Operations Research, Systems Engineering and Industrial Engineering Commons^™

Reliability Analysis Of Repairable Systems With Recurrent Misuse-Induced Failures And Normal-Operation Failures, Weiwen Peng, Lijuan Shen, Yan Shen, Qiuzhuang Sun

Research Collection College of Integrative Studies

Failure of a repairable system may be attributed to operators’ misuse or system deterioration. The misuse may further deteriorate the system under normal operating conditions. Motivated by a real-world data set that records the recurrence times of misuse-induced failures and the normal-operation failures, this study proposes a stochastic process model for recurrence data analysis, where one type of failures is affected by the other. A non-homogeneous Poisson process and a trend-renewal process are separately used as the baseline event process models for the misuse-induced failures and the normal-operation failures, respectively. These two models are then combined by treating the event …

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 …

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 …

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 …

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.

Statistical Monitoring Of Queuing Networks, Yaren Bilge Kaya

USF Tampa Graduate Theses and Dissertations

Queuing systems are important parts of our daily lives and to keep their operations at an efficient level they need to be monitored by using queuing Performance Metrics, such as average queue lengths and average waiting times. On the other hand queue lengths and waiting times are generally random variables and their distributions depend on different properties like arrival rates, service times, number of servers. We focused on detecting the change in service rates in this report. Therefore, we monitored queues by using Cumulative Sum(CUSUM) charts based on likelihood ratios and compared the Average Run Length values of different service …

L1 Month: Utilizing High Power Rocketry As A Training Tool For Student Organizations, Aaron Hunt, Oakley Copeland, Mckynzie Perry, Benjamin Thomas

Von Braun Symposium Student Posters

No abstract provided.

Stop “Droning” On About Unmanned Aircraft Systems And Do Something About It, Richard Ham

Operations Management Presentations

The use of Unmanned Aircraft Systems (UAS) is quickly becoming an expectation for inventory management, supply chain, engineering/construction and architectural inspections, agriculture assessment and surveillance. This webinar will provide an overview of compliance requirements, startup costs, and new use cases changing the way operations managers function and improve efficiency. Supply chain management and delivery, construction management, quality management inspections and homeland security requirements are already heavily invested in UAS integration. Learn how to use your knowledge as an operations manager to stay ahead of your competitors and discover creative ways to drive up productivity and reduce costs by adding UAS …

A Sysml Trade Study Of A Large-Scale Liquid Hydrogen Storage Tank With Zero Boiloff, Justin Conner

Von Braun Symposium Student Posters

No abstract provided.

Understanding The Rocket Economy, Luke Smith, Christopher White, Victor Lopez

Von Braun Symposium Student Posters

No abstract provided.

Analytical Modeling Of Heat Deposition In Propellant For Spacecraft Utilizing Nuclear Thermal Propulsion, Alexander Aueron

Von Braun Symposium Student Posters

No abstract provided.

Virtually Prototyping Power Consumption Using Sysml, Alay Shah

Von Braun Symposium Student Posters

No abstract provided.

A Sysml Model Based Simulation Of A Ntp Ground Test, Garrick Jennings, Dale Thomas

Von Braun Symposium Student Posters

No abstract provided.

Implications Of Using A New Systems Engineering Approach In A Multi-Team International Project, Garima Bhatia

Von Braun Symposium Student Posters

No abstract provided.

Using Value Modeling And Design Structure Matrices For The Nasa Marsbee Project, Shahrom S. Doneshwar, Giulia E. Palma

Von Braun Symposium Student Posters

No abstract provided.

A Mathematical Remodeling For Crop Portfolio Selection Under Limited Irrigation Resource, Li Zhang

S.C. Water Resources Conference

A mathematical model and optimization framework to aid farmers in selecting crop portfolios were proposed and discussed in (Bokhira et al. 2014; Chrispell et al. 2012). In this paper, we propose a refined mathematical model which reduces the number of constraints by nearly half while the number of decision variables is about the same. Also, the proposed model is easier to implement and maintain due to its generalized structure, and it provides more flexibility for us to expand the problem. Some key sensitive analysis is also provided.

Embedding Sustainability In Lean Six Sigma Efforts, Nadiye O. Erdil, Can B. Aktas, Omid M. Arani

Mechanical and Industrial Engineering Faculty Publications

The emphasis on the concept of sustainability in businesses and operations is growing either due to increasing public interest, regulatory pressures, or corporate social responsibility. However, where and how to integrate sustainability needs further development for broadening its applications. Using Lean and Six Sigma (LSS) principles in sustainability studies is becoming popular in research and practice. The common approach in these studies is to identify a sustainability project followed by current state sustainability performance assessment, and then work towards improving sustainability performance using LSS tools. The goal of this study was to develop a model framework to fully embed sustainability …

Identifying Key Factors Associated With High Risk Asthma Patients To Reduce The Cost Of Health Resources Utilization, Amani Ahmad

LSU Master's Theses

Asthma is associated with frequent use of primary health services and places a burden on the United States economy. Identifying key factors associated with increased cost of asthma is an essential step to improve practices of asthma management.

The aim of this study was to identify factors associated with over utilization of primary health services and increased cost via claims data and to explore the effectiveness of case management program in reducing overall asthma related cost.

Claims data analysis for Medicaid insured asthma patients in Louisiana was conducted. Asthma patients were identified using their ICD-9 and ICD-10 codes, forward variable …

Elm-Som: A Continuous Self-Organizing Map For Visualization, Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj Mikael Björk, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

This Paper Presents a Novel Dimensionality Reduction Technique: Elm-Som. This Technique Preserves the Intrinsic Quality of Self-Organizing Maps (Som): It is Nonlinear and Suitable for Big Data. It Also Brings Continuity to the Projection using Two Extreme Learning Machine (Elm) Models, the First One to Perform the Dimensionality Reduction and the Second One to Perform the Reconstruction. Elm-Som is Tested Successfully on Six Diverse Datasets. Regarding Reconstruction Error, Elm-Som is Comparable to Som While Bringing Continuity.