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Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski 2018 Wojciech Budzianowski Consulting Services

Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.


Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. McGehee, James Torner, Wayne Wakeland, Robert Wallace 2018 Department of Epidemiology, College of Public Health University of Iowa

Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. Mcgehee, James Torner, Wayne Wakeland, Robert Wallace

Systems Science Faculty Publications and Presentations

Background: Motor vehicle crashes remain the leading cause of teen deaths in spite of preventive efforts. Prevention strategies could be advanced through new analytic approaches that allow us to better conceptualize the complex processes underlying teen crash risk. This may help policymakers design appropriate interventions and evaluate their impacts.

Methods: System Dynamics methodology was used as a new way of representing factors involved in the underlying process of teen crash risk. Systems dynamics modeling is relatively new to public health analytics and is a promising tool to examine relative influence of multiple interacting factors in predicting a health outcome. Dynamics ...


Reactive Navigation In Partially Known Non-Convex Environments, Vasileios Vasilopoulos, Daniel E. Koditschek 2018 University of Pennsylvania

Reactive Navigation In Partially Known Non-Convex Environments, Vasileios Vasilopoulos, Daniel E. Koditschek

Departmental Papers (ESE)

This paper presents a provably correct method for robot navigation in 2D environments cluttered with familiar but unexpected non-convex, star-shaped obstacles as well as completely unknown, convex obstacles. We presuppose a limited range onboard sensor, capable of recognizing, localizing and (leveraging ideas from constructive solid geometry) generating online from its catalogue of the familiar, non-convex shapes an implicit representation of each one. These representations underlie an online change of coordinates to a completely convex model planning space wherein a previously developed online construction yields a provably correct reactive controller that is pulled back to the physically sensed representation to generate ...


Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang 2018 University of Arkansas, Fayetteville

Budget-Constrained Regression Model Selection Using Mixed Integer Nonlinear Programming, Jingying Zhang

Theses and Dissertations

Regression analysis fits predictive models to data on a response variable and corresponding values for a set of explanatory variables. Often data on the explanatory variables come at a cost from commercial databases, so the available budget may limit which ones are used in the final model.

In this dissertation, two budget-constrained regression models are proposed for continuous and categorical variables respectively using Mixed Integer Nonlinear Programming (MINLP) to choose the explanatory variables to be included in solutions. First, we propose a budget-constrained linear regression model for continuous response variables. Properties such as solvability and global optimality of the proposed ...


Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy 2018 Purdue University

Smart Disease Prevention App: Informing The Public In Their Own Geographic Location, Apoorva Sulakhe, Shafali Rana, Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, Alyssa Zielinski, Vincent G. Duffy

Purdue Journal of Service-Learning and International Engagement

Apoorva Sulakhe and Shefali Rana are graduate students in the School of Industrial Engineering at Purdue. They have both been teaching assistants under their coauthor, Dr. Vincent Duffy, while supervising multiple projects. Coauthors Zoe Disori, William Nogay, Kyle Plummer, Meredith Shannon, Morgan Young, and Alyssa Zielinski are listed in alphabetical order. They were all seniors in School of Industrial Engineering at the time of this project in 2017. The purpose of their study, described in this article, was to develop an application to provide users with accurate information about diseases spreading in their geographic locations.


Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey 2018 Southwestern Oklahoma State University

Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey

Student Research

Over the last few years, the state of Oklahoma has been looking at ways to reduce expenses to address concerns about a budget deficit. There have been efforts made to reduce expenses due to the use of energy. It has been said, when the lights are on, work is getting done. Running lights is therefore the cost of doing business. Our research examines the question, “is there a way to provide better lighting while operating at a lower cost.” This research examines the current lighting at Southwestern State University, primarily fluorescent lighting (FL), and a cost benefit analysis of switching ...


Quantifying The Effect Of Uncertainty In The Gas Spot Price On Power System Dispatch Costs With Estimated Correlated Uncertainties, Dan Hu, Sarah M. Ryan 2018 Iowa State University

Quantifying The Effect Of Uncertainty In The Gas Spot Price On Power System Dispatch Costs With Estimated Correlated Uncertainties, Dan Hu, Sarah M. Ryan

Sarah M. Ryan

Electricity generation increasingly relies on natural gas for fuel. The competing demands for gas by other users who may have higher priority, the lack of coordination between gas and electricity markets, and extreme weather events all pose risks to systems with high dependence on gas. When the gas supply on which generators have planned is limited, operators may dispatch more costly units and generators may switch to alternative fuels or procure gas at high spot prices. All these efforts to avoid load-shedding result in higher electricity costs. To assess this economic risk we approximate the distribution of the daily operational ...


Reactive Velocity Control Reduces Energetic Cost Of Jumping With A Virtual Leg Spring On Simulated Granular Media, Sonia F. Roberts, Daniel E. Koditschek 2018 University of Pennsylvania

Reactive Velocity Control Reduces Energetic Cost Of Jumping With A Virtual Leg Spring On Simulated Granular Media, Sonia F. Roberts, Daniel E. Koditschek

Departmental Papers (ESE)

Robots capable of dynamic locomotion behaviors and high-bandwidth sensing with their limbs have a high cost of transport, especially when locomoting over highly dissipative substrates such as sand. We formulate the problem of reducing the energetic cost of locomotion by a Minitaur robot on sand, reacting to robot state variables in the inertial world frame without modeling the ground online. Using a bulk-behavior model of high-velocity intrusions into dry granular media, we simulated single jumps by a one-legged hopper using a Raibert-style compression-extension virtual leg spring. We compose this controller with a controller that added damping to the leg spring ...


Supporting Shrinkage: Better Planning And Decision-Making For Legacy Cities, Michael P. Johnson Jr., Justin B. Hollander, Eliza Davenport Whiteman 2018 Tufts University

Supporting Shrinkage: Better Planning And Decision-Making For Legacy Cities, Michael P. Johnson Jr., Justin B. Hollander, Eliza Davenport Whiteman

Michael P. Johnson

Planning and policy design for shrinking and distressed regions is challenging. Traditionally, planners use
a variety of tools and incentives to encourage land uses that accommodate changes in populations,
infrastructure and activities to maximize quality of life and social and environmental sustainability.
These are generally designed for growing cities and politically and socially active communities. Since
many regions face significant disparities in social supports, financial resources and quality of life, use of
these tools is thus problematic.

Information technology and the Internet have transformed the production of goods and services. The
‘big data’, ‘smart cities’ and ‘e-government’ movements make it ...


Evaluating The Effect Of Shear Stress On Graft-To Zwitterionic Polycarboxybetaine Coating Stability Using A Flow Cell, Andrew Belanger, Andre Decarmine, Shaoyi Jiang, Keith Cook, Kagya Amoako 2018 University of New Haven

Evaluating The Effect Of Shear Stress On Graft-To Zwitterionic Polycarboxybetaine Coating Stability Using A Flow Cell, Andrew Belanger, Andre Decarmine, Shaoyi Jiang, Keith Cook, Kagya Amoako

Mechanical and Industrial Engineering Faculty Publications

The effect of surface coatings on the performance of antifouling activity under flow can be influenced by the flow/coating interactions. This study evaluates the effect of surface coatings on antifouling activity under different flows for the analyses of coating stability. This was done by exposing DOPA-PCB-300/dopamine coated polydimethylsiloxane (PDMS) to physiological shear stresses using a recirculation system which consisted of dual chamber acrylic flow cells, tygon tubing, flow probe and meter, and perfusion pumps. The effect of shear stress induced by phosphate buffered saline flow on coating stability was characterized with differences in fibrinogen adsorption between control (coated ...


Issues In Reproducible Simulation Research, Ben G. Fitzpatrick 2018 Loyola Marymount University

Issues In Reproducible Simulation Research, Ben G. Fitzpatrick

Annual Symposium on Biomathematics and Ecology: Education and Research

No abstract provided.


The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco 2018 University of Central Florida

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco

Buenaventura "Ven" Basco

No abstract provided.


Retention Of Female Faculty Members, Susan L. Murray, Mariesa Crow, Suzanna M. Rose 2018 Missouri University of Science and Technology

Retention Of Female Faculty Members, Susan L. Murray, Mariesa Crow, Suzanna M. Rose

Suzanna Rose

The recruitment and the retention of female undergraduate and graduate students into engineering courses is discussed. A similar challenge lies in recruiting female faculty member from the limited pool of candidates in several fields at most universities. It is found that about half the females who were hired did not stay at the university. It is suggested that programs should be introduced to encourage mentoring and career development as such improvements would benefit all faculty members both female and male.


Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes 2018 Missouri University of Science and Technology

Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes

Donald C. Wunsch

This paper presents two neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.


Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes 2018 Missouri University of Science and Technology

Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Donald C. Wunsch

This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs.


Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani 2018 Missouri University of Science and Technology

Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani

Donald C. Wunsch

This paper presents a neural network (NN) based decentralized excitation controller design for large scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem controllers can be guaranteed. NNs are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded (UUB). Simulation results with a 3-machine power system demonstrate ...


Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani 2018 Missouri University of Science and Technology

Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani

Donald C. Wunsch

In power system controls, simplified analytical models are used to represent the dynamics of power system and controller designs are not rigorous with no stability analysis. One reason is because the power systems are complex nonlinear systems which pose difficulty for analysis. This paper presents a feedback linearization based power system stabilizer design for a single machine infinite bus power system. Since practical operating conditions require the magnitude of control signal to be within certain limits, the stability of the control system under control limits is also analyzed. Simulation results under different kinds of operating conditions show that the controller ...


Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow 2018 Missouri University of Science and Technology

Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow

Donald C. Wunsch

A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set.


Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes 2018 Missouri University of Science and Technology

Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Donald C. Wunsch

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of ...


Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow 2018 Missouri University of Science and Technology

Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow

Donald C. Wunsch

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. In power system control literature, the performances of the proposed controllers were mostly demonstrated using simulation results without any rigorous stability analysis. This paper proposes a stabilizing neural network (NN) controller based on a sixth order single machine infinite bus power system model. The NN is used to approximate the complex nonlinear dynamics of power system. Unlike the other indirect adaptive NN control schemes, there is no offline training process and the NN can be directly ...


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