Operations Research, Systems Engineering and Industrial Engineering Commons^™

Extrinsic And Intrinsic Control Of Integrative Processes In Neural Systems, Anirban Nandi

McKelvey School of Engineering Theses & Dissertations

At the simplest dynamical level, neurons can be understood as integrators. That is, neurons accumulate excitation from afferent neurons until, eventually, a threshold is reached and they produce a spike. Here, we consider the control of integrative processes in neural circuits in two contexts. First, we consider the problem of extrinsic neurocontrol, or modulating the spiking activity of neural circuits using stimulation, as is desired in a wide range of neural engineering applications. From a control-theoretic standpoint, such a problem presents several interesting nuances, including discontinuity in the dynamics due to the spiking process, and the technological limitations associated with …

Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani

Psychology Faculty Articles and Research

The emerging technology of connected vehicles generates a vast amount of data that could be used to enhance roadway safety. In this paper, we focused on safety applications of a real field connected vehicle data on a horizontal curve. The database contains connected vehicle data that were collected on public roads in Ann Arbor, Michigan with instrumented vehicles. Horizontal curve negotiations are associated with a great number of accidents, which are mainly attributed to driving errors. Aggressive/risky driving is a contributing factor to the high rate of crashes on horizontal curves. Using basic safety message data in connected vehicle data …

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 …

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 …

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 …

Answering Food Insecurity: Serving The Community With Food And Knowledge Using Technology, Courtney Simpson

Purdue Journal of Service-Learning and International Engagement

The courses of Tech120, CGT110, and ENGT 180/181 and Red Gold at Purdue collaborated to design a robot that would plant and water a garden for a local community charter school. The students centered the project on the users’ needs for fresh food, nutrition education, and early exposure to STEM for children. The school, Anderson Preparatory Academy (APA), is comprised of many children who come from low-income families and are in the free or reduced lunch program. Inspired from “Farm Bot,” a similar system that allows for almost hands-free gardening, the “Boiler Bot” is designed to be scalable so children …

Quantitative Analysis Of Regenerative Energy In Electric Rail Traction Systems, Mahmoud Saleh, Oindrilla Dutta, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper aims at determining the influential factors affecting regenerative braking energy in DC rail transit systems. This has been achieved by quantitatively evaluating the dependence of regenerative energy on various parameters, such as vehicle dynamics, train scheduling, ground inclination and efficiency of the electrical devices. The recuperated power and energy have been presented by a mathematical model, comprising of a set of empirical forms, which allows for thorough analysis. A detailed simulation model of a typical DC-traction system has been developed to validate the developed empirical forms. The results verified the validity of the proposed mathematical model, and demonstrated …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco

Libraries' Newsletters

No abstract provided.

Numerical Methods For Nonlinear Optimal Control Problems And Their Applications In Indoor Climate Control, Runxin He

McKelvey School of Engineering Theses & Dissertations

Efficiency, comfort, and convenience are three major aspects in the design of control systems for residential Heating, Ventilation, and Air Conditioning (HVAC) units. In this dissertation, we study optimization-based algorithms for HVAC control that minimizes energy consumption while maintaining a desired temperature, or even human comfort in a room. Our algorithm uses a Computer Fluid Dynamics (CFD) model, mathematically formulated using Partial Differential Equations (PDEs), to describe the interactions between temperature, pressure, and air flow. Our model allows us to naturally formulate problems such as controlling the temperature of a small region of interest within a room, or to control …

Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung

Morris Chang

Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article is part of …

A Multiperiod Generalized Network Flow Model Of The U.S. Integrated Energy System: Part I—Model Description, Ana Quelhas, Esteban Gil, James D. Mccalley, Sarah M. Ryan

James McCalley

This paper is the first of a two-part paper presenting a multiperiod generalized network flow model of the integrated energy system in the United States. Part I describes the modeling approach used to evaluate the economic efficiencies of the system-wide energy flows, from the coal and natural gas suppliers to the electric load centers. Under the proposed problem formulation, fuel supply and electricity demand nodes are connected via a transportation network, and the model is solved for the most efficient allocation of quantities and corresponding prices. The methodology includes physical, economic, and environmental aspects that characterize the different networks. Part …

An Exact Analysis For Four-Order Acousto-Optic Bragg Diffraction Which Incorporates Both Incident Light Angle And Sound Frequency Dependencies, Adeyinka Sunday Ademola

Electrical Engineering Theses

This thesis extends the prior work which produced an exact solution to the four-order acousto-optic (AO) Bragg cell with assumed fixed center frequency and with exact Bragg angle incident light. The extension predicts the model that incorporates the dependencies of both the input angle of light and the sound frequency. Specifically, a generalized 4^th order linear differential equation (DE), is developed from a simultaneous analysis of four coupled AO system of DEs. Through standard methods, the characteristic roots, which requires solving a quartic equation, is produced. Subsequently, a derived system of homogeneous solutions, which absorbs the roots obtained using …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

Predicting Solar Performance In A Contingency Environment To Meet Net-Zero Facility Power, Anthony D. Williams

Theses and Dissertations

The U.S. government is involved in contingency operations all over the world and these operations require operational support and sustainment in these locations; this includes the reliable delivery of power to base infrastructure. The traditional means of delivering this support requirement in austere environments has been the use of diesel-power generation that has an extensive logistical and economic tail. The research sought out contingency solar applications that may be implemented and operated to offset the facility demand loads in the location to achieve net-zero power. This research explores the technical feasibility of a deployable photovoltaic microgrid to deliver power to …

Optimal Bidding Strategy For A Strategic Power Producer Using Mixed Integer Programming, Sayed Abdullah Sadat

USF Tampa Graduate Theses and Dissertations

The thesis focuses on a mixed integer linear programming (MILP) formulation for a bi-level mathematical program with equilibrium constraints (MPEC) considering chance constraints. The particular MPEC problem relates to a power producer’s bidding strategy: maximize its total benefit through determining bidding price and bidding power output while considering an electricity pool’s operation and guessing the rival producer’s bidding price. The entire decision-making process can be described by a bi-level optimization problem. The contribution of our thesis is the MILP formulation of this problem considering the use of chance constrained mathematical program for handling the uncertainties.

First, the lower-level poor operation …

Image Data Mining For Quality Control Of Nanofiber Reinforced Piezoelectric Nanocomposites Based On Sem Images, Zhonghua Hu

Open Access Theses & Dissertations

Recently, portable and wireless nano-scaled devices have been widely used in environmental monitoring, medical implants, defense technology, industrial safety, and personal electronics, such as the nanowire-based gas and chemical sensors and programmable nanowire circuit for nano-processors. There has been an increasing demand for high energy density capacitors that can be engineered for various applications in advanced devices. In it, piezoelectric nanofiber materials play critical role in producing new products. A piezo-ceramic polymer composite contains a polymer of high dielectric strength and high permittivity ceramic inclusions, making it well suited as a high energy density capacitor. Furthermore, the research shows that …

Sensitivity Analysis Method To Address User Disparities In The Analytic Hierarchy Process, Marie Ivanco, Gene Hou, Jennifer Michaeli

Mechanical & Aerospace Engineering Faculty Publications

Decision makers often face complex problems, which can seldom be addressed well without the use of structured analytical models. Mathematical models have been developed to streamline and facilitate decision making activities, and among these, the Analytic Hierarchy Process (AHP) constitutes one of the most utilized multi-criteria decision analysis methods. While AHP has been thoroughly researched and applied, the method still shows limitations in terms of addressing user profile disparities. A novel sensitivity analysis method based on local partial derivatives is presented here to address these limitations. This new methodology informs AHP users of which pairwise comparisons most impact the derived …

Experimental Investigation Of Reading Passive Uhf Tags In A Multi-Tag Environment, Yi Zhou

Theses and Dissertations--Mechanical Engineering

Recently, the Internet of things (IoT) has emerged as a promising solution for several industrial applications. One of the key components in IoT is passive radio frequency identification (RFID) tags which do not require a power source for operations. Specifically, ultra-high frequency (UHF) tags are studied in this paper. However, due to factors such as tag-to-tag interference and inaccurate localization, RFID tags that are closely spaced together are difficult to detect and program accurately with unique identifiers. This thesis investigates several factors that affect the ability to encode a specific tag with unique information in the presence of other tags, …

Target Read Operation Of Passive Ultra High Frequency Rfid Tag In A Multiple Tags Environment, Zi Qin Phua

Theses and Dissertations--Mechanical Engineering

Passive ultra-high frequency (UHF) radio frequency Identification (RFID) has emerged as a promising solution for many industrial applications. Passive UHF systems are relatively inexpensive to implement and monitor, as no line of sight is required for the communication. There are several advantages to using a passive RFID system. For example, no internal power source is required to activate the tags, and lower labor costs and efficient multitasking operations are expected in a long term scenario. However, due to factors such as tag-to-tag interference and inaccurate localization, RFID tags that are closely spaced together are difficult to detect and program accurately …