Operations Research, Systems Engineering and Industrial Engineering Commons^™

Corner Localization In Digital Images Based On Radon Transform, Xuguang Wang, Zhang Qin, Su Jie

Journal of System Simulation

Abstract: Location accuracy is one of the key indexes of measuring the performance of feature point.. High location accuracy feature point detection has important implications for the applications such as 3D reconstruction, motion estimation, target tracking and recognition, image registration, etc. A corner location algorithm based on Radon transform is proposed.Edge binary images are obtained with traditional method first, ideal straight lines and curves are extracted then, potential corner locations are calculated next, fake corners are rejected finally. Experimental results on both simulation and real images show that, this method performs better than the existing methods on interest point localization …

Artificial Bee Colony Algorithm For Solving Fuzzy Multi-Objective Bed Allocation Model, Abdulhakeem Luqman Hasan

Karbala International Journal of Modern Science

With the improvement of the medical services frameworks rivalry, hospitals face more and more challenges. In the interim, allotment of resource has a crucial influence on performing competitive benefits in a hospitals. To choose the suitable beds number is one of the most essential tasks in hospital administration. Anyway, in true condition, bed allotment choice is a multiple-side problem with weakness and haphazardness of the information available. It is so sophisticated. Therefore, the research about bed allotment difficulty is comparatively rare under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we …

Mazak Laser Optimization, Maylon Ellington, Terrilian E. Agbor Oji, William N. Palm

Senior Design Project For Engineers

Starflex Fabrication is a manufacturing company that thrives to provide custom, precision fabricated parts, and assemblies to their customers.The Mazak laser is Starflex Fabrication’s primary cutting machine and is critical to the overall process for each order. Team Flex will look to optimize the laser’s process and improve overall shop throughput.

Investigation Of Retrieved Cardiac Devices, Anmar Salih, Iosif Papadakis Ktistakis, Spyridon Manganas, Abdul Wase, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Damage assessment of lead and pulse generator with various exposure times is important in the development of cardiac devices. Approximately, 92.1 million patients in the US suffer from cardiovascular diseases with an estimated healthcare cost of over $300 billion and at least one million with implantable cardiac devices. These devices are complex and composed on multiple levels and present challenges while assessing the damage. However, the study on the analysis of cardiac devices may lend insight into common damage patterns and improve future cardiac devices design. The objective of this work is to perform a thorough in vivo damage assessment …

Space Optimization And Process Improvement, Harith Alshareef

Senior Design Project For Engineers

Siemens Energy warehouse located in Suwanee, GA runs out of space in the Precision Lab due to rapid growth, seasonal peaks, and poor space utilization. The objective of the project is to redesign the Precision Lab layout and improve the tool assessment process to increase efficiency, productivity, and profitability.

The first solution is to add shelves in the Precision lab as well as the Torque lab and reduce the honeycombing effect on the shelves, which results in a 120%-150% increase in the storage space. We propose adding Tablets that include barcode scanner features to reduce the time spent on the …

Investigation Of A Neuro-Stimulator Retrieved Posthumously, Megan Markl, Rodney J. Gutherie, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

A neurostimulator was investigated in this paper posthumously. Device was presented to our anatomical gift program. Investigation was multi-fold and contained visual inspection, using an optical microscope, and mechanical and electrical testing of leads and its insulator. It was concluded that the device could have been damaged during implantation, in vivo, during removal, and/or during transportation to author’s laboratories. The damage observed on the lead insulation is similar to that which can occur due to anchoring of the lead and hardening due to oxidation. Insulation stiffness was determined to be 1/10 of new insulator. The results reported here on the …

Simulation Of Skull Fracture Due To Falls, Anthony Vicini, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

This study presents novel predictive equations for von Mises stress values of bones in the frontal and lateral regions of the skull. The equations were developed based on results of a finite element model developed during this research. The model was validated for frontal and lateral loading conditions with input values mimetic to fall scenarios. Using neural network processing of the information derived from the model achieved R2 values of 0.9990 for both the stress and deflection. Based on the outcome of the fall victims, a threshold von Mises stress of 40.9 to 46.6 MPa was found to indicate skull …

Assessing The Impact Of Principal Component Analysis On Accurately Predicting Melanoma Diagnosis Applied On Different Classification Models, Juan Cristobal Olmedo Rivera

Industrial, Manufacturing, and Systems Theses - Archive

With huge amounts of data at our disposal in the medical field, mathematical models are built to diagnose diseases. This study focuses on melanoma because it’s the type of skin cancer that accounts for most deaths, up to 7,230 in 2019 according to the American Cancer Society. The study focuses on the effectiveness on diagnosing melanoma and how Principal Component Analysis (PCA) impacts the performance of four models being assessed, which are: K Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Each model evaluates the melanoma dataset before and after performing the PCA …

Planning And Optimization Of A Stochastic Multi-Phase Multi- Criteria Multi-Echelon Humanitarian Logistics Network, A B M Mainul Bari

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Disasters, may that be anthropogenic or natural, cause much havoc to vast area and population. Property and infrastructures get destroyed. People are often in need of urgent relief like dry foods and water to survive. In a country which is in the underdeveloped part of the world, relief and evacuation activities are usually carried out by local government run aid agencies. Most of the time, the local decision makers do the coordination or planning of these humanitarian activities largely based on either past experience or sometimes just pure hunch, which is neither efficient nor economic. Proper planning and coordination in …

A Governance Perspective For System-Of-Systems, Polinpapilinho F. Katina, Charles B. Keating, James A. Bobo, Tyrone S. Toland

Engineering Management & Systems Engineering Faculty Publications

The operating landscape of 21st century systems is characteristically ambiguous, emergent, and uncertain. These characteristics affect the capacity and performance of engineered systems/enterprises. In response, there are increasing calls for multidisciplinary approaches capable of confronting increasingly ambiguous, emergent, and uncertain systems. System of Systems Engineering (SoSE) is an example of such an approach. A key aspect of SoSE is the coordination and the integration of systems to enable ‘system-of-systems’ capabilities greater than the sum of the capabilities of the constituent systems. However, there is a lack of qualitative studies exploring how coordination and integration are achieved. The objective of this …

Multivariate Time Series Pattern Recognition Using Machine Learning And Deep Learning Methods, Sai Abhishek Devar

Industrial, Manufacturing, and Systems Theses - Archive

In this research work, we have implemented machine learning & deep-learning algorithms on real-time multivariate time series datasets in the manufacturing & health care fields. The research work is organized in two case-studies. The case study-1 is about rare event classification in multivariate time series in a pulp and paper manufacturing industry, data was collected of multiple sensors at each stage of production line, the data contains a rare event of paper break that commonly occurs in the industry. For preprocessing we have implemented sliding window approach for calculating first order difference method to capture the variation in the data …

Evaluating The Resiliency Of Industrial Internet Of Things Process Control Using Protocol Agnostic Attacks, Hector L. Roldan

Theses and Dissertations

Improving and defending our nation's critical infrastructure has been a challenge for quite some time. A malfunctioning or stoppage of any one of these systems could result in hazardous conditions on its supporting populace leading to widespread damage, injury, and even death. The protection of such systems has been mandated by the Office of the President of the United States of America in Presidential Policy Directive Order 21. Current research now focuses on securing and improving the management and efficiency of Industrial Control Systems (ICS). IIoT promises a solution in enhancement of efficiency in ICS. However, the presence of IIoT …

Machine Learning Applications To Predict Road Crash And Soccer Game Outcomes, Lu Bai

Master's Theses

Machine learning has become a cutting-edge and widely studied data science field of study in recent years across many industries and disciplines. In this thesis, two problems (1- crash severity prediction, 2- soccer game outcome prediction.) were investigated by using a set of machine learning approaches, namely: Ridge regression, Lasso Regression, Support Vector Machine (SVM), Neural Network (NN), Random Forest (RF).

The first study is focused on investigating the critical factors affecting crash severity on a comprehensive time-series state-wide traffic crash data. The dataset covers crashes occurred in the state of Connecticut between 1995 and 2014. Traffic crashes are an …

Deep Learning Models For Visibility Forecasting, Luz Carolina Ortega Gomez

Theses and Dissertations

This dissertation addresses the task of visibility forecasting via deep learning models using data from weather stations. Visibility is one of the most critical weather impacts on transportation systems. Low visibility conditions can seriously impact safety and traffic operations, leading to adverse scenarios, causing accidents, and jeopardizing transportation systems. Accurate visibility forecasting plays a key role in decision-making and management of transportation systems. However, due to the complexity and variability of weather variables, visibility forecasting remains a highly challenging task and a matter of significant interest for transportation agencies nationwide. This dissertation explores the use of deep learning models for …

Resource Allocation And Task Scheduling Optimization In Cloud-Based Content Delivery Networks With Edge Computing, Yang Peng

Operations Research and Engineering Management Theses and Dissertations

The extensive growth in adoption of mobile devices pushes global Internet protocol (IP) traffic to grow and content delivery network (CDN) will carry 72 percent of total Internet traffic by 2022, up from 56 percent in 2017. In this praxis, Interconnected Cache Edge (ICE) based on different public cloud infrastructures with multiple edge computing sites is considered to help CDN service providers (SPs) to maximize their operational profit. The problem of resource allocation and performance optimization is studied in order to maximize the cache hit ratio with available CDN capacity.

The considered problem is formulated as a multi-stage stochastic linear …

Resource-Constrained Project Scheduling With Autonomous Learning Effects, Jordan M. Ticktin

Master's Theses

It's commonly assumed that experience leads to efficiency, yet this is largely unaccounted for in resource-constrained project scheduling. This thesis considers the idea that learning effects could allow selected activities to be completed within reduced time, if they're scheduled after activities where workers learn relevant skills. This paper computationally explores the effect of this autonomous, intra-project learning on optimal makespan and problem difficulty. A learning extension is proposed to the standard RCPSP scheduling problem. Multiple parameters are considered, including project size, learning frequency, and learning intensity. A test instance generator is developed to adapt the popular PSPLIB library of scheduling …

Shared Or Dedicated Infrastructures: On The Impact Of Reprovisioning Ability, Roch A. Guérin, Kartik Hosanagar, Xinxin Li, Soumya Sen

Computer Science and Engineering Faculty Research

New technologies, such as virtualization, are transforming the way in which software and services are deployed and delivered to their users. They are behind the emergence of IT offerings such as cloud computing and converged networks, and manifest themselves through two important trends: (1) lower the cost of sharing a common infrastructure across multiple services with disparate resource requirements, and (2) dynamic provi- sioning of capacity in response to demand. Conventional wisdom is that both of these capabilities are synergistic, with greater provisioning flexibility improving the benefits derived from sharing computing or network resources. Consequently, a service operator should now …

Process Improvement And Lift Design For The Installation Of A Metrology Machine Assembly, Dalt J. Lasell, James Mitchell O'Meara, Matthew Steensma

Industrial and Manufacturing Engineering

The objective is to work with Onto Innovations, a leading provider of semiconductor metrology and manufacturing solutions, to develop a system that safely installs a 250lb optics plate into the Atlas III: one of their metrology machines. Based in Milpitas, CA, Onto Innovations utilizes a variety of operations to create different products and assembles each product on site. The 250lb optics plates are WIP that are transferred between fixtures and the Atlas III using a combination of lifts and human workers. The WIP have long lead times, high tolerances, and large costs associated with their manufacturing process.

Onto Innovations identified …

Automation Of Data Analysis In Formula 1, Adam Joseph Mourad, Prescott Jeanne Delzell, Patrick Conner Mccabe

Industrial and Manufacturing Engineering

This paper explores economic solutions for Formula 1 racing companies who are interested in data visualization tools. The research was conducted on the current development of data gathering, data visualization, and data interpretation in Formula 1 racing. It was found that a large chunk of racing companies within the league needs an affordable, effective, and automated visualization tool for data interpretation. As data collection in Formula 1 arises, the need for faster and more powerful software increases. Racing companies profit off-brand exposure and the more a racing team wins, the more exposure they receive. The goal of the paper focuses …

Simulation And Optimization Of A Multi-Agent System On Physical Internet Enabled Interconnected Urban Logistics., Long Zheng

Electronic Theses and Dissertations

An urban logistics system is composed of multiple agents, e.g., shippers, carriers, and distribution centers, etc., and multi-modal networks. The structure of Physical Internet (PI) transportation network is different from current logistics practices, and simulation can effectively model a series of PI-approach scenarios. In addition to the baseline model, three more scenarios are enacted based on different characteristics: shared trucks, shared hubs, and shared flows with other less-than-truckload shipments passing through the urban area. Five performance measures, i.e., truck distance per container, mean truck time per container, lead time, CO₂ emissions, and transport mean fill rate, are included in …

Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders

Graduate Theses and Dissertations

The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created …

Effects Of Resampled Data On Time Series Forecasting Accuracy, Jennifer Garland

Theses and Dissertations

This thesis will look at time series forecasting of the air pollutants in Beijing, China and the power consumption of an individual household located in Sceaux, France. The forecast will be taken from two classical methods, the Holt-Winters’ methods and the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The Holt-Winters’ method will be looked at from the additive, multiplicative and damped methods. The SARIMA model will be looked at as a uni-variate model. In this thesis, it will be shown that less complex algorithms, such as the Holt-Winters’ methods can process larger data sets without the need of resampling, and …

Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis

Engineering Management and Systems Engineering Faculty Research & Creative Works

The article "Better beware: comparing metacognition for phishing and legitimate emails", written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 20 July 2019 without open access.

Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction, allowing them to better manage portfolio risk. However, the financial crisis of 2008 has heightened investor sensitivity to the high fees, illiquidity, lack of transparency, and lockup periods typically associated with hedge funds. Hedge fund replication products, or clones, seek to answer these challenges by providing daily liquidity, transparency, and immediate exposure to a desired hedge fund strategy. Nonetheless, although lowering cost and adding simplicity by using a common set of factors, traditional replication …

Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. However, few studies have focused on forecasting daily stock market returns, especially when using powerful machine learning techniques, such as deep neural networks (DNNs), to perform the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation function, and model parameters, with their performance depending on the format of the data representation. This paper presents a comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 …

A Case Study: The First Coastal Nuclear Decommissioning Project In California, Willie Aaron Quiros

Construction Management

San Onofre Nuclear Generating System (SONGS) is one of two nuclear power plants in California. Since the shut down in 2012, there is only one actively remaining, Diablo Canyon Nuclear Power Plant, which is set to shut down in 2024. This paper will examine the decommissioning of SONGS thus far; the first coastal nuclear decommissioning project in California’s stringent permitting process. This project was awarded as a joint venture to AECOM and Energy Solutions, both having experiencing in the field of nuclear decommissioning. This paper will outline what nuclear decommissioning challenges have been in the past; general steps of decommissioning …

Aisle Design For Order Picking Operations With Unit-Load Replenishment., Dominic Ian Sleigh

Electronic Theses and Dissertations

The warehouse design problem has been addressed in the last decade with fewer constraints than ever before. Between optimization for unit load and order picking warehouses, the former has had extensively more research performed. Unit load optimization efforts have promised labor savings of 20-22%. Of the existing research for order-picking warehouses, only small improvements of less than 4% have been claimed. We propose the design optimization for order-picking warehouses requires consideration for inherently incurred unit load operations from pallet inbound activities, as well as forward-pick area replenishment. We perform experiments comparing optimization of aisle design using order picking data with …

A Systematic Approach For Automatically Answering General-Purpose Objective And Subjective Questions, Lok Prasad Acharya

Theses and Dissertations

In this era of information explosion, people generally rely on the Internet, and more precisely, the search engines to get answers to their questions. However, what a search engine can do is just retrieve documents. Given some keywords, it only returns the relevant ranked documents that contain the keywords. Although users often want a precise answer to a question, they are left to extract answers from the documents themselves. This is where Automatic Question Answering (AQA) systems come into play. An AQA system takes questions in natural language as input and searches related answers in the set of documents and …

Improving Grapheme-To-Phoneme Translation With The Use Of Nalu Attention Mechanisms, Brian Sheldon Smith

Theses and Dissertations

In recent years, Natural Language Processing in the field of machine learning has seen some major improvements. Data scientists have shown that neural networks are capable of breaking down semantics of sentences, translating languages, and answering complex questions with fast recall. While impressive, these feats all hinge on having access to a massive amount of clean text, or data sets with almost perfect grammar and spelling. Without this, neural networks will usually fail to converge on a meaningful result. To partially this dependency, Grapheme-to-Phoneme conversion can be employed. This is the conversion of words from their spellings to a form …

Uncertainty And Error In Combat Modeling, Simulation, And Analysis, Jason A. Blake

Theses and Dissertations

Due to the infrequent and competitive nature of combat, several challenges present themselves when developing a predictive simulation. First, there is limited data with which to validate such analysis tools. Secondly, there are many aspects of combat modeling that are highly uncertain and not knowable. This research develops a comprehensive set of techniques for the treatment of uncertainty and error in combat modeling and simulation analysis. First, Evidence Theory is demonstrated as a framework for representing epistemic uncertainty in combat modeling output. Next, a novel method for sensitivity analysis of uncertainty in Evidence Theory is developed. This sensitivity analysis method …