adversarial examples, which are intentionally calculated perturbations that cause a neural network to misclassify the correct input label. This vulnerability makes the use of neural networks risky, especially in critical applications. Extensive prior research studies to build a robust neural network using diverse approaches have been proposed to tackle this problem, including customized models and their parameters, input pre-processing to detect and remove adversarial perturbations, blocking the adversarial input, …

An Empirical Investigation Of The Evidence Recovery Process In Digital Forensics, Kevin Parviz

CCAC Theses and Dissertations

The widespread use of the digital media in committing crimes, and the steady increase of their storage capacity has created backlogs at digital forensic labs. The problem is exacerbated especially in high profile crimes. In many such cases the judicial proceedings mandate full analysis of the digital media, when doing so is rarely accomplished or practical. Prior studies have proposed different phases for forensic analysis, to lessen the backlog issues. However, these phases are not distinctly differentiated, and some proposed solutions may not be practical. This study utilized several past police forensic analyses. Each case was chosen for having five …

Exploring The Existing And Unknown Side Effects Of Privacy Preserving Data Mining Algorithms, Hima Bindu Sadashiva Reddy

CCAC Theses and Dissertations

The data mining sanitization process involves converting the data by masking the sensitive data and then releasing it to public domain. During the sanitization process, side effects such as hiding failure, missing cost and artificial cost of the data were observed. Privacy Preserving Data Mining (PPDM) algorithms were developed for the sanitization process to overcome information loss and yet maintain data integrity. While these PPDM algorithms did provide benefits for privacy preservation, they also made sure to solve the side effects that occurred during the sanitization process. Many PPDM algorithms were developed to reduce these side effects. There are several …

Mapping Of Microseismic Aftershock Sequences Following The 2017 Lincoln, Montana M 5.8 Earthquake, Reyer M. Fenoff

Undergraduate Theses, Professional Papers, and Capstone Artifacts

The Rocky Mountains of western Montana have long been experiencing tectonic compression and extension that has shaped much of western North America. This activity consistently produces seismic events, like the 6 July 2017 M 5.8 earthquake 11 km southeast of Lincoln, MT, which can be used to advance understanding of crust and mantle dynamics and structure. Seismic mapping is vital to understanding structure and tectonic activity in western Montana as well as in analogous locations across the world. Recently deployed seismometers from the University of Montana as well as the Montana Regional Seismic Network (MRSN) from the Montana Bureau of …

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

The Privacy Leakage Of Ip Camera Systems, Lee R. Castro

Theses, Dissertations and Culminating Projects

For in-home security, intelligent operations like top individual recognition and minimizing losses due to home break-ins, emergencies, and fraud are keys to success. This application integrates the closed-circuit television (CCTV) camera and the deep learning algorithms used to process these images. Automated intrusion detection alerts, real-time fire alerts, smart checkout, and potentially fraudulent point of sale (POS) transactions are its main features. Dynamic intrusion with machine learning is a software program in which the price of certain products changes over time through an algorithm that considers a variety of pricing variables. The face locator is a part of the algorithm …

Development And On-Road Applications Of A 1/10-Scale Autonomous Vehicle, Laura Cornejo Paulino

Theses, Dissertations and Culminating Projects

Autonomous vehicles (AVs) are a key component in the creation of the new transportation infrastructure. Over the last several decades, nations across the world have experienced an increase in traffic congestion, environmental deprecation due to greenhouse gas emissions and an increase in time loss and productivity. A key factor in these components is the increase in numbers of vehicles on the road, a number that continues to increase gradually every year. In addition, the continued increase in vehicles on the road poses a threat to human and environmental safety. There is strong evidence to support that accidental vehicular deaths and …

Diagnosis Of Errors In Stalled Inter-Organizational Workflow Processes, Mudassar Habib Ghazi

CCAC Theses and Dissertations

Fault-tolerant inter-organizational workflow processes help participant organizations efficiently complete their business activities and operations without extended delays. The stalling of inter-organizational workflow processes is a common hurdle that causes organizations immense losses and operational difficulties. The complexity of software requirements, incapability of workflow systems to properly handle exceptions, and inadequate process modeling are the leading causes of errors in the workflow processes.

The dissertation effort is essentially about diagnosing errors in stalled inter-organizational workflow processes. The goals and objectives of this dissertation were achieved by designing a fault-tolerant software architecture of workflow system’s components/modules (i.e., workflow process designer, workflow engine, …

A Validity-Based Approach For Feature Selection In Intrusion Detection Systems, Eljilani Hmouda

CCAC Theses and Dissertations

Intrusion detection systems are tools that detect and remedy the presence of malicious activities. Intrusion detection systems face many challenges in terms of accurate analysis and evaluation. One such challenge is the involvement of many features during analysis, which leads to high data volume and ultimately excessive computational overhead. This research surrounds the development of a new intrusion detection system by employing an entropy-based measure called v-measure to select significant features and reduce dimensionality. After the development of the intrusion detection system, this feature reduction technique was tested on public datasets by applying machine learning classifiers such as Decision Tree, …

Image-Data-Driven Deep Learning For Slope Stability Analysis, Behnam Azmoon

Dissertations, Master's Theses and Master's Reports

Landslides cause major infrastructural issues, damage the environment, and cause socio-economic disruptions. Therefore, various slope stability analysis methods have been developed to evaluate the stability of slopes and the probability of their failure. This dissertation attempts to take advantage of the recent advancements in remote sensing and computer technology to implement a deep-learning-based landslide prediction method.

Considering the novelty of this approach, this dissertation leads with proof-of-concept studies to evaluate and establish the suitability of deep learning models for slope stability analysis. To achieve this, a simulated 2D dataset of slope images was created with different geometries and soil properties. …

Lpvit: A Transformer Based Model For Pcb Image Classification And Defect Detection, Kang An, Yanping Zhang

Computer Science Faculty Scholarship

PCB (printed circuit board) is an extremely important component of all electronic products, which has greatly facilitated human life. Meanwhile, tons of PCBs in the waste streams become a waste of resources, which puts the recycling and reuse of PCBs in urgent need. In the manufacturing and recycling of electronic products, the classification of PCBs, recognition of sub-components, and defect detection have been the key technology. Traditional manual detection and classification are subjective and rely on individuals’ experience. With the development of artificial intelligence, lots of research efforts have been dedicated to the automated detection and recognition of PCBs. In …

A Framework For And Design Of A Smart Academic Building Using Sensors, Citizen Participation, And Volunteered Geographic Information, Neelam Raigangar

CGU Theses & Dissertations

Population growth and migration patterns have shown an influx of residents from rural to urban environments. To deal with the problems caused by unprecedented urban influx, cities should plan to use technology in a smart and distinctive way. Tackling at the city scale is hard. But a set of smart buildings that are interconnected by technology will lead to smarter communities which are then interconnected to create a smart city. Smart lobby, building, community, or city is distinguished by its application of integrated software, hardware, and network technologies, along with access to real-time data enabling decision-making, facilitating tracing, tracking and …

Cybersecurity & Correctional Institutions, Kelly Himelwright

Cybersecurity Undergraduate Research Showcase

Cybersecurity is becoming an increasingly important aspect of correctional operations. To properly maintain security, more jails and prisons are using comprehensive cyber protection techniques. Correctional facilities face risks that were perhaps unimaginable only a few decades ago. Many organizations have used information technology to help them run their businesses, but few have the resources or vision to foresee and adequately manage the cyber dangers that come with it. Institutions need to be more aware of these hazards, as well as have more information security experts on staff.

Multiple-Place Swarm Foraging With Dynamic Robot Chains, Dohee Lee, Qi Lu, Tsz-Chiu Au

Computer Science Faculty Publications

The goal of foraging robot swarms is to search and deliver resources to a specific central collection zone quickly. In the previously proposed multiple-place foraging algorithm with dynamic depots, foraging performance decreases as search areas and swarm sizes increase: depots need to travel long distances to deliver resources to the center, and more robots produce more congestion on their journeys. We propose a novel extension to the multiple-place foraging in which multiple robot chains are deployed dynamically. Each robot chain connects a foraging location to the central collection zone. Instead of delivering resources by a single robot, resources are passed …

A Cloud Computing-Based Dashboard For The Visualization Of Motivational Interviewing Metrics, E Jinq Heng

Browse all Theses and Dissertations

Motivational Interviewing (MI) is an evidence-based brief interventional technique that has been demonstrated to be effective in triggering behavior change in patients. To facilitate behavior change, healthcare practitioners adopt a nonconfrontational, empathetic dialogic style, a core component of MI. Despite its advantages, MI has been severely underutilized mainly due to the cognitive overload on the part of the MI dialogue evaluator, who has to assess MI dialogue in real-time and calculate MI characteristic metrics (number of open-ended questions, close-ended questions, reflection, and scale-based sentences) for immediate post-session evaluation both in MI training and clinical settings. To automate dialogue assessment and …

Drivers And Challenges Of Wearable Devices Use: Content Analysis Of Online Users Reviews, Ahmed El Noshokaty, Omar El-Gayar, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Tareq Nasralah

Computer Information Systems Faculty Publications (Archived)

With recent advancements in wearable device technologies, there is still a need to investigate drivers and challenges associated with the use of these devices. Following a content analysis approach, this study leverages recent “found large-scale” data to better understand the drivers and challenges that affect the adoption and use of such devices. Analyzing a total of 16,717 online reviews about wearable devices, the findings emphasized the importance of various functionalities (perceived usefulness), appeal, and a number of device design features as the most prominent drivers, while concerns about quality, credibility, and perceived value as potential challenges to wearable adoption and …

Customer Drinks Purchasing Behavior During Covid-19 Pandemic Analysis, Krittayot Bherngjitt

Chulalongkorn University Theses and Dissertations (Chula ETD)

The COVID-19 pandemic has caused many changes to the lifestyle of people all over the world. The lockdown forced people to stay at home for many months. This has led to the changes in purchasing behavior as well such as the increase in delivery order. This research, which has received sales data of drinks during the pandemic from a large beverage company, seeks to analyze the changes in customer behavior during the pandemic by using machine learning to perform clustering and observe the changes in the purchases of each product type. We will use clustering to group customers based on …

A Game Theoretical Model Of Radiological Terrorism Defense, Shraddha Rane, Jason Timothy Harris

International Journal of Nuclear Security

Radiological dispersal devices (RDD) pose a threat to the United States. Healthcare facilities housing high-risk radioactive materials and devices are potentially easy targets for unauthorized access and are vulnerable to malevolent acts of theft or sabotage. The three most attractive candidates for use in RDD considered in this study are: ⁶⁰Co (radiosurgery devices), ¹³⁷Cs (blood irradiators) and ¹⁹²Ir (brachytherapy high dose radiation device). The threat posed by RDDs has led to evaluating the security risk of radioactive materials and defending against attacks. The concepts of risk analysis used in conjunction with game theory lay the foundations of …

Genetic Algorighm Representation Selection Impact On Binary Classification Problems, Stephen V. Maldonado

Honors Undergraduate Theses

In this thesis, we explore the impact of problem representation on the ability for the genetic algorithms (GA) to evolve a binary prediction model to predict whether a physical therapist is paid above or below the median amount from Medicare. We explore three different problem representations, the vector GA (VGA), the binary GA (BGA), and the proportional GA (PGA). We find that all three representations can produce models with high accuracy and low loss that are better than Scikit-Learn’s logistic regression model and that all three representations select the same features; however, the PGA representation tends to create lower weights …

Static Analysis Of The Build System To Accelerate Continuous Testing Of Highly Configurable Software, Necip Fazil Yildiran

Electronic Theses and Dissertations, 2020-2023

Continuous testing is widely used for facilitating fast and reliable software delivery. However, build-time configurability makes such testing harder for configurable software. As configurable software forms the basis of much of our computing infrastructure, there is even more need for better continuous testing for configurable software. In this dissertation, our goal is to improve the quality of configurable software. To this end, we tackle two, previously unsolved problems. The build system of configurable software is one of the biggest reasons why testing configurable software is hard. Therefore, in our solutions, we deal with the build system by using a comprehensive …

Translations To Support Loop Invariant Generation In Jml, Kohei Koja

Electronic Theses and Dissertations, 2020-2023

Software is used in many critical systems in the real world such as autonomous cars and medical devices. Such software must be reliable to protect the general public. One standard way to make reliable software is to use Hoare-style verification techniques. However, for Hoare-style verification of loop correctness, loop invariants are necessary but are difficult for people to write themselves. Since Java is one of the most popular programming languages in the world, it is useful to have a tool to generate loop invariants for Java programs. OpenJML is a widely used program verification tool for Java. However, it does …

Effficient Graph-Based Computation And Analytics, Bingbing Rao

Electronic Theses and Dissertations, 2020-2023

With data explosion in many domains, such as social media, big code repository, Internet of Things (IoT), and inertial sensors, only 32% of data available to academic and industry is put to work, and the remaining 68% goes unleveraged. Moreover, people are facing an increasing number of obstacles concerning complex analytics on the sheer size of data, which include 1) how to perform dynamic graph analytics in a parallel and robust manner within a reasonable time? 2) How to conduct performance optimizations on a property graph representing and consisting of the semantics of code, data, and runtime systems for big …

Predicting Customer Loyalty In The Mobile Banking Setting: An Integrated Approach, Nhuong Bui, Zach Moore, Hayden Wimmer, Long Pham

Information Technology: Faculty Publications

This study uses a novel theoretical approach that combines two multidimensional service quality models that focus on customer satisfaction, perceived value, and customer loyalty as outcomes of service quality in the context of mobile banking. Additionally, the study assesses the potential moderating effects of switching costs between mobile banking service quality and customer loyalty. The study found a strong direct effect between service quality, perceived value, customer satisfaction, and loyalty. The moderating effect of switching costs was found to be inconsequential to customer loyalty. The study demonstrates that financial institutions should focus on building and maintaining functional, secure mobile banking …

The Effect Of Touch Simulation In Virtual Reality Shopping, Ha Kyung Lee, Namhee Yoon, Dooyoung Choi

STEMPS Faculty Publications

This study aims to explore the effect of touch simulation on virtual reality (VR) store satisfaction mediated by VR shopping self-efficacy and VR shopping pleasure. The moderation effects of the autotelic and instrumental need for touch between touch simulation and VR store satisfaction are also explored. Participants wear a head-mounted display VR device (Oculus Go) in a controlled laboratory environment, and their VR store experience is recorded as data. All participants’ responses (n = 58) are analyzed using SPSS 20.0 for descriptive statistics, reliability analysis, exploratory factor analysis, and the Process macro model analysis. The results show that touch simulation …

Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan

Electronic Theses and Dissertations

Neural Networks have been used in many decision-making models and been employed in computer vision, and natural language processing. Several works have also used Neural Networks for developing Pseudo-Random Number Generators [2, 4, 5, 7, 8]. However, despite great performance in the National Institute of Standards and Technology (NIST) statistical test suite for randomness, they fail to discuss how the complexity of a neural network affects such statistical results. This work introduces: 1) a series of new Long Short- Term Memory Network (LSTM) based and Fully Connected Neural Network (FCNN – baseline [2] + variations) Pseudo Random Number Generators (PRNG) …