Digital Commons Network^™

Efficient And Green Large Language Models For Software Engineering: Literature Review, Vision, And The Road Ahead, Jieke Shi, Zhou Yang, David Lo

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software Engineering (LLM4SE) area. However, limited attention has been paid to developing efficient LLM4SE techniques that demand minimal computational cost, time, and memory resources, as well as green LLM4SE solutions that reduce energy consumption, water usage, and carbon emissions. This article aims to redirect the focus of the research community toward the efficiency and greenness of LLM4SE, while also sharing potential research directions to achieve this goal. It commences with a brief overview of the significance …

Deepvec: State-Vector Aware Test Case Selection For Enhancing Recurrent Neural Network, Zhonghao Jiang, Meng Yan, Li Huang, Weifeng Sun, Chao Liu, Song Sun, David Lo

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNN) have realized significant achievements across various application domains. There is no doubt that testing and enhancing a pre-trained DNN that has been deployed in an application scenario is crucial, because it can reduce the failures of the DNN. DNN-driven software testing and enhancement require large amounts of labeled data. The high cost and inefficiency caused by the large volume of data of manual labeling, and the time consumption of testing all cases in real scenarios are unacceptable. Therefore, test case selection technologies are proposed to reduce the time cost by selecting and only labeling representative test …

Satellite And Eddy Covariance Analysis Reveals Short-Lived Evapotranspiration Changes After Fire In Mediterranean Woodland, Hoang Long Nguyen, Simone Gelsinari, J. Nik Callow, Richard Silberstein, Sally E. Thompson

Research outputs 2022 to 2026

Ecosystem evapotranspiration (ET) varies through space and time in response to environmental gradients and disturbances like fire. Field-based techniques (e.g. eddy covariance) can directly measure how ET responds to fire; however, these measurements are localised and only represent small areas. Remotely sensed ET products can potentially evaluate fire impacts on ecosystem ET, but their performance for this task remains largely unassessed. This paper uses three widely available remote sensing products: the CSIRO MODIS ReScaled ET (CMRSET), MODIS ET (MOD16), and Penman–Monteith–Leuning (PML), to assess ET changes caused by a fuel reduction burn in a Mediterranean woodland in comparison to the …

Collision Kinematics For Fast Positron Impact Ionization Of Argon, Robert D. Dubois, Károly Tőkési

Physics Faculty Research & Creative Works

Classical trajectory Monte Carlo calculations for 1 keV positron impact ionization of argon are presented. A combination of energy-weighted triple differential cross-sections is shown to provide good to excellent agreement compared with experimental data, depending on the ejected electron azimuthal angular acceptance range used to define in-plane scattering. For ejected electron energies less than 100 eV, information about the influence of pre- (the impact parameter) and post-(the direction of scattering) collision kinematics on the triple differential level is obtained. An overall picture of these kinematic properties is also presented for single differential cross-sections as a function of ejected electron energy …

Performance Evaluation Of Aminated Multi-Walled Carbon Nanotubes Incorporated With Green Synthesized Iron Nanoparticles For Toxic Dyes Sequestration From Textile Wastewater, Titus Chinedu Egbosiuba, Cynthia Chukwuemeka, Jonah Chukwudi Umeuzuegbu, Nwanneka Chibuzo Mmonwuba, Ugochukwu Ewuzie, Monday Uchenna Okoronkwo, Valentine Chikaodili Anadebe, Saheed Mustapha, Ambali Saka Abdulkareem, Jimoh Oladejo Tijani, Ashish Patel, Virendra Kumar Yadav

Chemical and Biochemical Engineering Faculty Research & Creative Works

This study evaluates the performance of aminated multi-walled carbon nanotubes (AM-MWCNTs) integrated with zerovalent iron nanoparticles (ZVI) synthesized using cashew leaf (Anacardium occidentale) extract (AM-MWCNTs@ZVI) for the removal of Congo Red (CR) and Methylene Blue (MB) dyes from textile industrial wastewater. The nanocomposite was characterized using FTIR, XRD, BET, HRSEM, and HRTEM analyses, confirming its functional groups, crystalline structure, and enhanced surface area of 1050.4 m²/g. The ecological risk degree of the textile pollutants was assessed to determine the percentage concentrations of crystal violet, Congo red, methyl orange, methylene blue and rhodamine B. Batch adsorption experiments identified optimal …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori

Theses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Design Of A Deployable Rolled Antenna System For Satellite Applications, Ashwaq Abdulla Alkaabi

Theses

This project presents the development of a deployable Synthetic Aperture Radar (SAR) antenna designed for a 16U CubeSat platform. The primary challenge in SAR satellite design lies in the need for large antennas to achieve high-resolution imaging, which traditionally results in increased satellite size and cost. To address this, the proposed solution employs a scalable 4 × 21 patch antenna array operating at 1.275 GHz, fabricated on a flexible Polyimide-based Printed Circuit Board (PCB). This flexible PCB allows the antenna to safely roll during deployment, avoiding damage and facilitating compact storage. However, Polyimide poses challenges due to higher losses and …

Advancing Academic Advising With Knowledge Graphs: Integrating Machine Learning And Llms For Personalized Course Planning, Sara Alshamsi

Theses

Academic advising plays a critical role in helping students make informed decisions, improve academic performance, and successfully navigate their university journey. However, with increasing university enrollment, traditional advising methods often struggle to scale, leading to student frustration and overburdened advisors. Additionally, designing course offerings that match student demand is a complex and error-prone process involving multiple stakeholders. To address these challenges, this thesis proposes an automated, data-driven system for generating personalized academic plans for students. The primary aim of this thesis is to develop a system that reduces students’ dependency on advisors while simultaneously providing accurate estimates of course demand …

Numerical Methods For Approximating Line Integrals Over Implicitly Defined Curves, Raghd Alsaadawi

Theses

In this thesis, we develop and investigate a predictor-corrector method for the numerical tracing of implicitly defined curves. The study begins with the introduction of modified numerical integration techniques — specifically, the modified trapezoidal and modified midpoint rules — for evaluating the line integral of a vector field along an implicitly defined curve. Furthermore, we explore higher-order methods aimed at improving the accuracy of such integrals. Theoretical and numerical results, including asymptotic error expansions, are presented to support the analysis. In addition, several numerical experiments are carried out to illustrate the effectiveness and robustness of the proposed approaches.

Wavelet-Based Multi-Step Methods For Systems Of Differential Equations, Rashad Assad Hijji

Theses

Wavelets have been widely used in many areas of engineering and mathematics, including the development of multistep algorithms to solve initial value problems (IVPs) in the context of the Galerkin method using Daubechies' wavelets. The main scope of our work is to build a comprehensive framework for solving Systems of Differential equations using the compactly supported wavelets proposed by I. Daubechies. Wavelets are mathematical functions that decompose data into distinct frequency components, and each element is analyzed with a resolution that matches its scale. Compact support of Daubechies wavelets is key in allowing them to be computationally efficient for high-dimensional …

A Neutrosophic And Q-Rung Orthopair Fuzzy Sets Approach For Desertification Susceptibility Mapping: A Case Study In Matrouh, Egypt, Nabil M. Abdelaziz, Khalid A. Eldrandaly, Amira M. Fawzy, Gehan A. Fouad, Safa Al-Saeed

Neutrosophic Systems with Applications

This study introduces an innovative approach to desertification susceptibility mapping by integrating q-rung orthopair fuzzy sets (Q-ROFS) with a neutrosophic environment. Conducted in Matrouh, Egypt, the research quantifies desertification risk through advanced modeling techniques that address uncertainty and non-linearity in environmental data. The Q-ROFS framework enhances risk prediction by capturing complex relationships among desertification indicators. Neutrosophic logic, meanwhile, effectively addresses imprecision and ambiguity. The resulting susceptibility map clearly distinguishes between vulnerable and non-vulnerable regions, offering valuable guidance for policymakers and planners. The analysis revealed that approximately 79.98% of the study area falls under moderate susceptibility, 14.27% under high susceptibility, and …

A Proposed Mathematical Framework For Fuzzy It Service Management (F-Itsm) And Neutrosophic It Service Management (N-Itsm), Takaaki Fujita

Neutrosophic Systems with Applications

Fuzzy sets, rough sets, hyperrough sets, intuitionistic fuzzy sets, neutrosophic sets, plithogenic sets , and other frameworks for handling uncertainty are under active research every day. These concepts can model a wide range of real-world phenomena and are frequently investigated to facilitate more efficient decision-making. IT Service Management is a systematic approach to designing, delivering, managing, and improving IT services in alignment with organizational objectives. In this paper, we explore the Mathematical Frameworks for Fuzzy IT Service Management (F-ITSM) and Neutrosophic IT Service Management (N-ITSM), which combine these uncertainty-based ideas with IT Service Management practices.

Evaluating Disaster Relief In Supply Chains Using A Neutrosophic Mcdm Approach, Nada A. Nabeeh

Neutrosophic Systems with Applications

Disaster-prone regions and affected areas encounter persistent challenges in maintaining supply chain continuity due to environmental uncertainties and infrastructure disruptions. Effective supply chain disaster management (SCDM) is essential for relief disaster disruptions, specifically in upstream processes and functions within the humanitarian supply chain. The integration of advanced technologies like the metaverse and Multiple-Criteria Decision-Making (MCDM) methods supports strategic planning and enhances resilience. This study presents a multi-criteria decision-making (MCDM) proposed approach for disaster relief evaluation in supply chain management. The proposed model integrates Interval-Valued Neutrosophic Numbers (IVNNs) to manage uncertainty and ambiguity inherent in disaster various criteria which are often …

A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache

Neutrosophic Systems with Applications

Neutrosophic statistical analysis has gained attention for incorporating the degree of indeterminacy when analyzing imprecise and interval data under uncertainty–-an aspect often overlooked by classical statistics, fuzzy statistical analysis, and interval statistics. Recently, critical discussions have emerged regarding the use and applications of neutrosophic statistics, with some questioning its usefulness and validity. In this paper, we present a critical assessment of the existing literature, focusing on areas where misunderstandings and misinterpretations of neutrosophic statistical methods have occurred. We also examine flawed comparisons made between the results of neutrosophic statistics and interval statistics. Furthermore, substantial issues have been identified in the …

Biochar Suppresses Growth, Pupation And Eclosion Success Of A Specialist (Manduca Sexta) And A Generalist (Spodoptera Frugiperda) Insect Herbivore, Nischal Wagle, Soumya Unnikrishnan, Satinderpal Kaur, Engil Isadora Pujol Pereira, Rupesh R. Kariyat

School of Earth, Environmental, & Marine Sciences Faculty Publications

Biochar is a charcoal-like substance made by the pyrolysis of organic material from agricultural and forestry waste. While biochar is well documented for altering soil physicochemical conditions, few studies have investigated its possible effects on the management of arthropod pests. Tobacco hornworm (Manduca sexta) and fall armyworm (Spodoptera frugiperda, FAW) are specialist and generalist insect herbivores respectively, that can cause significant defoliation in natural and agricultural ecosystems. In this study, we examined whether walnut shell biochar can affect growth and development of these herbivores. Specifically, we investigated how biochar influences parameters such as mass gain, length …

Exposure To Metoprolol And Propranolol Mixtures On Biochemical, Immunohistochemical, And Molecular Alterations In The American Oyster, Crassostrea Virginica, Andrew Salinas, Md Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Pharmaceutical drugs, particularly beta-blockers (e.g., metoprolol, propranolol, etc.), are extensively used to treat human cardiovascular conditions, yet pose significant risks to non-target aquatic organisms when introduced into coastal and marine environments via wastewater effluent. This study aimed to investigate the effects of short-term exposure (one week) to environmentally relevant concentrations of metoprolol and propranolol (MP) mixtures (low-dose: 50 ng/L propranolol and 250 ng/L metoprolol, and high-dose: 250 ng/L propranolol and 650 ng/L metoprolol) in the American oyster (Crassostrea virginica, a commercially and ecologically important marine bivalve mollusk) under controlled laboratory conditions. Histopathological assessments revealed structural damage to gills, …

Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preformed particle gel (PPG) treatment has proved to be among the most effective methods to reduce excessive water production in fractured reservoirs. The blocking ability of PPGs to fractures or fracture-like features is highly dependent on injected gel properties and volume. Gel dehydration during extrusion through fracture is common and has a considerable effect on gel properties, transport, and plugging efficiency. As the gel particles propagate through the fracture, continuous dehydration is often associated and causes the gel to concentrate and require high-pressure gradients to move. Dehydration might be desirable to a certain limit because it can help to form …

Impact Of Seed Moisture And Temperature On Hemp Seed Germination, Paul Cockson, Andrea Webb, Natalia Martinez-Ochoa, Lindsey Moffitt, Robert Pearce, Manohar Chakrabarti

School of Integrative Biological & Chemical Sciences Faculty Publications

Germination rates of commercial lots of hemp have been highly variable, resulting in poor stand establishment. Germination rates in some seed lots have decreased by 50% after only 1 year of storage. The objective of this trial was to investigate the impact of seed storage conditions on seed germination over time. Industrial hemp (IH) seeds (cv. NWG2730) were harvested from the field. The seeds were cleaned, sorted, and dried to specific moisture contents (MC) 6%, 8%, 10%, and 14%. Seeds were subdivided, placed in hermetically sealed packets, and stored at temperatures of −20°C, 4°C, 10°C, or 21°C for 3, 6, …

The Right Answer For The Wrong Reason: Preservice Science And Mathematics Teacher Preferences And Explanations Of Inquiry-Based Teaching, Elizabeth R. Goldberg, Taylor K. Darwin

School of Integrative Biological & Chemical Sciences Faculty Publications

Inquiry in science and mathematics education has a long and established history within the student-centered teaching movement because it can positively impact student learning, retention, and engagement. Yet few teachers have embraced these practices in the classroom. Potential reasons include misalignment of teachers’ attitudes about inquiry and a lack of understanding of what inquiry is and how to implement it in the classroom. This mixed-methods study compares these claims by examining preservice teachers’ attitudes and knowledge about inquiry-based teaching. Eighty-seven discussion posts were analyzed on preservice science and math teachers’ preferences for inquiry-based versus teacher-centered instruction at the beginning and …

Influence Of Plasma Screening On High-Density Inverse Bremsstrahlung Absorption, D. Turnbull, R. K. Follett, M. Sherlock, D. J. Strozzi, J. Katz, D. Cao, N. R. Shaffer, K. Aytekin, D. H. Edgell, L. Stanton, D. H. Froula

Faculty Research, Scholarly, and Creative Activity

A spherical-implosion platform diagnosed with the "beamlets"scattered-light detector provides high sensitivity to the impact of plasma screening on inverse bremsstrahlung absorption. Contrary to the more restrictive screening length suggested previously [D. Turnbull et al., Phys. Rev. Lett. 130, 145103 (2023)0031-900710.1103/PhysRevLett.130.145103; D. Turnbull et al., Phys. Plasmas 31, 063304 (2024)1070-664X10.1063/5.0203446], the beamlets data indicate that the electron-only Debye length is the relevant screening length for high-density inverse bremsstrahlung absorption. Using the updated absorption model, we simulate the OMEGA direct-drive inertial confinement fusion implosion database and show that bang times are well reproduced without any ad hoc multipliers.

Modeling Femtosecond Laser Interaction With Glass For Optical Fabrication, Nathan Klein

Theses

The fabrication of precision optics is critical for a wide range of applications, including biosensors, virtual and augmented reality, medical imaging, and micro-electronics. However, it is challenging to meet the demands of these applications with conventional chemical and mechanical fabrication methods, as they can introduce chemical waste, mid-spatial-frequency errors, and subsurface damage that degrades image quality. Femtosecond lasers have emerged as a promising alternative, offering fast, non-contact, and chemical-free machining with single digit nanometer precision. This thesis presents a computational model designed to investigate the interaction process between a high-intensity femtosecond laser pulse and dielectric material. A pulse propagation model …

Investigating Hardware Injections In Ligo O3 Data: Simulated Signals From A Neutron Star In A Low-Mass X-Ray Binary, Jediah Gofhaone Tau

Theses

Simulated continuous gravitational wave (CW) signals, called hardware (HW) injections were added to the data in the LIGO detectors' third observing run (O3), including two periodic signals mimicking a spinning neutron star in a binary system, similar to the Low-Mass X-Ray Binary (LMXB) Scorpius X-1 (Sco X-1). Using a cross-correlation pipeline, which searched for CWs from Sco X-1 in O3, we searched for these HW injections, using an uncertainty around the true signal parameters akin to the uncertainty associated with the parameters of Sco X-1. One of the signals, residing in the 230-235 Hz frequency band, was detected. The other …

Observational Predictions For Convective Common Envelopes, Nikki Noughani

Theses

Common envelopes (CEs) are thought to be the main method for producing tight binary systems in the universe, as the orbital period shrinks by several orders of magnitude during this phase. Despite their importance for many stellar evolution channels, direct detections are rare, and thus observational constraints on common envelope physics are often inferred from post-CE populations. Recently, galactic population observations suggest that the CE phase must be highly inefficient at using orbital energy to drive envelope ejection for low-mass systems and highly efficient for high-mass systems. Such a dichotomy has been explained by an interplay between convection, radiation, and …

Artificial Intelligence & Defamation Law: An Excuse To Do Away With The Infamously Controversial Section 230?, Kathryn Binder

UC Law Journal

With the growing prevalence of artificial intelligence (AI) in various aspects of our lives, it is not surprising that it has become a subject of legal disputes and controversy. In 2023, an individual filed the first defamation lawsuit against AI company, OpenAI, for its ChatGPT service, leaving many to speculate how the court will proceed. This Note assesses the viability of defamation actions against generative AI platforms and their broader effect on defamation law. Particularly, this Note considers how courts may characterize these platforms and how specific characterizations could further the controversy over an already polarizing and hotly debated piece …

Poa Annua Ecology, Biology, And Integrated Weed Management Practices In Turfgrass, David Ervin

Environmental Science and Management Faculty Publications and Presentations

Poa annua L. is one of the most widespread and troublesome weeds of turfgrass. It persists as both an annual and perennial and is adaptable to almost any static maintenance regime, including adaptation to mowing heights and evolution of herbicide resistance. This management guide is intended to provide stakeholders with a summary of new and existing knowledge on integrated Poa annua management. Here we review the basic biology and ecology, as well as practical integrated weed management (IWM) strategies developed for its control.

Indigenous Science And The Legacy Of Fire: Resilience, Fuels, Mosaics, And Eco-Cultural Landscapes In Oregon’S Coastal And Cascade Range, Julia Alcalá

University Honors Theses

Most of Oregon's western Cascade and Coastal range is a landscape that has historically been considered devoid of mid to low-intensity fires by Western science. However, for time immemorial, Indigenous peoples have been stewarding the forests through the use of "good fire," creating diverse and heterogenous landscapes with mixed fire regimes, ranging from less than a decade to several centuries since the last fire, resulting in a mosaic of patchy forest, oak savannas, prairies, and wetlands. Yet centuries of Indigenous displacement, cultural assimilation, and suppression of cultural burning contributed to this prevailing belief. Despite that, in recent decades, Western scientists …

Surface Temperature Analysis Report: Kellogg Creek Restoration & Community Enhancement Project, Dalton Palin

University Honors Theses

Kellogg Creek is located in the Kellogg-Mt Scott watershed which flows through downtown Milwaukie, Oregon into the Willamette River. At the confluence of Kellogg Creek and the Willamette River is the Kellogg Dam. This dam impedes salmon, steelhead, and lamprey movement up Kellogg Creek, which is known historically as a salmon and steelhead rearing and migrating habitat. A plan to remove Kellogg Dam and restore 14 acres of Kellogg Creek is in progress by North Clackamas Watersheds Council (NCWC) and partners. Water temperature studies in Kellogg Creek have been conducted for the past several years, this report analyzed thermal surface …

An Exposition Of "Probabilistic Polynomials And Hamming Nearest Neighbors", Vivek Srirama

University Honors Theses

This paper is an exposition of the paper Probabilistic Polynomials and Hamming Nearest Neighbors by Josh Alman and Ryan Williams. It presents the findings of this paper in a more accessible format for Computer Science students earlier in their career who may not be as familiar with Computational Theory and its concepts as their PhD counterparts are. The paper assumes that the reader has a basic understanding of Algorithms and Complexity, typically obtained in an introductory level Algorithms course.

The paper by Alman and Williams analyzes a specific problem known as the Hamming Nearest Neighbor problem. All known solutions for …

Nf2 Loss-Of-Function And Hypoxia Drive Radiation Resistance In Grade 2 Meningiomas, Bhuvic Patel, Sangami Pugazenthi, Collin W English, Vijay Nitturi, Shree S Pari, Tatenda Mahlokozera, William A Leidig, Hsiang-Chih Lu, Alicia Yang, Kaleigh Roberts, Patrick Desouza, Kyle P Mcgeehan, Diane D Mao, Namita Sinha, Joseph E Ippolito, Sonika Dahiya, Allegra Petti, Hiroko Yano, Tiemo J Klisch, Akdes S Harmanci, Akash J Patel, Albert H Kim

Duncan NRI Faculty and Staff Publications

Background: World Health Organization Grade 2 meningiomas (G2Ms) often recur and resist therapies. Grade 2 meningiomas with histopathological necrosis have been associated with worse local control (LC) after radiation therapy, but the drivers and biomarkers of radiation resistance in G2Ms remain unknown.

Methods: We performed genetic sequencing and histopathological analysis of 113 G2Ms and investigated the role of genetic and microenvironmental factors on clonogenic survival after ionizing radiation. We performed transcriptional profiling of our in vitro model and 18 human G2M tumors by bulk RNA sequencing as well as 8 G2Ms by single nuclei RNA sequencing.

Results: NF2 loss-of-function (LOF) …

Contract Quality Feature Extraction Using Llm, Aaron C. Washington

Theses and Dissertations

This study explored the potential insights generated from linguistic complexity measurements and large language model (LLM) based assessments on the quality of contract documents. By combining structured True/False prompts with log-probability analysis and ambiguity scoring, the study introduced novel contract-quality assessment methods. Results support a feature-driven approach to contract evaluation, one that offers automated, scalable insights for triaging risk and improving drafting practices. These assessment methods contribute to the growing field of legal natural language processing by offering modular tools for effective contract analysis.