Computer Sciences Commons^™

Examination Of Corporate Investments In Privacy: An Event Study, Joseph Michael Squillace

CCAC Theses and Dissertations

The primary objective of any corporate entity is generating as much wealth as possible. Investing financially in technology domains has historically been a successful strategy for generating increased corporate and shareholder wealth. However, investments in Information Technology (IT), Information Systems (IS) and Information Security (InfoSec) to specifically generate increased wealth must be implemented carefully.

Shareholders reacting to corporate investments perceive financial value from individual investments. The investment’s perceived value is then reflected in the corporation’s updated stock market value. IS, IT, and InfoSec investments perceived to possess positive financial value, indicating strong potential for increased wealth, are rewarded by shareholders …

Pause For A Cybersecurity Cause: Assessing The Influence Of A Waiting Period On User Habituation In Mitigation Of Phishing Attacks, Amy Antonucci

CCAC Theses and Dissertations

Social engineering costs organizations billions of dollars a year. Social engineering exploits the weakest link of information security systems, the people who are using them. Phishing is a form of social engineering in which the perpetrator depends on the victim’s instinctual thinking towards an email designed to create a fear or excitement response. It is well-documented in literature that users continue to click on phishing emails costing them and their employers significant monetary resources and data loss. Training does not appear to mitigate the effects of phishing much; other solutions are necessary to mitigate phishing.

Kahneman introduced the concepts of …

Increasing Software Reliability Using Mutation Testing And Machine Learning, Michael Allen Stewart

CCAC Theses and Dissertations

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. The goal of mutation testing was to reduce complex program errors by preventing the related simple errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs.

This …

An Empirical Assessment Of Users' Information Security Protection Behavior Towards Social Engineering Breaches, Nisha Jatin Patel

CCAC Theses and Dissertations

User behavior is one of the most significant information security risks. Information Security is all about being aware of who and what to trust and behaving accordingly. Due to technology becoming an integral part of nearly everything in people's daily lives, the organization's need for protection from security threats has continuously increased. Social engineering is the act of tricking a user into revealing information or taking action. One of the riskiest aspects of social engineering is that it depends mainly upon user errors and is not necessarily a technology shortcoming. User behavior should be one of the first apprehensions when …

Interpretable Machine Learning Model For Clinical Decision Making, Ali El-Sharif

CCAC Theses and Dissertations

Despite machine learning models being increasingly used in medical decision-making and meeting classification predictive accuracy standards, they remain untrusted black-boxes due to decision-makers' lack of insight into their complex logic. Therefore, it is necessary to develop interpretable machine learning models that will engender trust in the knowledge they generate and contribute to clinical decision-makers intention to adopt them in the field.

The goal of this dissertation was to systematically investigate the applicability of interpretable model-agnostic methods to explain predictions of black-box machine learning models for medical decision-making. As proof of concept, this study addressed the problem of predicting the risk …

Investigating The User Experience With A 3d Virtual Anatomy Application, Winnyanne Kunkle

CCAC Theses and Dissertations

Decreasing hours dedicated to teaching anatomy courses and declining use of human cadavers have spurred the need for innovative solutions in teaching anatomy in medical schools. Advancements in virtual reality (VR), 3D visualizations, computer graphics, and medical graphic images have enabled the development of highly interactive 3D virtual applications. Over recent years, variations of interactive systems on computer-mediated environments have been used as supplementary resource for learners. However, despite the growing sophistication of these resources for learning anatomy, studies show that students predominantly prefer traditional methods of learning and hands-on cadaver-based learning over computer-mediated platforms.

There is limited research on …

Development Of A Social Engineering Exposure Index (Sexi) Using Open-Source Personal Information, William Shawn Wilkerson

CCAC Theses and Dissertations

Millions of people willingly expose their lives via Internet technologies every day, and even the very few ones who refrain from the use of the Internet find themselves exposed through data breaches. Billions of private information records are exposed through the Internet. Marketers gather personal preferences to influence shopping behavior. Providers gather personal information to deliver enhanced services, and underground hacker networks contain repositories of immense data sets. Few users of Internet technologies have considered where their information is going or who has access to it. Even fewer are aware of how decisions made in their own lives expose significant …

Human Errors In Data Breaches: An Exploratory Configurational Analysis, Gabriel A. Cornejo

CCAC Theses and Dissertations

Information Systems (IS) are critical for employee productivity and organizational success. Data breaches are on the rise—with thousands of data breaches accounting for billions of records breached and annual global cybersecurity costs projected to reach $10.5 trillion by 2025. A data breach is the unauthorized disclosure of sensitive information—and can be achieved intentionally or unintentionally. Significant causes of data breaches are hacking and human error; in some estimates, human error accounted for about a quarter of all data breaches in 2018. Furthermore, the significance of human error on data breaches is largely underrepresented, as hackers often capitalize on organizational users’ …

A Study Of Factors That Influence Symbol Selection On Augmentative And Alternative Communication Devices For Individuals With Autism Spectrum Disorder, William Todd Dauterman

CCAC Theses and Dissertations

According to the American Academy of Pediatrics (AAP), 1 in 59 children are diagnosed with Autism Spectrum Disorder (ASD) each year. Given the complexity of ASD and how it is manifested in individuals, the execution of proper interventions is difficult. One major area of concern is how individuals with ASD who have limited communication skills are taught to communicate using Augmentative and Alternative Communication devices (AAC). AACs are portable electronic devices that facilitate communication by using audibles, signs, gestures, and picture symbols. Traditionally, Speech-Language Pathologists (SLPs) are the primary facilitators of AAC devices and help establish the language individuals with …

Public Interest Technology – Exploring Covid-19 Health Data, Sarah Zelikovitz

Open Educational Resources

This module is part of a Introduction to Data Science course that covers the different parts of the data science process: data acquisition, cleaning, exploratory data analysis, and modeling. The COVID-19 pandemic has created much interest in public health data, as well as interest in visualization of all types of data. Public health data has a set of challenges that is unique to health data, with HIPAA laws, and real time collection of data. With COVID-19, the challenges are particularly amplified, as data collection and statistics collected are constantly changing in response to feedback from labs, hospitals, drug companies, and …

Deep Learning-Based Covid-19 Detection System Using Pulmonary Ct Scans, Rajit Nair, Adi Alhudhaif, Deepika Koundal, Rumi Iqbal Doewes, Preeti Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

One of the most significant pandemics has been raised in the form of Coronavirus disease 2019 (COVID19). Many researchers have faced various types of challenges for finding the accurate model, which can automatically detect the COVID-19 using computed pulmonary tomography (CT) scans of the chest. This paper has also focused on the same area, and a fully automatic model has been developed, which can predict the COVID-19 using the chest CT scans. The performance of the proposed method has been evaluated by classifying the CT scans of community-acquired pneumonia (CAP) and other non-pneumonia. The proposed deep learning model is based …

A Novel Design Of Current Differencing Transconductance Amplifier With Hightransconductance Gain And Enhanced Bandwidth, Shireesh Kumar Rai, Rishikesh Pandey, Bharat Garg, Sujit Patel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, transconductance gain of current differencing transconductance amplifier (CDTA) has been boosted by using a novel approach. Transconductance is generally varied by two well-known techniques. In the first technique, bias current of differential pair MOSFETs is varied whereas in the second technique, aspect ratios of differential pair MOSFETs are changed. The drawbacks of first technique are limited range of transconductance and higher power dissipation whereas second technique restricts dynamic range, output swing and bandwidth of CDTA. To overcome these drawbacks, 2 new structures of CDTA, namely high transconductance gain CDTAs (HTG-CDTA-I & HTG-CDTA-II) have been proposed. HTG-CDTA-I utilizes …

Mismatch Error Shaping Of Dac Unit Elements In Multibit $\Delta$$\Sigma$ Modulators Using A Novel Unified Adc/Dac, Leila Sharifi, Omid Hashemipour

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a unified analog to digital converter (ADC) and digital to analog converter (DAC) for multibit $\Delta\Sigma$ modulators. The unified ADC/DAC circuit provides error shaping for mismatches between DAC unit elements. Hence, the dynamic element matching (DEM) circuit or digital calibration is not required resulting in the area and power saving as well as the elimination of the excess loop delay introduced by DEM circuit. Incorporating a 6-bit unified ADC/DAC, the $\Delta\Sigma$ modulator achieves 16.15-bit resolution utilizing only a second order loop filter and oversampling ratio of 40. The proposed modulator is simulated in a 65-nm CMOS process. …

Deep Learning For Electricity Forecasting Using Time Series Data, Hanan Abdullah Alshehri

Theses, Dissertations and Culminating Projects

The complexity and nonlinearities of the modern power grid render traditional physical modeling and mathematical computation unrealistic. AI and predictive machine learning techniques allow for accurate and efficient system modeling and analysis. Electricity consumption forecasting is highly valuable in energy management and sustainability research. Furthermore, accurate energy forecasting can be used to optimize energy allocation. This thesis introduces Deep Learning models including the Convolutional Neural Network (CNN), the Recurrent neural network (RNN), and Long Short-Term memory (LSTM). The Hourly Usage of Energy (HUE) dataset for buildings in British Columbia is used as an example for our investigation, as the dataset …

Human-Robot Collaboration Using Commonsense Knowledge In Smart Manufacturing Contexts, Christopher Joseph Conti

Theses, Dissertations and Culminating Projects

Human-robot collaboration (HRC), where humans and robots work together on specific tasks, is a growing part of smart manufacturing that entails artificial intelligence (AI) techniques in manufacturing processes. Robots need to be able to dynamically understand their working environments and human partners both accurately and quickly, as inaccurate or slow predictions can be dangerous to humans and collaborative tasks. To handle challenging environments, robots need to utilize commonsense knowledge (CSK), which is everyday knowledge about fundamental concepts, such as how basic objects interact with each other, what their properties are, and how they are associated. Human beings utilize CSK regularly, …

Assisting Humans In Human-Robot Co-Carry Tasks Using Robot-Trusting-Human Model, Corey Hannum

Theses, Dissertations and Culminating Projects

Robots are increasingly being employed for diverse applications where they must work and coexist with humans. The trust in human-robot collaboration (HRC) is a critical aspect of any shared task performance for both the human and the robot. The study of human-trusting-robot has been investigated by numerous researchers. However, robot-trusting-human, which is also a significant issue in HRC, is seldom explored in the field of robotics. In this paper we propose a novel trust-assist framework for human-robot co-carry tasks. This framework allows the robot to determine a trust level on the human co-carry partner. The calculations of this trust level …

A Secure And Verifiable Computation For K-Nearest Neighbor Queries In Cloud, Salma Yahya Bokhary

Theses, Dissertations and Culminating Projects

The popularity of cloud computing has increased significantly in the last few years due to scalability, cost efficiency, resiliency, and quality of service. Organizations are more interested in outsourcing the database and DBMS functionalities to the cloud owing to the tremendous growth of big data and on-demand access requirements. As the data is outsourced to untrusted parties, security has become a key consideration to achieve the confidentiality and integrity of data. Therefore, data owners must transform and encrypt the data before outsourcing. In this paper, we focus on a Secure and Verifiable Computation for k-Nearest Neighbor (SVC-kNN) problem. The existing …

Small Business Owner App To Showcase Covid Prevention Policies And Reopening Guidelines, Christopher Duran

Theses, Dissertations and Culminating Projects

Almost a year after the emergence of the Coronavirus, the pandemic still negatively affects the world’s economy and quality of life. In the U.S., Covid-19 has shut down nearly 100,000 businesses.

The goal of this project is to develop an app that can assist business owners to accurately display their coronavirus prevention methods so that people can feel safe while using their services. This project will focus on how the business owner (Vendor) will be able to interact, utilize, and display important information for the customer (Patron) to use.

The vendor will be able to create an individual profile for …

Identifying The Impact Of Perceived Shared Cultural Values On Knowledge Sharing Through A Social Media Application, Mel Anthony Tomeo

CCAC Theses and Dissertations

Knowledge sharing (KS) has been determined by many researchers as an important tool for problem-solving experiences and achieving success. Recent studies have explained KS as an activity in which knowledge is exchanged through individuals or between organizations. KS can help facilitate decision-making capabilities, stimulate cultural change, and create innovation. Through KS, individuals and organizations can capture explicit and tacit knowledge to save time and money. Previous studies have indicated a lack of research in how perceived shared cultural values impact KS through a social media application.

The purpose of this research was to add new information to the body of …

An Empirical Examination Of The Impact Of Organizational Injustice And Negative Affect On Attitude And Non-Compliance With Information Security Policy, Celestine Kemah

CCAC Theses and Dissertations

Employees’ non-compliance with Information Security (IS) policies is an important socio-organizational issue that represents a serious threat to the effective management of information security programs in organizations. Prior studies have demonstrated that information security policy (ISP) violation in the workplace is a common significant problem in organizations. Some of these studies have earmarked the importance of this problem by drawing upon cognitive processes to explain compliance with information security policies, while others have focused solely on factors related to non-compliance behavior, one of which is affect. Despite the findings from these studies, there is a dearth of extant literature that …

Feature Selection On Permissions, Intents And Apis For Android Malware Detection, Fred Guyton

CCAC Theses and Dissertations

Malicious applications pose an enormous security threat to mobile computing devices. Currently 85% of all smartphones run Android, Google’s open-source operating system, making that platform the primary threat vector for malware attacks. Android is a platform that hosts roughly 99% of known malware to date, and is the focus of most research efforts in mobile malware detection due to its open source nature. One of the main tools used in this effort is supervised machine learning. While a decade of work has made a lot of progress in detection accuracy, there is an obstacle that each stream of research is …

The Construction And Internal Validation Of A Model For The Effective Collaboration Of Distributed Agile Teams, Ernesto Custodio

CCAC Theses and Dissertations

Agile approaches to software development have increased steadily over the past decade. Agile processes emphasize iterative and collaborative discovery of requirements and solutions executed by self-organizing, cross-functional teams. Software development using distributed teams, including distributed sub-teams, fully dispersed teams, and partially dispersed teams, has also increased due to benefits such as access to global talent and faster delivery, among others.

However, most Agile approaches, models, and frameworks only address the needs of colocated teams. Distributed teams come with unique challenges when it comes to effective collaboration. The goal was to construct and validate internally a model for the effective collaboration …

Neural Network Variations For Time Series Forecasting, David Ason

CCAC Theses and Dissertations

Time series forecasting is an area of research within the discipline of machine learning. The ARIMA model is a well-known approach to this challenge. However, simple models such as ARIMA do not take into consideration complex relationships within the data and quite often fail to produce a satisfactory forecast. Neural networks have been presented in previous works as an alternative. Neural networks are able to capture non-linear relationships within the data and can deliver an improved forecast when compared to ARIMA models.

This dissertation takes neural network variations and applies them to a group of time series datasets found in …

Improving Employees’ Compliance With Password Policies, Enas Albataineh

CCAC Theses and Dissertations

Employees’ lack of compliance with password policies increases password susceptibility, which leads to financial damages to the organizations as a result of information disclosure, fraud, and unauthorized transactions. However, few studies have examined what motivates employees to comply with password policies.

The purpose of this quantitative cross-sectional study was to examine what factors influence employees’ compliance with password policies. A theoretical model was developed based on Protection Motivation Theory (PMT), General Deterrence Theory (GDT), Theory of Reasoned Action (TRA), and Psychological Ownership Theory to explain employees’ compliance with password policies.

A non-probability convenience sample was employed. The sample consisted of …

Enterprise Social Network Systems Implementation Model For Knowledge Sharing Among Supply Chain It Professionals, Edgardo Luis Velez-Mandes

CCAC Theses and Dissertations

With the increased use of social network technologies in organizational environments, there is a need to understand how these technologies facilitate organizational knowledge management, particularly knowledge sharing. Prior research has focused on the relationship between knowledge management and enterprise social networking systems (ESNS), but little research has been conducted relating to how organizations implement and use ESNS for knowledge sharing. The goal was to construct and validate internally a model that offers guidance for the successful implementation and use of ESNS for knowledge sharing and building successful virtual communities of practice (vCoPs) among IT supply chain professionals in a healthcare …

The Empirical Study Of The Factors That Influence Threat Avoidance Behavior In Ransomware Security Incidents, Heriberto Aurelio Acosta Maestre

CCAC Theses and Dissertations

Ransomware security incidents have become one of the biggest threats to general computer users who are oblivious to the ease of infection, severity, and cost of the damage it causes. University networks and their students are susceptible to ransomware security incidents. College students have vast technical skills and knowledge, however they risk ransomware security incidents because of their lack of mitigating actions to the threats and the belief that it would not happen to them. Interaction with peers may play a part in college students’ perception of the threats and behavior to secure their computers. Identifying what influences students’ threat …

The Role Of Ammonia In Atmospheric New Particle Formation And Implications For Cloud Condensation Nuclei, Arshad Arjunan Nair

Legacy Theses & Dissertations (2009 - 2024)

Atmospheric ammonia has received recent attention due to (a) its increasing trend across various regions of the globe; (b) the associated direct and indirect (through PM2.5) effects on human health, the ecosystem, and climate; and (c) recent evidence of its role in significantly enhancing atmospheric new particle formation (NPF or nucleation) rates. The mechanisms behind nucleation in the atmosphere are not fully understood, although over the last decade there have been significant developments in our understanding. This dissertation aims at improving our understanding of atmospheric ammonia in the atmosphere, its spatiotemporal variability, its role in atmospheric new particle formation, and …

Learning Graphs For Object Tracking And Counting, Shengkun Li

Legacy Theses & Dissertations (2009 - 2024)

As important problems in computer vision, object tracking and counting attract increasing amounts of attention in recent years due to its wide range of applications, such as video surveillance, human- computer interaction, smart city. Despite much progress has been made in object tracking and counting with the arriving of deep neural networks (DNN), there still remains much room for improvement to satisfy the real-world applications.

Collateral Data Quality Challenges Of Iot Sensor-Generated Data, Richard Allen Herrin

Graduate Student Publications

Thousands of academic articles have been written about the various facets of the Internet of Things (IoT). Added to those are books of multiple flavors, conference proceedings, and a host of web-based content authored by a diverse cast of IoT community constituents. While there are many examples of successful IoT application solutions, participating technologies and how best to use them, are still relatively immature. These solutions are complex, geographically diverse, incorporate a broad spectrum of ever-evolving technologies that allow organizations to gather new data, create new value and do new things they haven’t been able to do effectively before.

Despite …

ระบบวางบิลหลายแพลตฟอร์มอัจฉริยะสําหรับร้านซูชิสายพาน, พัชริยา ปิยะอารมณ์รัตน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

ร้านซูชิสายพานเป็นที่นิยมทั่วโลก เนื่องจากราคาถูกกว่าร้านซูชิที่มีบริการ รวมทั้งรายการอาหารมีความหลากหลาย เพื่อประหยัดเวลาในการรับประทานอาหารธุรกิจซูชิสายพานจะแสดงราคาอาหารจากสีของจานรองที่แตกต่างกัน ขึ้นอยู่กับราคา การคำนวณการชำระบิลสามารถทำได้โดยการนับจำนวนจานแต่ละประเภท การตรวจจับวัตถุพัฒนาโดยใช้ปัญญาประดิษฐ์ เพื่อตรวจจับเพื่อลดระยะเวลาในการนับจานเพื่อคำนวณการชำระบิลแบบเดิม ระบบวางบิลอัจฉริยะพัฒนาโดยใช้ฟลัตเตอร์ สามารถทำงานได้บนหลายแพลตฟอร์ม โดยผู้ใช้สามารถถ่ายรูปกองจานซูชิเพื่อใช้เป็นภาพอินพุตเพื่อให้แบบจำลองที่พัฒนาด้วยโยโลวีสี่จำแนกจานสีต่างๆ ในวิทยานิพนธ์นี้พัฒนาในส่วนของการปรับปรุงภาพและแอปพลิเคชัน เนื่องจากระบบสามารถทำงานได้บนระบบปฏิบัติการไอโอเอส และแอนดรอยด์ เทคนิคการถ่ายโอนสีด้วยช่วงสีเอลเอบี คอนทราสต์ลิมิตอเดปทีฟอีควอไลเซชัน และเอสอาร์-ซีเอ็นเอ็น ถูกนำมาใช้เพื่อปรับปรุงคุณภาพของภาพ ผลการทดลองรายงานด้วยการตรวจจับวัตถุสำเร็จด้วยค่าความมั่นในการตรวจจับวัตถุที่สูงขึ้น