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Measurement Uncertainty, Barton L. Smith, Douglas R. Neal

Mechanical and Aerospace Engineering Textbooks

This text is based on the graduate Measurements course notes from BLS at Utah State University. It is intended as a textbook for graduate students in engineering or physics or as a reference text.

If one collects several texts on measurement uncertainty, it quickly becomes clear that the measurement uncertainty community lacks a consistent language or nomenclature. This can be confusing to a new reader who may view measurement uncertainty as a very old and settled topic. The lack of consensus on nomenclature likely stems from the lack of a clear winner–a paradigm and nomenclature set sufficiently superior to be …

The Student Movement Volume 110 Issue 7: Packed Calendars, High Stakes, And Cowboy Hats, Aiko J. Ayala Rios, Esther Martin, Megan Constantine, Reagan Westerman, Jj Nixon, Isa Demoraes, Caleb Chung, Laura Pérez, Finnegan Blake, Michael Orellana, Ayanda Dewa, Melissa Moore, Anna Rybachek, Nicoleta Cojan, Corinna Bevier

The Student Movement V. 110 (2025-2026)

ARTS & ENTERTAINMENT

AUSO Travels Through Emotions and Space with Sibelius and Holst, Aiko J. Ayala Rios

More Than A Teacher: Mark Moreno's Influence at SAID, Esther Martin

Roll for Friendship: How the Gaming Club Helps Students Build New Connections, Megan Constantine

More Than Medicine: A Look Into Zoë Oster's Time at Andrews, Reagan Westerman

NEWS

Boots on the Ground and Christmas All Around: AUSA's Holiday Barn Party, JJ Nixon

Men's Cardinals Tip-Off Basketball Season with a Strong Start, Isa DeMoraes

"The Choir of Heaven": Andrews University Fall Choirs' Concert, Caleb Chung

AU Packs Christmas Spirit for Prisoners, Laura Pérez …

Artificial Intelligence (Ai) In Pharmaceutical Formulation And Dosage Calculations., Sameer Joshi, Sandeep Sheth

PCOM Scholarly Works

Artificial intelligence (AI) is reforming pharmaceutical sciences by renovating traditional drug formulation and dosage calculation approaches. This review provides a comprehensive overview of how AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), are currently being used in pharmaceutical calculations to improve accuracy, efficiency, and personalization. We have explored the role of AI in predicting drug properties, excipient optimization, and formulation design, as well as its applications in pharmacokinetic/pharmacodynamic (PK/PD) modeling, real-time dose adjustment, and precision medicine. Despite significant progress, data quality, interpretability, regulatory acceptance, and ethical considerations persist. Therefore, this review examines the …

High School Teachers' Use Of Project-Based Learning To Address Issues Of Equity, Social Justice, And Cultural Relevance, April Serenity Riser

Walden Dissertations and Doctoral Studies

In many educational settings, marginalized populations—African American or Black students, Hispanic students, students in special education programs, and economically disadvantaged students—struggle with traditional assessments, which may create learning gaps. Grounded in Dewey, Vygotsky, and Bruner’s theories, the research problem and purpose of this qualitative single context exploratory case study was to explore high school teachers use of PBL as an innovation to address issues of equity, social justice, and cultural relevance to engage marginalized high school students. Purposeful sampling was utilized to identify 11 high school teachers who employ PBL from multiple campuses in a single school district. Data sources …

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

Infographic: Pisa Insights – Encouraging Mathematical Thinking, Dominique Russell

Teacher infographics

Each cycle of the global Programme for International Student Assessment (PISA) includes a teacher questionnaire. One questionnaire topic – encouraging mathematical thinking – can help foster critical thinking, enhance problem-solving skills and allow students to see the relevance and connectedness of mathematics in their lives.

An Analysis Of Large Language Model Hallucination And Creativity: Linear Representations And Causal Roles, Mckay Bowcut

Theses and Dissertations

Large language models (LLMs) show remarkable abilities in both factual and creative tasks, yet the problem of hallucination persists despite advances in training and post-training methods. Recent progress in model interpretability suggests that model behavior can be predicted and influenced by analyzing and manipulating internal activations. In this thesis, we address three questions: (1) Can we identify linear representations of hallucination and creativity in the model’s latent space? (2) Do these representations play a causal role in model behavior when manipulated? (3) Are creativity and hallucination causally intertwined? To answer these, we construct a novel dataset of factual, hallucinated, and …

From The Editors, Rully Karim Dr.

Journal of Project Management & Construction

The Journal of Project Management and Construction (JPMC) is a peer-reviewed publication dedicated to advancing the field of project management and construction, grounded in the principles outlined in the PMBOK 6th Edition. Our focus encompasses the ten knowledge areas essential to successful project management: Integration, Scope, Schedule, Cost, Quality, Resource, Communications, Risk, Procurement, and Stakeholder Management.

JPMC publishes original research papers written in English that provide deeper insights into these knowledge areas and contribute to the development of best practices in project management and construction. Submissions may include theoretical analyses, computational models, experimental observations, or a combination of both theoretical …

Perceptions Of K–5 Teacher Challenges In Supporting Military-Connected Children Overseas Who Experience Trauma, Lachanda Garrison

Walden Dissertations and Doctoral Studies

Teachers serving U.S. military-connected students (MCS) overseas regularly address student trauma in the classroom that stems from relocation and separation events due to parents’ or guardians’ military service. The problem addressed in this study was that Grade K–5 teachers struggle to support overseas who experience trauma. The purpose of this basic qualitative study was to explore Grade K–5 teachers’ perceptions of the challenges to support MCS overseas who have experienced trauma. The study was guided by three principles from Soma and Allen’s trauma informed model, which emphasizes understanding trauma as an experience, prioritizing social and emotional skill development, and supporting …

Teachers’ Perceptions Of The National Professional Development Policies And Mathematics Performance In Guyana, Nicola Marcia Johnson

Walden Dissertations and Doctoral Studies

The Ministry of Education in Guyana has focused on improving primary students’ performance in mathematics; however, low student performance persists. The problem addressed in this study was the limited understanding of how Guyanese primary teachers used the national professional development policies (NPDP) to address the low performance of students on the Math National Grade 6 Assessment (MNGSA). Grounded in Bandura’s social cognitive theory and Senge’s systems thinking theory, the purpose of this study was to explore Guyanese primary teachers’ perceptions of their successes and challenges using the NPDP to address the low performance of students on the MNGSA. For this …

Semiconductors & Microelectronics In Middle School Technology & Engineering: Integrating Emerging Stem Workforce Contexts Into The Classroom, Greg J. Strimel, Deana Lucas, Yubin Lee, Victoria Constantine, Tamara J. Moore, Morgan Hynes, Selcen Guzey

School of Engineering Technology Faculty Publications

This case study explores the integration of microelectronics contexts and content into middle school classrooms as part of a workforce development initiative intended to address national labor force needs arising from increased investments in the semiconductor industry. The study follows four middle school technology and engineering teachers as they develop, implement, and refine an instructional unit designed to introduce students to microelectronics production and semiconductor-related careers. Through classroom observations and iterative curriculum development, this exploratory case study reviewed how emerging STEM workforce contexts, such as semiconductors and microelectronics, can be integrated into middle school instruction. The results provide a practical …

Sga 57 Senate 2025-11-07 Minutes, Niu Student Government Association Senate

Student Government Association Archives

No abstract provided.

On Heat Engines Having Efficiencies That Degrade With Every Cycle That Are Nonetheless Reversible: The Wonders Of Hilbert Curves In The Pressure-Volume Plane, Daniel Graham

Chemistry: Faculty Publications and Other Works

Heat engines are cornerstones in classical thermodynamics, not to mention fixtures of everyday life. As everyone knows, real heat engines are rife with sources of irreversibility, and, in turn, have efficiencies that degrade over time. Here we chart a classical heat engine whose efficiency degrades with every cycle, but maintains perfect reversibility nonetheless. There are no paradoxes in play due to the inviolability of the thermodynamic laws. Rather the engine operates transparently according to Hilbert curves that fill the pressure-volume plane. The assembly of the curves is iterative and digital whereby no information is lost over every cycle.

On Perturbed Best Response Learning And Equilibrium Selection In Homogeneous And Bayesian Evolutionary Games, Sayan Mukherjee

Doctoral Theses

Evolutionary game theory is a sub-field of game theory concerned with the behavior of large populations of strategically interacting players who recurrently revise their strategies based on the availability of better payoff opportunities. In such games, rather than directly focusing on the equilibrium analysis (as in the case of static/one-shot games), the strategic behavior of the population is modeled via an evolutionary game dynamic (a differential equation on a suitable state space of the population). Consequently, the theory aims to study the asymptotic properties (such as stability, convergence) of these evolutionary dynamics. An important class of evolutionary dynamic studied in …

Development And Initial Validation Of An Instrument To Measure Teachers’ Socioscientific Issues Instruction Perceptions, Michael Edward Mitchell

USF Tampa Graduate Theses and Dissertations

Little is known about how high school science teachers perceive Socioscientific Issues (SSI) on a broad scale, including what factors shape their views of a pedagogical shift to adopt SSI. To address this critical gap, I constructed the Teachers’ Socioscientific Issues (SSI) Perceptions Survey (TSPS), the first instrument specifically designed and initially validated to measure teacher perceptions of SSI integration. This study presents the development and validation of the TSPS, offering robust evidence for its reliability, fairness, and construct validity.

Survey development adhered to gold-standard psychometric protocols (Bandalos, 2018; Crocker & Algina, 1986; DeVellis, 2012; McCoach et al., 2013) and …

Spatio-Temporal Characterization Of Trace Metals Across The West Florida Shelf And During The Decline Of The North Atlantic Spring Bloom, Delfina Paola Navarro-Estrada

USF Tampa Graduate Theses and Dissertations

Phytoplankton in the marine environment require the trace metals manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd) to catalyze cellular processes driving photosynthesis, including macronutrient (nitrogen, phosphorus, and carbon) acquisition, light harvesting, and protection from oxidative stress. The high biological demand for these elements, coupled with their low concentrations in the ocean, can limit primary production and shape community composition in marine ecosystems, highlighting the need to understand the drivers behind trace metal distributions and their interplay with phytoplankton growth across biogeochemical regimes. This dissertation characterizes the spatial and temporal distributions of dissolved …

Saudi Early Childhood Teacher Educators’ And Preservice Teachers’ Perspectives Of Early Field Experiences, Amani M. Alodwani

USF Tampa Graduate Theses and Dissertations

This qualitative descriptive study explores how teacher educators perceive the integration of field experiences within the curriculum and their perspectives on the preservice early childhood education (ECE) teachers they supervise. It also examines preservice teachers’ views regarding their field experiences and how these experiences contribute to their professional preparation. The Ministry of Education (MOE) emphasizes that teacher preparation programs should provide extended field experiences that connect theoretical coursework with practical application. Semi-structured interviews were conducted with three Saudi teacher educators and four preservice teachers from Kingdom University. Thematic analysis using inductive coding was employed to identify recurring themes and differences …

Sound Practices In Human Resources: A Critical Analysis Of How Ai Applicant Screening Tools Are Used With Deaf Individuals In The Hospitality And Tourism Sector, Sherry L. Gaynor

USF Tampa Graduate Theses and Dissertations

This study explores the intersection of Career and Workforce Education, Deaf Education, and artificial intelligence (AI) technologies used in hiring practices. The purpose of this research is to identify potential barriers to equitable employment for Deaf and Hard-of-Hearing (DHH) individuals and to propose effective methods for evaluating and assessing AI and machine learning applications utilized in recruitment and selection processes. Although AI is increasingly embedded in human resource management (HRM), there remains a significant lack of research addressing its use with special populations. In particular, no prior studies have examined how voice recognition software, facial analysis, psychometric testing, and virtual …

Statistical Challenges And Simulation Results For Pilot Clinical Trials, Weiliang Cen

USF Tampa Graduate Theses and Dissertations

Background: The effect size estimated from a pilot trial is often an inaccurate reflection of the true effect size observed in a large trial, leading to either underestimation or overestimation. Published data suggest that effect sizes from large trials are typically smaller than those reported in their corresponding pilot trials. To address this discrepancy, conservative or discount adjustment methods are widely recommended to modify pilot trial effect sizes when calculating sample sizes, thereby maintaining adequate statistical power. This study aims to assess effect sizes from both pilot and large trials and to evaluate the performance of existing adjustment methods.

Methods: …

A Robust And Energy-Efficient Federated Ids For Iiot Using Spiking Neural Networks And Differential Evolution With Adversarial Resilience, Mohammad Othman Nassar

Iraqi Journal for Computer Science and Mathematics

The Industrial Internet of Things (IIoT) is faced with increasing cybersecurity threats that require lightweight, fast, and resilient intrusion detection systems (IDS). This study presents a novel federated IDS framework that integrates federated learning (FL), Spiking Neural Networks (SNNs), and differential evolution (DE). The use of SNNs within a federated context is a rare and innovative contribution that enables effective temporal feature extraction from IIoT traffic. DE is employed as a global optimization mechanism, enhancing robustness and generalization beyond conventional federated aggregation. To further strengthen resilience, synthetic adversarial noise is injected during training, allowing evaluation in realistic poisoning scenarios. The …

Enhancing It Security Management With An Advanced Intrusion Detection System Based On Machine Learning And Explainable Ai, Hanan Alzubaidi

Thesis/ Dissertation Defenses

The fast-changing landscape of cyber threats continues to challenge the development of strong and reliable security frameworks for IT management systems. Traditional defense tools, such as Intrusion Detection Systems (IDS), often struggle to keep up with today’s advanced and constantly evolving attack methods. This thesis explores these ongoing challenges and looks into how machine learning (ML) and explainable artificial intelligence (XAI) can be used to boost IDS performance.

The research outlines a smart, adaptive system that combines supervised learning for real-time threat detection, unsupervised models for anomaly analysis, and proactive defense strategies. The goal is to improve detection accuracy, cut …

Augmented Reality-Assisted E-Module On Temperature Andheat Content (Emarks), Tetri Sabrina, Ika Mustika Sari, Dedi Sasmita

Jurnal Pendidikan Sains

Temperature and heat content (calor) material in physics often involves concepts and phenomena that are difficult to observe directly or are abstract (such as energy transfer, particle movement, and changes in state). EMARKS (AR-based E-modules) are important because Augmented Reality (AR) allows the visualization of these abstract concepts in the form of interactive 3D models in the user's real environment. This helps students understand the concepts more concretely and easily. The development of E-modules is an innovation in learning media that is relevant to the demands of the digital era and the needs of modern students. The use of advanced …

Analysis Of An Effective Training Curriculum: Solutions Toincrease Participants' Interest In Training Teachingmaterials, Maulidya Husnul Khatimah, Yoto Yoto

Jurnal Pendidikan Sains

This research is important because it analyzes the curriculum as a primary tool for generating and maintaining participant interest. Curricula that are irrelevant, monotonous, or misaligned with participant needs are often the main causes of low motivation and participation. Furthermore, this research encourages the exploration and implementation of more innovative teaching methods and materials in training curricula. External pressure in the form of demands or instructions, rather than internal motivation, drives most training activities. This can reduce engagement and learning effectiveness. To overcome this, training institutions need to design programs that are relevant, flexible, and able to encourage participants' intrinsic …

The Effect Of Guided Inquiry Model With Deep Learningapproach On Student’S Hots In Elements, Compounds,And Mixtures At Junior High School, Friska Pakpahana, Retno Dwi Suyanti

Jurnal Pendidikan Sains

The current education curriculum places a strong emphasis on developing HOTS skills (such as analyzing, evaluating, and creating) to prepare students for the challenges of the 21st century. School learning often focuses on lower-level cognitive domains (memorizing and understanding). This research seeks to address this gap by offering a potentially effective learning model. The guided inquiry model positions students as active participants in learning, encouraging them to investigate, discover, and formulate concepts independently with teacher guidance. This strongly supports the development of critical thinking and problem-solving skills. Therefore, this study aims to analyze the effect of the guided inquiry model …

Development Of Problem-Based Learning Worksheet Toenhance Ecoliteracy: Human Impact On Ecosystem, Ulina M.S. Simangunsong, B. Manurung, Martina Asiati Napitupulu

Jurnal Pendidikan Sains

Ecoliteracy (ecological literacy) is an individual's ability to understand basic ecological principles and make environmentally responsible decisions. Improving ecoliteracy is a crucial foundation for realizing Education for Sustainable Development (ESD), which prepares students to become proactive citizens in protecting the environment. The problem-based learning model helps students learn on their own by using real-world environmental cases to get them to think critically and solve problems. Therefore, this research aims to determine the effectiveness of using problem-based learning worksheets to enhance the ecoliteracy of seventh-grade students. The development model used is 4-D. The research instruments include expert validation forms for subject, …

Development Of E-Lkpd Assisted By Phet Colorado Basedon Discovery Learning: Critical Thinking Skills On Lightmaterial At Junior High School, Flora Yani Saragih, Pintor Simamora

Jurnal Pendidikan Sains

Critical thinking is necessary for 21st-century pupils, but PISA data suggest that Indonesian students, especially junior high school students, lack it. The junior high science/physics light material is abstract and involves in-depth reasoning (reflection, refraction, and shadow generation). Without critical thinking, kids memorize formulas or notions without analyzing real phenomena. Discovery learning involves pupils discovering concepts via observation and experimentation. Critical thinking requires initiative, exploration, and reasoning, which these foster. Therefore, this study aims to develop E-LKPD based on Discovery Learning assisted by an interactive simulation of PhET Colorado to strengthen the critical thinking skills of grade VIII students on …

Guided Inquiry Learning Assisted By Crossword Puzzlemedia: Student Scientific Literacy And Critical Thinkingability For Middle School, Agis Putri Niswa, Mariati Purnama Simanjuntak, Ramlan Silaban, Fauziyah Harahap, Ridwan Abdullah Sani

Jurnal Pendidikan Sains

Scientific literacy and critical thinking skills are two fundamental competencies that students need in the 21st century. Scientific literacy is essential for students to understand and use scientific knowledge to make informed decisions, while critical thinking trains students to analyze information, evaluate arguments, and solve problems logically. Therefore, the intent of this study was to determine the effect of the guided inquiry learning model assisted by crossword puzzle media on students’ scientific literacy and critical thinking skills. The type of research used was quasi-experimental with a two-group pretest-posttest design. The sample consisted of two classes: class VII-8 as the control …

Computer Organization With Arm64, Seth D. Bergmann

OER Textbooks

This book is intended to be used for a first course in computer organization, or computer architecture. It assumes that all digital components can be constructed from fundamental logic gates.

The book begins with number representation schemes and assembly language for the ARM-64 architecture, including assembler directives and floating point instructions. It then describes the machine language instruction formats, and shows the student how to translate an assembly language program to machine language.

There is then an introduction to boolean algebra and digital logic, followed by a description of the memory hierarchy, including cache memory, RAM, and virtual memory.

The …

Torso Synthetic Ct Generation By Integrating Deep Learning And Segmentation For Fdg-Pet/Mr Attenuation Correction, Jin Uk Heo, Robert S. Jones, Theodore Higgins Arsenault, Jennifer Dorth, Tithi Biswas, Raymond F. Muzic Jr

Faculty Scholarship

Introduction. Positron Emission Tomography/Magnetic Resonance (PET/MR) offers benefits over PET/CT including simultaneous PET and MR acquisition, intrinsic spatial registration accuracy, MR-based functional information, and superior soft tissue contrast. However, accurate attenuation correction (AC) for PET remains challenging as MR signals do not directly correspond to attenuation. Using deep learning algorithms that learn complex relationships, we generate synthetic CT (sCT) from MR for AC. Our novel method for AC, merges deep learning with threshold-based segmentation, to produce an AC map for the entire torso from Dixon MR images, which heretofore has not been demonstrated. Method. Twenty-nine prospectively collected, paired FDG-PET/CT and …

Interpretable Machine Learning For Cardiovascular Risk Prediction: Insights From Nhanes Dietary And Health Data, Md Ahiduzzaman, Md Nahid Hasan

Faculty Publications

Background: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination Survey (NHANES) data from 2017–2023 to predict CVD risk based on dietary and health factors.

Methods: We analyzed data from 12,382 adults (aged 18 and older) from NHANES 2017–2023, including 41 dietary, anthropometric, clinical, and demographic variables. Recursive Feature Elimination (RFE) was used to select an optimal subset of 30 predictors. To address substantial class imbalance in the outcome, we applied the Random Over-Sampling Examples …