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Moon Adaptive Technology For Extraterrestrial Architectural Robotics (Matear), Candela Noemi Solis Zampini May 2026

Moon Adaptive Technology For Extraterrestrial Architectural Robotics (Matear), Candela Noemi Solis Zampini

Theses and Dissertations

The Moon Adaptive Technology for Extraterrestrial Architectural Robotics (MATEAR) focuses on the development of an autonomous robotic system capable of providing structural building blocks directly from lunar regolith. As a sustained human presence on the Moon becomes a necessity, the costly and limited payload capacity associated with transporting construction goods from Earth creates a critical challenge. MATEAR addresses this problem through in-situ resource utilization (ISRU), integrating a regolith processing system onto a remote operated vehicle. The proposed system is designed to collect lunar dust, mechanically compact the material, and apply thermal treatment to enhance cohesion through sintering. These regolith-made bricks …


Exploring Cognitive Load Theory In The Post-Secondary Engineering Classroom, Gabriel Q. Van Dyke May 2026

Exploring Cognitive Load Theory In The Post-Secondary Engineering Classroom, Gabriel Q. Van Dyke

All Graduate Theses and Dissertations, Fall 2023 to Present

Engineering programs often emphasize subject-matter expertise over pedagogical training, which can leave students struggling with course demands and contribute to retention challenges. This study applied Cognitive Load Theory (CLT) to examine how undergraduate engineering students experience the cognitive demands of their coursework compared to non-engineering classes. Using a sequential explanatory mixed methods design, cognitive load surveys were followed by interviews to address two research questions: (1) What are the differences in intrinsic and extraneous cognitive load levels between engineering courses and non-engineering courses taken concurrently by undergraduate engineering students? (2) How do engineering students perceive the unique challenges or benefits …


A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson May 2026

A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible …


Ionospheric Plasma Electron Density Measurement And Theory Using Impedance Probe Techniques, Justin Wellington May 2026

Ionospheric Plasma Electron Density Measurement And Theory Using Impedance Probe Techniques, Justin Wellington

All Graduate Theses and Dissertations, Fall 2023 to Present

The ionosphere plays a critical role in how radio frequency (RF) signals, like those used in Global Position System (GPS) satellite communications, travel through space. Disturbances in the ionosphere, such as equatorial plasma bubbles (EPB), scatter these signals and cause communication dropouts or navigational errors. To study these conditions, spacecraft use instruments that measure the surrounding plasma directly. One of these instruments is an impedance probe, which applies a small electrical signal to a sensor and determines electron density from the measured impedance.

This thesis improves the modeling and interpretation of impedance probe measurements. A numerical method is developed that …


Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio May 2026

Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio

All Graduate Theses and Dissertations, Fall 2023 to Present

Measuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better …


Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks May 2026

Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores two types of reconfigurable, steerable antennas. These antennas change their beam direction based on electric input signals. The antennas have a layer that overlays the main antenna circuit board. The layer has small copper rectangles (pixels) that may be connected using either varactor diodes (which behave as voltage-controlled capacitors) or PIN diodes (electronic switches). The first antenna can steer in the xz-plane in any direction within about 23° from boresight (straight up from the antenna) and in the yz-plane to about 29° from boresight. The antenna uses varactor diodes on a planar layer. The second …


Freshwater Mussel Reintroduction And Recolonization Habitat Modeling Using Hydraulic, Sediment And Geomorphic Parameters, Megan Elizabeth Dinicola May 2026

Freshwater Mussel Reintroduction And Recolonization Habitat Modeling Using Hydraulic, Sediment And Geomorphic Parameters, Megan Elizabeth Dinicola

All Graduate Theses and Dissertations, Fall 2023 to Present

Freshwater mussels are an important group of aquatic animals that live within the riverbed, but their populations have been drastically reduced by habitat alteration and other anthropogenic activities. In an effort to bolster populations, river managers and biologists are using mussel reintroductions as part of their restoration efforts but there are gaps in our understanding of where to reintroduce mussels within a river to see them create self-sustaining populations. This research helps shrink this gap by better understanding the physical habitat needs and population expansion potential of subadult freshwater mussels, or the size of mussel that hatcheries grow for reintroduction, …


Developing And Improving Digital Image Correlation (Dic) Techniques For Challenging Environments, Prasenjit Dewanjee May 2026

Developing And Improving Digital Image Correlation (Dic) Techniques For Challenging Environments, Prasenjit Dewanjee

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding how materials and parts deform during testing is crucial for creating safer and more reliable engineering systems. Engineers need to measure not only how much a part deforms, but also where deformation concentrates before any damage or failure happens. Digital image correlation (DIC) is a camera-based, non-contact measurement method that tracks surface motion and deformation across a whole area. It is particularly useful when traditional contact-based measurement techniques cannot withstand harsh conditions or capture enough detail. This dissertation develops optical methods to improve DIC in three challenging measurement situations. First, a shortwave ultraviolet lighting technique is developed to reduce …


Extracting Wildfire Influence From Natural Streamflow Variability To Inform Post-Fire Peak Flow Predictions, Haley Anne Canham May 2026

Extracting Wildfire Influence From Natural Streamflow Variability To Inform Post-Fire Peak Flow Predictions, Haley Anne Canham

All Graduate Theses and Dissertations, Fall 2023 to Present

Wildfire is a natural process, however, wildfire occurrence, severity, and size is increasing globally along with large storms. Despite the expectation that floods will be larger after wildfire, a large range in post-fire flood size has been observed. This creates challenges for emergency managers to prepare for flooding in areas where wildfire might occur. Aside from wildfire, many other factors influence the size of floods, making it difficult to isolate the influence of wildfire. This work finds that factors including wetter versus drier years and seasons can alter the size of a flood, effectively hiding the influence of wildfire. Additionally, …


Examining Motivations And Perceptions In Secondary Technology And Engineering Education: A Gendered Analysis Using The Fit-Choice Scale, Abigail Villanueva May 2026

Examining Motivations And Perceptions In Secondary Technology And Engineering Education: A Gendered Analysis Using The Fit-Choice Scale, Abigail Villanueva

All Graduate Theses and Dissertations, Fall 2023 to Present

This study examined why individuals choose to become secondary technology and engineering education (TEE) teachers and whether motivations differ between men and women. TEE programs help prepare students for careers in science, technology, engineering, and math (STEM), yet schools face teacher shortages and low female representation in the field. Understanding what draws people to this profession can support better recruitment and retention efforts. Sixty-six current TEE teachers completed a survey about the factors that influenced their decision to teach. Overall, the strongest motivations were a personal interest in teaching, enjoyment of working with young people, and the desire to make …


A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes Apr 2026

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.


Implementation Of Kansei Engineering Method In Designing Spreadable Cheese Packaging, Novi Purnama Sari, Mega Analisa, Suci Puji Lestari, Khofifah Nur Amalia Apr 2026

Implementation Of Kansei Engineering Method In Designing Spreadable Cheese Packaging, Novi Purnama Sari, Mega Analisa, Suci Puji Lestari, Khofifah Nur Amalia

Makara Journal of Technology

Some spreadable cheese packaging uses flexible plastic without additional features and easily damaged boxes. This packaging causes several problems, such as difficulty in re-storage, loss of product information due to damaged box packaging, wasteful use of packaging materials, and making the product less hygienic. The purpose of this study is to develop packaging that focuses on consumer emotions. The packaging was developed using the Kansei Engineering method, supported by Principal Component Analysis (PCA) as a determinant of the design concept, and Quantification Theory Type 1 (QTT1) to identify design elements. This study produced 46 packaging samples and 40 Kansei words. …


Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi Apr 2026

Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

The computation of eigenvalues and eigenvectors under uncertainty is a fundamental problem in fuzzy linear algebra and decision analysis. When matrix elements are represented by fuzzy numbers, classical spectral methods cannot be directly applied due to nonlinearity, ambiguity in ordering, and the propagation of uncertainty. Moreover, in many practical applications, particularly those involving pairwise comparison matrices, the reliability of eigenvalue-based results strongly depends on the consistency of the underlying data. This paper proposes a consistency-based framework for computing fuzzy eigenvalues and fuzzy eigenvectors that explicitly integrates consistency analysis into the spectral derivation process. The proposed method preserves the fuzzy structure …


Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov Apr 2026

Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …


Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov Apr 2026

Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov

Chemical Technology, Control and Management

This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …


Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova Apr 2026

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.


Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed Apr 2026

Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered …


Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput Apr 2026

Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput

Neutrosophic Systems with Applications

Predicting the stock market is never easy because it is influenced by many uncertain and constantly changing factors such as economic conditions, investor behaviour, and global events. Traditional models like the Crisp Markov Chain (CMC) try to predict market movements by using fixed probabilities for different states like bullish, bearish, or stagnant. However, real markets do not behave in such a strict way—they often move gradually between states, which these models fail to capture. To overcome this limitation, this study introduces a Fuzzy Markov Chain (FMC) model, where fuzzy logic is used to handle uncertainty and allow smoother transitions between …


Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem Apr 2026

Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem

Thesis/ Dissertation Defenses

Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …


The Impact Of People Interests In Evaluating The Open Public Spaces' Quality In The City Centre, Hasan Hadi, Adil Al-Saidi, Haitham Alshamari Apr 2026

The Impact Of People Interests In Evaluating The Open Public Spaces' Quality In The City Centre, Hasan Hadi, Adil Al-Saidi, Haitham Alshamari

HBRC Journal

The quality of open public spaces in city centres significantly affects people's satisfaction and responses to their built environment. The significance of these areas allow people to assess their performance. this paper addresses the issue of People's interests that affect their evaluation of public urban spaces in city centres. The research applied an ontological methodology that is people's experiences determine the spatial quality of the public spaces in city centres. In order to discover and assess the seven value variables, it recommended diagnosing a random sample of users as a group (A) and (B). The urban space in the historic …


The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien Apr 2026

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …


Improving Transfer Portal Decision-Making Through A Microsoft Excel Optimization Model, Peyton Steffes Apr 2026

Improving Transfer Portal Decision-Making Through A Microsoft Excel Optimization Model, Peyton Steffes

Honors Projects

The creation of the transfer portal has increased the mobility of collegiate athletes, giving players the autonomy to switch teams throughout their career. As a result, the roster development process has become more complex, as coaches are tasked with the challenge of recruiting from the transfer portal, which involves an extensive decision-making process. Coaches not only have to evaluate a substantial pool of players, but they also must consider the following constraints they are under: scholarship budget, roster spots available, and positional needs. To simplify this decision-making process, this analysis includes the results of a Microsoft Excel data optimization model …


Problems With Small Drinking Water Systems In Developing And Developed Countries: How Do They Compare?, Kurt Kesteloot Apr 2026

Problems With Small Drinking Water Systems In Developing And Developed Countries: How Do They Compare?, Kurt Kesteloot

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation compares the factors that drive the long-term functionality of small drinking water systems (serving fewer than 10,000 people) in developing and developed country contexts, with a focus on groundwater supplies. Using regression analysis in SAS and complementary fuzzy-set Qualitative Comparative Analysis (fsQCA) for developing countries, the study integrates two datasets: 23 Engineers Without Borders project surveys (90+ variables across 14 countries) and a multi-year National Park Service inspection dataset (approximately 1,561 systems; 7,460 recorded deficiencies, enriched with U.S. Census ZIP-code aggregates). In developing countries, statistically significant predictors of success include government cash contributions (odds ratio [OR] ≈ 67.6), …


Quantitative Study Of The Predictive Correlational Relationship Between Passenger Knowledge, Attitudes, And Behaviors In Aviation Ground Safety Events, Nikkolas Howard Kraay Apr 2026

Quantitative Study Of The Predictive Correlational Relationship Between Passenger Knowledge, Attitudes, And Behaviors In Aviation Ground Safety Events, Nikkolas Howard Kraay

Doctoral Dissertations and Projects

This study examined the relationships between passenger cabin safety knowledge, attitude, and behavior using the Knowledge-Attitude-Behavior (KAB) framework as the guiding theoretical model. Although prior aviation safety research has demonstrated a linear progression from knowledge to attitudes to behaviors, these studies were conducted primarily in Asian cultural contexts. The present study investigated whether this linear sequence would hold within a larger cultural passenger population. A predictive correlational design was used, and data was collected through an online survey completed by 194 adult airline passengers. The instrument measured cabin safety knowledge, attitudes, and behavioral intent, along with demographic characteristics.

Data was …


Study Of Complex Biological Systems Through Ai-Empowered Metabolomic Analysis And Modeling, Runyu Zhao Apr 2026

Study Of Complex Biological Systems Through Ai-Empowered Metabolomic Analysis And Modeling, Runyu Zhao

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation establishes an integrated framework that leverages artificial intelligence (AI) and advanced metabolomics to overcome the "complexity bottleneck" in microbial engineering, specifically addressing the global crises of plastic waste and carbon emissions. By framing the research within the complex biosystems for effective bioproduction and bioremediation, this work develops novel strategies to engineer and analyze biological systems for a circular bioeconomy. In the "Build" phase (Chapter 2), the study addresses the instability of synthetic microbial consortia. By utilizing calcium-alginate hydrogel compartmentalization, the research successfully decouples the growth of the phototroph Synechococcus elongatus from its heterotrophic partners (P. putida and Y. …


Individualized Models For Perception And Cognition, Dominic Marticorena Apr 2026

Individualized Models For Perception And Cognition, Dominic Marticorena

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation develops individualized models of perceptual and cognitive behavior, inferring latent capacities from limited data with sufficient efficiency, precision, and generality for person-level prediction. In perception, a nonparametric Bayesian framework for adaptive psychophysics is extended from audition to vision, producing an estimator that recovers dense individualized contrast sensitivity profiles through variational inference, a generalized kernel, and information-guided stimulus selection. A multitask extension enables simultaneous estimation of multiple psychometric fields by exploiting shared latent structure. Transferring this inferential logic to cognition, where relevant dimensions must be supplied by task design rather than physics, requires new measurement infrastructure. A Minecraft-based platform …


Inference-Time Scaling For Robust And Adaptive Computational Imaging, Yuyang Hu Apr 2026

Inference-Time Scaling For Robust And Adaptive Computational Imaging, Yuyang Hu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging has transformed fields such as medical imaging, computational photography, and remote sensing by combining physical measurement models with advanced image reconstruction algorithms. Two major paradigms have driven significant progress: model-based deep learning (MBDL), which integrates learned priors with physics-based data consistency, and generative models, especially diffusion models, which capture complex image distributions and enable posterior sampling for uncertainty quantification. Despite their success, most existing methods still operate under static inference: they rely on fixed pretrained priors, predetermined sampling procedures, and a fixed forward model during reconstruction. This rigidity limits their robustness in the presence of distribution shift, complex …


A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan Apr 2026

A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan

Thesis/ Dissertation Defenses

Photoplethysmography (PPG) sensing is an important technology used for measuring health parameters like, heart rate, respiratory rate, blood oxygen saturation, and blood pressure (BP). The PPG sensing is used for individuals who have to periodically monitor their health due to chronic health conditions. The basic requirements of a wearable PPG sensor include non-invasiveness, prolonged battery life, and being user-friendly. These type of sensors have great demand in the healthcare applications and there is a significant rise in the demand of these sensors. The basic objective of these PPG sensors is to make the continuous vital health monitoring easier without the …


Project Management Practices In Manufacturing: An Analytical Case Study, Margaret Randle, Robert Reynolds Apr 2026

Project Management Practices In Manufacturing: An Analytical Case Study, Margaret Randle, Robert Reynolds

Honors Capstones

Global industries are undergoing significant transitions in organizational models, technological innovation, and non-economic indicators of product quality, including sustainability and operational efficiency. The current workforce needs to not only develop competency of these technical skills, but also an adaptive, system-oriented approach to problem-solving as well. This case study, which highlights a manufacturing company’s project of increasing production efficiency, presents concepts learned through the textbook Project Management: Achieving Competitive Advantage by Jeffrey K. Pinto. The study thoroughly breaks down the full project lifecycle and the integration of systems of people, data, and initiatives in a framework that can be used to …


Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens Apr 2026

Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens

Senior Honors Theses

One of the challenges in creating computer generated music is producing life-like sounds. Music produced through computer synthesis can often sound thin and synthetic rather than vibrant and energetic. Wavetable synthesis is a method of waveform generation that uses a wavetable, which is a set of single period waves, or frames, that have varying characteristics. This method allows a synthesizer to transition between waveforms to produce a sound with time varying tone and harmonic characteristics. This adds life and movement to computer generated sounds. Wavetable synthesis is often used to imitate actual instruments, but unique wavetables can be created that …