Digital Commons Network^™

Cutting Mechanisms And Control Systems Required For Precision Cutting With An Autonomous Lettuce Harvester, Aidan V. Fischer

Master's Theses

43% of California’s vast land is consumed for agricultural production to feed the United States and other nations Lettuce production alone brought in over $3 billion in 2022 in California. Most of the lettuce today is still harvested by hand using large groups of seasonal laborers; however, this has become increasingly difficult with an immigrant labor shortage. The objective of this study was to design a low-cost autonomous lettuce harvester prototype and evaluate the performance of the harvester capable of harvesting romaine lettuce preciously on a raised bed.

The harvester is equipped with an electrohydraulic control system that is used …

Neuronal And Glial Cell Alterations Involved In The Retinal Degeneration Of The Familial Dysautonomia Optic Neuropathy, Anastasia Schultz, Henar Albertos-Arranz, Xavier Sánchez Sáez, Jamie Morgan, Diane Darland, Alejandra Gonzalez-Duarte, Horacio Kaufmann, Carlos E. Mendoza-Santiesteban, Nicolás Cuenca, Frances Lefcort

Biology Faculty Publications

Familial dysautonomia (FD) is a rare genetic neurodevelopmental and neurodegenerative disorder. In addition to the autonomic and peripheral sensory neuropathies that challenge patient survival, one of the most debilitating symptoms affecting patients' quality of life is progressive blindness resulting from the steady loss of retinal ganglion cells (RGCs).Within the FD community, there is a concerted effort to develop treatments to prevent the loss of RGCs. However, the mechanisms underlying the death of RGCs are not well understood. To study the mechanisms underlying RGC death, Pax6-cre;Elp1loxp/loxp male and female mice and postmortem retinal tissue from an FD patient were used to …

Understanding Ai Literacy: Implications For Practice, Sara Westall, Janet Anderson, Devon Olson

Librarian Publications

A presentation developed for the fall 2024 University of North Dakota School of Medicine and Health Sciences Medical Curriculum Advance, exploring the connections between information literacy, artificial intelligence literacy, and algorithmic literacy and their relevance to health education from the perspective of research and instruction librarians.

Decoding Emotions: Unveiling Facial Expressions Through Acoustic Sensing With Contrastive Attention, Guangjing Wang, Juexing Wang, Ce Zhou, Weikang Ding, Huacheng Zeng, Tianxing Li, Qiben Yan

Computer Science Faculty Research & Creative Works

Expression recognition holds great promise for applications such as content recommendation and mental healthcare by accurately detecting users’ emotional states. Traditional methods often rely on cameras or wearable sensors, which raise privacy concerns and add extra device burdens. In addition, existing acoustic-based methods struggle to maintain satisfactory performance when there is a distribution shift between the training dataset and the inference dataset. In this paper, we introduce FacER+, an active acoustic facial expression recognition system, which eliminates the requirement for external microphone arrays. FacER+ extracts facial expression features by analyzing the echoes of near-ultrasound signals emitted between the 3D facial …

From A Timeline Contact Graph To Close Contact Tracing And Infection Diffusion Intervention, Yipeng Zhang, Zhifeng Bao, Yuchen Li, Baihua Zheng, Xiaoli Wang

Research Collection School Of Computing and Information Systems

This paper proposes a novel graph structure to address the problems of information spreading in a real-world, frequently updating graph, with two main contributions at hand: accurately tracing infection diffusion according to fine-grained user movements and finding vulnerable vertices under the virus immunization scenario to mitigate infection diffusion. Unlike previous work that primarily predicts the long-term epidemic trend at the census level, this study aims to intervene in the short-term at the individual level. Therefore, two downstream tasks are formulated to illustrate practicalities: Epidemic Mitigating in Public Area problem (EMA) and Epidemic Maximized Spread in Public Area problem (ESA), where …

Adan: Adaptive Nesterov Momentum Algorithm For Faster Optimizing Deep Models, Xingyu Xie, Pan Zhou, Huan Li, Zhouchen Lin, Shuicheng Yan

Research Collection School Of Computing and Information Systems

In deep learning, different kinds of deep networks typically need different optimizers, which have to be chosen after multiple trials, making the training process inefficient. To relieve this issue and consistently improve the model training speed across deep networks, we propose the ADAptive Nesterov momentum algorithm, Adan for short. Adan first reformulates the vanilla Nesterov acceleration to develop a new Nesterov momentum estimation (NME) method, which avoids the extra overhead of computing gradient at the extrapolation point. Then Adan adopts NME to estimate the gradient's first- and second-order moments in adaptive gradient algorithms for convergence acceleration. Besides, we prove that …

Towards Privacy-Aware Iot Communications: Delegable, Revocable, And Efficient, Pengfei Wu, Jianfei Sun, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is widely recognized for its potential to enhance efficiency and productivity across various industries. However, its increasing prevalence has also made it a more attractive target for cybercriminals. While many advanced cryptographic solutions have been developed to secure IoT, some practical security and privacy issues such as self-sovereign delegation, flexible revocation, and lightweight access remain inadequately addressed in existing solutions. In this paper, we propose PLIC, a Privacy-aware Lightweight IoT Communication scheme, which not only enables any authorized user to flexibly delegate their lightweight access privileges to other delegatees, such that they can also access …

Ohss: Optimizing Homomorphic Secret Sharing To Support Fast Matrix Multiplication, Shuguang Zhang, Jianli Bai, Kun Tu, Ziyue Yin, Chan Liu

Research Collection School Of Computing and Information Systems

Homomorphic Secret Sharing (HSS) has evolved as a state-of-the-art methodology for achieving secure two-party computation, synthesizing the advantages of secret sharing and homomorphic encryption. This amalgamation ensures minimal computational and communicational overhead, making it particularly adept at arithmetic operations. However, HSS faces challenges in scalability and efficiency when confronted with extensive matrix operations, including both matrix-vector and matrix-matrix multiplications, which are fundamental in numerous privacy-preserving computations, notably within the realm of privacy-preserving machine learning. In this research, we introduce Optimized Homomorphic Secret Sharing (OHSS), a refined version of HSS, crafted to address these limitations. Our contributions include enhancements to the …

Reflections On Linear B, (Part 6): Possible Origin Of The Shape And Pronunciation /Ko/ Of Sign 70, Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

This article suggests that the shape of Linear B sign 70 may derive from the Egyptian hieroglyph uatch ‘young plant, green’ and that its pronunciation /ko/ is explainable by the Greek word for green (χλωρός).

Collaboration! Towards Robust Neural Methods For Routing Problems, Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang, Zhiqi Shen

Research Collection School Of Computing and Information Systems

Despite enjoying desirable efficiency and reduced reliance on domain expertise, existing neural methods for vehicle routing problems (VRPs) suffer from severe robustness issues – their performance significantly deteriorates on clean instances with crafted perturbations. To enhance robustness, we propose an ensemble-based Collaborative Neural Framework (CNF) w.r.t. the defense of neural VRP methods, which is crucial yet underexplored in the literature. Given a neural VRP method, we adversarially train multiple models in a collaborative manner to synergistically promote robustness against attacks, while boosting standard generalization on clean instances. A neural router is designed to adeptly distribute training instances among models, enhancing …

Towards General Conceptual Model Editing Via Adversarial Representation Engineering, Yihao Zhang, Zeming Wei, Jun Sun, Meng Sun

Research Collection School Of Computing and Information Systems

Since the rapid development of Large Language Models (LLMs) has achieved remarkable success, understanding and rectifying their internal complex mechanisms has become an urgent issue. Recent research has attempted to interpret their behaviors through the lens of inner representation. However, developing practical and efficient methods for applying these representations for general and flexible model editing remains challenging. In this work, we explore how to leverage insights from representation engineering to guide the editing of LLMs by deploying a representation sensor as an editing oracle. We first identify the importance of a robust and reliable sensor during editing, then propose an …

Ali-Agent: Assessing Llms’ Alignment With Human Values Via Agent-Based Evaluation, Jingnan Zheng, Han Wang, Tai D. Nguyen, An Zhang, Jun Sun, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) can elicit unintended and even harmful content when misaligned with human values, posing severe risks to users and society. To mitigate these risks, current evaluation benchmarks predominantly employ expertdesigned contextual scenarios to assess how well LLMs align with human values. However, the labor-intensive nature of these benchmarks limits their test scope, hindering their ability to generalize to the extensive variety of open-world use cases and identify rare but crucial long-tail risks. Additionally, these static tests fail to adapt to the rapid evolution of LLMs, making it hard to evaluate timely alignment issues. To address these challenges, …

Replay-And-Forget-Free Graph Class-Incremental Learning: A Task Profiling And Prompting Approach, Chaoxi Niu, Guansong Pang, Ling Chen, Bing Liu

Research Collection School Of Computing and Information Systems

Class-incremental learning (CIL) aims to continually learn a sequence of tasks, with each task consisting of a set of unique classes. Graph CIL (GCIL) follows the same setting but needs to deal with graph tasks (e.g., node classification in a graph). The key characteristic of CIL lies in the absence of task identifiers (IDs) during inference, which causes a significant challenge in separating classes from different tasks (i.e., inter-task class separation). Being able to accurately predict the task IDs can help address this issue, but it is a challenging problem. In this paper, we show theoretically that accurate task ID …

Safety Through Feedback In Constrained Rl, Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri

Research Collection School Of Computing and Information Systems

In safety-critical RL settings, the inclusion of an additional cost function is often favoured over the arduous task of modifying the reward function to ensure the agent's safe behaviour. However, designing or evaluating such a cost function can be prohibitively expensive. For instance, in the domain of self-driving, designing a cost function that encompasses all unsafe behaviours (e.g., aggressive lane changes, risky overtakes) is inherently complex, it must also consider all the actors present in the scene making it expensive to evaluate. In such scenarios, the cost function can be learned from feedback collected offline in between training rounds. This …

Converting Vocal Performances Into Sheet Music Leveraging Large Language Models, Jinjing Jiang, Nicole Teo, Haibo Pen, Seng-Beng Ho, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Advanced natural language processing (NLP) models are increasingly applied in music composition and performance, particularly for generating vocal melodies and simulating singing voices. While NLP techniques have been effective in analyzing vocal performance data to assess quality and style, the automatic transcription of vocal performances into sheet music remains a significant challenge. Manual transcription tools often fall short due to the intricate dynamics of vocal expression. This study tackles the automation of vocal performance transcription into sheet music using innovative techniques, including large language models (LLMs). We propose a method to translate vocal audio input into display-ready sheet music effectively. …

Predictors In Help-Seeking Intentions For Friends With Eating Disorders, Allie M. Robb

Honors Theses

Emotional intelligence is a significant factor in one’s well-being as high emotional intelligence predicts sound mental well-being and a better quality of life as one can accurately understand emotions (Kulkarni & Velhal, 2023). However, low emotional intelligence has also been found to be a predictor not only of the development of mental health disorders but also have the lowest intentions to seek help (Ciarrochi et. al., 2002; Kulkarni & Velhal, 2023). Because they are unlikely to seek help, it is important for others who see the potential cause to help intervene. The purpose of this study is to investigate the …

Examining Primary Teachers' Concerns, Self-Efficacy, Attitudes, Intentions, And Challenges Of Implementing Inclusive Pedagogy In English Literacy Classrooms For Bilingual Dyslexic Students In The Uae, Robin Ogdol, Jose Roan Adorna, Romee Capate, Aisha Alteneiji

All Works

The United Arab Emirates has embraced inclusive education across all academic levels since 2006. However, the degree of teacher acceptance of inclusive practice varies. This mixed-methods case study investigated 48 primary school teachers’ concerns, self-efficacy, attitudes, and intentions regarding inclusive pedagogy in English literacy for bilingual dyslexic students aged 5-11. It also identified challenges faced by teachers in mainstream classes. Using correlation analysis, results showed negative associations between teachers’ concerns and efficacy, attitudes, and intentions for inclusive practices. On the other hand, positive associations were found between teacher efficacy, attitude, and intentions for inclusive practices. Challenges included reconciling the bilingual …

Understanding The Equality Of Parties In Arbitration: A Case Comment On International Seaport Dredging Private Limited V Kamarajar Port Limited, Sahana Ramesh

National Law School Journal

While the Supreme Court of India has emphasised the equality of arbitrating parties in several decisions, the court often had to use various tools to assert this. It is a question of policy as to whether statutory undertakings—that perform public functions by entering commercial transactions—must be given preferential treatment in certain aspects of the dispute settlement process, including when they choose to challenge an arbitral award. This case comment considers the decision of the Supreme Court of India in International Seaport Dredging Private Limited v Kamarajar Port Limited to highlight the nuances involved in the court’s conclusion that all …

Reimagining Constitutional Institutions: Integrity, Efficiency, And Accountability (Justice Es Venkataramiah Centennial Memorial Lecture), Justice Ps Narasimha

National Law School Journal

In this 'Justice ES Venkataramiah Centennial Memorial Lecture' delivered at the National Law School of India University in 2024, Justice PS Narasimha lays down the importance of fourth branch institutions. He points to the constitutional history and framework that established them, lays down their evolution, and examines their role and functioning in the current context.

Comparison Of Statistical And Machine Learning Genomic Prediction Methods In Plant Breeding: Case Studies In Maize And Soybean, Igor Kuivjogi Fernandes

Graduate Theses and Dissertations

Plant breeding is essential to increase genetic gain and food production worldwide. This study was conducted to evaluate new ways to use machine learning (ML) to tackle plant breeding challenges, where two ideas were tested — the first chapter focuses on how to combine genetic and environmental data using ML to improve the prediction of maize grain yield in multi-environment trials, while the second chapter centers on how to couple feature selection of molecular markers with ML to enhance prediction of yield in soybean, and, in both cases, ML approaches were compared to well-established statistical methods greatly adopted by the …

Preventing Depression In Grandparents Raising Grandchildren: An Educational Video Series, Sabrina Casares

Student Capstone Papers

This paper presents a doctoral capstone project that created and implemented a self-help occupation-based educational video series to prevent and manage depression among grandparent caregivers. It consists of a literature review regarding the impact of depression on grandparent caregivers, the population’s barriers and statistics relating to the correlation of developing depression as a grandparent caregiver. It includes the process to create the video series including review of the literature and the development process. Texas Grandparents Raising Grandchildren (TXGRG) is a non-profit organization dedicated to providing resources and support to empower and advocate for grandparent caregivers. Problem: There is a lack …

The Effects Of Multiple Acute Turkesterone Doses On Indirect Measures Of Hypertrophy And Metabolic Measures: A Preliminary Investigation, Dillon R. Harris, Tomas Chapman-Lopez, Steven B. Machek, Jeffery S. Forsse, Tracey Sulak, Leslee K. Funderburk

Kinesiology Faculty Publications and Presentations

Turkesterone is a naturally occurring plant steroid touted for its medicinal, pharmacological, and biological properties with no reported adverse side effects compared with traditional anabolic androgenic steroids (AAS). However, this ostensible enhancement to increase muscle protein synthesis and facilitate augmented thermogenesis remains undescribed despite uninformed and potentially haphazard consumption. To investigate whether turkesterone enhances insulin-like growth factor-1 (IGF-1) and resting metabolic rate (RMR), eleven apparently healthy males (23.3 ± 2.2) volunteered to participate in the present study with samples collected pre-, 3H post-, and 24H post-ingestion. Subsequent analyses failed to reveal any significant main condition, time, or interaction main effects …

Dealing With Divisiveness: Ignatian Principles For Better Relationships, Thomas G. Plante Phd, Abpp

Psychology

Interpersonal and intergroup relationships seem to have steadily deteriorated in recent years, with an increase in the lack of civility and decency along with a greater willingness to attack and cancel anyone who does not agree with one’s cherished perspective on numerous matters. New popular phrases such as cancel culture, public shaming, air rage, and gaslighting have entered the common vernacular. Ignatian spirituality offers several helpful strategies for dealing with these contemporary divisive conflicts in a productive manner. These include (1) seeing God (or the sacred) in all things, (2) striving towards kinship with others through the pathway of civility, …

Technical Report: Technical Support For Developing And Field Testing In Situ Bioassays In The Surface Mixing Layer Of Marine Waters At Oil Spill, G. A. Burton, A. Crane, B. Chadwick, G. Rosen, G. Stewart, S. Allan, O. Garcia-Pineda

Coastal Response Research Center

An in situ technology was developed to assess the toxicity of oil spills to aquatic organisms in the water column. This technology, named the Drifting Exposure and Effects Assessment Ring (DEEAR), is comprised of a bioassay tool known as the Sediment Ecotoxicity Assessment Ring (SEA Ring), mounted within a drifting drogue known as the Drifting Particle Simulator (DPS). The technology also includes a UV fluorometer that continuously senses oil fluorescence, as well as passive sampling devices that can be used to quantify average concentrations of oil-based compounds. The DEEAR system was tested in the field in 2019, after which refinements …

A105: Correlation Analysis Between Cognitive Style And Judgment Accuracy Of Tennis Umpires In Zhejiang Province, Kairui Cai, Wensheng He

International Journal of Physical Activity and Health

Background/Purpose: The influence of cognitive style on decision-making in sports has always been a hot research direction in sports psychology. As the law enforcers in the stadium, the individual cognitive style of the umpire in the penalty will also affect the results of a game to an extent. This paper studied the accuracy of on-the-spot decision-making judgment of tennis umpires classified by field dependent-field independent cognitive style and provided a new idea and scientific method for the selection and cultivation of tennis umpires.

Methods/Design: In this experiment, literature method, experimental method, mathematical statistics, logical analysis method and other related research …

A143: Integrating Stakeholder Theory And Swot Analysis To Examine Covid-19 Outbreak Impact On Fitness Programs, Xinxin Li, Ran Ran

International Journal of Physical Activity and Health

Background/Purpose: The fitness industry has been an important segment in the sports-related global market (SFIA, 2020). The U.S. Bureau of Labor Statistics Occupations Projection (2016-2026) indicated there would be an 18.70% annual occupational employment percentage increase in the need for athletic trainers (CareerOneStop, 2019). The U.S. 71394 Gym, Health & Fitness Clubs Report revealed a 1%–6% revenue increase each year since 2012. This projection indicated that the fitness market uptrend would continue in the next decade. However, the COVID-19 outbreak had a significant impact on the fitness market, and it was projected to have a 10% revenue decline in 2020 …

Biological Validation Of Peak-Width Of Skeletonized Mean Diffusivity As A Vcid Biomarker: The Markvcid Consortium, Alison M Luckey, Saptaparni Ghosh, Chen-Pin Wang, Alexa Beiser, Rebecca Bernal, Zhiguang Li, Djass Mbangdadji, Elyas Fadaee, Haykel Snoussi, Angel Gabriel Velarde Dediós, Hector A Trevino, Monica Goss, Laura J Hillmer, Christopher E Bauer, Adam M Staffaroni, Lara Stables, Marilyn Albert, Jayandra J Himali, Thomas H Mosley, Lars Forsberg, Vilmundur Guðnason, Baljeet Singh, Herpreet Singh, Kristin Schwab, Joel H Kramer, Gary A Rosenberg, Karl G Helmer, Steven M Greenberg, Mohamad Habes, Danny J J Wang, Brian T Gold, Hanzhang Lu, Arvind Caprihan, Myriam Fornage, Lenore J Launer, Konstantinos Arfanakis, Sudha Seshadri, Charles Decarli, Pauline Maillard, Claudia L Satizabal

Faculty, Staff and Student Publications

BACKGROUND: Peak-width of skeletonized mean diffusivity (PSMD), a neuroimaging marker of cerebral small vessel disease (SVD), has shown excellent instrumental properties. Here, we extend our work to perform a biological validation of PSMD.

METHODS: We included 396 participants from the Biomarkers for Vascular Contributions to Cognitive Impairment and Dementia (MarkVCID-1) Consortium and three replication samples (Cohorts for Heart and Aging Research in Genomic Epidemiology = 6172, Rush University Medical Center = 287, University of California Davis Alzheimer's Disease Research Center = 567). PSMD was derived from diffusion tensor imaging using an automated algorithm. We related PSMD to a composite measure …

Primary And Secondary Resonances Of Fringe Effect Electrostatically Actuated Mems Cantilever Resonators, Miguel Armando Martinez

Theses and Dissertations

The nonlinear dynamics of micro-electromechanical system (MEMS) cantilever resonators actuated by the fringe field at parametric and primary resonances are studied. Three models are used based on different descriptions of the system capacitance. In the fringe and capacitance models, the electrostatic force due to the parallel-plate capacitance is neglected due to a hole in the ground plate (removes overlapping area). The SolidWorks model is based on numerical capacitance simulations performed on SolidWorks using EMS. All three models that approximate the fringe field capacitance are compared with one another. The Method of Multiple Scales (MMS) and Reduced Order Model (ROM) up …

The Effects Of Livestock On Mosquito Diversity And Abundance In Hidalgo County, Taylor Nicole Moya

Theses and Dissertations

Mosquitoes are detrimental to animals and threaten humans. More information is needed on how farm animal presence may impact mosquito abundance and diversity at farms. My goal in this study is to determine if there is any correlation between animal abundance or diversity on a farm and the abundance and diversity of mosquitoes collected. Hidalgo County, Texas, has a subtropical desert climate, ideal for mosquitoes. I hypothesized that the mosquito abundance and diversity indices would increase as the livestock abundance or diversity increases. Adult mosquitoes were collected using two CO2-baited light traps per farm from Spring 2022 to Fall 2022. …

Structure Modifications And Alternative Monitoring Designs Of Wildlife Road Mitigation Structures, Madison T. Nadler

Theses and Dissertations

Wildlife mitigation structures are designed to keep animals off roadways while providing them safe passage to the other side and not impeding traffic flow. Camera traps are commonly used to assess the success of these mitigation structures, but there are downfalls to both the methods and structures. Alternative mitigation structure designs are needed to better prevent wildlife from accessing roadways in areas where they should be deterred. Additionally, traditional camera trapping methods do not accurately capture the full wildlife communities that may be utilizing these structures and other survey methods are needed, specifically aimed at small mammals, amphibians, and reptiles. …