Engineering Commons^™

An Analysis Of The Size And Impact Of Digital Footprints, Whitney Nielsen Maxwell

Theses and Dissertations

Personal information available online is known as a digital footprint. While many have a digital footprint, few if any, know what it encapsulates or how to control it. Technology and personal information are becoming more intertwined as technology becomes more integrated with everyday activities. Personal information can be defined as details that apply to a person such as race or shopping habits. Shopping habits are considered personal information by many corporations who spend money to track, or even predict purchases of individuals, whereas more traditional forms of personal information are details like gender, birthdate, and home town. With a wide …

Airport Security Investment Model, Joshua Daniel Bolton

Graduate Theses and Dissertations

In an increasingly mobile and diverse world, it is difficult to quantify the risk, or danger, associated with traveling. Airports have suffered greatly for being unable to define potential risks and protect against them. Intelligent adversary risk is a complicated high-level issue for many airports. Airports are targeted because of the large amount of people in a confined space and the social, economic, and psychological impact of terrorist attacks on the American people. In the months following September 11th, 2001, the airline industry in the United States lost $1.1 billion in revenue. The American people stayed grounded, for fear of …

Methodologies For Solving Integrated Transportation And Scheduling Problems, Fereydoun Adbesh

Graduate Theses and Dissertations

This research proposes novel solution techniques to optimize two real-world problems in the area of scheduling and transportation. We first consider a model for optimizing the operations of dredges. In this problem, scheduling and assignment decisions are integrated across a finite planning horizon. Additional constraints and problem elements explicitly considered include, but are not limited, to environmental work window restrictions, budget limitations, dredge operation rates and schedule-dependent dredge availability. Our approach makes use of Constraint Programming (CP) to obtain quality and robust solutions within an amount of time small enough to be useful to practitioners. The expanded feature set of …

Law Enforcement Resource Optimization With Response Time Guarantees, Jonathan Chase, Jiali Du, Na Fu, Truc Viet Le, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In a security-conscious world, and with the rapid increase in the global urbanized population, there is a growing challenge for law enforcement agencies to efficiently respond to emergency calls. We consider the problem of spatially and temporally optimizing the allocation of law enforcement resources such that the quality of service (QoS) in terms of emergency response time can be guaranteed. To solve this problem, we provide a spatio-temporal MILP optimization model, which we learn from a real-world dataset of incidents and dispatching records, and solve by existing solvers. One key feature of our proposed model is the introduction of risk …

Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Port capacity is determined by three major infrastructural resources namely, berths, yards and gates. Theadvertised capacity is constrained by the least of the capacities of the three resources. While a lot ofattention has been paid to optimizing berth and yard capacities, not much attention has been given toanalyzing the gate capacity. The gates are a key node between the land-side and sea-side operations in anocean-to-cities value chain. The gate system under consideration, located at an important port in an Asiancity, is a multi-class parallel queuing system with non-homogeneous Poisson arrivals. It is hard to obtaina closed form analytic approach for …

Policy Gradient With Value Function Approximation For Collective Multiagent Planning, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Decentralized (PO)MDPs provide an expressive framework for sequential decision making in a multiagent system. Given their computational complexity, recent research has focused on tractable yet practical subclasses of Dec-POMDPs. We address such a subclass called CDec-POMDP where the collective behavior of a population of agents affects the joint-reward and environment dynamics. Our main contribution is an actor-critic (AC) reinforcement learning method for optimizing CDec-POMDP policies. Vanilla AC has slow convergence for larger problems. To address this, we show how a particular decomposition of the approximate action-value function over agents leads to effective updates, and also derive a new way to …

Improving Service Level Of Free-Floating Bike Sharing Systems, Aritra Pal

USF Tampa Graduate Theses and Dissertations

Bike Sharing is a sustainable mode of urban mobility, not only for regular commuters but also for casual users and tourists. Free-floating bike sharing (FFBS) is an innovative bike sharing model, which saves on start-up cost, prevents bike theft, and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. Efficient management of a FFBS requires: 1) analyzing its mobility patterns and spatio-temporal imbalance of supply and demand of bikes, 2) developing strategies to mitigate such imbalances, and 3) understanding the causes of a bike getting damaged and developing strategies to minimize them. All of these …

Design And Analysis Of A Lean Manufacturing Laboratory Layout, Abdoalrahman M. Hakami

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science Morehead State University in partial fulfillment of the requirements for the Degree of Master of Science by Abdoalrahman M. Hakami on November 10, 2017.

Virtual Commissioning For Industrial Automation, Saihiranmitra Mudiki

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Saihiranmitra Mudiki on November 7, 2017.

A Decision Support Tool For Building Integrated Renewable Energy Microgrids Connected To A Smart Grid, Damilola A. Asaleye, Michael D. Murphy, Michael Breen

Publications

The objective of this study was to create a tool that will enable renewable energy microgrid (REμG) facility users to make informed decisions on the utilization of electrical power output from a building integrated REμG connected to a smart grid. A decision support tool for renewable energy microgrids (DSTREM) capable of predicting photovoltaic array and wind turbine power outputs was developed. The tool simulated users’ daily electricity consumption costs, avoided CO₂ emissions and incurred monetary income relative to the usage of the building integrated REμG connected to the national electricity smart grid. DSTREM forecasted climate variables, which were used …

Chaotic Behavior In High-Gain Interleaved Dc-Dc Converters, Ahmad Alzahrani, Pourya Shamsi, Mehdi Ferdowsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, chaotic behavior in high gain dc-dc converters with current mode control is explored. The dc-dc converters exhibit some chaotic behavior because they contain switches. Moreover, in power electronics (circuits with more passive elements), the dynamics become rich in nonlinearity and become difficult to capture with linear analytical models. Therefore, studying modeling approaches and analysis methods is required. Most of the high-gain dc-dc boost converters cannot be controlled with only voltage mode control due to the presence of right half plane zero that narrows down the stability region. Therefore, the need of current mode control is necessary to …

Classification Of Rest And Active Periods In Actigraphy Data Using Pca, Isaac W. Muns, Yogesh Lad, Ivan G. Guardiola, Matthew S. Thimgan

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper we highlight a clustering algorithm for the purpose of identifying sleep and wake periods directly from actigraphy signals. The paper makes use of statistical Principal Component Analysis to identify periods of rest and activity. The aim of the proposed methodology is to develop a quick and efficient method to determine the sleep duration of an individual. In addition, a robust method that can identify sleep periods in the accelerometer data when duration, time of day varies by individual. A selected group of 10 individual's sensor data consisting of actigraphy from an accelerometer (3-axis), near body temperature, and …

Energy Consumption Modeling Of Stereolithography-Based Additive Manufacturing Toward Environmental Sustainability, Yiran Yang, Lin Li, Yayue Pan, Zeyi Sun

Engineering Management and Systems Engineering Faculty Research & Creative Works

Additive manufacturing (AM), also referred as three-dimensional printing or rapid prototyping, has been implemented in various areas as one of the most promising new manufacturing technologies in the past three decades. In addition to the growing public interest in developing AM into a potential mainstream manufacturing approach, increasing concerns on environmental sustainability, especially on energy consumption, have been presented. To date, research efforts have been dedicated to quantitatively measuring and analyzing the energy consumption of AM processes. Such efforts only covered partial types of AM processes and explored inadequate factors that might influence the energy consumption. In addition, energy consumption …

Reward/Penalty Design In Demand Response For Mitigating Overgeneration Considering The Benefits From Both Manufacturers And Utility Company, Md Monirul Islam, Zeyi Sun, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The high penetration of renewable sources in electricity grid has led to significant economic, environmental, and societal benefits. However, one major side effect, overgeneration, due to the uncontrollable property of renewable sources has also emerged, which becomes one of the major challenges that impedes the further large-scale adoption of renewable technology. Electricity demand response is an effective tool that can balance the supply and demand of the electricity throughout the grid. In this paper, we focus on the design of reward/penalty mechanism for the demand response programs aiming to mitigate the overgeneration. The benefits for both manufacturers and utility companies …

A General Algorithm For Assessing Product Architecture Performance Considering Architecture Extension In Cyber Manufacturing, Md Monirul Islam, Zeyi Sun, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In modern manufacturing, the product architecture design options are usually restricted to those that can be produced with 100% confidence using those proven technologies to satisfy the existing customer requirement. As a result, the inefficiencies of architecture design are considerable due to such limitations. This issue is of particular interests in cyber manufacturing when exploring the tradeoff between generality and feasibility in product design and manufacturing. It can be expected that the improvement and extension of the existing product architecture may be required to meet new customer requirement when new technologies become available. An effective system performance assessment algorithm is …

Analysis Of Autonomous Unmanned Aerial Systems Based On Operational Scenarios Using Value Modelling, Akash Vidyadharan, Robert Philpott Iii, Benjamin J. Kwasa, Christina L. Bloebaum

Engineering Management and Systems Engineering Faculty Research & Creative Works

In recent years, the use of UAS (Unmanned Aerial Systems) has moved beyond the realm of military operations and has made its way into the hands of consumers and commercial industries. Although the applications of UAS in commercial industries are virtually endless, there are many issues regarding their operations that need to be considered before these valuable pieces of equipment are allowed for widespread civil use. Currently, UAS operations in the public domain are guided and controlled by the FAA Part 107 rules after overwhelming public pressure caused by the earlier 333 exemption. In order to approach such larger issues, …

An Optimal Milk Production Model Selection And Configuration System For Dairy Cows, Fan Zhang

PhDs

Milk production forecasting in the dairy industry has been an independent research topic since the early 20th century. The accurate prediction of milk yield can benefit both the processor (creameries) and the producer (dairy farmer) through developing short-term production schedules, planning long-term road maps, facilitating trade and investment in the dairy industry, improving business operations, optimising the existing infrastructure of the dairy industry, and reducing operating costs. Additionally, due to the innate characteristics of the milk production process, the accurate prediction of milk yield has been a challenging issue in the dairy industry. With the abolishment of EU milk quotas …

Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun

Computer Science Faculty Research & Creative Works

The utilization of onsite generation system with renewable sources in manufacturing plants plays a critical role in improving the resilience, enhancing the sustainability, and bettering the cost effectiveness for manufacturers. When designing the capacity of onsite generation system, the manufacturing energy load needs to be met and the cost for building and operating such onsite system with renewable sources are two critical factors need to be carefully quantified. Due to the randomness of machine failures and the variation of local weather, it is challenging to determine the energy load and onsite generation supply at different time periods. In this paper, …

Learning Curve Analysis Using Intensive Longitudinal And Cluster-Correlated Data, Xiao Zhong, Zeyi Sun, Haoyi Xiong, Neil Heffernan, Md Monirul Islam

Engineering Management and Systems Engineering Faculty Research & Creative Works

Intensive longitudinal and cluster-correlated data (ILCCD) can be generated in any situation where numerical or categorical characteristics of multiple individuals or study units are observed and measured at tens, hundreds, or thousands of occasions. The spacing of measurements in time for each individual can be regular or irregular, fixed or random, and the number of characteristics measured at each occasion may be few or many. Such data can also arise in situations involving continuous-time measurements of recurrent events. Generalized linear models (GLMs) are usually considered for the analysis of correlated non-normal data, while multivariate analysis of variance (MANOVA) is another …

Modeling And Simulation Of Microgrid, Ahmad Alzahrani, Mehdi Ferdowsi, Pourya Shamsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

Complex computer systems and electric power grids share many properties of how they behave and how they are structured. A microgrid is a smaller electric grid that contains several homes, energy storage units, and distributed generators. The main idea behind microgrids is the ability to work even if the main grid is not supplying power. That is, the energy storage unit and distributed generation will supply power in that case, and if there is excess in power production from renewable energy sources, it will go to the energy storage unit. Therefore, the electric grid becomes decentralized in terms of control …

Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi

Electrical and Computer Engineering Faculty Research & Creative Works

Predicting solar irradiance has been an important topic in renewable energy generation. Prediction improves the planning and operation of photovoltaic systems and yields many economic advantages for electric utilities. The irradiance can be predicted using statistical methods such as artificial neural networks (ANN), support vector machines (SVM), or autoregressive moving average (ARMA). However, they either lack accuracy because they cannot capture long-term dependency or cannot be used with big data because of the scalability. This paper presents a method to predict the solar irradiance using deep neural networks. Deep recurrent neural networks (DRNNs) add complexity to the model without specifying …

Open Access, Open Access, How Does Your Catalog Grow? With Selection, Access, And Usage All In A Virtual Row!, David W. Schuster, Susan J. Martin

Charleston Library Conference

Much of the open access (OA) focus and discussion has been on journals (think Glossa), but the open access monograph has come fully into its own. University and scholarly publishers are providing high-quality books, often in areas that rely on long-form scholarship. However, open access monographs presented a challenge. How do they fit into the traditional models of selection, acquisition, cataloging, and tracking usage?

In the spring of 2016, Texas Woman’s University Libraries created a simple workflow to make open access monographs accessible through the libraries’ discovery layer using Google Sheets to track the workflow and EZproxy to track usage.

Development Of A User-Friendly System Model And Simulation For An Amateur Liquid-Fueled Rocket, Daniel Corey, Thomas Bennett, Brendan Luke, James Biaglow

Von Braun Symposium Student Posters

No abstract provided.

Diagnosing Failures In Complex Engineered Systems, Jalyn Gariepy

Von Braun Symposium Student Posters

No abstract provided.

Evaluating Benefits Of Sysml In Creating Value Models Using Nasa's Nea Scout, Garima Bhatia

Von Braun Symposium Student Posters

No abstract provided.

Nasa Habitat: Framework For An Analysis Of Preference Communication, Giulia Palma

Von Braun Symposium Student Posters

No abstract provided.

Analytical Modeling Of Radiation Attenuation And Heat Deposition In Propellant For Nuclear Thermal Rockets, Alexander Aueron

Von Braun Symposium Student Posters

No abstract provided.

Expendable Rs-25 Engine Affordability Study, Adam Bower, Dale Thomas

Von Braun Symposium Student Posters

No abstract provided.

Where Mbse And Plm Fit Into The Digital Thread, Zach Thomas

Von Braun Symposium Student Posters

No abstract provided.

Underwater Object Tracking Strategy Via Multi-Scale Retinex And Partial Least Squares Analysis, Baochen Hao, Yue Zhu, Ruijie Chang, Rui Nian, Bo He, Lujie Cao, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Underwater Object Tracking is One of the Most Essential and Fundamental Tasks in Ocean Investigations Recent Years. in This Paper, We Try to Capture Multi-Scale Retinex (MSR) Model as Well as the Partial Least Square (Pls) Analysis for Underwater Object Tracking. We First Make Use of Multi-Scale Retinex Model to Evolve and Enhance the Partial Color Constancy from the Underwater Video Sequences, Which Could Provide a Versatile Automatic Strategy to Simultaneous Sharpening, Dynamic Range Compression and Color Rendition. the Partial Least Square Analysis is Further Taken to Capture the Trajectories of Underwater Objects by Learning a Set of Underwater Appearance …