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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 ...


Similarity Evaluation Of Topography Measurement Results By Different Optical Metrology Technologies For Additive Manufactured Parts, Yi Zheng, Xiao Zhang, Shaodong Wang, Qing Li, Hantang Qin, Beiwen Li Mar 2020

Similarity Evaluation Of Topography Measurement Results By Different Optical Metrology Technologies For Additive Manufactured Parts, Yi Zheng, Xiao Zhang, Shaodong Wang, Qing Li, Hantang Qin, Beiwen Li

Industrial and Manufacturing Systems Engineering Publications

The surface topographic measurements can be used by the additive manufacturing (AM) industry for in-situ quality inspection. However, disagreements may arise when we use different technologies to measure the topography of the same sample surface due to noise, sampling or optical properties of the sample surface, which may cause miscommunications or confusions between manufacturers. Thus, proposing methods for rating the similarities to match surface topographic data measured by various optical techniques is of crucial importance. This research investigates similarity evaluation methods for three-dimensional point-cloud topography data acquired by different technologies. Two different optical techniques (focus variation microscopy and structured light ...


Achieving Consistency With Cutting Planes, Danial Davarnia, Atefeh Rajabalizadeh, John Hooker Jan 2020

Achieving Consistency With Cutting Planes, Danial Davarnia, Atefeh Rajabalizadeh, John Hooker

Industrial and Manufacturing Systems Engineering Publications

Cutting planes accelerate branch-and-bound search primarily by cutting off fractional solutions of the linearprogramming (LP) relaxation, resulting in tighter bounds for pruning the search tree. Yet cutting planes canalso reduce backtracking by excluding inconsistent partial assignments that occur in the course of branching.A partial assignment is inconsistent with a constraint set when it cannot be extended to a full feasibleassignment. The constraint programming community has studied consistency extensively and used it as aneffective tool for the reduction of backtracking. We extend this approach to integer programming (IP) bydefining concepts of consistency that are useful in a branch-and-bound context. We ...


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 ...


Generating Partial Civil Information Model Views Using A Semantic Information Retrieval Approach, Tuyen Le, H. David Jeong, Stephen B. Gilbert, Evgeny Chukharev-Hudilainen Jan 2020

Generating Partial Civil Information Model Views Using A Semantic Information Retrieval Approach, Tuyen Le, H. David Jeong, Stephen B. Gilbert, Evgeny Chukharev-Hudilainen

Industrial and Manufacturing Systems Engineering Publications

Open data standards (e.g. LandXML, TransXML, CityGML) are a key to addressing the interoperability issue in exchanging civil information modeling (CIM) data throughout the project life-cycle. Since these schemas include rich sets of data types covering a wide range of assets and disciplines, model view definitions (MVDs) which define subsets of a schema are required to specify what types of data to be shared in accordance with a specific exchange scenario. The traditional procedure for generating and implementing MVDs is time-consuming and laborious as entities and attributes relevant to a particular data exchange context are manually identified by domain ...


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 ...


Coupling Machine Learning And Crop Modeling Improves Crop Yield Prediction In The Us Corn Belt, Mohsen Shahhosseini, Guiping Hu, Sotirios V. Archontoulis, Isaiah Huber Jan 2020

Coupling Machine Learning And Crop Modeling Improves Crop Yield Prediction In The Us Corn Belt, Mohsen Shahhosseini, Guiping Hu, Sotirios V. Archontoulis, Isaiah Huber

Industrial and Manufacturing Systems Engineering Publications

This study investigates whether coupling crop modeling and machine learning (ML) improves corn yield predictions in the US Corn Belt. The main objectives are to explore whether a hybrid approach (crop modeling + ML) would result in better predictions, investigate which combinations of hybrid models provide the most accurate predictions and determine the features from the crop modeling that are most effective to be integrated with ML for corn yield prediction. Five ML models and six ensemble models have been designed to address the research question. The results suggest that adding simulation crop model variables (APSIM) as input features to ML ...


Improved Weighted Random Forest For Classification Problems, Mohsen Shahhosseini, Guiping Hu Jan 2020

Improved Weighted Random Forest For Classification Problems, Mohsen Shahhosseini, Guiping Hu

Industrial and Manufacturing Systems Engineering Publications

Several studies have shown that combining machine learning models in an appropriate way will introduce improvements in the individual predictions made by the base models. The key to make well-performing ensemble model is in the diversity of the base models. Of the most common solutions for introducing diversity into the decision trees are bagging and random forest. Bagging enhances the diversity by sampling with replacement and generating many training data sets, while random forest adds selecting a random number of features as well. This has made the random forest a winning candidate for many machine learning applications. However, assuming equal ...


Specifying And Validating Probabilistic Inputs For Prescriptive Models Of Decision Making Over Time, Sarah Mcallister Ryan Jan 2020

Specifying And Validating Probabilistic Inputs For Prescriptive Models Of Decision Making Over Time, Sarah Mcallister Ryan

Industrial and Manufacturing Systems Engineering Publications

Optimization models for making decisions over time in uncertain environments rely on probabilistic inputs, such as scenario trees for stochastic mathematical programs. The quality of model outputs, i.e., the solutions obtained, depends on the quality of these inputs. However, solution quality is rarely assessed in a rigorous way. The connection between validation of model inputs and quality of the resulting solution is not immediate. This chapter discusses some efforts to formulate realistic probabilistic inputs and subsequently validate them in terms of the quality of solutions they produce. These include formulating probabilistic models based on statistical descriptions understandable to decision ...


Teleporting Through Virtual Environments: Effects Of Path Scale And Environment Scale On Spatial Updating, Jonathan W. Kelly, Alec G. Ostrander, Alex F. Lim, Lucia A. Cherep, Stephen B. Gilbert Jan 2020

Teleporting Through Virtual Environments: Effects Of Path Scale And Environment Scale On Spatial Updating, Jonathan W. Kelly, Alec G. Ostrander, Alex F. Lim, Lucia A. Cherep, Stephen B. Gilbert

Industrial and Manufacturing Systems Engineering Publications

Virtual reality systems typically allow users to physically walk and turn, but virtual environments (VEs) often exceed the available walking space. Teleporting has become a common user interface, whereby the user aims a laser pointer to indicate the desired location, and sometimes orientation, in the VE before being transported without self-motion cues. This study evaluated the influence of rotational self-motion cues on spatial updating performance when teleporting, and whether the importance of rotational cues varies across movement scale and environment scale. Participants performed a triangle completion task by teleporting along two outbound path legs before pointing to the unmarked path ...


Decision Making Under Uncertainty For Design Of Resilient Engineered Systems, Cameron A. Mackenzie, Chao Hu Dec 2019

Decision Making Under Uncertainty For Design Of Resilient Engineered Systems, Cameron A. Mackenzie, Chao Hu

Industrial and Manufacturing Systems Engineering Publications

Designing resilient engineered systems that can sense and withstand adverse events and recover from the effects of the adverse events is increasingly seen as an important goal of engineering design. This paper proposes a value-driven design for resilience (VD2R) framework in order to enable the assessment of system resilience and the optimization of decision variables (or design characteristics) that maximize the value of the system for a firm. The VD2R framework possesses three unique features that allow system resilience and value to be addressed in a theoretically founded and explicit way. First, it assesses the time-dependent resilience of an engineered ...


Integrating Narratives Into Decision Making For Complex Systems Engineering Design Issues, Cameron A. Mackenzie, Kris Bryden, Anna A. Prisacari Sep 2019

Integrating Narratives Into Decision Making For Complex Systems Engineering Design Issues, Cameron A. Mackenzie, Kris Bryden, Anna A. Prisacari

Industrial and Manufacturing Systems Engineering Publications

Engineering decision making and design requires collaboration between groups from different disciplines, each with different tools, vocabulary, and concerns. Traditional engineering decision-making tools are generally based on understanding the decision makers’ values, modeling uncertainty with probability, and selecting the alternative that maximizes utility. This rational approach to decision making may not be well understood or used by many stakeholders involved in the engineering design process. Constructing narratives, a basic means of human communication, may aid in engineering communication and comprehension and help with decision making. Narratives represent events by means of a story and usually include characters or agents who ...


The Effects Of Load Weight And Load Starting Height On Variability Of Lifting Kinematics And Kinetics, Hamid Norasi, Jordyn Koenig, Gary A. Mirka Sep 2019

The Effects Of Load Weight And Load Starting Height On Variability Of Lifting Kinematics And Kinetics, Hamid Norasi, Jordyn Koenig, Gary A. Mirka

Industrial and Manufacturing Systems Engineering Publications

Trunk kinematic variables have been used to understand the risk of low back injuries in the workplace. Variability in the trunk kinematics as an individual performs a repetitive lifting task is an underexplored area of research. In the current study, it was hypothesized that workplace variables (starting height of lift and load weight) would have an impact on the variance in the kinematic and kinetic variables. Twenty participants performed 60 repetitions of an asymmetric lifting task under four different conditions representing two levels of load weight (5% or 10% of the participant's body weight) and two levels of starting ...


Identifying And Mitigating Supply Chain Risks Using Fault Tree Optimization, Michael D. Sherwin, Hugh R. Medal, Cameron A. Mackenzie, Kennedy J. Brown Jul 2019

Identifying And Mitigating Supply Chain Risks Using Fault Tree Optimization, Michael D. Sherwin, Hugh R. Medal, Cameron A. Mackenzie, Kennedy J. Brown

Industrial and Manufacturing Systems Engineering Publications

Although supply chain risk management and supply chain reliability are topics that have been studied extensively, a gap exists for solutions that take a systems approach to quantitative risk mitigation decision making and especially in industries that present unique risks. In practice, supply chain risk mitigation decisions are made in silos and are reactionary. In this article, we address these gaps by representing a supply chain as a system using a fault tree based on the bill of materials of the product being sourced. Viewing the supply chain as a system provides the basis to develop an approach that considers ...


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 ...


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 ...


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 ...


Computational Aspects Of Bayesian Solution Estimators In Stochastic Optimization, Danial Davarnia, Burak Kocuk, Gerard Cornuejols Jan 2019

Computational Aspects Of Bayesian Solution Estimators In Stochastic Optimization, Danial Davarnia, Burak Kocuk, Gerard Cornuejols

Industrial and Manufacturing Systems Engineering Publications

We study a class of stochastic programs where some of the elements in the objective function are random, and their probability distribution has unknown parameters. The goal is to find a good estimate for the optimal solution of the stochastic program using data sampled from the distribution of the random elements. We investigate two common optimization criteria for evaluating the quality of a solution estimator, one based on the difference in objective values, and the other based on the Euclidean distance between solutions. We use risk as the expected value of such criteria over the sample space. Under a Bayesian ...


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 ...


Biclustermd: An R Package For Biclustering With Missing Values, John Reisner, Hieu Pham, Sigurdur Olafsson, Stephen B. Vardeman, Jing Li Jan 2019

Biclustermd: An R Package For Biclustering With Missing Values, John Reisner, Hieu Pham, Sigurdur Olafsson, Stephen B. Vardeman, Jing Li

Industrial and Manufacturing Systems Engineering Publications

Biclustering is a statistical learning technique that attempts to find homogeneous partitions of rows and columns of a data matrix. For example, movie ratings might be biclustered to group both raters and movies. biclust is a current R package allowing users to implement a variety of biclustering algorithms. However, its algorithms do not allow the data matrix to have missing values. We provide a new R package, biclustermd, which allows users to perform biclustering on numeric data even in the presence of missing values.


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 ...


Statistical Reliability Of Wind Power Scenarios And Stochastic Unit Commitment Cost, Didem Sari, Sarah M. Ryan Nov 2018

Statistical Reliability Of Wind Power Scenarios And Stochastic Unit Commitment Cost, Didem Sari, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

Probabilistic wind power scenarios constitute a crucial input for stochastic day-ahead unit commitment in power systems with deep penetration of wind generation. To minimize the cost of implemented solutions, the scenario time series of wind power amounts available should accurately represent the stochastic process for available wind power as it is estimated on the day ahead. The high computational demands of stochastic programming motivate a search for ways to evaluate scenarios without extensively simulating the stochastic unit commitment procedure. The statistical reliability of wind power scenario sets can be assessed by approaches extended from ensemble forecast verification. We examine the ...


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 ...


Fabrication And Evaluation Of Poly(Lactic Acid), Chitosan, And Tricalcium Phosphate Biocomposites For Guided Bone Regeneration, Srikanthan Ramesh, Lisa Lungaro, Dimitrios Tsikritsis, Eric Weflen, Iris V. Rivero Aug 2018

Fabrication And Evaluation Of Poly(Lactic Acid), Chitosan, And Tricalcium Phosphate Biocomposites For Guided Bone Regeneration, Srikanthan Ramesh, Lisa Lungaro, Dimitrios Tsikritsis, Eric Weflen, Iris V. Rivero

Industrial and Manufacturing Systems Engineering Publications

This study presents and evaluates an approach for fabricating poly(lactic acid) (PLA)/chitosan (CS)/tricalcium phosphate (TCP) electrospun scaffolds for guided bone regeneration, a dental procedure that uses membranes to direct and delineate regions of osteogenesis. Biomaterials were pre‐processed using cryomilling, a solid‐state grinding technique that facilitates the generation of powdered biocomposites conducive to electrospinning. X‐ray diffraction (XRD) confirmed the generation of cryomilled blends consisting of PLA, CS, and TCP. Results from the differential scanning calorimetry showed an upward shift in glass transition temperature and an increase in crystallinity with the inclusion of TCP reinforcing the ...


A Bayesian State-Space Model Using Age-At-Harvest Data For Estimating The Population Of Black Bears (Ursus Americanus) In Wisconsin, Maximilian L. Allen, Andrew S. Norton, Glenn Stauffer, Nathan M. Roberts, Yanshi Luo, Qing Li, David Macfarland, Timothy R. Van Deelen Aug 2018

A Bayesian State-Space Model Using Age-At-Harvest Data For Estimating The Population Of Black Bears (Ursus Americanus) In Wisconsin, Maximilian L. Allen, Andrew S. Norton, Glenn Stauffer, Nathan M. Roberts, Yanshi Luo, Qing Li, David Macfarland, Timothy R. Van Deelen

Industrial and Manufacturing Systems Engineering Publications

Population estimation is essential for the conservation and management of fish and wildlife, but accurate estimates are often difficult or expensive to obtain for cryptic species across large geographical scales. Accurate statistical models with manageable financial costs and field efforts are needed for hunted populations and using age-at-harvest data may be the most practical foundation for these models. Several rigorous statistical approaches that use age-at-harvest and other data to accurately estimate populations have recently been developed, but these are often dependent on (a) accurate prior knowledge about demographic parameters of the population, (b) auxiliary data, and (c) initial population size ...


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 ...