Operations Research, Systems Engineering and Industrial Engineering Commons^™

Analysis Of Parkinson's Disease Data, Ram Deepak Gottapu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we investigate the diagnostic data from patients suffering with Parkinson's disease (PD) and design classification/prediction model to simplify the diagnosis. The main aim of this research is to open possibilities to be able to apply deep learning algorithms to help better understand and diagnose the disease. To our knowledge, the capabilities of deep learning algorithms have not yet been completely utilized in the field of Parkinson's research and we believe that by having an in-depth understanding of data, we can create a platform to apply different algorithms to automate the Parkinson's Disease diagnosis to certain extent. We …

Densenet For Anatomical Brain Segmentation, Ram Deepak Gottapu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Automated segmentation in brain magnetic resonance image (MRI) plays an important role in the analysis of many diseases and conditions. In this paper, we present a new architecture to perform MR image brain segmentation (MRI) into a number of classes based on type of tissue. Recent work has shown that convolutional neural networks (DenseNet) can be substantially more accurate with less number of parameters if each layer in the network is connected with every other layer in a feed forward fashion. We embrace this idea and generate new architecture that can assign each pixel/voxel in an MR image of the …

Early Detection Of Disease Using Electronic Health Records And Fisher's Wishart Discriminant Analysis, Sijia Yang, Jian Bian, Zeyi Sun, Licheng Wang, Haojin Zhu, Haoyi Xiong, Yu Li

Engineering Management and Systems Engineering Faculty Research & Creative Works

Linear Discriminant Analysis (LDA) is a simple and effective technique for pattern classification, while it is also widely-used for early detection of diseases using Electronic Health Records (EHR) data. However, the performance of LDA for EHR data classification is frequently affected by two main factors: ill-posed estimation of LDA parameters (e.g., covariance matrix), and "linear inseparability" of the EHR data for classification. To handle these two issues, in this paper, we propose a novel classifier FWDA -- Fisher's Wishart Discriminant Analysis, which is developed as a faster and robust nonlinear classifier. Specifically, FWDA first surrogates the distribution of "potential" inverse …

Multi-Objective Evolutionary Neural Network To Predict Graduation Success At The United States Military Academy, Gene Lesinski, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents an evolutionary neural network approach to classify student graduation status based upon selected academic, demographic, and other indicators. A pareto-based, multi-objective evolutionary algorithm utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) fitness evaluation scheme simultaneously evolves connection weights and identifies the neural network topology using network complexity and classification accuracy as objective functions. A combined vector-matrix representation scheme and differential evolution recombination operators are employed. The model is trained, tested, and validated using 5100 student samples with data compiled from admissions records and institutional research databases. The inputs to the evolutionary neural network model are used to classify …

System Of Systems Architecting Problems: Definitions, Formulations, And Analysis, Hadi Farhangi, Dincer Konur

Engineering Management and Systems Engineering Faculty Research & Creative Works

The system of systems architecting has many applications in transportation, healthcare, and defense systems design. This study first presents a short review of system of systems definitions. We then focus on capability-based system of systems architecting. In particular, capability-based system of systems architecting problems with various settings, including system flexibility, fund allocation, operational restrictions, and system structures, are presented as Multi-Objective Nonlinear Integer Programming problems. Relevant solution methods to analyze these problems are also discussed.

Study Of Cost Overrun And Delays Of Department Of Defense (Dod)'S Space Acquisition Program, Nazareen Sikkandar Basha, Benjamin J. Kwasa, Christina Bloebaum

Engineering Management and Systems Engineering Faculty Research & Creative Works

Defense and Aerospace Systems Acquisition projects, just like any other Large-Scale Complex Engineered Systems (LSCES) experience delays and cost overrun during the acquisition process. Cost overrun and delays in LSCES are due, in part, to high complexity, size of the project, involvement of various stakeholders, organizations, political disruptions, changes in requirements and scope. These uncertainties, due to the exogenous factors, have cost the federal government billions of dollars and delays in completion of the programs. Cost estimation of federal programs is usually based on previous generations of systems produced and almost all the time the costs are underestimated. Underestimation of …

A Retention Model For Community College Stem Students, Jennifer Snyder, Elizabeth A. Cudney

Engineering Management and Systems Engineering Faculty Research & Creative Works

The number of students attending community colleges that take advantage of transfer pathways to universities continues to rise. Therefore, there is a need to engage in academic research on these students and their attrition in order to identify areas to improve retention. Community colleges have a very diverse population and provide entry into science, technology, engineering, and math (STEM) programs, regardless of student high school preparedness. It is essential for these students to successfully transfer to universities and finish their STEM degrees to meet the global workforce demands. This research develops a predictive model for community college students for degree …

Transmission Line Inspection Using Suspended Robot: Cost Effective Analysis And Operational Routing Identification, Balaji Rathinam Nagarajan

Masters Theses

"High voltage transmission lines form a crucial part of the energy infrastructure of a country. Effective maintenance is required to maintain its reliability and reduce the probability of the occurrence of the outage. Conventionally, the routine inspection of the transmission line was conducted by linemen with the assistance of hot stick and helicopter, which is considered dangerous, time-consuming, and expensive.

In this thesis, we focus on the initial study of seeking the state of the art robotics technology to by largely replace human beings in transmission line inspection. The existing robotics technologies that are interested by utility companies, as well …

Computational Intelligence Methods For Predicting Fetal Outcomes From Heart Rate Patterns, Vinayaka Nagendra Harikishan Gude Divya Sampath

Masters Theses

"In this thesis, methods for evaluating the fetal state are compared to make predictions based on Cardiotocography (CTG) data. The first part of this research is the development of an algorithm to extract features from the CTG data. A feature extraction algorithm is presented that is capable of extracting most of the features in the SISPORTO software package as well as late and variable decelerations. The resulting features are used for classification based on both U.S. National Institutes of Health (NIH) categories and umbilical cord pH data. The first experiment uses the features to classify the results into three different …

Analyzing Sensor Based Human Activity Data Using Time Series Segmentation To Determine Sleep Duration, Yogesh Deepak Lad

Masters Theses

"Sleep is the most important thing to rest our brain and body. A lack of sleep has adverse effects on overall personal health and may lead to a variety of health disorders. According to Data from the Center for disease control and prevention in the United States of America, there is a formidable increase in the number of people suffering from sleep disorders like insomnia, sleep apnea, hypersomnia and many more. Sleep disorders can be avoided by assessing an individual's activity over a period of time to determine the sleep pattern and duration. The sleep pattern and duration can be …

Analyzing Factors Affecting Patient Satisfaction Using The Kano Model, Tejaswi Materla

Doctoral Dissertations

"Customer needs associated with the healthcare sector are constantly evolving with the technological advancements, rising costs, and shifts in patient demographics. Challenges associated with understanding patient needs impact the quality of care and life, safety, and satisfaction. The objective of this research was to develop a methodology to collect and analyze the needs associated with healthcare units that differ based on the type of care and services and patient perceptions over time. The proposed methodology provides insights into the voice of the customer through visualization of the relationship between the performance of quality attributes and customer satisfaction. Cronbach's alpha is …

Data Driven Decision Making Tools For Transportation Work Zone Planning, Samareh Moradpour

Doctoral Dissertations

"This research provides tools and methods for integrating stakeholder input and crash data analytics to better guide transportation engineers in effective work zone design and management. Three key contributions are presented: the importance of stakeholder input in traffic management strategies, application of data mining and pattern recognition to identify high-risk drivers in work zones, and the use of multinomial logistic regression (MLR) as a tool to understand key findings from historic crash data. Work zone signage is mandated by the Manual on Uniform Traffic Control Devices (MUTCD), but the current configurations are often criticized by the driving public and state …

A Methodology To Predict Community College Stem Student Retention And Completion, Jennifer Lynn Snyder

Doctoral Dissertations

"Numerous government reports point to the multifaceted issues facing the country's capacity to increase the number of STEM majors, while also diversifying the workforce. Community colleges are uniquely positioned as integral partners in the higher education ecosystem. These institutions serve as an access point to opportunity for many students, especially underrepresented minorities and women. Community colleges should serve as a major pathway to students pursuing STEM degrees; however student retention and completion rates are dismally low. Therefore, there is a need to predict STEM student success and provide interventions when factors indicate potential failure. This enables educational institutions to better …

Evaluating Microgrid Effectiveness In Transitioning Energy Portfolios, Jacob Marshal Hale

Masters Theses

"Microgrid energy systems have emerged as a potential solution to rising greenhouse gas emissions from dependence on fossil fuels. This research provides a framework for evaluating the utility of microgrids. Three key findings are presented: use of a state-of-the-art matrix (SAM) analysis to identify gaps in key research areas that inhibit wide-spread microgrid adoption, development of a system dynamics (SD) model, and a cost benefit analysis case study to evaluate microgrid feasibility in partially meeting the energy demand of a building. Governments play a central role in developing clean energy strategies. A SAM was developed to determine if key microgrid …

An Investigation Of The Economic Order Quantity Model With Quantity Discounts Under An Environmental Objective, Tiffanie Marie Toles

Masters Theses

"In a sustainable supply chain, retailers are the direct link between customers and products. Retailers play an important role by relaying feedback such as customer satisfaction, inventory improvement, or product improvement to the other key players in a supply chain. Their overall goal is to reduce supply chain costs, such as the cost of ordering product, transporting product, or holding product in inventory. Other costs associated in a supply chain can include environmental and operations costs. It is important to consider these costs due to the impact environmental operations play in the role of how sustainable a supply chain can …