Digital Commons Network^™

The Implications Of Insecure Use Of Fonts Against Pdf Documents And Web Pages, Junjie Xiong, Mingkui Wei, Xiao Han, Zhuo Lu, Yao Liu

Computer Science Faculty Research & Creative Works

This paper identifies the importance of the safe use of fonts in web and document security. We find multiple attack surfaces that can be exploited by an adversary using malicious fonts. We conduct a comprehensive evaluation of Portable Document Format (PDF) documents collected from the real world to investigate how an attacker can bypass PDF signatures. We further evaluate the potential security threats that an attacker can bring to web-based emails. Our study shows that various security issues may be caused by the inappropriate use of fonts, which are nevertheless overlooked in the past years. As such, guidelines promoting the …

2025-08-18 Revisal Of Pac-22 - Draft, Morehead State University. Faculty Senate.

Faculty Senate Records

Draft of the revisal for PAc-22 submitted to the Faculty Senate on August 18, 2025.

Cardiac And Coronary Hemodynamics: Using An Integrated Ex-Vivo Beating Heart Experiments And Computational Modeling, Chenghan Cai

Master's Theses (2009 -)

Cardiovascular function arises from the complex interactions among the heart, the arterial system, and the coronary circulation. Questions such as how variations in left ventricular (LV) loading conditions affect LV and aortic functions through LV–aorta interactions; and how coronary artery diseases, such as stenosis, impact cardiac function and myocardial perfusion including left and right coronary perfusion via LV–coronary interactions, remain understudied. To answer these questions, this thesis focuses on two core objectives: (1) investigate the effects of LV loading conditions on LV and aortic functions through LV–aortic interactions by performing ex-vivo beating rat heart experiments, and (2) elucidate the impact …

Cationic Liposome Nanoparticles For Drug Delivery To The Inner Ear, Firas Al-Ashker

Master's Theses (2009 -)

Cisplatin is a widely used chemotherapy drug associated with a high incidence of hearing loss, particularly in younger patients. This ototoxicity is linked to the drug’s long-term accumulation in the cochlea, where it can persist for years following treatment. Current clinical interventions, such as sodium thiosulfate (STS), offer partial protection against hearing loss but are limited by poor drug penetration into the inner ear. The objective of this study was to develop and evaluate a targeted drug delivery platform capable of overcoming anatomical and physiological barriers to reach the cochlea more effectively. Specifically, we aimed to design cationic liposome nanoparticles …

Spectral Mixture Analyses Of Hematite-Rich And Clay-Bearing Terrains In Meridiani And Oxia Planum, Mars, Thomas Jake Condus

Arts & Sciences Graduate Student Theses and Dissertations

Minerals have characteristic absorption features in the visible and near-infrared wavelength range, which can be detected in remotely sensed observations using methods such as spectral parameter maps or modeled via spectral mixtures. My dissertation uses both methods on orbital and ground-based single-scattering albedo data to assess the surface compositions of Meridiani Planum and Oxia Planum, regions of Mars that are rich in secondary minerals. A probabilistic approach to spectral unmixing was adopted to account for the nonuniqueness of model solutions, with endmember abundance and grain size maps being produced for Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) orbital images. For …

Photolysis Of Emerging Agricultural Applications Under Environmental Conditions, Kun-Pu Ho

McKelvey School of Engineering Graduate Student Theses & Dissertations

Novel agricultural applications are rapidly emerging to protect crops from weeds or pests in the US and worldwide. Isoxaflutole is a proherbicide considered agriculturally significant because it controls weeds that have developed resistance to other commonly used herbicides. In addition, RNA interference (RNAi) technology is regarded as a next-generation biopesticide because the technology has less toxicity to humans and more specificity to pests than traditional pesticides, which pose risks to the environment and the health of humans and livestock. However, we cannot disregard the possible risks of the emerging proherbicides and biopesticides to humans or non-target organisms. Therefore, the study …

Development, Numerical Simulation, And Optimization Of Quiet Supersonic Transport Aircraft And Extension Of The Wray-Agarwal Algebraic Transition Model To Include Compressibility And Crossflow Effects, Dean Ryan-Simmons

McKelvey School of Engineering Graduate Student Theses & Dissertations

In the first part of this thesis, the goal of the research is to implement and extend multi fidelity methods for conceptual design and optimization of a commercial supersonic transport (SST). Most modern commercial aircraft operate at a cruise condition between Mach 0.7 and 0.9, as this is the optimal trade-off of flight efficiency, operational cost, and adherence of noise regulations for overland travel. Advancements in aviation propulsion fuel efficiency and design materials suggests a primary restraint on commercial supersonic transport is noise regulations. At speeds above Mach 1, the shock waves generated by the airframe are strong enough to …

Harnessing Metabolic Modeling And Artificial Intelligence For Next-Generation Bioproduction, Zhengyang Xiao

McKelvey School of Engineering Graduate Student Theses & Dissertations

Bioproduction in microbial hosts faces two main challenges: (1) unique metabolism of each species is difficult to generalize, and it requires precise quantification before metabolic engineering. (2) Past experiment data are fragmented in different studies, making it difficult to combine these non-standardized data for future experiment design. These challenges lead to high costs and risks in scaling up biomanufacturing processes, where R&D requires substantial budgets and iterative experiments are expensive. This thesis addresses both challenges through two research pillars. Part I uses 13C metabolic flux analysis (MFA) and genome-scale model (GSM) to investigate metabolic limitations in bioproduction hosts. In Escherichia …

A Mechanistic Understanding Of Transcutaneous Auricular Vagus Nerve Stimulation, Kara Michelle Donovan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Transcutaneous auricular vagus nerve stimulation (taVNS) offers great potential as a noninvasive neuromodulation technique with expanding therapeutic potential across a range of neurological and systemic indications. Yet despite strong clinical interest, the mechanistic foundations of taVNS remain incompletely understood. In contrast to the invasive form of vagus nerve stimulation (VNS), taVNS has seen more limited parametric characterization, with many studies relying on parameters adopted from invasive protocols without systematic validation at the noninvasive level. This dissertation focuses on developing a more comprehensive understanding of the underlying mechanisms of taVNS. It extends existing literature by leveraging intracranial electrophysiology to directly quantify …

Combining Code Analysis And Pedagogical Guidance: Automated Tools For Teaching Debugging In Introductory Programming, Yana Malysheva

McKelvey School of Engineering Graduate Student Theses & Dissertations

The ability to debug code is critical to being a programmer and represents a distinct skill from writing code. Yet debugging is rarely explicitly taught in introductory programming and Computer Science courses. Instead, novices typically develop their own debugging habits and strategies when they encounter bugs in their code, which are often less effective than those of expert programmers. When students do seek help with debugging, they traditionally turn to office hours conducted by Teaching Assistants (TAs) or, increasingly, to Large Language Models such as ChatGPT. However, both sources of assistance have limitations. TAs are often students themselves with limited …

Code Stories For Software Evolution, John Joseph Allen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Programmers spend more than half of their time comprehending code, and in particular struggle to answer questions about the rationale, intent, and history behind software artifacts. Through this dissertation, I explore how history-aware tools can help programmers understand unfamiliar software artifacts. First, I investigated how providing additional context -- historical code changes grouped by the original developer's stated subgoals and the web foraging activity of the original developer impacted the process of code reuse. I found that programmers utilized these resources to 1) make better analogies between their reuse scenario and what code was already written, and 2) anchor into …

Towards Graph Foundation Models: Few-Shot And Zero-Shot Learning On Graphs, Hao Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graphs naturally model complex relationships and interactions across various domains, including social networks, biological systems, and recommender platforms. Graph Neural Networks (GNNs) have emerged as powerful tools for learning effective graph representations through iterative message passing, significantly improving performance in tasks such as node classification, link prediction, and graph classification. However, the success of GNNs largely depends on abundant labeled data, posing challenges in practical scenarios where labeled data is scarce or unavailable. This dissertation addresses these challenges by exploring few-shot and zero-shot learning within the graph domain. We first propose COLA, a self-supervised few-shot node classification method that exploits …

Multi-Layer Support For Component-Based Cyber-Physical Systems Applications, Oren Bell

McKelvey School of Engineering Graduate Student Theses & Dissertations

Component-based design is a paradigm meant to aid in development of software applications by modularizing different functionalities of a system. This building-block approach is used extensively in cyber–physical and robotic systems. Common and established solutions to specific problems, such as perception nodes, state estimators, and motion planners, can be developed, verified, and reused as off-the-shelf modules. These modules may be integrated atop today’s heterogeneous hardware platforms, where an application can be distributed across GPUs, FPGAs, and CPU cores. When heterogeneous computational devices share the workload of a collection of components, the very act of integration may inject timing uncertainty. For …

The Psychology Of Sharing Experiences, Hyebin Kim

Olin Business School Graduate Student Theses and Dissertations

From dinners with family to parties with friends, consumers frequently spend time with and share experiences with other people. Sharing consumption with other people can uniquely shape people’s decisions and experiences, often in ways that differ from when individuals are on their own. In my research, I examine what kinds of experiences consumers like to share with other people, and how being the one who organizes gatherings for other people influences consumers’ decisions and experiences during shared consumption. In Chapter One, “When Sharing Experiences with Others, People Prefer Novel Experiences,” I examine how the social context of an experience, in …

Assessing University Students’ Self-Reported Vocabulary Learning Strategy Use, Yirgalem Girma

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

Learning vocabulary is certainly a vital component of language learning and without this integral component of language communication becomes hardly meaningful. Thus, students are expected to have rich vocabulary power that enables them to communicate successfully via listening, speaking, reading, and writing; it assists students in expressing a range of meanings in various communicative situations for various purposes. This demands students to learn vocabulary using diverse vocabulary learning strategies that assist them in learning (internalizing, storing, recalling, and using) words properly. However, several students barely manage vocabulary learning tasks and/or use appropriate and diverse vocabulary in English classes. Consequently, this …

Transition And Instability Characteristics Of The Separated Shear Layer Formed At Low Reynolds Number Over Three-Dimensional Irregular Rough Surface, Ganesh Kt Mr

Theses and Dissertations

The present experimental work investigates the effects of irregularly roughened surfaces and imposed streamwise pressure gradients on the topological, transitional, and instability characteristics of the laminar separated shear layer (SSL). Experiments are conducted in the low-speed wind tunnel for 𝑅𝑒𝑡=30000, based on the thickness of the airfoil model, t, and freestream turbulence intensity, fst = 0.8%. The airfoil model used in this study features a semicircular leading edge followed by a constant-thickness flat portion and a pitchable trailing-edge flap. Test conditions include two rough surfaces: sandblasted (SB) and sand-deposited (SD), and flap deflections: 𝛽=−30° and 𝛽=+30°, imposing adverse (APG) and …

Buddhism For Thinkers, Chang-Seong Hong, Sun Kyeong Yu

MSU Authors Collection

This book is an introduction to Buddhist philosophy. It uses the methods of analytic philosophy to approach the major topics of Buddhism.

An Exploration Of Factors That Influence A Clinical Supervisor's Decision To Address The Personal Development And Dispositions Of Supervisees, Kirsten K. Hagen

Psychology

Research suggests that addressing a supervisee’s personal factors in clinical supervision is critical to developing their therapeutic capacities (Aponte, 1994; Krug and Schneider, 2016; Southern, 2007; Zorga et al., 2001). However, little is known about the factors contributing to clinical supervisors’ decisions to address supervisees’ personal development and dispositions in clinical supervision, despite their importance in supervisees’ professional development. The purpose of this grounded theory study was to discern the nuanced narratives of clinical supervisors and construct a theory of factors related to their decisions regarding whether to address or not address the personal development and dispositions of supervisees in …

Ligand Substitution Versus Dna-Binding Affinity : ǂB Syntheses, Structures, And In Vitro Anticancer Activities Of Pt(Ch₃)₂I₂{2,2'-Bipy-N,N'-(Ch₃)₂} (N,N' = 4,4'; 5,5'; 6,6'), Shadrach Stitz

Chemistry and Biochemistry

In chemotherapeutic treatment for leukemia, the drug cisplatin is highly effective. However, there is an immense need for cisplatin analogues that are more clinically viable. Cancer cell assay studies have shown that the platinum(IV) complex Pt(CH₃)₂I₂{2,2'-bipyridine} exhibits significant anticancer activity against the human breast cancer cell line ZR-75-1, with an EC50 (effective concentration 50%) concentration of 6.1 μM— substantially lower than that of cisplatin (16.4 μM). To explore the unknown structure-activity relationship between DNA binding and anti-cancer activity, three isomers — Pt(CH₃)₂I₂{2,2'-bipy-n,n'-(CH₃)₂} where n,n’ = 4,4’; 5,5’; 6,6’— were synthesized. The intent was to demonstrate decreased cytotoxicity as complex-DNA steric …

The Transformational Learning By Web-Conferencing Circuit Board: A Conceptual Model Outlining The Conditions That Facilitate Transformation In Synchronous Spaces, Rachel L. Reilly

Communication

As synchronous technologies and high-speed internet have become more accessible, opportunities for learning in web-conferencing settings have also increased. Despite the ubiquity of learning experiences taking place over web-conferencing, there is a lack of research on what makes for effective adult learning in synchronous settings from learners’ perspectives. Moreover, there are few studies examining how transformational learning—learning that changes an adult’s mindset, beliefs, or perceptions—occurs in web-conferencing settings. This qualitative study explores the conditions through which transformational learning occurs in web-conferencing settings. It includes the perspectives of adult learners (all at least eighteen years old) who have participated in a …

Understanding Secondary Atmospheric Chemistry In Extremely Cold And Dark Environments Through Hydroxymethanesulfonate (Hms) Measurements In Wintertime Fairbanks, Alaska, James R. Campbell

Chemistry and Biochemistry

Fairbanks, Alaska is a subarctic city that regularly violates PM2.5 air quality standards in the winter, exacerbated by strong wintertime inversion layers and wood stove heating. While primary sources of PM2.5 in Fairbanks have been studied extensively, secondary chemistry remains not well understood. Here, we focus on the aqueous secondary product hydroxymethanesulfonate (HMS), a major sulfur(IV) particulate species, to help understand what drives secondary pollution in Fairbanks. In 2020 and 2021, we used a particle-into-liquid sampler coupled with ion chromatography (PILS-IC) to measure HMS and sulfate concentrations. We report that HMS concentrations are high compared to other highly polluted regions …

Alaska Earthquake Center Quarterly Review January-March 2025, Heather Mcfarlin, Will Dienstfrey, Alexandra Farrell, Beth Grassi, Stephen Holtkamp, Nate Murphy, Elisabeth Nadin, Carolyn Parcheta, Angelica Stabs, Michael West

Alaska Earthquake Center Reports

This series of technical quarterly reports from the Alaska Earthquake Center (AEC) includes detailed summaries and updates on Alaska seismicity, the AEC seismic network and stations, fieldwork, our online presence, public outreach, and lists publications and presentations by AEC staff. Multiple AEC staff members contributed to this report.

Design And Development Of Deep Learning Based Generic Platform For Promoting Precision Agriculture, Srilakshmi A

Theses and Dissertations

Precision agriculture also referred as precision farming or smart farming, is an innovative approach to agricultural management that leverages technology and data to optimize various aspects of the farming process. This approach aims to make farming more effective, sustainable, and profitable by affording farmers with the application tools and information they need to make more informed decisions.

Precision agriculture combines elements of agriculture, technology, and data science to enhance crop production, and resource utilization. Precision agriculture techniques can be highly effective in leaf disease detection within crop fields. Machine learning has been developed incredibly across multiple domains and shown it …

Factors Influencing The Performance Of Farmer-Producer Organizations (Fpos) And Their Societal Impact In Tamil Nadu, Arjune S

Theses and Dissertations

Farmer Producer Organizations (FPOs) are formed mainly for the farmers to have better institutional access to acquire them. They are also under the inspiration of the director's abstinence and the incentive of getting more money. These are socio-psychological individual differences and thus of importance to markets, the perception of markets, and market relevance of group interaction. Self-esteem, attitude to participation in group activities, and willingness to participate in these types of activities are of some significance for his/her performance because they have an effect on their performance afterward.

Farmer social empowerment increased but not farmer economic empowerment did so much …

Hindcasting The Occurrence Time Of Major Earthquakes Using Machine Learning And Time Series Analysis, Rubidha Devi D

Theses and Dissertations

An earthquake is an intense shaking of the ground that typically occurs when tectonic plates move beneath the surface of the Earth. Scientists analyze historical seismic records and geophysical and atmospheric signs to build models estimating the probability of major earthquakes by detecting patterns and anomalies in data such as ground deformation and seismic waves. This study would help in predicting earthquakes to minimize risks of people and buildings.

The present study investigates the devastating earthquakes along the Chilean subduction zone in South America, linking non-seismic data to machine learning predictions of Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) …

Computational Studies On The Major Antioxidant Enzymes Of Wuchereria Bancrofti Towards The Development Of Anti Filarial Leads, Sureshan M

Theses and Dissertations

Lymphatic filariasis (LF), or elephantiasis, is a mosquito-borne parasitic disease affecting the lymphatic system, primarily in tropical and subtropical regions. It is the second leading cause of long-term disability and a neglected tropical disease. According to WHO, LF threatens 882 million people in 44 countries, with over 9 billion treatments administered. The disease is caused by three nematodes: Wuchereria bancrofti (90% of cases worldwide, including India), Brugia malayi (10% in Southeast and Eastern Asia), and Brugia timori (found in Timor and nearby islands). Lymphatic filariasis (LF) is an ancient disease that continues to challenge scientists and physicians. Current treatments include …

Management Concepts In Shishupalavadha, Sathyanarayanan V

Theses and Dissertations

Management of organizations, people, and entities has been a subject matter of great interest today. Schools of business and management were established in the West about 125 years ago, and countries in other parts of the world, including India, simply followed these practices. Consequently, there is a widespread feeling today that management concepts originated in the West. All Indian business schools teach management concepts propounded by Western scholars in the last 100 years or so.

Going by the first principles, whenever multiple people, resources, entities, and institutions are involved, there is a requirement for Management. This implies that management as …

Hindcasting The Occurrence Time Of Major Earthquakes Using Machine Learning And Time Series Analysis, Rubidha Devi D

Theses and Dissertations

An earthquake is an intense shaking of the ground that typically occurs when tectonic plates move beneath the surface of the Earth. Scientists analyze historical seismic records and geophysical and atmospheric signs to build models estimating the probability of major earthquakes by detecting patterns and anomalies in data such as ground deformation and seismic waves. This study would help in predicting earthquakes to minimize risks of people and buildings. The present study investigates the devastating earthquakes along the Chilean subduction zone in South America, linking non-seismic data to machine learning predictions of Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) …

Artificial Intelligence-Based Adaptive Data-Driven Techniques For Disruption Prediction In Tokamak, Priyanka M

Theses and Dissertations

Tokamaks are nuclear fusion reactors designed to generate sustainable energy by confining plasma, yet plasma disruptions remain a major obstacle as they can damage reactor components and interrupt fusion reactions. Addressing this challenge requires reliable models that can classify plasma discharges and predict disruptions in advance. This thesis develops machine learning and deep learning approaches to improve both classification and forecasting.The first contribution is a semi-supervised active learning framework, Nearest Margin-Ranked Batch Mode Active Learning (NM-RBMAL), integrated with an ensemble model.

Unlike traditional classifiers that operate on static training data, this approach continuously adapts to new plasma conditions, reducing model …

Ai Based Early Detection Of Hormonal Imbalance And Poly-Cystic Ovary Syndrome In Young Women, Reka S

Theses and Dissertations

A hormonal disorder, Poly-Cystic Ovary Syndrome (PCOS) usually affects women during the reproductive age. It is characterised by imbalances in hormones, particularly a rise in the female body's androgen level (male hormone) and enlarged ovaries with small cysts. PCOS can cause ovarian cysts, weight gain, acne, excessive hair growth, insulin resistance, and irregular menstrual cycles along with other health problems. While the exact origin of PCOS is uncertain and its symptoms are unclear, diagnosing PCOS in real-world conditions is a difficult task. Therefore, prompt and precise PCOS diagnosis is essential for efficient treatment and for averting long-term issues.

Clinicians typically …