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2025-2026 Lindenwood University Undergraduate Course Catalog, Lindenwood University

Course Catalogs

Lindenwood University Undergraduate Course Catalog

Internet Of Things And Modern Digital Evidence Collection, Muhammad T. Haider

Student Theses

The ever-evolving landscape of technology and its innovations are populating our houses, streets and all kinds of industries. The use of smart devices is booming from most developed nations to underdeveloped countries. The complications which come with the use of the Internet of Things has been an active discussion for the past many years. If we look around in a room of 30 people, we will most likely find double the amount of IoT devices than the people in that room. All of those devices are connected to the Internet, and are communicating with data servers across the world. The …

Bystanders Intervening During Acts Of Cyberbullying: Examining The Moderating Influence Of “Likes” And Pleas For Help, Joseph Kallman

Student Theses

Abstract

Cyberbullying research has only recently begun exploring “cyberstanders,” also known as bystanders, and their role in cyberbullying, as well as testing the bystander effect (Barlinska et al., 2013; Machackova et al., 2013; Obermaier et al., 2016; Shultz et al., 2014). In the current study, we aim to deepen our understanding of the bystander effect by manipulating the number of likes, which will indicate the number of bystanders present and the plea for help on social media via Twitter among college students, by examining how participants respond to fictitious cyberbullying incidents. The results of this study did not support our …

Night-Time Warming And Prey Availability Interact To Influence Physiology In Prairie Lizards (Sceloporus Consobrinus), Allison R. Litmer, Morgan K. Pelley, Steven J. Beaupre

Biological Sciences Faculty Publications and Presentations

Among ectotherms, temperature and food availability are drivers of individual and population characteristics. Increasing night-time temperatures due to climate change can increase energetic demands, potentially amplified or mitigated by prey consumption. Few studies examine night-time temperatures specifically, and consequences of co-occurring changes in the abiotic and biotic environment. Thus, we examined interactions between warming night-time temperatures and prey availability (as a proxy of foraging time and effectiveness), and how they affect food consumption, digestive passage time, metabolizable energy intake (MEI), assimilated energy, and fecal and urate production in a model organism, prairie lizards (Sceloporus consobrinus). Three temperature treatments (current conditions, …

Training Robot Swarms For Adaptive Foraging In Environments With Obstacles, Pigar Biteng, Tameem Uz Zaman, Qi Lu

Computer Science Faculty Publications

In this work, we train adaptive and efficient foraging strategies for robot swarms in a large, unmapped search space with multiple randomly distributed box obstacles using the penalty-reward based NeuroEvolution of Augmented Topologies (NEAT), P-NeatFA. This model enables efficient multi-robot foraging behavior and obstacle avoidance by rewarding effective actions and penalizing inefficient ones, thereby minimizing redundant exploration and outperforming traditional stochastic foraging algorithms. We optimize foraging strategies and search patterns in robot swarms by training models that maximize cumulative rewards in three types of resource distribution environments. The evaluation focuses on the number of resources collected within a fixed time …

Evolving Adaptive Foraging Robot Swarms With Neat In Environments With Obstacles, Tameem Uz Zaman, Pigar Biteng, Qi Lu

Computer Science Faculty Publications

We apply NeuroEvolution of Augmented Topologies (NEAT) to evolve adaptive and efficient swarm foraging behaviors in unknown environments with randomly placed obstacles. By rewarding effective actions and penalizing inefficient ones using the proposed strategy P-NeatFA, the training generates efficient foraging and obstacle avoidance strategies, reducing redundancy and outperforming traditional stochastic foraging algorithms. Optimization is guided by cumulative reward-based fitness, evaluated through simulations involving three types of distributed resources. Foraging performance is assessed in terms of resource retrieval rates. We compare the performance of our proposed P-NeatFA with that of CPFA and NeatFA. Experimental results show that P-NeatFA significantly outperforms the …

Assessing Meteorological Impacts On Hydrological Switches In The Conus, Surendra Maharjan, Wenzhao Li, Sujan Shrestha, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hydrological switches, defined as rapid transitions between extreme meteorological events such as droughts and floods, are becoming increasingly frequent across the contiguous United States (CONUS) due to climate variability. This study analyzes the spatial and temporal patterns of these hydrological switches and their correlation with large-scale meteorological indices, such as the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Streamflow data from the US Geological Survey (USGS) is analyzed to investigate the impact of meteorological drivers on hydrological variability. Results indicate that regions dependent on snowmelt exhibit delayed hydrological responses to climatic conditions, while areas in the Eastern …

The Abduction Of Juan Manuel Fangio And Its Impact On The Cuban Revolution, Shalom Nissi Ramirez

Theses and Dissertations

On February 23, 1958, Juan Manuel Fangio, the five-time Formula One Champion, was kidnapped by the 26th of July Movement (M-26) in Havana, Cuba, during the Cuban Revolution. The kidnapping took place on the eve of the Havana Grand Prix as an act of sabotage against Fulgencio Batista's government. Fangio's abduction became a symbol of political resistance, challenging Batista's authority and raising the profile of M-26 as a revolutionary group. This thesis examines how the incident, amplified by worldwide media coverage, influenced international perceptions of the Cuban Revolution. It argues that using Fangio’s fame strategically helped accelerate awareness of the …

Collaboration In Action: An Exploration Of Collaborative Practice-Based Learning In Perservice Teacher Coursework, Logan W. Qualls

All Dissertations

New teachers report not feeling prepared to effectively collaborate with other professionals and families; however, collaboration is a large component of their day-to-day work. Thus, there is a need for teacher preparation programs to incorporate instructional methods that provide preservice teachers with opportunities to not only learn about the concept of collaboration but also to put those skills into place prior to entering the classroom. One possible answer to this need is to incorporate practice-based learning. Practice-based learning has been shown to effectively increase skill implementation for instructional and behavior management strategies; however, there is a lack of research regarding …

Chemical & Electromagnetic Signatures Of Binary Neutron Star Mergers, Benjamin Amend

All Dissertations

Binary neutron star (BNS) mergers are some of the most energetic events in the universe, producing both short gamma-ray bursts (GRBs) and kilonovae. GRBs are brief, bright flashes of gamma rays, powered by ultra-relativistic jets launched during the merger. These jets produce a prompt burst of gamma rays, followed by a broadband afterglow generated by external shocks as the outflow interacts with the surrounding medium. Kilonovae are optical-infrared transients from the radioactive decay of heavy, neutron-rich nuclei formed through the rapid neutron capture process (r-process) in the merger ejecta. Together, GRBs and kilonovae provide unique laboratories for probing fundamental physics …

Robust Online Inertia Estimation In Power Systems Using Ambient Data In The Presence Of Inverter-Based Resources, Narges Ghiasi

All Dissertations

The increasing penetration of Inverter-Based Resources (IBRs) in power systems has significantly altered system dynamics, reducing the system's effective rotational inertia and challenging frequency stability. Accurate online inertia estimation is essential for maintaining system reliability under these evolving conditions. This paper introduces a robust methodology for online inertia estimation using ambient data collected during normal system operation. The proposed method employs a state-space model to represent system dynamics and introduces synthetic step changes to simulate disturbances. By analyzing the frequency response and applying advanced signal processing techniques, the methodology estimates system inertia without requiring real large-scale disturbances. The approach is …

Advancing Smart And Adaptive Living Spaces Through Design And Development Of Reconfigurable Multifunctional Robot Rooms, Nithesh Kumar

All Dissertations

This work explores and introduces prototype hardware for a new category of robots: ‘Robot Rooms’, in an effort to refine the concept of traditional smart spaces and human-robot interaction. Unlike traditional robots that tend to be compact and exist within a space, this new category of robots is designed to be expansive: they do not exist within a space but rather shape space around them. We present several design concepts for potential robotic elements of a Robot Room. We then develop and demonstrate, at full scale, a new and novel concept: a ‘slice’ of a Robot Room. This slice changes …

Replacement Optimization For Offshore Wind Turbine Farms, Morteza Soltani

All Dissertations

This dissertation is concerned with devising optimal replacement policies for offshore wind turbines with a focus on minimizing the costs associated with major component replacements and production losses due to downtime. Like their onshore counterparts, offshore wind turbines are subject to progressive degradation due to normal operations, as well as the influence of dynamic environmental conditions that influence their rate of degradation. Due to their proximity, wind farm turbines share common environmental conditions, as well as specialized maintenance resources. Their common exposure to the environment and need to share resources introduce both stochastic and economic dependence between the wind turbines. …

Bifunctional Fusion Protein Pdl1sfv/Micae For Cancer Immunothearpy, Junyi Li

All Dissertations

Cancer immunotherapy has highlighted the importance of immune checkpoint blockade and innate immune cell engagement in battling tumor-mediated immune suppression in the past few decades. However, with cancer development, advanced tumors are often found to develop resistance towards single-target immunotherapy due to the complexity of the immunosuppressive mechanisms within the tumor microenvironment (TME). To address this, we developed a novel bifunctional fusion protein, PDL1sFv/MICAe, which combines the tumor-targeting capability of an anti-PDL1 single-chain variable fragment (sFv) with the NK cells immunostimulatory properties of the MICA extracellular domain.

In vitro functional assays revealed that PDL1sFv/MICAe significantly enhanced cytotoxicity towards natural killer …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Designing Self-Healable Aromatic Copolymers And Olefinic Composites, Samruddhi Yashwant Gaikwad

All Dissertations

Self-healing polymers capable of recovering from mechanical damage are promising materials for advanced applications, especially those involving mechanical and/or physical fatigue. In these studies, we have developed techniques to achieve autonomous self-healing in commodity Styrene/n-butyl acrylate copolymers. The mechanism of self-healing in the designed polymers involves inter-and/or intrachain non-covalent interactions between π-cloud and polar linkages of acrylic nBA in random/preferentially alternating copolymers. A combination of spectroscopic tools, thermo-mechanical analysis, and molecular dynamics (MD) simulations has been used to elucidate the mechanism of self-healing. These studies further show the incorporation of dipolar C-F groups to understand the effect of having fluorinated …

Improving Retention Of Students With Disabilities In Stem Through Math-Based Type Science Readiness, Eleni N. Koukoularis

All Dissertations

Abstract

This Dissertation in Practice examined the impact of a Math for Science Readiness (MSR) intervention on the science course planning behaviors of Students with Disabilities (SWD) in College Preparatory Basic (CPB) Chemistry, with the aim of increasing enrollment into Physics 1 College Placed Academic (CPA). Using an approach grounded in sociocultural theory and strength-based practices, the intervention implemented 16 short modules connecting chemistry and physics through shared math themes to reinforce math concepts across disciplines.

Data collected included physics interest surveys, common assessment exam scores, enrollment data, and counselor feedback to evaluate whether targeted math support could promote progression …

Organizational Metamorphosis: When Artificial Intelligence Transforms Companies Into New Economic Life Forms, Allan M. Glass

All Dissertations

Traditional theories of organizational change fall short in explaining how artificial intelligence (AI) transforms organizations. This grounded theory study, based on interviews with 34 organizational leaders, identifies a novel phenomenon: organizational metamorphosis - the irreversible transformation of organizations into fundamentally new entities through deep integration with AI as a cognitive partner.

The metamorphosis process unfolds in three phases. Individual Awakening occurs when leaders experience powerful interactions with AI, prompting a rapid shift from skepticism to advocacy. Once a critical mass of leaders undergo this shift, it initiates Organizational Restructuring, characterized by reimagined work design, boundary dissolution, and altered temporal rhythms. …

Toward A Unified Theory Of Fire-Induced Spalling Of Concrete: Transcending Domain Knowledge Limitations Through Explainable Artificial Intelligence, Causal Discovery And Inference, Mohammad Al Bashiti

All Dissertations

When concrete is exposed to fire, it can suddenly break apart in a dangerous process called spalling. This can severely weaken buildings and even trigger a collapse. While researchers have studied this problem for years, we still don’t fully understand what causes it. My research uses a combination of data, and advanced AI techniques to identify and quantify the key factors that increase the risk of spalling. I collected data from over 1,000 fire tests and used AI models to predict when spalling might happen. I also applied explainable AI tools to understand why it happens.

The results showed that …

Regulatory Tension In Highly Structured Organizations, David Elliott Sr.

All Dissertations

This study examines the psychological mechanisms by which employees with a pronounced propensity for risk-taking navigate highly formalized organizational environments. Utilizing a longitudinal, three-wave cross-sectional design with temporal separation, the research surveyed 220 employees with psychometrically validated instruments to assess personality traits, role conflict, and organizational identification. Anchored in an integrative framework that combines regulatory focus theory (Higgins, 1997) and identity theory (Burke & Stets, 2009), the study hypothesized that self-verification striving and a growth mindset mediate the relationships between risk-seeking tendencies and the outcomes of role conflict and organizational identification, with organizational structure serving as a moderating variable. Structural …

Evolutionary Biomechanics In Cetartiodactyla: Impacts Of Ecological Shifts On Bone Material Properties And Control Surface Morphology, Danielle S. Adams

All Dissertations

Extreme ecological transitions expose organisms to novel selective pressures that can reshape morphology and performance. This dissertation investigates how the transition from land to water has influenced form and material properties in cetaceans (whales, dolphins, and porpoises), a clade that has undergone dramatic morphological and physiological adaptations to a fully aquatic lifestyle. I integrate comparative morphology, material property testing, and phylogenetic analyses, to explore how ecological demands, particularly related to foraging mode and prey detection, have shaped multiple aspects of cetacean morphology and function. Using nanoindentation and microCT, I measured elastic modulus and bone density of the skull and mandible …

Investigation Of Solid-State Reactive Sintering And Rapid Laser Reactive Sintering For Al-Doped Li7la3zr2o12 Solid-State Electrolyte, Aaron Santomauro

All Dissertations

As a society, we’ve exhausted an extreme amount of fossil fuels and put an overwhelming strain on Earth’s natural resources. From this, it is critical to think about the successful future of our planet and ourselves by developing energy devices such as all-solid-state lithium-ion batteries (ASSLIBs). These devices offer a greener and more efficient alternative to power our daily lives, such as electric vehicles (EVs), portable electronics, medical devices, grid-scale energy storage, and aerospace/aviation. ASSLIBs are an excellent alternative to liquid-state batteries, which pose dangerous safety concerns (e.g., flammability, electrolyte leakage, etc.). These ASSLIBs are known to have generally high …

Experimental Design And Analysis For Decision Making: Methodology And Applications, Yezhuo Li

All Dissertations

This dissertation develops and applies advanced statistical and optimization frameworks to enhance decision-making under uncertainty, particularly in engineering and manufacturing contexts. First, we introduce an approach for the optimal design of controlled experiments that accounts for observational covariates, enabling more precise and personalized decisions. Second, we explore the application of constrained Bayesian optimization, using Gaussian process surrogate models, to optimize composite cure processes, significantly reducing computational effort while maintaining high predictive accuracy. Building on this foundation, we extend Bayesian optimization to bivariate Gaussian process models that capture correlations between objective and constraint functions, offering new insights into multidimensional decision landscapes. …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Structural Design Using Conditional-Gan Fused With Property Text Information: A Case For Masonry Structures, Arash Teymori Gharah Tapeh

All Dissertations

Structural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a "copilot," collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific …

An Investigation Into The Impact Of Inverter Based Resources On Critical Clearing Time, Trupal Patel

All Dissertations

Renewable energy sources, mainly inverter-based resources (IBRs) such as solar and wind plants are being connected in large numbers to the bulk power grid in the United States and around the world. Additionally, generation using fossil fuels are being phased out, which results in the loss of rotor inertia, a key contributor to the transient stability of power systems. Therefore, the large-signal behavior of IBRs and its impact on transient stability must be studied.

This work studies this impact through the metric of critical clearing time (CCT). Impact of grid topology, generation mix and control modes of IBRs on CCT …

Three Essays In The Economics Of Disagreements: Incentives, Measurement And Persistence, Mustafa W. Alam

All Dissertations

This dissertation presents three chapters that contribute to the study of economic forces shaping disagreements in society.

In Chapter 1, I demonstrate that political polarization can intensify due to innovations in the information market even if a population's ideological distribution is fixed. Viewership-maximizing news firms cater to a diverse audience who assess source accuracy using noisy private signals that vary in precision and ideological bias. If better-informed consumers disproportionately migrate to newer platforms for news (e.g., the Internet), traditional media firms increase news slant to appeal more to less-informed partisans on both sides of the ideological spectrum. This leads to …

Decoding The Mobile App Playbook: How Sdks And Cross-Promotions Drive Market Performance, Pranith Abbaraju

All Dissertations

This dissertation investigates the strategic determinants of mobile app success within the evolving mobile platform ecosystem, focusing on app development choices and user acquisition strategies. Drawing on large-scale longitudinal data from the iOS platform, the research comprises two empirical studies contributing to the literature on digital platforms, modular design, and mobile advertising.

The first study examines how the integration of software development kits (SDKs)—a central mechanism of modular innovation—affects app market performance. The analysis identifies SDK popularity as a dual-edged strategic attribute. While popular SDKs can enhance app quality by enabling access to reliable, widely adopted functionalities, their widespread adoption …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Communicators In Crisis: Lessons Learned From Communications Professionals During The Great Resignation, Julia K. Longaker

All Dissertations

This study investigated the experiences of communication professionals who participated in the Great Resignation phenomenon between 2020-2022. The research questions focused on the role participants’ working relationship with leadership as it related to their decision to leave their role or pursue a new job. Ten communication professionals participated in a qualitative study comprising of an online interview discussing their experiences during the Great Resignation. Using the interview transcripts, the researcher employed grounded theory to extract recurring codes and draw conclusions based on the participants’ answers. The results of this study inform recommendations for improved working relationships between communication professionals and …