Physical Sciences and Mathematics Commons^™

Computation Of Separate Ratio And Regression Estimator Under Neutrosophic Stratified Sampling: An Application To Climate Data, Abhishek Singh, Hemant Kulkarni, Florentin Smarandache, Gajendra K. Vishwakarma

Branch Mathematics and Statistics Faculty and Staff Publications

In this article, we introduce a novel approach by presenting separate ratio and regression estimators in the context of neutrosophic stratified sampling for the very first time, incorporating auxiliary variables. We have conducted a thorough analysis to estimate these newly proposed estimators' bias and mean square error (MSE) up to the first-order approximation. Theoretically using efficiency comparison criteria, our findings demonstrate the superior performance of these estimators compared to traditional unbiased estimators. Also, numerically based on real-life and artificial data, we have shown the supremacy of the neutrosophic stratified sampling over neutrosophic simple random sampling along with the supremacy of …

Row-Column Designs: A Novel Approach For Analyzing Imprecise And Uncertain Observations, Abdulrahman Alaita, Muhammad Aslam, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Classical row-column designs cannot be applied when the underlying data set contains some imprecise, uncertain, or undetermined observations. In this paper, we discuss row-column design under a neutrosophic statistical framework. A significant contribution of our study is to propose a novel approach to analyzing row-column designs using neutrosophic data. This approach involves calculating the neutrosophic analysis of variance (NANOVA) table for the proposed design and using it to derive the FN -test in an uncertain environment. Two numerical examples have been used to assess the proposed design’s performance. Results from the study indicated that a row column design under …

Examining Information Systems Use To Facilitate The Workplace Accommodation Process, Shiya Cao

Statistical and Data Sciences: Faculty Publications

BACKGROUND: The workplace accommodation process is often affected by ineffective and inefficient communications and information exchanges among disabled employees and other stakeholders. Information systems (IS) can play a key role in facilitating a more effective and efficient accommodation process since IS has been shown to facilitate business processes and effect positive organizational changes.

OBJECTIVE: Since there is little to no research that exists on IS use to facilitate the workplace accommodation process, this paper, as a critical first step, examines how IS have been used in the accommodation process.

METHODS: Thirty-six interviews were conducted with disabled employees from various organizations. …

Generating Neutrosophic Random Variables Based Gamma Distribution, Maissam Ahmad Jdid, Florentin Smarandache, Khalifa Al Shaqsi

Branch Mathematics and Statistics Faculty and Staff Publications

In practical life, we encounter many systems that cannot be studied directly, either due to their high cost or because some of these systems cannot be studied directly. Therefore, we resort to the simulation method, which depends on applying the study to systems similar to real ones and then projecting these results if they are suitable for the real system. The simulation process requires a good understanding of probability distributions and the methods used to transform random numbers that follow a regular distribution in the field [0,1] into random variables that follow them, so that we can achieve the greatest …

Gender Wage Gap: Analysis Of Women In Statistical Industries And Financial Effects Of The Wage Gap, Renee Delos

Honors Projects in Mathematics and Economics

Women in statistical and mathematical industries are continuing to be mistreated within the workforce. Women are constantly being paid less than men, despite prior qualifications that should show otherwise. An overall pay gap between male and female employees not only affects the women’s work at the company, but also their lives outside of the corporate world. This thesis analyzes the direct effects of this pay difference, and how women are truly treated throughout the working world. The data collected through surveys is used as the basis in determining the real pay gap, and the overall emotions and degree of comfort …

Cryptographic Algorithms, Cryptocurrencies, And A Predictive Model Of Bitcoin Value By Pls Regression, Paul Kenneth O'Connor

Masters Theses

"With the invention of Bitcoin in 2009, as a seemingly timed response to the ongoing financial crisis, the popularity of the cryptocurrency has since continued to grow. Just this year, the Security Exchange Commission approved Bitcoin for exchange traded funds, allowing major investment firms to begin product trading. With this approval, and during this very moment of writing, Bitcoin has entered a bull market and reached a record value of over 72,000 USD. In addition, the Bitcoin halving event in April of 2024 is expected to increase demand even further. It has been anticipated that Bitcoin and other cryptocurrencies will …

Bayesian Variable Selection With Shrinkage Priors And Generative Adversarial Networks For Fraud Detection, Amina Issoufou Anaroua

Graduate Thesis and Dissertation 2023-2024

This research paper focuses on fraud detection in the financial industry using Generative Adversarial Networks (GANs) in conjunction with Uni and Multi Variate Bayesian Model with Shrinkage Priors (BMSP). The problem addressed is the need for accurate and advanced fraud detection techniques due to the increasing sophistication of fraudulent activities. The methodology involves the implementation of GANs and the application of BMSP for variable selection to generate synthetic fraud samples for fraud detection using the augmented dataset. Experimental results demonstrate the effectiveness of the BMSP GAN approach in detecting fraud with improved performance compared to other methods. The conclusions drawn …

Utility In Time Description In Priority Best-Worst Discrete Choice Models: An Empirical Evaluation Using Flynn's Data, Sasanka Adikari, Norou Diawara

Mathematics & Statistics Faculty Publications

Discrete choice models (DCMs) are applied in many fields and in the statistical modelling of consumer behavior. This paper focuses on a form of choice experiment, best-worst scaling in discrete choice experiments (DCEs), and the transition probability of a choice of a consumer over time. The analysis was conducted by using simulated data (choice pairs) based on data from Flynn's (2007) 'Quality of Life Experiment'. Most of the traditional approaches assume the choice alternatives are mutually exclusive over time, which is a questionable assumption. We introduced a new copula-based model (CO-CUB) for the transition probability, which can handle the dependent …

Advanced Techniques In Time Series Forecasting: From Deterministic Models To Deep Learning, Xue Bai

Graduate Theses, Dissertations, and Problem Reports

This dissertation discusses three instances of temporal prediction, applied to population dynamics and deep learning.

In population modeling, dynamic processes are frequently represented by systems of differential equations, allowing for the analysis of various phenomena. The first application explores modeling cloned hematopoiesis in chronic myeloid leukemia (CML) via a nonlinear system of differential equations. By tracking the evolution of different cell compartments, including cycling and quiescent stem cells, progenitor cells, differentiated cells, and terminally differentiated cells, the model captures the transition from normal hematopoiesis to the chronic and accelerated-acute phases of CML. Three distinct non-zero steady states are identified, representing …

Investigation Of Space Charge Effects On Co2 Electrocatalytic Reduction On Gd-Doped Ceria Via Scanning Kelvin Probe And Model-Based Bayesian Analysis, Alejandro Mejia

Graduate Theses, Dissertations, and Problem Reports

In studying novel energy conversion and storage systems, such as high-temperature electrolysis, numerous underlying fundamental physical processes remain unclear or inadequately understood. Among these, the modeling and comprehension of surface reaction mechanisms, coupled with the intricate effects of space‑charge interfaces, remains an unclear and challenging area of research.

The work of this dissertation involves the development of a 2D finite element analysis model, leveraging the robust MOOSE framework from INL. This model, featuring inhomogeneous defect thermodynamics for near-surface chemistry, formulated through Poisson‑Cahn variational theory, has been exploited for studying the electrocatalytic reduction of CO₂ on gadolinia doped ceria. The …

Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen

Theses and Dissertations (Comprehensive)

The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …

Incorporating Effects-Based Approaches Into Environmental Impact Assessment To Improve Post-Development Monitoring, Carolyn J M Brown

Theses and Dissertations (Comprehensive)

Over the last 50 years, improvements in design of industrial facilities have significantly reduced environmental impacts. But impacts still occur and monitoring programs are the main mechanism to inform when modification/implementation of mitigation is needed. Informed decisions require adequate baseline (pre-development) data to predict impacts based on the development’s design and to understand when the post-development environment has changed. An adaptive monitoring plan provides an effective way to evaluate monitoring results and allow for proactive responses to environmental change before impacts become difficult or challenging to reverse. Unfortunately, baseline data gathered during an environmental impact assessment (EIA) is often inadequate …

Evaluation Of Imputation Methods Focusing On Categorical Outcomes, Nadia Bernardo Mendoza

CGU Theses & Dissertations

In general, standard statistical analysis models typically rely on completely observed cases, excluding incomplete rows from the dataset. This approach poses particular challenges when the objective is to predict a rare outcome, especially when some of the ob servations with the rare outcome are incomplete. In such cases, the available information to support the model in predicting this event is reduces. Theoretically correct models may pre dict all instances in the majority class achieving high accuracy, but fail in predicting the rare cases, which are often the most interesting ones. Therefore, it is crucial to make the most of all …

Disentangling Cyclic Causality: An Instance-Based Framework For Causal Discovery, Chase A. Yakaboski

Dartmouth College Ph.D Dissertations

Correlation does not imply causation" is one of the fundamental principles taught in science, emphasizing that associations between variables do not necessarily indicate causality. Yet, over the past three decades, extensive research has begun to challenge this perspective by developing sophisticated methods to differentiate causal from correlative relationships. This research suggests that correlations often involve a blend of confounded and causal interactions, which, given certain assumptions, can be disentangled to uncover actionable insights and deepen our understanding of physical, biological, and societal systems.

Accurately discovering causal relationships from data amidst cyclic dynamics remains a challenging open problem in causality research. …

Dice Are Blessed Or Cursed, Warren Campbell, Cameron Miller

SEAS Faculty Publications

Dice are cursed or blessed; that is, they roll low or high, but they are never fair. They cannot be manufactured with uniform density and geometric precision. This is particularly true of 20-sided dice or D20s. Faces are smaller than 6-sided dice, and manufacturing tolerances are similar. However, some dice are fairer than others. In our studies of plastic-mold dice about 1 in 4 test fair in 3000 rolls. We have used different statistical tests, including chi-square, modified Kolmogorov Smirnov, and double binomial tests. Of these, the method that consistently performed better is the chi-square goodness of fit test. The …

Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan

Journal of Environmental Science and Sustainable Development

Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Cabozantinib Plus Atezolizumab In Previously Untreated Advanced Hepatocellular Carcinoma And Previously Treated Gastric Cancer And Gastroesophageal Junction Adenocarcinoma: Results From Two Expansion Cohorts Of A Multicentre, Open-Label, Phase 1b Trial (Cosmic-021)., Daneng Li, Yohann Loriot, Adam Burgoyne, James Cleary, Armando Santoro, Daniel Lin, Santiago Ponce Aix, Ignacio Garrido-Laguna, Ramu Sudhagoni, Xiang Guo, Svetlana Andrianova, Scott Paulson

Kimmel Cancer Center Faculty Papers

BACKGROUND: Cabozantinib is approved for previously treated advanced hepatocellular carcinoma (aHCC) and has been investigated in gastric cancer (GC) and gastroesophageal junction adenocarcinoma (GEJ). Atezolizumab plus bevacizumab is approved for unresectable or metastatic HCC untreated with prior systemic therapy. We evaluated efficacy and safety of cabozantinib plus atezolizumab in aHCC previously untreated with systemic anticancer therapy or previously treated GC/GEJ.

METHODS: COSMIC-021 (ClinicalTrials.gov, NCT03170960) is an open-label, phase 1b study in solid tumours with a dose-escalation stage followed by tumour-specific expansion cohorts, including aHCC (cohort 14) and GC/GEJ (cohort 15). Eligible patients were aged ≥18 years with measurable locally advanced, …

Prt543, A Protein Arginine Methyltransferase 5 Inhibitor, In Patients With Advanced Adenoid Cystic Carcinoma: An Open-Label, Phase I Dose-Expansion Study, Renata Ferrarotto, Paul Swiecicki, Dan Zandberg, Robert Baiocchi, Robert Wesolowski, Cristina Rodriguez, Meredith Mckean, Hyunseok Kang, Varun Monga, Rajneesh Nath, Neil Palmisiano, Naveen Babbar, William Sun, Glenn Hanna

Department of Medical Oncology Faculty Papers

OBJECTIVES: Currently, no systemic treatments are approved for patients with recurrent and/or metastatic (R/M) adenoid cystic carcinoma (ACC). PRT543, a protein arginine methyltransferase 5 inhibitor that downregulates NOTCH1 and MYB signalling in tumours, is a potential candidate for R/M ACC treatment. We report the safety, tolerability and preliminary efficacy of PRT543 in a dose-expansion cohort of patients with R/M ACC.

MATERIALS AND METHODS: This phase I multicentre, open-label, sequential-cohort, dose-escalation and dose-expansion study (NCT03886831) enrolled patients with advanced solid tumours and select haematologic malignancies. Dose-escalation study design and results were reported previously. In the dose expansion, patients with R/M ACC …

Stereotactic Mr-Guided On-Table Adaptive Radiation Therapy (Smart) For Borderline Resectable And Locally Advanced Pancreatic Cancer: A Multi-Center, Open-Label Phase 2 Study, Michael Chuong, Percy Lee, Daniel Low, Joshua Kim, Kathryn Mittauer, Michael Bassetti, Carri Glide-Hurst, Ann Raldow, Yingli Yang, Lorraine Portelance, Kyle Padgett, Bassem Zaki, Rongxiao Zhang, Hyun Kim, Lauren Henke, Alex Price, Joseph Mancias, Christopher Williams, John Ng, Ryan Pennell, M Raphael Pfeffer, Daphne Levin, Adam Mueller, Karen Mooney, Patrick Kelly, Amish Shah, Luca Boldrini, Lorenzo Placidi, Martin Fuss, Parag Jitendra Parikh

Department of Radiation Oncology Faculty Papers

BACKGROUND AND PURPOSE: Radiation dose escalation may improve local control (LC) and overall survival (OS) in select pancreatic ductal adenocarcinoma (PDAC) patients. We prospectively evaluated the safety and efficacy of ablative stereotactic magnetic resonance (MR)-guided adaptive radiation therapy (SMART) for borderline resectable (BRPC) and locally advanced pancreas cancer (LAPC). The primary endpoint of acute grade ≥ 3 gastrointestinal (GI) toxicity definitely related to SMART was previously published with median follow-up (FU) 8.8 months from SMART. We now present more mature outcomes including OS and late toxicity.

MATERIALS AND METHODS: This prospective, multi-center, single-arm open-label phase 2 trial (NCT03621644) enrolled 136 …

Atmospheric 14Co2 Observation: A Novel Method To Evaluate Carbon Emissions, Zhenchuan Niu, Peng Wang, Shugang Wu, Weijian Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

As an important carbon emitter, China faces the stress of carbon peaking and carbon neutrality goals and international carbon reduction duty. The accurate data of carbon emissions are important to evaluate the carbon peaking and carbon neutrality goals and fulfill the international duty of carbon reduction. The Intergovernmental Panel on Climate Change (IPCC) report recommends the combination of top-down atmospheric CO₂ observation with atmospheric inversion to verify the bottom-up inventory of carbon emissions, and the atmospheric ¹⁴CO₂ observation can make the verification more accurate. Radiocarbon (14C) is the most precise tracer of fossil fuel CO₂ and …

Challenges And Countermeasures For Treatment And Remediation Of Contaminated Mega-Sites In China, Xiaoyong Liao, Yixuan Hou, You Li, Tianyi Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The treatment and remediation of pollution at contaminated mega-sites poses a significant challenge in the environmental science both domestically and internationally. Contaminated mega-sites are characterized by their widespread impact, multiple types of pollutants, and significant ecological and environmental threats. The environmental behavior cognition and efficient remediation at contaminated mega-sites face enormous challenges, among which key technological issues such as the formation mechanism of soil and groundwater pollution, accurate identification of pollution sources, and intelligent decision-making optimization urgently need to be solved. In China, contaminated mega-sites are concentrated in economically developed regions such as Beijing-Tianjin-Hebei, the Yangtze River Economic Belt, and …

Spatial Agglomeration And Environmental Effects Of Heavy Polluting Industries In China: Characteristics And Enlightenment, Hongyang Chen, Jianhui Yu, Wenzhong Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Heavy polluting industries are the important sources of industrial pollutant. Understanding the spatial agglomeration characteristics, influencing factors, agglomeration mechanism and environmental effects of China’s heavy polluting industries can help identify potential pollution risk areas to cope with increasingly severe environmental pollution problems. Based on the industrial economic data from 1999 to 2021, the spatial distribution and agglomeration characteristics of heavy polluting industries are characterized. It is found that: (1) Shandong, Jiangsu, Zhejiang, and Guangdong are the regions with high output value of the development of heavy polluting industries in the past 20 years, while Xinjiang, Inner Mongolia, Shanxi, Shaanxi, Henan, …

Interpretable Word-Level Sentiment Analysis With Attention-Based Multiple Instance Classification Models, Chenyu Yang

Statistical Science Theses and Dissertations

In this study, our main objective is to tackle the black-box nature of popular machine learning models in sentiment analysis and enhance model interpretability. We aim to gain more insight into the decision-making process of sentiment analysis models, which is often obscure in those complex models. To achieve this goal, we introduce two word-level sentiment analysis models.

The first model is called the attention-based multiple instance classification (AMIC) model. It combines the transparent model structure of multiple instance classification and the self-attention mechanism in deep learning to incorporate the contextual information from documents. As demonstrated by a wine review dataset …

Microplate-Like Metal Pyrophosphate Engineered On Ni-Foam Towards Multifunctional Electrode Material For Energy Conversion And Storage, Rishabh Srivastava

Electronic Theses & Dissertations

High clean energy demand, dire need for sustainable development, and low carbon footprints are the few intuitive challenges, leading researchers to aim for research and development for high-performance energy devices. The development of materials used in energy devices is currently focused on enhancing the performance, electronic properties, and durability of devices. Tunning the attributes of transition metals using pyrophosphate (P₂O₇) ligand moieties can be a promising approach to meet the requirements of energy devices such as water electrolyzers and supercapacitors, although such a material’s configuration is rarely exposed for this purpose of study.

Herein, we grow …

Test Event Example 12/14/23, Metzalli Demolastname

Annual Research Symposium

No abstract provided.

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre

SMU Data Science Review

Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …

The Dose-Response Effect Of Aerobic Exercise On Inflammation In Colon Cancer Survivors, Justin C. Brown, Stephanie L.E. Compton, Jeffrey A. Meyerhardt, Guillaume Spielmann, Shengping Yang

School of Medicine Faculty Publications

Background; Physical activity after surgical resection for colon cancer is associated with significantly longer disease-free survival. Inflammation is hypothesized to mediate the association between physical activity and disease-free survival in colon cancer. Methods; In this exploratory analysis of a randomized dose-response trial, 39 colon cancer survivors who completed standard therapy were stratified by cancer stage and randomized in a 1;1;1 ratio to one of three treatment groups for 24 weeks of usual-care control, 150 min/wk of moderate-intensity aerobic exercise (low-dose), or 300 min/wk of moderate-intensity aerobic exercise (high-dose). Inflammation outcomes included high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL6), and soluble tumor …

Optimal Stopping And Related Topics, Jackson Scott Hebner

Honors Scholar Theses

Suppose we are observing a randomly evolving system and have the ability to freeze it at any time. If we want to maximize some function of the state of the system, how can we determine the best time to freeze the system based on observations only up until the present moment? That is, without seeing the future, how can we form a rule for stopping the system such that we optimize the expected value of the function of interest to us? This is an informal statement of the concept of optimal stopping, a topic with deep theory and numerous applications. …