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Nsu Florida Undergraduate Student Catalog 2025-2026, Nova Southeastern University

Undergraduate Programs Course Catalogs

No abstract provided.

Economic Outlook Of Battle Creek: Challenges And Opportunities, Iryna V. Lendel, Chloe Wieber, Sevrin Williams, Gerrit Anderson

Upjohn Institute Technical Reports

This report by the W.E. Upjohn Institute for Employment Research examines labor market dynamics in Battle Creek, finding that roughly 75 percent of jobs in the city are held by workers who live outside the city limits, with significant skill mismatches between city residents and local employer needs. This mismatch helps explain persistently low wages, elevated poverty rates, and high reliance on public assistance among city residents despite a strong manufacturing base and growing logistics, food processing, and machining sectors. Limited housing supply, inadequate public transportation, and childcare shortages further restrict residents’ access to employment. The report underscores the urgency …

Electron Transport Layers In Thin-Film Solar Cells: Materials, Interfaces, And Device Performance, Mohammad Khairul Basher, Samiul Sadek, Tarek Abedin, Mohammad Nur-E-Alam, Mongi Amami, Rajesh Haldhar, M. Khalid Hossain

Research outputs 2022 to 2026

Thin-film photovoltaic technologies such as perovskite, CIGS, CdTe, and organic solar cells have gained considerable attention due to their potential for low-cost, flexible, and lightweight energy conversion solutions, necessitating advanced components to optimize device efficiency and stability. A complex component in these devices is the electron transport layer (ETL), which governs charge extraction and recombination dynamics, directly impacting overall performance. Despite numerous advances, there remains a lack of unified understanding of ETL materials and interface engineering, highlighting a research gap in cross-technology comparative studies and universal design principles. This review addresses this gap by systematically analyzing ETL materials, interface modification …

Comparison Of The Behavior Of Semiconductor Lasers Under The Influence Of Changing Bias Current With Optoelectronic Feedback, Tareq A. Al Attabi, Salam Jasim Majeed, Muwaffaq Abdullah

AUIQ Conference Proceedings

Direct pump modulation is one feature of semiconductor lasers that sets them apart from other types of lasers. Another degree of flexibility is the injection current disruption. Consequently, instabilities are caused by the disruption of the injection current in semiconductor lasers, and the modulation of the injection current does in fact show instabilities and chaotic behaviors. This research investigates a comparative study between conventional and nanoscale semiconductor lasers. The occurrence of different laser outputs from both types of semiconductor lasers, including the typical output from these devices as well as periodic, multi-periodic, aperiodic, and chaotic ones that arise from injection …

Critical Design And The Robotic Imaginary: Design Criticism And Critical Robots, Jörgen Behrendtz

The Journal of Sociotechnical Critique

This paper brings critical design and design criticism to critical robot studies. Critical design can be described as an umbrella term for approaches making use of speculative designs to highlight and challenge narrow assumptions, preconceptions or even taken-for-granted truths about the role products play (in a wide sense) in everyday life. Design criticism refers to a reasoned procedure that investigates emancipatory and/or limiting potentials of designs, theorizes the roles of affordances, materials and embodied perception as epistemological resources in media interaction, and clarifies connections between specific design choices and their associated experiential qualities, seductive powers, ideological underpinnings, material operations, and …

Scattering Point, Jeff Gundy

Creative Nonfiction Magazine

No abstract provided.

Are Banks "Ripping Off' The Consumer When It Comes To Mortgages?

Journal of Economics and Finance Education

In this pedagogical paper, we answer two questions: If someone has a fixed-rate mortgage and pays it off after only a few years, is the bank "ripping off' the consumer because of the low equity; and when is the interest portion of a mortgage payment exactly equal to the principal portion? The mathematics inherent to a fixed-rate mortgage dictate that a greater portion of interest is paid in the early years. To find the exact point in time when the interest and principal payments are exactly equal requires examining this question using continuous function mathematics.

Know Math Or Take A Bath On A Finance Final Exam

Journal of Economics and Finance Education

Math is central to finance education, yet three-quarters of this sample of 159 introductory finance students lack critical quantitative skills on the first day of class, leading to overall underperformance. By utilizing criterion-referenced mathematics pretest items and matching applied finance posttest items, we find that students with substandard math skills rarely catch-up in the quantitative aspects of introductory finance. Indeed, the pretest determines a significant proportion of final exam performance, with the average student gaining a meager 5% between pretest and posttest. We discuss curricular implications of these findings and research-based approaches to facilitate course readiness.

Cover To Cover Reviews Of New Books, Laurie Graham, Betsy Hurley, Bruce Dobler, Larry Bielawski, Lea Simonds

Creative Nonfiction Magazine

No abstract provided.

Blow Out, Blow Back, Blow Up, Blow Off: The Plutonomic Politics Of Economic Crisis Since 2001, Timothy W. Luke

Fast Capitalism

No abstract provided.

Does Math Confidence Matter? How Student Perceptions Create Barriers To Success In Economics Classes

Journal of Economics and Finance Education

One of the most common obstacles in the economics classroom is facing students’ disinclination to perform tasks requiring basic quantitative skills. Economics, relative to other disciplines, is particularly bridled by this challenge since mastery of economics requires sufficient mathematical proficiency to elicit anxiety and resistance in many students but is not widely regarded as math intensive enough to generate a selection effect of highly quantitative students. This paper attempts to measure undergraduate economics students’ perceptions of their level of “mathiness” or mathematical abilities and anxieties and then identifies the impact of those perceptions on the students’ performance in economics courses.

Clarifying The Meaning Of Noninteger N Values In Annuity Calculations

Journal of Economics and Finance Education

Time value of money problems are integral to finance. We focus attention on the issues raised when a noninteger solution results from solving for the variable N (number of periods) in a time value of money annuity problem. We show that such a numerical solution, while mathematically correct, can deviate from the narrative of the problem. This deviation from the narrative could cause misunderstandings between instructors and their students and practitioners and their clients. We demonstrate how instructors and practitioners can explain the deviation from the narrative in such cases, and how cash flows can be adjusted to avoid missing …

An Excel-Based Approach For Teaching Markowitz’S Portfolio Optimization Theory

Journal of Economics and Finance Education

This paper presents a simple method for teaching the Markowitz Portfolio Optimization topic. The use of Microsoft Excel or Corel Quattro Pro enables students and investors who do not possess a great deal of mathematical and programming expertise to identify meanvariance efficient portfolios which consist of more than two assets. Through this hands-on learning experience, students achieve a deeper understanding of the theory. The exercise also gives the students an eye opening lesson on the practical usability of spreadsheets.

Predictors Of Success In An Online Undergraduate Core Course In Finance

Journal of Economics and Finance Education

Because finance is a technically oriented business subject where competence in math and accounting plays a role in student success, we posit that technical knowledge, as proxied by math and accounting pre-tests, may predict success in an online undergraduate finance course. Since little or no lecture support is generally offered while taking an online course, students that struggle with math or accounting may have a greater challenge with the online format for a finance course. Accordingly, the purpose of this study is to evaluate the key determinants of success in an online core course in finance.

Teaching Mathematical Economics Using Public Choice: The Median Voter Model

Journal of Economics and Finance Education

The median voter model (MVM) is a core model in public choice comparable to the demand and supply competitive market model in microeconomics. In this paper I introduce and discuss the mathematical treatment of a simple version of the model. This allows instructors to apply a wide range of concepts commonly introduced in a first undergraduate class in mathematical economics. The approach will help students to understand the interplay of concepts separately introduced during the first phase of the course. Hopefully the method will foster an interest in public choice through the study of one of its most important benchmark …

A Clinical Mathematical Model Estimating Postoperative Urine Output In Children Underwent Cardiopulmonary Bypass For Congenital Heart Surgery, Orkun Baloglu, Shawn D. Ryan, Ali M. Onder, David Rosen, Charles J. Mullett, Daniel S. Munther

Journal of Pediatric Intensive Care

Objectives: To build a proof of concept clinical mathematical model estimating postoperative urine output (UOP) utilizing pre-operative, intra-operative and immediate postoperative variables in children underwent cardiopulmonary bypass (CPB) for congenital heart surgery. Methods: Single-center, retrospective cohort study in a university-affiliated children’s hospital. Patients younger than 21 years old who underwent CPB for congenital heart surgery and were postoperatively admitted to West Virginia University Children’s Hospital`s pediatric intensive care unit (PICU) between September 1, 2007, and June 31, 2013 were included in the study. Body surface area, CPB duration, first measured hematocrit, serum pH, central venous pressure and vasoactive-inotropic score in …

Proactive Learned Indexing Driven By Query Workload Forecasting, Mukesh Kumar Marodia, Virender Kumar Singla, Saurabh Uttam

Defensive Publications Series

Systems for data indexing can involve a trade-off between the upfront cost of static indexes and potentially suboptimal performance from on-demand data scanning, while some reactive adaptive methods may incur an initial query latency penalty. This disclosure describes systems and methods for predictive, learned adaptive indexing. A forecasting component, which may use a sequence-aware machine learning model, can analyze historical query patterns to predict future data access ranges. Based on these predictions, a system can speculatively trigger just-in-time index construction on anticipated data partitions, for example, using available system resources. This proactive approach, which can be combined with a reactive …

Creating Realistic Virtual Spaces Using Laser Scans And Panoramic Images, Qian Zhang, Yunwen Zhou, Erin Hong, Eric Lee Turner, Dinghuang Ji, Jürgen Sturm

Defensive Publications Series

A method is disclosed for generating scalable, high-fidelity scene replicas by optimizing 3D Gaussian Splats directly within the equirectangular domain. Conventional pipelines often convert spherical scanner data into perspective views or surface meshes, a process that frequently introduces stitching artifacts, geometric seams, and floaters. To address these limitations, the described approach utilizes a differentiable panorama splat rasterizer. This component processes registered laser scan data and 3D point clouds natively in a spherical format, without projecting imagery onto flat perspective planes. By refining spherical harmonic coefficients and opacity through backpropagation against the original panoramic inputs, the method effectively mitigates conversion-induced distortions. …

Scalable Personalized Score Approximation Via Core Subgraph Pre-Computation, Leonid Kuligin

Defensive Publications Series

Computing link analysis algorithm scores for individual nodes in a large-scale graph can be computationally expensive, which may limit practical application. A technique for approximating such a computation may be applied to graphs that can be partitioned into a core subgraph (G1) and a peripheral subgraph (G2) without edges pointing from G1 to G2. The approach may involve pre-computing and caching pruned vectors for nodes within the G1 subgraph. A link analysis algorithm score for a node in the G2 subgraph can then be approximated by calculating a linear combination, such as an arithmetic mean, of the cached vectors corresponding …

Adaptive Correction Of Digital Map Features Using A Text-Guided Generative Model, Yotam Intrator, Idan Kligvasser, Ehud Rivlin, Amir Livne

Defensive Publications Series

Static machine learning models applied in automated cartography may produce inaccurate map features or may not adapt to localized guidelines without potentially costly retraining. A post-processing framework can utilize a multi-modal, text-guided generative model to perform adaptive corrections. For example, a system can receive a visual representation of a map segment, such as a raster image of road markings, and a set of natural language guidelines as input. The generative model can then process these inputs to synthesize a new visual representation where map features may be altered to conform with the specified guidelines. This approach can decouple correction logic …

Global Spatiotemporal Multi-Criteria Analysis Of Coastal Risk: Current And Future Hot Spots And Clusters, Marco Bidoia, Carlo Giupponi

Fondazione Eni Enrico Mattei Working Papers

Coastal zones are among the environments most threatened by climate change. Although various efforts for global mapping and classification of coastal social and ecological systems have been undertaken, the ability to analyse and describe the spatial heterogeneity and multidimensionality of these phenomena remains limited. In the current study, we developed a methodological framework for assessing risk from extreme sea levels and examined its application at the global level. A multi-criteria analysis method was applied to the current scenario and to two future combinations of shared socioeconomic (SSP2 and 5) and representative concentration pathways (RCP4.5 and 8.5), accounting for risk attitudes. …

Better It Disaster Recovery And Procedures To Improve Response After Computer Crime, Allan Eduardo Arroyo-Melendez

Walden Dissertations and Doctoral Studies

A lack of an effective disaster recovery plan (DRP) can negatively impact business outcomes following a cyberattack. Information technology (IT) managers are concerned that the lack of DRP may increase the risk of ransomware, fines, and public distrust. Grounded in the unified theory of acceptance and use of technology, the purpose of this qualitative pragmatic inquiry study is to explore strategies that some IT managers use to implement a DRP. The participants are four IT managers in the southeast United States. Data were collected through semistructured interviews and a review of publicly available documents. Through thematic analysis, three themes were …

Teacher Perspectives Of Their Challenges In Supporting K-3 Students In Mathematics Proficiency, Jasmine Chanel Mills

Walden Dissertations and Doctoral Studies

The problem for this study was that mathematics preparation for students in K–3 classrooms often does not lead to mathematics proficiency for third grade students. Guided by Wigfield’s expectancy value theory, the purpose of this qualitative study was to explore teachers’ perspectives of children’s expectations and values related to mathematics and challenges teachers describe in supporting children’s mathematics achievement. Data were collected through 12 semistructured interviews with K–3 teachers in in a public school district in the eastern United States. Thematic analysis using open coding resulted in six themes which indicated that teacher beliefs and expectations are associated with mathematics …

Use Of Electrocardiograms To Identify Coronary Artery Disease: Cross-Validation Of An Artificial Intelligence Model, Michael Leasure, Indu Poornima, Adam Butchy, Utkars Jain, Devin Vasoya, Michael Warnick, Brent Williams, John Rehder, Prahlad Menon, Veronica A. Covalesky, Gary S. Mintz

Department of Medicine Faculty Papers

BACKGROUND: The current gold standard for the diagnosis of coronary artery disease (CAD) is invasive angiography; however, it is an invasive procedure. Therefore, we developed an artificial intelligence model designed to predict significant CAD from a resting digital 12-lead electrocardiogram (ECG).

OBJECTIVES: This retrospective study assessed the model's ability to predict clinically significant CAD in a patient population presenting for coronary angiography.

METHODS: From 2019 to 2021, 16,476 patients had a resting 12-lead digital ECG recorded within 90 days prior to coronary angiography. The artificial intelligence model was developed using 10-fold cross-validation methodology. Clinically significant disease was defined as angiographic …

Black Hole Spectroscopy And Tests Of General Relativity With Gw250114, The Ligo Scientific Collaboration, The Virgo Collaboration, The Kagra Collaboration

Department of Physics and Astronomy Faculty Scholarship and Creative Works

The binary black hole signal GW250114, the loudest gravitational wave detected to date, offers a unique opportunity to test Einstein’s general relativity (GR) in the high-velocity, strong-gravity regime and probe whether the remnant conforms to the Kerr metric. Upon perturbation, black holes emit a spectrum of damped sinusoids with specific, complex frequencies. Our analysis of the postmerger signal shows that at least two quasinormal modes are required to explain the data, with the most damped remaining statistically significant for about one cycle. We probe the remnant’s Kerr nature by constraining the spectroscopic pattern of the dominant quadrupolar (ℓ =𝑚 =2) …

Black Hole Spectroscopy And Tests Of General Relativity With Gw250114, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang

Physics & Astronomy Faculty Publications

The binary black hole signal GW250114, the loudest gravitational wave detected to date, offers a unique opportunity to test Einstein’s general relativity (GR) in the high-velocity, strong-gravity regime and probe whether the remnant conforms to the Kerr metric. Upon perturbation, black holes emit a spectrum of damped sinusoids with specific, complex frequencies. Our analysis of the postmerger signal shows that at least two quasinormal modes are required to explain the data, with the most damped remaining statistically significant for about one cycle. We probe the remnant’s Kerr nature by constraining the spectroscopic pattern of the dominant quadrupolar (ℓ =𝑚 =2) …

2026 January 29 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Geometric Modeling Through Multiple Implicit Functions, Yiwen Ju

McKelvey School of Engineering Graduate Student Theses & Dissertations

Implicit representations have become a dominant paradigm in computational settings ranging from learning-based geometry generation to advanced manufacturing. While treating geometry as the level set of a black-box function provides significant modeling flexibility, converting these representations into explicit surface meshes remains a major challenge. Standard volumetric extraction methods are fundamentally designed for smooth manifolds and therefore struggle to capture sharp geometric features such as creases, corners, and non-manifold junctions that are critical for high-fidelity industrial design and engineering tasks. Many of these intricate features arise from modeling multiple implicit functions. Examples include Constructive Solid Geometry (CSG), material interfaces, and more …

A High-Resolution Daily Precipitation Fusion Framework Integrating Radar, Satellite, And Nwp Data Using Machine Learning Over South Korea, Hyoju Park, Hiroyuki Miyazaki, Menas Kafatos, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) daily precipitation fusion framework that integrates Korea Meteorological Administration (KMA) radar, Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), and Local Data Assimilation and Prediction System (LDAPS) data. The framework employs a Random Forest model augmented with a monthly Empirical Cumulative Distribution Function (ECDF) correction. Auxiliary predictors are incorporated to enhance physical interpretability and stability, including terrain attributes to represent orographic effects, land-cover …

Artificial Intelligence In Higher Education, Opportunities, And Challenges: A Review, Sharifa Alblooshi

All Works

Artificial intelligence (AI) is a growing force of change in higher education, providing assistance to students, teachers, and administrators in teaching, learning, and administration. As AI technologies advance rapidly, they present a combination of significant opportunities and complex challenges. In this study, we examine the role of AI in higher education, highlighting both its positive and negative impacts, as well as current policy gaps and issues arising from its deployment. The literature on the topic was reviewed to determine how AI decisively impacts teaching and learning, the role of AI in assessments and academic integrity, as well as ethics, psychological …