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Articles 31 - 60 of 139
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
A New Method To Estimate The Impact On The L5/Si Spinal Disc From Speed Lifting Of Unstable Loads, Asymmetrically, Suhaib Al-Lababidi
A New Method To Estimate The Impact On The L5/Si Spinal Disc From Speed Lifting Of Unstable Loads, Asymmetrically, Suhaib Al-Lababidi
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Background: The most significant causes of lower back injuries at work are probably from manual lifting activities. Lifting unstable loads pose a significant strain to the lower back and can cause debilitating lumbar spine injuries. The primary function of the vertebral column is to support the upper body. The L5/S1 disc junction located between the lumbar and the sacral regions of the vertebral column is the most critical joint in spine with respect to lifting strain. Because of its position and the amount of upper body weight it handles, it is particularly vulnerable to misalignment, wear and tear, and injury.Lifting …
A Comparative Assessment Of Co2 Emission Between Gasoline, Electric, And Hybrid Vehicles: A Well-To-Wheel Perspective Using Agent-Based Modeling, Mdmamunur Rahman
A Comparative Assessment Of Co2 Emission Between Gasoline, Electric, And Hybrid Vehicles: A Well-To-Wheel Perspective Using Agent-Based Modeling, Mdmamunur Rahman
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Road transports in the U.S. are almost entirely dependent on the consumption of fossil fuel. This high dependency on fossil fuel is significantly contributing to carbon dioxide (CO2) emission, one of the leading Green House Gases (GHGs) responsible for global warming. Electrification of passenger vehicles could be an effective strategy to curb GHG emissions. Though Electric Vehicles (EVs) have zero tailpipe emissions, the power required to charge EV batteries may not necessarily come from carbon-free power plants. In this study, for a comprehensive comparison between EV and Gasoline Vehicle (GV), we developed an agent-based simulation model for the entire energy …
Robust, Time-Critical, Evidence-Based Adaptive Data Fusion, Mohammad Amin Javadi
Robust, Time-Critical, Evidence-Based Adaptive Data Fusion, Mohammad Amin Javadi
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Sensors have become inevitable part of many studies and working areas ranging from navigation, transportation and medical applications. A sensor can help a user in a variety of situations including dangerous, inaccessible, time and money-consuming circumstances. Applying multiple sensors simultaneously allows for improving the accuracy of measurement estimates for system states. As an example, a part of this study uses a GPS sensor to increase the accuracy of the position estimation obtained by an IMU in an indoor environment. The same GPS device with position outputs can also be studied to provide a new measuring dimension such as velocity. This …
Some New Results On Statistical Information And Evidence, Maryam Moghimi
Some New Results On Statistical Information And Evidence, Maryam Moghimi
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
This dissertation represents an attempt to relate some fundamental statistical problems using the notions of information, entropy, and evidence.
Identifying And Addressing Improvement Opportunities In Primary Care Clinics, Mozhdeh Sadighi
Identifying And Addressing Improvement Opportunities In Primary Care Clinics, Mozhdeh Sadighi
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
ABSTRACT: The main aim of this dissertation is to study how unrecognized opportunities for improving efficiency of in-person patient visits in a primary care clinic can be identified and addressed. To fulfill this goal, the research is divided into three distinct but related sections. Section one, with the most holistic view, uses a combination of scientific and rigorous methods along two research paths and, as a result, explores two opportunities for improvement in the clinic. These opportunities are high patient waiting time and unbalanced workload. Sections two and three each focus on underlying conditions driving one of these two opportunities. …
Mathematical Modeling Approaches In Sustainable Food Supply Chains, Amin Gharehyakheh
Mathematical Modeling Approaches In Sustainable Food Supply Chains, Amin Gharehyakheh
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Access to high quality and safe food is vital for sustainable development in societies. Perishable foods lose a major portion of their quality after harvesting until the consumption point due to poor storage and distribution conditions. Thus, improvements in food supply chain operations are very critical in the sustainable development of society and the industry. The first part of this dissertation seeks to find a cost-effective and reliable tool to monitor the quality loss and implementation of the least shelf life first-out inventory management policy in food banks. Application of the Gompertz model and Arrhenius equation based on time-temperature data …
Planning And Optimization Of A Stochastic Multi-Phase Multi- Criteria Multi-Echelon Humanitarian Logistics Network, A B M Mainul Bari
Planning And Optimization Of A Stochastic Multi-Phase Multi- Criteria Multi-Echelon Humanitarian Logistics Network, A B M Mainul Bari
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Disasters, may that be anthropogenic or natural, cause much havoc to vast area and population. Property and infrastructures get destroyed. People are often in need of urgent relief like dry foods and water to survive. In a country which is in the underdeveloped part of the world, relief and evacuation activities are usually carried out by local government run aid agencies. Most of the time, the local decision makers do the coordination or planning of these humanitarian activities largely based on either past experience or sometimes just pure hunch, which is neither efficient nor economic. Proper planning and coordination in …
Mars Knot Positioning And Global Optimization, Xinglong Ju
Mars Knot Positioning And Global Optimization, Xinglong Ju
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Multivariate adaptive regression splines (MARS) is a statistical modeling approach with wide real-world applications. In the MARS model building process, knot positioning is a critical step that potentially affects the accuracy of the final MARS model. Identifying well-positioned knots entails assessing the quality of many knots in each model building iteration, which requires much computation efforts. By exploring the change in the residual sum of squares (RSS) within MARS, we find that local optima from previous iterations can be very close to those of the current iteration. In our approach, the prior change in RSS information is used to “warm …
Analyzing Collaboration In Food Assistance Networks Using Agent-Based Modeling, Joyita Mostafa
Analyzing Collaboration In Food Assistance Networks Using Agent-Based Modeling, Joyita Mostafa
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
To address the issue of food insecurity, many small independent agencies, known as food pantries, collect and distribute donated food to food-insecure clients. However, the supply of donated food varies significantly from week to week, leading to frequent mismatches in supply and demand. One approach to addressing this problem is to facilitate greater food pantry collaboration, such that they are able to balance supply and demand among themselves. However, their interpersonal relationships and the additional costs associated with transshipments can be a barrier to collaboration. The objective of this research is to use modeling to gain a better understanding of …
A Multi-Agent Demand Response Planning And Operational Optimization Framework, Alireza Fallahi
A Multi-Agent Demand Response Planning And Operational Optimization Framework, Alireza Fallahi
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
This research describes a real-time optimization model for multi-agent demand response (DR) from a Load Serving Entity (LSE) perspective. We formulate two infinite horizon stochastic optimization models; specifically, an LSE model and a dynamic pricing customer model. The objective of these models is to minimize long-term cost and discomfort penalty of the LSE and dynamic pricing customers. We solve a deterministic finite horizon linear program as an approximation of the suggested stochastic model and provide computational experiments. In stochastic programming (SP), a wait-and-see solution is at least as good as an optimal policy. On the other hand, a policy that …
Uncovering Underlying Features For State Transition Modeling, Ashkan Farahani
Uncovering Underlying Features For State Transition Modeling, Ashkan Farahani
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Modeling of a dynamic system is the representation of the interconnectivity of system state variables and their evolutionary trajectory over time. In this dissertation, the terminology “state transition modeling” refers to a situation when the system state transitions and its evolution is unknown and needs to be estimated. There are situations in many application settings where one does not simply observe the behavior of the system, but also has a desire to take action, intervene, and manipulate one or more system variables, and is interested in seeing the causal effect of the intervention. These interventions within a purely observational setting, …
A Dynamic Policing Simulation Framework, Khan Md Ariful Haque
A Dynamic Policing Simulation Framework, Khan Md Ariful Haque
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Crime is a serious problem to a society, and its costs are an economic burden. With the help of technology and developed tools, law enforcement agencies are making significant efforts to combat crime, so as to create a safer environment for society, both mentally and physically. The dynamic nature of crime and limited police resources often make their efforts challenging. Although there are numerous crime prediction models found in the policing literature, guidelines for policing strategies based on those models are still lacking. Towards addressing this gap, this dissertation constructs a dynamic policing simulation framework based on the concept of …
A Parametric Process-Based Cost Estimation Framework To Support Conceptual Product Family Design And Production, Zahra Banakar
A Parametric Process-Based Cost Estimation Framework To Support Conceptual Product Family Design And Production, Zahra Banakar
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
In today’s globally competitive environment, production costs estimation is a challenging task. This competitive market has brought specific strategies in the manufacturing sector, such as introducing more new products into the market with lower prices. In order to have the most accurate production costs estimation, accurate production cost information in a useful and relevant form is needed. This study presents a cost estimation framework that integrates both activity and parametric cost estimation methods to increase the ease, accuracy, and speed of producing cost estimates for a family of products or services. There is a need for an integrated production cost …
A Dynamic Multiple Stage, Multiple Objective Optimization Model With An Application To A Wastewater Treatment System, Prashant Tarun
A Dynamic Multiple Stage, Multiple Objective Optimization Model With An Application To A Wastewater Treatment System, Prashant Tarun
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Decision-making for complex dynamic systems involves multiple objectives. Various methods balance the tradeoffs of multiple objectives, the most popular being weighted-sum and constraint-based methods. Under convexity assumptions an optimal solution to the constraint-based problem can also be obtained by solving the weighted-sum problems, and all Pareto optimal solutions can be obtained by systematically varying the weights or constraint limits. The challenge is to generate meaningful weights or constraint limits that yield practical solutions. In this dissertation, we utilize the Analytic Hierarchy Process (AHP) and develop a methodology to generate weight vectors successively for a dynamic multiple stage, multiple objective (MSMO) …
Proposing A Sparse Weighted Directed Network Construction Method And A Novel Mutual-Information Based Sparse Feature Selection Algorithm For Multivariate Time-Series Analysis And Its Application In Medical Diagnostic Problems, Rahilsadat Hosseini
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
The main purpose of this study is feature engineering/learning from multivariate (MV) time-series to achieve a more interpretable model by dimension reduction. This aim is fulfilled in 2 main parts. In part 1, we proposed a network estimation approach namely SWDN which stands for sparse weighted directed network. In this approach, the directed subgraph of the underlying network was detected by maximum spanning tree (MST) algorithm that created a null model of connections with maximum inter-dependence (pairwise correlation or mutual information) forming the backbone structure of the MV time-series as an empirical reference. The edge weights were estimated using the …
Supervised Sparse Learning With Applications In Bioinformatics, Kin Ming Puk
Supervised Sparse Learning With Applications In Bioinformatics, Kin Ming Puk
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
In machine learning and mathematical optimization, sparse learning is the use of mathematical norms such as L1-norm, group norm and L21-norm in order to seek a trade-off between the goodness-of-fit measure and sparsity of the result. Sparsity of result leads to a parsimonious learning model - in other words, only few features from the data matrix are required to build the learning model and for further interpretation. The motivations of employing sparse learning in bioinformatics are two-fold: firstly, a parsimonious learning model enhances the explanatory power; and secondly, a parsimonious model generally allows better prediction and generalizes better to new …
Adjusting For Time Varying Confounding In Adaptive Interdisciplinary Pain Management Program, Nilabh Ohol
Adjusting For Time Varying Confounding In Adaptive Interdisciplinary Pain Management Program, Nilabh Ohol
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Interdisciplinary pain management combines multiple disciplines of professionals to understand the biological and psychosocial factors causing a patient's pain and to determine the best treatments among many to administer. The Eugene McDermott Center of Pain at University of Texas at Southwestern Medical Center in Dallas runs a two stage adaptive interdisciplinary pain management program with the aim to improve current and future pain outcomes. The sequential treatment regime for the pain and the observational nature of data yield to time varying confounding and a form of endogeneity. This yields biased estimates of the treatment effects which is undesirable. Our adaptive …
Tk-Mars: An Efficient Approach For Deterministic And Stochastic Black-Box Optimization, Hadis Anahideh
Tk-Mars: An Efficient Approach For Deterministic And Stochastic Black-Box Optimization, Hadis Anahideh
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Surrogate optimization approaches for black-box functions focus on approximating the underlying function, using metamodeling techniques, in order to optimize computationally expensive simulation models. Historically, surrogate optimization models have been validated by deterministic (noiseless) functions with every variable being significant. As a result, many surrogate optimization models used interpolating surrogates. However, many real world experiments often times include parameters that are insignificant and uncertainties associated with the black-box function. Using traditional interpolating surrogate optimization methods can lead to surrogate models with unnecessary predictors and sensitivity to noise. Consequently, a surrogate model with flexible, non-interpolating, and parsimonious characteristics is required to overcome …
Statistical Meta-Model For Air Traffic Flow And Capacity Management Based On Airspace Optimization-Simulation: The Continuous Challenge Of The Hub Of The America Congestion, Juan Marcos Castillo
Statistical Meta-Model For Air Traffic Flow And Capacity Management Based On Airspace Optimization-Simulation: The Continuous Challenge Of The Hub Of The America Congestion, Juan Marcos Castillo
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Panama is only Country on the Americas with a Canal and the hub of Logistics that include the interaction of the Atlantic and the Pacific in a less than a day. This Logistics growth after the Panama Canal Expansion resulted in an overwhelming growth in Aviation. Furthermore, the economic and Logistic growth at Panama is increasing the demand of air transportation and it is creating potential for Air Logistics. Thus, the air traffic congestion is one of the greatest challenges that the Aviation Industry is seeking to address. The objective of this research is to understand if the Air Traffic …
Sparse Representation And Learning For Discriminative Eeg Source Imaging, Feng Liu
Sparse Representation And Learning For Discriminative Eeg Source Imaging, Feng Liu
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
As a direct measurement modality of neural electrical firing patterns, electroencephalogram (EEG) has a much higher temporal resolution up to millisecond compared to positron emission topography (PET) and functional magnetic resonance imaging (fMRI) and it has become one of the popular neuroimaging tools to find signatures of brain diseases and to understand how the brain works. Other advantages of EEG include low cost, easy portability, and non-invasive. However, a limitation of EEG is its low spatial resolution since the measurement is on the scalp rather than inside the brain. Given the recorded scalp EEG data, to reconstruct the activated brain …
Optimizing A System Of Electric Vehicle Charging Stations, Ukesh Chawal
Optimizing A System Of Electric Vehicle Charging Stations, Ukesh Chawal
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
There has been a significant increase in the number of electric vehicles (EVs) mainly because of the need to have a greener living. Thus, ease of access to charging facilities is a prerequisite for large scale deployment for EV. The first component of this dissertation research seeks to formulate a deterministic mixed-integer linear programming (MILP) model to optimize the system of EV charging stations, the locations of the stations and the number of slots to be opened to maximize the profit based on the user-specified cost of opening a station. Despite giving the optimal solution, the drawback of MILP formulation …
Development Of A Framework And Analysis System To Support Intervention In Newborn Healthcare, Holly E. Lane
Development Of A Framework And Analysis System To Support Intervention In Newborn Healthcare, Holly E. Lane
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
One of the most vulnerable populations in healthcare is the newborn infant. As hospitalization for childbirth is the largest cause for entry into a healthcare facility, the population of newborns each year is extensive as is their cost of care. Newborn infants also may have additional costs associated with readmission for common or preventable illnesses, which may occur due to insufficient infant screening or lack of caregiver knowledge. Much research has been done to attempt to determine causes of readmission, what contributes to an increased or decreased readmission rate among newborns, and how healthcare interventions can impact these rates and …
Some New Results For Equilibria Of N-Person Games, Ahmad Nahhas
Some New Results For Equilibria Of N-Person Games, Ahmad Nahhas
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
In this dissertation, we present four journal articles in the area of game theory. In the first article, we define a generalized equilibrium for n-person normal form games. We prove that the Nash equilibrium and the mixed Berge equilibrium are special cases of the generalized equilibrium. In the second article, we study the computational complexity of finding a mixed Berge equilibrium in n-person normal form games. In particular, we prove that the problem is an NP-complete problem for n >= 3. In the third article, we give an interpretation of mixed strategies via resource allocation. Finally, in the fourth article, …
Probability Of Success In Program Management, Tejas Pawar
Probability Of Success In Program Management, Tejas Pawar
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
The field of Program Management is subject to high program failures. The Project Management Institute (PMI) states that 74% of programs are executed unsuccessfully (Mulcahy, Rita). The high rate of program failures is primarily due to inadequate planning before a program begins and inadequate management of a program when it is being executed. To avoid these high failure rates, a Program Manager needs a tool to help him assess the Probability of Success (POS) of fully accomplishing the objectives of his program from the initial planning phase and throughout all phases of program execution. Purpose: The purpose of this research …
Multi-Objective Two-Stage Stochastic Programming For Adaptive Interdisciplinary Pain Management With Piece-Wise Linear Network Transition Models, Gazi Md Daud Iqbal
Multi-Objective Two-Stage Stochastic Programming For Adaptive Interdisciplinary Pain Management With Piece-Wise Linear Network Transition Models, Gazi Md Daud Iqbal
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Pain is the most common symptom when a patient visits a physician. People experience pain throughout their lifetime at different degrees. If short term pain is not treated properly, then it can become long term pain, which is also known as chronic pain. The Eugene McDermott Center for pain management at UT Southwestern Medical Center conducts a two-stage pain management program for chronic pain. This research uses a two-stage stochastic programming approach to optimize personal adaptive treatment strategies for pain management. The goal is to generate adaptive treatment strategies using statistics based optimization approaches that can be used by physicians …
Using Approximate Dynamic Programming To Control An Electric Vehicle Charging Station System, Ying Chen
Using Approximate Dynamic Programming To Control An Electric Vehicle Charging Station System, Ying Chen
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Dynamic programming (DP) as a mathematical programming approach to optimize a system evolving over time has been applied to solve the multi-stage optimization problems in a lot of areas such as manufacturing systems and environmental engineering. Due to the “curses of dimensionality”, traditional DP method is only able to solve a low dimensional problem or problems under very limiting restrictions, In order to employ DP to solve high-dimensional practical complex systems, approximate dynamic programming (ADP) is proposed. Several versions of ADP has been introduced in the literature and for this study, the author takes advantage of design and analysis of …
Risk Assessment And Analysis Of Pharmaceutical Industry Due To Recalls, Sowmya Dinamani Rao
Risk Assessment And Analysis Of Pharmaceutical Industry Due To Recalls, Sowmya Dinamani Rao
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
In the past five years, there have been 5900 recalls of drugs by the U.S. Food and Drug Administration (FDA) which created distraught consumers and shareholders of pharmaceutical companies. In addition, recalls cause disruption in the supply chain mak-ing the pharmaceutical companies vulnerable to various types of risks. These risks include the potential for losing customers and investors as well as the huge financial losses from fines, penalties, lawsuits, revenue loss, market share and increased operations costs. Purpose: The purpose of this research is to study the consequences of product recall on Pharmaceutical Company. Methodology: Event study methodology was used …
Evaluating Increasing Hospital Closure Rates In U.S: A Model Framework And A Lean Six Sigma Deployment Approach For Quality Improvement Initiatives To Prevent Further Closures In Rural And Disadvanaged Locations, Soma Sekar Balasubramanian
Evaluating Increasing Hospital Closure Rates In U.S: A Model Framework And A Lean Six Sigma Deployment Approach For Quality Improvement Initiatives To Prevent Further Closures In Rural And Disadvanaged Locations, Soma Sekar Balasubramanian
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
Hospital Closures occur from time to time. Several rural hospitals were closed in the U.S recently in an unprecedented manner and hundreds of others are at the risk of closing. The Patient Protection and Affordable Care Act (PPACA) which was amended in 2010, has brought sea of changes in the healthcare industry right from changing the way how hospitals receive reimbursements by introducing several new programs targeting hospitals’ quality of care to expanding health insurance for millions of poor and underprivileged populations in the country. The goal of this study is to understand the closure of rural hospitals in line …
Evaluating The Impacts Of Sleep Disruptions In Women Through Automated Analysis (Sjsl Framework), Shalini Gupta
Evaluating The Impacts Of Sleep Disruptions In Women Through Automated Analysis (Sjsl Framework), Shalini Gupta
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
The proposed research suggests a solution for female sleep disruption by using automated analytics and attempts to improve our understanding of sleep disruption physiology. Although, sleep disruption monitoring is gaining attention with the use of sleep monitoring devices that track sleep disruptions. Automated technology can capture repeated measurements, evaluate sleep patterns, and make suggestions. However, facts revealed by clinical research suggest that it can measure sleep – disruption records, and sleep disorders. Moreover, this research can be useful for prescribing individual treatment, and hence improve individual healthcare optimization. In fact, some of the health tracking electronic devices assist individuals in …
Evaluating The Impacts Of The Internet Of Things To Reduce Runway Incursions: Understanding The Why, How, And When, Samuel Inanore Okate
Evaluating The Impacts Of The Internet Of Things To Reduce Runway Incursions: Understanding The Why, How, And When, Samuel Inanore Okate
Industrial, Manufacturing, and Systems Engineering Dissertations - Archive
The Federal Aviation Administration’s (FAA) mission is to maintain the safest and most efficient aerospace system in the world. The FAA has stated that runway safety is one of their top priorities, which encapsulates pilots, air traffic controllers, and airport vehicle drivers and workers (Federal Aviation Administration, June 2015). Federal Aviation Administration categorizes a runway incursion as a hazardous event that can occur in the Air Operations Area (AOA) that involves an incorrect presence of an aircraft, vehicle or person in the protected area of a surface designated for the landing and takeoff of an aircraft (Federal Aviation Administration, June …