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Profile Interview With Vincent Duffy, Apoorva Sulakhe 2017 Purdue University

Profile Interview With Vincent Duffy, Apoorva Sulakhe

Purdue Journal of Service-Learning and International Engagement

Dr. Vincent Duffy is an associate professor in the Department of Industrial Engineering at Purdue University holding a joint appointment with Agricultural and Biological Engineering. Duffy focuses on human factors engineering and ergonomic design. His interest in teaching began early when he was a teaching assistant for IE 386 at Purdue University while pursuing his master’s degree. As an industrial engineering master’s non-thesis student, Duffy realized he had a natural inclination toward teaching. This motivation, along with the support and mentorship of Ferdinand Leimkuhler, the head of the department, turned him toward the fi eld of research. He ...


Consumer-Adoption Modeling Of Distributed Solar Using An Agent-Based Approach, Anuj Mittal, Wanyu Huang, Caroline C. Krejci 2017 Iowa State University

Consumer-Adoption Modeling Of Distributed Solar Using An Agent-Based Approach, Anuj Mittal, Wanyu Huang, Caroline C. Krejci

Anuj Mittal

The electricity market in the U.S. is changing rapidly from a utility-scale centralized generation-distribution model to a more distributed and customer-sited energy model. Increasingly, residential consumers are showing interest in solar-based electricity, which has resulted in increased adoption of distributed solar on the rooftops of owner-occupied residences. However, limited accessibility of rooftop PV has led to equity concerns among policymakers, and utility companies face a decline in revenues as more residents adopt rooftop PV. In response to these issues, utility companies must consider providing alternative renewable energy options to their customers and incorporate consumer adoption modeling in their expansion ...


Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou 2017 Wright State University - Main Campus

Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts’ decision-making process. We investigated the effects of different noise stimuli on analysts’ performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in ...


Identification Of Reverse Engineering Candidates Utilizing Machine Learning And Aircraft Cannibalization Data, Marc Banghart 2017 Embry Riddle Aeronautical University

Identification Of Reverse Engineering Candidates Utilizing Machine Learning And Aircraft Cannibalization Data, Marc Banghart

International Journal of Aviation, Aeronautics, and Aerospace

As military aircraft continue to remain in service and age, cannibalization of parts is increasing. Proactive identification of parts that are at high risk for cannibalization will inform engineering processes such as reverse engineering, thus allowing potentially reducing lead time to develop new parts. The research objective was to develop a causal structure that can be used for prediction of when cannibalization actions may occur. Bayesian networks allow encoding of causality between various descriptive features given a data set. The method utilized a tabu search algorithm, identified the underlying causal structure and the associated node probabilities. The method is then ...


Creating A Team Tutor Using Gift, Stephen B. Gilbert, Anna Slavina, Michael C. Dorneich, Anne M. Sinatra, Desmond Bonner, Joan Johnston, Joseph Holub, Anastacia MacAllister, Eliot H. Winer 2017 Iowa State University

Creating A Team Tutor Using Gift, Stephen B. Gilbert, Anna Slavina, Michael C. Dorneich, Anne M. Sinatra, Desmond Bonner, Joan Johnston, Joseph Holub, Anastacia Macallister, Eliot H. Winer

Industrial and Manufacturing Systems Engineering Publications

With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of creating such systems. An ITS for teams must be able to assess complex interactions between team members (team skills) as well as the way they interact with the system itself (task skills). Assessing team skills can be difficult because they contain social ...


Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou 2017 Wright State University - Main Campus

Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou

Nasser H. Kashou

Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts’ decision-making process. We investigated the effects of different noise stimuli on analysts’ performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in ...


Adaptive Learning Pedagogy In Udl And Multi-Modal Training, Ziho Kang, Mattlyn R. Dragoo, Randa L. Shehab, Han Yuan, Lei Ding, Stephen G. West 2017 University of Oklahoma Norman Campus

Adaptive Learning Pedagogy In Udl And Multi-Modal Training, Ziho Kang, Mattlyn R. Dragoo, Randa L. Shehab, Han Yuan, Lei Ding, Stephen G. West

National Training Aircraft Symposium (NTAS)

Currently, most learning methods are based on classroom teaching through unidirectional communication using boards or slides. However, the Universal Design for Learning (UDL) asserts that the students can increase their performance if the instructors can provide the students with diversified information representation, expression, and engagement means. Although UDL minimizes the mismatch between the teaching and learning styles, we lack the detailed methods to implement the UDL and its associated multi-modal training methods in the context of air traffic control candidates and/or technical operators. We propose an approach that adapts the Index of Learning Styles (ILS) based on four categories ...


Pilot Performance With Advance Sensor Technlogies Considerations, Erin R. Groll, Nsikak Udo-Imeh, Steven Landry Dr. 2017 Purdue University

Pilot Performance With Advance Sensor Technlogies Considerations, Erin R. Groll, Nsikak Udo-Imeh, Steven Landry Dr.

The Summer Undergraduate Research Fellowship (SURF) Symposium

Research on human performance indicates people may discretely shift modes as the difficulty in tasks changes. These modes are referred to as “cognitive control modes.” Cognitive control modes are ways people operate and handle their process of thinking during a series of tasks. However, past work has been confined to subjective reports of these mode changes - objective markers in data of cognitive control modes, which should appear if these mode changes are truly discrete, have not be identified. This work will attempt to identify markers of cognitive control modes in data collected on pilots flying instrument approaches. Specifically, a simulated ...


Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico 2017 Purdue University

Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico

The Summer Undergraduate Research Fellowship (SURF) Symposium

Neuroimaging, particularly functional magnetic resonance imaging (fMRI), is a rapidly growing research area and has applications ranging from disease classification to understanding neural development. With new advancements in imaging technology, researchers must employ new techniques to accommodate the influx of high resolution data sets. Here, we replicate a new technique: connectome-based predictive modeling (CPM), which constructs a linear predictive model of brain connectivity and behavior. CPM’s advantages over classic machine learning techniques include its relative ease of implementation and transparency compared to “black box” opaqueness and complexity. Is this method efficient, powerful, and reliable in the prediction of behavioral ...


Simulation Modeling Approach For Evaluating A Solution Designed To Alleviate The Congestion Of Passenger Flow At The Composure Area Of Security Checkpoints, Maria Luisa Janer Rubio 2017 University of Arkansas, Fayetteville

Simulation Modeling Approach For Evaluating A Solution Designed To Alleviate The Congestion Of Passenger Flow At The Composure Area Of Security Checkpoints, Maria Luisa Janer Rubio

Theses and Dissertations

In a previous study, we found that replacing the exit roller of a security checkpoint lane for a continuously circulating conveyor could potentially increase the throughput of passengers by over 28% while maintaining the TSA security-waiting time limit (Janer and Rossetti 2016). This study intends to expand this previous effort by investigating the impact of this circulating conveyor on the secondary screening related processes. Leone and Liu (2011) found that imposing a limit on the x-ray screening time, and diverting any item exceeding this limit to secondary screening, could decrease the waiting time by 43%. Our objective is to verify ...


Essays In Measuring, Controlling, And Coordinating Supply Chain Inventory And Transportation Operations, Payam Parsa 2017 University of Arkansas, Fayetteville

Essays In Measuring, Controlling, And Coordinating Supply Chain Inventory And Transportation Operations, Payam Parsa

Theses and Dissertations

Supply chain collaboration programs, such as continuous replenishment program (CRP), is among the most popular supply chain management practices. CRP is an arrangement between two partners in a supply chain to share information on a regular basis for lowering logistics costs while maintaining or increasing service levels. CRP shifts the replenishment responsibility to the upstream partner to avoid the bullwhip effect across the supply chain. This dissertation aims to quantify, measure, and expand the benefits of CRP for the purpose of reducing logistics cost and improving customer service. The developed models in this dissertation are all applied in different case ...


Bringing Interpretability And Visualization With Artificial Neural Networks, Andrey Gritsenko 2017 University of Iowa

Bringing Interpretability And Visualization With Artificial Neural Networks, Andrey Gritsenko

Theses and Dissertations

Extreme Learning Machine (ELM) is a training algorithm for Single-Layer Feed-forward Neural Network (SLFN). The difference in theory of ELM from other training algorithms is in the existence of explicitly-given solution due to the immutability of initialed weights. In practice, ELMs achieve performance similar to that of other state-of-the-art training techniques, while taking much less time to train a model. Experiments show that the speedup of training ELM is up to the 5 orders of magnitude comparing to standard Error Back-propagation algorithm.

ELM is a recently discovered technique that has proved its efficiency in classic regression and classification tasks, including ...


Models And Methodologies To Address Emerging Needs In Network And Supply Chain Optimization, Forough Enayaty Ahangar 2017 University of Arkansas, Fayetteville

Models And Methodologies To Address Emerging Needs In Network And Supply Chain Optimization, Forough Enayaty Ahangar

Theses and Dissertations

In this dissertation, we model three different security scenarios and propose solution methodologies to address each problem.

Chapter 2 presents a large-scale optimization approach for solving a dynamic bi-level network interdiction problem (NIP) in which interdiction activities must be scheduled in order to minimize the cumulative maximum flow over a finite time horizon. A logic-based decomposition (LBD) approach is proposed that utilizes constraint programming to exploit the scheduling nature of this dynamic NIP. Chapter 3 considers a set of centers to which content (e.g., data or smuggled items), are assigned to ensure availability. An interdictor (e.g., border security ...


Personalized Decision Modeling For Intervention And Prevention Of Cancers, Fan Wang 2017 University of Arkansas, Fayetteville

Personalized Decision Modeling For Intervention And Prevention Of Cancers, Fan Wang

Theses and Dissertations

Personalized medicine has been utilized in all stages of cancer care in recent years, including the prevention, diagnosis, treatment and follow-up. Since prevention and early intervention are particularly crucial in reducing cancer mortalities, personalizing the corresponding strategies and decisions so as to provide the most appropriate or optimal medical services for different patients can greatly improve the current cancer control practices. This dissertation research performs an in-depth exploration of personalized decision modeling of cancer intervention and prevention problems. We investigate the patient-specific screening and vaccination strategies for breast cancer and the cancers related to human papillomavirus (HPV), representatively. Three popular ...


An Economic Analysis Of Residential Photovoltaic Systems With And Without Energy Storage, Rodney Moses Kizito 2017 University of Arkansas, Fayetteville

An Economic Analysis Of Residential Photovoltaic Systems With And Without Energy Storage, Rodney Moses Kizito

Theses and Dissertations

Residential photovoltaic (PV) systems serve as a source of electricity generation that is separate from the traditional utilities. Investor investment into residential PV systems provides several financial benefits such as federal tax credit incentives for installation, net metering credit from excess generated electricity added back to the grid, and savings in price per kilowatt-hour (kWh) from the PV system generation versus the increasing conventional utility price per kWh. As much benefit as stand-alone PV systems present, the incorporation of energy storage yields even greater benefits. Energy storage (ES) is capable of storing unused PV provided energy from daytime periods of ...


Knowledge Management Determinants Of Continuance Behavior: Evaluating The Air Force Knowledge Now Knowledge Management System, Eric Tucker 2017 University of Central Florida

Knowledge Management Determinants Of Continuance Behavior: Evaluating The Air Force Knowledge Now Knowledge Management System, Eric Tucker

Eric M. Tucker

Knowledge management (KM) encompasses the set of capabilities, processes, tools, and techniques for the most effective use of knowledge by an organization. The goal of KM is to improve the organization's ability to create, transfer, retain, and apply knowledge. Knowledge management is a goal that many organizations seek to achieve. Organizations apply their strategies, plans, and implementation to achieve KM. Organizations use technology to implement their KM strategy. For some, this approach has worked well; however, for others, the results have fallen short. KM shortcomings revolve around employees' infrequent use of the technology. This research seeks to understand what ...


Interaction Of Automation Visibility And Information Quality In Flight Deck Information Automation View Document, Michael C. Dorneich, Rachel Dudley, Emmanuel Letsu-Dake, William Rogers, Stephen D. Whitlow, Michael Dillard, Erik Nelson 2017 Iowa State University

Interaction Of Automation Visibility And Information Quality In Flight Deck Information Automation View Document, Michael C. Dorneich, Rachel Dudley, Emmanuel Letsu-Dake, William Rogers, Stephen D. Whitlow, Michael Dillard, Erik Nelson

Industrial and Manufacturing Systems Engineering Publications

An empirical study evaluated key human factors issues related to automation visibility and information quality, based on a refined definition of information automation. Next-generation air transportation system operational concepts will dramatically affect the types and amount of information available on flight decks. Information automation systems collect, process, and present information to support pilot tasks and awareness. The definition of flight deck information automation was refined to differentiate it from other types of automation. Pilots interacted with an example information automation system to investigate the premise that automation visibility will have an impact on the ability of pilots to detect problems ...


Virtual Operator Models For Off-Highway Machine Virtual Prototyping, Yu Du, Michael C. Dorneich, Brian L. Steward 2017 Iowa State University

Virtual Operator Models For Off-Highway Machine Virtual Prototyping, Yu Du, Michael C. Dorneich, Brian L. Steward

Agricultural and Biosystems Engineering Conference Proceedings and Presentations

Increasing demands on the world‘s resources require the design of off-highway machines that provide greater functionality and productivity along with greater efficiency. Model-based or virtual design provides a means for achieving these design improvements with reduced time and costs. However, virtual design is often limited by the fidelity with which human operators are modeled. A greater understanding of how highly skilled operators obtain high machine performance and productivity can inform machine development and advance agricultural and construction machine automation technology. This research investigated how machine operator expertise, strategies, and decision-making can be integrated into operator models that simulate authentic ...


Utilizing Six Sigma Methodology For Training Undergraduate Student For Conducting Global Field Research, Kritika Chopra, Shweta Chopra, Chad Laux 2017 Iowa State University

Utilizing Six Sigma Methodology For Training Undergraduate Student For Conducting Global Field Research, Kritika Chopra, Shweta Chopra, Chad Laux

Shweta Chopra

With the increase in demand for the global research, scholars in engineering and technology discipline do not hesitate in taking up global opportunity for conducting research. Training the next generation for such international research opportunity is key and involving undergraduate students’ beyond study abroad is important.


One-Sample Bayes Inference For Symmetric Distributions Of 3-D Rotations, Yu Qiu, Danial J. Nordman, Stephen B. Vardeman 2017 Iowa State University

One-Sample Bayes Inference For Symmetric Distributions Of 3-D Rotations, Yu Qiu, Danial J. Nordman, Stephen B. Vardeman

Stephen B. Vardeman

A variety of existing symmetric parametric models for 3-D rotations found in both statistical and materials science literatures are considered from the point of view of the “uniform-axis-random-spin” (UARS) construction. One-sample Bayes methods for non-informative priors are provided for all of these models and attractive frequentist properties for corresponding Bayes inference on the model parameters are confirmed. Taken together with earlier work, the broad efficacy of non-informative Bayes inference for symmetric distributions on 3-D rotations is conclusively demonstrated.


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