Digital Commons Network^™

Teaching Health Justice And Reimagining Narratives Of Place Through Community-Driven Science Practices, Tammie Visintainer

Faculty Research, Scholarly, and Creative Activity

This study explores how a biology teacher from a summer science program engaged high school students of color in a three-week science unit exploring community health at the intersection of history, race, place, and power. The goal of this study is to better understand what community-driven science looks like in a science classroom when a health equity unit is guided by a biology teacher who engages the socio-historical, political, and relational aspects of community structure and agency. Using student and instructor interviews, program observations, and student artifacts, I examine how the instructor's positioning as a Black woman scientist shaped her …

The Critical Role Of Happiness In Education: Resilience, Retention, And What Happy Teachers Do Differently, Jill Marie Hayes White

Dissertations and Theses @ UNI

Teachers are unhappy, stressed, and leaving the field at an alarming rate. This paper analyzes how teacher happiness is related to resilience and retention. It also looks for patterns that identify what happy teachers do differently at work. To complete this investigation, current K-12 public school teachers throughout Iowa completed electronic surveys that assessed their happiness, resilience, and work life. These surveys included the Subjective Happiness Scale (Lyubomirsky & Lepper, 1999), the Brief Resilience Scale (Smith, et al., 2008), and 14 additional survey questions created by the researcher. Correlational, comparative, and descriptive analyses were completed to examine potential relationships and …

Mapping For Impact: Actionable Spatial Literacy Through Counter-Mapping, Rachel Hansen

Dissertations and Theses @ UNI

Counter-mapping is a technique that young people can use to take informed action on community issues through the mapping process. This mixed-methods study examined how ninth-graders in a large urban district in Iowa developed spatial thinking skills while engaging in counter-mapping in their community and the extent to which they used those maps to take informed action. A nine-week learning progression for counter-mapping scaffolded progress variables across three different spatial thinking standards and one inquiry standard. Findings indicated that students improved throughout the learning progression, but some needed teacher support to conduct spatial inquiries. Chances of reaching the upper anchor …

A Graduate Recital In Piano, Heather Gillis

Dissertations and Theses @ UNI

Heather Gillis presented a full graduate piano recital on Friday, March 10, 2023. The recital was performed at 8:00 p.m. in Davis Hall in the Gallagher-Bluedorn Performing Arts Center at the University of Northern Iowa. This recital was given in partial fulfillment of the Master of Music degree in Piano Performance and Pedagogy. The program consisted of works by Sergei Prokofiev, Robert Schumann, and Joseph Haydn. This abstract contains further discussion of performed works.

Catalog Revision Gen Ed, Academic Affairs

Executive Actions

No abstract provided.

Modification Of Cellulose Ether With Organic Carbonate For Enhanced Thermal And Rheological Properties: Characterization And Analysis, Ghulam Abbas, Abdul H. Tunio, Khalil R. Memon, Aftab A. Mahesar, Faisal H. Memon, Ghazanfer R. Abbasi

Research outputs 2022 to 2026

Reduction in viscosity at higher temperatures is the main limitation of utilizing cellulose ethers in high thermal reservoir conditions for petroleum industry applications. In this study, cellulose ether (hydroxyethyl methyl cellulose (HEMC)) is modified using organic carbonates, i.e., propylene carbonate (PC) and diethyl carbonate (DEC), to overcome the limitation of reduced viscosity at high temperatures. The polymer composites were characterized through various analytical techniques, including Fourier-transform infrared (FTIR), H-NMR, X-ray diffraction (XRD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), -potential measurement, molecular weight determination, and rheology measurements. The experimental results of structural and morphological characterization confirm …

Lost Circulation Control During Drilling And Completion In Complex Formations, Chong Lin, Arash D. Taleghani, Chengyuan Xu, Zhenjiang You

Research outputs 2022 to 2026

Well drilling is a common method for Earth exploration, underground mineral resource extraction, and geological storage of nuclear waste and carbon dioxide. Drilling fluid circulates in the well during drilling, cooling the drill bit, transporting rock cuttings, preventing wellbore collapse, and balancing formation pressure. Lost circulation occurs when less fluid returns from the wellbore than is pumped into it, resulting in economic losses due to drilling fluid wastage and nonproductive time. Untreated losses can cause well control issues, poor hole cleaning, pack-offs, and stuck pipe, impairing normal drilling. Lost circulation incidents are more likely to occur with the increasing share …

Edna Metabarcoding Of Avocado Flowers: ‘Hass’ It Got Potential To Survey Arthropods In Food Production Systems?, Joshua H. Kestel, Philip W. Bateman, David L. Field, Nicole E. White, Rose Lines, Paul Nevill

Research outputs 2022 to 2026

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection of these managed and unmanaged taxa. Here, …

A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung

Research outputs 2022 to 2026

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …

An Integrative Review Of Project Portfolio Management Literature: Thematic Findings On Sustainability Mindset, Assessment, And Integration, Masoud Aghajani, Gesa Ruge, Kam Jugdev

Research outputs 2022 to 2026

Sustainability integration in project portfolio management helps shape strategic, organizational, and project-based contexts. The authors conducted a structured literature review from 2000 to 2021 and developed a novel integrative framework presenting a holistic view highlighting three substantive research themes: sustainability mindset, sustainability assessment, and sustainability integration in project portfolio processes. Noteworthy progress has been made at the strategic and portfolio levels toward framing a sustainability mindset (definition, values, and principles) and developing frameworks/tools for sustainability assessment and project portfolio selection. However, areas for more research include integrating sustainability into project portfolio processes, reporting, and organizational learning for portfolio improvement.

What Do Mathematics Lessons Look Like? Analyses Of Primary Students’ Drawings, Benjamin Rott, Laura Barton, Vesife Hatisaru

Research outputs 2022 to 2026

The use of student drawings to assess their experiences and beliefs about teaching and learning of mathematics has become almost a regular research method – especially when working with young students who may not express themselves well, for example, in self-report questionnaires. These methods, nevertheless, need to be improved regarding their objectivity and validity. By building on the existing research, in this study, we focus on objectivity and validity issues in drawing-based methods. We use a drawing-based instrument: Draw A Mathematics Classroom (DAMC) and present 104 fourth-grade students to draw a picture of their regular mathematics lessons. We especially aim …

Invisible Women: Gender Representation In High School Science Courses Across Australia, Kathryn Ross, Shanika Galaudage, Tegan Clark, Nataliea Lowson, Andrew Battisti, Helen Adam, Alexandra K. Ross, Nici Sweaney

Research outputs 2022 to 2026

The visibility of female role models in science is vital for engaging and retaining women in scientific fields. In this study, we analyse four senior secondary science courses delivered across the states and territories in Australia: Biology, Chemistry, Environmental Science, and Physics. We compared male and female representation within the science courses by examining the mentions of male and female scientists along with the context of their inclusions in the syllabuses. We find a clear gender bias with only one unique mention of a female scientist. We also find a clear Eurocentric focus and narrow representation of scientists. This bias …

An Artificial Therapist (Manage Your Life Online) To Support The Mental Health Of Youth: Co-Design And Case Series, Aimee-Rose Wrightson-Hester, Georgia Anderson, Joel Dunstan, Peter M. Mcevoy, Christopher J. Sutton, Bronwyn Myers, Sarah Egan, Sara Tai, Melanie Johnston-Hollitt, Wai Chen, Tom Gedeon, Warren Mansell

Research outputs 2022 to 2026

Background: The prevalence of child and adolescent mental health issues is increasing faster than the number of services available, leading to a shortfall. Mental health chatbots are a highly scalable method to address this gap. Manage Your Life Online (MYLO) is an artificially intelligent chatbot that emulates the method of levels therapy. Method of levels is a therapy that uses curious questioning to support the sustained awareness and exploration of current problems. Objective: This study aimed to assess the feasibility and acceptability of a co-designed interface for MYLO in young people aged 16 to 24 years with mental health problems. …

Hybrid Warfare And Disinformation: A Ukraine War Perspective, Sascha-Dominik Dov Bachmann, Dries Putter, Guy Duczynski

Research outputs 2022 to 2026

Misinformation, disinformation and mal information are part of the information disorder construct, dominating the information warfare domain. These are key enablers associated with grey zone operations, and an integral part of current adversaries' and competitors' hybrid warfare tool kit. Disinformation, in combination with influence operations, also plays an important role within the concept of hybrid warfare; both from a threat–and own resilience perspective. This article reflects on these information warfare tools and their application by Russia in the current Russo-Ukraine war, offering potentially considerable force multipliers in the information domain for the Russian aggressor. Hybrid warfare and associated threats, specifically …

Spatial Heterogeneity In Sediment And Carbon Accretion Rates Within A Seagrass Meadow Correlated With The Hydrodynamic Intensity, Jiarui Lei, Rachel Schaefer, Phil Colarusso, Alyssa Novak, Juliet C. Simpson, Pere Masqué, Heidi Nepf

Research outputs 2022 to 2026

The majority of the carbon stored in seagrass sediments originates outside the meadow, such that the carbon storage capacity within a meadow is strongly dependent on hydrodynamic conditions that favor deposition and retention of fine organic matter within the meadow. By extension, if hydrodynamic conditions vary across a meadow, they may give rise to spatial gradients in carbon. This study considered whether the spatial gradients in sediment and carbon accretion rates correlated with the spatial variation in hydrodynamic intensity within a single meadow. Field measurements were conducted in three depth zones across a Zostera marina L. (eelgrass) meadow in Nahant …

Mobile Big Data Analytics Using Deep Learning And Apache Spark, Muhammad Azeem, Bassam M. Abualsoud, Dimuthu Priyadarshana

Mesopotamian Journal of Big Data

The new mobile big data is the outcome of the widespread use of mobile devices like smartphones and IoT devices. Without employing suitable analytical and learning methodologies to extract crucial facts and hidden designs from the data, collecting MBDs is not economically viable. We drew on the work of other academics who published their findings between 2015 and 2021 for this analysis. This white paper gives an introduction to deep learning in MBD analysis and a straightforward training exercise, and it verifies the viability of customizable learning architectures via Apache Spark. Certain deep learning tasks, in particular, are carried out …

Large Scale Data Using K-Means, Raheela Zaib, Ourlis Ourabah

Mesopotamian Journal of Big Data

Because of the exponential growth of high-layered datasets, conventional database querying strategies are inadequate for extracting useful information, and analysts must now devise novel techniques to meet these demands. Such massive articulation data results in a plethora of new computational triggers as a result of both the rise in data protests and the increase of elements/ascribes. Preprocessing the data with a reliable dimensionality reduction method improves the efficacy and precision of mining operations on densely layered data. Therefore, we have compiled the opinions of numerous academics. Cluster analysis is a data analysis tool that has recently acquired prominence in a …

Effectual Text Classification In Data Mining: A Practical Approach, Israa Ezzat, Alaa Wagih Abdulqader, Atheel Sabih Shaker

Mesopotamian Journal of Big Data

Text classification is the process of setting records into classes that have already been set up based on what they say. It automatically puts texts in natural languages into categories that have already been set up. Text classification is the most crucial part of text retrieval systems, which find texts based on what the user requests, and text understanding systems, which change the text in some way, like by making summaries, answering questions, or pulling out data. Existing algorithms that use supervised learning to classify text automatically need enough examples to learn well. The algorithms for data mining are used …

The Data-Driven Future Of Healthcare: A Review, Muhammad Miftahul Amri, Saad Abbas Abed

Mesopotamian Journal of Big Data

The future of disease detection, treatment, and prevention may very well lie in data-driven healthcare. Here, we take stock of where things stand and highlight certain emerging issues and long-standing difficulties. We looked at all the research that has been published on the topic of data-driven healthcare decision-making. Our research shows that the use of data in healthcare has already improved patient care and results. However, there are substantial obstacles that must be overcome, such as the need to more effectively integrate data from multiple sources, as well as issues with data quality, privacy, and security. Furthermore, healthcare data use …

A Novel Approach Of Reducing Energy Consumption By Utilizing Big Data Analysis In Mobile Cloud Computing, Mostafa Abdulghafoor Mohammed, Nicolae Țăpuș

Mesopotamian Journal of Big Data

With the rapid proliferation of smart mobile devices and increasing adoption of cloud computing services, energy efficiency has become an important issue in mobile cloud environments. High energy consumption not only results in higher operational costs but also creates sustainability concerns related to cloud infrastructure and services. This paper proposes leveraging big data techniques such as machine learning and predictive analytics to optimize resource allocation and reduce energy consumption in mobile cloud computing. The massive amount of data on factors like user behavior, mobility patterns, network availability, and resource utilization can provide key insights to improve energy efficiency. We present …

Optimizing Big Data Analytics For Reliability And Resilience: A Survey Of Techniques And Applications, El-Houcine El Baqqaly, Alaa Hussein Khaleel

Mesopotamian Journal of Big Data

The advent of big data has revolutionized various industries, enabling organizations to make data- driven decisions and gain valuable insights. However, the sheer volume, velocity, and variety of big data pose significant challenges in ensuring the reliability and resilience of big data analytics pipelines. In this context, optimization techniques play a crucial role in enhancing the reliability and resilience of big data analytics. This paper provides a comprehensive survey of optimization techniques for reliable and resilient big data analytics. The paper first discusses the motivation for optimizing big data analytics for reliability and resilience. Then, it presents a detailed overview …

Navigating The Void: Uncovering Research Gaps In The Detection Of Data Poisoning Attacks In Federated Learning-Based Big Data Processing: A Systematic Literature Review, Mohammad Aljanabi, Hijaz Ahmad

Mesopotamian Journal of Big Data

This systematic literature review scrutinizes the landscape of research at the intersection of federated learning, big data processing, and data poisoning attacks. Employing a meticulous search strategy across multiple databases, the studyunveils a surge in annual scientific production, emphasizing a growing interest in federated learning and related fields. However, a critical research gap becomes evident during the investigation of data poisoning attacks specifically in the context of federated learning when processing big data. The most relevant keywords and a visually compelling word cloud further illuminate the prevailing themes and emphases within the literature, emphasizing the lack of explicit focus on …

Levels Of Autotrophy And Heterotrophy In Mesophotic Corals Near The End Photic Zone, Amy Carmignani, Veronica Z. Radice, Kathryn M. Mcmahon, Alex I. Holman, Karen Miller, Kliti Grice, Zoe Richards

Biological Sciences Faculty Publications

Mesophotic corals live at ~30-150 m depth and can sustain metabolic processes under light-limited conditions by enhancing autotrophy through specialized photoadaptations or increasing heterotrophic nutrient acquisition. These acclimatory processes are often species-specific, however mesophotic ecosystems are largely unexplored and acclimation limits for most species are unknown. This study examined mesophotic coral ecosystems using a remotely operated vehicle (Ashmore Reef, Western Australia at 40–75m depth) to investigate the trophic ecology of five species of scleractinian coral (from genera Leptoseris, Pachyseris, and Craterastrea) using stable isotope analyses (δ¹³C and δ¹⁵N) of host and symbiont tissues …

Discussing Artificial Intelligence's Role In Combatting The Covid-19 Pandemic: A Review, Rusul Ali Radhi

Mesopotamian Journal of Artificial Intelligence in Healthcare

The COVID-19 pandemic is considered one of the most dangerous diseases that have emerged in recent years, as it began at the end of 2019 in China and quickly spread to become a severe epidemic. This virus has become, in a short period of time, threatening millions of the earth's populations, and infected individuals show symptoms that may lead to the loss of their lives. In this article, the author concentrates on the significance and methods of artificial intelligence strategies in facing COVID-19 and the primary role of these technologies. AI techniques have been applied in various areas, including creating …

Operating Artificial Intelligence To Assist Physicians Diagnose Medical Images: A Narrative Review, Oluwaseun Adelaja, Hussein Alkattan

Mesopotamian Journal of Artificial Intelligence in Healthcare

Medical image diagnostics is crucial to healthcare since it aids in the diagnosis and treatment of a variety of diseases and conditions. However, the process is time-consuming and prone to human error. In recent years, artificial intelligence has been a powerful tool for enhancing medical imaging diagnosis. Using AI algorithms for medical picture interpretation has the potential to revolutionise the field by improving accuracy, efficacy, and standardization. These algorithms can quickly sift through enormous amounts of medical imaging, finding anomalies, quantifying features, and providing useful information to help medical professionals make judgments. AI-based systems can be used to track the …

Treating Psychological Depression Utilising Artificial Intelligence: Ai For Precision Medicine- Focus On Procedures, Marwa M. Eid, Wang Yundong, George Benneh Mensah, Pramila Pudasaini

Mesopotamian Journal of Artificial Intelligence in Healthcare

Depression is a common and complex mental health condition that affects millions of people in the world. Medical advice, medications, and constant medical supervision by a specialist are common components of traditional treatment methods. Recently, there has been a growing interest in the potential of artificial intelligence to improve the diagnosis, monitoring, and treatment of depression. The potential of artificial intelligence algorithms has been demonstrated in the development of chatbots, or virtual agents, that can provide treatment, assistance, and support to individuals with depression. These artificial intelligence (AI) systems can simulate therapy sessions, offer strategies, monitor progress in treatment phases, …

Determinants Of Intention To Use E-Wallet: Personal Innovativeness And Propensity To Trust As Moderators, Madugoda Gunaratnege Senali, Mohammad Iranmanesh, Fatin Nadzirah Ismail, Noor Fareen Abdul Rahim, Mana Khoshkam, Maryam Mirzaei

Research outputs 2022 to 2026

This study aims to investigate the determinants of intention to use e-wallets. Drawing on the technology acceptance model (TAM), the conceptual framework was developed. The study extends the TAM in the context of e-wallets, by testing the influences of product-related factors namely perceived compatibility, perceived risk, and perceived emotions and investigating the moderating impacts of personal innovativeness and propensity to trust. To conduct an empirical study, the data were collected from Malaysian individuals with no experience with e-wallets using an online survey. Data from 374 participants were obtained and analyzed using the partial least squares technique. The results showed that …

Mapping For Accountability: Decolonizing Land Acknowledgment Initiatives, Salma Monani, Sarah E. Gilsoul

Environmental Studies Faculty Publications

What does it mean to map Indigenous presence onto lands that have been appropriated by settler colonial nation states? This chapter examines the challenges and potentials of re-inscribing Indigenous land relations through a digital mapping project, Indigenous Pennsylvania: Past, Present and Future. Situating itself within the growing scholarship of Indigenous cartographies, the chapter presents Indigenous Pennsylvania as an example of d-ecomedia, a shorthand we offer for ecomedia projects that foreground decolonial methodologies. Such methodologies prompt us to attend to a storied sense of Indigenous place-based relations through attention to Indigenous spatial and temporal modes of mediation.

Covid-19 Two Years On: A Review Of Covid-19-Related Empirical Research In Major Tourism And Hospitality Journals, Songshan (Sam) Huang, Xuequn Wang

Research outputs 2022 to 2026

Purpose: This study aims to provide a timely review of the COVID-19-related empirical research published in 19 quartile one (Q1) and quartile two (Q2) tourism and hospitality journals in social science citation index (SSCI).

Design/methodology/approach: A total of 407 COVID-19-related empirical papers were collected from the 19 SSCI Q1 and Q2 tourism and hospitality journals via Scopus database. Thematic content analysis was supplemented with Leximancer software to identify the research themes/subthemes, research methods and countries/regions of research.

Findings: The study found studies of COVID-19’s impact on consumer behaviour predominate in number, followed by studies on response actions and recovery strategies, …

Long Future Frame Prediction Using Optical Flow Informed Deep Neural Networks For Enhancement Of Robotic Teleoperation In High Latency Environments, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam

Research outputs 2022 to 2026

High latency in teleoperation has a significant negative impact on operator performance. While deep learning has revolutionized many domains recently, it has not previously been applied to teleoperation enhancement. We propose a novel approach to predict video frames deep into the future using neural networks informed by synthetically generated optical flow information. This can be employed in teleoperated robotic systems that rely on video feeds for operator situational awareness. We have used the image-to-image translation technique as a basis for the prediction of future frames. The Pix2Pix conditional generative adversarial network (cGAN) has been selected as a base network. Optical …