Digital Commons Network^™

Differences In Software Usability Level Based On User Background, Abdur Rohman Sholeh, Agung Fatwanto

Elinvo (Electronics, Informatics, and Vocational Education)

The development of software must consider usability as one of its key success indicators. Relatively few studies discuss the factors influencing usability, including users' backgrounds. The purpose of this research was to investigate the impact of user background, specifically gender, class (year of college admission), and frequency of use on the rating of usability. This research utilized a descriptive quantitative method with instruments: the usability matrix of the Computer System Usability Questionnaire (CSUQ), the System Usability Scale (SUS), the Usability Metric for User Experience (UMUX), and the Net Promoter Score (NPS). The research object was the Learning Management System (LMS) …

Visitor Decision System In Selection Of Tourist Sites Based On Hybrid Of Chi-Square And K-Nn Methods, Devie Rosa Anamisa, Fifin Ayu Mufarroha, Achmad Jauhari

Elinvo (Electronics, Informatics, and Vocational Education)

Madura Island is one of the islands with a lot of tourism spread over four districts, such as natural, religious, and cultural tourism. And every year, various visitors visit various tourist sites in Madura, so an increase in the number of visitors has been found in multiple places. This is influenced in addition to the type of tourist attraction but also changes in tourist behavior in making decisions to visit tourist objects. Most of the researchers have applied the right decision-making with intelligence-based measurement. However, the accuracy obtained has not yet reached the optimal solution. Therefore, this study uses the …

Analysis Of Community-Based Pattern Of Water Demand And Supply, Ishaku Dibal Joshua, Abdullahi Chado Salihu, Ayuba Musa Mshelia, Nchedo Nnedinma Ubachukwu

Journal of Environmental Science and Sustainable Development

Gombi rural community of Adamawa state, Nigeria, has witnessed significant growth in human population, which has contributed to an increase in water demand. Thus, the study analyzed water demand and supply patterns in Gombi communities of Adamawa State, Nigeria. A structured questionnaire was used for data collection. Descriptive statistics such as mean and percentages and inferential statistics like Analysis of Variance (ANOVA), chi-square, and linear regression were adopted for the analysis. The results on socioeconomic characteristics showed that the majority were females, with low household income levels, large household sizes, and in their active ages. Hand-dug well water was the …

Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan

Journal of Environmental Science and Sustainable Development

Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …

Stereotactic Mr-Guided On-Table Adaptive Radiation Therapy (Smart) For Borderline Resectable And Locally Advanced Pancreatic Cancer: A Multi-Center, Open-Label Phase 2 Study, Michael Chuong, Percy Lee, Daniel Low, Joshua Kim, Kathryn Mittauer, Michael Bassetti, Carri Glide-Hurst, Ann Raldow, Yingli Yang, Lorraine Portelance, Kyle Padgett, Bassem Zaki, Rongxiao Zhang, Hyun Kim, Lauren Henke, Alex Price, Joseph Mancias, Christopher Williams, John Ng, Ryan Pennell, M Raphael Pfeffer, Daphne Levin, Adam Mueller, Karen Mooney, Patrick Kelly, Amish Shah, Luca Boldrini, Lorenzo Placidi, Martin Fuss, Parag Jitendra Parikh

Department of Radiation Oncology Faculty Papers

BACKGROUND AND PURPOSE: Radiation dose escalation may improve local control (LC) and overall survival (OS) in select pancreatic ductal adenocarcinoma (PDAC) patients. We prospectively evaluated the safety and efficacy of ablative stereotactic magnetic resonance (MR)-guided adaptive radiation therapy (SMART) for borderline resectable (BRPC) and locally advanced pancreas cancer (LAPC). The primary endpoint of acute grade ≥ 3 gastrointestinal (GI) toxicity definitely related to SMART was previously published with median follow-up (FU) 8.8 months from SMART. We now present more mature outcomes including OS and late toxicity.

MATERIALS AND METHODS: This prospective, multi-center, single-arm open-label phase 2 trial (NCT03621644) enrolled 136 …

Prt543, A Protein Arginine Methyltransferase 5 Inhibitor, In Patients With Advanced Adenoid Cystic Carcinoma: An Open-Label, Phase I Dose-Expansion Study, Renata Ferrarotto, Paul Swiecicki, Dan Zandberg, Robert Baiocchi, Robert Wesolowski, Cristina Rodriguez, Meredith Mckean, Hyunseok Kang, Varun Monga, Rajneesh Nath, Neil Palmisiano, Naveen Babbar, William Sun, Glenn Hanna

Department of Medical Oncology Faculty Papers

OBJECTIVES: Currently, no systemic treatments are approved for patients with recurrent and/or metastatic (R/M) adenoid cystic carcinoma (ACC). PRT543, a protein arginine methyltransferase 5 inhibitor that downregulates NOTCH1 and MYB signalling in tumours, is a potential candidate for R/M ACC treatment. We report the safety, tolerability and preliminary efficacy of PRT543 in a dose-expansion cohort of patients with R/M ACC.

MATERIALS AND METHODS: This phase I multicentre, open-label, sequential-cohort, dose-escalation and dose-expansion study (NCT03886831) enrolled patients with advanced solid tumours and select haematologic malignancies. Dose-escalation study design and results were reported previously. In the dose expansion, patients with R/M ACC …

Social Justice Mathematics: Classroom Practices That Give Students Rigor While Building Agency, Emily Marquise

Masters Theses

The purpose of this study is to examine the impact of a social justice approach to mathematics instruction. While many students have math aversion, students in low socioeconomic communities exhibit this to a higher degree putting them at a disadvantage as they progress through their educational career. More than 3.4 million K-12 students in the United States come from families that earn less than the median income yet achieve scores in the top percentile (Wyner et al., 2007). This raises the question of why so many students in low-socioeconomic settings are not given rigorous content that will keep them competitive …

Ungrading: Reflections Through A Feminist Pedagogical Lens, Erin M. Eggleston, Shelby Kimmel

Feminist Pedagogy

Ungrading is a pedagogical approach in which no grades are given on any assignments. Instead, students are provided with many opportunities to submit work and gain feedback. The goal is to shift student focus from achieving a grade to growth as a learner and a person. As instructors, our ungrading approach utilized personalized learning plans, checkpoint reflections, and student-professor learning conferences to put agency in the hands of our students. We employed this method in upper-level biology and computer science courses and provide critical reflections here regarding our experiences and the connections between this approach and feminist STEM pedagogy tenets. …

Feminist Pedagogy In Stem: The Intersection Of Stem Pedagogy And Feminist Theory, Lesley-Ann Giddings, Candice R. Price

Feminist Pedagogy

No abstract provided.

Tiny Machine Learning For Underwater Image Enhancement: Pruning And Quantizaition Approach, Dr Khaled Nagaty, The British University In Egypt, Andreas Pester Dr

Computer Science

Many people have expressed an interest in underwater image processing in a variety of fields, including underwater vehicle control, archaeology, marine biological studies, etc. Underwater exploration is becoming an increasingly important element of our lives, with applications ranging from underwater marine and creature research to pipeline and communication logistics, military use, touristic and entertainment use. Underwater images suffer from poor visibility, distortion, and poor quality for a variety of causes, including light propagation. The major issue arises when these images must be captured at depths greater than 500 feet and artificial lighting needs to be provided. Efficient algorithms and models …

Rolling The Crypto Dice: The Interplay Of Legal Environments, Market Uncertainty, And Gambling Attitudes On Users’ Behavioral Intentions, Ayman Abdalmajeed Alsmadi, Ahmed Shuhaiber, Khaled Saleh Al-Omoush

All Works

The high volatility and inherent high-risk nature of cryptocurrency investments promote the study of the determinants of value perception and the various factors influencing individuals’ intentions regarding whether to adopt, abstain from, or continue their investments in these dynamic cryptocurrency markets. The main aim of this study is to examine the determinants of behavioral intention to continue using cryptocurrencies. In addition, it is aimed at exploring the effect of gambling attitudes on the perceived benefits and legal environment in the cryptocurrency context. An online questionnaire was developed in order to gather data from 258 respondents in the United Arab Emirates …

Learning Mortality Risk For Covid-19 Using Machine Learning And Statistical Methods, Shaoshi Zhang

Electronic Thesis and Dissertation Repository

This research investigates the mortality risk of COVID-19 patients across different variant waves, using the data from Centers for Disease Control and Prevention (CDC) websites. By analyzing the available data, including patient medical records, vaccination rates, and hospital capacities, we aim to discern patterns and factors associated with COVID-19-related deaths.

To explore features linked to COVID-19 mortality, we employ different techniques such as Filter, Wrapper, and Embedded methods for feature selection. Furthermore, we apply various machine learning methods, including support vector machines, decision trees, random forests, logistic regression, K-nearest neighbours, na¨ıve Bayes methods, and artificial neural networks, to uncover underlying …

Tikaram And Chandrakala Dhananjaya: A Collaborative Couple In Mathematics From Nepal, Deepak Basyal, Brigitte Stenhouse

Mathematics and Statistics

Within the history of mathematics and mathematics education in Nepal, Tikaram and Chandrakala Dhananjaya are relatively well-known figures for their two books Śiśubodha Taraṅgiṇī and Līlāvatī. This is despite there being almost no archival or manuscript materials offering a window into their lives: we have no letters, notebooks, diaries, or school records. Rather than focusing on either individual in isolation, in this article we present an argument for considering the Dhananjayas as an analytically indivisible collaborative couple in mathematics. Of the two aforementioned books, one is attributed to Chandrakala and the other to Tikaram; but in fact, both are translations …

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

Impact Of Covid-19 On Recruitment Of High School Athletes To Di Track And Field, Christopher Haub, Jon Paugh, Alonso Salcido, Monnie Mcgee

SMU Data Science Review

Due to COVID-19, in the spring of 2020, the NCAA gave scholarship athletes an extra year of eligibility but did not increase the number of scholarships a school could issue. This potentially led to increased competition for scholarships as coaches could choose between retaining athletes or recruiting new ones. Furthermore, the Spring 2020 track and field season for high school seniors ended early – limiting high school athletes’ chance to get their best scores, and interrupting student to college interaction. This research looks specifically at the impact of COVID-19, and the resulting NCAA policy changes, on the recruitment to DI …

A Prompt Engineering Approach To Creating Automated Commentary For Microsoft Self-Help Documentation Metric Reports Using Chatgpt, Ryan Herrin, Luke Stodgel, Brian Raffety

SMU Data Science Review

Microsoft collects an immense amount of data from the users of their product-self-help documentation. Employees use this data to identify these self-help articles' performance trends and measure their impact on business Key Performance Indicators (KPIs). Microsoft uses various tools like Power BI and Python to analyze this data. The problem is that their analysis and findings are summarized manually. Therefore, this research will improve upon their current analysis methods by applying the latest prompt engineering practices and the power of ChatGPT's large language models (LLMs). Using VBA code, Microsoft Excel, and the ChatGPT API as an Excel add-in, this research …

The Impact Of The Covid-19 Pandemic On Faculty Productivity And Gender Inequalities In Stem Disciplines, Monnie Mcgee, Raag Patel, Roslyn Smith, Satvik Ajmera

SMU Data Science Review

Women and minorities within STEM disciplines historically encounter obstacles in academic advancement, a situation compounded by the COVID-19 pandemic due to the imposition of additional responsibilities like caregiving. This study meticulously probes into the pandemic's influence on traditional academic productivity metrics – specifically publication and submission frequency, citation volume, and leadership in scholarly entities, by employing Natural Language Processing to extract and analyze data from key journals within various scientific domains. A critical revelation from the research indicates a notable downturn in publication activity during 2021, potentially attributed to pandemic-induced disruptions, with a compensatory surge observed in 2022. Although a …

How Are Oregon's Rural Indigenous Communities Overcoming Water Access Issues?, Tyren John Thompson

Dissertations and Theses

This study investigates how water insecurity affects Indigenous communities in Grand Ronde, Warm Springs, and Umatilla, Oregon, through loss of clean drinking water, access to culturally significant foods, and exposure to pollution. Each community offers innovative solutions drawing on their Indigenous knowledge to overcome water supply challenges. Communities with more resources are better equipped to cope with water insecurity and environmental degradation.

Tiny Drifters Amidst Global Change: Examining Environmental Drivers, Trophic Impacts, And Management Strategies Of Estuarine Plankton Communities In The Anthropocene, Taylor Nicole Dodrill

Dissertations and Theses

Plankton productivity supports estuarine food webs, and has been tied to the success of fisheries, macroinvertebrates, and cultured shellfish yields. Climate change and alterations to nutrient loads are thought to be influencing plankton assemblages, with toxin-producing harmful algal blooms (HABs) on the rise and nutritional quality of plankton declining globally. These shifts in plankton communities may contribute to low biomass yields and toxin-based closures of important fisheries. The objectives of this dissertation are to identify environmental drivers, trophic impacts, and management strategies to understand and respond to changing estuarine plankton communities. To address these objectives, I used a combination of …

Overcoming Foreign Language Anxiety In An Emotionally Intelligent Tutoring System, Daneih Ismail

College of Computing and Digital Media Dissertations

Learning a foreign language entails cognitive and emotional obstacles. It involves complicated mental processes that affect learning and emotions. Positive emotions such as motivation, encouragement, and satisfaction increase learning achievement, while negative emotions like anxiety, frustration, and confusion may reduce performance. Foreign Language Anxiety (FLA) is a specific type of anxiety accompanying learning a foreign language. It is considered a main impediment that hinders learning, reduces achievements, and diminishes interest in learning.

Detecting FLA is the first step toward reducing and eventually overcoming it. Previously, researchers have been detecting FLA using physical measurements and self-reports. Using physical measures is direct …

Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin

Introduction to Research Methods RSCH 202

This study aims to explore the complex implications of declining birth rates on the economy, focusing on GDP per capita as a crucial metric, and aims to uncover both potential opportunities and challenges stemming from this demographic transformation using regression analysis. Using a quantitative methodology and secondary data from OECD.stat, World Population Review, and World Bank, the study explores the relationship between declining birth rates and economic impacts. GDP per capita serves as an essential dependent variable, and it accounts for control variables such as labour force participation, literacy, and education levels, child dependence ratio, and physical capital. Past studies …

The Perception Of Natural Resource Management In Nebraska: Efforts For Cross-Boundary Collaborative Management, Daniel Morales

School of Natural Resources: Dissertations, Theses, and Student Research

Nebraska’s agricultural landscapes are rapidly changing, affecting natural resources and their successful management. I utilized two surveys and scenario planning (Chapters 1: statewide survey, 2: local survey, and 3: scenario-planning workshop) to investigate attitudes and perceptions of natural resource management and cross-boundary collaboration. My first objective focused on determining what prevents Nebraskans from addressing natural resources challenges, considering demographics amongst generations and the type of areas they live in (rural versus urban). The second objective focused on whether landowners engaged with their community in managing natural resources. The third objective was to develop alternative future scenarios for the Denton Hills …

Perception Of Bias In Chatgpt: Analysis Of Social Media Data, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Ahmed El Noshokaty, Tareq Nasralah

Computer Information Systems Faculty Publications

In this study, we aim to analyze the public perception of Twitter users with respect to the use of ChatGPT and the potential bias in its responses. Sentiment and emotion analysis were also analyzed. Analysis of 5,962 English tweets showed that Twitter users were concerned about six main types of biases, namely: political, ideological, data & algorithmic, gender, racial, cultural, and confirmation biases. Sentiment analysis showed that most of the users reflected a neutral sentiment, followed by negative and positive sentiment. Emotion analysis mainly reflected anger, disgust, and sadness with respect to bias concerns with ChatGPT use.

Human Dimensions Of Woody Encroachment Management In Nebraska, Emily Rowen

School of Natural Resources: Dissertations, Theses, and Student Research

Woody plant encroachment (WPE) is a social-ecological problem that will challenge conservation professionals and agricultural producers to adapt their management strategies. This research first examined WPE from the perspective of individual conservation professionals through an online survey. Conservation professionals’ attitudes about adaptation to vegetation transitions, such as WPE, were of interest because these attitudes are one measure of how prepared this group is to respond to WPE. Hypothesized predictors of adaptation attitude were tested through linear regression modeling. These predictors included ecological change, observation of WPE, or risk perception. It was found that risk perception was the strongest predictor of …

Metrics For Comparison Of Complex Networks, Clarissa Reyes

Open Access Theses & Dissertations

Heuristic network statistics are used as a preliminary approach to identify change across networks. In networks where there is known node correspondence (KNC), conventional network comparison methods include taking a norm of the difference matrix, or calculating dissimilarity measures like DeltaCon and cut distance. Since different KNC measures provide varying insight to the network comparison problem, we propose employing Rank Score Characteristic Functions (RSCFs) and the rank-score process as a method for reaching a consensus when ranking quantified change across multiple pairs of networks â?? which is particularly useful for ranking change across subpopulations or subgraphs. Additionally, we propose a …

Integrating Machine Learning Methods For Medical Diagnosis, Jazmin Quezada

Open Access Theses & Dissertations

Abstract:The rapid advancement of machine learning techniques has revolutionized the field of medical diagnosis by offering powerful tools to analyze complex data sets and make accurate predictions. In this proposed method, we present a novel approach that integrates machine learning and optimization models to enhance the accuracy of medical diagnoses. Our method focuses on fine-tuning and optimizing the parameters of machine learning algorithms commonly used in medical diagnosis, such as logistic regression, support vector machines, and neural networks. By employing optimization techniques, we systematically explore the parameter space of these algorithms to discover the most optimal configurations. Moreover, by representing …

Triple Helix: Ai-Artist-Audience Collaboration In A Performative Art Experience, Xuedan Zou

Dartmouth College Master’s Theses

Imagine an art exhibition that morphs its content according to the audience’s experience like a chameleon, reflecting the audience’s mind and culture and turning the artist’s exhibition into the viewer’s. But when the viewers leave, the work fades back to the creator’s original work and waits for the next audience. In this project, my team introduced an interactive exhibition called "Triple Helix," where audience members were provided the opportunity to alter the artworks created by the artist, thus imbuing them with their own perspectives. This interactive exhibition was held at three physical-locations and online, and a comprehensive user study was …

The Broadwater Formation (Pliocene) Of Nebraska And Southeastern Wyoming, Robert F. Diffendal Jr., James B. Swinehart

Robert F. Diffendal, Jr., Publications

The Broadwater Formation, initially defined in 1945, is a Pliocene-aged coarse-grained alluvial deposit in Nebraska and southeastern Wyoming. It is characterized by a complex stratigraphic history and debated geologic interpretations. The formation is a rich resource of groundwater for the citizens of Nebraska and the Central Great Plains. We aim to synthesize and redefine the Broadwater Formation, shedding light on its distribution, geological characteristics, and paleoenvironmental significance. While historical hypotheses on Broadwater Formation paleovalley trajectories suggested northwest-southeast trending valleys, later investigations proposed wind-driven erosional patterns to explain the unique topographic features observed. The Broadwater is divided into an unnamed Upper …

Last Digit Tendency: Lucky Number And Psychological Rounding In Mobile Transactions, Hai Wang, Tian Lu, Yingjie Zhang, Yue Wu, Yiheng Sun, Jingran Dong, Wen Huang

Research Collection School Of Computing and Information Systems

The distribution of digits in numbers obtained from different sources reveals interesting patterns. The well-known Benford’s law states that the first digits in many real-life numerical data sets have an asymmetric, logarithmic distribution in which small digits are more common; this asymmetry diminishes for subsequent digits, and the last digit tends to be uniformly distributed. In this paper, we investigate the digit distribution of numbers in a large mobile transaction data set with 835 million mobile transactions and payments made by approximately 460,000 users in more than 300 cities. Although the first digits of the numbers in these mobile transactions …

Combat Covid-19 At National Level Using Risk Stratification With Appropriate Intervention, Xuan Jin, Kar Way Tan

Research Collection School Of Computing and Information Systems

In the national battle against COVID-19, harnessing population-level big data is imperative, enabling authorities to devise effective care policies, allocate healthcare resources efficiently, and enact targeted interventions. Singapore adopted the Home Recovery Programme (HRP) in September 2021, diverting low-risk COVID-19 patients to home care to ease hospital burdens amid high vaccination rates and mild symptoms. While a patient's suitability for HRP could be assessed using broad-based criteria, integrating machine learning (ML) model becomes invaluable for identifying high-risk patients prone to severe illness, facilitating early medical assessment. Most prior studies have traditionally depended on clinical and laboratory data, necessitating initial clinic …