Digital Commons Network^™

Causality Analysis For Neural Network Security, Bing Sun

Dissertations and Theses Collection (Open Access)

While neural networks are demonstrating excellent performance in a wide range of applications, there has been a growing concern on their reliability and dependability.Similar to traditional decision-making programs, neural networks inevitably have defects that need to be identified and mitigated at times. Neural networks are usually inherently black-boxes and do not provide explanations on how and why decisions are made. As a result, these defects are more ``hidden" and more challenging to eliminate. It is thus crucial to develop systematic approaches to identify and mitigate defects in a neural network in a rigorous way.

In this dissertation, we focus on …

Robust Learning With Probabilistic Relaxation Using Hypothesis-Test-Based Sampling, Zilin Wang

Dissertations and Theses Collection (Open Access)

In recent years, deep learning has been a vital tool in various tasks. The performance of a neural network is usually evaluated by empirical risk minimization. However, robustness issues have gained great concern which can be fatal in safety-critical applications. Adversarial training can mitigate the issue by minimizing the loss of worst-case perturbations of data. It is effective in improving the robustness of the model, but it is too conservative, and the plain performance of the model can be unsatisfying. Probabilistic Robust Learning (PRL) empirically balances the average- and worst-case performance while the robustness of the model is not provable …

Towards Robust, Secure, And Privacy-Aware Large Language Models Of Code, Zhou Yang

Dissertations and Theses Collection (Open Access)

The field of software engineering has witnessed a surge in large language models specifically tailored to understand and process code, which we call large language models for code (LLM4Code). The increasing popularity of LLM4Code is inseparable from three key factors: the availability of extensive datasets compiled from diverse data sources, the advancements in deep learning algorithms and computational power that facilitate the training of these powerful models, and the active engagement and collaboration within the research community fostering innovation and the rapid exchange of ideas and methodologies. As evidenced by a series of studies, LLM4Code has been experiencing rapid development …

Manufacturing Enterprises' Gross Margins And Performance: A Study On The Moderating Effect Of Management Expenses And R&D Expenses, Jiuliu Zhang

Dissertations and Theses Collection (Open Access)

In the context of globalization, manufacturing enterprises are integral to national economies, with their financial stability closely related to increasingly fierce market competition. Among various financial metrics, gross margin stands out as a key indicator of product profitability, significantly impacting production decisions, cost control, and pricing strategies. Understanding the relationship between the gross margins of manufacturing enterprises and their performance is essential for optimizing their financial structures and enhancing their market competitiveness. The study aims to investigate the correlation between gross margin and enterprise performance by developing complex, scientifically sound models and utilizing big data analysis technology. Additionally, it examines …

Hafnium Oxide Coating To Improve The Oxidation Behavior Of Zirconium Diboride, Jan E. Förster, William G. Fahrenholtz, Gregory E. Hilmas, Ravisankar Naraparaju

Materials Science and Engineering Faculty Research & Creative Works

Hafnium dioxide (HfO₂) coatings were successfully deposited on zirconium diboride (ZrB₂) using reactive magnetron sputtering. After the oxidation at 1500°C or 1600°C, the mutual dissolution of HfO₂ and thermally grown ZrO₂ was observed which has resulted in the formation of a mixed oxide zone. As the enrichment of the mixed oxide zone by ZrO₂ progresses, monoclinic/tetragonal phase transition temperature of ∼1790°C for nominally pure HfO₂ moves towards ∼1500 °C. Finally, the inevitable phase transition from monoclinic to tetragonal structure results in the development of cracks, pores, and gaps within the mixed oxide …

Machine Learned Interatomic Potentials For Ternary Carbides Trained On The Aflow Database, Josiah Roberts, Biswas Rijal, Simon Divilov, Jon Paul Maria, William G. Fahrenholtz, Douglas E. Wolfe, Donald W. Brenner, Stefano Curtarolo, Eva Zurek

Materials Science and Engineering Faculty Research & Creative Works

Large-density functional theory (DFT) databases are a treasure trove of energies, forces, and stresses that can be used to train machine-learned interatomic potentials for atomistic modeling. Herein, we employ structural relaxations from the AFLOW database to train moment tensor potentials (MTPs) for four carbide systems: CHfTa, CHfZr, CMoW, and CTaTi. The resulting MTPs are used to relax ~6300 random symmetric structures and are subsequently improved via active learning to generate robust potentials (RP) that can relax a wide variety of structures, and accurate potentials (AP) designed for the relaxation of low-energy systems. This protocol is shown to yield convex hulls …

A General Model For The Ductility Of Intermetallics Applied To Fe-Co Alloys, Wesley Everhart, Joseph Newkirk

Materials Science and Engineering Faculty Research & Creative Works

The mechanical properties, specifically ductility, of high performing soft magnets such as Fe-Co alloys are a limiting factor to their broader use in a number of systems. The understanding of the mechanical robustness in these materials is currently insufficient to be able to support the growing interest in applications such as magnetic shielding or electric motors. Fe-Co alloys provide the highest commercially available magnetic saturation and high magnetic permeability but have very poor ductility. The addition of vanadium to these alloys has allowed for significant commercialization and some ductility improvements, but the fundamental reasons for the observed improvements are not …

Observation Of Dense Collisional Soliton Complexes In A Two-Component Bose-Einstein Condensate, Sean M. Mossman, Garyfallia C. Katsimiga, Simeon I. Mistakidis, Alejandro Romero-Ros, Thomas M. Bersano, Peter Schmelcher, Panayotis G. Kevrekidis, Peter Engels

Physics Faculty Research & Creative Works

Solitons Are Nonlinear Solitary Waves Which Maintain their Shape over Time and through Collisions, Occurring in a Variety of Nonlinear Media from Plasmas to Optics. We Present an Experimental and Theoretical Study of Hydrodynamic Phenomena in a Two-Component Atomic Bose-Einstein Condensate Where a Soliton Array Emerges from the Imprinting of a Periodic Spin Pattern by a Microwave Pulse-Based Winding Technique. We Observe the Ensuing Dynamics Which Include Shape Deformations, the Emergence of Dark-Antidark Solitons, Apparent Spatial Frequency Tripling, and Decay and Revival of Contrast Related to Soliton Collisions. for the Densest Arrays, We Obtain Soliton Complexes Where Solitons Undergo Continued …

Publisher Correction: Observation Of Dense Collisional Soliton Complexes In A Two-Component Bose-Einstein Condensate (Communications Physics, (2024), 7, 1, (163), 10.1038/S42005-024-01659-W), Sean M. Mossman, Garyfallia C. Katsimiga, Simeon I. Mistakidis, Alejandro Romero-Ros, Thomas M. Bersano, Peter Schmelcher, Panayotis G. Kevrekidis, Peter Engels

Physics Faculty Research & Creative Works

In the first paragraph of the Methods section, the sentence "We begin with an elongated BEC of approximately 9 x 10587Rb atoms…," has erroneously been written without a space between the two superscripts "5" and "87". This has now been corrected in both the HTML and PDF of the article, and the same expression reads: We begin with an elongated BEC of approximately 9 x 105 87Rb atoms…"

Author Correction: Dual Nature Of Magnetism Driven By Momentum Dependent F-D Kondo Hybridization (Communications Physics, (2024), 7, 1, (186), 10.1038/S42005-024-01631-8), Byungkyun Kang, Yongbin Lee, Liqin Ke, Hyunsoo Kim, Myoung Hwan Kim, Chul Hong Park

Physics Faculty Research & Creative Works

Correction to: Communications Physicshttps://doi.org/10.1038/s42005-024-01631-8, published online 12 June 2024 In this article the grant number DE-AC02-07CH11358 relating to Ames National Laboratory was omitted. The original article has been corrected.

Publisher Correction: Observation Of Dense Collisional Soliton Complexes In A Two-Component Bose-Einstein Condensate (Communications Physics, (2024), 7, 1, (163), 10.1038/S42005-024-01659-W), Sean M. Mossman, Garyfallia C. Katsimiga, Simeon I. Mistakidis, Alejandro Romero-Ros, Thomas M. Bersano, Peter Schmelcher, Panayotis G. Kevrekidis, Peter Engels

Physics Faculty Research & Creative Works

In the first paragraph of the Methods section, the sentence "We begin with an elongated BEC of approximately 9 x 10587Rb atoms…," has erroneously been written without a space between the two superscripts "5" and "87". This has now been corrected in both the HTML and PDF of the article, and the same expression reads: We begin with an elongated BEC of approximately 9 x 105 87Rb atoms…"

Density Effects On The Interferometry Of Efimov States By Modulating Magnetic Fields, G. Bougas, S. I. Mistakidis, P. Giannakeas

Physics Faculty Research & Creative Works

Dynamical association of Efimov trimers in thermal gases by means of modulated magnetic fields has proven very fruitful in determining the binding energy of trimers. The latter was extracted from the number of remaining atoms, which featured oscillatory fringes stemming from the superposition of trimers with atom-dimers. Subsequent theoretical investigations utilizing the time-dependent three-body problem revealed additional association mechanisms, manifested as superpositions of the Efimov state with the trap states and the latter with atom-dimers. The three atoms were initialized in a way to emulate a thermal gas with uniform density. Here, this analysis is extended by taking into account …

Multiphoton-Dressed Rydberg Excitations In A Microwave Cavity With Ultracold Rb Atoms, J. D.Massayuki Kondo, Seth T. Rittenhouse, Daniel Varela Magalhaes, Vasil Rokaj, S. I. Mistakidis, H. R. Sadeghpour, Luis Gustavo Marcassa

Physics Faculty Research & Creative Works

We investigate magneto-optical trap-loss spectroscopy of Rydberg excited Rb85 (66≤n≤68S1/2) atoms, placed inside a tailored microwave cavity. The cavity frequency at 13.053 GHz is in resonance with the 67S1/2→66P3/2 transition, inducing a ladder multiphoton microwave Rydberg absorption and emission. The observed spectra are modeled with an extended Jaynes-Cummings formalism that accounts for nonlinear multiphoton absorption from and emission into the cavity, the loss from the trap due to Rydberg excitation, and cavity imperfection. We calculate the average photons in each spectral feature and find evidence for fractional photon emission into the cavity modes within the loss spectra. The microwave cavity …

Assessing The Predictive Validity Of Expectancy Theory For Academic Performance, Vahe Permzadian, Ting Shen

Psychological Science Faculty Research & Creative Works

Background: Despite expectancy theory's widespread appeal and influence as a framework for motivation in organizational and educational settings, studies that have examined the theory's validity for performance-based outcomes, particularly with academic performance as the criterion, have been characterized by inconsistent results. Given numerous methodological concerns associated with past studies (e.g., prevalence of between-person rather than within-person design), we examined the predictive validity of expectancy theory for academic performance using methods that were consistent with the theory's original conceptualization. Additionally, we assessed the validity of the theory for students' study effort. Methods: The final sample included 123 undergraduate students who reported …

Nodal Superconductivity In Miassite Rh17s15, Hyunsoo Kim, Makariy A. Tanatar, Marcin Kończykowski, Romain Grasset, Udhara S. Kaluarachchi, Serafim Teknowijoyo, Kyuil Cho, Aashish Sapkota, John M. Wilde, Matthew J. Krogstad, Sergey L. Bud'ko, Philip M.R. Brydon, Paul C. Canfield, Ruslan Prozorov

Physics Faculty Research & Creative Works

Solid state chemistry has produced a plethora of materials with properties not found in nature. For example, high-temperature superconductivity in cuprates is drastically different from the superconductivity of naturally occurring metals and alloys and is frequently referred to as unconventional. Unconventional superconductivity is also found in other synthetic compounds, such as iron-based and heavy-fermion superconductors. Here, we report compelling evidence of unconventional nodal superconductivity in synthetic samples of Rh₁₇S₁₅ (Tc = 5.4 K), which is also found in nature as the mineral miassite. We investigated the temperature-dependent variation of the London penetration depth Δλ(T) and the disorder …

Optimisation Of Open Pit Slope Design Considering Groundwater Effects Using Particle Swarm Optimisation And Scaled Boundary Finite Element Method, Dakshith Ruvin Wijesinghe, Ethmadalage Perera, Ean Hin Ooi, Sundararajan Natarajan, Taghi Sherizadeh, Ean Tat Ooi

Mining Engineering Faculty Research & Creative Works

Slopes are a crucial structure in open pit mines. Their design has implications on the economic, safety and environmental operation of the mining industry. Designing stable slopes can be challenging due to the complexities introduced by the stratigraphy and hydrology of the strata. With rising commodity costs and inflation rates, mining operating costs are increasing. Reducing operational costs is necessary for mining industries to remain competitive. While steepening the pit slope can decrease stripping materials and save money, it also increases the risk associated with slope surges. Therefore, optimizing slopes is crucial for both financial and safety reasons. Numerical models …

Full Issue 16(5) Special Issue

Journal of Comparative & International Higher Education

No abstract provided.

Faculty Constructions Of Internationalization: Practice And Perception In Omani Higher Education, Said Al Furqani, Sylvie Lomer

Journal of Comparative & International Higher Education

No abstract provided.

On The Decomposability Of Fractional Allocations, Shurojit Chatterji, Peng Liu

Research Collection School Of Economics

A common practice in dealing with the allocation of indivisible objects is to treat them as infinitely divisible and specify a fractional allocation, which is then implemented as a lottery on integer allocations that are feasible. The question we study is whether an arbitrary fractional allocation can be decomposed as a lottery on an arbitrary set of feasible integer allocations. The main result is a characterization of decomposable fractional allocations, that is obtained by transforming the decomposability problem into a maximum flow problem. We also provide a separate necessary condition for decomposability.

Active Transportation Term Guide, Kalonni Steib

Capstone Projects and Master's Theses

The Monterey County Health Department, through its Planning, Evaluation, and Policy (PEP) Department, is dedicated to promoting health equity by implementing strategic plans, aligning performance standards with national accreditation, and addressing social and environmental policies. Serving underserved and unincorporated communities, PEP focuses on overcoming language barriers in Monterey County, which has a significant Hispanic and Latino population. This project aimed to develop a bilingual glossary of active transportation terms to enhance communication between the community and government agencies. Implemented over three to six months, the glossary was piloted for feedback and updates. The project successfully identified key transportation terms and …

Communicating Development For Adults With Developmental Disabilities, Ruby Mandujano

Capstone Projects and Master's Theses

Adults with intellectual and developmental disabilities (IDDs) often face significant communication barriers that hinder their ability to express needs, access essential services, and engage fully in social, vocational, and healthcare settings. This paper explores how American Sign Language (ASL) can effectively reduce these communication barriers and promote self-advocacy among adults with developmental disabilities. The Gateway Center of Monterey County, an agency serving adults with intellectual and developmental disabilities aged 18 and over, provides a model of communication support by incorporating ASL into its programs. Although Gateway serves only a tiny percentage of the larger population of adults with intellectual and …

Identifying Gaps: Mixtec Parents’ Experiences Within The Salinas Union High School District, Daniela Maldonado Prudencio

Capstone Projects and Master's Theses

The Salinas Union High School District has identified low academic performance among Mixtec-speaking students as a significant issue. Since these students are learning English and Spanish simultaneously, they often face language barriers that affect their academic progress. The school system lacks culturally relevant systems and practices to support their unique needs. This gap also leads to limited parental engagement, as Mixtec-speaking parents struggle to navigate the school system further impacting student’s success. Low graduation rates, limited access to higher education, and limited career opportunities are some of the outcomes. In response, Salinas Union High School Pupil and Personnel Services worked …

Work-Stealing Scheduler For Parallel Cache-Adaptive Algorithms, Chuqi Jiang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Modern computing systems with hierarchical memory structures, such as multiple cache levels, main memory, and external storage, pose significant challenges in optimizing memory usage for algorithm efficiency. Traditional models like the Disk Access Model (DAM) and advancements such as cache-oblivious algorithms have focused on minimizing memory transfers without requiring explicit knowledge of memory hierarchy parameters. However, these approaches assume fixed memory sizes and exclusive cache access, limiting their applicability in real-world, shared-memory environments where memory allocations fluctuate. To address these limitations, cache-adaptive algorithms were developed to dynamically adjust to changing memory profiles, enabling near-optimal performance even in multi-process systems. While …

A Data-Driven Approach For Automated Multi-Site Competitive Facility Location, Ming Hui Tan, Kar Way Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper addresses the challenge of optimal retail expansion in competitive urban environments through a novel approach to the Competitive Facility Location (CFL) problem. Traditional methods for solving CFL problems often struggle with large-scale scenarios, relying on manual pre-selection of candidate sites and imposing limitations on the number of new locations. Our approach leverages Adaptive Large Neighborhood Search (ALNS) enhanced with data enrichment techniques, including community detection on road networks and population weighting based on mobility data. We developed two ALNS variants: Community Geometric Centroid (CGC-ALNS) and Population Weighted Centroid (PWC-ALNS). These methods automate site selection, eliminating manual pre-selection while …

Harnessing The Power Of Ai-Instructor Collaborative Grading Approach: Topic-Based Effective Grading For Semi Open-Ended Multipart Questions, Phyo Yi Win Myint, Siaw Ling Lo, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Semi open-ended multipart questions consist of multiple sub questions within a single question, requiring students to provide certain factual information while allowing them to express their opinion within a defined context. Human grading of such questions can be tedious, constrained by the marking scheme and susceptible to the subjective judgement of instructors. The emergence of large language models (LLMs) such as ChatGPT has significantly advanced the prospect of automatic grading in educational settings. This paper introduces a topic-based grading approach that harnesses LLM capabilities alongside a refined marking scheme to ensure fair and explainable assessment processes. The proposed approach involves …

Gtree: Gpu-Friendly Privacy-Preserving Decision Tree Training And Inference, Qifan Wang, Shujie Cui, Lei Zhou, Ye Dong, Jianli Bai, Yun Sing Koh, Giovanni Russello

Research Collection School Of Computing and Information Systems

Outsourcing Decision tree (DT) training and inference to cloud platforms raises privacy concerns. Recent Secure Multi-Party Computation (MPC)-based methods are hindered by heavy overhead. Few recent studies explored GPUs to improve MPC-protected deep learning, yet integrating GPUs into MPC-protected DT with massive data-dependent operations remains challenging, raising question: can MPC-protected DT training and inference fully leverage GPUs for optimal performance?We present GTree, the first scheme that exploits GPU to accelerate MPC-protected secure DT training and inference. GTree is built across 3 parties who jointly perform DT training and inference with GPUs. GTree is secure against semi-honest adversaries, ensuring that no …

Was 2024 A Good Year For You? Let’S Review Your Yardsticks…, Seow Hon Tan, Su Ching Lim

Research Collection Yong Pung How School Of Law

This op-ed encourages all to reflect on their year and examine whether they have lived meaningfully according to their yardstick of meaning, the legacy they want to leave behind, and whether their talents and credentials are empowering and enabling, rather than restricting them. It is written as part of a research project examining success and flourishing in Singapore.

Introducing The Second-Order Features Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations—Ii: Illustrative Application To Heat And Energy Transfer In The Nordheim–Fuchs Phenomenological Model For Reactor Safety, Dan Gabriel Cacuci

Faculty Publications

This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently the exact expressions of the first- and second-order sensitivities of NODE decoder responses to the neural net’s underlying parameters (weights and initial conditions). The application of the 2nd-FASAM-NODE methodology will be illustrated using the Nordheim–Fuchs phenomenological model for reactor safety, which describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted. The representative model responses that will …

Towards Verified Vision-Based Neural Network Controllers For Autonomous Lane-Following, Xinhang Ma

McKelvey School of Engineering Graduate Student Theses & Dissertations

Vision-based neural network controllers have shown promising results in autonomous lane-following tasks, but verifying their safety properties remains a significant challenge due to the high dimensionality of image inputs. This thesis designs an approach to enable formal verification of vision-based lane-following controllers by first developing an end-to-end autonomous system combining deep learning-based lane detection with reinforcement learning control. To enable formal verification, we introduce a generator-based framework that bridges the gap between high-dimensional image space and low-dimensional vehicle states, allowing us to leverage existing verification tools while maintaining the vision-based nature of the controller.

We further enhance our verification framework …

A Low-Cost Microvascular Phantom For Photoacoustic Imaging Using Loofah, Jinhua Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Existing photoacoustic phantoms are inadequate for mimicking the complex microvascular structures found in human tissue due to their inability to replicate varying sizes and distri- butions of vasculature. This limitation underscores the need for a new material capable of replicating intricate microvascular networks. In this thesis, we introduce loofah as a novel natural phantom material with complex fiber networks ranging from 50 to 400 μm, enabling the fabrication of phantoms with controlled optical properties comparable to those of human microvasculature.

By incorporating a controllable chromophore into the loofah material, we adjusted its ab- sorption properties to match desired specifications. The …