Operations Research, Systems Engineering and Industrial Engineering Commons^™

A Model To Estimate The Lifetime Of Bess For The Prosumer Community Of Manufacturers With Ogs, Md Monirul Islam, Cihan H. Dagli, Zeyi Sun

Engineering Management and Systems Engineering Faculty Research & Creative Works

Onsite generation system (OGS) with renewable sources for modern manufacturing plant is considered as a critical alternative energy source for the manufacturers. Prosumer community can be formed by aggregating such manufacturers to achieve a mutual goal of sustainable and resilient power system. As the sustainability of the network depends on the reliable operations of each component in the network, it is required to monitor the performance and lifetime of the components existed in the network. One of the critical as well as costly components used to enhance the reliability and performance of the network is the battery energy storage system …

An Agent-Based Model To Study Competitive Construction Bidding And The Winner's Curse, Amr Elsayegh, Cihan H. Dagli, Islam H. El-Adaway

Engineering Management and Systems Engineering Faculty Research & Creative Works

Reverse auction theory is the basis for competitive construction bidding process. The lowest bid method is utilized for selecting contractors in public projects. The winning contractor having the lowest bid value could be cursed when the submitted bid value results in negative profits. This is caused by many factors such as the contractor's estimation accuracy and markup. This is addressed in this paper by providing a model simulating the construction competitive bidding and the occurrence of the winner's curse. To this end, the authors show the extent to which the winner's curse affects the status of contracting companies. The objectives …

Efficient Architecture Search For Deep Neural Networks, Ram Deepak Gottapu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper addresses the scalability challenge of automatic deep neural architecture search by implementing a parameter sharing approach with regularized genetic algorithm (RGE). The key idea is to use a regularized genetic algorithm (RGE) on a pre-determined template and discover a high-performance architecture by searching for the optimal chromosome. During evolution, each model corresponding to a discovered chromosome is trained for a fixed number of epochs to minimize a canonical cross-entropy loss on a given training dataset. Meanwhile, the performance of the trained model on validation dataset is used as a fitness value to perform the evolutions. Because of parameter …

Agent Based Modeling For Flood Inundation Mapping And Rerouting, Vinayaka Gude, Steven Corns, Cihan H. Dagli, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

Natural disasters like earthquakes and floods can have a serious impact on road networks, which are critical to supply chain infrastructure and to provide connectivity. These extreme events can result in isolating people in the affected area from hospitals and emergency response. This paper presents an agent-based model for understanding flood propagation and developing inundation mapping. The results from the mapping are used to identify the roads prone to floods based on elevation data and flood simulation. A simulation environment was set up in SUMO, and the costs associated with the traffic disruption are evaluated. This paper discusses the integration …

Modeling And Simulation Of A Robotic Bridge Inspection System, Md Monirul Karim, Cihan H. Dagli, Ruwen Qin

Engineering Management and Systems Engineering Faculty Research & Creative Works

Inspection and preservation of the aging bridges to extend their service life has been recognized as one of the important tasks of the State Departments of Transportation. Yet manual inspection procedure is not efficient to determine the safety status of the bridges in order to facilitate the implementation of appropriate maintenance. In this paper, a complex model involving a remotely controlled robotic platform is proposed to inspect the safety status of the bridges which will eliminate labor-intensive inspection. Mobile cameras from unmanned airborne vehicles (UAV) are used to collect bridge inspection data in order to record the periodic changes of …

Preface To The Special Issue: "Complex Adaptive Systems," Malvern, Pennsylvania, November 13-15, 2019, Nil Kilicay-Ergin, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

No abstract provided.

A System Dynamics Approach For Study Of Population Growth And The Residential Housing Market In The Us, Gasser Galal Ali, Islam H. El-Adaway, Cihan H. Dagli

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The US Consensus bureau estimated the total construction spending at 1,320,305 Million Dollars, in February 2020, with an increase of 1.1% since last February. The construction market is large, and risky. Prediction of the market behavior, for several years ahead, is needed in order to take strategic investment decision for long and expensive projects. The goal of this research is to study the relationship between population growth and the housing market. To that end, a system dynamics model is developed. System dynamics is a top-down approach that starts with the high-level behavior of a complex system to simulate the behavior …

A System Dynamics Model For Construction Safety Behavior, Mohamad Abdul Nabi, Islam H. El-Adaway, Cihan H. Dagli

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Construction Industry has always been reputed by its high incident rates and poor safety performance. Construction accidents are, in most cases, resulted from the unsafe behaviors of construction workers on site. The study of workers' behavior is crucial in order to understand the causation of unsafe behaviors. Therefore, the objective of this paper is to simulate construction safety behavior in order to predict the number of safety incidents and better understand their causation factors. The simulation model illustrates how construction system influences construction labors on site in terms of unsafe behavior. The standard leading indicators of safety performance are first …

A System-Of-Systems Model To Simulate The Complex Emergent Behavior Of Vehicle Traffic On An Urban Transportation Infrastructure Network, Rayan Assaad, Cihan H. Dagli, Islam H. El-Adaway

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transportation agencies face escalating challenges in forecasting the traffic demand. Traditional prediction methods focused on individual transportation sectors and failed to study the inter-dependencies between the different transportation systems. Hence, there is a need for more advanced and holistic modeling techniques. To this end, this paper models and analyses an urban transportation system-of-systems incorporating seven various systems: population and GDP, CO₂ emission, gasoline price and total vehicle trips, traffic demand, public and private transportation, transportation investment, and traffic congestion. Accordingly, this research simulates transportation networks as a collection of task-oriented systems that combine their resources to form a complex …

An Agent-Based Approach To Artificial Stock Market Modeling, Samuel Vanfossan, Cihan H. Dagli, Benjamin J. Kwasa

Engineering Management and Systems Engineering Faculty Research & Creative Works

Consumer stock markets have long been a target of modeling efforts for the economic gains anticipatorily enabled by well-performing models. Aimed at identifying strategies capable of achieving desired returns, many modeling approaches have attempted to capture the innumerable and intricate complexities present within these adaptive socio-technical systems. Decreasingly constrained by available computation power, contemporary models have grown in sophistication to include several of the features present in de facto market systems. However, these models require extensive effort to dictate the variety of states, behaviors, and adaptations that entities of the system may exhibit. Mandating the development of complex formulas and …

Exploring The Relationship Between Sustainable Projects And Institutional Isomorphisms: A Project Typology, Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi

Engineering Management and Systems Engineering Faculty Research & Creative Works

With the increase in awareness about the wide range of issues and adverse effects associated with the use of conventional energy sources came an increase in project management research related to sustainability and sustainable development. Part of that research is devoted to the development of sustainable project typologies that classify projects based on a variety of external factors that can significantly impact these projects. This research focuses on developing a sustainable project typology that classifies sustainable projects based on the external institutional influences. The typology explores the influence of the coercive, normative, and mimetic institutional isomorphisms on the expected level …

Comparison Of Mpi And Spark For Data Science Applications, Manvi Saxena, Shweta Jha, Saba Khan, John Rodgers, Peggy Lindner, Edgar Gabriel

Engineering Management and Systems Engineering Faculty Research & Creative Works

Data Science applications represent a growing fraction of the scientific computing workload, many of them written in Python. The goal of this paper is to compare two popular parallel programming models, namely MPI and Apache Spark for Python based Data Science applications. The paper presents communication and file I/O microbenchmarks to evaluate the MPI support for Python applications and uses two applications use-cases from Natural Language Processing to compare the performance of the MPI and the Spark versions. Our results indicate that the MPI version shows better scalability and performance than the PySpark version of the code. On the other …

Flood Prediction And Uncertainty Estimation Using Deep Learning, Vinayaka Gude, Steven Corns, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

Floods are a complex phenomenon that are difficult to predict because of their non-linear and dynamic nature. Therefore, flood prediction has been a key research topic in the field of hydrology. Various researchers have approached this problem using different techniques ranging from physical models to image processing, but the accuracy and time steps are not sufficient for all applications. This study explores deep learning techniques for predicting gauge height and evaluating the associated uncertainty. Gauge height data for the Meramec River in Valley Park, Missouri was used to develop and validate the model. It was found that the deep learning …

Embedded Spectral Descriptors: Learning The Point-Wise Correspondence Metric Via Siamese Neural Networks, Zhiyu Sun, Yusen He, Andrey Gritsenko, Amaury Lendasse, Stephen Baek

Engineering Management and Systems Engineering Faculty Research & Creative Works

A Robust and Informative Local Shape Descriptor Plays an Important Role in Mesh Registration. in This Regard, Spectral Descriptors that Are based on the Spectrum of the Laplace-Beltrami Operator Have Been a Popular Subject of Research for the Last Decade Due to their Advantageous Properties, Such as Isometry Invariance. Despite Such, However, Spectral Descriptors Often Fail to Give a Correct Similarity Measure for Nonisometric Cases Where the Metric Distortion between the Models is Large. Hence, They Are Not Reliable for Correspondence Matching Problems When the Models Are Not Isometric. in This Paper, it is Proposed a Method to Improve the …

Computational Model For Neural Architecture Search, Ram Deepak Gottapu

Doctoral Dissertations

"A long-standing goal in Deep Learning (DL) research is to design efficient architectures for a given dataset that are both accurate and computationally inexpensive. At present, designing deep learning architectures for a real-world application requires both human expertise and considerable effort as they are either handcrafted by careful experimentation or modified from a handful of existing models. This method is inefficient as the process of architecture design is highly time-consuming and computationally expensive.

The research presents an approach to automate the process of deep learning architecture design through a modeling procedure. In particular, it first introduces a framework that treats …

Real-Time Assembly Operation Recognition With Fog Computing And Transfer Learning For Human-Centered Intelligent Manufacturing, Wenjin Tao, Md Al-Amin, Haodong Chen, Ming-Chuan Leu, Zhaozheng Yin, Ruwen Qin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In a human-centered intelligent manufacturing system, every element is to assist the operator in achieving the optimal operational performance. The primary task of developing such a human-centered system is to accurately understand human behavior. In this paper, we propose a fog computing framework for assembly operation recognition, which brings computing power close to the data source in order to achieve real-time recognition. For data collection, the operator's activity is captured using visual cameras from different perspectives. For operation recognition, instead of directly building and training a deep learning model from scratch, which needs a huge amount of data, transfer learning …

Predicting Complex System Behavior Using Hybrid Modeling And Computational Intelligence, Vinayaka Gude

Doctoral Dissertations

“Modeling and prediction of complex systems is a challenging problem due to the sub-system interactions and dependencies. This research examines combining various computational intelligence algorithms and modeling techniques to provide insights into these complex processes and allow for better decision making. This hybrid methodology provided additional capabilities to analyze and predict the overall system behavior where a single model cannot be used to understand the complex problem. The systems analyzed here are flooding events and fetal health care. The impact of floods on road infrastructure is investigated using graph theory, agent-based traffic simulation, and Long Short-Term Memory deep learning to …

Development Of A System Architecture For The Prediction Of Student Success Using Machine Learning Techniques, Tatiana A. Cardona

Doctoral Dissertations

“ The goals of higher education have evolved through time based on the impact that technology development and industry have on productivity. Nowadays, jobs demand increased technical skills, and the supply of prepared personnel to assume those jobs is insufficient. The system of higher education needs to evaluate their practices to realize the potential of cultivating an educated and technically skilled workforce. Currently, completion rates at universities are too low to accomplish the aim of closing the workforce gap. Recent reports indicate that 40 percent of freshman at four-year public colleges will not graduate, and rates of completion are even …

An Approach To System Of Systems Resiliency Using Architecture And Agent-Based Behavioral Modeling, Paulette Bootz Acheson

Doctoral Dissertations

”In today’s world it is no longer a question of whether a system will be compromised but when the system will be compromised. Consider the recent compromise of the Democratic National Committee (DNC) and Hillary Clinton emails as well as the multiple Yahoo breaches and the break into the Target customer database. The list of exploited vulnerabilities and successful cyber-attacks goes on and on. Because of the amount and frequency of the cyber-attacks, resiliency has taken on a whole new meaning. There is a new perspective within defense to consider resiliency in terms of Mission Success.

This research develops a …

Development Of A Modeling Algorithm To Predict Lean Implementation Success, Richard Charles Barclay

Doctoral Dissertations

”Lean has become a common term and goal in organizations throughout the world. The approach of eliminating waste and continuous improvement may seem simple on the surface but can be more complex when it comes to implementation. Some firms implement lean with great success, getting complete organizational buy-in and realizing the efficiencies foundational to lean. Other organizations struggle to implement lean. Never able to get the buy-in or traction needed to really institute the sort of cultural change that is often needed to implement change. It would be beneficial to have a tool that organizations could use to assess their …

Enabling Flexibility Through Strategic Management Of Complex Engineering Systems, Walter Louis Barnes Ii

Doctoral Dissertations

”Flexibility is a highly desired attribute of many systems operating in changing or uncertain conditions. It is a common theme in complex systems to identify where flexibility is generated within a system and how to model the processes needed to maintain and sustain flexibility. The key research question that is addressed is: how do we create a new definition of workforce flexibility within a human-technology-artificial intelligence environment?

Workforce flexibility is the management of organizational labor capacities and capabilities in operational environments using a broad and diffuse set of tools and approaches to mitigate system imbalances caused by uncertainties or changes. …

The Development Of A Project Typology And Selection Tool To Improve Decision-Making In Sustainable Projects, Rakan Alyamani

Doctoral Dissertations

"Decision-making in sustainable projects is a complex and challenging process, especially during the initiating and planning phases of project development, due to influence from several external factors, as well as the uncertain environments surrounding their creation. It is essential to improve the decision-making process in sustainable projects during these two phases by relying on strong decision-making tools. The first contribution in this work identifies gaps in the literature of how institutionalization can impact sustainable projects through the effects of institutional isomorphisms from institutional theory. This helps decision makers better understand the relationship between institutionalization and sustainable projects. The second contribution …

Critical Success Factors And Risk Mitigation Strategy For New Product Development, Rodney A. Ewing

Doctoral Dissertations

”Success in new product development (NPD) offers a competitive and comparative advantage in the marketplace. A primary objective in an NPD project is to launch world class products with minimal risk. To deliver the superior quality and performance customers require, a company must develop the right NPD structure and framework for seamless execution by the NPD project teams throughout the product lifecycle. Companies must understand how to identify and mitigate risk to enable the success of their NPD projects. The costs to develop new products are often a considerable portion of an organization’s budget; however, studies have shown only 60 …

Balancing Labor Requirements In A Manufacturing Environment, Patrick Bernard Dwyer

Doctoral Dissertations

“This research examines construction environments within manufacturing facilities, specifically semiconductor manufacturing facilities, and develops a new optimization method that is scalable for large construction projects with multiple execution modes and resource constraints. The model is developed to represent real-world conditions in which project activities do not have a fixed, prespecified duration but rather a total amount of work that is directly impacted by the level of resources assigned. To expand on the concept of resource driven project durations, this research aims to mimic manufacturing construction environments by allowing a non-continuous resource allocation to project tasks. This concept allows for resources …

Microgrid Design, Control, And Performance Evaluation For Sustainable Energy Management In Manufacturing, Md. Monirul Islam

Doctoral Dissertations

"This research studies the capacity sizing, control strategies, and performance evaluation of the microgrids with hybrid renewable sources for manufacturing end use customers towards a distributed sustainable energy system paradigm. Microgrid technology has been widely investigated and applied in commercial and residential sector, while for manufacturers, it has been less explored and utilized. To fill the gap, the dissertation first proposes a cost-effective sizing model to identify the capacities as well as control strategies of the components in microgrids considering a commonly used energy tariff, i.e., Time of Use (TOU). Then, the sizing model is extended by integrating control strategies …

Integrating Resilience Into Military Infrastructure Mission Assurance Assessments And Decision Making, John Richards

Doctoral Dissertations

“This research created the Mission Assurance Resilience Matrix, a decision framework that integrates existing infrastructure assessment methods with emerging resilience research to model resilience under uncertainty as part of a detailed infrastructure management system. This framework enables military decision makers to easily visualize deficiencies in infrastructure resilience and assess where to most efficiently allocate resources. This research further extends results by including modules on training and education as a component of the scope of work.

There are three significant contributions of this research. The first identifies the gaps of how and where modeling under uncertainty, infrastructure systems management, and resilient …

Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis

Engineering Management and Systems Engineering Faculty Research & Creative Works

The article "Better beware: comparing metacognition for phishing and legitimate emails", written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 20 July 2019 without open access.

Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. However, few studies have focused on forecasting daily stock market returns, especially when using powerful machine learning techniques, such as deep neural networks (DNNs), to perform the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation function, and model parameters, with their performance depending on the format of the data representation. This paper presents a comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 …

Hedge Fund Replication Using Strategy Specific Factors, Sujit Subhash, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction, allowing them to better manage portfolio risk. However, the financial crisis of 2008 has heightened investor sensitivity to the high fees, illiquidity, lack of transparency, and lockup periods typically associated with hedge funds. Hedge fund replication products, or clones, seek to answer these challenges by providing daily liquidity, transparency, and immediate exposure to a desired hedge fund strategy. Nonetheless, although lowering cost and adding simplicity by using a common set of factors, traditional replication …

Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis

Engineering Management and Systems Engineering Faculty Research & Creative Works

Every electronic message poses some threat of being a phishing attack. If recipients underestimate that threat, they expose themselves, and those connected to them, to identity theft, ransom, malware, or worse. If recipients overestimate that threat, then they incur needless costs, perhaps reducing their willingness and ability to respond over time. In two experiments, we examined the appropriateness of individuals' confidence in their judgments of whether email messages were legitimate or phishing, using calibration and resolution as metacognition metrics. Both experiments found that participants had reasonable calibration but poor resolution, reflecting a weak correlation between their confidence and knowledge. These …