Physical Sciences and Mathematics Commons^™

Establishing Practical Equivalence Of Factor Loadings In Multigroup Confirmatory Factor Analysis, Christopher Edward Shank

Dissertations

This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group difference; despite this, the conventional approach to measurement invariance analysis relies upon NHT. EQT has proved effective for invariance detection using global model-data fit statistics in simulated and real-world data (Counsell et al., 2020) but its use in partial measurement invariance (PMI) analysis for evaluation of factor loading differences between groups has …

A “How-To” Manual For Doing Standard Statistics In R, Elizabeth Newton

OER Textbooks

This “How To….” Manual is intended to assist the new user in implementing standard statistical methods, both parametric and non-parametric, using R statistical software. Its focus is on R implementation, not statistical theory. It includes the R commands, with examples, for the following: proportion tests, t-tests, ANOVA, variance tests, several correlation measures and regression models, Mann-Whitney-Wilcoxon tests, Kruskal-Wallis tests, chi-squared tests, multiple pairwise comparisons and effect sizes. Basic graphical methods are also illustrated.

[See note on 2024 update below.]

Time Series Models For Predicting Application Gpu Utilization And Power Draw Based On Trace Data, Dorothy Xiaoshuang Parry

Electrical & Computer Engineering Theses & Dissertations

This work explores collecting performance metrics and leveraging various statistical and machine learning time series predictive models on a memory-intensive application, Inception v3. Trace data collected using nvidia-smi measured GPU utilization and power draw for two runs of Inception3. Experimental results from the statistical and machine learning-based time series predictive algorithms showed that the predictions from statistical-based models were unable to capture the complex changes in the trace data. The Probabilistic TNN model provided the best results for the power draw trace, according to the test evaluation metrics. For the GPU utilization trace, the RNN models produced the most accurate …

Accurate Estimation Of Ethanol Content In Fruit Juices Using Cielab Color Space And Chemometrics Via Smartphone-Based Digital Image Colorimetry, Chairul Ichsan, Yasir Amrulloh, Desti Erviana

Makara Journal of Science

This study aims to investigate the optimal color space and chemometric technique for digital image colorimetry to determine ethanol content (% v/v) in apple, orange, and grape juices, using potassium dichromate (K₂Cr₂O₇) under acidic conditions. The accuracy of colorimetric–chemometric integration across various color spaces (RGB, HSV, CIELab, CMYK, CIELuv, CIEXYZ, and CIELch) was benchmarked against UV–Vis spectrophotometry using metrics such as coefficient of determination (R²), mean absolute percentage error (MAPE), and root–mean–squared error (RMSE). Various chemometric techniques (PLS, PCR, MLR, multivariable–SVR, and multivariable NN regression) were evaluated. Results demonstrate that combining the CIELab color …

Mpt And Capm Mismeasure Risk, Gary N. Smith

Pomona Economics

Mean-variance analysis and the capital asset pricing model provide many useful insights for investors who want to measure and manage risk. However, their focus on short-term returns is of limited use and potentially misleading for investors with long horizons. A value investing approach suggests that risk might be better measured by long-run uncertainty about asset income than by short-run uncertainty about asset prices.

Lstm-Based Recurrent Neural Network Predicts Influenza-Like-Illness In Variable Climate Zones, Alfred Amendolara, Christopher Gowans, Joshua Barton, David Sant, Andrew Payne

Annual Research Symposium

Purpose: Influenza virus is responsible for a recurrent, yearly epidemic in most temperate regions of the world. For the 2021-2022 season the CDC reports 5000 deaths and 100,000 hospitalizations, a significant number despite the confounding presence of SARS-CoV-2. The mechanisms behind seasonal variance in flu burden are not well understood. Based on a previously validated model, this study seeks to expand understanding of the impact of variable climate regions on seasonal flu trends. To that end, three climate regions have been selected. Each region represents a different ecological region and provides different weather patterns showing how the climate variables impact …

The Impact Of Data Preparation And Model Complexity On The Natural Language Classification Of Chinese News Headlines, Torrey J. Wagner, Dennis Guhl, Brent T. Langhals

Faculty Publications

Given the emergence of China as a political and economic power in the 21st century, there is increased interest in analyzing Chinese news articles to better understand developing trends in China. Because of the volume of the material, automating the categorization of Chinese-language news articles by headline text or titles can be an effective way to sort the articles into categories for efficient review. A 383,000-headline dataset labeled with 15 categories from the Toutiao website was evaluated via natural language processing to predict topic categories. The influence of six data preparation variations on the predictive accuracy of four algorithms was …

Research On Chinese Data Sovereignty Policy Based On Lda Model And Policy Instruments, Han Qiao, Junru Xu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Data sovereignty has become an important component of national sovereignty in the dual context of the digital economy development and the overall national security concept. Major countries and regions are actively carrying out data sovereignty strategic deployment and engaging in fierce competition in data resources, data technology, and data rules. This work adopts the policy text analysis method to study China’s data sovereignty policy, and employs the LDA model and policy instruments to quantitatively analyze the process evolution and thematic characteristics of China’s data sovereignty policy. Drawing on these findings, this study comprehensively considers the global data sovereignty policy and …

Application And Effectiveness Of Artificial Intelligence For The Border Management Of Imported Frozen Fish In Taiwan, Wen-Chin Tu, Wan-Ling Tsai, Chi-Hao Lee, Chia-Fen Tsai, Jen-Ting Wei, King-Fu Lin, Shou-Mei Wu, Yih-Ming Weng

Journal of Food and Drug Analysis

In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection system (import food inspection (IFI) system) to select batches via a random sampling method to manage the risk levels of various food products complying with regulatory inspection procedures. Several countries have implemented artificial intelligence (AI) technology to improve domestic governmental processes, social service, and public feedback. AI technologies are applied in border inspection by the Taiwan Food and Drug Administration (TFDA). Risk management of border inspections …

Utilizing Machine Learning Techniques For Accurate Diagnosis Of Breast Cancer And Comprehensive Statistical Analysis Of Clinical Data, Myat Ei Ei Phyo

USF Tampa Graduate Theses and Dissertations

Breast cancer represents a formidable malignancy, presenting a substantial threat to global health and individual well-being. Conventionally, it is widely held that the prognosis for breast cancer patients hinges predominantly upon the timing of diagnosis and the extent of cancer progression, typically delineated by its stage. However, emerging evidence from robust regression and machine learning analyses challenges this prevailing notion. The results indicate that survival months cannot be solely attributed to diagnosis and socio-economic factors. Instead, additional variables such as existing diseases and treatment complexities may contribute to the intricate landscape of breast cancer outcomes.

This research aims to delve …

Novel Lipid Mediator 7s,14r-Docosahexaenoic Acid: Biogenesis And Harnessing Mesenchymal Stem Cells To Ameliorate Diabetic Mellitus And Retinal Pericyte Loss, Yan Lu, Haibin Tian, Hongying Peng, Quansheng Wang, Bruce A. Bunnell, Nicolas G. Bazan, Song Hong

School of Medicine Faculty Publications

Introduction: Stem cells can be used to treat diabetic mellitus and complications. ω3-docosahexaenoic acid (DHA) derived lipid mediators are inflammation-resolving and protective. This study found novel DHA-derived 7S,14R-dihydroxy-4Z,8E,10Z,12E,16Z,19Z-docosahexaenoic acid (7S,14R-diHDHA), a maresin-1 stereoisomer biosynthesized by leukocytes and related enzymes. Moreover, 7S,14R-diHDHA can enhance mesenchymal stem cell (MSC) functions in the amelioration of diabetic mellitus and retinal pericyte loss in diabetic db/db mice. Methods: MSCs treated with 7S,14R-diHDHA were delivered into db/db mice i.v. every 5 days for 35 days. Results: Blood glucose levels in diabetic mice were lowered by 7S,14R-diHDHA-treated MSCs compared to control and untreated MSC groups, accompanied by …

Stability Of Predator-Prey Model For Worm Attack In Wireless Sensor Networks, Rajeev Kishore, Padam Singh

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we propose a predator-prey mathematical model for analyzing the dynamical behaviors of the system. This system is an epidemic model, and it is capable of ascertaining the worm's spreading at the initial stage and improving the security of wireless sensor networks. We investigate different fixed points and examine the stability of the projected model.

A Novel Fuzzy Time Series Forecasting Method Based On Probabilistic Fuzzy Set And Cpbd Approach, Krishna Kumar Gupta, Suneet Saxena

Applications and Applied Mathematics: An International Journal (AAM)

Probabilistic fuzzy set is used to model the non-probabilistic and probabilistic uncertainties simultaneously in the system. This study proposes a cumulative probability-based discretization and probabilistic fuzzy set based novel fuzzy time series forecasting method. It also proposes a novel discretization approach based on cumulative probability to tackle the probabilistic uncertainty in partitioning of datasets. Gaussian probability distribution function has been used to construct probabilistic fuzzy set. The advantage of the proposed work is that it addresses the uncertainties due to randomness and fuzziness simultaneously and also improves accuracy rate in time series forecasting. A proposed forecasting method is applied on …

Assessment Of Method Effects Of Keying And Wording In Instruments: A Mixed-Methods Explanatory Sequential Study, Lin Ma

Electronic Theses and Dissertations

This dissertation presents an innovative approach to examining the keying method, wording method, and construct validity on psychometric instruments. By employing a mixed methods explanatory sequential design, the effects of keying and wording in two psychometric assessments were examined and validated. Those two self-report psychometric assessments were the Effortful Control assessment (Ellis & Rothbart, 2001) and the Grit assessment (Duckworth & Quinn, 2009). Moreover, the quantitative phase utilized structural equation modeling to analyze 2,104 students’ responses and assess the construct of keying and wording. Various hypothetical models were investigated and evaluated. The reliability of each construct in each method was …

Thermal Performance Of Forced Convection Of Water- Nepcm Nanofluid Over A Semi-Cylinder Heat Source, Xiaoming Wang, Rassol H. Rasheed, Babak Keivani, Dheyaa J. Jasim, Abbas J. Sultan, Sajad Hamedi, Hamed Kazemi-Varnamkhasti, Soheil Salahshour, Davood Toghraie

Mathematics and Statistics Faculty Research & Creative Works

1) Background: Phase change materials (PCMs) have been used statically, which has caused the use of these materials to face challenges. Encapsulating PCMs and combining them with the base fluid can significantly solve the problem of using PCMs in BTM systems. In the present study, based on computational fluid dynamics, forced convection heat transfer of nano-encapsulated phase change materials (NEPCM) in a BTM system are simulated. The main aim of the present research is to reduce the temperature at the surface of the hot cylinder. 2) Methods: In this research, we simulated lithium battery thermal management systems in both steady …

Identifying Rural Health Clinics Within The Transformed Medicaid Statistical Information System (T-Msis) Analytic Files, Katherine Ahrens Mph, Phd, Zachariah Croll, Yvonne Jonk Phd, John Gale Ms, Heidi O'Connor Ms

Rural Health Clinics

Researchers at the Maine Rural Health Research Center describe a methodology for identifying Rural Health Clinic encounters within the Medicaid claims data using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files.

Background: There is limited information on the extent to which Rural Health Clinics (RHC) provide pediatric and pregnancy-related services to individuals enrolled in state Medicaid/CHIP programs. In part this is because methods to identify RHC encounters within Medicaid claims data are outdated.

Methods: We used a 100% sample of the 2018 Medicaid Demographic and Eligibility and Other Services Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files for 20 states …

Road Traffic Noise Annoyance And Cardiovascular Disease Risk In Population: A Case Series Study In Kota Bharu, Malaysia, Faridah Naim, Nurin H M Nasir

Kesmas

Noise pollution can cause annoyance, significantly threatening the population’s health and well-being. This study aimed to find an association between road traffic noise exposure and cardiovascular disease (CVD) risk among residents in Kota Bharu, Malaysia. This descriptive study used a case series approach and surveyed 34 residents in selected residential areas near main roads. An adapted questionnaire was distributed to residents using a purposive sampling method. Questions related to sociodemographic information, self-reporting about CVD, and road traffic noise assessment were asked to investigate the underlying risk factors for CVD. The average score of CVD assessment was classified as moderate risk. …

Effects Of Maternal Anthropometry On Infant Anthropometry: A Cross-Sectional Study At Public Hospital X In Ternate, Indonesia, Yuni Nurwati, Hardinsyah Hardinsyah, Sri Anna Marliyati, Budi Iman Santoso, Dewi Anggraini

Kesmas

Infant anthropometry is an indicator of neonatal survival. This study aimed to determine the effects of maternal anthropometry on estimating infant anthropom­etry. This cross-sectional study on 173 pregnant women at Public Hospital X in Ternate, Indonesia, was conducted from August 2018 to March 2023. The el­igible criteria were pregnant women aged ≥18 years, single pregnancy, and antenatal care (ANC) visits to the same hospital. The variables used included ma­ternal anthropometric measurements (body weight, body height, third-trimester weight (TTW)), gestational weight gain (GWG), education, age, ANC visits, and gestational age at delivery (GAD). A logistic regression model was employed to estimate …

Implementation Of Digital Health In Addressing Global Threats: Lessons From The Use Of Technology During Covid-19 Pandemic In Indonesia, Naili Shifa, Anisa Tiasari, Kemal N. Siregar

Kesmas

This research conducted a systematic literature review to explore the implementation of digital health in Indonesia, focusing on the digital health policies, usage during the COVID-19 pandemic, benefits, and lessons learned. The study identified 10 relevant journals through database searches and analyzed the trends in publication, productive journals, and top institutions involved in digital health research. The findings revealed an increasing interest in digital health, with a growing number of published articles from 2021 to 2023. ScienceDirect emerged as the most productive journal, followed by PubMed and MDPI. The University of Indonesia and the University of Gajah Mada were the …

Bactericidal Efficacy Of The Combination Of Maresin-Like Proresolving Mediators And Carbenicillin Action On Biofilm-Forming Burn Trauma Infection-Related Bacteria, Anbu Mozhi Thamizhchelvan, Abdul Razak Masoud, Shanchun Su, Yan Lu, Hongying Peng, Yuichi Kobayashi, Yu Wang, Nathan K. Archer, Song Hong

School of Medicine Faculty Publications

Biofilm-associated bacterial infections are the major reason for treatment failure in many diseases including burn trauma infections. Uncontrolled inflammation induced by bacteria leads to materiality, tissue damage, and chronic diseases. Specialized proresolving mediators (SPMs), including maresin-like lipid mediators (MarLs), are enzymatically biosynthesized from omega-3 essential long-chain polyunsaturated fatty acids, especially docosahexaenoic acid (DHA), by macrophages and other leukocytes. SPMs exhibit strong inflammation-resolving activities, especially inflammation provoked by bacterial infection. In this study, we explored the potential direct inhibitory activities of three MarLs on Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa and Escherichia coli) bacteria in their biofilms that are leading …

Editorial: Ipps 2022 - Plant Phenotyping For A Sustainable Future, Elias Kaiser, Philipp Von Gillhaussen, Jennifer Clarke, Ulrich Schurr

Department of Statistics: Faculty Publications

Plants are a venue for addressing the challenges facing humanity. The need for a reliable supply of food, feed, materials, chemicals and energy as well as ways to manage agroecology and climate change are among the challenges that we can address through the sustainable use of plants and plant ecosystems. The research community needs to integrate plant systems approaches, from molecular to organismal to applications in the field and ecosystems, to increase productivity sustainably while using fewer land, water, and nutrient resources. In the past two decades, plant phenotyping research has developed a highly valuable portfolio of technologies, processes and …

Optimizing Buying Strategies In Dominion, Nikolas A. Koutroulakis

Rose-Hulman Undergraduate Mathematics Journal

Dominion is a deck-building card game that simulates competing lords growing their kingdoms. Here we wish to optimize a strategy called Big Money by modeling the game as a Markov chain and utilizing the associated transition matrices to simulate the game. We provide additional analysis of a variation on this strategy known as Big Money Terminal Draw. Our results show that player's should prioritize buying provinces over improving their deck. Furthermore, we derive heuristics to guide a player's decision making for a Big Money Terminal Draw Deck. In particular, we show that buying a second Smithy is always more optimal …

Revolutionizing Denture Excellence: An Invigorating In-Vitro Exploration Of Organic Products In Prosthetic Rehabilitation, Nighila Ravindran, Sneha Joseph, Aswani Surya K

Annual Research Symposium

The denture base comes into contact with diverse substances in the oral cavity, acting as a reservoir for microorganisms like corynebacterium, streptococcus, lactobacillus, and candida. This colonization elevates the risk of complications such as denture stomatitis and candidiasis. Commercial denture cleaners have explored the use of natural ingredients, less commonly employed but offering various advantages. These ingredients aim to mitigate the potential issues associated with microbial colonization on denture surfaces, contributing to improved oral hygiene for denture wearers. The exploration of natural elements reflects a nuanced approach to denture care, considering both efficacy and less conventional alternatives.

Investigating Racial And Ethnic Healthcare Disparities In Screenable Ob/Gyn-Related Cancers, Lara Laughrey

Annual Research Symposium

This is a scoping review of peer-reviewed literature addressing healthcare inequity based on race and ethnicity with a specific focus on Ob/Gyn-related management and treatment of screenable cancers.

Assessment Of Emotional Intelligence Among Students In Dental College, Gowri Nandana S Final Year Student, Sudeep C. B Professor And Head Of The Department Of Public Health Dentistry

Annual Research Symposium

Over an extended period, the examination of intelligence predominantly centered on the adaptive deployment of cognitive abilities. In more recent times, scholars such as Gardner (1983) and Sternberg (1988) have proposed comprehensive frameworks for comprehending intelligence. Pioneering the concept of "emotional intelligence," Salovey and Mayer (1990) posited that emotional intelligence encompasses three distinct categories of adaptive capabilities: the evaluation and expression of emotions, the regulation of emotions, and the utilization of emotions in problem-solving. The objective is to evaluate emotional intelligence among dental students across various educational institutions.

Quality Of Life In Orthodontics, Claudia Eisenhuth, Gabriel Eisenhuth, Connor Schwartz, Amir Mohajeri, Man Hung, Tiffany Nelson, Ryann Glenn

Annual Research Symposium

Orthodontic treatment goes beyond mere cosmetic enhancement; it significantly impacts various aspects of an individual's quality of life. Beyond the physical benefits of improved oral function and prevention of dental issues, orthodontics also yields profound psychological benefits. Aligned teeth enhance self-confidence, reduce social anxiety, and contribute to better relationships and professional opportunities. Moreover, addressing dental concerns through orthodontic treatment reduces psychological distress and promotes overall happiness and satisfaction. Real-life case studies vividly illustrate the transformative effects of orthodontic interventions, emphasizing the importance of considering quality of life outcomes in dental care.

Exploring The Interconnected Role Of The Oral Microbiome And Periodontal Disease In The Development And Progression Of Oral Squamous Cell Carcinoma, Malak Al-Regib, Claudia M. Tellez Freitas

Annual Research Symposium

This comprehensive review explores the complex linkage among the oral microbiome, periodontal disease, and the onset and progression of oral squamous cell carcinoma (OSCC).

Anomaly Detection On Small Wind Turbine Blades Using Deep Learning Algorithms, Bridger Altice, Edwin Nazario, Mason Davis, Mohammad Shekaramiz, Todd K. Moon, Mohammad A. S. Masoum

Electrical and Computer Engineering Faculty Publications

Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five base deep learning architectures are investigated for anomaly detection on wind turbine blades, including Xception, Resnet-50, AlexNet, and VGG-19, along with a custom convolutional neural network. For further analysis, transfer learning approaches were also proposed and developed, utilizing these architectures as the feature extraction layers. In order to investigate model performance, a new dataset containing 6000 RGB images was created, making use of indoor and …

Success And Challenges Of Infrazygomatic Crest Implants In Orthodontics, Gauri Gill

Annual Research Symposium

Poster on success rates of mini implants used in the infrazygomatic region for orthodontic anchorage , as well as the factors that influence the success of the mini implant placed in IZC region.

Investigating The Role Of Chaos In Minimizing Tumor Growth, Maxwell Geiger

Annual Research Symposium

Chaos is a type of motion found in mathematical systems that is highly sensitive to initial conditions. While many biological systems described in literature have been analyzed for the presence of chaotic dynamics, there are still many that are yet to be discovered. The goal of this project is to reassess Itik and Banks’ discovery of chaotic behavior in their population dynamics model of cancer growth. Once chaotic behavior is confirmed, we want to investigate how chaos could possibly be controlled to minimize tumor growth and discover novel treatments for cancer patients.