Digital Commons Network^™

Establishing Metrics To Encourage Broader Use Of Atomic Requirements – A Call For Exchange And Experimentation, William L. Honig

Computer Science: Faculty Publications and Other Works

There are seemingly many advantages to being able to identify, document, test, and trace single or “atomic” requirements during system development and maintenance. Ongoing work with Agile development has focused on “user stories” that can capture individual features for implementation. However, it is still difficult to evaluate the quality of such requirements and teaching their creation is difficult.

Based on a working definition of atomic requirement, this paper proposes a set of metrics for their evaluation. Ten metrics designed to measure atomic requirements are presented here: five used on individual requirements statements and five applied to a requirements document or …

Singleadv: Single-Class Target-Specific Attack Against Interpretable Deep Learning Systems, Eldor Abdukhamidov, Mohammed Abuhamad, George K. Thiruvathukal, Hyoungshick Kim, Tamer Abuhmed

Computer Science: Faculty Publications and Other Works

In this paper, we present a novel Single-class target-specific Adversarial attack called SingleADV. The goal of SingleADV is to generate a universal perturbation that deceives the target model into confusing a specific category of objects with a target category while ensuring highly relevant and accurate interpretations. The universal perturbation is stochastically and iteratively optimized by minimizing the adversarial loss that is designed to consider both the classifier and interpreter costs in targeted and non-targeted categories. In this optimization framework, ruled by the first- and second-moment estimations, the desired loss surface promotes high confidence and interpretation score of adversarial samples. By …

Synthetic Realities And Artificial Intelligence-Generated Contents, Daniel Moreira, Sebastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Welcome to the IEEE Security & Privacy Special Issue on Synthetic Realities and Artificial Intelligence-Generated Contents! In this edition, we delve into the topic of synthetic realities, where generative artificial intelligence (GAI) is revolutionizing the construction of narratives, blurring the boundaries between fact and fiction, for the good and the bad. Indeed, content created or enabled by GAI spans a wide spectrum of usage and intentions, from fostering positive experiences, such as entertainment, training, and education, to more questionable utilization, such as deception, propaganda, and manipulation.

A Computer Vision Solution To Cross-Cultural Food Image Classification And Nutrition Logging​, Rohan Sethi, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

The US is a culturally and ethnically diverse country, and with this diversity comes a myriad of cuisines and eating habits that expand well beyond that of western culture. Each of these meals have their own good and bad effects when it comes to the nutritional value and its potential impact on human health. Thus, there is a greater need for people to be able to access the nutritional profile of their diverse daily meals and better manage their health. A revolutionary solution to democratize food image classification and nutritional logging is using deep learning to extract that information from …

Terry Riley's "In C" For Mobile Ensemble, David B. Wetzel, Griffin Moe, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

This workshop presents a mobile-friendly Web Audio application for a “technology ensemble play-along” of Terry Riley’s 1964 composition In C. Attendees will join in a reading of In C using available web-enabled devices as musical instruments. We hope to demonstrate an accessible music-technology experience that relies on face-to-face interaction within a shared space. In this all-electronic implementation, no special musical or technical expertise is required.

Accepted for presentation and publication at WAC 2024.

Artificial Intelligence And/Or Machine Learning (Ai &| Ml), George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

These slides are from an invited panel presentation at my home institution, Loyola University Chicago, organized by the Loyola University Chicago Retiree Association (LUCRA). I was asked to give a broad historical overview of AI and ML and speak about its societal impacts.

"The Loyola University Chicago Retiree Association embraces the Vision of Loyola University Chicago and will assist students, faculty, and administrators as they strive to serve humanity. The group values freedom of inquiry, the pursuit of truth, and care of others and embraces a commitment to excellence, service that promotes social justice, values based leadership, and global awareness."

Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

Prior research has demonstrated relationships between personality traits of social media users and the language used in their posts. Few studies have examined whether there are relationships between personality traits of users and how they use emojis in their social media posts. Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, which depict faces with expressions, objects, animals, and activities. We conducted a study with two samples (n = 76 and n = 245) in which we examined how emoji use on X (formerly Twitter) related to users’ personality traits and language use …

Biochemical And Structural Analysis Of The Bacterial Enzyme Succinyl-Diaminopimelate Desuccinylase (Dape) From Acinetobacter Baumannii, Emma H. Kelley, George Minasov, Katherine Konczak, Ludmilla Shuvalova, Joseph S. Brunzelle, Shantanu Shukla, Megan Beulke, Teerana Thabthimthong, Ken W. Olsen, Nicole L. Inniss, Karla Jf Satchell, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

There is an urgent need for new antibiotics given the rise of antibiotic resistance, and succinyl-diaminopimelate desuccinylase (DapE, E.C. 3.5.1.18) has emerged as a promising bacterial enzyme target. DapE from Haemophilus influenzae (HiDapE) has been studied and inhibitors identified, but it is essential to explore DapE from different species to assess selective versus broad-spectrum therapeutics. We have determined the structure of DapE from the ESKAPE pathogen Acinetobacter baumannii (AbDapE) and studied inhibition by known inhibitors of HiDapE. AbDapE is inhibited by captopril and sulfate comparable to HiDapE, but AbDapE was not significantly …

Cyclobutanone Inhibitors Of Diaminopimelate Desuccinylase (Dape) As Potential New Antibiotics, Thahani Shifna Habeeb Mohammad, Emma H. Kelley, Cory T. Reidl Dr., Katherine Konczak, Megan Beulke, Janielle Javier, Ken W. Olsen, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

Based on our previous success in using cyclobutanone derivatives as enzyme inhibitors, we have designed and prepared a 37-member library of α-aminocyclobutanone amides and sulfonamides, screened for inhibition of the bacterial enzyme diaminopimelate desuccinylase (DapE), which is a promising antibiotic target, and identified several inhibitors with micromolar inhibitory potency. Molecular docking suggests binding of the deprotonated hydrate of the strained cyclobutanone, and thermal shift analysis with the most potent inhibitor (3y, IC50 = 23.1 µM) enabled determination of a Ki value of 10.2 +/− 0.26 µM and observed two separate Tm values for H. influenzae DapE (HiDapE).

Conventions, Definitions, Identities, And Other Useful Formulae, Robert A. Mcnees Iv

Physics: Faculty Publications and Other Works

As the name suggests, these notes contain a summary of important conventions, definitions, identities, and various formulas that I often refer to. They may prove useful for researchers working in General Relativity, Supergravity, String Theory, Cosmology, and related areas.

Actionpoint: An App To Combat Cyberbullying By Strengthening Parent-Teen Relationships, Maddie Juarez, Natali Barragan, Deborah Hall, George K. Thiruvathukal, Yasin Silva

Computer Science: Faculty Publications and Other Works

No abstract provided.

Neutrino Self-Interactions: A White Paper, Jeffrey M. Berryman, Nikita Blinov, Vedran Brdar, Thejs Brinckmann, Mauricio Bustamante, Francis-Yan Cyr-Racine, Anirban Das, André De Gouvêa, Peter B. Denton, P.S. Bhupal Dev, Bhaskar Dutta, Ivan Esteban, Damiano Fiorillo, Martina Gerbino, Subhajit Ghosh, Tathagata Ghosh, Evan Grohs, Tao Han, Steen Hannestad, Matheus Hostert, Patrick Huber, Jeffrey Hyde, Kevin J. Kelly, Felix Kling, Zhen Liu, Massimiliano Lattanzi, Marilena Loverde, Sujata Pandey, Ninetta Saviano, Manibrata Sen, Ian M. Shoemaker, Walter Tangarife, Yongchao Zhang, Yue Zhang

Physics: Faculty Publications and Other Works

Neutrinos are the Standard Model (SM) particles which we understand the least, often due to how weakly they interact with the other SM particles. Beyond this, very little is known about interactions among the neutrinos, i.e., their self-interactions. The SM predicts neutrino self-interactions at a level beyond any current experimental capabilities, leaving open the possibility for beyond-the-SM interactions across many energy scales. In this white paper, we review the current knowledge of neutrino self-interactions from a vast array of probes, from cosmology, to astrophysics, to the laboratory. We also discuss theoretical motivations for such self-interactions, including neutrino masses and possible …

The Age Of Synthetic Realities: Challenges And Opportunities, João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive. In this paper, we delve into the concept of synthetic realities and their implications for Digital Forensics and society at large within the rapidly advancing field of AI. We highlight the crucial need for the development of forensic techniques capable of identifying harmful synthetic creations and distinguishing them from reality. This is especially important in scenarios involving the creation and dissemination of fake news, …

Optimized Uncertainty Estimation For Vision Transformers: Enhancing Adversarial Robustness And Performance Using Selective Classification, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep Learning models often exhibit undue confidence when encountering out-of-distribution (OOD) inputs, misclassifying with high confidence. The ideal outcome, in these cases, would be an "I do not know" verdict. We enhance the trustworthiness of our models through selective classification, allowing the model to abstain from making predictions when facing uncertainty. Rather than a singular prediction, the model offers a prediction distribution, enabling users to gauge the model’s trustworthiness and determine the need for human intervention. We assess uncertainty in two baseline models: a Convolutional Neural Network (CNN) and a Vision Transformer (ViT). By leveraging these uncertainty values, we minimize …

Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep Learning (DL) methods have shown substantial efficacy in computer vision (CV) and natural language processing (NLP). Despite their proficiency, the inconsistency in input data distributions can compromise prediction reliability. This study mitigates this issue by introducing uncertainty evaluations in DL models, thereby enhancing dependability through a distribution of predictions. Our focus lies on the Vision Transformer (ViT), a DL model that harmonizes both local and global behavior. We conduct extensive experiments on the ImageNet-1K dataset, a vast resource with over a million images across 1,000 categories. ViTs, while competitive, are vulnerable to adversarial attacks, making uncertainty estimation crucial for …

Peatmoss: Mining Pre-Trained Models In Open-Source Software, Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajiv Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis

Computer Science: Faculty Publications and Other Works

Developing and training deep learning models is expensive, so software engineers have begun to reuse pre-trained deep learning models (PTMs) and fine-tune them for downstream tasks. Despite the widespread use of PTMs, we know little about the corresponding software engineering behaviors and challenges. To enable the study of software engineering with PTMs, we present the PeaTMOSS dataset: Pre-Trained Models in Open-Source Software. PeaTMOSS has three parts: a snapshot of (1) 281,638 PTMs, (2) 27,270 open-source software repositories that use PTMs, and (3) a mapping between PTMs and the projects that use them. We challenge PeaTMOSS miners to discover software engineering …

Fermion Pair Radiation From Accelerating Classical Systems, Margarita Gavrilova, Mitrajyoti Ghosh, Yuval Grossman, Walter Tangarife, Tien-Hsueh Tsai

Physics: Faculty Publications and Other Works

Accelerating classical systems that couple to a fermion-antifermion pair at the microscopic level can radiate pairs of fermions and lose energy in the process. In this work, we derive the generalization of the Larmor formula for fermion pair radiation. We focus on the case of a point-like classical source in an elliptical orbit that emits fermions through vector and scalar mediators. Ultra-light fermion emission from such systems becomes relevant when the mass of the mediator is larger than the frequency of the periodic motion. This enables us to probe regions of the parameter space that are inaccessible in on-shell bosonic …

Finite Charges From The Bulk Action, Robert Mcnees, Céline Zwikel

Physics: Faculty Publications and Other Works

Constructing charges in the covariant phase space formalism often leads to formally divergent expressions, even when the fields satisfy physically acceptable fall-off conditions. These expressions can be rendered finite by corner ambiguities in the definition of the presymplectic potential, which in some cases may be motivated by arguments involving boundary Lagrangians. We show that the necessary corner terms are already present in the variation of the bulk action and can be extracted in a straightforward way. Once these corner terms are included in the presymplectic potential, charges derived from an associated codimension-2 form are automatically finite. We illustrate the procedure …

A Critical Inter-Subunit Interaction For The Transmission Of The Allosteric Signal In The Agrobacterium Tumefaciens Adp-Glucose Pyrophosphorylase, Hiral Patel, Gabriela Martinez-Ramirez Ms., Emily Dobrzynski, Alberto A. Iglesias, Dali Liu, Miguel Ballicora

Chemistry: Faculty Publications and Other Works

ADP-glucose pyrophosphorylase is a key regulatory enzyme involved in starch and glycogen synthesis in plants and bacteria, respectively. It has been hypothesized that inter-subunit communications are important for the allosteric effect in this enzyme. However, no specific interactions have been identified as part of the regulatory signal. The enzyme from Agrobacterium tumefaciens is a homotetramer allosterically regulated by fructose 6-phosphate and pyruvate. Three pairs of distinct subunit-subunit interfaces are present. Here we focus on an interface that features two symmetrical interactions between Arg11 and Asp141 from one subunit with residues Asp141 and Arg11 of the neighbor subunit, respectively. Previously, scanning …

2023 Chairs’ Welcome, Daniel Moreira, Aparna Bharati, Cecilia Pasquini, Yassine Yousfi

Computer Science: Faculty Publications and Other Works

Welcome to the 11th edition of the ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec ‘23). This year’s workshop continues the tradition of representing one of the prime events in information hiding and multimedia security, attracting researchers and practitioners worldwide. Carrying on with the efforts of the previous edition to overcome the Pandemics and reunite the IH&MMSec community to present and discuss their work, this year’s meeting is held fully in person at the Water Tower Campus of Loyola University Chicago, located right at the heart of the Windy City. Bathed by the fresh waters of Lake Michigan, Chicago …

Exploring The Genotypic And Phenotypic Differences Distinguishing Lactobacillus Jensenii And Lactobacillus Mulieris, Adriana Ene, Swarnali Banerjee, Alan J. Wolfe, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii are dominant species of the urogenital microbiota. Prior studies suggest that these Lactobacillus species play a significant role in the urobiome of healthy females. In our prior genomic analysis of all publicly available L. jensenii and Lactobacillus mulieris genomes at the time (n = 43), we identified genes unique to these two closely related species. This motivated our further exploration here into their genotypic differences as well as into their phenotypic differences. First, we expanded genome sequence representatives of both species to 61 strains, including publicly available …

Exploring The Genotypic And Phenotypic Differences Distinguishing Lactobacillus Jensenii And Lactobacillus Mulieris, Adriana Ene, Swarnali Banerjee, Alan J. Wolfe, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii are dominant species of the urogenital microbiota. Prior studies suggest that these Lactobacillus species play a significant role in the urobiome of healthy females. In our prior genomic analysis of all publicly available L. jensenii and Lactobacillus mulieris genomes at the time (n = 43), we identified genes unique to these two closely related species. This motivated our further exploration here into their genotypic differences as well as into their phenotypic differences. First, we expanded genome sequence representatives of both species to 61 strains, including publicly available …

Tree-Based Unidirectional Neural Networks For Low-Power Computer Vision, Abhinav Goel, Caleb Tung, Nick Eliopoulos, Amy Wang, Jamie C. Davis, George K. Thiruvathukal, Yung-Hisang Lu

Computer Science: Faculty Publications and Other Works

This article describes the novel Tree-based Unidirectional Neural Network (TRUNK) architecture. This architecture improves computer vision efficiency by using a hierarchy of multiple shallow Convolutional Neural Networks (CNNs), instead of a single very deep CNN. We demonstrate this architecture’s versatility in performing different computer vision tasks efficiently on embedded devices. Across various computer vision tasks, the TRUNK architecture consumes 65% less energy and requires 50% less memory than representative low-power CNN architectures, e.g., MobileNet v2, when deployed on the NVIDIA Jetson Nano.

Big Ideas In Sports Analytics And Statistical Tools For Their Investigation, Benjamin S. Baumer, Gregory J. Matthews, Quang Nguyen

Mathematics and Statistics: Faculty Publications and Other Works

Sports analytics—broadly defined as the pursuit of improvement in athletic performance through the analysis of data—has expanded its footprint both in the professional sports industry and in academia over the past 30 years. In this article, we connect four big ideas that are common across multiple sports: the expected value of a game state, win probability, measures of team strength, and the use of sports betting market data. For each, we explore both the shared similarities and individual idiosyncracies of analytical approaches in each sport. While our focus is on the concepts underlying each type of analysis, any implementation necessarily …

Assessing The Impact Of A Csforall Research-Practice Partnership Using The Prosper Framework: A Case Study Of The Chicago Alliance For Equity In Computer Science (Cafécs), Erin Henrick, Steven Mcgee, Ronald I. Greenberg, Dale Reed, Don Yanek, Lucia Dettori, Haley Williamson

Computer Science: Faculty Publications and Other Works

The Chicago Alliance for Equity in Computer Science (CAFÉCS) Research Practice Partnership (RPP) has been working for more than a decade towards their mission to engage in research and development that enables Chicago Public Schools (CPS) to ensure that all students in Chicago participate in engaging, relevant, and rigorous computing experiences, increase opportunities for all students to pursue computing pathways and prepare all students for the future of work. The partnership engaged in an iterative design process to develop a framework for understanding the areas of RPP impact on a district. This paper applies the PROSPER framework to the CAFÉCS …

Carborane-Containing Hydroxamate Mmp Ligands For The Treatment Of Tumors Using Boron Neutron Capture Therapy (Bnct): Efficacy Without Tumor Cell Entry, Sebastian Flieger, Mao Takagaki, Natsuko Kondo, Marlon Lutz Jr., Yash Gupta, Hiroki Ueda, Yoshinori Sakurai, Graham Moran, Prakasha Kempaiah, Narayan Hosmane, Minoru Suzuki, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

New carborane-bearing hydroxamate matrix metalloproteinase (MMP) ligands have been synthesized for boron neutron capture therapy (BNCT) with nanomolar potency against MMP-2, -9 and -13. New analogs are based on MMP inhibitor CGS-23023A, and two previously reported MMP ligands 1 (B1) and 2 (B2) were studied in vitro for BNCT activity. The boronated MMP ligands 1 and 2 showed high in vitro tumoricidal effects in an in vitro BNCT assay, exhibiting IC₅₀ values for 1 and 2 of 2.04 × 10⁻² mg/mL and 2.67 × 10⁻² mg/mL, respectively. The relative killing effect of 1 to L-boronophenylalanine (BPA) is …

Conversations With Chatgpt About C Programming: An Ongoing Study, James C. Davis, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

AI (Artificial Intelligence) Generative Models have attracted great attention in recent years. Generative models can be used to create new articles, visual arts, music composition, even computer programs from English specifications. Among all generative models, ChatGPT is becoming one of the most well-known since its public announcement in November 2022. GPT means {\it Generative Pre-trained Transformer}. ChatGPT is an online program that can interact with human users in text formats and is able to answer questions in many topics, including computer programming. Many computer programmers, including students and professionals, are considering the use of ChatGPT as an aid. The quality …

In Silico Binding Of 2-Aminocyclobutanones To Sars-Cov-2 Nsp13 Helicase And Demonstration Of Antiviral Activity, Thahani S. Habeeb Mohammad, Yash Gupta, Cory T. Reidl, Vlad Nicolaescu, Haley Gula, Ravi Durvasula, Prakasha Kempaiah, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

The landscape of viral strains and lineages of SARS-CoV-2 keeps changing and is currently dominated by Delta and Omicron variants. Members of the latest Omicron variants, including BA.1, are showing a high level of immune evasion, and Omicron has become a prominent variant circulating globally. In our search for versatile medicinal chemistry scaffolds, we prepared a library of substituted α-aminocyclobutanones from an α-aminocyclobutanone synthon (11). We performed an in silico screen of this actual chemical library as well as other virtual 2-aminocyclobutanone analogs against seven SARS-CoV-2 nonstructural proteins to identify potential drug leads against SARS-CoV-2, and more broadly against coronavirus …

Observing Human Mobility Internationally During Covid-19, Shane Allcroft, Mohammed Metwaly, Zachery Berg, Isha Ghodgaonkar, Fischer Bordwell, Xinxin Zhao, Xinglei Liu, Jiahao Xu, Subhankar Chakraborty, Vishnu Banna, Akhil Chinnakotla, Abhinav Goel, Caleb Tung, Gore Kao, Wei Zakharov, David A. Shoham, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

This article analyzes visual data captured from five countries and three U.S. states to evaluate the effectiveness of lockdown policies for reducing the spread of COVID-19. The main challenge is the scale: nearly six million images are analyzed to observe how people respond to the policy changes.

Neutrino Forces In Neutrino Backgrounds, Mitrajyoti Ghosh, Yuval Grossman, Walter Tangarife, Xun-Jie Xu, Bingrong Yu

Physics: Faculty Publications and Other Works

The Standard Model predicts a long-range force, proportional to G² F /r⁵, between fermions due to the exchange of a pair of neutrinos. This quantum force is feeble and has not been observed yet. In this paper, we compute this force in the presence of neutrino backgrounds, both for isotropic and directional background neutrinos. We find that for the case of directional background the force can have a 1/r dependence and it can be significantly enhanced compared to the vacuum case. In particular, background effects caused by reactor, solar, and supernova neutrinos enhance the force by many …