Relevant bibliographies by topics / Distributed Sensing and Control

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Distributed Sensing and Control'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Distributed Sensing and Control"

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Henderson, Tom, Chuck Hansen, and Bir Bhanu. "The specification of distributed sensing and control." Journal of Robotic Systems 2, no. 4 (1985): 387–96. http://dx.doi.org/10.1002/rob.4620020405.

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Yuksel, S., and S. Tatikonda. "A Counterexample in Distributed Optimal Sensing and Control." IEEE Transactions on Automatic Control 54, no. 4 (2009): 841–44. http://dx.doi.org/10.1109/tac.2008.2009680.

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Tang, Yujie, Vikram Ramanathan, Junshan Zhang, and Na Li. "Communication-Efficient Distributed SGD With Compressed Sensing." IEEE Control Systems Letters 6 (2022): 2054–59. http://dx.doi.org/10.1109/lcsys.2021.3137859.

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ZHANG, WEIJIAN. "Gain of optical distributed sensing in distributed parameter systems." International Journal of Systems Science 22, no. 12 (1991): 2521–40. http://dx.doi.org/10.1080/00207729108910811.

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Martin, Jeffrey W., Tammy D. Henson, Joseph C. Wehlburg, James M. Redmond, Patrick S. Barney, and John A. Main. "Distributed Sensing and Shape Control of Piezoelectric Bimorph Mirrors." Journal of Intelligent Materials Systems and Structures 11, no. 10 (2000): 744–57. http://dx.doi.org/10.1177/104538900772663784.

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Ningxu Cai, M. Gholami, Litao Yang, and R. W. Brennan. "Application-Oriented Intelligent Middleware for Distributed Sensing and Control." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42, no. 6 (2012): 947–56. http://dx.doi.org/10.1109/tsmcc.2011.2174982.

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Panagou, Dimitra, Dusan M. Stipanovic, and Petros G. Voulgaris. "Distributed Dynamic Coverage and Avoidance Control Under Anisotropic Sensing." IEEE Transactions on Control of Network Systems 4, no. 4 (2017): 850–62. http://dx.doi.org/10.1109/tcns.2016.2576403.

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Martin, Jeffrey W., James M. Redmond, Patrick S. Barney, Tammy D. Henson, Joseph C. Wehlburg, and John A. Main. "Distributed Sensing and Shape Control of Piezoelectric Bimorph Mirrors." Journal of Intelligent Material Systems and Structures 11, no. 10 (2000): 744–57. http://dx.doi.org/10.1106/2ulx-mnqh-y1af-8b5v.

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Choi, Jinho. "Data-Aided Sensing for Distributed Detection." IEEE Wireless Communications Letters 10, no. 5 (2021): 1138–41. http://dx.doi.org/10.1109/lwc.2021.3064690.

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Tzou, H. S. "Integrated distributed sensing and active vibration suppression of flexible manipulators using distributed piezoelectrics." Journal of Robotic Systems 6, no. 6 (1989): 745–67. http://dx.doi.org/10.1002/rob.4620060606.

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Dissertations / Theses on the topic "Distributed Sensing and Control"

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Fariborzi, Fariborz. "Distributed sensing and control of a simply supported plate." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0012/NQ32829.pdf.

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Dai, Hanping. "Distributed control system architecture and smart sensing for intelligent semi-autonomous vehicles." Thesis, De Montfort University, 2002. http://hdl.handle.net/2086/4784.

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Grocholsky, Ben. "Information-Theoretic Control of Multiple Sensor Platforms." Thesis, The University of Sydney, 2002. http://hdl.handle.net/2123/796.

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This thesis is concerned with the development of a consistent, information-theoretic basis for understanding of coordination and cooperation decentralised multi-sensor multi-platform systems. Autonomous systems composed of multiple sensors and multiple platforms potentially have significant importance in applications such as defence, search and rescue mining or intelligent manufacturing. However, the effective use of multiple autonomous systems requires that an understanding be developed of the mechanisms of coordination and cooperation between component systems in pursuit of a common goal. A
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Grocholsky, Ben. "Information-Theoretic Control of Multiple Sensor Platforms." University of Sydney. School of Aerospace, Mechanical and Mechatronic Engineering, 2002. http://hdl.handle.net/2123/796.

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This thesis is concerned with the development of a consistent, information-theoretic basis for understanding of coordination and cooperation decentralised multi-sensor multi-platform systems. Autonomous systems composed of multiple sensors and multiple platforms potentially have significant importance in applications such as defence, search and rescue mining or intelligent manufacturing. However, the effective use of multiple autonomous systems requires that an understanding be developed of the mechanisms of coordination and cooperation between component systems in pursuit of a common goal. A
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Van, Den Biggelaar Olivier. "Distributed spectrum sensing and interference management for cognitive radios with low capacity control channels." Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209612.

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Cognitive radios have been proposed as a new technology to counteract the spectrum scarcity issue and increase the spectral efficiency. In cognitive radios, the sparse assigned frequency bands are opened to secondary users, provided that interference induced on the primary licensees is negligible. Cognitive radios are established in two steps: the radios firstly sense the available frequency bands by detecting the presence of primary users and secondly communicate using the bands that have been identified as not in use by the primary users.<p><p>In this thesis we investigate how to improve the
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Bassil, Antoine. "Distributed fiber optics sensing for crack monitoring of concrete structures." Thesis, Nantes, 2019. http://www.theses.fr/2019NANT4057.

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Le travail de thèse présenté dans ce mémoire vise à développer et valider une technique de suivi d’ouvertures de fissures à l'aide de mesures réparties de déformation par fibres optiques. Dans un premier temps les différentes théories existantes sur le transfert de déformation du matériau hôte vers la fibre optique sont présentées avec leurs domaine de validité. Le problème de l’adhésion parfaite entre couche est ensuite étudié et un modèle analytique à trois couches tenant compte d’une adhésion imparfaite est élaboré. Ce modèle est ensuite généralisé aux systèmes multicouches. Les études expé
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Lion, Stephen Todd. "Control Authorities of a Distributed Actuation and Sensing Array on a Blended-Wing-Body Uninhabited Aerial Vehicle." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-03272007-011124/.

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A distributed actuation array was installed on a blended-wing-body uninhabited aerial vehicle and tested in the 12-foot subsonic wind tunnel at NASA?s Langley Research Center. From the results of these tests, a discussion is given of the baseline aircraft, its conventional control surfaces, and the distributed array. Each effector in the distributed array was tested individually as well as pre-determined configurations incorporating all 12 effectors on each wing. From the tests on the individual effectors, a method was created that allows for the prediction of the control authorities for any c
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Suh, Peter M. "Robust modal filtering for control of flexible aircraft." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51780.

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The work in this dissertation comprises aeroservoelastic simulation development, two modal filter design case studies and theoretical improvement of the modal filter. The modal filter is made robust to sensor bias. Studies have shown that the states estimated by the modal filter can be integrated into active structural control. The integration of modal filters into aircraft structural control systems is explored. Modal filters require distributed sensing to achieve accurate modal coordinate estimates. Distributed sensing technology has progressed to the point, where it is being tested on airc
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Mazloomzadeh, Ali. "Development of Hardware in the Loop Real-Time Control Techniques for Hybrid Power Systems Involving Distributed Demands and Sustainable Energy Sources." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1666.

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The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the
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Sundman, Dennis. "Greedy Algorithms for Distributed Compressed Sensing." Doctoral thesis, KTH, Kommunikationsteori, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-144907.

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Compressed sensing (CS) is a recently invented sub-sampling technique that utilizes sparsity in full signals. Most natural signals possess this sparsity property. From a sub-sampled vector, some CS reconstruction algorithm is used to recover the full signal. One class of reconstruction algorithms is formed by the greedy pursuit, or simply greedy, algorithms, which is popular due to low complexity and good performance. Meanwhile, in sensor networks, sensor nodes monitor natural data for estimation or detection. One application of sensor networking is in cognitive radio networks, where sensor no
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Books on the topic "Distributed Sensing and Control"

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Tzou, H. S. Piezoelectric shells: Distributed sensing and control of continua. Kluwer Academic, 1993.

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Tzou, H. S. Piezoelectric Shells: Distributed Sensing and Control of Continua. Springer Netherlands, 1993.

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Dai, Hanping. Distributed control system architecture and smart sensing for intelligent semi-autonomous vehicles. De Montfort University, 2002.

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Balakrishnan, A. V. Application of optical distributed sensing and computation to control of large space structures: Final technical report on NASA grant, NAG 11-1074. National Aeronautics and Space Administration, 1992.

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Elhoseny, Mohamed, Xiaohui Yuan, and Salah-ddine Krit, eds. Distributed Sensing and Intelligent Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-64258-7.

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Coluccia, Giulio, Chiara Ravazzi, and Enrico Magli. Compressed Sensing for Distributed Systems. Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-390-3.

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Mazzeo, Pier Luigi, Paolo Spagnolo, and Thomas B. Moeslund, eds. Activity Monitoring by Multiple Distributed Sensing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13323-2.

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Benitez-Pérez, Héctor. Reconfigurable distributed control. Springer, 2004.

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Héctor, Benítez-Pérez, ed. Reconfigurable distributed control. Springer, 2005.

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Guo, Yi. Distributed Cooperative Control. John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119216131.

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Book chapters on the topic "Distributed Sensing and Control"

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Ganguli, Anurag, Jorge Cortés, and Francesco Bullo. "Distributed coverage of nonconvex environments." In Networked Sensing Information and Control. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68845-9_12.

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Saligrama, Venkatesh, and David A. Castañón. "Reliable Distributed Estimation with Intermittent Communications." In Networked Sensing Information and Control. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68845-9_10.

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Huang, Zhenhua, Fangxu Dong, and Arthur C. Sanderson. "Adaptive Distributed Sensing and Control Methods." In Handbook of Advanced Lighting Technology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-00176-0_30.

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Huang, Zhenhua, Fangxu Dong, and Arthur C. Sanderson. "Adaptive Distributed Sensing and Control Methods." In Handbook of Advanced Lighting Technology. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-00295-8_30-1.

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Wang, Ye, Nan Ma, Manqi Zhao, Prakash Ishwar, and Venkatesh Saligrama. "Distributed Field Estimation with One–bit Sensors." In Networked Sensing Information and Control. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68845-9_6.

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Dimakis, Alexandros G., and Kannan Ramchandran. "Network Coding for Distributed Storage in Wireless Networks." In Networked Sensing Information and Control. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-68845-9_5.

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Bullo, Francesco, and Jorge Cortés. "Adaptive and Distributed Coordination Algorithms for Mobile Sensing Networks." In Cooperative Control. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31595-7_3.

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Sela, Lina, and Waseem Abbas. "Distributed Sensing for Monitoring Water Distribution Systems." In Encyclopedia of Systems and Control. Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-5102-9_100105-1.

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Sela, Lina, and Waseem Abbas. "Distributed Sensing for Monitoring Water Distribution Systems." In Encyclopedia of Systems and Control. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_100105.

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Jamil, Abu Rafe Md, Kishan Kumar Ganguly, and Naushin Nower. "An Experimental Analysis of Reward Functions for Adaptive Traffic Signal Control System." In Distributed Sensing and Intelligent Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-64258-7_44.

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Conference papers on the topic "Distributed Sensing and Control"

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Montgomery, Raymond C., and Dave Ghosh. "Control with Distributed Sensing and Processing." In 1991 American Control Conference. IEEE, 1991. http://dx.doi.org/10.23919/acc.1991.4791616.

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Taou, H. S., Y. Bao, V. B. Venkayya, and H. Bahrami. "Shell Transformations and Distributed Sensing/Control Characteristics." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/vib-3935.

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Abstract Adaptive and controllable shapes and geometries of shells are desirable in many engineering applications, such as antenna dishes, rotor blades, airplane wings, nozzles, etc. In this paper, detailed sensing and control behavior of an adaptive shell panel are investigated. The shell panel changes its geometry from an open shallow shell (30°) to a deep cylindrical shell (150°). Natural frequencies, distributed sensing and damping control characteristics associated with the curvature changes are investigated. Mathematical modeling is presented first, followed by solution procedures. Membr
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Morye, A. A., C. Ding, A. K. Roy-Chowdhury, and J. A. Farrell. "Constrained optimization for opportunistic distributed visual sensing." In 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580825.

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Ishihara, Abraham K., Shahar Ben-Menahem, Alex Kazemi, Bernard Kress, and Mykola Kulishov. "LPFG sensing network for distributed shape control." In SPIE Optical Engineering + Applications, edited by Alex A. Kazemi, Bernard C. Kress, and Edgar A. Mendoza. SPIE, 2014. http://dx.doi.org/10.1117/12.2062377.

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Dang, Fengying, and Feitian Zhang. "DMD-Based Distributed Flow Sensing for Bio-Inspired Autonomous Underwater Robots." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9113.

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This paper presents a novel flow sensing method for autonomous underwater robots using distributed pressure measurements. The proposed flow sensing method harnesses a Bayesian filter and a dynamic mode decomposition (DMD)-based reduced-order flow model to estimate the dynamic flow environments. This data-driven estimation method does not rely on any analytical flow models and is applicable to many and various dynamic flow fields for arbitrarily shaped underwater robots. To demonstrate the effectiveness of the proposed distributed flow sensing approach, a simulation study with a Joukowski-foil-
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Lu, Shiyuan, Che Lin, Zhiyun Lin, Ronghao Zheng, and Gangfeng Yan. "Distributed Kalman filter for relative sensing networks." In 2015 34th Chinese Control Conference (CCC). IEEE, 2015. http://dx.doi.org/10.1109/chicc.2015.7260835.

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"A MULTIROBOT SYSTEM FOR DISTRIBUTED SENSING." In 4th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0001649601370142.

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Chen, Bo. "Mobile Agent Technology for Distributed Sensing and Actuation Systems." In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2233.

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Distributed sensing and actuation systems research has drawn a great attention in recent years from various research communities. These systems are usually deployed in wild fields using a wireless network for the communication. Due to the shortage of power supply and bandwidth, the less communication between system components is desired since it consumes much more power comparing with local computation and uses network bandwidth. In addition, the dynamics of the deployed environments requires distributed sensing and actuation systems being self-organized, scalable, and adaptable. To achieve th
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Nagarkatti, Siddharth P., Christopher O. Rahn, Darren M. Dawson, Erkan Zergeroglu, and Aniket A. Malatpure. "Modal Control of Flexible Systems Using Distributed Sensing." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-2003.

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Abstract In this paper, we design a modal controller for conservative flexible systems that uses distributed sensing. Spatial filtering of the distributed displacement and velocity measurements based on the system eigenfunctions prevents spillover instabilities in the closed-loop system. The proposed control is proven to stabilize a discrete set of controlled modes without destabilizing the remaining, residual modes. We then apply the theory to a single flexible link robot arm and experimentally demonstrate the feasibility of the proposed control strategy. The experiments use high speed video
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Beipeng Mu, Girish Chowdhary, and Jonathan P. How. "Efficient distributed sensing using adaptive censoring based inference." In 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580477.

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Reports on the topic "Distributed Sensing and Control"

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Hurtado, John E. Distributed Sensing & Cooperative Control for Plume Tracing. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada410645.

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Baron, Dror, Marco F. Duarte, Michael B. Wakin, Shriram Sarvotham, and Richard G. Baraniuk. Distributed Compressive Sensing. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada521228.

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Morse, A. S. Intelligent Distributed Control. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada567139.

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Moura, Jose M. Distributed Sensing and Processing: A Graphical Model Approach. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada455686.

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Walmsley, Ian. Scalable Quantum Networks for Distributed Computing and Sensing. Defense Technical Information Center, 2016. http://dx.doi.org/10.21236/ad1007637.

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Juntao Wu. Distributed Fiber Optic Gas Sensing for Harsh Environment. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/938805.

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Levchuk, Georgiy, Andres Ortiz, and John-Collonna Romano. Distributed Sensing and Processing Adaptive Collaboration Environment (D-SPACE). Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada608436.

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Quinn, Meghan. Geotechnical effects on fiber optic distributed acoustic sensing performance. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41325.

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Distributed Acoustic Sensing (DAS) is a fiber optic sensing system that is used for vibration monitoring. At a minimum, DAS is composed of a fiber optic cable and an optic analyzer called an interrogator. The oil and gas industry has used DAS for over a decade to monitor infrastructure such as pipelines for leaks, and in recent years changes in DAS performance over time have been observed for DAS arrays that are buried in the ground. This dissertation investigates the effect that soil type, soil temperature, soil moisture, time in-situ, and vehicle loading have on DAS performance for fiber opt
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Chin, Bryan A. Welding GAP Control Using Infrared Sensing. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada390032.

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Hickey, Jason, John Hauser, and Richard Murray. High Confidence Reconfigurable Distributed Control. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada435114.

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