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Detecting Prescribed Fire, Haying and Grazing Events via Remote Sensing to Create Grassland Disturbance Landcovers for the Ring-necked Pheasant (\u3cem\u3ePhasianus colchicus\u3c/em\u3e)
No full textThis dissertation developed disturbance detection models to fulfill the need for remote sensing landcover products describing grassland structure. The use of landcover products derived from remote sensing is increasing over time in pheasant (Phasianus colchicus) research. Such landcover, however, does not provide relevant pheasant structural habitat information (Chapter 1). Pheasants require tall, high-density grassland for nesting, tall grassland with medium density for brood rearing, and tall grassland for wintering. Time since disturbance can serve as a proxy for structure, as it shapes vegetation by removing biomass and resetting succession. Disturbance is easier to detect than structure with current freely available remote sensing products. In the Great Plains, prescribed fire, haying, and grazing are significant sources of disturbance, so disturbance-specific detection models were developed and applied in northeast Nebraska from 2020 to 2023 to produce grassland disturbance landcover layers. Sentinel-2 remote sensing vegetation indices, weather data and management information were used to train Random Forest models to detect prescribed fire (Chapter 2), haying (Chapter 3), and grazing (Chapter 4). The models performed well, with the fire detection model having a 3% error and a false negative tendency, and the haying and grazing models having a 10% error and a false positive tendency. According to the models\u27 predictions, in 2020, 6% of the study area grassland was disturbed, in 2021, 33%, in 2022, 93%, and in 2023, 45%. These disturbance layers enhance our understanding of wildlife habitat disturbance. This information helps management evaluate cumulative disturbance over time, allowing for predictions of grassland structure for the following years. Practices can then accordingly be adjusted to create a landscape mosaic of grasslands with varied structural types that support pheasants throughout their life cycle.
Advisors: Daniel Uden and Andrew Littl
FireLog: An Open-source, Low-cost System for Temperature Logging during Wildland Fires with high Spatial and Temporal Resolution
No full textMeasuring flame, air, and soil temperatures during wildland fires, including wildfires and controlled burns in land management contexts, is crucial for research and applications in fire ecology, safety, and management in a wide array of ecosystems, from grasslands to forests. However, open-source and commercial systems are needed for measuring and logging flame and air temperatures that are user-friendly, economical, modular, and customizable. This paper details the design, development, and validation of the FireLog system. Laboratory validation experiments demonstrated high measurement accuracy, with a minimum coefficient of determination (R2) of 0.98 and the highest observed root mean square error (RMSE) of 29.5 °C when compared with a Campbell Scientific data logger in furnace tests spanning 20–1000 °C. These results confirm the FireLog system’s precision, repeatability, and robustness under controlled conditions. Field deployment during prescribed burns further validated its operational performance, confirming its ability to record temperature dynamics reliably in active fire environments. FireLog represents a practical and scalable tool for researchers and practitioners in fire science and land management
In-field Tractor Operational Load Profile Generation in Support of Advanced Tractor Testing in Mixedmode Power
No full textThis dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque transducer, with ISOBUS and J1939 CAN-bus signals via a modular SCANGate data acquisition system. This architecture enables synchronized monitoring of drawbar, PTO, and hydraulic loads in real time while maintaining compatibility with standard implement interfaces.
Over two growing seasons, ISOBUS/CAN data and physical sensor measurements were collected from a John Deere 7250R tractor during commercial corn production in Nebraska. The results demonstrate wide variation in power demands: anhydrous application produced sustained drawbar loads averaging 47; planting operations combined draft (80%) with hydraulic (20%) demand averaging 36 kW; and grain cart hauling introduced diverse drawbar and PTO cycles, including 48 kW during unloading and 6−12 kW drawbar loads during empty and full cart movement.
Using these datasets, mixed-mode load profiles were developed for each operation and then combined into a single proposed duty cycle. This cycle captures idle, operating, turning, unloading, and transport phases with time and load fractions derived directly from measured field behavior. The proposed cycle aligns more closely with real tractor power use than steady-state tests and supports efforts to develop advanced testing. This work establishes a methodology for capturing and applying real-world mixed-mode load profiles and provides a foundation for future tractor testing, design, and energy optimization.
Advisor: Santosh Pitl
Public Perceptions of Leadership Effectiveness in Ethiopia over the Last Decade
No full textEthiopia is one of the largest countries in Africa, with a fast-growing economy, rich history, diverse agroecology, more than 70 languages, and a population exceeding 130 million. However, the country continues to face serious internal conflict, high malnutrition, and economic hardship, while the study of leadership effectiveness remains limited and lacks consistent longitudinal research. To help fill this gap, this study examined how public perceptions of leadership effectiveness and development outcomes changed in Ethiopia between 2013 and 2023, using Afrobarometer survey data. The analysis explored how citizens’ views about governance, wellbeing, and access to services evolved during a decade of political transition, social change, and economic uncertainty.
The results show both progress and decline. There were notable improvements in education, household ownership of assets, and digital access, but perceptions of government performance in managing the economy, infrastructure, and corruption control have worsened. In addition, major inequalities remain between urban and rural areas and across regions. Regression results show that urban residence, access to services, and perceptions of corruption strongly influence how people judge leadership. Internet use was negatively related to positive views, suggesting that greater exposure to information increases awareness of governance weaknesses. Perceptions were also affected by social identity and fairness, reflecting the influence of Ethiopia’s ethnic federal system. Overall, the study concludes that Ethiopia achieved development progress without corresponding improvement in public trust or satisfaction with leadership. The widening gap between citizen expectations and leadership performance shows that corruption, insecurity, and lack of accountability continue to undermine governance. The study recommends leadership development based on ethics, servant and transformational principles, expansion of digital literacy and civic engagement, and stronger participatory mechanisms such as citizen feedback and social audits. Further longitudinal and evidence-based research is needed to strengthen accountability, transparency, and inclusiveness in Ethiopia’s leadership system. Ways to immediately settle the ongoing conflict was also recommended since its short and long-term costs are irreversible.
Advisor: Heather Aki
Assessing Crop Rotation Productivity, Soil Health, and Fertility, and Economic Performance, to Enhance Semi-arid High Plains Cropping Systems Sustainability
No full textSustainable crop production in the semi-arid High Plains of Nebraska faces challenges from limited precipitation, high interannual variability, and economic risk. This dissertation investigates the long-term productivity, water use, soil health, and economic sustainability of dryland crop rotations, with emphasis on the role of pulses as alternatives to fallow.
Chapter 1 analyzes nearly three decades (1995–2023) of on-farm data from the High Plains Agricultural Laboratory (Sidney, Nebraska) to compare seven crop rotations, including wheat, corn, millet, sunflower, and field peas. Results showed that wheat–corn–fallow (W–C–F) consistently outperformed traditional wheat–fallow (W–F) and more intensified four-year rotations, providing the highest grain yields, net returns, and precipitation-use efficiency.
Chapter 2 expands this analysis to additional long-term sites (North Platte and Brule, Nebraska), confirming that C-C-F and W–C–F remains a resilient rotation, while continuous wheat and heavily intensified rotations suffered yield penalties and economic losses, suggesting a threshold at cropping intensity at 0.67 CI.
Chapter 3 applied principal component analysis to soil chemical, microbial, enzymatic, and agronomic variables on a set of six crop rotations. Results demonstrated that water availability was the dominant driver of variability across systems but also revealed that crop rotations shape distinct microbial and soil fertility associations. Sustainable outcomes were linked to higher organic matter, enzyme activity, and balanced microbial communities.
Chapter 4 examined the replacement of fallow or cover crops with field peas and chickpeas. Results underscore the complexity of soil–crop–climate interactions and highlight the need for rotation designs that optimize yield and soil health. Integrating pulse crops seems promising for enhancing SOM benefits, whereas other certain crop sequences may require complementary nutrient or residue management to avoid trade-offs.
These findings demonstrate that sustainable intensification in west Nebraska is constrained by water availability. Moderate-intensity rotations such as W–C–F strike the most favorable balance between productivity, profitability, and ecological stability in the semiarid High Plains. Pulse crops like chickpeas and fields peas not only bring cash income but also ecosystem services like nitrogen credits and reduced erosion, suggesting more benefits than those obtained from oats cover crops.
Advisor: Cody Creec
Securing Connected and Autonomous Vehicles
No full textA vehicular network is susceptible to various security flaws and attacks. Cryptographic techniques are used in vehicular networks but these alone cannot provide proper security to the network. Identifying various types of attacks is necessary to secure vehicular communication networks. In this dissertation, we focused on detecting various insider attacks in vehicular networks to enhance the security of the network.
Our first contribution in this dissertation is the detection of both binary and multi-class data replay and data replay Sybil attacks in vehicular networks. A publicly available dataset, VeReMi-Extension is used to detect these attacks. This dataset has been reformulated to generate novel features aimed at detecting attacks in vehicular networks accurately. Machine learning-based methods have been applied to the reformulated dataset for the detection of attacks in vehicular networks. The extensive simulation results show that the proposed scheme can detect the attacks both for binary and multi-class scenarios effectively in vehicular networks.
Connected and autonomous vehicles (CAVs) leverage sensing, decision-making, and wireless communication technologies to enable autonomous driving. In particular, CAVs use various types of sensors and communication channels to share real-time data inside the network. However, CAVs are vulnerable to a range of attacks due to real-time data sharing. Recently, Federated Learning (FL) has been widely applied as a decentralized technique to train machine learning (ML) models on local devices, with the updated parameters shared for secure aggregation into a global model. However, even though the original data is not shared, FL could still be vulnerable to data poisoning attacks. For example, a malicious vehicle can introduce poisoned data during the training phase, decreasing the performance of the global model. We propose Malicious Client Detection Scheme (MCDS) to counter such data poisoning attacks and detect malicious clients among CAVs. In MCDS, each local client updates two key metrics, i.e., average accuracy and model weights, to the central server, who detects malicious clients and updates the global model. If the performance of any locally trained model deteriorates compared to others, the corresponding local client will be flagged as malicious and excluded from further processing as a mitigation of data poisoning attacks. The new metric applied in the MCDS allows the identification of anomalous clients without using any threshold values. Hence, only trustworthy client updates are used to update the model. The results demonstrate that the proposed MCDS can successfully identify and mitigate data poisoning attacks from CAVs.
At the same time, we have proposed two other schemes focused on detection backdoor attacks and label-flipping attacks from FL-based CAVs. For detecting, backdoor attacks, we have utilized SHAP and weight distance with K-means clustering while for detecting label-flipping attacks, we have utilized SHAP, Grad-CAM, and weight distance with K-means clustering. In both of cases, our proposed scheme can detect these attacks successfully. However, our for label-flipping attack we have false positive rates while for backdoor attack there is no false positive rates. Therefore, our proposed work can successfully identify various insider attacks from CAVs to enhance the security of CAVs.
Advisor: Yi Qia
Read Yourself In: Enhancing First-year Student Belonging through Place as Text Pedagogy
No full textThis study considers how Place as Text (PAT) pedagogy can foster a sense of belonging, efficacy, and persistence among first-year honors students. Author engages students in mapping, observing, listening, and reflecting exercises to observe how PAT helps them connect critically with their campus environment. Analyses of student reflections (qualitative) and historical enrollment data (quantitative) suggest that Place as Text deepens students’ engagement with the university, strengthens a sense of belonging, and enhances academic and social integration. Pointing to the strong correlation between belonging and persistence, author argues that PAT pedagogy should be expanded throughout honors colleges and curricula to support institutional efforts for improving student retention. Future research for tracking PAT’s long-term impact through institutional data analysis is called for as a way of reinforcing its value as a scalable and effective practice in honors education
Keeping Company: Genuine Conversation as a First-Year Honors Seminar Pedagogy
No full textDespite the challenges of a conversational approach to the FYS, the pedagogy has become engrained enough in the gateway seminar to the Westminster University Honors College that it would be hard to imagine adopting another strategy. Faculty tend to improve over time at leading such classrooms and regularly focus on the conversation-based features of their classes in their end-of-term self-reflections, as two teaching partners did in the following comments about the honors core course Global Welfare and Justice: “The strength of the class was the group dynamic and constellation of voices. It was an incredibly engaged class. Students challenged and built on each other’s comments in ways that led to rich analysis” (Etter and Weston). Alums, too, regularly return to campus, reporting the communication skills developed in Welcome to Thinking and other honors seminars as particularly formative and valuable. Even students considering the program understand the centering of student voices as fundamental; it always appears as one of the top five reasons prospective students apply to the honors college. For the fall 2018 and 2020 cohorts, the conversation-based pedagogy appeared as the second reason, and for the fall 2019, 2021, and 2022 cohorts it came in third. In fact, prospective students who visit Welcome to Thinking are most often struck by the apparent ease with which students engage in conversations about difficult texts and the inclusiveness of those discussions. We usually remind such visitors, however, that those confident displays reflect months of hard practice.
Ultimately, this conversation-based approach asks students to embrace “a life lived actively” (Rich 234) because that is the only way to fulfill our potential as individuals and as a society. As universities struggle to convince an increasingly skeptical public of the value of higher education, they might make more headway by demonstrating their ability to produce citizens skilled in making connections across differences and community building. If the next generation does not possess such competencies, we will most likely encounter, as Flammang warns us, a continued erosion of democracy and the emergence of even more authoritarian forms of government
Developing Peer Mentors as Co-educators for the Honors First-year Seminar
No full textOur decision at the University of Missouri–St. Louis (UMSL) to develop a peer mentor program in the Pierre Laclede Honors College (PLHC) First-year seminar (FYS) began in a spring 2014 campuswide FYS committee meeting. Having previously developed three essential cornerstones that all variations of the FYS on campus would need to include—campus connections, academic engagement, and development support—university leaders decided that best practices in FYS courses demanded the inclusion of peer mentors in all versions of the course. As honors faculty, we had frankly never contemplated this addition to our fully developed and successful academic FYS program. In fact, without such prompting from the university, the faculty members teaching the course would have undoubtedly questioned the need for mentors or perhaps even actively lobbied against the significant work and intrusion into class time that such an initiative could create. Because the faculty team realized that our continued independent control of the honors FYS and university funding to support its activities and events depended on our use of peer mentors, they agreed to fashion a role for peer mentors within our academic seminar FYS. Despite this challenging beginning, we now consider this peer mentor program one of the highlights of our FYS and a significant source of innovation, academic improvement, and community building within our honors college
Creating Superwicking Surfaces on Aluminum Nitride Using Femtosecond Laser Surface Processing
No full textAluminum nitride (AlN) is a high-performance ceramic with excellent thermal conductivity and electrical insulation properties, making it a promising material for use in next-generation electronic devices. However, its naturally low surface wettability provides a challenge for integrating the material into applications that require fluid spreading, adhesion, or thermal management based on two-phase processes. This thesis serves to explore the use of femtosecond laser surface processing (FLSP) to modify the surface of AlN and enhance its wetting characteristics. A thorough laser parameter study was conducted using a high-power, high-repetition rate Amplitude Tangor 300 femtosecond laser system. AlN surfaces were processed under a range of fluence values (0.66-1.45 J/cm2) and pulse counts (800-25,600). The resulting micro- and nano-scale surface structures were characterized using scanning electron microscopy (SEM) and laser scanning confocal microscopy (LSCM). Structural metrics such as relative peak and valley positions and surface structure height (Rz) were analyzed against the processing parameters of fluence and pulse count, as well as a normalization metric of accumulated fluence. It was found that structure height generally increased with both fluence and pulse count but plateaued at high accumulated fluences due to peak erosion. Low pulse count values were considered ineffective at any fluence value to create dense or tall surface structures.Notably, results from lower accumulated fluence values suggested that fluence and pulse count can both distinctly govern structure formation more so than the absolute amount of energy accumulation from the laser. The enhanced surfaces were evaluated for their fluid handling performance through wicking diffusion rate (WDR) testing. Nine FLSP-processed samples were prepared across the fluence values of 0.79, 0.92, and 1.19 J/cm2, as well as pulse counts of 3,200, 6,400, and 25,600. All processed surfaces exhibited superhydrophilic behavior, with contact angles of 0° and significantly increased wicking rates compared to untreated AlN. Samples with higher pulse counts consistently exhibited faster wicking rates. When comparing samples with the same pulse counts, it was found that an increase in fluence results in an increase in WDR. These results confirm that FLSP is an effective and tunable technique for improving the wetting behavior of AlN. Advisor: Craig A. Zuhlk