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Space Analysis And Research Centers (Sparcs) For Ssa Data And Analytics, Phillip Cunio, Brien Flewelling 2016 ExoAnalytic Solutions, Inc.

Space Analysis And Research Centers (Sparcs) For Ssa Data And Analytics, Phillip Cunio, Brien Flewelling

Space Traffic Management Conference

Widespread use of massive data and increasing reliance on spaceborne infrastructure are two of the emerging megatrends of the early 21st century. However, both come with liabilities: movement and processing of large data volumes is very expensive, and reliance on spaceborne infrastructure adds risk that problems in the still incompletely-understood space domain might cause work disruptions.

ExoAnalytic proposes the use of Space Analysis and Research Centers (SpARCs) as a way to begin addressing both these issues. A SpARC is a facility which integrates volumes of data collected on satellites, centrally analyzes it, and makes available resulting useful information. The ...


Examining Time To Evacuate Dynamically Activated Aircraft Hazard Areas, Zheng Tao, Granghuai Wang, Ashley G. Williams, Jon L. Semanek, Jonathan L. Schwartz 2016 The MITRE Corporation

Examining Time To Evacuate Dynamically Activated Aircraft Hazard Areas, Zheng Tao, Granghuai Wang, Ashley G. Williams, Jon L. Semanek, Jonathan L. Schwartz

Space Traffic Management Conference

The growth in launch and reentry operations in the National Airspace System (NAS) presents the Federal Aviation Administration (FAA) with the challenge of integrating them more efficiently while also minimizing effects on other NAS users and maintaining safety. Currently, to maintain safety and account for unforeseen events such as vehicle breakup, the FAA segregates large amounts of airspace, called Aircraft Hazard Areas (AHAs), from traditional NAS users during launch and reentry operations. In order to minimize effects on NAS users, some AHAs during reentry are dynamically activated only if an unexpected event occurs. If a dynamic AHA is activated, then ...


Multi-Agent Distributed Optimization Via Inexact Consensus Admm, Tsung-Hui Chang, Mingyi Hong, Xiangfeng Wang 2016 National Taiwan University of Science and Technology

Multi-Agent Distributed Optimization Via Inexact Consensus Admm, Tsung-Hui Chang, Mingyi Hong, Xiangfeng Wang

Mingyi Hong

Multi-agent distributed consensus optimization problems arise in many signal processing applications. Recently, the alternating direction method of multipliers (ADMM) has been used for solving this family of problems. ADMM based distributed optimization method is shown to have faster convergence rate compared with classic methods based on consensus subgradient, but can be computationally expensive, especially for problems with complicated structures or large dimensions. In this paper, we propose lowcomplexity algorithms that can reduce the overall computational cost of consensus ADMM by an order of magnitude for certain large-scale problems. Central to the proposed algorithms is the use of an inexact step ...


Visualizing Complex Adaptive Systems: A Case Study Of The Missouri Maternal, Infant, And Early Childhood Home Visiting Program, Julie M. Kapp, Sara Schlemper, Riyad Haq, Sofia Campos Vidal Pires, Eduardo J. Simoes 2016 University of Missouri School of Medicine

Visualizing Complex Adaptive Systems: A Case Study Of The Missouri Maternal, Infant, And Early Childhood Home Visiting Program, Julie M. Kapp, Sara Schlemper, Riyad Haq, Sofia Campos Vidal Pires, Eduardo J. Simoes

Frontiers in Public Health Services and Systems Research

Background: The Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program was created by the 2010 Patient Protection and Affordable Care Act. MIECHV provides comprehensive services to at-risk families through evidence-based home visiting programs.

Purpose: The following question is addressed: Does the Missouri MIECHV system meet the definition of a complex adaptive system (CAS)?

Methods: A systematic review was conducted of documents related to MIECHV programs (federal, state, and local levels), and to affiliated programs with a home visiting and early childhood (aged birth to 5 years) scope. The organizations’ fit was identified for the scope of early childhood home ...


Mobile Robots As Remote Sensors For Spatial Point Process Models, Paul B. Reverdy, D. E. Koditschek 2016 University of Pennsylvania

Mobile Robots As Remote Sensors For Spatial Point Process Models, Paul B. Reverdy, D. E. Koditschek

Departmental Papers (ESE)

Spatial point process models are a commonly-used statistical tool for studying the distribution of objects of interest in a domain. We study the problem of deploying mobile robots as remote sensors to estimate the parameters of such a model, in particular the intensity parameter lambda which measures the mean density of points in a Poisson point process. This problem requires covering an appropriately large section of the domain while avoiding the objects, which we treat as obstacles. We develop a control law that covers an expanding section of the domain and an online criterion for determining when to stop sampling ...


A Bayesian-Influence Model For Error Probability Analysis Of Combine Operations In Harvesting, Yu Du, Michael C. Dorneich, Brian L. Steward, Cameron A. MacKenzie 2016 Iowa State University

A Bayesian-Influence Model For Error Probability Analysis Of Combine Operations In Harvesting, Yu Du, Michael C. Dorneich, Brian L. Steward, Cameron A. Mackenzie

Industrial and Manufacturing Systems Engineering Publications

Harvesting is one of the most important agricultural operations because it captures the value from the entire cropping season. In modern agriculture, grain harvesting has been mechanized through the combine harvester. A combine harvester enables highly productive crop harvesting. Combine harvesting performance depends on the highly variable skill of combine operators and associated operator error. An approach was developed to analyze the risk of the combine harvesting operation as it relates to operator error. Specifically, a risk analysis model was built based on a task analysis from operator interviews and estimates of the probability of operator error. This paper employs ...


A Hybrid Systems Model For Simple Manipulation And Self-Manipulation Systems, Aaron M. Johnson, Sam Burden, Daniel E. Koditschek 2016 University of Pennsylvania

A Hybrid Systems Model For Simple Manipulation And Self-Manipulation Systems, Aaron M. Johnson, Sam Burden, Daniel E. Koditschek

Departmental Papers (ESE)

Rigid bodies, plastic impact, persistent contact, Coulomb friction, and massless limbs are ubiquitous simplifications introduced to reduce the complexity of mechanics models despite the obvious physical inaccuracies that each incurs individually. In concert, it is well known that the interaction of such idealized approximations can lead to conflicting and even paradoxical results. As robotics modeling moves from the consideration of isolated behaviors to the analysis of tasks requiring their composition, a mathematically tractable framework for building models that combine these simple approximations yet achieve reliable results is overdue. In this paper we present a formal hybrid dynamical system model that ...


Network-Centric Localization In Manets Based On Particle Swarm Optimization, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Ann K. Miller, Cihan H. Dagli 2016 Missouri University of Science and Technology

Network-Centric Localization In Manets Based On Particle Swarm Optimization, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Ann K. Miller, Cihan H. Dagli

Cihan Dagli

There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is ...


Implementing An Architectural Framework To Define And Deliver Net-Centric Capability To Legacy Military Air Assets Operating Within A System Of Systems, Mark S. Anderson, S. M. Martin, Cihan H. Dagli, Ann K. Miller 2016 Missouri University of Science and Technology

Implementing An Architectural Framework To Define And Deliver Net-Centric Capability To Legacy Military Air Assets Operating Within A System Of Systems, Mark S. Anderson, S. M. Martin, Cihan H. Dagli, Ann K. Miller

Cihan Dagli

The United States Air Force (USAF) is implementing an integrated net-centric system of systems for airborne operations in support of the global war on terror (GWOT). The GWOT demands that a successful architecture framework transforms and delivers net-centric assets to the war-fighter in a timely manner. A critical component of this implementation is the transformation of legacy strategic air platforms into net-centric air power assets operating within a system of systems. The System Architectural (SA) framework, and the Department of Defense Architectural Framework (DoDAF) are ways of managing complexity and organizing information within a system of systems network. This paper ...


Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli 2016 Missouri University of Science and Technology

Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli

Cihan Dagli

The creation of strategies to meet abstract goals is an important behavior exhibited by natural organisms. A situation requiring the development of such strategies is the predator-evader problem. To study this problem, Khepera robots are chosen as the competing agents. Using computer simulations the evolution of the adaptive behavior is studied in a predator-evader interaction. A bilaterally symmetrical multilayer perceptron neural network architecture with evolvable weights is used to model the “brains” of the agents. Evolutionary programming is employed to evolve the predator for developing adaptive strategies to meet its goals. To study the effect of learning on evolution a ...


A Generic, Adaptive Systems Engineering Information Model I, Ann K. Miller, Joseph J. Simpson, Scott Erwin Grasman, Cihan H. Dagli 2016 Missouri University of Science and Technology

A Generic, Adaptive Systems Engineering Information Model I, Ann K. Miller, Joseph J. Simpson, Scott Erwin Grasman, Cihan H. Dagli

Cihan Dagli

This paper proposes a new network centric architecture that can be used by first responders to effectively respond to crisis situations. The powerful network-centric concept originally developed for and mainly used in the military environment, can be effectively used for civilian security and emergency response missions. This paper also proposes the use of a swarm of intelligent robots as a part of the network-centric architecture to aid the first responders. The swarm of robots works in tandem with the first responders and provides them with the necessary information on a real time basis. The proposed network centric architecture with a ...


Development Of An Associate Degree Level Course On Lean, Jeremy Espinoza 2016 Bowling Green State University

Development Of An Associate Degree Level Course On Lean, Jeremy Espinoza

Master of Technology Management Plan II Graduate Projects

Lean training and education has become a focal point in both industry and the realm of academics; however, the need within the industry remains, and oftentimes companies must take on the additional and high expense of training new graduates once they enter the workforce. Often, the classes that students study in the lean methodology, if any are studied at all, are taught within other disciplines, and the instruction is in a general sense as opposed to in depth and hands on. Within the past eight years it has been referenced in different academic articles that students are not coming into ...


Exploring Regional And Telecoupled Land Use Change Impacts From Environmental Shocks, Kevin Hill, Liz Wachs, Brady Hardiman, David Yu, Shweta Singh 2016 Purdue University

Exploring Regional And Telecoupled Land Use Change Impacts From Environmental Shocks, Kevin Hill, Liz Wachs, Brady Hardiman, David Yu, Shweta Singh

The Summer Undergraduate Research Fellowship (SURF) Symposium

Natural disasters or environmental shocks have the potential to disrupt local agricultural systems as well as distant agricultural systems through cascading effects. In this work we selected two distinct environmental shocks and traced their cascading effects on land use change. Quantifying cascading effects is a salient issue because climate change forecasts indicate an increase in frequency and intensity of global environmental shocks. This study incorporated the concept of telecoupled systems involving interrelating ecological, economic and political/social components. A telecoupled framework involving cascading effects was implemented using three approaches. The first approach involved using bilateral agricultural trade matrix data to ...


A Systems Approach To Healthcare: Agent-Based Modeling, Community Mental Health, And Population Well-Being, Barry G. Silverman, Nancy Hanrahan, Gnana K. Bharathy, Kim Gordon, Dan Johnson 2016 University of Pennsylvania

A Systems Approach To Healthcare: Agent-Based Modeling, Community Mental Health, And Population Well-Being, Barry G. Silverman, Nancy Hanrahan, Gnana K. Bharathy, Kim Gordon, Dan Johnson

Barry G Silverman

Purpose

Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society).

Methods

The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent's daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of ...


Rich Socio-Cognitive Agents For Immersive Training Environments: Case Of Nonkin Village, Barry G. Silverman, David Pietrocola, Ben Nye, Nathan Weyer, Oleg Osin, Dan Johnson, Ransom Weaver 2016 University of Pennsylvania

Rich Socio-Cognitive Agents For Immersive Training Environments: Case Of Nonkin Village, Barry G. Silverman, David Pietrocola, Ben Nye, Nathan Weyer, Oleg Osin, Dan Johnson, Ransom Weaver

Barry G Silverman

Demand is on the rise for scientifically based human-behavior models that can be quickly customized and inserted into immersive training environments to recreate a given society or culture. At the same time, there are no readily available science model-driven environments for this purpose (see survey in Sect. 2). In researching how to overcome this obstacle, we have created rich (complex) socio-cognitive agents that include a large number of social science models (cognitive, sociologic, economic, political, etc) needed to enhance the realism of immersive, artificial agent societies. We describe current efforts to apply model-driven development concepts and how to permit other ...


Holistically Evaluating Agent Based Social System Models, Gnana K. Bharathy, Barry G. Silverman 2016 University of Pennsylvania

Holistically Evaluating Agent Based Social System Models, Gnana K. Bharathy, Barry G. Silverman

Barry G Silverman

The philosophical perspectives on model evaluation can be broadly classified into reductionist/logical positivist and relativist/holistic. In this paper, we outline some of our past efforts in, and challenges faced during, evaluating models of social systems with cognitively detailed agents. Owing to richness in the model, we argue that the holistic approach and consequent continuous improvement are essential to evaluating complex social system models such as these. A social system built primarily of cognitively detailed agents can provide multiple levels of correspondence, both at observable and abstract aggregated levels. Such a system can also pose several challenges, including large ...


Systems Social Seience: A Design Inquiry Approach For Stabilization And Reconstruction Of Social Systems, Barry G. Silverman 2016 Selected Works

Systems Social Seience: A Design Inquiry Approach For Stabilization And Reconstruction Of Social Systems, Barry G. Silverman

Barry G Silverman

This paper explores novel approaches under the design inquiry paradigm that promise to help organizations better understand and solve socio-technical dilemmas. Design inquiry is contrasted with scientific inquiry (Section 1). Section 2 presents a meso-scale model of models methodology for design inquiry that synthesizes systems science, agent modeling and simulation, knowledge management architectures, and domain theories and knowledge. The goal is to focus computational science on exploring underlying mechanisms (white box modeling) and to support reflective theorizing and discourse to explain social dilemmas and potential resolutions. Section 3 then describes an evolving agent modeling and simulation testbed while Section 4 ...


Clustering-Based Robot Navigation And Control, Omur Arslan 2016 University of Pennsylvania

Clustering-Based Robot Navigation And Control, Omur Arslan

Departmental Papers (ESE)

In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths, capturing the connectivity of the underlying space. This dissertation introduces the use of clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures in ...


Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow 2016 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

Mariesa Crow

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.


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 2016 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

Mariesa Crow

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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