Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam

Research Collection School Of Computing and Information Systems

Hospitals have been trying to improve the utilization of operating rooms as it affects patient satisfaction, surgery throughput, revenues and costs. Surgical prediction model which uses post-surgery data often requires high-dimensional data and contains key predictors such as surgical team factors which may not be available during the surgical listing process. Our study considers a two-step data-mining model which provides a practical, feasible and parsimonious surgical duration prediction. Our model first leverages on domain knowledge to provide estimate of the first surgeon rank (a key predicting attribute) which is unavailable during the listing process, then uses this predicted attribute and …

Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin

Computer Science Faculty Research & Creative Works

Production innovations are occurring faster than ever. Manufacturing workers thus need to frequently learn new methods and skills. In fast changing, largely uncertain production systems, manufacturers with the ability to comprehend workers' behavior and assess their operation performance in near real-time will achieve better performance than peers. Action recognition can serve this purpose. Despite that human action recognition has been an active field of study in machine learning, limited work has been done for recognizing worker actions in performing manufacturing tasks that involve complex, intricate operations. Using data captured by one sensor or a single type of sensor to recognize …

Joint Manufacturing And Onsite Microgrid System Control Using Markov Decision Process And Neural Network Integrated Reinforcement Learning, Wenqing Hu, Zeyi Sun, Y. Zhang, Y. Li

Mathematics and Statistics Faculty Research & Creative Works

Onsite microgrid generation systems with renewable sources are considered a promising complementary energy supply system for manufacturing plant, especially when outage occurs during which the energy supplied from the grid is not available. Compared to the widely recognized benefits in terms of the resilience improvement when it is used as a backup energy system, the operation along with the electricity grid to support the manufacturing operations in non-emergent mode has been less investigated. In this paper, we propose a joint dynamic decision-making model for the optimal control for both manufacturing system and onsite generation system. Markov Decision Process (MDP) is …

Decision Making For Improving Maritime Traffic Safety Using Constraint Programming, Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Maritime navigational safety is of utmost importance to prevent vessel collisions in heavily trafficked ports, and avoid environmental costs. In case of a likely near miss among vessels, port traffic controllers provide assistance for safely navigating the waters, often at very short lead times. A better strategy is to avoid such situations from even happening. To achieve this, we a) formalize the decision model for traffic hotspot mitigation including realistic maritime navigational features and constraints through consultations with domain experts; and b) develop a constraint programming based scheduling approach to mitigate hotspots. We model the problem as a variant of …

Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang

Research Collection School Of Computing and Information Systems

Items adopted by a user over time are indicative ofthe underlying preferences. We are concerned withlearning such preferences from observed sequencesof adoptions for recommendation. As multipleitems are commonly adopted concurrently, e.g., abasket of grocery items or a sitting of media consumption, we deal with a sequence of baskets asinput, and seek to recommend the next basket. Intuitively, a basket tends to contain groups of relateditems that support particular needs. Instead of recommending items independently for the next basket, we hypothesize that incorporating informationon pairwise correlations among items would help toarrive at more coherent basket recommendations.Towards this objective, we develop a …

Direct Assessment Of Entrepreneurial Minded Learning Through Integrated E-Learning Modules, Aadtiyasinh Rana

Master's Theses

Entrepreneurial Minded Learning (EML) has a significant emphasis in engineering education

today. Several approaches have been used to assess the impact of various EML approaches. Many indirect assessment techniques have been used and a few direct assessment techniques have been developed. The work presented in this thesis investigates the effectiveness of two specific measurement methods to quantify entrepreneurial minded learning in students.

The University of New Haven has adopted the approach of integrating e-learning modules on entrepreneurial topics and related contextual activities into courses as the primary approach of developing an entrepreneurial mindset (EM) in students. This study focuses on …

A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation …

Preface, Cihan H. Dagli, Gursel A. Suer

Engineering Management and Systems Engineering Faculty Research & Creative Works

No abstract provided.

System Of Systems (Sos) Architecture For Digital Manufacturing Cybersecurity, Lirim Ashiku, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Technology advancements of real time connectivity and computing powers has evolved the way people manage activities triggering heavy reliance on smart devices. This has reshaped the ability to memorize crucial information, instead accumulate the information into devices allowing real-time fingertip access when needed. Inability to access such information when needed is routinely assumed with device malfunctioning bypassing the probability of compromise, but what if the information is now being accessed by adversaries depriving the data-owner access to crucial information? Cyber manufacturing systems are not immune from these issues. It is possible to approach this problem as generating SoS meta-architecture. In …

Automatic Methods To Enhance The Quality Of Colonoscopy Video, Nidhal Kareem Shukur Azawi

Graduate Theses and Dissertations

Colonoscopy is a form of endoscopy because it uses colonoscopy device to help the doctor to understand a colon patient. Enhancing the quality of Colonoscopy images is a challenge because of the wet and dynamic environment inside the colon causes many problems even the colonoscope devise has a good quality. Some of these problems are blurriness, specular highlights shiny areas.

In this work, different kinds of techniques have been investigated in order to improve the quality of colonoscopy images. Also, variety of preprocessing approaches (removing bad images, resizing images, median filtration with and without image resizing) have been conducted to …

Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization Under Uncertainty, Jonathan David Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Urban law enforcement agencies are under great pressure to respond to emergency incidents effectively while operating within restricted budgets. Minutes saved on emergency response times can save lives and catch criminals, and a responsive police force can deter crime and bring peace of mind to citizens. To efficiently minimize the response times of a law enforcement agency operating in a dense urban environment with limited manpower, we consider in this paper the problem of optimizing the spatial and temporal deployment of law enforcement agents to predefined patrol regions in a real-world scenario informed by machine learning. To this end, we …

Control Of Infectious Diseases In A Metapopulation, Ceyda Best

All Dissertations

With the motivation of the complex infectious disease control problem, we provide two different approaches to model the resource allocation problem to control an epidemic in a metapopulation. All of our models utilize a detailed stochastic simulation model that is validated with the data from the 2014 Ebola epidemic. This simulation model provides a tool for comparing the performance of different policies.

The first model defines a dynamic allocation problem, which is modeled by a Markov Decision Process, and aims to find feasible and effective quarantine policies to control an epidemic with limited resources. We assume that the populations share …

Simulated Annealing For The Multi-Vehicle Cyclic Inventory Routing Problem, Aldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a single objective optimization problem. A subset of customers is selected for each vehicle including the quantity to be delivered to each customer. For each vehicle, a cyclic distribution plan is developed. We construct a mathematical programming model and propose a simulated annealing (SA) metaheuristic for solving both SV-CIRP and MV-CIRP. For SV-CIRP, experimental results on benchmark …

Measuring Risks Of Interdependencies In Enterprise Systems: An Application To Ghana’S Salt Enterprise, Yaw Mensah

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation describes the use of Functional Dependency Network Analysis (FDNA) for modeling risks resulting from dependencies among elements of enterprise systems with application to salt processing enterprise in Ghana. FDNA was developed to model dependencies among members of enterprise systems by highlighting two dimensions of dependency: strength and criticality. Nonetheless, the concepts and analytics for these two dimensions of dependencies needed further development and generalization in the context of project management and systems development in developing countries.

Managing risks within the interdependency in enterprise systems through integration will help improve global economic growth. Coherent theory for enterprise integration must …

Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Mid-late season weeds are those that escape the early season herbicide applications and those that emerge late in the season. They might not affect the crop yield, but if uncontrolled, will produce a large number of seeds causing problems in the subsequent years. In this study, high-resolution aerial imagery of mid-season weeds in soybean fields was captured using an unmanned aerial vehicle (UAV) and the performance of two different automated weed detection approaches – patch-based classification and object detection was studied for site-specific weed management. For the patch-based classification approach, several conventional machine learning models on Haralick texture features were …

Minimodal: Dimensional Domain Of Miniature Shipping Containers For Intermodal Freight Transportation, Lee Stapley

Ursidae: The Undergraduate Research Journal at the University of Northern Colorado

This study explores the feasibility of miniature shipping container usage within existing intermodal transportation (IT) supply chains. Smaller intermodal container shipments may help realign freight shipments with the most efficient transportation mode, rail. These containers embolden the dimensional domain (DD) of shipping. The shipping container dimensional domain (container size variation and modal fluidity) is widespread and results in shipments that are often larger or more infrequent than needed. The DD impacts transport mode, shipping frequency, shipment velocity, intermodal supply chain accessibility, and regional shipping networks. This study suggests that container size impacts the DD and, therefore, mode choice. As miniature …

Keeping Humans In The Loop: Pooling Knowledge Through Artificial Swarm Intelligence To Improve Business Decision Making, Lynn E. Metcalf, David A. Askay, Louis B. Rosenberg

Industrial Technology and Packaging

This article explores how a collaboration technology called Artificial Swarm Intelligence (ASI) addresses the limitations associated with group decision making, amplifies the intelligence of human groups, and facilitates better business decisions. It demonstrates of how ASI has been used by businesses to harness the diverse perspectives that individual participants bring to groups and to facilitate convergence upon decisions. It advances the understanding of how artificial intelligence (AI) can be used to enhance, rather than replace, teams as they collaborate to make business decisions.

Factors Influencing Revenue Collection For Preventative Maintenance Of Community Water Systems: A Fuzzy-Set Qualitative Comparative Analysis, Liesbet Olaerts, Jeffrey P. Walters, Karl G. Linden, Amy Javernick-Will, Adam Harvey

Faculty Publications - Biomedical, Mechanical, and Civil Engineering

This study analyzed combinations of conditions that influence regular payments for water service in resource-limited communities. To do so, the study investigated 16 communities participating in a new preventive maintenance program in the Kamuli District of Uganda under a public–private partnership framework. First, this study identified conditions posited as important for collective payment compliance from a literature review. Then, drawing from data included in a water source report and by conducting semi-structured interviews with households and water user committees (WUC), we identified communities that were compliant with, or suspended from, preventative maintenance service payments. Through qualitative analyses of these data …

Seven Hci Grand Challenges, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie Chen, Jianming Dong, Vincent Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Fu, Yinni Guo, Don Harris, Andri Ioannou, Kyeong-Ah (Kate) Jeong, Shin'ichi Konomi, Heidi Kromker, Masaaki Kurosu, James Lewis, Aaron Marcus, Gabriele Meiselwitz, Abbas Moallem, Hirohiko Mori, Fiona Fui-Hoon Nah, Stavroula Ntoa, Pei-Luen Rau, Dylan Schmorrow, Keng Siau, Norbert Streitz, Wentao Wang, Sakae Yamamoto, Panayiotis Zaphiris, Jia Zhou

Faculty Publications

This article aims to investigate the Grand Challenges which arise in the current and emerging landscape of rapid technological evolution towards more intelligent interactive technologies, coupled with increased and widened societal needs, as well as individual and collective expectations that HCI, as a discipline, is called upon to address. A perspective oriented to humane and social values is adopted, formulating the challenges in terms of the impact of emerging intelligent interactive technologies on human life both at the individual and societal levels. Seven Grand Challenges are identified and presented in this article: Human-Technology Symbiosis; Human-Environment Interactions; Ethics, Privacy and Security; …