Digital Commons Network^™

Push-Pull Farming System Helps Insure Smallholder Maize Production Under Climate Change, Yann Clough, Wilhelm May, Timothy Luttermoser, Dickens Nyagol, Nikolaos Alexandridis, Frank Chidawanyika, Mattias Jonsson, Charles A.O. Midega, Katja Poveda, Zeyaur R. Khan

All Peer-Reviewed Publications

Agroecological approaches harnessing in-field biodiversity have been highlighted as a sustainable way to reduce yield gaps, but long-term assessments of their ability to buffer production from weather extremes and increasing interannual and intraseasonal climate variability are scarce. Here, we analyze a 12-year dataset from 642 control vs. push-pull maize field pairs in western Kenya, where long-term climate trends include increasing temperatures and intensifying drought and rainfall. In push-pull, maize is intercropped with a fodder legume that improves soil fertility, suppresses weeds, and deters pests, and is bordered with fodder grasses attracting and suppressing the pests. We assess interactions between push-pull …

Constitutional Limits On Occupational Licensing Bans As Collateral Consequences Of A Criminal Conviction, Imran Rabbani

Student Works

No abstract provided.

An Assessment Of Carbon Dioxide Removal Potential From Stormwater Ponds Using Concrete-Based Materials, Yu-Hsuan Tai

Theses and Dissertations (Comprehensive)

Stormwater ponds (SWPs) are engineered stormwater infrastructure known to be major greenhouse gas (GHG) emitters, including carbon dioxide (CO₂). Concrete-based materials have great potential to capture CO₂ as carbonate minerals (CaCO₃), through aqueous carbonation, driven by their alkaline nature and high portlandite (Ca(OH)₂) content. However, the mechanistic understanding of how specific parameters including mass, surface area, and degradation of calcium silicate hydrate (C-S-H) phases collectively control carbonation kinetics and CO₂ uptake under dynamically evolving conditions remains underexplored. Laboratory-scale experiments were conducted to evaluate the effects of cement dosage, particle surface area, and …

Gimmick Leadership, George Padilla

Faculty Publications

In the 1960’s, “Gypsy,” a musical movie classic premiered about a domineering mother who sought self-glorification by pushing her young daughter into stripping. The young daughter, Gypsy, learned the trick of the trade from veteran strippers in a song—“You Gotta Have A Gimmick.”

While education has always been filled with fads and slogans, today, educational leaders loudly proclaim, “College Ready”/”College Started”/”College Complete”/Career Ready.” For many educational leaders, these are gimmick slogans because academic achievement remains low and many students are arriving at college academically unprepared—but, now, possibly with hollow college credits and at greater risk of failing. Our nation …

Southern Adventist University Undergraduate Catalog 2026-2027, Southern Adventist University

Catalog, Undergraduate

Southern Adventist University's undergraduate catalog for the academic year 2026-2027.

Southern Adventist University Graduate Catalog 2026-2027, Southern Adventist University

Catalog, Graduate

Southern Adventist University's graduate catalog for the academic year 2026-2027.

Sexual Di(Et)Morphism: Using Experimental Evolution To Test Whether Resource Partitioning Promotes Divergence Of The Sexes In Drosophila Melanogaster, Owen A. Jamieson

Theses and Dissertations (Comprehensive)

Sexual dimorphism has been a long-studied phenomenon in the field of evolutionary biology. Usually, these differences in morphology, physiology and/or behaviour between the sexes are studied through the parsimonious lens of sexual selection. However, there are natural history cases where this lens does not seem applicable. Some species show sex specific morphological traits whose presence may not be due to a direct benefit to reproduction, but a difference in how each sex interacts with the environment and differing selective pressures from the environment on either sex. Darwin even brought up examples of this kind of dimorphism and pondered their existence, …

Logupdater: Automated Detection And Repair Of Specific Defects In Logging Statements, Renyi Zhong, Yichen Li, Jinxi Kuang, Wenwei Gu, Yintong Huo, R. Michael Lyu

Research Collection School Of Computing and Information Systems

Developers write logging statements to monitor software runtime behaviors and system state. However, poorly constructed or misleading log messages can inadvertently obfuscate actual program execution patterns, thereby impeding effective software maintenance. Existing research on analyzing issues within logging statements is limited, primarily focusing on detecting a singular type of defect and relying on manual intervention for fixes rather than automated solutions.To address the limitation, we initiate a systematic study that pinpoints four specific types of defects in logging statements (i.e., statement code inconsistency, static dynamic inconsistency, temporal relation inconsistency, and readability issues) through the analysis of real-world log-centric changes. We …

Breaking The Silence: Investigating The Impact Of Stigma On Help-Seeking Behaviors Among Adults With A History Of Adverse Childhood Experiences In Ghana, Deborah Amoako-Atta

West Chester University Graduate Theses, Dissertations, and Final Projects

In Ghana, cultural beliefs often silence open discussion about mental health. Many view emotional struggles as spiritual weakness, leading to stigma and avoidance of care. For adults who experienced Adverse Childhood Experiences (ACEs), this silence can worsen the long-term impact of trauma. While Western research links stigma to reduced help-seeking and shows that trauma knowledge can promote openness, little is known about how these relationships function within Ghana’s cultural context. This cross-sectional study examined how stigma and trauma knowledge influence help-seeking behaviors among 103 Ghanaian adults (ages 19-62, M = 30.0; 49% women) with childhood adversity histories. Participants completed anonymous …

Faculty Handbook, Georgia Southern University

Faculty Handbooks

Faculty Handbook for Georgia Southern University for the 2026-2027 academic year. The Faculty Handbook is published online by the Office of the Vice President for Academic Affairs and archived in Digital Commons@Georgia Southern.

Time Series Mediation Analysis With Non-Linear And Machine Learning Methods, Timothy Marsh

Theses and Dissertations (Comprehensive)

Non-linearity in mediation analysis has been primarily studied in the context of binary variables which encode a treatment and control, estimating a `direct` and `indirect` effect of a covariate (a.k.a. treatment) X on a response Y, with a third variable M (the `mediator`) that is affected by X and in turn affects Y. The focus of mediation analysis in general is to quantify the overall effect of X on Y, including the effect through M. This presentation will focus on one or more continuous treatments and apply non-linear methods, including splines and machine learning models, to mediation analysis in a …

Imsa 2027 Profile, Office Of College And Academic Counseling

IMSA Profile

The nationally-ranked Illinois Mathematics and Science Academy (IMSA) develops creative, ethical leaders in science, technology, engineering and mathematics. As a teaching and learning laboratory created by the State of Illinois, IMSA enrolls academically talented Illinois students in its tuition-free residential Academy for grades 10-12. Students are challenged with a rigorous curriculum designed to develop them into problem solvers and critical thinkers.

Notable IMSA students include YouTube Co-Founder Steve Chen, PayPal Co-Creator Yu Pan, Yelp Co-Founder Russell Simmons, SparkNotes and OkCupid Co-Founder Sam Yagan, and Hearsay Social Founder Clara Shih.

Toward Mapping Multiphase Multicomponent Mixtures With Neural Networks, Kristen L. Hallas, Melissa De Jesus, Christine J. Wu, Jianzhi Li, Jason Bernstein, Philip C. Myint

School of Mathematical & Statistical Sciences Faculty Publications

Equation of state (EOS) tables are commonly used in hydrodynamic simulations of high-pressure, high-temperature phenomena in fields like planetary science, astrophysics, and high-energy-density science. However, generating and storing EOS tables for multiphase, multicomponent mixtures over a wide range of pressures and temperatures is computationally infeasible due to their memory-intensive nature. To address this issue, we have developed a neural network-based machine learning model to predict new EOS tables for binary mixtures. In particular, a deep feedforward neural network trained on a set of ten EOS tables at particular mixture compositions is able to predict nine new (hold-out) EOS tables at …

Robust Statistical Methods For Microbiome Abundance Data, Yiming Shi

WUSM Theses and Dissertations – All Programs

Differential abundance analysis in microbiome studies aims to identify taxa whose abundance differs across biological or clinical conditions. The observed data are typically taxon-specific sequencing read counts, representing reads assigned to different taxa within each sample. These counts are indirect measurements of the underlying microbial abundance profile and are constrained by sample-specific library sizes. Microbiome count data are also typically sparse, overdispersed, and heteroscedastic. Together, these characteristics create substantial challenges for differential abundance analysis and make the results highly sensitive to normalization procedures, model specification, and the statistical methods used for inference.

Normalization defines the scale on which samples are …

Port And Vessel Communication Traffic Intrusion Detection: A Variational Autoencoder‑Enhanced Multilayer Perceptron Approach, Chien-Lin Chiang, Hsien-Cheng Chou, Ming-Yuan Peng, Yi-Yuan Chiang, Yu-Shun Liu

Journal of Marine Science and Technology–Taiwan

Port and vessel networks increasingly operate on IP/Ethernet backbones with high‑noise, high‑dimensional traffic. We present a lightweight hybrid intrusion‑detection model that couples a variational autoencoder (VAE) with a multilayer perceptron (MLP) and augments training with a boundary‑oriented latent‑space mixup strategy. The VAE models the distribution of normal traffic and identifies anomalies through reconstruction errors. Subsequently, it generates robust latent vectors, enabling the MLP to perform highly accurate supervised classification. On the UNSW‑NB15 dataset, the proposed pipeline attains ≥97% accuracy and an outstanding recall of 99.56% in binary intrusion detection, and visualization of the latent space (PCA) together with reconstruction‑error analyses …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

Enhancing Shipboard Safety Management Under The Ism Code: An Innovative Risk Assessment Framework With A Stern Tube Case Study, Pi-Yen Lin

Journal of Marine Science and Technology–Taiwan

The shipboard safety management system (SMS) is designed to enhance safe operations, risk management, and emergency response to improve overall ship safety and efficiency. This paper demonstrates the use of an engine room simulator (ERS) for collecting failure modes and applies it to a comprehensive failure analysis of the stern tube lubricating oil system. A new risk closeness coefficient method was developed, integrating expert background knowledge and weighted risk assessments. The analysis, based on multiple expert evaluations, covered five subsystems, eight main components, 23 failure modes, and 112 failure causes. This study presents 26 recommendations for maritime practitioners and onboard …

Interpreting The Trispectrum As The Cross-Spectrum Of The Wigner-Ville Distribution, Aviva Abosch

All Publications

The fourth-order time-invariant spectrum, or trispectrum, has a simple derivation as the cross-spectrum among frequency bands in the Wigner-Ville distribution (WVD). Viewed this way, the trispectrum gains intuitive meaning as a measure of the linear dependence of power across frequencies, which yields some insight into its structure and interpretation. We highlight, in particular, a two-dimensional subdomain as useful for identifying modulated oscillations when the modulating envelope is non-negative or lowpass. Spectral characteristics of the carrier and modulating signals are revealed along separate axes of a two-dimensional representation of this domain. The application of this framework, combined with a previously described …

Long Range Battery-Free Wireless Power Transfer Testbed For Underground Mines Iot And Lpwan Devices, Anabi Hilary Kelechi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mines are susceptible to occasional roof falls and cave-ins, temporarily destroying the existing wireless communications and telemetry infrastructure. During this temporary outage, intermittent provision of electrical energy wirelessly to the already deployed low-power wireless area networks (LPWAN) and Internet of Things (IoT) devices assumes a fundamental requirement. In this article, we propose and design a long-range far-field radio frequency (RF) wireless power transfer (WPT) testbed to power LPWAN and IoT devices at 35 m in an underground mines facility. Class AB external power amplifier (PA) was introduced to achieve a long-distance RF WPT, in the 880 MHz band. Thus, …

Revisiting Ulam Stability For Boundary Value Problems, Martin Bohner, Snezhana Hristova, Agnieszka B. Malinowska, Ewa Girejko

Mathematics and Statistics Faculty Research & Creative Works

The main goal of this paper is to apply Ulam stability theory to boundary value problems for dynamic equations, while addressing several common misconceptions found in the existing literature. We identify the key issues that arise when applying Ulam stability to such problems and propose three distinct approaches to overcome them. To enhance clarity and accessibility, we begin with nonlinear ordinary differential equations and subsequently extend the analysis to nonlinear dynamic equations on time scales. Since a time scale is defined as any nonempty closed subset of the real numbers, our results are applicable to dynamic equations on continuous, discrete, …

Soil-Science Expertise In An Ai-Exposed World: Competencies, Curricula, And Careers For Soil Security, Gian Franco Capra, Thiago Assis Rodrigues Nogueira, Arun Dilipkumar Jani

Biology, Agriculture and Chemistry Faculty Publications and Presentations

Generative artificial intelligence (AI) is reshaping the world of knowledge-based work, with highly qualified professions appearing more exposed to substitution than routine manual ones. Soil science occupies a hybrid position, being a field that requires extensive knowledge and at the same time a strong dependency on field and laboratory activities, time-consuming and intrinsically “embodied.” This review examines what AI entails for soil science, asking which competencies are more or less exposed, how curricula should respond, and what actions institutions should undertake in the current AI-dominant academic environment. The analysis rests on two axes, namely the AI exposure of a task …

Kindergarten Teachers’ Perceptions Of Instructional Approaches For Teaching Sequencing Concepts: Worksheet, Hands-On, And Beebot-Integrated Lessons, Savannah P. Partin

Electronic Theses and Dissertations

The purpose of this qualitative multiple-case study was to explore kindergarten teachers’ perceptions of three instructional approaches for teaching sequencing concepts: worksheet-based instruction, hands-on manipulative instruction, and BeeBot-integrated instruction. Sequencing is a foundational early literacy skill that supports reading comprehension, story retelling, and understanding the order of events. Although sequencing is commonly taught through traditional instructional methods, limited research has examined how kindergarten teachers perceive the use of educational robotics as a tool for literacy instruction. The study was guided by constructivist theory, sociocultural theory, and developmental systems theory. Participants included six kindergarten teachers from a public elementary school in …

Harnessing Digital Twin (Dt) Technology For Food Security And Climate Resilience In Sub-Saharan Africa (Ssa), Henri E.Z. Tonnang, Francis Chianu, Siyabusa Mkuhlani, Francis Muthoni, John Michael Humphries Choptiany, Franck B.N. Tonle, Bonoukpoe M. Sokame, Mercy Lung’Aho

All Peer-Reviewed Publications

Sub-Saharan Africa (SSA) faces chronic food insecurity despite possessing approximately 60% of the world’s uncultivated arable land. Field trials generate evidence but are costly and insufficiently scaled to address accelerating climate and demographic pressures. Digital twin (DT) technology, defined as the continuous, bidirectional virtual replication of physical systems using real-time data, supports monitoring, modelling, and optimisation of agrifood systems. To our knowledge, however, no published synthesis has examined DT agriculture research through the lens of SSA food systems or smallholder farming realities. A PRISMA-compliant systematic review was conducted across bibliographic databases using a pre-defined Boolean search and adapted PICOS eligibility …

Optimizing Inventory Management, William Hawkins

Agricultural Economics and Agribusiness Undergraduate Honors Theses

Inventory management is extremely important for businesses to maximize their profitability. Many factors go into the decision-making process for how much inventory to hold and when to restock this inventory. Through the process of an internship, I determined that some of the most important factors were the amount of a part that needed to be ordered at a time and what order quantities would allow for high levels of customer satisfaction. In this research, I compared these factors between the different models I studied, and the data I received from Riggs CAT to determine whether or not maximum efficiency and …

Pieces Solving A Puzzle: Emerging Roles And Cross-Field Analogies During A Distributed Epistemic Game, Jenna Matthews

All Graduate Theses and Dissertations, Fall 2023 to Present

In an effort to describe why some problems can’t be solved, a character compared them to a cubic meter of platinum - a block so dense that all the people who could squeeze around it still couldn’t lift it off the ground. In the same way, these problems simply can’t have enough people gathered around and communicating about them - and so they remain unsolved.

This research looks at the first Polymath Project (2009) as an example of a distributed epistemic game to examine how groups engage with complex problems. and without a locally omniscient individual. In this setting of …

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

Quantifying Customer Sentiment For Automobile Brand Perception Analysis Using Machine Learning On Twitter, Sujith Samuel Mathew, Kadhim Hayawi, Neethu Venugopal, May El Barachi

All Works

Social networking sites provide a platform for individuals to express their opinions publicly. Brand managers actively use these platforms to gain insights into brand perceptions, as users often share their views on products and services. In this study, we use sentiment analysis to assess customer sentiment towards five leading automobile brands, analyzing text content shared on Twitter(or X). The research models the ’Brand Polarity Score’, which indicates whether customers perceive the brand positively or negatively. This score is further weighted based on the tweet’s influence, characterized by the engagement metrics of the tweet and the author’s follower count. We also …

Power At Sea Develop Phase, Jake Lauer, Isabella Heinemann, Bailey Gargasz, Zachery Boyer

Mechanical Engineering

This project develops a renewable, wave-powered charging system designed to extend the mission duration of Autonomous Underwater Vehicles by eliminating the need for frequent manual battery replacement. Building upon a prior oscillating water column prototype from the CONCEPT phase, the team redesigned and tested an improved system capable of converting wave-induced air motion into electrical power using a Wells turbine. Key enhancements include doubling the column diameter to increase displaced air volume, integrating a flared inlet and bi-directional nozzle to improve airflow, and selecting corrosion-resistant materials suitable for long-term deployment in marine environments. Multiple prototypes were constructed and evaluated through …

A Deep Learning Ensemble Framework For Multi-Subtype Renal Tumor Classification Using Contrast-Enhanced Ct, Hisham Abdeltawab, Ahmed Alksas, Mohamed Ghazal, Ashraf Khalil, Norah Saleh Alghamdi, Rasha T. Abouelkheir, Ahmed Elmahdy, Mohamed Abou El-Ghar, Sohail Contractor, Ayman El–Baz

All Works

Renal cell carcinoma (RCC) is considered the most aggressive and common form of renal cancer. Therefore, early detection is crucial to ensure appropriate and effective treatment planning. In our study, we propose a novel computer-aided diagnostic (CAD) approach which incorporates a deep learning ensemble to differentiate between five renal tumor subtypes, utilising the modality of contrast-enhanced computed tomography (CE-CT). The addressed renal lesions are malignant tumors (chromophobe RCC (chRCC), papillary RCC (pRCC), and clear cell RCC (ccRCC)) and benign tumors (renal oncocytoma (RO) and angiomyolipoma (AML)). Our study includes 280 patients who underwent renal biopsy, 112 patients were diagnosed with …

Artificial Intelligence (Ai) For Social Innovation In Health Education: Promoting Health Literacy Through Personalized Ai-Driven Learning Tools – A Systematic Review, Dina Mansour Tbaishat, Maha Waleed Elfadel

All Works

Background: Artificial Intelligence (AI) is transforming health education by enabling personalized, adaptive, and scalable approaches that may enhance aspects of health literacy. Despite rapid adoption, comprehensive synthesis of AI tools’ impact on health literacy as social innovation is limited. Understanding these effects guides educators, developers, and policymakers in designing potentially effective, inclusive, and ethical AI interventions. This review examines generative AI models, chatbots, and adaptive learning systems in supporting health literacy globally. Methods: A systematic review was conducted following PRISMA guidelines. Literature was identified primarily through PubMed/Medline, Scopus, and ScienceDirect. Connectedpapers.com was used exclusively as a citation chasing tool, performing …