Statistical Models Commons^™

Dynamic Influence Diagram-Based Deep Reinforcement Learning Framework And Application For Decision Support For Operators In Control Rooms, Joseph Mietkiewicz, Ammar N. Abbas, Chidera Winifred Amazu, Anders L. Madsen, Gabriele Baldissone

Articles

In today’s complex industrial environment, operators are often faced with challenging situations that require quick and accurate decision-making. The human-machine interface (HMI) can display too much information, leading to information overload and potentially compromising the operator’s ability to respond effectively. To address this challenge, decision support models are needed to assist operators in identifying and responding to potential safety incidents. In this paper, we present an experiment to evaluate the effectiveness of a recommendation system in addressing the challenge of information overload. The case study focuses on a formaldehyde production simulator and examines the performance of an improved Human-Machine Interface …

Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine

Faculty Publications

Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …

Constitutive Model Of Lateral Unloading Creep Of Soft Soil Under Excess Pore Water Pressure, Wei Huang, Kejun Wen, Xiaojia Deng, Junjie Li, Zhijian Jiang, Yang Li, Lin Li, Farshad Amini

Civil and Architectural Engineering Faculty Research

Presented in this paper is a study on the lateral unloading creep tests under different excess pore water pressures. The marine sedimentary soft soil in Shenzhen, China, was selected in this study. The results show that the excess pore water pressure plays a significant role in enhancing the unloading creep of soft soil. Higher excess pore water pressure brings more obvious creep deformation of soft soil and lower ultimate failure load. Meanwhile, the viscoelastic and the viscoplastic modulus of soft soil were found to exponentially decline with creep time. A modified merchant model and a combined model of the modified …

Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang

FIU Electronic Theses and Dissertations

Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …

Measuring Localization Confidence For Quantifying Accuracy And Heterogeneity In Single-Molecule Super-Resolution Microscopy, Hesam Mazidi, Tianben Ding, Arye Nehorai, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We present a computational method, termed Wasserstein-induced flux (WIF), to robustly quantify the accuracy of individual localizations within a single-molecule localization microscopy (SMLM) dataset without ground- truth knowledge of the sample. WIF relies on the observation that accurate localizations are stable with respect to an arbitrary computational perturbation. Inspired by optimal transport theory, we measure the stability of individual localizations and develop an efficient optimization algorithm to compute WIF. We demonstrate the advantage of WIF in accurately quantifying imaging artifacts in high-density reconstruction of a tubulin network. WIF represents an advance in quantifying systematic errors with unknown and complex distributions, …

Conditional Survival Analysis For Concrete Bridge Decks, Azam Nabizadeh, Habib Tabatabai, Mohammad A. Tabatabai

Civil and Environmental Engineering Faculty Articles

Bridge decks are a significant factor in the deterioration of bridges, and substantially affect long-term bridge maintenance decisions. In this study, conditional survival (reliability) analysis techniques are applied to bridge decks to evaluate the age at the end of service life using the National Bridge Inventory records. As bridge decks age, the probability of survival and the expected service life would change. The additional knowledge gained from the fact that a bridge deck has already survived a specific number of years alters (increases) the original probability of survival at subsequent years based on the conditional probability theory. The conditional expected …

Context-Aware Personalized Point-Of-Interest Recommendation System, Ramesh Raj Baral

FIU Electronic Theses and Dissertations

The increasing volume of information has created overwhelming challenges to extract the relevant items manually. Fortunately, the online systems, such as e-commerce (e.g., Amazon), location-based social networks (LBSNs) (e.g., Facebook) among many others have the ability to track end users' browsing and consumption experiences. Such explicit experiences (e.g., ratings) and many implicit contexts (e.g., social, spatial, temporal, and categorical) are useful in preference elicitation and recommendation. As an emerging branch of information filtering, the recommendation systems are already popular in many domains, such as movies (e.g., YouTube), music (e.g., Pandora), and Point-of-Interest (POI) (e.g., Yelp).

The POI domain has many …

Pawnee Dam Inflow Design Flood (Idf) Update And Stage-Frequency Curve Development Using Rmcrfa, Jennifer P. Christensen, Joshua J. Melliger

United States Geological Survey: Water Reports and Publications

Pawnee Dam is one of the ten Salt Creek Dams designed and built in the 1960s to mitigate flooding in Lincoln, Nebraska. This short paper illustrates the update of the Pawnee Dam inflow design flood (IDF) through calibration to recent high flow events and the development of its stage-frequency or hydrologic loading curve with the U.S. Army Corps of Engineers’ Risk Management Center Reservoir Frequency Analysis (RMC-RFA) model. The IDF update follows Engineering Regulation 1110-8-2, Inflow Design Flood for Dams and Reservoirs, including unit hydrograph peaking and two antecedent pool elevations. Background information on the original design of the dam …

Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety, Amirfarrokh Iranitalab

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Transportation of hazardous materials (hazmat) in the United States (U.S.) constituted 22.8% of the total tonnage transported in 2012 with an estimated value of more than 2.3 billion dollars. As such, hazmat transportation is a significant economic activity in the U.S. However, hazmat transportation exposes people and environment to the infrequent but potentially severe consequences of incidents resulting in hazmat release. Trucks and trains carried 63.7% of the hazmat in the U.S. in 2012 and are the major foci of this dissertation. The main research objectives were 1) identification and quantification of the effects of different factors on occurrence and …

Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India, Arun Ravindranath, Naresh Devineni, Upmanu Lall, Paulina Concha Larrauri

Publications and Research

Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years …

Camel And Adcirc Storm Surge Models—A Comparative Study, Muhammad K. Akbar, Richard A. Luettich, Jason G. Fleming, Shahrouz K. Aliabadi

Mechanical and Manufacturing Engineering Faculty Research

The Computation and Modeling Engineering Laboratory (CaMEL), an implicit solver-based storm surge model, has been extended for use on high performance computing platforms. An MPI (Message Passing Interface) based parallel version of CaMEL has been developed from the previously existing serial version. CaMEL uses hybrid finite element and finite volume techniques to solve shallow water conservation equations in either a Cartesian or a spherical coordinate system and includes hurricane-induced wind stress and pressure, bottom friction, the Coriolis effect, and tidal forcing. Both semi-implicit and fully-implicit time stepping formulations are available. Once the parallel implementation is properly validated, CaMEL is evaluated …

Augmenting Bottom-Up Metamodels With Predicates, Ross J. Gore, Saikou Diallo, Christopher Lynch, Jose Padilla

VMASC Publications

Metamodeling refers to modeling a model. There are two metamodeling approaches for ABMs: (1) top-down and (2) bottom-up. The top down approach enables users to decompose high-level mental models into behaviors and interactions of agents. In contrast, the bottom-up approach constructs a relatively small, simple model that approximates the structure and outcomes of a dataset gathered fromthe runs of an ABM. The bottom-up metamodel makes behavior of the ABM comprehensible and exploratory analyses feasible. Formost users the construction of a bottom-up metamodel entails: (1) creating an experimental design, (2) running the simulation for all cases specified by the design, (3) …

Human-Intelligence/Machine-Intelligence Decision Governance: An Analysis From Ontological Point Of View, Faisal Mahmud, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

The increasing CPU power and memory capacity of computers, and now computing appliances, in the 21st century has allowed accelerated integration of artificial intelligence (AI) into organizational processes and everyday life. Artificial intelligence can now be found in a wide range of organizational processes including medical diagnosis, automated stock trading, integrated robotic production systems, telecommunications routing systems, and automobile fuzzy logic controllers. Self-driving automobiles are just the latest extension of AI. This thrust of AI into organizations and everyday life rests on the AI community’s unstated assumption that “…every aspect of human learning and intelligence could be so precisely described …

The Impacts Of Telecommuting On The Time-Space Distribution Of Daily Activities, Mario Benito Rojas Iv

FIU Electronic Theses and Dissertations

As major cities have aged, they have also met or exceeded their transportation infrastructure’s capacity. This has led to many negative impacts such as increased greenhouse gas emissions, delay, travel time, congestion, as well as decreased energy independence, standard of living for the cities’ inhabitants and the world as a whole. As a result, these cities will undoubtedly suffer and will struggle to meet the needs of their citizens. It is becoming more evident, and relevant, that the solution to today’s and tomorrow’s transportation problems will be overcome through the use of policy as well as innovative strategies, one of …

Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki

Department of Electrical Engineering and Computer Science - Daytona Beach

This paper presents an approach to measuring computer security understood as a system property, in the category of similar properties, such as safety, reliability, dependability, resilience, etc. First, a historical discussion of measurements is presented, beginning with views of Hermann von Helmholtz in his 19th century work “Zählen und Messen”. Then, contemporary approaches related to the principles of measuring software properties are discussed, with emphasis on statistical, physical and software models. A distinction between metrics and measures is made to clarify the concepts. A brief overview of inadequacies of methods and techniques to evaluate computer security is presented, followed by …

Modeling A Sensor To Improve Its Efficacy, Nabin K. Malakar, Daniil Gladkov, Kevin H. Knuth

Physics Faculty Scholarship

Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due with lower-quality sensors. Here we demonstrate via a case study how modeling a sensor can improve its efficacy when employed within a Bayesian inferential framework. As a test bed we employ a robotic arm that is designed to autonomously take its own measurements using an inexpensive LEGO light sensor to estimate the position and radius of a white circle on a black field. The light sensor integrates the light arriving from a …

Influenza Forecasting With Google Flu Trends, Andrea Freyer Dugas, Mehdi Jalalpour, Yulia Gel, Scott Levin, Fred Torcaso, Takeru Igusa, Richard E. Rothman

Civil and Environmental Engineering Faculty Publications

Background: We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy.

Methods: Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004–2011) divided into seven training and out-of-sample verification sets. Forecasting procedures …

Spatial And Temporal Correlations Of Freeway Link Speeds: An Empirical Study, Piotr J. Rachtan

Masters Theses 1911 - February 2014

Congestion on roadways and high level of uncertainty of traffic conditions are major considerations for trip planning. The purpose of this research is to investigate the characteristics and patterns of spatial and temporal correlations and also to detect other variables that affect correlation in a freeway setting. 5-minute speed aggregates from the Performance Measurement System (PeMS) database are obtained for two directions of an urban freeway – I-10 between Santa Monica and Los Angeles, California. Observations are for all non-holiday weekdays between January 1st and June 30th, 2010. Other variables include traffic flow, ramp locations, number of lanes and the …

Water Quality Models For Stormwater Runoff In Two Lincoln, Nebraska Urban Watersheds, Jake Fisher

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Water quality monitoring was conducted in two urban watersheds (Colonial Hills and Taylor Park) located in southeast Lincoln, NE over a three year period spanning from October 2008 through September 2011. In-line probes continuously measured for turbidity, conductivity, dissolved oxygen, and water temperature while other water quality constituents were analyzed for discrete water samples collected using grab and automatic sampling techniques. The water quality data was used to calculate event mean concentrations (EMCs) for sixteen storm events sampled over the duration of the project period. Three types of stormwater quality multiple linear regression models were developed for the estimation of …

Route Choice Behavior In Risky Networks With Real-Time Information, Michael D. Razo

Masters Theses 1911 - February 2014

This research investigates route choice behavior in networks with risky travel times and real-time information. A stated preference survey is conducted in which subjects use a PC-based interactive maps to choose routes link-by-link in various scenarios. The scenarios include two types of maps: the first presenting a choice between one stochastic route and one deterministic route, and the second with real-time information and an available detour. The first type measures the basic risk attitude of the subject. The second type allows for strategic planning, and measures the effect of this opportunity on subjects' choice behavior.

Results from each subject are …

Implementation Of Uncertainty Propagation In Triton/Keno, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

Monte Carlo methods are beginning to be used for three dimensional fuel depletion analyses to compute various quantities of interest, including isotopic compositions of used nuclear fuel. The TRITON control module, available in the SCALE 5.1 code system, can perform three-dimensional (3-D) depletion calculations using either the KENO V.a or KENO-VI Monte Carlo transport codes, as well as the two-dimensional (2-D) NEWT discrete ordinates code. To overcome problems such as spatially nonuniform neutron flux and non-uniform statistical uncertainties in computed reaction rates and to improve the fidelity of calculations using Monte Carlo methods, uncertainty propagation is needed for depletion calculations.

Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

The dimensions and the large amount of shielding required for Global Nuclear Energy Partnership (GNEP) facilities, advanced radiation shielding, and dose computation techniques are beyond today’s capabilities and will certainly be required. With the Generation IV Nuclear Energy System Initiative, it will become increasingly important to be able to accurately model advanced Boiling Water Reactor and Pressurized Water Reactor facilities, and to calculate dose rates at all locations within a containment (e.g., resulting from radiations from the reactor as well as the from the primary coolant loop) and adjoining structures (e.g., from the spent fuel pool).

The MAVRIC sequence is …

Implementation Of Uncertainty Propagation In Triton/Keno: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

Monte Carlo methods are beginning to be used for three-dimensional fuel depletion analyses to compute various quantities of interest, including isotopic compositions of used fuel.1 The TRITON control module, available in the SCALE 5.1 code system, can perform three dimensional (3-D) depletion calculations using either the KENO V.a or KENO-VI Monte Carlo transport codes, as well as the two-dimensional (2- D) NEWT discrete ordinates code. For typical reactor systems, the neutron flux is not spatially uniform. For Monte Carlo simulations, this results in non-uniform statistical uncertainties in the computed reaction rates. For spatial regions where the flux is low, e.g., …

Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis: To Support The Global Nuclear Energy Partnership, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

Monte Carlo methods are used to compute fluxes or dose rates over large areas using mesh tallies. For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas.

In this project the MAVRIC sequence will be evaluated along with the Monte Carlo engine Monaco to investigate its effectiveness and usefulness in facility shielding and dose rate analyses. A previously MCNP-evaluated cask …

Multiregional Interactions Between Energy And Transportation, Karen R. Polenske

Applications

Because of the number and complexity of the issues that will determine the use of coal by the electric-generating plants, an important asset of policy makers will be the availability of a method of analysis that allows for quick studies of many different combinations of assumptions and policies. The present prototype study is designed to show how the multiregional input-output model can be used to investigate each different assumption and policy alternative. For this paper, the analysis has necessarily been restricted to two issues. First, the results of using regional rather than national technologies in the model are assessed. This …