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Institutional Context Drives Mobility: A Comprehensive Analysis Of Academic And Economic Factors That Influence International Student Enrollment At United States Higher Education Institutions, Natalie Cruz 2021 Old Dominion University

Institutional Context Drives Mobility: A Comprehensive Analysis Of Academic And Economic Factors That Influence International Student Enrollment At United States Higher Education Institutions, Natalie Cruz

College of Education & Professional Studies (Darden) Posters

International student enrollment (ISE) has become a hallmark of world-class higher education institutions (HEIs). Although the U.S. has welcomed the largest numbers of international students since the 1950s, ISE shrunk by 10% in the previous three years from an all-time high of 903,127 students in 2016/2017 (IIE, 2019). Research studies about international student mobility and enrollment highlights the significant role that academic and economic rationales play for international students. This quantitative, ex post facto study focused on the influence of ranking, tuition, Optional Practical Training, Gross Domestic Product, and the unemployment rate on ISE at 2,884 ...


Statistical Study Of The Effect Of Implementing An Airveyor System On The Warpage Of Injection Molded Closures, Charles Wesley Bozarth 2021 Western Kentucky University

Statistical Study Of The Effect Of Implementing An Airveyor System On The Warpage Of Injection Molded Closures, Charles Wesley Bozarth

Masters Theses & Specialist Projects

Berry Global in Bowling Green, Kentucky produces predominantly polypropylene container closures. One variant, the 83mm lined jar closure, is produced by first being injection molded, placed in work-in-progress (WIP) hold for 24 hours to cool, and then finished through the auxiliary liner operation into a final product. While this process is an effective method to produce a quality large-diameter closure and allows the polypropylene adequate time to cool without warping out of shape, the 24-hour WIP time and the manpower needed to accomplish this can negatively impact several business metrics as well as employee safety.

The purpose of this thesis ...


Unsupervised Multivariate Time Series Clustering, Md Monibor Rahman, Lasitha Vidyaratne, Alex Glandon, Khan Iftekharuddin 2021 Old Dominion University

Unsupervised Multivariate Time Series Clustering, Md Monibor Rahman, Lasitha Vidyaratne, Alex Glandon, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

Clustering is widely used in unsupervised machine learning to partition a given set of data into non-overlapping groups. Many real-world applications require processing more complex multivariate time series data characterized by more than one dependent variables. A few works in literature reported multivariate classification using Shapelet learning. However, the clustering of multivariate time series signals using Shapelet learning has not explored yet. Shapelet learning is a process of discovering those Shapelets which contain the most informative features of the time series signal. Discovering suitable Shapelets from many candidates Shapelet has been broadly studied for classification and clustering of univariate time ...


The Fundamental Limit Theorem Of Countable Markov Chains, Nathanael Gentry 2021 Liberty University

The Fundamental Limit Theorem Of Countable Markov Chains, Nathanael Gentry

Senior Honors Theses

In 1906, the Russian probabilist A.A. Markov proved that the independence of a sequence of random variables is not a necessary condition for a law of large numbers to exist on that sequence. Markov's sequences -- today known as Markov chains -- touch several deep results in dynamical systems theory and have found wide application in bibliometrics, linguistics, artificial intelligence, and statistical mechanics. After developing the appropriate background, we prove a modern formulation of the law of large numbers (fundamental theorem) for simple countable Markov chains and develop an elementary notion of ergodicity. Then, we apply these chain convergence results ...


Adventuring Into Complexity By Exploring Data: From Complicity To Sustainability, Tim Lutz 2021 West Chester University

Adventuring Into Complexity By Exploring Data: From Complicity To Sustainability, Tim Lutz

Northeast Journal of Complex Systems (NEJCS)

Problems of sustainability are typically represented by major present-day challenges such as climate change, biodiversity loss, and environmental and social injustice. Framed this way, sustainable lives and societies depend on finding solutions to each problem. From another perspective, there is only one problem behind them all, stated by Gregory Bateson as: “…the difference between how nature works and the way people think,” and complexity provides a way to define and approach this problem. I extend Edgar Morin’s conceptions of restricted and general complexity into pedagogy to address problems of simplicity and reductionist teaching. The proposed pedagogy is based on ...


Testing Identifying Assumptions In Bivariate Probit Models, Santiago Acerenza, Otávio Bartalotti, Desire Kedagni 2021 Iowa State University

Testing Identifying Assumptions In Bivariate Probit Models, Santiago Acerenza, Otávio Bartalotti, Desire Kedagni

Economics Working Papers

This paper focuses on the bivariate probit model's identifying
assumptions: joint normality of errors, instrument exogeneity, and relevance conditions. First, we develop novel sharp testable equalities that can detect all possible observable violations of the assumptions. Second, we propose an easy-to-implement testing procedure for the model's validity based on feasible testable implications using existing inference methods for intersection bounds. The test achieves correct empirical size for moderately sized samples and performs well in detecting violations of the conditions in Monte Carlo simulations. Finally, we provide researchers with a road map on what to do when the bivariate probit ...


Entropic Dynamics Of Networks, Felipe Xavier Costa, Pedro Pessoa 2021 Department of Physics, University at Albany, State University of New York

Entropic Dynamics Of Networks, Felipe Xavier Costa, Pedro Pessoa

Northeast Journal of Complex Systems (NEJCS)

Here we present the entropic dynamics formalism for networks. That is, a framework for the dynamics of graphs meant to represent a network derived from the principle of maximum entropy and the rate of transition is obtained taking into account the natural information geometry of probability distributions. We apply this framework to the Gibbs distribution of random graphs obtained with constraints on the node connectivity. The information geometry for this graph ensemble is calculated and the dynamical process is obtained as a diffusion equation. We compare the steady state of this dynamics to degree distributions found on real-world networks.


An Image Segmentation Technique With Statistical Strategies For Pesticide Efficacy Assessment, Steven B. Kim, Dong Sub Kim, Xiaoming Mo 2021 California State University, Monterey Bay

An Image Segmentation Technique With Statistical Strategies For Pesticide Efficacy Assessment, Steven B. Kim, Dong Sub Kim, Xiaoming Mo

Mathematics and Statistics Faculty Publications and Presentations

Image analysis is a useful technique to evaluate the efficacy of a treatment for weed control. In this study, we address two practical challenges in the image analysis. First, it is challenging to accurately quantify the efficacy of a treatment when an entire experimental unit is not affected by the treatment. Second, RGB codes, which can be used to identify weed growth in the image analysis, may not be stable due to various surrounding factors, human errors, and unknown reasons. To address the former challenge, the technique of image segmentation is considered. To address the latter challenge, the proportion of ...


Modelling The Impact Of Clot Fragmentation On The Microcirculation After Thrombectomy, Wahbi K. El-Bouri, Andrew MacGowan, Tamas I. Jozsa, Matthew J. Gounis, Stephen J. Payne 2021 University of Oxford

Modelling The Impact Of Clot Fragmentation On The Microcirculation After Thrombectomy, Wahbi K. El-Bouri, Andrew Macgowan, Tamas I. Jozsa, Matthew J. Gounis, Stephen J. Payne

Radiology Publications

Many ischaemic stroke patients who have a mechanical removal of their clot (thrombectomy) do not get reperfusion of tissue despite the thrombus being removed. One hypothesis for this 'no-reperfusion' phenomenon is micro-emboli fragmenting off the large clot during thrombectomy and occluding smaller blood vessels downstream of the clot location. This is impossible to observe in-vivo and so we here develop an in-silico model based on in-vitro experiments to model the effect of micro-emboli on brain tissue. Through in-vitro experiments we obtain, under a variety of clot consistencies and thrombectomy techniques, micro-emboli distributions post-thrombectomy. Blood flow through the microcirculation is modelled ...


Generalized Fiducial Inference On The Mean Of Zero-Inflated Poisson And Poisson Hurdle Models, Yixuan Zou, Jan Hannig, Derek S. Young 2021 Genentech

Generalized Fiducial Inference On The Mean Of Zero-Inflated Poisson And Poisson Hurdle Models, Yixuan Zou, Jan Hannig, Derek S. Young

Statistics Faculty Publications

Zero-inflated and hurdle models are widely applied to count data possessing excess zeros, where they can simultaneously model the process from how the zeros were generated and potentially help mitigate the effects of overdispersion relative to the assumed count distribution. Which model to use depends on how the zeros are generated: zero-inflated models add an additional probability mass on zero, while hurdle models are two-part models comprised of a degenerate distribution for the zeros and a zero-truncated distribution. Developing confidence intervals for such models is challenging since no closed-form function is available to calculate the mean. In this study, generalized ...


Validation Of Icd-10-Cm Codes For Injuries Complicating Pregnancy, Childbirth And The Puerperium: A Medical Record Review, Anna Hansen, Dana Quesinberry, Peter Akpunonu, Julia Martin, Svetla Slavova 2021 University of Kentucky

Validation Of Icd-10-Cm Codes For Injuries Complicating Pregnancy, Childbirth And The Puerperium: A Medical Record Review, Anna Hansen, Dana Quesinberry, Peter Akpunonu, Julia Martin, Svetla Slavova

Kentucky Injury Prevention and Research Center Faculty Publications

INTRODUCTION: The purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.

METHODS: A medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an ...


Predictive Modeling And Estimation Of The Doubling Time Of Confirmed Cases Of Covid-19 In Niger, Ibrahim Sidi Zakari, Hadiza Galadima 2021 Old Dominion University

Predictive Modeling And Estimation Of The Doubling Time Of Confirmed Cases Of Covid-19 In Niger, Ibrahim Sidi Zakari, Hadiza Galadima

Community & Environmental Health Faculty Publications

Modeling is increasingly used to assess scenarios and make projections on the future course of new coronavirus disease. This allows for better planning of care as well as a relaxation or tightening of the restrictive measures decreed by the government and the health authorities. The data analyzed in this study covers the period from March 19 to June 05, 2020 and allowed predictions of new cases of COVID-19 based on a growth model with a growth rate that changes linearly over time. In addition, we calculated and predicted the doubling time of the number of positive cases in each region ...


Node Classification On Relational Graphs Using Deep-Rgcns, Nagasai Chandra 2021 California Polytechnic State University, San Luis Obispo

Node Classification On Relational Graphs Using Deep-Rgcns, Nagasai Chandra

Master's Theses

Knowledge Graphs are fascinating concepts in machine learning as they can hold usefully structured information in the form of entities and their relations. Despite the valuable applications of such graphs, most knowledge bases remain incomplete. This missing information harms downstream applications such as information retrieval and opens a window for research in statistical relational learning tasks such as node classification and link prediction. This work proposes a deep learning framework based on existing relational convolutional (R-GCN) layers to learn on highly multi-relational data characteristic of realistic knowledge graphs for node property classification tasks. We propose a deep and improved variant ...


Continuous-Time Controlled Branching Processes, Ines Garcia, George Yanev, Manuel Molina, Nikolay Yanev, Miguel Velasco 2021 University of Extremadura, Spain

Continuous-Time Controlled Branching Processes, Ines Garcia, George Yanev, Manuel Molina, Nikolay Yanev, Miguel Velasco

Mathematical and Statistical Sciences Faculty Publications and Presentations

Controlled branching processes with continuous time are introduced and limiting distributions are obtained in the critical case. An extension of this class as regenerative controlled branching processes with continuous time is proposed and some asymptotic properties are considered.


Enhancing Data Generation For National Development In Nigeria: Institutional And Structural Issues1, Olu Ajakaiye 2021 Central Bank of Nigeria

Enhancing Data Generation For National Development In Nigeria: Institutional And Structural Issues1, Olu Ajakaiye

CBN Journal of Applied Statistics (JAS)

In this presentation, attention is focused on data generation for the purposes of reasoning, discussing and calculating the status, process and prospects of economic development. Economic development has also been defined in various ways. Again for the present purposes, economic development will be conceived as the process of economic growth and structural transformation (Ajakaiye, 2002). Clearly, data, as a gathered body of facts about the economy, is a basic requirement in the process of economic growth and transformation. Foremost, facts about the economy are necessary in order to appreciate the current state of the economy in terms of growth and ...


Testing The Weak-Form Efficiency Market Hypothesis: Evidence From Nigerian Stock Market, Gimba K. Victor 2021 Central Bank of Nigeria

Testing The Weak-Form Efficiency Market Hypothesis: Evidence From Nigerian Stock Market, Gimba K. Victor

CBN Journal of Applied Statistics (JAS)

In recent years, the Nigerian Stock Exchange (NSE) has witnessed an unprecedented growth in market capitalization, membership, value and volume traded. By December 2007, the All Share Index has grown massively over 57,990.2 from 1113.4 in January 1993. This rising interest in investment opportunities in the NSE raises questions about its efficiency. This paper tests the Weak-form Efficient Market Hypothesis of the NSE by hypothesizing Normal distribution and Random walk of the return series. Daily and weekly All Share Index and five most traded and oldest bank stocks of the NSE are examined from January 2007 to ...


A Business Cycle Model For Nigeria, Alege O. Philip 2021 Central Bank of Nigeria

A Business Cycle Model For Nigeria, Alege O. Philip

CBN Journal of Applied Statistics (JAS)

The current global financial meltdown draws, once again, attention to the existence of business cycle fluctuations. Experts are of the view that the ongoing crisis is far deeper than the great depression of the 1930s. It should be recalled that the Keynes and Keynesianism was a response to that depression. Therefore, the objective of this paper is to develop a small business cycle model in the spirit of Dynamic Stochastic General Equilibrium (DSGE) model for Nigeria designed to examine the sources of business cycles, and use the model for policy analysis. This paper considers the implications of three policy shocks ...


Fiscal Federalism In Nigeria: A Cluster Analysis Of Revenue Allocation To States And Local Government Areas, 1999 – 2008, Sam O. Olofin, Olusanya E. Olubusoye, Bello K. Ajide, Salisu A. Afees, Olalekan S. Akinola 2021 Central Bank of Nigeria

Fiscal Federalism In Nigeria: A Cluster Analysis Of Revenue Allocation To States And Local Government Areas, 1999 – 2008, Sam O. Olofin, Olusanya E. Olubusoye, Bello K. Ajide, Salisu A. Afees, Olalekan S. Akinola

CBN Journal of Applied Statistics (JAS)

Existing literature on revenue allocation in Nigeria shows more concern for merits and demerits of sharing principles and /or formulae. Several alternatives have been proposed and will continue to be developed to address the unending agitations from beneficiaries. Contrary however, this paper analyzes two items of revenue (statutory and VAT) shared among the states including FCT and all the Local Government Areas (LGAs) between May 1999 and December 2008. The net statutory allocation after deductions was also analyzed. Using Cluster analysis to evaluate revenue allocation in Nigeria, States and LGAs exhibiting similarity in revenue received were grouped and their common ...


Threshold Effect Of Inflation On Economic Growth In Nigeria, Sani Bawa, Abdullahi S. Ismaila 2021 Central Bank of Nigeria

Threshold Effect Of Inflation On Economic Growth In Nigeria, Sani Bawa, Abdullahi S. Ismaila

CBN Journal of Applied Statistics (JAS)

It is widely believed that price stability promote long-term economic growth, whereas high inflation is inimical to growth. This paper utilized a quarterly time series data for the period 1981 – 2009 to estimate a threshold level of inflation for Nigeria. Using a threshold regression model developed by Khan and Senhadji (2001), the study estimated a threshold inflation level of 13 per cent for Nigeria. Below the threshold level, inflation has a mild effect on economic activities, while above it, the magnitude of the negative effect of inflation on growth was high. The negative and significant relationship between inflation and economic ...


Reactions Of Stock Market To Monetary Policy Shocks During The Global Financial Crisis: The Nigerian Case, Aliyu Shehu U.R. 2021 Central Bank of Nigeria

Reactions Of Stock Market To Monetary Policy Shocks During The Global Financial Crisis: The Nigerian Case, Aliyu Shehu U.R.

CBN Journal of Applied Statistics (JAS)

This paper seeks to assess the reactions of Nigeria’s stock market to monetary policy innovations during the period of global financial crisis on the basis of monthly data over the period January, 2007 to August, 2011. In particular, stock market return was regressed against major monetary policy instruments; money stock (M1, and M2) and monetary policy rate (MPR). The theoretical basis for the paper stems from the works of new classical macroeconomics and rational expectation hypothesis (REH). Lucas (1972) postulated that only the unanticipated monetary shock influences real economic activity. Using the GARCH by developed Engle and Bollerslev (1986 ...


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