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Articles 1 - 15 of 15

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

Multistage Stochastic Programming Modeling For Farmland Irrigation Management Under Uncertainty, Qi Li, Guiping Hu Jun 2020

Multistage Stochastic Programming Modeling For Farmland Irrigation Management Under Uncertainty, Qi Li, Guiping Hu

Industrial and Manufacturing Systems Engineering Publications

Farmland management and irrigation scheduling are vital to a productive agricultural economy. A multistage stochastic programming model is proposed to maximize farmers’ annual profit under uncertainty. The uncertainties considered include crop prices, irrigation water availability, and precipitation. During the first stage, pre-season decisions including seed type and plant density are made, while determinations of when to irrigate and how much water to be used for each irrigation are made in the later stages. The presented case study, based on a farm in Nebraska, U.S.A., showed that a 10% profit increase could be achieved by taking the corn price ...


The Interaction Between Physical And Psychosocial Stressors, Esraa S. Abdelall, Zoe Eagle, Tor Finseth, Ahmad A. Mumani, Zhonglun Wang, Michael C. Dorneich, Richard T. Stone May 2020

The Interaction Between Physical And Psychosocial Stressors, Esraa S. Abdelall, Zoe Eagle, Tor Finseth, Ahmad A. Mumani, Zhonglun Wang, Michael C. Dorneich, Richard T. Stone

Industrial and Manufacturing Systems Engineering Publications

Do physical and psychosocial stressors interact to increase stress in ways not explainable by the stressors alone? A preliminary study compared participants’ stress response while subjected to a physical stressor (reduced or full physical load) and a predetermined social stressor (confronted by calm or aggressive behavior). Salivary cortisol samples measured endocrine stress. Heart rate variability (HRV) and electrodermal activity (EDA) measured autonomic stress. Perceived stress was measured via discomfort and stress state surveys. Participants with a heavier load reported increased distress and discomfort. Encountering an aggressive individual increased endocrine stress, distress levels, and perceived discomfort. Higher autonomic stress and discomfort ...


Complementarity‐Based Selection Strategy For Genomic Selection, Saba Moeinizade, Megan Wellner, Guiping Hu, Lizhi Wang Jan 2020

Complementarity‐Based Selection Strategy For Genomic Selection, Saba Moeinizade, Megan Wellner, Guiping Hu, Lizhi Wang

Industrial and Manufacturing Systems Engineering Publications

Genomic selection is a technique that breeders use to select plant or animal individuals to mate and produce new generations of species. The conventional selection method is to select individuals that are either observed or predicted to be the best based on the assumption that parents with better phenotypes will produce better offspring. A major limitation of this method is its focus on the short‐term genetic gains at the cost of genetic diversity and long‐term growth potential. Recently, several new genomic selection methods were proposed to maximize the long‐term potential. Along this research direction, we propose a ...


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 ...


Optimizing Selection And Mating In Genomic Selection With A Look-Ahead Approach: An Operations Research Framework, Saba Moeinizade, Guiping Hu, Lizhi Wang, Patrick Schnable Jul 2019

Optimizing Selection And Mating In Genomic Selection With A Look-Ahead Approach: An Operations Research Framework, Saba Moeinizade, Guiping Hu, Lizhi Wang, Patrick Schnable

Industrial and Manufacturing Systems Engineering Publications

New genotyping technologies have made large amounts of genotypic data available for plant breeders to use in their efforts to accelerate the rate of genetic gain. Genomic selection (GS) techniques allow breeders to use genotypic data to identify and select, for example, plants predicted to exhibit drought tolerance, thereby saving expensive and limited field-testing resources relative to phenotyping all plants within a population. A major limitation of existing GS approaches is the trade-off between short-term genetic gain and long-term potential. Some approaches focus on achieving short-term genetic gain at the cost of reduced genetic diversity necessary for long-term gains. In ...


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 ...


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 ...


Evaluating Operator Harvest Technology Within A High-Fidelity Combine Simulator, Chase Meusel, Don Kieu, Stephen Gilbert, Greg R. Luecke, Brian Gilmore, Norene Kelly, Tim Hunt May 2018

Evaluating Operator Harvest Technology Within A High-Fidelity Combine Simulator, Chase Meusel, Don Kieu, Stephen Gilbert, Greg R. Luecke, Brian Gilmore, Norene Kelly, Tim Hunt

Industrial and Manufacturing Systems Engineering Publications

Farming today is more complex than it has ever been. Operators are increasingly reliant on technology to aid and improve harvest performance. New harvest technology is under development that will advise harvest operators on the proper adjustment of machine harvest settings, as well as automatically adjust these machine settings without operator intervention, improving the harvest performance of the machine, and reducing the cognitive load of the operator. In this work a high-fidelity, interactive harvest combine simulator is used to understand how harvest operators currently use existing harvest technology, and to evaluate the performance improvements provided by new prototype machine control ...


Three New Approaches To Genomic Selection, Lizhi Wang, Guodong Zhu, Will Johnson, Mriga Kher Jan 2018

Three New Approaches To Genomic Selection, Lizhi Wang, Guodong Zhu, Will Johnson, Mriga Kher

Industrial and Manufacturing Systems Engineering Publications

Conventional genomic selection approaches use breeding values to evaluate individual plants or animals and to make selection decisions. Multiple variants of breeding values and selection approaches have been proposed, but they suffer two major limitations. First, selection decisions are not responsive to changes in time and resource availability. Second, selection decisions are not coordinated with related decisions such as mating and resource allocation. We present three new genomic selection approaches that attempt to address these two limitations, which were designed by engineering students in a class project at Iowa State University. Compared with previous approaches using the same data set ...


Assessing The Validity Of Facilitated-Volunteered Geographic Information: Comparisons Of Expert And Novice Ratings, Kelly Kalvelage, Michael C. Dorneich, Christopher Seeger, Gregory Welk, Stephen B. Gilbert, Jon Moon, Imad Jafir, Phyllis Brown May 2017

Assessing The Validity Of Facilitated-Volunteered Geographic Information: Comparisons Of Expert And Novice Ratings, Kelly Kalvelage, Michael C. Dorneich, Christopher Seeger, Gregory Welk, Stephen B. Gilbert, Jon Moon, Imad Jafir, Phyllis Brown

Industrial and Manufacturing Systems Engineering Publications

Facilitated-voluntary geographic information (f-VGI) is a promising method to enable systematic collection of data from residents about their physical and social environment. The method capitalizes on ubiquitous mobile smartphones to empower collection of geospatially-referenced data. It is important to evaluate the validity of user-generated content for use in research or program planning. The purpose of this study was to test whether the aggregated environmental (“bikeability”) ratings from novice community residents converges with ratings from experts using a robust research-based, paper audit-tool (the established Pedestrian Environment Data Scan (PEDS) tool). Equivalence testing statistically showed overall agreement between the composite ratings of ...


Systematic Design For Trait Introgression Projects, John N. Cameron, Ye Han, Lizhi Wang, William D. Beavis Jan 2017

Systematic Design For Trait Introgression Projects, John N. Cameron, Ye Han, Lizhi Wang, William D. Beavis

Industrial and Manufacturing Systems Engineering Publications

We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing ...


Utility Of Baroreflex Sensitivity As A Marker Of Stress, Amanda A. Anderson, Nir Keren, Andrew Lilja, Kevin Godby, Stephen B. Gilbert, Warren D. Franke Jun 2016

Utility Of Baroreflex Sensitivity As A Marker Of Stress, Amanda A. Anderson, Nir Keren, Andrew Lilja, Kevin Godby, Stephen B. Gilbert, Warren D. Franke

Industrial and Manufacturing Systems Engineering Publications

Presently, adaptive systems use various cognitive and cardiovascular measures to evaluate the functional state of the operator. One marker that has been largely ignored as an assessment tool is baroreflex sensitivity (BRS). This study examined the extent to which BRS changed in response to acute psychological and physical stressors. A total of 20 participants underwent 6-min exposures to a psychological stressor and a physical stressor. Baroreceptor sensitivity, blood pressure, heart rate, heart rate variability, stroke volume, cardiac output, mean blood pressure, total peripheral resistance, left ventricular ejection time, and pre-ejection period were continuously measured at rest and throughout the testing ...


Analysis Of Food Hub Commerce And Participation Using Agent-Based Modeling: Integrating Financial And Social Drivers, Caroline C. Krejci, Richard Stone, Michael Dorneich, Stephen B. Gilbert Feb 2016

Analysis Of Food Hub Commerce And Participation Using Agent-Based Modeling: Integrating Financial And Social Drivers, Caroline C. Krejci, Richard Stone, Michael Dorneich, Stephen B. Gilbert

Industrial and Manufacturing Systems Engineering Publications

Objective: Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants.

Background: Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models.

Method: Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on ...


Medial Longitudinal Arch Deformation During Walking And Stair Navigation While Carrying Loads, Elizabeth Rose Hageman, Michelle Hall, Eric Gerard Sterner, Gary A. Mirka Jan 2011

Medial Longitudinal Arch Deformation During Walking And Stair Navigation While Carrying Loads, Elizabeth Rose Hageman, Michelle Hall, Eric Gerard Sterner, Gary A. Mirka

Industrial and Manufacturing Systems Engineering Publications

Background:

Understanding the biomechanics of the medial longitudinal arch (MLA) may provide insights into injury risk and prevention, as well as function of the arch-supporting structures. Our understanding of MLA deformation is currently limited to sit-to-stand, walking, and running.

Material and Methods:

Three-dimensional deformation of the MLA of the right foot was characterized in 17 healthy participants during several simulated activities of daily living. MLA deformation was quantified by both changes in arch length and navicular displacement during the stance phase of three motions: walking, stair ascent, and stair descent. Three levels of load were also evaluated: no load, a ...