Digital Commons Network^™

Queer Formations Of The Self In Woolf And Forster, Margaret M. Bancroft

Scripps Senior Theses

This thesis examines queerness and the Bildungsroman in three novels by Virginia Woolf and E.M. Forster: Jacob’s Room (1922), Maurice (1971), and Orlando (1928).

Investigating Factors Contributing To Differences In Air Pollutants Between Metropolitan Areas In The Us, Ellen Hu

Scripps Senior Theses

Densely populated regions around the United States exhibit varying concentrations of air pollutants that can impact the health of urban populations and surrounding ecosystems. Understanding why these differences exist can be important in addressing health issues as the human population continues to increase and communities across the globe move to accommodate these trends. To investigate the impact of natural processes and anthropogenic sources on pollutant concentrations, EPA daily fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃) pollutant concentrations from seven metropolitan regions across the US for 2018-2022 were used. A Spearman Rank-Order …

Nitrate Contamination In Two California Groundwater Basins: What Creates Disparities?, Catherine Protiva

Scripps Senior Theses

Nitrate contamination is a major problem within California groundwater basins. A form of nitrogen, nitrates leach into groundwater aquifers from the surface where they remain for many decades. The most common source for the contaminant is agricultural sources like nitrogen fertilizer. Consequently, the problem is concentrated in regions of the state with a history of large-scale agricultural production. When water is pulled from contaminated basins and used as drinking water, the nitrates can cause serious negative health consequences, most commonly methemoglobinemia, also known as blue baby syndrome. In this thesis, I will examine what factors contribute to a region’s ability …

First Destination Survey 2024: For Degrees Awarded December 2023-August 2024, Hart Career Center, Illinois Wesleyan University

First Destination Survey

No abstract provided.

The Modern Way To Write A Statute Is To Tell A Story, Richard K. Neumann Jr.

Hofstra Law Faculty Scholarship

Except for the United States, the English-speaking world has been moving toward writing statutes as stories with characters and plot tensions. British statutes are the most advanced in this respect.

To illustrate the British method, the key statutes in the Mar-a-Lago Indictment are redrafted in this article to resemble the form they would take if recently enacted by Parliament. l compare the statutes and the redrafts side-by-side. And I do the same thing with two sections of the Electoral Count Act, which governs what Congress does on every January 6 following a presidential election year.

The article explains how the …

An Investigation Of Simulation Research Trends In Asian Countries From 2006 To 2021 - A Bibliometric Review, Lulu Sherif Mahmood, Felicita Livia Saldanha, Sinéad Lydon, Paul O’Connor, Dara Byrne, Caoimhe Madden

Health Professions Education

In this bibliometric review, we have examined five English-language journals to investigate the distribution and characteristics of simulation-based research in Asia from 2006 to 2021. The handsearching method was used for accessing articles from online issues. Eight variables were extracted and the frequency of each variable within 2 time frames (2012-2016; 2016 to 2021) was quantified to compare the trends. The results depicted that a majority were research publications (86.4%) from Eastern and Western Asia, with intervention (66.1%) as the primary focus and mannequin (34.7%) as the major simulation modality. There was an equal representation of healthcare professionals (47.5%) and …

Academic Well-Being In Medical Students: The Role Of Spiritual Health And Academic Hope, Zahra Taheri-Kharameh, Zohreh Khalili, Hossein Sharafi, Iman Khahan-Yazdi

Health Professions Education

Purpose. Academic well-being plays a crucial role in the success and satisfaction of medical students. However, the factors that contribute to academic well-being in this population are not well understood. This study aims to investigate the impact of spiritual health and hope on predicting academic well-being in a sample of medical students from Iran.

Method. A cross-sectional study was conducted on 180 medical students from a university in Iran. The participants completed the Spiritual Health Scale, the Hope for Education Scale and the Academic Well-being Scale. The data collection was conducted in the second semester of the academic year 2022-2023. …

Predicting Medical Laboratory Science Certification Examination Success: The Role Of Affective Performance, Jed Doxtater, Charlie P. Cruz

Health Professions Education

Purpose: This study aimed at associating the Board of Certification (BOC) pass rates with the affective performances of Medical Laboratory Science (MLS) students.

Method: Retrospective data analysis on the BOC pass rates, advanced clinical practicum (ACP) routes, affective assessment, grade point average (GPA), highest academic degree (HAD) upon graduation, years to degree completion, and gender was conducted on thirty-three (33) MLS graduates between 2017 and 2022 from a higher education institution (HEI) in Wyoming.

Results: Based on the Chi-square (X2) test, BOC was associated with HAD and affective performance, but no significant statistical association was established between …

A Comprehensive Study Of The Literature On The Implications Of Covid-19 Epidemic On Pupils' Academic Performance In The Educational System, Md Sarfaraz Alam, Milap Sharma, Waseem Ahmad, Zulquernain Mallick

Health Professions Education

BACKGROUND: The COVID-19 epidemic negatively affected every aspect of society on a global scale, including the economy, healthcare, and education. This affected "1.6 billion" students and "63 million" teachers globally, as "191 countries" closed schools nationwide.

PURPOSE: The purpose of this study is to review the state-of-the-art and emerging trends in the field of COVID-19 and student academic performance (SAP).

METHODS: A comprehensive analysis considering various factors has been utilized to evaluate the current level of research on COVID-19 and the SAP. In this study, “content analysis” approach was used for a “systematic literature review (SLR)” on …

Digital Physicians: Unleashing Artificial Intelligence In Transforming Healthcare And Exploring The Future Of Modern Approaches, Ban Salman Shukur, Mohd Khanapi Abd Ghani, Burhanuddin Bin Mohd Aboobaider

Mesopotamian Journal of Artificial Intelligence in Healthcare

Growing global awareness that attention to health care is the basis for maintaining citizens' quality of life. Health institutions seek to increase interest in electronic care services and enhance patient results by integrating artificial intelligence techniques. Artificial intelligence tools are indispensable to diagnosis, treatment, and patient care. Integrating artificial intelligence techniques into the development of the electronic healthcare environment works to enhance public health and disease prevention and provide free services to all citizens. Designing electronic platforms raises health awareness in society, provides health programs and initiatives, and reaches homes, gardens, schools, and universities through applications based on artificial intelligence. …

Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …

Conditional Constrained And Unconstrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we present the idea of conditional quantization for a Borel probability measure P on a normed space Rk. We introduce the concept of conditional quantization in both constrained and unconstrained scenarios, along with defining the conditional quantization errors, dimensions, and coefficients in each case. We then calculate these values for specific probability distributions. Additionally, we demonstrate that for a Borel probability measure, the lower and upper quantization dimensions and coefficients do not depend on the conditional set of the conditional quantization in both constrained and unconstrained quantization.

Structure Of Fine Selmer Groups In Abelian P-Adic Lie Extensions, Debanjana Kundu, Filippo Alberto Edoardo Nuccio Mortarino Majno Di Capriglio, Sujatha Ramdorai

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies fine Selmer groups of elliptic curves in abelian p -adic Lie extensions. A class of elliptic curves are provided where both the Selmer group and the fine Selmer group are trivial in the cyclotomic Z p -extension. The fine Selmer groups of elliptic curves with complex multiplication are shown to be pseudonull over the trivializing extension in some new cases. Finally, a relationship between the structure of the fine Selmer group for some CM elliptic curves and the Generalized Greenberg's Conjecture is clarified.

Flow And Stability Of Three-Dimensional Rotating Viscoelastic Jet, Daniel N. Riahi

School of Mathematical & Statistical Sciences Faculty Publications

We consider rotationally driven nonlinear viscoelastic jet. In contrast to previous unrealistic planar studies with no gravity effect, we investigate here realistic three-dimensional jet with gravity effect. Using theoretical and computational methods, we develop models for such jet and its stability and determine the solutions. We find three-dimensional jet with gravity effect leads to faster and thinner jet. For jet arc length higher than its exit diameter, our calculation with typical parameter values shows that jet radius is smaller by a factor of more than 1.4 and jet speed is higher by factor of more than 2 as are compared …

Ivermectin, Colleen Aldous, Eleftherios Gkioulekas, Philip Oldfield

School of Mathematical & Statistical Sciences Faculty Publications

No abstract provided.

Enhanced Resolution Method For Electromagnetic Vortex Imaging Based On Electromagnetic Information Theory, Da Liu, Hongyin Shi, Ting Yang, Zhijun Qiao

School of Mathematical & Statistical Sciences Faculty Publications

The electromagnetic vortex imaging possesses independent orbital angular momentum with orthogonal degrees of freedom (DoF), which implies the existence of enhanced information capacity. However, high-mode orbital angular momentum (OAM) beams have stringent generation conditions and inefficient information carrying capacity, which results in limited resolution. This paper proposes a method to combine the electromagnetic information theory (EIT) with the traditional electromagnetic vortex imaging technique, which allows one may obtain more target azimuth information. The DoF, as the main component of information, has been increased to achieve higher azimuth resolution. First, the propagation and imaging model for the electromagnetic vortex with statistical …

Optimizing Energy Consumption In Smart Homes Using Ga-Lstm, Akibor Junior Chukwuka, Bakare-Bolaji Moyosoreoluwa, Baboucarr Dibba

School of Mathematical & Statistical Sciences Faculty Publications

The need to optimize energy consumption arises from the inadequate energy supply many homes face. However, to optimize energy consumption in a home, one must be equipped with the knowledge of the energy consumption rate and energy supply rate in the home. This paper proposed the use of a Long Short-Term Memory (LSTM) model optimized by Genetic Algorithm (GA) to optimize the energy consumption in a smart home. The model was designed using 8 input variables, which were observed weather information of a given region over a span of 350 days. The data set was split into a training data …

Heuristics For Anti-Cyclotomic ℤp-Extensions, Debanjana Kundu, Lawrence C. Washington

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies Iwasawa invariants in anti-cyclotomic towers. We do this by proposing two heuristics supported by computations. First we propose the Intersection Heuristics: these model “how often” the p-Hilbert class field of an imaginary quadratic field intersects the anti-cyclotomic tower and to what extent. Second we propose the Invariants Heuristics: these predict that the Iwasawa invariants 𝜆 and 𝜇 usually vanish for imaginary quadratic fields where p is non-split.

2024 Viewbook, Office Of Admissions

Viewbook

At IMSA, you will be part of a community of 652 diverse students passionate about learning. Located in suburban Aurora, IMSA’s campus consists of seven residence halls spread across 97 acres. While living and learning on campus, you’ll make new friends, encounter new ideas, and learn to live independently. You will also have the opportunity to explore over 85 clubs, organizations, and IHSAsponsored co-curricular and athletic programs. IMSA provides a safe, nurturing environment. Professional Resident Counselors (RCs) live in each hall and will help you navigate your home away from home through the Residential Life Curriculum. Through this curriculum, you’ll …

Riemannian Frameworks For The Harmonization Of Resting-State Functional Mri Scans, Nicolas Honnorat, Sudha Seshadri, Ron Killiany, John Blangero, David C. Glahn, Peter T. Fox, Mohamad Habes

School of Medicine Publications

Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols can significantly impact MRI scans. The development of statistical methods able to reduce this variability without altering the relevant information in the scans, often coined harmonization methods, has been the topic of an increasing research effort supported by the recent growth of publicly available neuroimaging data sets and new possibilities for combining them to achieve greater statistical power. In this work, we focus on the challenges specifically raised by the harmonization of resting-state functional MRI scans. We propose to harmonize resting-state fMRI scans by reducing the …

A Survey On Artificial Intelligence In Cybersecurity For Smart Agriculture: State-Of-The-Art, Cyber Threats, Artificial Intelligence Applications, And Ethical Concerns, Guma Ali, Maad M. Mijwil, Bosco Apparatus Buruga, Mostafa Abotaleb, Ioannis Adamopoulos

Mesopotamian Journal of Computer Science

Wireless sensor networks and Internet of Things devices are revolutionizing the smart agriculture industry by increasing production, sustainability, and profitability as connectivity becomes increasingly ubiquitous. However, the industry has become a popular target for cyberattacks. This survey investigates the role of artificial intelligence (AI) in improving cybersecurity in smart agriculture (SA). The relevant literature for the study was gathered from Nature, Wiley Online Library, MDPI, ScienceDirect, Frontiers, IEEE Xplore Digital Library, IGI Global, Springer, Taylor & Francis, and Google Scholar. Of the 320 publications that fit the search criteria, 180 research papers were ultimately chosen for this investigation. The review …

Segment Anything: A Review, Firas Hazzaa, Innocent Udoidiong, Akram Qashou, Sufian Yousef

Mesopotamian Journal of Computer Science

Segment Anything (SA) is a state-of-the art method for universal object segmentation, which does not need task-specific training. Herein, we emphasize that SA can overcome the limitations of traditional segmentation frameworks based on requiring extensive manually annotated datasets and predefined architectures, as extensively documented in this review. SB supercharges performance and reduces cost by combining Mutual Information learning with an Efficient Transformer architecture, benefiting from a substantially larger pool of in-the-wild data. In this paper we review SA and its specific key innovations generality, resource boundedness, and scalability to large datasets. We also face obstacles such as data biases, computational …

An Optimized Model For Liver Disease Classification Based On Bpso Using Machine Learning Models, El-Sayed M. El-Kenawy, Nima Khodadadi, Abdelhameed Ibrahim, Marwa M. Eid, Ahmed M. Osman, Ahmed M. Elshewey

Mesopotamian Journal of Computer Science

Liver disease (LD) is a world health concern that requires accurate diagnostic methods. This study proposes an optimized machine learning model (ML) based on BPSO for LD classification using a shared public dataset from kaggle Indicates to liver patients from India. The paper used six ML models such as Random Forest (RF), Support Vector Machine (SVM), Dummy Classifier (DC), Extra Trees Classifier (ET), K-Nearest Neighbors (KNN), and Logistic Regression (LT) to evaluate the performance. Through observations we detected that ET achieved an accuracy of 79.82%. The BPSO hyperparameter optimization optimized ET to enhance accuracy to reach 85%. The paper used …

Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi

Mesopotamian Journal of Artificial Intelligence in Healthcare

The accurate prediction and classification of medical data, such as Hepatitis C, play a significant role in upgrading symptomatic accuracy and treatment planning. This study utilized progressed machine learning algorithms, including RF, SVR, and Gradient Boosting, to analyze features and predict outcomes viably. By coordination robust preprocessing strategies and feature engineering, the models tended to missing values and categorical transformations, enabling exact predictions from complex datasets. The models accomplished high accuracy and unwavering quality in execution, as prove by comparative measurements and validation results. These discoveries highlight the potential of machine learning in increasing clinical decision-making and emphasize the require …

Hybrid Model Approaches For Accurate Time Series Predicting Of Covid-19 Cases, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Benson Turyasingura

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study compares the performance of ARIMA, LSTM, and hybrid models in predicting COVID-19 cases and analyzing forecast errors. Utilizing real-world data, the models were assessed for accuracy and trend prediction over numerous months. Heatmaps of prediction errors revealed that the hybrid model reliably outperformed ARIMA and LSTM by accomplishing lower error extents. The findings highlight the preferences of combining statistical and deep learning approaches for time series predicting. The results contribute to progressing predicting accuracy, which is basic for pandemic response arranging and public health administration.

A Comprehensive Review On Cryptographic Techniques For Securing Internet Of Medical Things: A State-Of-The-Art, Applications, Security Attacks, Mitigation Measures, And Future Research Direction, Wamusi Robert, Asiku Denis, Adebo Thomas, Aziku Samuel, Simon Peter Kabiito, Zaward Morish, Guma Ali

Mesopotamian Journal of Artificial Intelligence in Healthcare

As healthcare becomes increasingly dependent on the Internet of Medical Things (IoMT) infrastructure, it is essential to establish a secure system that guarantees the confidentiality and privacy of patient data. This system must also facilitate the secure sharing of healthcare information with other parties within the healthcare ecosystem. However, this increased connectivity also introduces cybersecurity attacks and vulnerabilities. This comprehensive review explores the state-of-the-art in the IoMT, security requirements in the IoMT, cryptographic techniques in the IoMT, application of cryptographic techniques in securing the IoMT, security attacks on cryptographic techniques, mitigation strategies, and future research directions. The study adopts a …

Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction …

Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer

Research outputs 2022 to 2026

Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …

On Design Load Prediction And Extreme Response Modelling Of Floating Offshore Renewable Energy Structures, Tom Tosdevin

School of Engineering, Computing and Mathematics Theses

FLOATING offshore renewable energy (FORE) is a marginal industry and as such cost reductions are essential in order for it to become competitive with other forms of electricity generation. Design practices for evaluating the extreme responses of FORE devices are still under consideration by standards authorities, thus methods that enable potential speeding up of the design and development phases, particularly physical model testing are needed. Probabilistic design approaches have proved effective in bringing down costs in the aerospace and automobile industries and so provide a potential route to viability by allowing partial safety factors to be reduced. However, the scarcity …

Investigation And Modelling Of A Cortical Learning Algorithm In The Neocortex, Damir Dobric

School of Engineering, Computing and Mathematics Theses

Many algorithms today provide a good machine learning solution in the specific problem domain, like pattern recognition, clustering, classification, sequence learning, image recognition, etc. They are all suitable for solving some particular problem but are limited regarding flexibility. For example, the algorithm that plays Go cannot do image classification, anomaly detection, or learn sequences. Inspired by the functioning of the neocortex, this work investigates if it is possible to design and implement a universal algorithm that can solve more complex tasks more intelligently in the way the neocortex does. Motivated by the remarkable replication degree of the same and similar …