Browsing Industrial engineering by Title
Now showing items 27-46 of 76
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Improving Efficiency in Allocating Pediatric Ambulatory Care Clinics
Low utilized resources is a common problem in the health care sector. As health care costs and the need for more efficient operations increases, managers are looking for new methods to increase the utilization of their ... -
Incorporating Expert Knowledge into Rule Learning via Reinforcement Learning
Rule learning algorithms have great interpretability compared with other machine learning models. They also express strong power in discovering interactions between diverse variables. However, the performance of rule ... -
Information theoretic learning methods for Markov decision processes with parametric uncertainty
Markov decision processes (MDPs) model a class of stochastic sequential decision problems with applications in engineering, medicine, and business analytics. There is considerable interest in the literature in MDPs with ... -
Information-directed policy sampling for episodic Bayesian Markov decision processes
The research objective of this dissertation is to apply information theoretic methods to design provably efficient approximate solution algorithms for Markov decision processes (MDPs), partially observable MDPs (POMDPs), ... -
Integrated Approach and Analysis of Reliability, Robustness, Resilience and Infrastructure Applications
A rising number of man-made and natural disasters have occurred since the beginning of the 21st century in the United States. Improving the quality of civil infrastructure in an increasingly hazardous environment has become ... -
An Investigation of Applications of Artificial Neural Networks in Medical Prognostics
(2013-02-25)During the course of care, patients frequently develop escalating health problems that lead to medical complications, costly treatments, severe pains, disabilities and even death. Predicting such escalations provides ... -
Large-Scale Personalized Health Surveillance by Collaborative Learning and Selective Sensing
Recent advance in sensing and information technology provides abundance of risk predictive data, leading to the development of personalized health surveillance. However, effective use of the sensing technology is prohibited ... -
Learning Rule-based Decision-Making Systems from Heterogeneous Longitudinal Data
Recent advances in sensing technology have greatly expanded our capacities to collect data from a diverse pool of patients in unprecedented spatial-temporal resolutions and from a variety of different sources. These ... -
Methodology for the Preliminary Design of a System of Integrated Clinical Laboratories
Clinical laboratory testing is used for deriving patient diagnoses, monitoring treatment and predicting the expected outcome of a disease (prognosis). Thus, the performance of clinical laboratories is critical for our ... -
Mixed Integer Quadratic Optimization for Learning Directed Acyclic Graphs from Continuous Data
The study of probabilistic graphical models (PGMs) is an essential topic in statistics and machine learning fields. Bayesian networks (BNs), arguably one of the most central classes of PGMs, is frequently used to represent ... -
Modeling Depression Progression Dynamics from Electronic Health Record
To assess and monitor the progression dynamics of patients' depression severity conditions, Markov models are refined from other disease progression modeling methodologies to identify the characteristics and evolvement of ... -
Modeling driver behavior and their interactions with driver assistance systems
As vehicle automation becomes increasingly prevalent and capable, drivers have the opportunity to delegate primary driving task control to automated systems. In recent years, significant efforts have been placed on developing ... -
Modeling Heterogeneous User Behavior in Interactive Systems by Graphical Model and Collaborative Learning Framework
In recent years, the rapid technological innovations of smart personal technologies have given rise to the growth of smart apps that can interact with users and implement personalized incentives to coordinate and change ... -
Modeling memory processes in phishing decision making using instance based learning and natural language processing
Phishing is a type of social engineering attack that uses psychological manipulations to influence people into revealing their personal information. Despite advancements in security technologies, phishing attacks continue ... -
Modeling Students’ Procrastination in Higher Education: Causes, Outcomes, and Prediction
Students spend little time completing tasks when deadlines are far off; however, theytend to increase their work amounts as deadline approaches. This phenomenon, which is called deadline rush, can be modeled by exponential ... -
Non-invasive Real-time Assessment of Muscle Fatigue during Computer Use: Using Mouse Button-Click and Keystroke Durations
(2012-09-13)Musculoskeletal disorders (MSDs) account for a large proportion of occupational injuries. As the computer has become ubiquitous in office work environments, so have computer-related MSDs. Since most work-related MSDs ... -
Objective Methods for Characterizing Physical Exposures which may contribute to Work-related Musculoskeletal Disorders in Agricultural Workers
US Migrant farmworkers perform physically-demanding work but are less likely to report poor working conditions, which exposes them to greater risk for musculoskeletal disorders (e.g., prolonged non-neutral postures, ... -
Ontology-driven Education: Teaching Anatomy with Intelligent 3D Games on the Web
Human anatomy is a challenging and intimidating subject whose understanding is essential to good medical practice, taught primarily using a combination of lectures and the dissection of human cadavers. Lectures are cheap ... -
Optimization and Machine Learning Frameworks for Complex Network Analysis
Networks are all around us, and they may be connections of tangible objects in the Euclidean space such as electric power grids, the Internet, highways systems, etc. Among the wide range of areas in the network analysis, ... -
Optimization and Machine Learning Methods for Medical and Healthcare Applications
The increasing amounts of data being gathered in healthcare and medical systems and the convergence of different domains are leading medical and healthcare research to a new direction of precision and personalized medicine. ...