Digital Commons Network^™

Navigating Enterprise Constraints: Building A Hybrid Multi-Modal Mobile Intelligent App, Ketan Malempati, Akshat Gupta, Kaikai Liu

Faculty Research, Scholarly, and Creative Activity

The promise of artificial intelligence (AI) has prompted various industries to explore how it can enhance their businesses and improve customer experiences. However, the practical deployment of AI services faces challenges due to internal infrastructure limitations, data policies, and network restrictions. In this paper, we present our current project - a solution designed to empower mental health centers with AI tools while adhering to stringent data and network constraints. Our approach involves deploying AI services and data within internal enterprise networks, while the customer-facing mobile app resides in the public cloud. We introduce a custom AI agent system that monitors …

Rapid Simulation Framework For Superconducting Qubit Readout System Inverse Design And Optimization, Albert Lu, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

Qubit readout is one of the most important operations in quantum computers. In superconducting quantum computers, the success of readout depends on many parameters and is difficult to optimize due to the high dimensionality of the problem. In this work, a rapid simulation framework that comprises an analytical model, a neural network (NN), and optimizers using the NN as a surrogate model is proposed. The analytical model is calibrated to the experimental result and allows rapid simulations to generate enough data to train NNs. Single and multi-objective optimizations are performed. It is shown that a better solution can be found …

Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu, William B. Andreopoulos

Faculty Research, Scholarly, and Creative Activity

This paper presents a novel approach to enhancing the Llama language model for generating customized resumes tailored to domain-specific job descriptions. Unlike traditional methods that rely heavily on extensive fine-tuning, we implement scalable adapter modules to minimize parameter adjustments. This approach preserves the model's inherent ability to generate coherent and contextually appropriate language across diverse tasks, ensuring that its general linguistic capabilities remain intact. Additionally, we employ a prompting strategy to dynamically create a diverse and comprehensive dataset, ensuring high relevance to various job roles. Using a dataset of 10,000 job descriptions and resumes, our approach resulted in a 20% …

Rescaling: Change Agency And The Emerging Geography Of Economic Relationships, Markus Grillitsch, Björn Asheim, Nichola Lowe, Sophie Kelmenson, Lea Fünfschilling, Karl Johan Lundquist, Yahia Mahmoud, Mikhail Martynovich, Pauline Mattsson, Magnus Nilsson, Johan Miörner, Torben Schubert

Faculty Research, Scholarly, and Creative Activity

In this paper, we propose a theoretical and conceptual framework for articulating and studying changes in the global economic landscape and illustrate this framework in the current context. The framework pivots around the notion of rescaling, which is interpreted from a human agency perspective. We disentangle three theoretically distinct dimensions of rescaling and show how they play together using concrete examples. The theoretical and conceptual framework links the intended and unintended consequences of globalisation to current rescaling efforts, and allows us to investigate when, why, and how changes to the geography of economic relationships occur.

Study Of Using Variational Quantum Linear Solver For Solving Poisson Equation, Nithin Reddy Govindugari, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

Quantum computing is promising in speeding up the system of linear equations (SLE) solving process. However, its performance is limited by noise. The variational quantum linear solver (VQLS) algorithm is expected to be more resilient to noise than gate-based quantum computing algorithms. This is because error correction is not available yet and VQLS is based on cost function minimization. In this paper, the gate insulator Poisson equation is solved using VQLS. The results are compared to technology computer-aided design (TCAD) results and gate-based quantum algorithm results. We show that, even without error-free qubits, the IBM-Q quantum computer hardware can solve …

Tcad Structure Input File Generation Using Large Language Model, Le Minh Long Nguyen, Albert Lu, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

In this paper, we study the possibility of using Large Language Models (LLMs) to create Technology Computer-Aided-Design (TCAD) structure generation input files. LLMs are machine learning models trained on vast amounts of text data from the Web and are designed to understand, generate, and interact with humans through natural languages such as English. However, unlike programming languages with abundant training examples on the Web, TCAD examples are scarce. In this work, by using TCAD Sentaurus Structure Editor (SSE) as an example, 7000 nanowire data are generated to fine-tune open-source models (Llama 2 and 3) to obtain chatbots that can generate …

The Applicability Of Llms In Generating Textual Samples For Analysis Of Imbalanced Datasets, Saroj Gopali, Faranak Abri, Akbar Siami Namin, Keith S. Jones

Faculty Research, Scholarly, and Creative Activity

In machine learning class imbalance is a pressing issue, where the model is biased towards the majority classes and underperforms in the minority classes. In textual data, the natural language processing (NLP) model bias significantly reduces overall accuracy, along with poor performance in minority classes. This paper investigates and compares the performance of transformer-based models, such as Multi-head Attention with the data levels and algorithmic levels approaches and BERT (Bidirectional Encoder Representations from Transformers) with LLM-based data augmentation. The research utilized the approaches, such as Random Over Sampler, Synthetic Minority Over-sampling Technique (SMOTE), SMOTEENN, data augmentation at word level, class …

The Role Of Paradata In Algorithmic Accountability, Ciaran B. Trace, James A. Hodges

Faculty Research, Scholarly, and Creative Activity

This chapter examines how the doings of the algorithm (instantiated through its operations, actions, and steps) and its accompanying algorithmic system are revealed and explored through an engagement with the paradata created as a part of this data-making effort. In doing so, the chapter explores how the concept of paradata helps us understand how information professionals and domain stakeholders conceptualize accountable algorithmic entities and how this influences how they emerge as documented and describable entities. Two complementary frameworks for capturing and preserving paradata for accountability purposes are examined in the process. The first is associated with diplomatic theory and archival …

Machine Learning, Fuzzy Logic And Zero Trust-Based Quishing Prevention Solution For Android Smartphones, Felix William

Theses

QR code phishing, or "quishing," exploits the widespread adoption of QR codes to embed malicious URLs that lead users to phishing sites or initiate malware downloads. Unlike traditional phishing methods, QR phishing is uniquely deceptive, leveraging the inherent trust and convenience associated with QR codes while bypassing standard detection mechanisms. This thesis presents the SEQR scanner, a novel solution tailored to detect and prevent QR phishing attacks, specifically focusing on Android platforms. By integrating multiple detection mechanisms—machine learning prediction, fuzzy logic algorithm, and third-party blacklisting APIs—the solution effectively identifies malicious QR codes with precision. A zero-trust-based mechanism is implemented alongside …

Florescence, Evan D. Jaccodine

Theses

Florescence is a photographic project that provokes conversation between mediums, methods, and attitudes in art and design. Starting as grainy, screened Risograph prints mounted into custom wood frames, the uniformity of mechanical reproduction is distorted by handmade craft elements. The images examine the materiality of making as part of the message they produce; they are both eclectic handmade objects and mass-produced products. These pictures intend to communicate an idea like an advertisement, except the message, meaning, or intention isn’t clear. I am interested in the moment when the viewer comes close enough to the image to see the prints' poor …

Tiktok As Social Communication Tool To Encourage Participation In Volunteering Projects, Belén Moreno-Albarracín, Tania Blanco-Sánchez

Faculty Research, Scholarly, and Creative Activity

Social media are regarded as tools of communication and social influence. Notwithstanding this, TikTok’s majority audience in 2023 is made up of members of generations Z and Alpha, associated in previous studies with a participatory crisis. Given this contradiction, a research question is proposed: do young people use TikTok to consolidate social values such as solidarity? To answer it, the main objective is to analyse the use of TikTok as an instrument for youth participation in volunteer projects. A mixed methodology is used, based on a content analysis of the 150 videos uploaded to TikTok with the hashtag #voluntariado and …

Cross-Cultural Adaptation Of The Voice-Related Experiences Of Nonbinary Individuals - Veni To Brazilian Portuguese, Isabela Dos Santos, Mara Behlau, Grace Shefcik, Pei Tzu Tsai, Vanessa Veis Ribeiro

Faculty Research, Scholarly, and Creative Activity

Purpose: This study aimed to translate and cross-culturally adapt the “Voice-related Experiences of Nonbinary Individuals” (VENI) to Brazilian Portuguese (BP). Methods: Cross-cultural adaptation was performed based on the combined guidelines of the World Health Organization’s (WHO) Translation Recommendations and the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). The process included five stages: a) Translation of the instrument into BP by a translator specialized in the construct and a non-specialist, both native BP speakers and fluent in English; b) Synthesis of the two translations by consensus; c) Back-translation by a translator specialized in the construct and a non-specialist, …

A Comparative Multivariate Analysis Of Var And Deep Learning-Based Models For Forecasting Volatile Time Series Data, Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin

Faculty Research, Scholarly, and Creative Activity

The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), Simple Exponential Smoothing (SES), deep learning models, and, most notably, univariate Long Short-Term Memory (LSTM) built based on univariate variable where the next lag of time series is leveraged for forecasting the next cycle of data. This paper takes this line of research to the next level by focusing on forecasting time series data based on “multivariate” modeling and analysis. To have a better insight of the performance of various deep learning-based models when multivariate …

Algorithmic Embeddedness And The ‘Gig’ Characteristics Model: Examining The Interplay Between Technology And Work Design In Crowdwork, Francesca Bellesia, Elisa Mattarelli, Fabiola Bertolotti, Maurizio Sobrero

Faculty Research, Scholarly, and Creative Activity

This article systematically reviews the literature on online task crowdwork to investigate the complex relationship between technology and work design on crowdwork platforms. We highlight the diverse interpretations and uses of technology, specifically platform features and algorithms, in relation to work design. Our review reveals that platform features serve as antecedents to work design characteristics, while algorithms are so intertwined with job execution that a new work characteristic is needed to model this interplay. We introduce this new work characteristic as algorithmic embeddedness and show that it varies in degree. When high, algorithmic embeddedness can be perceived as either an …

Anti-Trafficking And Humanitarian Operations: Transferring Learnings For A Better World, Kezban Yagci Sokat, Maria Besiou

Faculty Research, Scholarly, and Creative Activity

Purpose: The purpose of this study is twofold: first, to draw insights from the rich literature on humanitarian operations efforts to combat human trafficking; second, to inspire humanitarian operations researchers to work more on human anti-trafficking. Design/methodology/approach: This is a conceptual paper inspired by recent relevant reports, the academic literature and the authors’ years of involvement in both humanitarian operations and anti-trafficking. Findings: Humanitarian supply chains and human trafficking supply chains very often operate in the same environments and hence face similar challenges. The paper highlights the overlaps between the two domains and demonstrates how two decades of learnings from …

Assessment Of Digital Collaboration Skills, Esperanza Huerta, Ana Lidia Franzoni Velázquez, Scott Jensen

Faculty Research, Scholarly, and Creative Activity

This exploratory study proposes a methodology for assessing digital collaboration skills based on the students' actual behavior. Students' comments using a digital collaboration tool during a one-month long project were manually coded. This methodology is not context specific and can be used across different domains. This assessment contrasts with self-reported measures in which students rate themselves as already possessing collaboration skills. Finally, the study explores the use of generative AI to automatically code student's comments to alleviate the labor-intensive process that coding requires and to enable scalability in coding data.

Graduate Public Health Student Learning Experiences, Social Connectedness, And Mental Health During Covid-19: Pedagogical Implications For Public Health Academic Departments, Harit Agroia, Rachel Berkowitz, Andrew Carter, Vicky Gomez, Monica Allen

Faculty Research, Scholarly, and Creative Activity

Introduction: The COVID-19 pandemic impacted college student learning both globally and nationally. Current literature points to decreases in social connectedness, adverse mental health outcomes, and decreased overall learning outcomes; however, there are limited findings from higher education institutions within the Bay Area, California. There are also limited studies that examine the COVID-19 impact among public health graduate students, especially to understand how the pandemic renewed their interest in the field. The purpose of this study was to investigate the effects of COVID-19 on graduate student learning experiences, social connectedness and mental health within the Master of Public Health program at …

Is Knowledge Management (Finally) Extractive? – Fuller’S Argument Revisited In The Age Of Ai, Norman Mooradian

Faculty Research, Scholarly, and Creative Activity

Aim/Purpose The rise of modern artificial intelligence (AI), in particular, machine learning (ML), has provided new opportunities and directions for knowledge management (KM). A central question for the future of KM is whether it will be dominated by an automation strategy that replaces knowledge work or whether it will support a knowledge-enablement strategy that enhances knowledge work and uplifts knowledge workers. This paper addresses this question by re-examining and updating a critical argument against KM by the sociologist of science Steve Fuller (2002), who held that KM was extractive and exploitative from its origins. Background This paper re-examines Fuller’s argument …

Andalusian Electoral Campaign 2022: Analysis Of The Relationships Between Interest, Media Use And Citizen Participation, Ana Castillo Díaz, Belén Moreno

Faculty Research, Scholarly, and Creative Activity

This paper analyzes the media coverage of the 2022 Andalusian election campaign and its connection to the interest expressed by citizens in the campaign, as well as their participation through voting and as transmitters of campaign-related content. To determine the existence of relationships between the variables considered, the chi-square hypothesis test is used. The strength of the associations is measured using Cramer’s V and the contingency coefficient. The results show an association between interest in the campaign and media coverage. Television is the preferred medium for staying informed, followed by digital press and radio. Debates and interviews are the most …

Computer Vision Intelligence Test Modeling And Generation: A Case Study On Smart Ocr, Jing Shu, Bing Jiun Miu, Eugene Chang, Jerry Gao, Jun Liu

Faculty Research, Scholarly, and Creative Activity

AI-based systems possess distinctive characteristics and introduce challenges in quality evaluation at the same time. Consequently, ensuring and validating AI software quality is of critical importance. In this paper, we present an effective AI software functional testing model to address this challenge. Specifically, we first present a comprehensive literature review of previous work, covering key facets of AI software testing processes. We then introduce a 3D classification model to systematically evaluate the image-based text extraction AI function, as well as test coverage criteria and complexity. To evaluate the performance of our proposed AI software quality test, we propose four evaluation …

Emergence Of Preferential Flow Paths And Intermittent Dynamics In Emulsion Transport In Porous Media, Michael Izaguirre

Theses

This dissertation aims to study the underlying physics of anomalous transport of emulsions in porous media and quantify the role of droplet-pore and droplet-droplet interactions in transport in porous media experimentally. The complexities of this problem arise from the network heterogeneity, correlations between the pores across the medium, interfacial properties of the fluids, and the correlations between the pore scale dynamics and system-level transport. This dissertation presents significant advancements in the study of emulsion dynamics within two-dimensional porous media through the development of innovative image analysis and tracking methods. These advancements include precise detection and tracking of deformable objects, which …

Enhancing Product Designing With The Help Of Artificial Intelligence, Dhyeykumar Nikalwala, Minnie H. Patel

Faculty Research, Scholarly, and Creative Activity

In the ever-changing world of Business, making a successful product design requires quickly trying out new ideas and listening to what users think. With the integration of Artificial Intelligence (AI), the process of rapidly generating content from existing data becomes easier, accelerating the creation of innovative product concepts. To use this cutting-edge technology to build novel products a framework is essential. The paper aims to propose a novel framework that caters to a customer-centric integration of AI in Product Design. The paper goes beyond theoretical explanation, implementing the framework to iteratively design 3 diverse products. The implementation also highlights the …

Reconstruct, Jenna Deal

Theses

This thesis explores how construction materials can be used in sculpture, pushing artistic boundaries and challenging traditional perceptions. It examines the potential of materials like mortar, PVC, HVAC duct, carpet, and asphalt roofing, aiming to redefine the relationship between labor, materials, and artistic expression. By breaking free from construction norms and engaging with materials in unexpected ways, the study aims to foster a deeper understanding of the value and creative possibilities inherent in the materials of our built environment.

Review Of Literature On Efficacy And Safety Of Birthing Positions With Emphasis On International Cultural Influences On Obstetric Care, Ava E. Retsch

Theses

• Background: When examining most non-Westernized societies, parturients hold all the power in the birthing space with traditional birth attendants and medical staff serving as guiding forces and protectors, not directors of the process. Social media in Western countries is filled with stories from birthing people who felt unsupported, ignored, or discriminated against by their healthcare providers; this is particularly prevalent in parturients who express a preference for non-supine birthing positions. Methods: This work is a review of the existing body of literature on quantitative and qualitative outcome measures of alternative birthing positions. In total, 44 articles were analyzed …

The Impact Of Banning Confidential Settlements On Discrimination Dispute Resolutio, Blair D. Bullock, Joni Hersch -- Cornelius Vanderbilt Professor Of Law And Economics

Vanderbilt Law Review

The #MeToo movement exposed how workplace harassment plagues employment in the United States. Several states responded by passing legislation aimed at curbing harassment and employment discrimination in the workplace. One of the most common legislative efforts was to ban confidentiality provisions in certain settlement agreements. These bans, in part, attempted to stop "secret settlements" by shining light on workplace discrimination and exposing serial harassers as a means to motivate firms to actively deter workplace discrimination.

But do bans on confidentiality agreements deter the bad act? For these laws to have a deterrent effect, claims must be revealed in a public …

Access To Justice For Black Inventors, Jordana R. Goodman, Khamal Patterson

Vanderbilt Law Review

To receive a patent, an inventor must meet certain inventive and procedural standards. Their invention must be novel, nonobvious, and written in such a way that any person skilled in the inventive subject can make and use the invention without undue experimentation. This process is far from objective.

An inventor is not always communicating within their own social circle. An inventor is required to communicate their invention so that a patent examiner believes a person having ordinary skill in the art ("PHOSITA") would recognize the invention as nonobvious. Moreover, a fictitious skilled person must be able to make and use …

Examining The Multifaceted Impacts Of Drug Decriminalization On Public Safety, Law Enforcement, And Prosecutorial Discretion, Kelsey S. Henderson, Christopher M. Campbell, Brian C. Renauer

Criminology and Criminal Justice Faculty Publications and Presentations

This final report provides the findings of a multi-year project to understand the effects of successive drug policy efforts in Oregon. Since 2013, Oregon has implemented three changes that reclassified and lowered the seriousness of low-level drug possession offenses, with multiple years between each policy change: Justice Reinvestment in 2013, defelonization in 2017, and decriminalization in 2021. This project parses out the individual impacts of these unique events on law enforcement, prosecution, courts and sentencing, and public safety & health.

The Evolving Role Of Libraries In The Fourth Industrial Revolution: Navigating Digital Transformation, Abdullahi Olayinka Isiaka, Abdulfatai Soliu, Biliamin Abiola Aremu, Benjamin Adebisi Bamidele, Saidu Saba-Jibril, Adelani Rotimi Ibitoye

Library Philosophy and Practice (e-journal)

Abstract

This article explores the transformative impact of the Fourth Industrial Revolution (4IR) on libraries and their pivotal role in navigating the challenges and opportunities brought forth by rapid technological advancements. Libraries, traditionally perceived as repositories of books and information, are undergoing a profound metamorphosis in the digital age. The 4IR, characterized by breakthroughs in Artificial Intelligence, the Internet of Things, and Data Analytics, demands a redefinition of the library’s purpose and services. The first section introduces the concept of the 4IR and its key technological advancements. Emphasis is placed on understanding the dynamic landscape of the 4IR and the …

Environmental Law: The Negotiable Implementation Of Environmental Law, Dave Owen

The Judges' Book

No abstract provided.

Optimizing Neural Networks For Iiot Attack Detection, Hamad Alblooshi

Theses

The Industrial Internet of Things (IIoT) stands as a revolutionary force, intertwining physical devices, sensors, and industrial systems to usher in advanced automation and data-driven decision-making across various sectors. However, this increased connectivity has exposed these systems to a growing array of cyber threats. Safeguarding IIoT environments becomes crucial to maintain the integrity, availability, and confidentiality of critical industrial processes. In response, this research explores the optimization of neural network parameters using Genetic Algorithms (GA). The application of GA has led to achieve a remarkable accuracy of 95% across various attack types. The results demonstrate a high performance in identifying …