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Operations Research, Systems Engineering and Industrial Engineering Commons™
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Articles 1 - 7 of 7
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Integrated Cyberattack Detection And Handling For Nonlinear Systems With Evolving Process Dynamics Under Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand
Integrated Cyberattack Detection And Handling For Nonlinear Systems With Evolving Process Dynamics Under Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
Safety-critical processes are becoming increasingly automated and connected. While automation can increase effciency, it brings new challenges associated with guaranteeing safety in the presence of uncertainty especially in the presence of control system cyberattacks. One of the challenges for developing control strategies with guaranteed safety and cybersecurity properties under suffcient conditions is the development of appropriate detection strategies that work with control laws to prevent undetected attacks that have immediate closed-loop stability consequences. Achieving this, in the presence of uncertainty brought about by plant/model mismatch and process dynamics that can change with time, requires a fundamental understanding of the characteristics …
Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad
Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad
Wayne State University Dissertations
Massive amount of electronic medical records (EMRs) accumulating from patients and populations motivates clinicians and data scientists to collaborate for the advanced analytics to create knowledge that is essential to address the extensive personalized insights needed for patients, clinicians, providers, scientists, and health policy makers. Learning from large and complicated data is using extensively in marketing and commercial enterprises to generate personalized recommendations. Recently the medical research community focuses to take the benefits of big data analytic approaches and moves to personalized (precision) medicine. So, it is a significant period in healthcare and medicine for transferring to a new paradigm. …
The Impact Of Machine Learning Algorithms On Benchmarking Process In Healthcare Service Delivery, Egbe-Etu Emmanuel Etu
The Impact Of Machine Learning Algorithms On Benchmarking Process In Healthcare Service Delivery, Egbe-Etu Emmanuel Etu
Wayne State University Theses
Currently, organizations have adopted and implemented a variety of innovative quality management philosophies, approaches, and techniques to stay competitive in an ever-changing global economy. Benchmarking is one of such techniques deployed by organizations to stay competitive. The motivation for this research stems from a real-world problem being faced by hospitals in the healthcare industry who have amassed a ton of data and want to embark on benchmarking project to assess the performance of the emergency departments due to challenges faced with poor management of operations which has led to high patient boarding rates, high patient wait-times, poor quality service, low …
A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park
A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park
Wayne State University Dissertations
Numerous and various research projects have been conducted to utilize historical manufacturing process data in product design. These manufacturing process data often contain data inconsistencies, and it causes challenges in extracting useful information from the data. In resistance spot welding (RSW), data inconsistency is a well-known issue. In general, such inconsistent data are treated as noise data and removed from the original dataset before conducting analyses or constructing prediction models. This may not be desirable for every design and manufacturing applications since every data can contain important information to further explain the process. In this research, we propose a prediction …
Predictive Analytics For Disease Condition Of Patients In Emergency Department, Azade Tabaie
Predictive Analytics For Disease Condition Of Patients In Emergency Department, Azade Tabaie
Wayne State University Theses
Emergency Departments (EDs) in hospitals are experiencing severe crowding and prolonged patient waiting times. The reported crowding in hospitals shows patients in hospital hallways, long waiting times and full occupancy of ED beds. ED crowding has several potential unfavorable effects including patients and staff frustration, lower patient satisfaction and poor health outcomes. The primary motivations behind this study are shortening the patients’ waiting time and improving patient satisfaction and level of care.
The very initial interaction between clinicians and a patient is recorded on nurse triage notes which contain details of the reason for patient’s visit including specific symptoms and …
A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina
A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina
Wayne State University Dissertations
Cross-selling and product bundling are prevalent strategies in the retail sector. Instead of static bundling offers, i.e. giving the same offer to everyone, personalized dynamic cross-selling generates targeted bundle offers and can help maximize revenues and profits. In resolving the two basic problems of dynamic cross-selling, which involves selecting the right complementary products and optimizing the discount, the issue of computational complexity becomes central as the customer base and length of the product list grows. Traditional recommender systems are built upon simple collaborative filtering techniques, which exploit the informational cues gained from users in the form of product ratings and …
Task Analysis, Modeling, And Automatic Identification Of Elemental Tasks In Robot-Assisted Laparoscopic Surgery, Lavie Pinchas Golenberg
Task Analysis, Modeling, And Automatic Identification Of Elemental Tasks In Robot-Assisted Laparoscopic Surgery, Lavie Pinchas Golenberg
Wayne State University Dissertations
Robotic microsurgery provides many advantages for surgical operations, including tremor filtration, an increase in dexterity, and smaller incisions. There is a growing need for a task analyses on robotic laparoscopic operations to understand better the tasks involved in robotic microsurgery cases. A few research groups have conducted task observations to help systems automatically identify surgeon skill based on task execution. Their gesture analyses, however, lacked depth and their class libraries were composed of ambiguous groupings of gestures that did not share contextual similarities.
A Hierarchical Task Analysis was performed on a four-throw suturing task using a robotic microsurgical platform. Three …