Computer Sciences Commons^™

Technology And Homelessness: How Website Design And Blockchain Technology Could Impact The Unhoused, Casey Pratt

Undergraduate Theses, Capstones, and Recitals

Although technology could be used to combat inequality, it is instead increasing it. This paper discusses how the unhoused population suffers at the hand of technological inequality despite being relatively offline. It presents theories on how this would change if we reapproached how technology is used to assist the unhoused. It suggests implementing blockchain as a resource as well as modifying the websites built to assist in accessing benefits. Employees at shelters are interviewed for this paper about their experiences with using digital resources to rehouse and restabilize the vulnerable. They are asked how the sites can be improved for …

Evaluating The Effect Of Domain-Specific Large Language Models On Question And Response, Phillip D. Crippen

Electronic Theses and Dissertations

Large Language Models have emerged to great fanfare in the Information Technology market. Business and Information Technology leaders are currently exploring ways to apply these models to assist their organizations in executing business processes and generating innovation. Software vendors, consultants, and academics promote various approaches to making Large Language Models work effectively for business. However, little academic literature is available today that quantifies the degree of improvement possible with these domain-specific approaches over the standard capabilities of generalized Large Language Models.

The study seeks to quantify the benefits of one approach, Retrieval Augmented Generation. The study uses a collection of …

Mapping Mental Models Through An Improved Method For Identifying Causal Structures In Qualitative Data, Erin S. Kenzie, Wayne Wakeland, Antonie Jetter, Kristen Hassmiller Lich, Mellodie Seater, Melinda M. Davis

Complex Systems Faculty Publications and Presentations

Qualitative data are commonly used in the development of system dynamicsmodels, but methods for systematically identifying causal structures in qualita-tive data have not been widely established. This article presents a modifiedprocess for identifying causal structures (e.g., feedback loops) that are commu-nicated implicitly or explicitly and utilizes software to make coding, tracking,and model rendering more efficient. This approach draws from existingmethods, system dynamics best practice, and qualitative data analysis tech-niques. Steps of this method are presented along with a description of causalstructures for an audience new to system dynamics. The method is applied to aset of interviews describing mental models of …

The Institutional Challenges Of A Quantified Self Study: An Attempt To Ascertain How Data Collected From A Mobile Device Can Be An Indicator Of Personal Mental Health Over Time, Julian Lazaras

University Honors Theses

The adoption of an application of new technology always comes with a bias, this is never more true for the case of human behavioral analytics within higher education. While movements such as the quantified self movement make strides to reinterpret the realm of data analytics, psychology, and computer science, there are inevitably limitations to the adoption and application of such approaches within the standard realm of research. Herein is presented a case where an effort to evaluate the prospect of use of mobile phone data as secondary indicators of personal mental health through the lens of data analysis was put …

Cards With Class: Formalizing A Simplified Collectible Card Game, Dan Ha

University Honors Theses

Collectible card games (CCGs) have been a wildly popular game genre since the release of Wizards of the Coast's Magic: The Gathering. These games revolve around their thousands of cards and the hundreds of thousands of interactions they can create with their many effects. For designers, it is an incredibly demanding task to ensure that every single card works properly and that each card's text unambiguously conveys its intended behavior in all cases. The task only grows more difficult over time as the number of cards in the game grows and card effects become more complex or experimental. If the …

Heterogeneous Resources In Infrastructures Of The Edge Network Paradigm: A Comprehensive Review, Qusay S. Alsaffar, Leila Ben Ayed

Karbala International Journal of Modern Science

The late 1990s saw the rise of the edge computing network paradigm, as well as an increase in the number of IoT de-vices. This concept is viewed as a link between cloud servers and end-devices, bringing processing and storage re-sources closer to clients. As a result of its low latency and high performance, researchers and developers have expressed interest in it. However, this paradigm confronts a number of obstacles and restrictions, including restricted and hetero-geneous resources at network edges. In this paper, we provide a detailed review of heterogeneous resources in edge network infrastructures using a three-dimensional method. These three …

Classification And Removal Of Hazy Images Based On A Transmission Fusion Strategy Using The Alexnet Network, Roa'a M. Al-Airaji, Haider Th. Salim Alrikabi, Rula Kamil

Karbala International Journal of Modern Science

Outdoor images are used in many domains, such as surveillance, geospatial mapping, and autonomous vehicles. The occurrence of noise in outdoor images is a widely observed phenomenon. They are primarily attributed to extreme natural and manufactured meteorological conditions, such as haze, smog, and fog. In autonomous vehicle navigation, recovering the ground truth image is essential, enabling the system to make more informed decisions. Accurate air-light and transmission map calculation is vital in recovering the ground truth image. An efficient approach for image dehazing that utilizes the mean channel prior (MCP) is presented in this paper to estimate the transmission map, …

Data Visualization, Licensing, And Other Generative Ai Initiatives At Minnesota State University Mankato, Evan Rusch, Nat Gustafson-Sundell

Library Services Publications

At Minnesota State University Mankato (MNSU), we’ve undertaken several experiments and initiatives focused on Generative Artificial Intelligence. At the start of the fall semester, we collaborated with university Information Technology Services to present a professional development session for returning faculty through the MNSU Center for Excellence in Teaching & Learning on “5 Tips for Teaching with AI.” We also presented to librarians across the regional consortium, Minitex, on “The Library & Generative AI.” This presentation included several demonstrations. It was offered as an introduction to Generative AI focused on topics most relevant to librarians, including information literacy, as well as …

Federated Learning Based Autoencoder Ensemble System For Malware Detection On Internet Of Things Devices, Steven Edward Arroyo

Theses and Dissertations

New technologies are being introduced at a rate faster than ever before and smaller in size. Due to the size of these devices, security is often difficult to implement. The existing solution is a firewall-segmented “IoT Network” that only limits the effect of these infected devices on other parts of the network. We propose a lightweight unsupervised hybrid-cloud ensemble anomaly detection system for malware detection. We perform transfer learning using a generalized model trained on multiple IoT device sources to learn network traffic on new devices with minimal computational resources. We further extend our proposed system to utilize federated learning …

Methionine Sulfoxide Speciation In Mouse Hippocampus Revealed By Global Proteomics Exhibits Age- And Alzheimer’S Disease-Dependent Changes Targeted To Mitochondrial And Glycolytic Pathways, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Mengzhen Li, Serhan Yılmaz, Rihua Wang, Xin Qi, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications

Methionine oxidation to the sulfoxide form (MSox) is a poorly understood post-translational modification of proteins associated with non-specific chemical oxidation from reactive oxygen species (ROS), whose chemistries are linked to various disease pathologies, including neurodegeneration. Emerging evidence shows MSox site occupancy is, in some cases, under enzymatic regulatory control, mediating cellular signaling, including phosphorylation and/or calcium signaling, and raising questions as to the speciation and functional nature of MSox across the proteome. The 5XFAD lineage of the C57BL/6 mouse has well-defined Alzheimer’s and aging states. Using this model, we analyzed age-, sex-, and disease-dependent MSox speciation in the mouse hippocampus. …

High-Performance Computing In Next-Generation Sequencing Read Alignment, Minh H. Pham

USF Tampa Graduate Theses and Dissertations

Advancements in Next-Generation Sequencing (NGS) have dramatically reduced the cost and increased the speed of DNA sequencing. However, this rapid influx of data necessitates efficient and robust analysis tools, particularly for the complex task of aligning short NGS reads to reference genomes such as the human genome. We explore groundbreaking computational strategies and hardware acceleration to optimize this critical alignment process. This dissertation is structured around three innovative studies. First, we introduce a novel approach to dynamic memory allocation tailored for massively parallel systems, particularly Graphical Processing Units (GPUs), to support NGS alignment and other applications. Unlike traditional memory allocators …

Methionine Sulfoxide Speciation In Mouse Hippocampus Revealed By Global Proteomics Exhibits Age- And Alzheimer’S Disease-Dependent Changes Targeted To Mitochondrial And Glycolytic Pathways, Filipa Blasco Tavares Pereira Lopes, Daniela Schlatzer, Mengzhen Li, Serhan Yılmaz, Rihua Wang, Xin Qi, Marzieh Ayati, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications

Methionine oxidation to the sulfoxide form (MSox) is a poorly understood post-translational modification of proteins associated with non-specific chemical oxidation from reactive oxygen species (ROS), whose chemistries are linked to various disease pathologies, including neurodegeneration. Emerging evidence shows MSox site occupancy is, in some cases, under enzymatic regulatory control, mediating cellular signaling, including phosphorylation and/or calcium signaling, and raising questions as to the speciation and functional nature of MSox across the proteome. The 5XFAD lineage of the C57BL/6 mouse has well-defined Alzheimer’s and aging states. Using this model, we analyzed age-, sex-, and disease-dependent MSox speciation in the mouse hippocampus. …

Securing The Inbox: Advancing Cyber Resilience With Fine-Tuned Bert, Fatima Rashed Al Saedi

Thesis/ Dissertation Defenses

In recent years, phishing attacks have persisted as a widespread threat in the contemporary digital environment, presenting substantial risks to individuals and organizations. Cybercriminals are devising increasingly sophisticated strategies to deceive users through malicious emails. In response to this challenge, this research focuses on developing a new tool for detecting phishing emails utilizing the BERT algorithm. The tool aims to enhance email security by accurately identifying deceptive emails and protecting users from potential cyber threats. The primary objective of this study is to investigate how leveraging the BERT algorithm can improve the detection of phishing emails compared to traditional methods. …

Machine Learning Multimodal Framework For Fake News Detection And Mitigation, Nada A. Gaballah

Theses and Dissertations

Social media has become our new reality, people wake up every morning and the first thing they do before getting out of bed, is check their social media. Nowadays, people rarely read newspapers, they even rarely watch TV news or listen to radio broadcasts. In recent years, we have witnessed lots of fake news roaming social media every second, with people simply believing it and spreading it even more without checking the credibility of this news. This fake news affected several domains like what happened in the US election in 2016 and again in 2020, the false information about Covid-19 …

The Robot On The Hill, James Ryan

College of Computing and Digital Media Dissertations

“The Robot on the Hill” is a rogue-like autobattler that procedurally models the state of the individual in the information age. The game abruptly transitions between diverse framings - a hill, a bedroom, a pond, a chessboard, the void - in order to highlight the disjointedness that is present in the informationalizing of self and reality. It dialogues with Byung Chul Han and Heidegger to portray what Han describes as a ‘narrative crisis’ in modernity and the devaluation of experience. When the value of experience diminishes and disintegrates, “all that is left is bare life, a kind of survival.” …

Case Studies For Energy Efficient Machine Learning Inference Acceleration, Recep Erol

Theses and Dissertations

The advancements in machine learning, deep learning and AI have yielded remarkable tools and innovations, but certain groups face barriers preventing their utilization of these technologies. This research identifies and categorizes these barriers, focusing on three distinct groups: those lacking computational power, seeking to deploy models across multiple devices, and struggling with optimization challenges in high-performance computing centers. The study highlights the disconnect between academia's proposed solutions and their practical integration within industries and research centers, emphasizing the lack of convenience and integration among existing tools. To bridge this gap, this research offers a multifaceted approach. Firstly, it introduces publicly …

Achieving Domain-Independent Certified Robustness Via Knowledge Continuity, Alan Wenyuan Sun

Computer Science Senior Theses

We present knowledge continuity, a novel definition inspired by Lipschitz continuity which aims to certify the robustness of neural networks across input domains (such as continuous and discrete domains in vision and language, respectively). Most existing approaches that seek to certify robustness, especially Lipschitz continuity, lie within the continuous domain with norm and distribution-dependent guarantees. In contrast, our proposed definition yields certification guarantees that depend only on the loss function and the intermediate learned metric spaces of the neural network. These bounds are independent of domain modality, norms, and distribution. We further demonstrate that the expressiveness of a model …

Implementing Selective Signature Scanning To Optimize Malware Detection, Lucas Gray Wilbur

Computer Science Senior Theses

Signature scanning is one of the oldest types of malware detection, and it remains an essential lightweight detection method for many antivirus programs. However, signature scanning has unavoidable limitations, including an inevitably increasing runtime as malware signature databases continually expand. In this paper, we discuss the current state of signature scanning, including usage of the open-source signature scanning tool YARA. We test Zemlyanaya et al’s assertion that scanning only the beginning and end of files can reduce the runtime cost of signature database expansion — while maintaining a high level of accuracy — and find it inaccurate in the case …

Evading Antivirus Detection By Abusing File Type Identification, Chavin Udomwongsa

Computer Science Senior Theses

File type identification is a vital step in automated file processing, especially in the realm of malware detection. The challenges with file type identification and evasion techniques that take advantage of them were pointed out over a decade ago. We show that this remains the case: file type identification implementations are still fragile, especially for files with ambiguous file types. We present a novel antivirus bypass technique via crafted tar archives that evades all detection from VirusTotal and numerous antiviruses: BitDefender, F-Secure, Kaspersky, Panda Dome, Trend Micro, Quick Heal, IKARUS, Avira. These crafted files evade detection by tricking file type …

Curating Familiarity Within The Unfamiliar: Exploring Non-Native Mobile App Experiences To Create Cross-Cultural Design Frameworks, Hanna Hong

Computer Science Senior Theses

Global mobility and markets are expanding, and as a result, countries are becoming less and less monocultural. With multiple cultural affinity groups to cater towards, companies often will deploy different versions of a website or app based on the country a user is accessing it from. This strategy of catering to geographic location results in a lack of accommodation for people living within a culture that is different from their native one. In order to increase accessibility and equal ease-of-use for all audiences, designers should understand and work towards the needs of a multicultural user base. This study investigates how …

Designing Of Human Serum Albumin Nanoparticles For Drug Delivery: A Potential Use Of Anticancer Treatment, Ali Al-Ani, Rasha Alsahlanee

Karbala International Journal of Modern Science

Human serum albumin (HSA) nanoparticles have been widely used as versatile drug delivery systems for improving the efficiency and pharmaceutical properties of drugs. The present study aimed to design HSA nanoparticle encapsulated with the hydrophobic anticancer pyridine derivative (2-((2-([1,1'-biphenyl]-4-yl)imidazo[1,2-a]pyrimidin-3-yl)methylene)hydrazine-1-carbothioamide (BIPHC)). The synthesis of HSA-BIPHC nanoparticles was achieved using a desolvation process. Atomic force microscopy (AFM) analysis showed the average size of HSA-BIPHC nanoparticles was 80.21 nm. The percentages of entrapment efficacy, loading capacity and production yield were 98.11%, 9.77% and 91.29%, respectively. An In vitro release study revealed that HSA-BIPHC nanoparticles displayed fast dissolution at pH 7.4 compared to pH …

Modified Toulmin's Argumentation Model Based On Prior Experiences, Ali Hadi Hasan, Mohamad Ab. Saleh, Ahmed T. Sadiq

Karbala International Journal of Modern Science

Our work focuses on the usefulness of previously stored correct extracted results, which form a sort of stored knowledge got from previous experiences, from enhancing Toulmin's argument model that deals with drug conflict problems in therapeutic diagnostics. New patients are entered using friendly user interface to store in files and then they are matched with the records of previous results, patients’ symptoms and histories datasets which also contain the correct best drugs extracted results. If the new entered record of a patient is matching with any previous record then the correct result of drug will be found immediately and displayed. …

Flying Base Station Channel Capacity Limits: Dependent On Stationary Base Station And Independent Of Positioning, Sang-Yoon Chang, Kyungmin Park, Jonghyun Kim, Jinoh Kim

Faculty Publications

Flying base stations, also known as aerial base stations, provide wireless connectivity to the user and utilize their aerial mobility to improve communication performance. Flying base stations depend on traditional stationary terrestrial base stations for connectivity, as stationary base stations act as the gateway to the backhaul/cloud via a wired connection. We introduce the flying base station channel capacity to build on the Shannon channel capacity, which quantifies the upper-bound limit of the rate at which information can be reliably transmitted using the communication channel regardless of the modulation and coding techniques used. The flying base station’s channel capacity assumes …

Cellmarkerpipe: Cell Marker Identification And Evaluation Pipeline In Single Cell Transcriptomes, Yinglu Jia, Pengchong Ma, Qiuming Yao

School of Computing: Faculty Publications

Assessing marker genes from all cell clusters can be time-consuming and lack systematic strategy. Streamlining this process through a unified computational platform that automates identification and benchmarking will greatly enhance efficiency and ensure a fair evaluation. We therefore developed a novel computational platform, cellMarkerPipe (https:// github. com/ yao- labor atory/ cellM arker Pipe), for automated cell-type specific marker gene identification from scRNA-seq data, coupled with comprehensive evaluation schema. CellMarkerPipe adaptively wraps around a collection of commonly used and state-of-the-art tools, including Seurat, COSG, SC3, SCMarker, COMET, and scGeneFit. From rigorously testing across diverse samples, we ascertain SCMarker’s overall reliable performance …

Artificial Intelligence As The Next Front In The Class War, Christopher Hill

Dissertations and Theses

For many years, artificial intelligence has been confined to the realm of science fiction, and while the technology has been in development, predicting the effects AI will have on our society has been a challenging endeavor. The release of ChatGPT in 2022, the subsequent mass adoption of the AI chatbot, and the response by other private firms in the field announced AI's permanent entrance into the public sphere. These recent strides made in the field of artificial intelligence reveal that the pace of technological development has outstripped the rate at which we are able to politically examine and understand these …

Resource-Constrained 2d Scene Recovery With Single-Photon Cameras, Daphne Ariadne Kurzenhauser

Dissertations and Theses

The modern world is built of images. However, in our goal to photograph and replicate what the human eye is capable of seeing, we are throttled by the restrictions of conventional imaging sensors in high- and low-illumination environments. Single-photon cameras (SPCs) have recently emerged as a promising alternative to conventional camera sensors for capturing images in challenging conditions such as high-dynamic range and fast scene motion. Compared to traditional CMOS cameras, SPCs exploit the arrival of individual photons rather than using an aggregate photon count to compute the brightness of pixels. However, SPCs are extremely resource-intensive, making them inconvenient for …

A Meta-Ensemble Predictive Model For The Risk Of Lung Cancer, Sideeqoh Oluwaseun Olawale-Shosanya, Olayinka Olufunmilayo Olusanya, Adeyemi Omotayo Joseph, Kabir Oluwatobi Idowu, Oyelade Babatunde Eriwa, Adedeji Oladimeji Adebare, Morufat Adebola Usman

Al-Bahir

The lungs play a vital role in supplying oxygen to every cell, filtering air to prevent harmful substances, and supporting defense mechanisms. However, they remain susceptible to the risk of diseases such as infections, inflammation, and cancer that affect the lungs. Meta-ensemble techniques are prominent methods used in machine learning to enhance the accuracy of classifier learning systems in making predictions. This work proposes a robust predictive model using a meta-ensemble method to identify high-risk individuals with lung cancer, thereby taking early action to prevent long-term problems benchmarked upon the Kaggle Machine Learning practitioners' Lung Cancer Dataset. Three machine learning …

Ai's Ethical Frontier

DePaul Magazine

Artificial intelligence (AI) is affecting every aspect of the university and society. Experts from across DePaul share their insights on artificial intelligence's advantages and pitfalls. Learn about DePaul's new Artificial Intelligence Institute and research projects that use AI for societal benefit.

What's In A Social Computing Course: Analyzing Computer And Information Science Syllabi, C. G. Delcourt, Sukrit Venkatagiri, E. Chandrasekharan

Computer Science Faculty Works

Social computing systems—such as social media and e-commerce platforms as well as search engines and collaboration software—not only drive vast economic value and societal impact, but are also becoming prominent topics in policy discourse. Although social technology companies heavily recruit students from Computer and Information Science (CS and IS) programs, and social computing is a well-established scholarly field within human-computer interaction (HCI) focused on the social interactions between people mediated through computational systems, little is known about social computing education. Consequently, in this paper we analyzed 25 undergraduate and graduate level courses titled “social computing.” First, as a fast-paced discipline …

Machines Of The Absurd: Leveraging Generative Ai For Creativity, Humor, And Playfulness, Tyler Sanders

College of Computing and Digital Media Dissertations

Machines of The Absurd is a collection of four projects exploring how generative AI can be leveraged for creativity, humor and playfulness.

1. neverOS — A node-based visual playground for interacting with large language models.

2. Other Calc — An iOS app with a calculator interface, where players can “calculate” text instead of numbers.

3. What Must Burn — An experiment where players type in text that can be dragged into a campfire to produce contextually appropriate sound effects.

4. Jazz vs Waffles — A turn-based comedy game, where players battle anything they type in.

Together, these projects make the …