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The Rider (2025-11-17), Daniela Martinez Salazar

The Rider Archives

Vol. 11, No. 12

Evaluating Semantic Representations In Multimodal Word Grounding, Saima Shaukat, Amir Aly, Thomas Wennekers, Angelo Cangelosi

School of Engineering, Computing and Mathematics

Word grounding tasks aim to associate individual words withcorresponding elements in visual scenes, enabling machines to link language with perception for effective human–machine interaction. However,existing grounding models struggle to generalize to synonyms or unseenlexical variants, limiting their performance in open-domain scenarios. Inthis paper, we present a Bayesian multimodal grounding model that incorporates word embeddings as priors within a probabilistic generativeprocess to improve robustness under lexical variation. We compare theeffects of static FastText and contextual BERT embeddings on grounding accuracy by conditioning word–visual associations on their semanticrepresentations. Experiments use CLEVR-generated 3D scenes pairedwith structured compositional descriptions to test the grounding of …

Trajectory Analysis Incorporating Non-Response Weights Via A Non-Parametric Feature-Based Approach And A Bayesian Finite Mixture Model Approach, Samia Sultana

Electronic Theses and Dissertations Archive

While conducting longitudinal population-based research, the most insight concerning a phenomenon can be achieved by analyzing the changing patterns of outcomes over time, rather than depending on overall measures that may mask significant within- and between-individual variation. Trajectory analyses address this need by grouping individuals into sub-populations with similar temporal patterns. In population surveys, dropout and wave non-response can distort estimated trajectories and their prevalence. Non-response weights, defined as the inverse probabilities of response, adjust the representation of under-represented individuals and mitigate the impact of over-represented ones, so restoring the population representativeness of the resultant patterns. Nonetheless, conventional trajectory analysis …

Development And Validation Of A Narrative-Based Personal Epistemology Scale: A Rasch-Guttman Scenario Approach, Luke Walden

Electronic Theses and Dissertations Archive

Quantitative measurement of personal epistemology has faced persistent challenges, with previous instruments often demonstrating poor psychometric functioning and instability across studies. This study introduces and provides an argument for the validity of the Epistemic Reasoning Measure (ERM), a novel scenario-based instrument utilizing the Rasch Guttman Scenario (RGS) methodology to assess absolutism and multiplism across a well-structured (biology) and an ill-structured (history) domain. A pilot sample of 350 undergraduate students and a second wave of 357 undergraduate students completed the four variants of the ERM (absolutism and multiplism for both biology and history). The psychometric properties of the scales were evaluated …

Dual Language In Higher Education: Assessing Student Success And Student Experiences, Katherine Christoffersen, Ramsés Ortín, Dania López García, Ming-Tsan Lu, Javier Cavazos Vela

Writing and Language Studies Faculty Publications

Although long-standing research has documented the many benefits of dual language (DL) education programs in the K-12 setting, there are few studies on the impact of DL in higher education. This study analyzes DL education at a Hispanic-Serving Institution (HSI) where certain classes are taught in Spanish or bilingually across diverse disciplines. In this mixed methods research study, we examine (1) how enrollment in these classes impacts student success through an analysis of cumulative grade point averages, retention, and time to degree and (2) how students perceive these classes through an analysis of course evaluations and surveys responses from current …

Tax Trends, E. S. Linett

Tax Adviser

No abstract provided.

درجة تضمين كتب اللغة الانكليزية السورية الصفين السابع والثامن لمؤشرات الذكاء اللغوي. The Degree Of Inclusion Of Linguistic Intelligence Indicators In The Seventh And Eighth Grade English Textbooks In Syria, سيناء مجمد ذيب الخطيب الجشي

Association of Arab Universities Journal for Education and Psychology

هدف البحث لمعرفة درجة تضمين كتب اللغة الإنكليزية الصفين السابع والثامن (كتاب الطالب وكتاب الأنشطة) في سورية لمؤشرات الذكاء اللغوي، ولتحقيق الهدف تم استخدام المنهج الوصفي التحليلي من خلال أسلوب تحليل المحتوى، وتم إعداد قائمة بمؤشرات الذكاء اللغوي تبعًا للمهارات اللغوية الخمس (الاستماع، القراءة، التحدث، الكتابة، الحس اللغوي)، وأجري لها اختبارات الصدق والثبات اللازمة لضمان موثوقية الأداة.

ولتحليل النتائج اُستخدمت التكرارات والنسب المئوية واختبار كا²(x²) لحسن المطابقة، وجاءت نتائج التحليل كالآتي: أن توزع الذكاء اللغوي جاء متوازن بالنسبة لكتاب الطالب في الصف السابع، بينما لم يكن متوازن بالنسبة للصف الثامن، وبالنسبة لكتابي الأنشطة لم يظهر التحليل …

Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …

Constraints On Inner Core Composition From Seismicanisotropy: The Importance Of Light Elements And Nickel, Jada Bollmeyer, Daniel A. Frost, Prajna Paramita Das

Faculty Publications

The inner core is seismically anisotropic, with PKIKP waves traversing the inner core parallel to the rotation axis faster than those in the equatorial plane. This anisotropy increases with depth into the inner core and may result from alignment of iron crystals deformed during inner core growth. Using previously calculated elastic properties of iron, we seek to determine the most likely iron-light element alloy (FeC, FeO, FeS, or FeSi). For each FeX alloy, we interpolate elastic tensors across the pressure and temperature range of the inner core and model the anisotropy resulting from flow during core growth. Lastly, we compare …

Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …

Climatology Of Northeast Winds In Northern And Central California: A New Characterization Of The Diablo Wind, Alana R. Macken

Master's Theses

Diablo winds in northern California are known for driving some of the most destructive wildfires in state history. The Camp Fire of 2018, which caused at least 85 civilian fatalities, is just one example of the devastating outcomes associated with these rapidly developing downslope windstorms. While they are known to occur most frequently from fall through spring, much about the structure, evolution, and full spatial extent of these events remains poorly understood. Most previous studies have focused on a limited number of high-impact cases or have defined events using humidity-based thresholds in isolated regions such as the North Bay. As …

A Novel Consensus Considering Endo-Confidence With Double-Hierarchy Hesitant Fuzzy Linguistic Term Set And Its Application, Wanqing Li

Double Helix Methodology

Consensus in group decision-making has become a hotspot to ensure the agreement opinions of decision makers (DMs). The irrational behaviors of DMs, such as confidence, will impact the consensus results, which should be considered. In addition, the existing self-confidence level directly given by DMs rather than exacted from evaluation information may generate malicious manipulation. Furthermore, double-hierarchy hesitant fuzzy linguistic term set (DHHFLTS) is an effective tool to express the complex evaluations of DMs. In this paper, the endo-confidence of DHHFLTS to reflect confidence of DMs from the perspective of evaluation information is defined. Then, we propose a novel consensus model …

An Evolutionary Game Approach To Enhancing Semiconductor Supply Chain Security In China: Collaborative Governance And Policy Optimization, Jiang Yu

Double Helix Methodology

In response to the changing international landscape and the risks associated with China’s supply chain security, conducting policy simulations on semiconductor supply chain security helps clarify the industry’s policies and governance strategies for semiconductor supply chain security in China. It also enables a better understanding of the current state and focus areas of China’s semiconductor supply chain security, which is of great significance for improving the security levels of semiconductor supply chains across provinces and cities and for constructing a secure, efficient, and autonomous semiconductor supply chain system. Firstly, this paper reviews the current research on semiconductor supply chains, supply …

Post-Quantum Cryptology: New Constructions And Cryptanalysis, Tran Ngo

Electronic Theses and Dissertations 2020 - Present

Classical cryptographic schemes, which are based on the hardness of factorization and discrete logarithmic problems, can be efficiently solved by the Shor algorithm on a quantum computer. This motivated the 2016 National Institute of Standards and Technology (NIST) call to identify efficient and secure cryptographic schemes that are resilient to potential attacks from both classical and quantum adversaries, a field referred to as post-quantum cryptography. In this work, we focus on designing efficient post-quantum cryptographic primitives based on code-based and lattice-based assumptions, and we analyze their underlying hardness using quantum cryptanalysis. On the construction side, we propose a ring signature …

Malapportionment: A Murder Mystery, Daniel Wodak

Northwestern University Law Review

Malapportionment—electoral districts with divergent ratios of people to representation—was ruled to be unconstitutional in a widely venerated series of cases before the Warren Court. Those cases held that a principle of political equality, one person, one vote, is required by the Constitution. But what is the content of that principle? Many Justices and commentators declare that it is vague, empty, circular, or meaningless. This creates a murder mystery. Malapportionment was killed, but by what exactly? This Article seeks an answer by focusing on the Supreme Court’s commitments about the scope and strictness of one person, one vote: it …

Physics-Informed Deep Learning Reveals Climate-Driven Snowpack Decline And Threatens Ecological Water Availability In A Californian Snow-Fed Catchment, Surendra Maharjan, Wenzhao Li, Rejoice Thomas, Shahyar Fazli, Arshad Ansari, Hesham Morgan, Ali Elgendy, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Mountain snowpack functions as a critical natural reservoir, and its gradual melt sustains streamflow for downstream ecosystems, particularly in arid and semi-arid regions. Climate warming is disrupting these historical patterns by shifting precipitation from snow to rain and accelerating melt, creating an urgent need for robust ecological forecasting tools that can anticipate threats to water availability. Physics-informed machine learning (PIML) offers a powerful approach to this challenge by integrating domain knowledge into flexible data-driven models. This study evaluates and compares the performance of three hydrological modeling approaches: (i) a calibrated process-based Soil and Water Assessment Tool (SWAT), (ii) a data-driven …

Magnesium, Iron, And Calcium Isotope Signatures Of Chicxulub Impact Spherules: Isotopic Fingerprint Of The Projectile And Plume Thermodynamics, Courtney Jean Rundhaug, Martin Schiller, Martin Bizzarro, Zhengbin Deng, Hermann D. Bermúdez

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

The Cretaceous-Paleogene boundary (KPB) represents a massive extinction event in Earth's history, probably triggered by the Chicxulub asteroid impact ∼66 Ma. The event dispersed vast volumes of ejecta materials including exceptionally preserved impact spherules in the Gorgonilla Island KPB section. Previous work identified three populations of spherules at Gorgonilla: 1) ballistically transported molten spherules, 2) a mixture of molten and condensed spherules dispersed by the expansion of a high-temperature, turbulent cloud (the "pyrocloud"), and 3) tiny droplets condensed from the plume (the "fireball layer"). We determine the Mg, Fe, and Ca isotopic compositions of pristine spherules to better understand the …

Shared Voices: How Pk-16 Leaders Perceive School University Partnership Alignment With Caep Standards, Ann-Marie Hancock

Doctoral Dissertations

This mixed-methods study examined PK–16 leaders’ perspectives regarding the alignment of an educator preparation provider (EPP) with the Council for the Accreditation of Educator Preparation (CAEP) Standards 2 (Clinical Partnerships and Practice) and 5 (Quality Assurance System and Continuous Improvement). Data were collected through a researcher-designed survey and semi-structured interviews with principals, district administrators, and university leaders. Survey results provided descriptive insights into stakeholder perceptions, while interviews offered deeper contextual understanding of the strengths and challenges within school–university partnerships. Findings indicated that leaders valued residency programs and recruitment pipelines as key strengths, highlighting the mutual benefits of sustained clinical partnerships. …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties In Gps-Denied Environments, Vivya Kalidindi

Doctoral Dissertations

This dissertation focuses on designing a robust and uncertainty-aware framework for autonomous systems operating in GPS-denied environments, such as indoor infrastructures, underground tunnels, and lunar surfaces. The proposed framework addresses the challenges posed by multi-modal uncertainties, including sensor noise, distributional shifts under adverse conditions, and conflicting decision-making preferences. These challenges compromise the reliability and adaptability of autonomous platforms. To overcome these challenges, the proposed framework adopts a layered architecture that integrates advanced methodologies across the sensing, perception, and decision-making layers. At the sensing layer, an Edge-Kalman Filter combined with a density ratio-based update mechanism is employed to reduce aleatoric uncertainty …

Inverse Design For Generating Initial Conditions In Scientific Simulations, Leslie Horace, Christin Whitton, Vanessa Job, William Jones, Nathan A. Debardeleben

Computing Sciences

We propose a conditional normalizing flow (CNF) surrogate model to solve generative, many-to-one inverse problems in scientific simulations governed by partial differential equations (PDEs) with time-evolving interactions between heterogeneous materials. We present two case studies: electrostatic potential and heat diffusion, which serve as proxy simulations for generating diverse sets of initial conditions that can reproduce an observed output state (transient or steady). Finally, we provide a comprehensive overview of the synthetic datasets, the model specification, each stage of the experimental workflow, evaluation of training performance, and uncertainty quantification for the generated samples.

Connected-Component Labeling Using Hls For High-Energy Particle Physics Instruments, Nick Song, Marion Sudvarg, Roger Chamberlain

Computer Science Faculty Research & Creative Works

Many instruments used in high-energy particle physics observations, e.g., gamma-ray telescopes, use FPGAs for front-end signal processing of raw sensor data. The use of high-level synthesis (HLS) to express the signal processing algorithms has the potential to significantly reduce development time for new instruments of this type. We describe our experience with one of the computational stages in the signal processing pipeline, island detection, exploring its implementation across multiple configurations: 1D versus 2D islands, and 4-way versus 8-way connected-component labeling (CCL) in the 2D configuration. We report resource usage and performance for both configurations of 2D island detection, including the …

Modular Architecture For High-Performance And Low Overhead Data Transfers, Rasman Mubtasim Swargo, Engin Arslan, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

High-performance applications necessitate rapid and dependable transfer of massive datasets across geographically dispersed locations. Traditional file transfer tools often suffer from resource underutilization and instability due to fixed configurations or monolithic optimization methods. We propose AutoMDT, a novel Modular Data Transfer Architecture, to address these issues by employing a deep reinforcement learning agent to simultaneously optimize concurrency levels for read, network, and write operations. This solution incorporates a lightweight network-system simulator, enabling offline training of a Proximal Policy Optimization (PPO) agent in approximately 45 minutes on average, thereby overcoming the impracticality of lengthy online training in production networks. AutoMDT's modular …

The Transitional Human Being: Literary, Journalistic, And Cinematographic Representations Of The Twentieth- And The Twenty-First-Centuries Italy, Ron Kubati

Purdue Studies in Romance Literatures

This book analyzes the crisis of the idea of human being based on timeless notions, in the Euroamerican context, as seen primarily through literature and cinema. It focuses on Italy, which has been and remains a crossroads for diverse cultural and political currents—open to Mediterranean cultural influences while remaining within a typically Western cultural context. The “new man,” defined by Corrado Alvaro during his trip in Russia in 1934 as “transitional,” implies a human being with a fundamental need for change. Instead of the “new man,” Italo Calvino in the 1960 preface to his I nostri antenati wrote about the …

Modeling And Optimizing Real-Time Telescope Interaction For Multi-Wavelength Observation Of Gamma-Ray Bursts, Ye Htet, Marion Sudvarg, Honghao Yang, Jeremy Buhler, Roger Chamberlain, James Buckley

Computer Science Faculty Research & Creative Works

Multi-wavelength observation of gamma-ray bursts (GRBs) requires real-time interaction among multiple telescopes. A gamma-ray telescope detects and localizes a GRB in the sky and must then communicate with an optical telescope to direct the latter toward the GRB as quickly as possible. We previously developed software for ADAPT, a suborbital gamma-ray telescope, to localize GRBs in real time, on a timescale shorter than that of the GRB itself. This work therefore studies progressive localization, in which ADAPT computes a series of increasingly accurate location estimates during a GRB to enable a partner instrument to more rapidly find it. We describe …

Forecasting Pediatric Emergency Department Arrivals: Evaluating The Role Of Exogenous Variables Using Deep Learning Models, Egbe Etu Etu, Jordan Larot, Kindness Etu, Joshua Emakhu, Sara Masoud, Imokhai Tenebe, Gaojian Huang, Satheesh Gunaga, Joseph Miller

Faculty Research, Scholarly, and Creative Activity

Background Forecasting pediatric emergency department (ED) demand remains a critical challenge in healthcare operations. This study aimed to identify exogenous variables influencing pediatric ED visits and evaluate the performance of different forecasting models. Method Using a retrospective observational design, we analyzed 192,347 pediatric ED visits across nine hospitals in Southeast Michigan between 2017 and 2019. Patient data were aggregated into daily arrival counts and enriched with exogenous variables such as weather, air quality, pollen, calendar, Google search trends, and chief complaints. Feature selection was performed using XGBoost and SHapley Additive exPlanations to identify the most influential predictors. Three forecasting models …

Quantum Readiness In Cybersecurity Education: A Framework For Preparing The Next Generation In The Post-Quantum Era, George Antoniou

Faculty and Staff Publications & Presentations

The rapid advancement of quantum computing represents both a revolutionary opportunity and an existential threat to contemporary cybersecurity infrastructure. While quantum computers promise unprecedented computational capabilities, they simultaneously pose a critical risk to current cryptographic protocols that protect sensitive data, financial systems, and national security frameworks. Post-quantum cryptography (PQC) standards, recently formalized by NIST in 2024, provide a roadmap for quantum-resistant encryption. However, a significant gap exists between technological advancement and educational preparedness, with most cybersecurity curricula failing to adequately prepare students for the quantum era. This paper addresses the urgent need for comprehensive quantum readiness in cybersecurity education across …

Advancements In Understanding Spasticity: A Neuromusculoskeletal Modeling Perspective, Mohammad S Shourijeh, Argyrios Stampas, Shuo-Hsiu Chang, Radha Korupolu, Gerard E Francisco

Faculty, Staff and Student Publications

Spasticity, a complex consequence of upper motor neuron lesions, poses challenges for clinical assessment due to its neural and mechanical origins. Traditional scales like the Modified Ashworth and Tardieu Scales provide subjective, context-limited insights, often missing spasticity's dynamic nature. Neuromusculoskeletal (NMS) modeling offers objective, quantitative insights by integrating patient-specific muscle-tendon properties, reflex dynamics, and multi-joint biomechanics. This scoping review examines advancements in spasticity modeling, comparing mechanical, neurological, and integrated approaches, and their applications in conditions like cerebral palsy and stroke. We highlight barriers to clinical translation, including computational demands and regulatory challenges, and propose future directions, such as real-time simulation …

Studying The Corrosion Inhibition Ability Of Metoclopramide Drug On The Copper Surface In Seawater And Theoretical Studies, Nafeesa J. Kadhim, Ahlam M. Farhan, Rasha A. Jassim, Muna S. Sando, Hawraa M. Abdulkareem, Taghried A. Salman

Baghdad Science Journal

Protection study of the corrosion behavior of Copper surface was conducted with several concentrations of drug. Experimentally, voltammetric measurements were used to check the inhibition efficiency (% IE) in saline solution of 3.5% NaCl. The results showed an increase in the inhibition efficiency with increasing the concentration of the drug was 95.90%. Theoretical treatment of the drug in the gas phase was performed using the (hyperchem-8.07) program for molecular mechanics and semi-empirical computations. The (PM3) approach was used to determine the heat of formation (ΔH˚f), binding energy (ΔEb), and total energy (ET) for durq at 298 K. To explore the …

Practicing With Avatars: Exploring Mixed Reality Simulation To Develop Msjccs, Amy L. Cook, Lillian Day, Kristin M. Murphy, Taylor Healy, Julia Kausel, Lindsay M. Fallon, Christopher B. Denning

Journal of Counselor Preparation and Supervision

This study used qualitative content analysis (QCA) to explore perceptions of engaging in Mixed Reality Simulation (MRS) with avatars on the development of Multicultural and Social Justice Counseling Competencies (MSJCCs) for school counselors in training. Results suggested that MRS contributed to improving participants’ confidence in MSJCCs, and they would have valued additional practice with MRS to address implicit bias with clients. Results indicate the need for additional MRS research to advance the development of MSJCCs in school counselor training.