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- Type:
- Article
- Descripción/Resumen:
- Not Available
- Creador/Autor:
- Cohen, Kelly and Ernest, Nick
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2015-12
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- This study introduces the technique of Genetic Fuzzy Trees (GFTs) through novel application to an air combat control problem of an autonomous squadron of Unmanned Combat Aerial Vehicles (UCAVs) equipped with next-generation defensive systems. GFTs are a natural evolution to Genetic Fuzzy Systems, in which multiple cascading fuzzy systems are optimized by genetic methods. In this problem a team of UCAV's must traverse through a battle space and counter enemy threats, utilize imperfect systems, cope with uncertainty, and successfully destroy critical targets. Enemy threats take the form of Air Interceptors (AIs), Surface to Air Missile (SAM) sites, and Electronic WARfare (EWAR) stations. Simultaneous training and tuning a multitude of Fuzzy Inference Systems (FISs), with varying degrees of connectivity, is performed through the use of an optimized Genetic Algorithm (GA). The GFT presented in this study, the Learning Enhanced Tactical Handling Algorithm (LETHA), is able to create controllers with the presence of deep learning, resilience to uncertainties, and adaptability to changing scenarios. These resulting deterministic fuzzy controllers are easily understandable by operators, are of very high performance and efficiency, and are consistently capable of completing new and different missions not trained for.
- Creador/Autor:
- Schumacher, Corey; Cohen, Kelly; Ernest, Nicholas; Casbeer, David, and Kivelevitch, Elad
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2015-05
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- This work presents a methodology for real-time estimation of wildland fire growth, utilizing a fire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deployability.
- Creador/Autor:
- Sharma, Balaji R.; Cohen, Kelly, and Kumar, Manish
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2013-10
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- Fire is a natural component of many ecosystems but wildland fires often do pose serious threats to public safety, properties and natural resources. Forest fire acts as a dominant factor in reshaping of terrain and change of the ecosystem of a particular area. The total damage due to wildland fire shows an increasing trend over the past decade. Forest Fire Decision Support Systems (FFDSS) have been developed for the last thirty years all over the world that supplies valuable information on forest fire detection, fire behavior and other aspects of forest fires but lacks in developing intelligent fire suppression strategies. In this paper, an effort has been made to generate intelligent fire suppression strategies with efficient resource allocation using the Genetic Algorithm based optimization tool in a heterogeneous and uncertain scenario. The goal of this research is to perform intelligent resource allocation along with the generation of optimal firelines that minimizes the total burned area due to wildland fire. The solutions generated at each generations of the Genetic Algorithm (GA) are used to build the firelines in a heterogeneous terrain where advanced forest fire propagation model is used to evaluate the fitness values of each generated solutions. The optimal firelines thus obtained through the Simulation-Optimization technique minimizes the total damage due to wildland fire and eliminates the chance of any fire escape i.e., firefront reaching the fireline positions before they are built. Such techniques integrated with the existing FFDSS hold promise in effectively controlling forest fires.
- Creador/Autor:
- Manish, Kumar; Cohen, Kelly, and HomChaudhuri, Baisravan
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2010-07
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- A general methodology has been developed for the design of a robust control law for a family of lightly damped second order problems. In this research effort, the passivity approach has been extended to systems having non-collocated input/output pairs by introducing an observer that incorporates the nominal dynamical model of the plant. The developed passive observer-based control law emulates numerous dynamic vibration absorbers which are tuned to a targeted frequency using classical methods and the tuning ratios are time-invariant. However, the uniqueness of this approach is that the damping parameters of the emulated absorbers are continuously varied by means of a fuzzy logic control algorithm to provide near minimum-time suppression of vibration. The developed approach is applied to both several benchmarks in the field of structural dynamics as well as experiments using piezo-ceramic sensors and actuators. Results show that this methodology provides stability and performance robustness on the one hand as well as requiring relatively low amount of actuation authority for desired nominal plant closeloop behavior.
- Creador/Autor:
- Weller, Tanchum; Cohen, Kelly, and Ben-Asher, Joseph
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2001-11
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- Unmanned Air Vehicle (UAV) teams are anticipated to provide surveillance support through algorithms, software, and automation. It is desirable to have algorithms that compute effective and efficient routes for multiple UAVs across a variety of missions. These algorithms must be realizable, practical, and account for uncertainties. In surveillance missions, UAVs act as mobile wireless communication nodes in a larger, underlying network consisting of targets where information is to be collected and base stations where information is to be delivered. The role of UAVs in these networks has primarily been to maintain or improve connectivity while undervaluing routing efficiency. Moreover, many current routing strategies for UAVs ignore communication constraints even though neglecting communication can lead to suboptimal tour designs. Generating algorithms for autonomous vehicles that work effectively despite these communication restrictions is key for the future of UAV surveillance missions. A solution is offered here based on a variation of the traditional vehicle routing problem and a simple communication model. In this work, the new routing formulation is defined, analyzed, and a heuristic approach is motivated and described. Simulation results show that the heuristic algorithm gives near-optimal results in real-time, allowing it to be used for large problem sizes and extended to dynamic scenarios.
- Creador/Autor:
- Cohen, Kelly; Sabo, Chelsea, and Kingston, Derek
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2014-01
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- The problem of assigning a group of Unmanned Aerial Vehicles (UAVs) to perform spatially distributed tasks often requires that the tasks will be performed as quickly as possible. This problem can be defined as the Min–Max Multiple Depots Vehicle Routing Problem (MMMDVRP), which is a benchmark combinatorial optimization problem. In this problem, UAVs are assigned to service tasks so that each task is serviced once and the goal is to minimize the longest tour performed by any UAV in its motion from its initial location (depot) to the tasks and back to the depot. This problem arises in many time-critical applications, e.g. mobile targets assigned to UAVs in a military context, wildfire fighting, and disaster relief efforts in civilian applications. In this work, we formulate the problem using Mixed Integer Linear Programming (MILP) and Binary Programming and show the scalability limitation of these formulations. To improve scalability, we propose a hierarchical market-based solution (MBS). Simulation results demonstrate the ability of the MBS to solve large scale problems and obtain better costs compared with other known heuristic solution.
- Creador/Autor:
- Sharma, Balaji R.; Cohen, Kelly; Ernest, Nicholas; Kumar, Manish, and Kivelevitch, Elad
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/03/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2014-01
- Licencia:
- All rights reserved
- Type:
- Article
- Descripción/Resumen:
- This use case appears in Curating Research Data V2, an ACRL publication edited by Lisa R Johnston. Both volumes of the book are available as open access editions at the following link. http://www.ala.org/acrl/publications/booksanddigitalresources/booksmonographs/catalog/publications The use case examines the metadata contributed in a self-submission repository model and what changes were made in the metadata form to encourage researchers to contribute quality metadata.
- Creador/Autor:
- Koshoffer, Amy; Hansen, Carolyn, and Newman, Linda
- Peticionario:
- Amy Koshoffer
- Fecha modificada:
- 01/30/2017
- Fecha modificada:
- 02/21/2017
- Fecha de creacion:
- 2016-02-12
- Licencia:
- Attribution-NonCommercial-NoDerivs 4.0 International
- Type:
- Media
- Descripción/Resumen:
- What initially looked like several change agents colliding to create a year of turbulence, came to be a year of transformation for our teaching practice. Both external forces, such as ACRL’s Framework for Information Literacy for Higher Education, and internal forces, such as new strategic directions in eLearning, provided momentum as we redesigned our research guides. The presentation includes a case study of a year-long process of re-envisioning our guides to enhance content based on the Framework’s threshold concepts, incorporate responsive and accessible design, and reflect our pedagogical practices. Throughout the process we collaborated with key campus stakeholders: eLearning strategists, English Composition faculty, and the student population. In addition, our process coincided with the renovation of one of our classrooms into a collaborative teaching and learning environment. The presentation demonstrates how the new space converged with our instruction strategies.
- Creador/Autor:
- Hart, Olga and Bach, Pamela
- Peticionario:
- Olga Hart
- Fecha modificada:
- 01/26/2017
- Fecha modificada:
- 01/26/2017
- Licencia:
- Attribution-NonCommercial-NoDerivs 4.0 International
- Type:
- Document
- Descripción/Resumen:
- This is the iBook version of chapter five of five. It requires the iBooks app to read. The media is embedded so no internet connection is necessary after the book has been downloaded. It contains many interactive widgets and videos that are not found in the epub, pdf, and mobi versions. However, the file size for this format is much larger and requires the book to be broken into individual chapters. All the text can be read by clicking the Closed Caption (CC) button on each video. There are keywords on the right side of each page to enable word searches.
- Creador/Autor:
- Petach, Jay
- Peticionario:
- Jay Petach
- Fecha modificada:
- 01/11/2017
- Fecha modificada:
- 01/11/2017
- Licencia:
- All rights reserved