Digital Commons Network^™

A Unified Framework For Neutrosophic Estimation Using Fractional Power, Exponential, And Logarithmic Functions With Bivariate Auxiliary Information, Anchal Yadav, Anuj Yadav

Neutrosophic Systems with Applications

This study develops a generalized neutrosophic ratio-type estimator for estimating the population mean by incorporating information from two auxiliary variables under Simple Random Sampling Without Replacement (SRSWOR). The proposed methodology extends the conventional single-auxiliary-variable approach by jointly incorporating bivariate auxiliary information within the neutrosophic framework, thereby accounting for uncertainty, indeterminacy, and inconsistency in the available information. The bias and mean squared error of the proposed estimator are derived using first-order approximations, and the corresponding efficiency conditions are established through theoretical comparisons with existing neutrosophic estimators. The performance of the proposed estimator is further examined using a real medical dataset represented …

A Hybrid Densenet121-Inceptionv3 Model For Multi-Output Race And Gender Classification, Maiwan Bahjat Abdulrazzaq, Mayyadah Ramiz Mahmood, Sardar Hasen Ali, Azar Abid Salih

Iraqi Journal for Computer Science and Mathematics

This research proposes and validates a novel Hybrid DenseNet121-InceptionV3 architecture for robust multi-output demographic classification from facial images, with a focus on optimizing both time efficiency and parameter utilization. The model was trained on a curated subset of the UTKFace dataset comprising 4,000 images, balanced across four racial groups with equal gender distribution. Our hybrid approach processes images through parallel feature extractors, strategically combining DenseNet121's parameter-efficient feature reuse with InceptionV3's multi-scale analysis capabilities. This architectural synergy achieves superior performance while maintaining computational efficiency. Through rigorous 3-fold cross-validation, the hybrid model demonstrated significant advantages in accuracy and training time, achieving 98.35% …

Machine Learning-Based Decision Support Models With Applications In Postsecondary Education, Marco Paolo Anglesio

Theses and Dissertations

This dissertation investigates the deployment of machine learning methodologies in an industrial engineering framework for the development of advanced decision support systems in the context of enrollment management. Drawing on techniques from educational data mining, the research addresses three key phases in the lifecycle of traditional and non-traditional students. First, it analyzes student retention using predictive classification models designed to identify individuals at elevated risk of attrition. Second, it employs temporal convolutional networks for time series forecasting, estimating aggregate enrollment levels over highly variable, finite planning horizons on the basis of partially observed data and using an asymmetric loss function. …

Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng

Journal of Aviation Technology and Engineering

This study evaluates the effectiveness of log transformation in enhancing multiple regression models used to forecast air traffic movements (ATMs) in South Africa during the COVID-19 pandemic. Using 60 monthly observations from October 2016 to September 2021, the analysis incorporates variables such as revenue, lockdown levels, COVID-19 metrics, exchange rates, gross domestic product, and population. Two models are compared: one using raw ATMs and another with log-transformed ATMs as the dependent variable.

While the untransformed model shows stronger explanatory power (R² = 0.904, adjusted R² = 0.891) compared to the log-transformed model (R² = 0.772, adjusted R² = 0.741), the …

Challenges And Best Practices For The Development Of Coastal Hazard Decision Support Tools, Noah Hallisey

Open Access Dissertations

There is growing interest in developing Decision Support Tools (DSTs) supporting emergency managers and other decision-makers during coastal storm events. Yet many tools fail to inform decision-making due to challenges associated with their development and transition into operational tools for real-time decision-making. This dissertation investigates these challenges and offers best practices for their development and implementation for real-world decision-making through a literature review, interviews with subject matter experts in the United States, and a real-world case study.

Manuscript 1 reviews existing published literature to understand whether and how tool developers are incorporating emergency managers in the development of DSTs and …

Transforming Movement Assessment In Physical Therapy Through Subaquatic Data Collection, Kaitlyn Mcdonald

Theses and Dissertations

This study explored the interest and perceived barriers to integrating subaquatic diagnostic technologies (SDTs) into hydrotherapy among licensed physical therapists. Seventeen semi-structured interviews were conducted using a mixed-methods design, with 15 interviews included in the final analysis. Quantitative data were analyzed using chi-square tests, while qualitative responses were coded thematically. Results indicated no statistically significant relationships between SDT interest and career stage or hydrotherapy access, though qualitative data highlighted concerns about cost, limited access, and usability. Despite mixed interest in adoption, participants identified several potential benefits of SDTs, including improved treatment tailoring, increased patient buy-in, and enhanced outcome monitoring. Functional …

Leveraging Usage Of Ai In Education: Knowledge, Attitude And Behavioral Analysis On Students, Bipllab Roy, Purnendu Bikash Acharjee, Rohit Kumar Sharma, Ruptaheen Kramsapi, Shruti P

Northeast Journal of Complex Systems (NEJCS)

The paper explores the possible advantages and drawbacks of artificial intelligence (AI) on sustainability, with an emphasis on using AI to positively achieve SDGs. The study finds a significant vacuum in the literature on the association between knowledge, attitudes, and behaviors towards the use of AI tools and techniques in education and demographic characteristics (sex, age, education level, area of study, and city of origin). The purpose of this research is to close this knowledge gap and advance our understanding of how these demographic factors affect the integration of AI in educational environments. The study specifically aims to comprehend how …

Providing A Solution For Active-Duty Servicewomen Facing Chronic Musculoskeletal Injuries Due To Improper Gear Fit, Celia Watson, Denver Tidwell, Hadi Obaji

Honors Theses

As senior biomedical engineering students at the University of Mississippi, we began our academic year brainstorming unmet clinical needs in healthcare intending to provide an innovative solution. After conducting personal inventories, determining a mission, and evaluating internal and external factors, we established acceptance criteria for our strategic focus and clarified our needs statement: develop a prophylactic device for chronic musculoskeletal injuries (MSKIs) in active-duty servicewomen (ADSW). The average female soldier is at a disadvantage compared to her male counterpart due to anthropometric and physiological differences between men and women in most aspects of physical performance (Epstein et al. 2673). These …

Assessing The Impact Of Internal Flow Dynamics On Detection Region Concentrations Of Low-Cost Optical Particle Counters, Livingstone Quarshie

Theses and Dissertations

Particulate matter (PM) poses significant risks to human health and the environment, making accurate measurement essential for exposure assessment and regulatory decisions. While traditional reference methods provide reliable data, they are often bulky, expensive, and difficult to maintain. Optical Particle Counters (OPCs) offer a cost-effective alternative, commonly used in clean rooms, residential spaces, and personal exposure monitoring. These devices rely on light scattering to measure PM concentrations. However, low cost OPCs face challenges related to calibration and measurement accuracy, requiring careful performance evaluation. This study used computational fluid dynamics (CFD) tools, CONVERGE Studio and ANSYS Fluent, to simulate a simplified …

Hidden Markov Model For Identifying Local Variants In Human Genomes Using Simulated Data, Scott Mccallum

Electronic Theses and Dissertations

Identifying adaptive mutations in genetic data is challenging due to the low frequency of occurrence of such events, and because signatures of selection are intertwined with the footprints of various other evolutionary forces that shape our genomes. Even when a larger region appears to be under selection, genomic sites that are linked to adaptive mutations have similar statistical signals, and thus can obfuscate the identification of the actual adaptive mutation. The new method described here uses a Hidden Markov Model that allows for classification of neutral, linked, and sweep (adaptive mutation) genomic sites. This model is general and can be …

Trip Production Models For Persons With Disabilities, Pouyan Saeidian

All Graduate Theses and Dissertations, Fall 2023 to Present

Nearly 13% of the US population consists of people with disabilities, yet finding an equitable and comprehensive approach to meet their travel needs remains a challenge. Our research delves into the mobility patterns of people with disabilities to understand how their daily travel—both the frequency of trips and the distance covered—compares to those without disabilities. We also explore the factors influencing their travel behaviors and how these insights can guide policymakers in improving accessibility and mobility for this community. Utilizing data from the 2022 US National Household Travel Survey, we applied a blend of statistical analysis and machine learning methods. …

The Professional Constructor, Full Issue, Volume 47, Number 01

The Professional Constructor

No abstract provided.

Current State Of The Workforce Demographics And Knowledge Transfer Strategies In The Southeast United States, Vivek Sharma, Dhaval Gajjar, Kapil Madathil, David Davis, Shreyas Patel

The Professional Constructor

The construction industry is a very diverse industry due to the unique nature of projects and expertise within various construction companies driven by multiple regional/national factors. The United States Department of Labor reported 44% of the current US employed population will be above 65 in eleven years by 2028, making workforce studies and knowledge transfer a key driver in leading construction business models. This study conducted an in-depth investigation in the southeast region of the US on the current state of workforce demographics and the need for knowledge transfer within the ranks of management coupled with trade personnel. The study …

Contributory Factors Of Fatigue Among Collegiate Aviation Pilots: An Ordinal Regression Analysis, Flavio A. C. Mendonca, Julius Keller, Daniel Kwasi Adjekum

Publications

Fatigue is a pervasive safety hazard in aviation affecting several aspects of a pilot's’ ability to safely perform their jobs. Several factors can contribute to fatigue, including inadequate sleep, stress, long work hours, excessive workload, and inadequate nutritional habits. In addition to flight training, some factors including academic, social, part-time work, and emerging time management skills are unique for Title 14 Code of Federal Regulations (CFR) Part 141 collegiate aviation pilots. By utilizing the Collegiate Aviation Fatigue Inventory (CAFI-II) at eight flight programs (n = 422), the current study examined factors such as fatigue training received, time spent working/studying and …

The Age-Dependent Characterization Of The Er-Alpha Positive Breast Cancer Tumor Microenvironment, Katie Marie Hamel

LSU Doctoral Dissertations

In disease states such as cancer, endocrine and paracrine signals from adipose tissue contribute to cancer progression and drug resistance. Young individuals diagnosed with estrogen receptor-alpha positive (ER-a+) breast cancer have an observed increase in resistance to endocrine therapies. This suggests that an alternative estrogen signaling pathway is active within these tumors. Despite this, the effects of stromal age on the endocrine response in breast cancer is not well known. Here, we review and highlight the involvement of the stromal age in both tumorigenesis and physiological wound healing. To identify specific differences between young and aged ER-a+ breast tumors, RNA …

Bagging Ensemble For Deep Learning Based Gender Recognition Using Test-Timeaugmentation On Large-Scale Datasets, Taner Danişman

Turkish Journal of Electrical Engineering and Computer Sciences

We present a bagging ensemble of convolutional networks in combination with the test-time augmentation technique to improve performance on the cross-dataset gender recognition problem. The bagging ensemble combines the predictions from multiple homogeneous models into the ensemble prediction. Augmentation techniques are often used in the learning phase of the CNNs to improve the generalization ability. On the other hand, test-time augmentation is not a common method used in the testing phase of the learned model. We conducted experiments on models trained using different hyperparameters. We augmented the test data and combine the predictive outputs from these network models. Experiments performed …

Assessing Impacts Of 5th Generation (5g) Cellular Telecommunications On Internet Of Things (Iot) Deployments, Michael Love, Marwan Jamal

Military Cyber Affairs

The Internet of Things (IoT) is emerging as a primary enabler of the transformation to digital business services in today’s economy. At the same time, 5^th Generation (5G) cellular transport technology is emerging as a viable means to support IoT data requirements. Although 5G is still in its infancy, DoD leaders need to understand the impacts that 5G will have on IoT projects as there are several challenges involved with integrating 5G into IoT. In order to achieve the maximum benefits of high bandwidth, low latency and superior performance, an entirely new grid of cell sites and access units …

Design Of An Offline Handwriting Recognition System Tested On The Bangla And Korean Scripts, Nishatul Majid

Boise State University Theses and Dissertations

This dissertation presents a flexible and robust offline handwriting recognition system which is tested on the Bangla and Korean scripts. Offline handwriting recognition is one of the most challenging and yet to be solved problems in machine learning. While a few popular scripts (like Latin) have received a lot of attention, many other widely used scripts (like Bangla) have seen very little progress. Features such as connectedness and vowels structured as diacritics make it a challenging script to recognize. A simple and robust design for offline recognition is presented which not only works reliably, but also can be used for …

Application Of Classification In Machine Learning: An Analysis Of Highway-Rail Grade Crossing Systems Safety, Christopher John Helmer Cox

Theses and Dissertations

Highway-rail grade crossing accidents are the second leading cause of fatalities within the railway transportation industry. Highway-rail grade crossing fatality statistics have failed to improve over the last decade, and in some years have increased. Because of these trends, research has found that considerable Federal funding initiatives exist to support and develop contemporary risk reduction methodologies involving machine learning and artificial intelligence. In accord with these initiatives, this thesis investigates the highway-rail grade crossing safety problem using machine learning to implement an ensemble decision tree-based classification application. The resulting classifier has been validated to achieve a less than three percent …

Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami

Graduate Theses, Dissertations, and Problem Reports (ETD)

Gender identification is an important technique that can improve the performance of authentication systems by reducing searching space and speeding up the matching process. Several biometric traits have been used to ascertain human gender. Among them, the human palmprint possesses several discriminating features such as principal-lines, wrinkles, ridges, and minutiae features and that offer cues for gender identification. The goal of this work is to develop novel deep-learning techniques to determine gender from palmprint images. PolyU and CASIA palmprint databases with 90,000 and 5502 images respectively were used for training and testing purposes in this research. After ROI extraction and …

Identifying Micro-Level Determinants That Influence The Transportation Network Companies (Tncs) Growth Through Analysis Of Transportation Users’ Preferences And Attitudes, Sahila Sarjana

All ETDs from UAB

In the recent years, the use of Transportation Network Companies (TNCs) such as Uber/Lyft as a mode of travel has been growing at a significant pace. Despite the rapid growth of several TNC markets, analyses of potential and actual impacts of TNCs presence on preferences and travel patterns of TNC-aware users are still very limited. Such analyses require detailed trip data which are not easily available due to privacy concerns, as well as technical and financial feasibility issues. To address some of these issues, the objective of this study was to document the factors that influence transportation users in the …

A Longitudinal Examination Of Biomechanical Balance And Quantitative Multidomain Assessments During Recovery Following Sport-Related Concussion, Moira Kate Pyrhoda

Electronic Theses and Dissertations

Sport-related concussion is an inherent risk to athlete health in contact and collision sports. Both short- and long-term risks are associated with the injury. Short-term, athletes may develop post-concussion syndrome (PCS), the persistence of cognitive, physical, and emotional symptoms for weeks or months after injury. Athletes who return to play (RTP) prematurely are at increased risk for lower extremity injury and repeated concussion injuries. Long-term, history of multiple concussions have been linked to neurodegenerative diseases. Due to these risks, concussion assessments must be sensitive to the injury and useful in the diagnosis, recovery, and RTP phases of the injury.

Sideline …

Effects Of Spinal Fusion For Idiopathic Scoliosis On Lower Body Kinematics During Gait, Karen M. Kruger, Christina R. Garman, Joseph J. Krzak, Adam Graf, Sahar Hassani, Sergey Tarima, Peter F. Sturm, Kim W. Hammerberg, Purnendu Gupta, Gerald F. Harris

Biomedical Engineering Faculty Research and Publications

Objectives

The purpose of this study was to compare gait among patients with scoliosis undergoing posterior spinal fusion and instrumentation (PSFI) to typically developing subjects and determine if the location of the lowest instrumented vertebra impacted results.

Summary of Background Data

PSFI is the standard of care for correcting spine deformities, allowing the preservation of body equilibrium while maintaining as many mobile spinal segments as possible. The effect of surgery on joint motion distal to the spine must also be considered. Very few studies have addressed the effect of PSFI on activities such as walking and even fewer address …

Uncovering Exceptional Predictions Using Exploratory Analysis Of Second Stage Machine Learning., Aneseh Alvanpour

Electronic Theses and Dissertations

Nowadays, algorithmic systems for making decisions are widely used to facilitate decisions in a variety of fields such as medicine, banking, applying for universities or network security. However, many machine learning algorithms are well-known for their complex mathematical internal workings which turn them into black boxes and makes their decision-making process usually difficult to understand even for experts. In this thesis, we try to develop a methodology to explain why a certain exceptional machine learned decision was made incorrectly by using the interpretability of the decision tree classifier. Our approach can provide insights about potential flaws in feature definition or …

Contingency Workload Demand Forecast Techniques For Cargo And Flying Hours, Calvin J. Bradshaw Iii

Theses and Dissertations

Accurate forecasting of contingency workload demand for USTRANSCOM (USTC) is a herculean effort. Transportation Working Capital Fund (TWCF) managers rely on various subject matters outside and within the combatant command to estimate future workload. Since rates are set annually, when TWCF activities use incorrect or incomplete projections of workload, this leads to erroneous price structures and misaligned customer billing rates. The USTC leadership lacks the ability to accurately forecast workload demand, which is a key driver for service provider rate-setting. As a result, some customers perceive spiked rates and seek service from other competitors, which generates lost revenue, customer dissatisfaction …

The Effect Of Integrated Science, Engineering, Technology, And Mathematics Lessons On Interest And Engagement Of Secondary Students, Cameron Nunan

Open Access Theses

This study set out to answer the research question: Does teaching a single lesson, utilizing the interconnected principles of STEM in STEM courses, increase overall student interest and engagement in STEM classes in secondary schools? The literature review established a need for student interest in STEM to help fill future STEM careers. ^ Integrated STEM lessons were a viable option for increasing interest, but existing research on the matter was limited. Integrated STEM lessons were applied at a test site school using a multiple baseline framework and evaluated responses with a variation of the Intrinsic Motivation Inventory (IMI). According to …

Anterior Cruciate Ligament Biomechanics, Computational Modeling Of Mechanical Behavior And Injury Risk, Bharadwaj Cheruvu

Browse all Theses and Dissertations

Knee joint involves interactions from various structures such as cartilage, bone, muscles, ligaments, tendon, as well as neural control. Anterior cruciate ligament (ACL) tears are one of the most frequent soft tissue injuries of the knee. A torn ACL leaves the joint unstable and at risk for further damage to other soft tissues manifested as pain, dislocation, and osteoarthritis. This injury is quite common in sports such as basketball, soccer and football. Females often tear their ACL 2-8 times more frequently than their male counterparts. An ACL injury can be devastating and significantly increases the athlete's risk for osteoarthritis long …

A Reference System For Animal Biometrics: Application To The Northern Leopard Frog, D. Petrovska-Delacrétaz, A. Edwards, J. Chiasson, G. Chollet, D. Pilliod

Electrical and Computer Engineering Faculty Publications and Presentations

Reference systems and public databases are available for human biometrics, but to our knowledge nothing is available for animal biometrics. This is surprising because animals are not required to give their agreement to be in a database. This paper proposes a reference system and database for the northern leopard frog (Lithobates pipiens). Both are available for reproducible experiments. Results of both open set and closed set experiments are given.

2013 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2013.

Driver Injury Severity At U.S. Highway-Rail Crossings, Wei Hao

Dissertations

There are approximately 240,000 highway-rail grade crossings in the United States and highway-rail grade crossing areas have been considered in this study as these are locations where crashes frequently occur. Existing studies on crash models at highway- rail grade crossings can be classified into two categories: accident frequency prediction models and driver injury severity models. Accident frequency prediction at highway-rail grade crossings have been investigated by previous studies using varied statistical models. Few studies, however, have focused on driver injury severity studies. Three drawbacks will be addressed in this research including limitations in traditional highway- rail grade crossings studies, limited …