Engineering Commons^™

Supporting Text And Data Analysis Across Campus From The Academic Library, Amy Kirchhoff, Hejin Shin Phd

Digital Initiatives Symposium

The ability to comprehend and communicate with text-based data is essential to future success in academics and employment, as evidenced in a recent survey from Bloomberg Research Services which shows that nearly 97% of survey respondents now use data analytics in their companies and 58% consider data and text mining a business analytics tool (https://www.sas.com/content/dam/SAS/bp_de/doc/studie/ba-st-the-current-state-of-business-analytics-2317022.pdf). This has fueled a substantial growth in text analysis research (involving the use of technology to analyze un- and semi-structured text data for valuable insights, trends, and patterns) across disciplines and a corresponding demand on academic libraries to support text analysis pedagogy and text analysis …

Fully Coupled Fluid Structure Interaction Simulation Of Bioprosthetic Heart Valves: A Numerical And Experimental Analysis, Masod Sadipour

Electronic Theses and Dissertations

Aortic stenosis impacts approximately 7% of the global population. In the past decade, the role of computational modeling has been becoming considerably important in the design of BHVs. To obtain reliable solutions in computational modeling, it is essential to consider accurate properties of bioprosthetic heart valves (BHVs), such as density and mechanical properties. Previous computational studies assumed (bovine pericardium) BP used in BHVs density was comparable to water or blood. Yet, BP is subjected to multiple treatments like fixation and anti-calcification. In Chapter 2, I measured BP density and its effect on BHV leaflet stress and strain. In the second …

Analyzing The Impact Of Automation On Employment In Different Us Regions: A Data-Driven Approach, Thejaas Balasubramanian

Electronic Theses, Projects, and Dissertations

Automation is transforming the US workforce with the increasing prevalence of technologies like robotics, artificial intelligence, and machine learning. As a result, it is essential to understand how this shift will impact the labor market and prepare for its effects. This culminating experience project aimed to examine the influence of computerization on jobs in the United States and answer the following research questions: Q1. What factors affect how likely different jobs will be automated? Q2. What are the possible effects of automation on the US workforce across states and industries? Q3. What are the meaningful predictors of the likelihood of …

The Effectiveness Of Visualization Techniques For Supporting Decision-Making, Cansu Yalim, Holly A. H. Handley

Modeling, Simulation and Visualization Student Capstone Conference

Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique's strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization …

Agen/Bsen 112 Final Project: Moving And Temperament Of Cattle, Elly Vo, Taetum Baxa, Ved Patel, Brady Giles, Tami M. Brown-Brandl, Rossana Villa-Rojas

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Cattle movement and weather may affect the body temperature of cows which in turn affects their natural behavior and can influence their metabolism. Cattle take several days to resume their normal eating patterns after being overheated, and that can affect dairy production. This project was assigned to study the effect of temperament (calm vs excitable) and evaporative cooling on the body temperature of moving animals to optimize the environmental conditions around the cattle and consequently, dairy production.

The project began with processing of a data set from Dr. Tami Brown-Brandl who was the client/adviser for the group. The data contained …

Updating The Bridge Construction Cost Database, Rachel Catchings, Ying Li, Ryan Griffith, Sudhir Palle

Kentucky Transportation Center Research Report

Adopting a comprehensive suite of methods to track, analyze, and maintain data on bridge construction costs can help state transportation agencies identify and implement strategies to mitigate the influence of factors which escalate project costs. This report discusses how the Kentucky Transportation Cabinet (KYTC) should approach updating, maintaining, and analyzing its bridge construction cost data. Based on a review of practices introduced at other agencies and interviews with public and private industry stakeholders, the report catalogues practical strategies for improving estimating procedures and tracking cost data as well as the most important cost drivers of bridge construction. Analysis of KYTC …

State Prediction Of Poverty Alleviation Objects Based On Hmm And Multidimensional Data, Jun He, Sunyan Hong, Yifang Zhou, Shikai Shen, Muquan Zou

Journal of System Simulation

Abstract: In order to solve the problems of inaccurate prediction of poverty, poverty reduction and poverty returen, and the difficulty in identifying the key factors affecting the state transition, 8 key features and 22 observed states are extracted from the poverty reduction basic data and multi-industry data. The relationship between observed state and implied state is constructed, and the hidden markov model (HMM) of poverty alleviation is established. Data of a deep poverty county for three consecutive years are used as samples for parameter training, test experiment and result verification. The results show that the method has a strong …

How Blockchain Solutions Enable Better Decision Making Through Blockchain Analytics, Sammy Ter Haar

Information Systems Undergraduate Honors Theses

Since the founding of computers, data scientists have been able to engineer devices that increase individuals’ opportunities to communicate with each other. In the 1990s, the internet took over with many people not understanding its utility. Flash forward 30 years, and we cannot live without our connection to the internet. The internet of information is what we called early adopters with individuals posting blogs for others to read, this was known as Web 1.0. As we progress, platforms became social allowing individuals in different areas to communicate and engage with each other, this was known as Web 2.0. As Dr. …

Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu

Big Data Mining and Analytics

With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, …

Descriptive Statistical Analysis Of Experimental Data For Wettability Alteration With Surfactants In Carbonate Reservoirs, Ya Yao, Mingzhen Wei, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surfactants have been the widely used agents to alter the wettability of carbonate rocks to more water-wet and enhanced oil recovery (EOR). As one of major EOR methods, an effective surfactant huff-puff application design requires comprehensive guidelines about where, how, and when this method could be applied. In order to construct such guidelines, a dataset including 338 effective surfactant imbibition tests is established by collecting information from nearly 50 publications. Based on this dataset, descriptive statistical analysis methods are used to conduct data analysis, including three main parts. The first part establishes the application guidelines for surfactant huff-puff treatments which …

The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and …

A Longitudinal Analysis Of Pathways To Computing Careers: Defining Broadening Participation In Computing (Bpc) Success With A Rearview Lens, Mercy Jaiyeola

Theses and Dissertations

Efforts to increase the participation of groups historically underrepresented in computing studies, and in the computing workforce, are well documented. It is a national effort with funding from a variety of sources being allocated to research in broadening participation in computing (BPC). Many of the BPC efforts are funded by the National Science Foundation (NSF) but as existing literature shows, the growth in representation of traditionally underrepresented minorities and women is not commensurate to the efforts and resources that have been directed toward this aim.

Instead of attempting to tackle the barriers to increasing representation, this dissertation research tackles the …

A Machine Learning Approach To Understanding Emerging Markets, Namita Balani

Graduate Theses and Dissertations

Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …

Intermittent Dynamics Of Dense Particulate Matter, Chao Cheng

Dissertations

Granular particle systems are scattered around the universe, and they can behave like solids when there exist strong force-bearing networks, so that the granular system can resist certain stress without deformation. When such a network is not present, particles yield to small stress and behave like a fluid. A wide range of systems exhibit intermittent dynamics as they are slowly loaded, with different dynamical regimes governing many industrial and natural phenomena. While a significant amount of research on exploring intermittent dynamics of granular systems has been carried out, not much is known about the connection between particle-scale response and the …

Deploying And Analyzing Air Quality Sensors In Mongolian Gers, Lehi Sttenio Alcantara

Theses and Dissertations

The purpose of this research is to develop best practices for deploying air quality sensors in a remote location such as Mongolia. I discussed the architecture and design constraints when collecting remote air quality sensors data, the challenges that emerge while implementing a sensor-based network in a remote location such as Mongolia. The tradeoffs of using different architectures are described. I observed the usage of electrical heaters in modified gers in remote locations and conclude how effective they are in reducing PM2.5 levels by analyzing air quality data and go through the process of cleaning up the data and removing …

Deploying And Analyzing Air Quality Sensors In Mongolian Gers, Lehi Alcantara

ScholarsArchive Data

This is work done for a thesis that would be way too long to attach to the thesis document. It contains code, spreadsheets, data.

Theoretical Analysis Of Experimental Data Of Sodium Diffusion In Oxidized Molybdenum Thin Films, Orlando Ayala, Benjamin Belfore, Tasnuva Ashrafee, John Akwari, Grace Rajan, Shankar Karki, Deewakar Poudel, Sylvain Marsillac

Engineering Technology Faculty Publications

In this work, the diffusion process of sodium (Na) in molybdenum (Mo) thin films while it was deposited on soda lime glass (SLG) was studied. A small amount of oxygen was present in the chamber while the direct-current (DC) magnetron sputtering was used for the deposition. The substrate temperatures were varied to observe its effect. Such molybdenum films, with or without oxidations, are often used in thin film solar cells, either as back contact or as hole transport layers. Secondary ion mass spectrometry (SIMS) was used to quantify the concentration of the species. A grain diffusion mechanistic model incorporating the …

Assessment Of Cable Length Limit For Effective Protection By Z-Source Circuit Breakers In Dc Power Networks, Ruiyun Fu, Sagar Bhatta, Joseph M. Keller, Yucheng Zhang

Electrical & Computer Engineering Faculty Publications

This paper introduces groundbreaking research on how to assess the Cable Length Limit (CLL) to ensure effective protection by Z-source Circuit Breakers (ZCBs) in DC power networks. It has been revealed that the line parameters of power cables have a significant impact on the cutoff performance of ZCBs. The question of assessing the CLL has been raised as an unsolved problem. In this paper, a method of CLL assessment is proposed based on physical models and simulation tests. To verify the proposed method, two studies were performed to assess the Cable Length Limits depending on fault levels and power delivery …

A Deep Machine Learning Approach For Predicting Freeway Work Zone Delay Using Big Data, Abdullah Shabarek

Dissertations

The introduction of deep learning and big data analytics may significantly elevate the performance of traffic speed prediction. Work zones become one of the most critical factors causing congestion impact, which reduces the mobility as well as traffic safety. A comprehensive literature review on existing work zone delay prediction models (i.e., parametric, simulation and non-parametric models) is conducted in this research. The research shows the limitations of each model. Moreover, most previous modeling approaches did not consider user delay for connected freeways when predicting traffic speed under work zone conditions. This research proposes Deep Artificial Neural Network (Deep ANN) and …

Forecasting Of Short-Term Power Load Of Secrpso-Svm Based On Data-Driven, Hairong Sun, Bixia Xie, Tian Yao, Zhuoqun Li

Journal of System Simulation

Abstract: For the parameter selection of support vector machine in modeling, a particle swarm optimization algorithm based on second-order oscillation and repulsion factor was proposed to optimize the parameter of SVM. The algorithm employed the nonlinear decreasing weight to balance the global and local search ability. Second-order oscillation factor could maintain the population diversity. The repulsion factor was introduced to make the swarm even distribution in search space, which could avoid local optimum. For the complex characteristics of nonlinearity, time-varying and multifactorial of electric power load, a support vector machine forecasting model based on data was proposed, and the influence …

Reconstitution Efficiency On Elution Process, Brandon Winter, Landon Beachy, Samantha Stejskal, Zachary Rice

Scholar Week 2016 - present

Our group is presenting on the Reconstitution Efficiency on Elution Process for MilliporeSigma. The process that we are working with is the mixing of BAAP (Bovine Albumin Acetone Powder) into reverse osmosis water. This process is the first step of many in the making of medical test kits, of which include HIV/AID, strep throat, and pregnancy tests. Our initial task was to reduce the mixing time by 50%, however after further exploration of the problem, a more stable and consistent process turned into our primary goal and a significant reduction in time became a secondary goal. Initially, we were using …

Securing The Emerging Technologies Of Autonomous And Connected Vehicles, Shahab Tayeb, Matin Pirouz

Mineta Transportation Institute

The Internet of Vehicles (IoV) aims to establish a network of autonomous and connected vehicles that communicate with one another through facilitation led by road-side units (RSUs) and a central trust authority (TA). Messages must be efficiently and securely disseminated to conserve resources and preserve network security. Currently, research in this area lacks consensus about security schemes and methods of disseminating messages. Furthermore, a current deficiency of information regarding resource optimization prevents further efficient development of this network. This paper takes an interdisciplinary approach to these issues by merging both cybersecurity and data science to optimize and secure the network. …

A Data Analysis Of Immiscible Carbon Dioxide Injection Applications For Enhanced Oil Recovery Based On An Updated Database, Sherif Fakher, Abdulmohsin Imqam

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Carbon dioxide (CO₂) injection is an enhanced oil recovery technique used worldwide to increase oil recovery from hydrocarbon reservoirs. Immiscible CO₂ injection involves injecting the CO₂ into the reservoir at a pressure below which it will become miscible in the oil. Even though immiscible CO₂ injection has been applied extensively, very little research has been conducted to provide a comprehensive understanding of the mechanism and the applications of immiscible CO₂ injection. This research performs an in-depth data analysis is performed based on more than 200 experiments and 20 field tests from more than 40 …

Algorithm Selection Framework: A Holistic Approach To The Algorithm Selection Problem, Marc W. Chalé

Theses and Dissertations

A holistic approach to the algorithm selection problem is presented. The “algorithm selection framework" uses a combination of user input and meta-data to streamline the algorithm selection for any data analysis task. The framework removes the conjecture of the common trial and error strategy and generates a preference ranked list of recommended analysis techniques. The framework is performed on nine analysis problems. Each of the recommended analysis techniques are implemented on the corresponding data sets. Algorithm performance is assessed using the primary metric of recall and the secondary metric of run time. In six of the problems, the recall of …

Social Media Based Algorithmic Clinical Decision Support Learning From Behavioral Predispositions, Radhika V. Medury

Doctoral Dissertations

Behavioral disorders are disabilities characterized by an individual’s mood, thinking, and social interactions. The commonality of behavioral disorders amongst the United States population has increased in the last few years, with an estimated 50% of all Americans diagnosed with a behavioral disorder at some point in their lifetime. AttentionDeficit/Hyperactivity Disorder is one such behavioral disorder that is a severe public health concern because of its high prevalence, incurable nature, significant impact on domestic life, and peer relationships. Symptomatically, in theory, ADHD is characterized by inattention, hyperactivity, and impulsivity. Access to providers who can offer diagnosis and treat the disorder varies …

Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …

Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell

Research Collection School Of Computing and Information Systems

Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation …

Twitter And Disasters: A Social Resilience Fingerprint, Benjamin A. Rachunok, Jackson B. Bennett, Roshanak Nateghi

Purdue University Libraries Open Access Publishing Fund

Understanding the resilience of a community facing a crisis event is critical to improving its adaptive capacity. Community resilience has been conceptualized as a function of the resilience of components of a community such as ecological, infrastructure, economic, and social systems, etc. In this paper, we introduce the concept of a “resilience fingerprint” and propose a multi-dimensional method for analyzing components of community resilience by leveraging existing definitions of community resilience with data from the social network Twitter. Twitter data from 14 events are analyzed and their resulting resilience fingerprints computed. We compare the fingerprints between events and show that …

Applications Of Machine Learning Methods In Macroscopic Crash Analysis For Transportation Safety Management, Somaye Garmroudi Dovirani

Doctoral Dissertations

Transportation Safety Planning (TSP) is a statewide-scale tool and combines transportation planning processes with safety aims to increase safety and reduce transportation fatalities and injuries. Traffic safety, which continues to remain a critical issue worldwide, has led to a myriad of modeling techniques to improve analytical capabilities with respect to crash modeling and prediction. State and metropolitan transportation planning processes must be consistent with Strategic Highway Safety Plans. This research aims to identify models and methods to improve the ability to capture variables that have the most significant impact on traffic safety through crash prediction modeling. In order to achieve …

Designing An On-Demand Dynamic Crowdshipping Model And Evaluating Its Ability To Serve Local Retail Delivery In New York City, Shirin Najaf Abadi

Dissertations and Theses

Nowadays city mobility is challenging, mainly in populated metropolitan areas. Growing commute demands, increase in the number of for-hire vehicles, enormous escalation in several intra-city deliveries and limited infrastructure (road capacities), all contribute to mobility challenges. These challenges typically have significant impacts on residents’ quality-of-life particularly from an economic and environmental perspective. Decision-makers have to optimize transportation resources to minimize the system externalities (especially in large-scale metropolitan areas). This thesis focus on the intra-city mobility problems experienced by travelers (in the form of congestion and imbalance taxi resources) and businesses (in the form of last-mile delivery), while taking into consideration …