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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Forecasting Corn Yield With Machine Learning Ensembles, Mohsen Shahhosseini, Guiping Hu, Sotirios Archontoulis Jan 2020

Forecasting Corn Yield With Machine Learning Ensembles, Mohsen Shahhosseini, Guiping Hu, Sotirios Archontoulis

Industrial and Manufacturing Systems Engineering Publications

The emerge of new technologies to synthesize and analyze big data with high-performance computing, has increased our capacity to more accurately predict crop yields. Recent research has shown that Machine learning (ML) can provide reasonable predictions, faster, and with higher flexibility compared to simulation crop modeling. The earlier the prediction during the growing season the better, but this has not been thoroughly investigated as previous studies considered all data available to predict yields. This paper provides a machine learning based framework to forecast corn yields in three US Corn Belt states (Illinois, Indiana, and Iowa) considering complete and partial in-season ...


Evaluating Machine Learning Performance In Predicting Injury Severity In Agribusiness Industries, Fatemeh Davoudi Kakhki, Steven A. Freeman, Gretchen A. Mosher Aug 2019

Evaluating Machine Learning Performance In Predicting Injury Severity In Agribusiness Industries, Fatemeh Davoudi Kakhki, Steven A. Freeman, Gretchen A. Mosher

Agricultural and Biosystems Engineering Publications

Although machine learning methods have been used as an outcome prediction tool in many fields, their utilization in predicting incident outcome in occupational safety is relatively new. This study tests the performance of machine learning techniques in modeling and predicting occupational incidents severity with respect to accessible information of injured workers in agribusiness industries using workers’ compensation claims. More than 33,000 incidents within agribusiness industries in the Midwest of the United States for 2008–2016 were analyzed. The total cost of incidents was extracted and classified from workers’ compensation claims. Supervised machine learning algorithms for classification (support vector machines ...


Shoulder Muscular Fatigue From Static Posture Concurrently Reduces Cognitive Attentional Resources, Mitchell L. Stephenson, Alec G. Ostrander, Hamid Norasi, Michael C. Dorneich Jun 2019

Shoulder Muscular Fatigue From Static Posture Concurrently Reduces Cognitive Attentional Resources, Mitchell L. Stephenson, Alec G. Ostrander, Hamid Norasi, Michael C. Dorneich

Industrial and Manufacturing Systems Engineering Publications

Objective: The goal of this work is to determine whether muscular fatigue concurrently reduces cognitive attentional resources in technical tasks for healthy adults.

Background: Muscular fatigue is common in the workplace but often dissociated with cognitive performance. A corpus of literature demonstrates a link between muscular fatigue and cognitive function, but few investigations demonstrate that the instigation of the former degrades the latter in a way that may affect technical task completion. For example, laparoscopic surgery increases muscular fatigue, which may risk attentional capacity reduction and undermine surgical outcomes.

Method: A total of 26 healthy participants completed a dual-task cognitive ...


Crop Yield Prediction Using Deep Neural Networks, Saeed Khaki, Lizhi Wang May 2019

Crop Yield Prediction Using Deep Neural Networks, Saeed Khaki, Lizhi Wang

Industrial and Manufacturing Systems Engineering Publications

Crop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. Accurate yield prediction requires fundamental understanding of the functional relationship between yield and these interactive factors, and to reveal such relationship requires both comprehensive datasets and powerful algorithms. In the 2018 Syngenta Crop Challenge, Syngenta released several large datasets that recorded the genotype and yield performances of 2,267 maize hybrids planted in 2,247 locations between 2008 and 2016 and asked participants to predict the yield performance in 2017. As one of the winning teams, we designed a deep neural network ...


Evaluation Of An Intelligent Team Tutoring System For A Collaborative Two-Person Problem: Surveillance, Alec Ostrander, Desmond Bonner, Jamiahus Walton, Anna Slavina, Kaitlyn M. Ouverson, Adam Kohl, Stephen Gilbert, Michael Dorneich, Anne Sinatra, Eliot H. Winer Jan 2019

Evaluation Of An Intelligent Team Tutoring System For A Collaborative Two-Person Problem: Surveillance, Alec Ostrander, Desmond Bonner, Jamiahus Walton, Anna Slavina, Kaitlyn M. Ouverson, Adam Kohl, Stephen Gilbert, Michael Dorneich, Anne Sinatra, Eliot H. Winer

Industrial and Manufacturing Systems Engineering Publications

This paper describes the development and evaluation of an Intelligent Team Tutoring System (ITTS) for pairs of learners working collaboratively to monitor an area. In the Surveillance Team Tutor (STT), learners performed a surveillance task in a virtual environment, communicating to track hostile moving soldiers. This collaborative problem solving task required significant communication to achieve the common goal of perfect surveillance. In a pilot evaluation, 16 two-person teams performed the task within one of three feedback conditions (Individual, Team, or None) across four trials each. The STT used a unique approach to filtering feedback so that teams in both individual ...


Optimizing Ensemble Weights And Hyperparameters Of Machine Learning Models For Regression Problems, Mohsen Shahhosseini, Guiping Hu, Hieu Pham Jan 2019

Optimizing Ensemble Weights And Hyperparameters Of Machine Learning Models For Regression Problems, Mohsen Shahhosseini, Guiping Hu, Hieu Pham

Industrial and Manufacturing Systems Engineering Publications

Aggregating multiple learners through an ensemble of models aims to make better predictions by capturing the underlying distribution more accurately. Different ensembling methods, such as bagging, boosting and stacking/blending, have been studied and adopted extensively in research and practice. While bagging and boosting intend to reduce variance and bias, respectively, blending approaches target both by finding the optimal way to combine base learners to find the best trade-off between bias and variance. In blending, ensembles are created from weighted averages of multiple base learners. In this study, a systematic approach is proposed to find the optimal weights to create ...


Maize Yield And Nitrate Loss Prediction With Machine Learning Algorithms, Mohsen Shahhosseini, Rafael A. Martinez-Feria, Guiping Hu, Sotirios Archontoulis Jan 2019

Maize Yield And Nitrate Loss Prediction With Machine Learning Algorithms, Mohsen Shahhosseini, Rafael A. Martinez-Feria, Guiping Hu, Sotirios Archontoulis

Industrial and Manufacturing Systems Engineering Publications

Pre-season prediction of crop production outcomes such as grain yields and N losses can provide insights to stakeholders when making decisions. Simulation models can assist in scenario planning, but their use is limited because of data requirements and long run times. Thus, there is a need for more computationally expedient approaches to scale up predictions. We evaluated the potential of five machine learning (ML) algorithms as meta-models for a cropping systems simulator (APSIM) to inform future decision-support tool development. We asked: 1) How well do ML meta-models predict maize yield and N losses using pre-season information? 2) How many data ...


Evaluating The Effectiveness Of Graduated Stress Exposure In Virtual Spaceflight Hazard Training, Tor T. Finseth, Nir Keren, Michael C. Dorneich, Warren D. Franke, Clayton C. Anderson, Mack C. Shelley Ii Dec 2018

Evaluating The Effectiveness Of Graduated Stress Exposure In Virtual Spaceflight Hazard Training, Tor T. Finseth, Nir Keren, Michael C. Dorneich, Warren D. Franke, Clayton C. Anderson, Mack C. Shelley Ii

Industrial and Manufacturing Systems Engineering Publications

Psychological and physiological stress experienced by astronauts can pose risks to mission success. In clinical settings, gradually increasing stressors help patients develop resilience. It is unclear whether graduated stress exposure can affect responses to acute stressors during spaceflight. This study evaluated psychophysiological responses to potentially catastrophic spaceflight operation, with and without graduated stress exposure, using a virtual reality environment. Twenty healthy participants were tasked with locating a fire on a virtual International Space Station (VR-ISS). After orientation, the treatment group (n = 10) practiced searching for a fire while exposed to a low-level stressor (light smoke), while the control group (n ...


Conditions Under Which Adjustability Lowers The Cost Of A Robust Linear Program, Ali Haddad-Sisakht, Sarah M. Ryan Oct 2018

Conditions Under Which Adjustability Lowers The Cost Of A Robust Linear Program, Ali Haddad-Sisakht, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

The adjustable robust counterpart (ARC) of an uncertain linear program extends the robust counterpart (RC) by allowing some decision variables to adjust to the realizations of some uncertain parameters. The ARC may produce a less conservative and costly solution than the RC does but cases are known in which it does not. While the literature documents some examples of cost savings provided by adjustability (particularly affine adjustability), it is not straightforward to determine in advance whether they will materialize. The affine adjustable robust counterpart, while having a tractable structure, still may be much larger than the original problem. We establish ...


A Probabilistic Model To Estimate Visual Inspection Error For Metalcastings Given Different Training And Judgment Types, Environmental And Human Factors, And Percent Of Defects, Michelle M. Stallard-Voelker, Cameron A. Mackenzie, Frank E. Peters Jul 2018

A Probabilistic Model To Estimate Visual Inspection Error For Metalcastings Given Different Training And Judgment Types, Environmental And Human Factors, And Percent Of Defects, Michelle M. Stallard-Voelker, Cameron A. Mackenzie, Frank E. Peters

Industrial and Manufacturing Systems Engineering Publications

Current methods for visual inspection of cast metal surfaces are variable in both terms of repeatability and reproducibility. Because of this variation in the inspection methods, extra finishing operations are often prescribed; much of this is over processing in attempt to avoid rework or customer rejection. Additionally, defective castings may pass inspection and be delivered to the customer. Given the importance of ensuring that customers receive high-quality castings, this article analyzes and quantifies the probability of Type I and II errors, where a Type I error is a false alarm, and a Type II error misses a present defect. A ...


Impact Of Pavement Surface Condition On Roadway Departure Crash Risk In Iowa, Ahmad Alhasan, Inya Nlenanya, Omar G. Smadi, Cameron A. Mackenzie Jun 2018

Impact Of Pavement Surface Condition On Roadway Departure Crash Risk In Iowa, Ahmad Alhasan, Inya Nlenanya, Omar G. Smadi, Cameron A. Mackenzie

Industrial and Manufacturing Systems Engineering Publications

Safety performance is a crucial component of highway network performance evaluation. Besides their devastating impact on roadway users, traffic crashes lead to substantial economic losses on both personal and societal levels. Due to the complexity of crash events and the unique conditions in each country and state, empirical local calibration for the correlation between attributes of interest and the safety performance is always recommended. Limited studies have established a procedure to analyze the impact of pavement condition on traffic safety in a risk analysis scheme. This study presents a thorough analysis of some roadway departure crashes which occurred in Iowa ...


Energy And Carbon Footprint Reduction During Textile-Based Product Design And Manufacturing, S. H. Seyedmahmoudi, Karl R. Haapala, Kyoung-Yun Kim, Gül Kremer Jun 2018

Energy And Carbon Footprint Reduction During Textile-Based Product Design And Manufacturing, S. H. Seyedmahmoudi, Karl R. Haapala, Kyoung-Yun Kim, Gül Kremer

Industrial and Manufacturing Systems Engineering Publications

Due to concerns over non-renewable energy consumption and associated emissions, industry has sought methods and technologies to support energy efficiency practices and use of alternative energy during product manufacturing, use, and end-of-life. Efforts have been undertaken to more precisely calculate environmental metrics, such as energy consumption and carbon footprint, to support broader sustainable design activities. The work reported endeavours to integrate sustainability principles into the design of products, manufacturing processes, and relevant supply chain networks to assist decision makers. Two backpacks are evaluated to examine the influence of design choices on energy consumption and carbon footprint. The study system boundary ...


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 Jun 2018

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 ...


Modeling Expertise And Adaptability In Virtual Operator Models, Yu Du, Michael C. Dorneich, Brian L. Steward Jun 2018

Modeling Expertise And Adaptability In Virtual Operator Models, Yu Du, Michael C. Dorneich, Brian L. Steward

Industrial and Manufacturing Systems Engineering Publications

To advance construction machine design and testing, model-based design and virtual operator models (VOMs) can be used to explore machine designs virtually. However, current VOM efforts have been restricted to mimicking known trajectories, recorded from actual machine operations. Previous work developed a VOM to use in closed-loop simulation with an excavator model. To advance the utility of model-based machine testing, the fidelity of the VOM was enhanced along three lines: 1) representation of expert work cycle operation, 2) adaptation to changes in work site environment and 3) adaptation to changes when operating different machines. To represent expertise, work cycle task ...


Evaluating Human–Automation Etiquette Strategies To Mitigate User Frustration And Improve Learning In Affect-Aware Tutoring, Euijung Yang, Michael C. Dorneich May 2018

Evaluating Human–Automation Etiquette Strategies To Mitigate User Frustration And Improve Learning In Affect-Aware Tutoring, Euijung Yang, Michael C. Dorneich

Industrial and Manufacturing Systems Engineering Publications

Human–automation etiquette applies human–human etiquette conventions to human–computer interaction (HCI). The research described in this paper investigates how to mitigate user frustration and support student learning through changes in the style in which a computer tutor interacts with a learner. Frustration can significantly impact the quality of learning in tutoring. This study examined an approach to mitigate frustration through the use of different etiquette strategies to change the amount of imposition feedback placed on the learner. An experiment was conducted to explore how varying the interaction style of system feedback impacted aspects of the learning process. System ...


Finalist—2017 M&Som Practice-Based Research Competition—The Hurricane Decision Simulator: A Tool For Marine Forces In New Orleans To Practice Operations Management In Advance Of A Hurricane, Eva D. Regnier, Cameron A. Mackenzie May 2018

Finalist—2017 M&Som Practice-Based Research Competition—The Hurricane Decision Simulator: A Tool For Marine Forces In New Orleans To Practice Operations Management In Advance Of A Hurricane, Eva D. Regnier, Cameron A. Mackenzie

Industrial and Manufacturing Systems Engineering Publications

The U.S. Marine Forces Reserve (MFR) in New Orleans is frequently threatened by hurricanes. To protect the safety of personnel and their families while maintaining mission capability, the Commander must make timely decisions to set up an alternate headquarters and allow for an orderly evacuation. The MFR relies on forecasts from the National Hurricane Center, but these forecasts are uncertain, are updated frequently, and can be difficult to interpret in the context of the MFR's decision timeline. In addition, there are few opportunities to learn from experience.We developed the Hurricane Decision Simulator (HDS) to allow MFR personnel ...


Online Testing To Assess Performance Of Students In A Large Engineering Class, Vrishtee Rane, Cameron A. Mackenzie May 2018

Online Testing To Assess Performance Of Students In A Large Engineering Class, Vrishtee Rane, Cameron A. Mackenzie

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Fall 2017: Engineering Economic Analysis course •242 students: in-class and distance learning •New assessment procedure: Online testing modules •7 required online testing modules •2 bonus testing modules to earn an A •Semester grades determined completely by number of modules passed •Unlimited number of attempts for each testing module •Randomly chosen questions


A Multi-Stage Stochastic Programming For Lot-Sizing And Scheduling Under Demand Uncertainty, Zhengyang Hu, Guiping Hu May 2018

A Multi-Stage Stochastic Programming For Lot-Sizing And Scheduling Under Demand Uncertainty, Zhengyang Hu, Guiping Hu

Industrial and Manufacturing Systems Engineering Publications

A stochastic lot-sizing and scheduling problem with demand uncertainty is studied in this paper. Lot-sizing determines the batch size for each product and scheduling decides the sequence of production. A multi-stage stochastic programming model is developed to minimize overall system costs including production cost, setup cost, inventory cost and backlog cost. We aim to find the optimal production sequence and resource allocation decisions. Demand uncertainty is represented by scenario trees using moment matching technique. Scenario reduction is used to select scenarios with the best representation of original set. A case study based on a manufacturing company has been conducted to ...


Affect-Aware Adaptive Tutoring Based On Human–Automation Etiquette Strategies, Euijung Yang, Michael C. Dorneich Mar 2018

Affect-Aware Adaptive Tutoring Based On Human–Automation Etiquette Strategies, Euijung Yang, Michael C. Dorneich

Industrial and Manufacturing Systems Engineering Publications

Objective: We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human–automation etiquette strategies.

Background: Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students’ motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration.

Method: Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors ...


Biomass Supply Contract Pricing And Environmental Policy Analysis: A Simulation Approach, Shiyang Huang, Guiping Hu Feb 2018

Biomass Supply Contract Pricing And Environmental Policy Analysis: A Simulation Approach, Shiyang Huang, Guiping Hu

Industrial and Manufacturing Systems Engineering Publications

This paper proposes an agent-based simulation model to study the biomass supply contract pricing and policy making in the biofuel industry. In the proposed model, the agents include farmers and a biofuel producer. Farmers' decision-making is assumed to be profit driven, which is formulated as a mixed-integer optimization model, and the biofuel producer's pricing decision is represented with a linear equation with an objective to maximize profits. A case study based on Iowa has been developed to analyze the interactions between the stakeholders and assist determination of the optimal pricing equation for the biofuel producer. Simulation results show that ...


Moving Toward The Automation Of The Systematic Review Process: A Summary Of Discussions At The Second Meeting Of International Collaboration For The Automation Of Systematic Reviews (Icasr), Annette M. O'Connor, Guy Tsafnat, Stephen B. Gilbert, Kristina A. Thayer, Mary S. Wolfe Jan 2018

Moving Toward The Automation Of The Systematic Review Process: A Summary Of Discussions At The Second Meeting Of International Collaboration For The Automation Of Systematic Reviews (Icasr), Annette M. O'Connor, Guy Tsafnat, Stephen B. Gilbert, Kristina A. Thayer, Mary S. Wolfe

Veterinary Diagnostic and Production Animal Medicine Conference Proceedings and Presentations

The second meeting of the International Collaboration for Automation of Systematic Reviews (ICASR) was held 3–4 October 2016 in Philadelphia, Pennsylvania, USA. ICASR is an interdisciplinary group whose aim is to maximize the use of technology for conducting rapid, accurate, and efficient systematic reviews of scientific evidence. Having automated tools for systematic review should enable more transparent and timely review, maximizing the potential for identifying and translating research findings to practical application. The meeting brought together multiple stakeholder groups including users of summarized research, methodologists who explore production processes and systematic review quality, and technologists such as software developers ...


Application Of Bayesian Belief Network For Agile Kanban Backlog Estimation, Eric D. Weflen, Kevin Korniejczuk, Sharon Lau, Steven S. Kryk, Cameron A. Mackenzie, Iris V. Rivero Jan 2018

Application Of Bayesian Belief Network For Agile Kanban Backlog Estimation, Eric D. Weflen, Kevin Korniejczuk, Sharon Lau, Steven S. Kryk, Cameron A. Mackenzie, Iris V. Rivero

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

What is Agile Kanban?

  • Different from Kanban for JIT manufacturing!
  • Visualization of workflow
  • Limit work in process (WIP)


A Design Framework For Additive Manufacturing Through The Synergistic Use Of Axiomatic Design Theory And Triz, Sarath C. Renjith, Gül E. Okudan Kremer, Kijung Park Jan 2018

A Design Framework For Additive Manufacturing Through The Synergistic Use Of Axiomatic Design Theory And Triz, Sarath C. Renjith, Gül E. Okudan Kremer, Kijung Park

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Additive manufacturing has emerged as an integral part of modern manufacturing because of its unique capabilities for rapid prototyping and the design flexibility. In order to take full advantage of additive manufacturing, Design for Additive Manufacturing (DfAM) has risen to provide design frameworks, methodologies, and a set of guidelines for effective product designs under additive manufacturing. However, the existing DfAM methods have limitations in that most methods rely on either too general or too specific design requirements and parameters for additive manufacturing; an effective design framework that can consider the capabilities and constraints of additive manufacturing at an early design ...


Application Of Bayesian Belief Network For Agile Kanban Backlog Estimation, Eric Weflen, Kevin Korniejczuk, Sharon Lau, Steven Kryk, Cameron A. Mackenzie, Iris V. Rivero Jan 2018

Application Of Bayesian Belief Network For Agile Kanban Backlog Estimation, Eric Weflen, Kevin Korniejczuk, Sharon Lau, Steven Kryk, Cameron A. Mackenzie, Iris V. Rivero

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

This paper presents an approach based on influence diagrams for reducing uncertainty in Agile Kanban backlog feature completion time. Agile project management techniques, including SCRUM and Kanban, are prevalent in software development and spreading to other product development fields. A key artifact of Agile is the product backlog, containing work which needs to be completed by the development team. Internal and external stakeholders often require projections for completion of backlogged requests or features. Current estimation techniques such as duration assignments through planning poker and the use of story points to calculate velocity require persistent team input, while task counting has ...


Determination Of Bus Station Locations Under Emission And Social Cost Constraints, Atousa Zarindast, Elif Elçin Günay, Kijung Park, Gül E. Okudan Kremer Jan 2018

Determination Of Bus Station Locations Under Emission And Social Cost Constraints, Atousa Zarindast, Elif Elçin Günay, Kijung Park, Gül E. Okudan Kremer

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

This study proposes a two-stage stochastic programming model to determine an optimal set of bus stations that minimizes operational, environmental, and social costs under uncertain weather conditions and customer perceptions on sustainability. The first stage of the proposed model focuses on the derivation of a set of bus stations under uncertain demand and weather conditions. Then, the second stage determines an optimal vehicle capacity (i.e., bus size) to minimize the impact of vehicle shortages. In the proposed model, different customer perceptions on sustainability are conceptualized through a range of dissatisfaction levels. Weather conditions are considered as causing higher dissatisfaction ...


Closed-Loop Supply Chain Network Design With Multiple Transportation Modes Under Stochastic Demand And Uncertain Carbon Tax, Ali Haddadsisakht, Sarah M. Ryan Jan 2018

Closed-Loop Supply Chain Network Design With Multiple Transportation Modes Under Stochastic Demand And Uncertain Carbon Tax, Ali Haddadsisakht, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

We optimize the design of a closed-loop supply chain network that encompasses flows in both forward and reverse directions and is subject to uncertainty in demands for both new and returned products. The model also accommodates a carbon tax with tax rate uncertainty. The proposed model is a three-stage hybrid robust/stochastic program that combines probabilistic scenarios for the demands and return quantities with uncertainty sets for the carbon tax rates. The first stage decisions are facility investments, the second stage concerns the plan for distributing new and collecting returned products after realization of demands and returns, and the numbers ...


Five Lenses On Team Tutor Challenges: A Multidisciplinary Approach, Stephen B. Gilbert, Michael Dorneich, Jamiahus Walton, Eliot Winer Jan 2018

Five Lenses On Team Tutor Challenges: A Multidisciplinary Approach, Stephen B. Gilbert, Michael Dorneich, Jamiahus Walton, Eliot Winer

Industrial and Manufacturing Systems Engineering Publications

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a ...


The Hurwicz Decision Rule’S Relationship To Decision Making With The Triangle And Beta Distributions And Exponential Utility, Sarat Sivaprasad, Cameron A. Mackenzie Jan 2018

The Hurwicz Decision Rule’S Relationship To Decision Making With The Triangle And Beta Distributions And Exponential Utility, Sarat Sivaprasad, Cameron A. Mackenzie

Industrial and Manufacturing Systems Engineering Publications

Non-probabilistic approaches to decision making have been proposed for situations in which an individual does not have enough information to assess probabilities over an uncertainty. One non-probabilistic method is to use intervals in which an uncertainty has a minimum and maximum but nothing is assumed about the relative likelihood of any value within the interval. The Hurwicz decision rule in which a parameter trades off between pessimism and optimism generalizes the current rules for making decisions with intervals. This article analyzes the relationship between intervals based on the Hurwicz rule and traditional decision analysis using a few probability distributions and ...


Utilizing Multivariate Analysis For Assessing Student Learning Through Effective College-Industry Partnerships, Caleb Burns, Shweta Chopra, Mack C. Shelley Ii, Gretchen A. Mosher Jan 2018

Utilizing Multivariate Analysis For Assessing Student Learning Through Effective College-Industry Partnerships, Caleb Burns, Shweta Chopra, Mack C. Shelley Ii, Gretchen A. Mosher

Political Science Publications

There is no doubt that college–industry collaborations are vital to the success of undergraduate students with engineering and technology majors. This collaboration provides students with an opportunity to bridge the gap between classroom education and real-world experience. Inviting industry representatives to engage in the classroom and involving students with professional organizations, student field trips, virtual plant tours, and industry-focused final projects are ways in which an instructor can incorporate student–industry engagement into their course. During their undergraduate degree program, students are required to participate in an internship program where they gain substantial industry engagement and opportunities to learn ...


A Regional Information-Based Multi-Attribute And Multi-Objective Decision-Making Approach For Sustainable Supplier Selection And Order Allocation, Kijung Park, Gül E. Okudan Kremer, Junfeng Ma Jan 2018

A Regional Information-Based Multi-Attribute And Multi-Objective Decision-Making Approach For Sustainable Supplier Selection And Order Allocation, Kijung Park, Gül E. Okudan Kremer, Junfeng Ma

Industrial and Manufacturing Systems Engineering Publications

Although extant studies proposed various models and frameworks for sustainable supplier selection problems, they paid limited attention to the incorporation of regional economic, social, and environmental factors simultaneously for global supply chain design due to the difficulty in reflecting varies dimensions of the global business environment and their associated risk in a decision model. Existing supplier selection models also tend to focus on the formulation of a simplified supply chain structure rather than considering more realistic supply chain operations under multiple sourcing and product designs. To facilitate the complex decision-making process of global supplier selection problems, this study proposes an ...