Relevant bibliographies by topics / Dynamic sensing

Contents

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

Academic literature on the topic 'Dynamic sensing'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Dynamic sensing"

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Braggins, Don. "Dynamic sensing." Sensor Review 24, no. 1 (2004): 30–32. http://dx.doi.org/10.1108/02602280410515789.

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HATANAKA, HIROSHI. "Dynamic pressure sensing." Journal of the Japan Society for Precision Engineering 52, no. 4 (1986): 615–18. http://dx.doi.org/10.2493/jjspe.52.615.

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Baden-Fuller, Charles, and David J. Teece. "Market sensing, dynamic capability, and competitive dynamics." Industrial Marketing Management 89 (August 2020): 105–6. http://dx.doi.org/10.1016/j.indmarman.2019.11.008.

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Yu, Francis T. S., Kun Pan, Dazun Zhao, and Paul B. Ruffin. "Dynamic fiber specklegram sensing." Applied Optics 34, no. 4 (1995): 622. http://dx.doi.org/10.1364/ao.34.000622.

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Talaie, Afshad, Ji-Yoon Lee, Kimihiro Adachi, Takahisa Taguchi, and Jose Romagnoli. "Dynamic polymeric electrodes, dynamic computer modeling and dynamic electrochemical sensing." Journal of Electroanalytical Chemistry 468, no. 1 (1999): 19–25. http://dx.doi.org/10.1016/s0022-0728(99)00091-1.

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J. V. Stafford and J. G. Hendrick. "Dynamic Sensing of Soil Pans." Transactions of the ASAE 31, no. 1 (1988): 0009–13. http://dx.doi.org/10.13031/2013.30656.

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Gamper, Urs, Peter Boesiger, and Sebastian Kozerke. "Compressed sensing in dynamic MRI." Magnetic Resonance in Medicine 59, no. 2 (2008): 365–73. http://dx.doi.org/10.1002/mrm.21477.

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Lingala, S. G., and M. Jacob. "Blind Compressive Sensing Dynamic MRI." IEEE Transactions on Medical Imaging 32, no. 6 (2013): 1132–45. http://dx.doi.org/10.1109/tmi.2013.2255133.

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Gilkerson, Robert. "A Disturbance in the Force: Cellular Stress Sensing by the Mitochondrial Network." Antioxidants 7, no. 10 (2018): 126. http://dx.doi.org/10.3390/antiox7100126.

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As a highly dynamic organellar network, mitochondria are maintained as an organellar network by delicately balancing fission and fusion pathways. This homeostatic balance of organellar dynamics is increasingly revealed to play an integral role in sensing cellular stress stimuli. Mitochondrial fission/fusion balance is highly sensitive to perturbations such as loss of bioenergetic function, oxidative stress, and other stimuli, with mechanistic contribution to subsequent cell-wide cascades including inflammation, autophagy, and apoptosis. The overlapping activity with m-AAA protease 1 (OMA1) met
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Villalon-Turrubiates, I. E. "DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4 (September 19, 2018): 213–19. http://dx.doi.org/10.5194/isprs-annals-iv-4-213-2018.

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<p><strong>Abstract.</strong> The analysis of dynamical models for prediction and geosimulation using the information extracted from a geographical region processed from the data provided by multispectral remote sensing systems provides useful information for urban planning and resource management. However, several topics of interest on this particular matter are still to be properly studied. Using the remote sensing data that has been extracted from multispectral images from a particular geographic region in discrete time, its dynamic study is performed in both, spatial reso
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Dissertations / Theses on the topic "Dynamic sensing"

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Tsan, Derek. "Zinc oxide nanowires for dynamic strain sensing." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44269.

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A dynamic strain sensor using piezoelectric zinc oxide nanowires was demonstrated for potential application in structural health monitoring. Simulations and reviews of literature determined that strain of the nanowires by uniaxial compression yields the largest piezoelectric potential and that the piezoelectric coefficient of zinc oxide nanowires is enhanced due to nanoscale size effects. The fabrication of zinc oxide nanowires on various substrates was investigated in order to determine the ideal materials and seed layer deposition methods to yield high quality vertically-aligned nanowires. N
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Ye, Yuxian. "Study of Sensing Issues in Dynamic Spectrum Access." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90184.

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Dynamic Spectrum Access (DSA) is now a commonly used spectrum sharing paradigm to mitigate the spectrum shortage problem. DSA technology allows unlicensed secondary users to access the unused frequency bands without interfering with the incumbent users. The key technical challenges in DSA systems lie in spectrum allocation problems and spectrum user's security issues. This thesis mainly focuses on spectrum monitoring technology in spectrum allocation and incumbent users' (IU) privacy issue. Spectrum monitoring is a powerful tool in DSA to help commercial users to access the unused bands. We
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Ward, Christopher Charles. "Terrain sensing and estimation for dynamic outdoor mobile robots." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42419.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.<br>Includes bibliographical references (p. 120-125).<br>In many applications, mobile robots are required to travel on outdoor terrain at high speed. Compared to traditional low-speed, laboratory-based robots, outdoor scenarios pose increased perception and mobility challenges which must be considered to achieve high performance. Additionally, high-speed driving produces dynamic robot-terrain interactions which are normally negligible in low speed driving. This thesis presents algorithms for estimating
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Goupil, Marc Y. "Dynamic Pressure Sensing for the Flight Test Data System." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2115.

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This thesis describes the design, assembly, and test of the FTDS-K, a new device in the Boundary Layer Data System (BLDS) family of flight data acquisition systems. The FTDS-K provides high-frequency, high-gain data acquisition capability for up to two pressure sensors and an additional three low-frequency pressure sensors. Development of the FTDS-K was separated into a core module, specialized analog subsystem, and practical testing of the FTDS-K in a flow measurement mission. The core module combines an nRF52840-based microcontroller module, switching regulator, microSD card, real-time clock
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Valieva, Inna. "Spectrum Sensing for Dynamic Spectrum Access in Cognitive Radio." Licentiate thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-52881.

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Abstract. The number of mobile devices is constantly growing, and the exclusivestatic spectrum allocation approach is leading to the spectrum scarcity problem whensome of the licensed bands are heavily occupied and others are nearly unused.Spectrum sharing and opportunistic spectrum access allow achieving more efficientspectrum utilization. Radio scene analysis is a first step in the cognitive radiooperation required to employ opportunistic spectrum access scenarios such as thedynamic spectrum access or frequency hopping spread spectrum. The objective of thiswork is to develop and virtual prot
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Wafula, Alfred Brian. "Dynamic Monitoring of Cytotoxicity Using Electric Cell Substrate Impendence Sensing." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/3800.

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Electric cell-substrate impedance sensing (ECIS) pioneered by Giaever and Keese is suitable for continuous, automatic and real-time cell attachment analysis. ECIS is a novel electrical method to study, in real time, many of the activities of animal cells when grown in tissue culture. These include morphological changes, cell locomotion, and other behaviors directed by the cell's cytoskeleton. One of the most direct ECIS measurements is that of the attachment and spreading behaviors of cells. These measurements allow one to study and quantify the interaction of cultured cells with extracellular
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Purohit, Aveek. "Controlled-mobile Sensor Networks for Dynamic Sensing and Monitoring Applications." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/357.

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Many potential indoor sensing and monitoring applications are characterized by hazardous and constantly-changing operating environments. For example, consider emergency response scenarios such as urban fire rescue. Traditionally, first responders have little access to situational information. In-situ information about the conditions, such as the extent and evolution of the indoor fire, can augment rescue efforts and reduce risk to emergency personnel. Static sensor networks that are pre-deployed or manually deployed have been proposed for such applications, but are less practical due to need f
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Naeli, Kianoush. "Optimization of piezoresistive cantilevers for static and dynamic sensing applications." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28247.

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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Brand, Oliver; Committee Member: Adibi, Ali; Committee Member: Allen, Mark G.; Committee Member: Bottomley, Lawrence A.; Committee Member: Degertekin, F. Levent.
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Jackson, Cornelius Christiaan. "Tactile force-sensing for dynamic gripping using piezoelectric force- sensors." Thesis, Bloemfontein : Central University of Technology, Free State, 2009. http://hdl.handle.net/11462/34.

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Oxborrow, Joseph B. "Dynamic Nanochannels for Biosensing Applications." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/4261.

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Inexpensive label-free detection of biomarker panels in serum could revolutionize earlycancer diagnosis and treatment. Such detection capabilities may be possible with dynamicnanochannels in conjunction with electrical impedance measurement. In Dr. Greg Nordin's lab I designed, fabricated and tested several iterations of these sensors with polydimethyl-siloxane microfluidics. The final design yielded a dynamic nanochannel array sensor thatshowed a 140% impedance change when exposed to 14µM bovine serum albumin in phos-phate buffered saline. For the geometry and noise limits of the tested devic
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Books on the topic "Dynamic sensing"

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Eskandari, Maryam. An experimental sensing set-up for dynamic dispatching, using surveillance cameras. National Library of Canada, 2002.

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Bastiaanssen, W. G. M. A methodology for the assessment of surface resistance and soil water storage variability at mesoscale based on remote sensing measurements: A case study with HAPEX-EFEDA data. International Association of Hydrological Sciences, 1994.

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Eleveld, Marieke A. Exploring coastal morphodynamics of Ameland (the Netherlands) with remote sensing monitoring techniques and dynamic modelling in GIS. ITC, 1999.

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Milʹshin, A. A. (Aleksandr Alekseevich), ed. Microwave radiation of the ocean-atmosphere: Boundary heat and dynamic interaction. Springer, 2010.

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Remote sensing and its application: A monograph monitoring vegetal landcover and desertification. University Book House, 2002.

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Wispelaere, G. de. Utilisation des données satellitaires dans une démarche de suivi de la dynamique de la végétation pastorale sahélienne dans le Nord Sénégal: Rapport scientifique. I.E.M.V.T./C.I.R.A.D. ; Paris : O.R.S.T.O.M., Institut français de recherche scientifique pour le développement en coopération, 1985.

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Rostami, Mohammad. Compressed Sensing with Side Information on the Feasible Region. Springer International Publishing, 2013.

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Proceedings, of SPIE ecosystems' dynamics agricultural remote sensing and modeling and site-specific agriculture. Ecosystems' dynamics, agricultural remote sensing and modeling, and site-specific agriculture: 7 August 2003, San Diego, California, USA. SPIE, 2003.

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Kyamakya, Kyandoghere. Selected Topics in Nonlinear Dynamics and Theoretical Electrical Engineering. Springer Berlin Heidelberg, 2013.

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P, Cracknell Arthur, and Rowan E. S, eds. Physical processes in the coastal zone: Computer modelling and remote sensing : proceedings of the forty ninth Scottish Universities Summer School in Physics, Dundee, August 1997. Scottish Universities Summer School in Physics, 1998.

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Book chapters on the topic "Dynamic sensing"

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Cutkosky, Mark R., and John Ulmen. "Dynamic Tactile Sensing." In Springer Tracts in Advanced Robotics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03017-3_18.

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Hannon, Bruce, and Matthias Ruth. "Odor Sensing." In Modeling Dynamic Biological Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05615-9_15.

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Ruth, Matthias, and Bruce Hannon. "Odor-Sensing Model." In Modeling Dynamic Biological Systems. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-0651-4_15.

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Liang, Ying-Chang. "Spectrum Sensing Theories and Methods." In Dynamic Spectrum Management. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0776-2_3.

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Terzic, Jenny, Edin Terzic, Romesh Nagarajah, and Muhammad Alamgir. "Ultrasonic Sensing Technology." In Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00633-8_2.

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Warren, Will, Logan Ott, Erynn Elmore, Erik Moro, and Matt Briggs. "Laser Speckle in Dynamic Sensing Applications." In Special Topics in Structural Dynamics, Volume 6. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04729-4_29.

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Dantu, Neeraj Kumar Reddy. "Dynamic Spectrum Sensing in Cognitive Radio Networks Using Compressive Sensing." In Lecture Notes in Electrical Engineering. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1823-4_9.

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Terzic, Edin, Jenny Terzic, Romesh Nagarajah, and Muhammad Alamgir. "Capacitive Sensing Technology." In A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4060-3_2.

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Jing, Zhongliang, Han Pan, and Gang Xiao. "Application to Environmental Surveillance: Dynamic Image Estimation Fusion and Optimal Remote Sensing with Fuzzy Integral." In Intelligent Environmental Sensing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12892-4_7.

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Zhao, Huijing, Long Xiong, Yiming Liu, Xiaolong Zhu, Yipu Zhao, and Hongbin Zha. "Dynamic Environment Sensing intelligent vehicle (IV) dynamic environment sensing Using an Intelligent Vehicle intelligent vehicle (IV)." In Encyclopedia of Sustainability Science and Technology. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_482.

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Conference papers on the topic "Dynamic sensing"

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Holman, Rob. "K3. NEARSHORE REMOTE SENSING." In Coastal Dynamics 2009 - Impacts of Human Activities on Dynamic Coastal Processes. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789814282475_0003.

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Yoon, Huisu, Dong-wook Lee, Juyoung Lee, Seung Hong Choi, Sung-Hong Park, and Jong Chul Ye. "Multiband dynamic compressed sensing." In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015). IEEE, 2015. http://dx.doi.org/10.1109/isbi.2015.7164021.

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Sitpathom, Nonthanan, Tanyakorn Muangnapoh, and Judith M. Dawes. "Dynamic Optical Strain Sensing." In Conference on Lasers and Electro-Optics/Pacific Rim. OSA, 2020. http://dx.doi.org/10.1364/cleopr.2020.p3_23.

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Stoykova, Elena, Youngmin Kim, and Joosup Park. "Compressed dynamic speckle sensing." In Digital Holography and Three-Dimensional Imaging. OSA, 2020. http://dx.doi.org/10.1364/dh.2020.hth4h.6.

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Li, Tianwei, and Qingze Zou. "Multi-Mobile Sensing With Temporal-Spatial Coupling via Compressed Sensing." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9218.

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Abstract In this paper, the problem of using a limited number of mobile sensors to sense/measure a time-varying distribution of a field over a multi dimensional space is considered. As the number of sensors, in general, is not adequate for capturing the dynamic distribution with the needed spatial resolution, the sensors are required to be transited between the sampled locations, resulting in intermittent measurement at each sampled location. Therefore, it becomes challenging to use the measured data to recover/restore not only the dynamic process at each sampled/measured location, but also th
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Li, Tianwei, and Qingze Zou. "Mobile Sensing of Multi-Dimensional Dynamic Field via Compressed Sensing." In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3264.

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Abstract In this paper, we consider to measure time-varying dynamic signals at discrete locations by using a single mobile sensor The challenge arises as the mobile sensor is required to transit between the sampling locations, resulting in intermittent measurements at each location, and the time-varying dynamic signals must be recovered from the intermittent measured data. In this work, we propose to tackle this single mobile sensing of multi-location dynamic signals through the compressed sensing framework. Both the temporal-spatial coupling arising from the random sampling requirement and th
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Pan, Shijia, Mostafa Mirshekari, Hae Young Noh, and Pei Zhang. "Structural sensing system with networked dynamic sensing configuration." In the 14th International Conference. ACM Press, 2015. http://dx.doi.org/10.1145/2737095.2737147.

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Wang, Hongwei, Hang Yu, Michael Hoy, Justin Dauwels, and Heping Wang. "Variational Bayesian dynamic compressive sensing." In 2016 IEEE International Symposium on Information Theory (ISIT). IEEE, 2016. http://dx.doi.org/10.1109/isit.2016.7541533.

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Abdelhamed, Yasser M. H., Mohamed A. Al Masri, and Abu B. Sesay. "Dynamic Distribution-Free Spectrum Sensing." In 2017 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2017. http://dx.doi.org/10.1109/wcnc.2017.7925634.

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Donval, A., T. Fisher, D. Cheskis, Y. Ofir, and M. Oron. "Increasing dynamic range of cameras with dynamic sunlight filter (DSF)." In SPIE Defense, Security, and Sensing, edited by Bjørn F. Andresen, Gabor F. Fulop, and Paul R. Norton. SPIE, 2011. http://dx.doi.org/10.1117/12.887732.

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Reports on the topic "Dynamic sensing"

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Armstrong, Derek Elswick, and Eddy Marcel Elvire Timmermans. Remote Sensing of Dynamic Events. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1530762.

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Hays, Park, Matthew J. Kagie, David B. Karelitz, Randolph "Rex" Kay, John Steven Mincey, and Mark Christopher Woods. SPARR: Spiking/Processing Array for Wide Dynamic Range and High Resolution Photonic Sensing. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1572222.

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Maffione, Robert A. Dynamic Optical Properties, Underwater Visibility, and Their Relationship to Hyperspectral Remote-Sensing Reflectance. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada636791.

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Umberger, Pierce. Experimental Evaluation of Dynamic Crack Branching in Poly(methyl methacrylate) (PMMA) Using the Method of Coherent Gradient Sensing. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada518614.

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Hay, Alex E., and Len Zedel. Toward a 3rd Generation Sediment Dynamics Sensing System. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada523302.

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Vrieling, A., and J. J. van der Sanden. Satellite Remote Sensing for Monitoring Coastline Dynamics of the Canadian Beaufort Sea Coast. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219760.

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Godin, Oleg A. Emergence of the Green's Functions from Noise and Passive Acoustic Remote Sensing of Ocean Dynamics. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada531686.

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Godin, Oleg A. Emergence of the Green's Functions from Noise and Passive Acoustic Remote Sensing of Ocean Dynamics. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada542098.

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Gardner, T. W., and A. C. Miller. Surface hydrology, sediment transport dynamics, and remote sensing of disturbed watersheds in a humid temperature region. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/6389923.

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Bodie, Mark, Michael Parker, Alexander Stott, and Bruce Elder. Snow-covered obstacles’ effect on vehicle mobility. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/38839.

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The Mobility in Complex Environments project used unmanned aerial systems (UAS) to identify obstacles and to provide path planning in forward operational locations. The UAS were equipped with remote-sensing devices, such as photogrammetry and lidar, to identify obstacles. The path-planning algorithms incorporated the detected obstacles to then identify the fastest and safest vehicle routes. Future algorithms should incorporate vehicle characteristics as each type of vehicle will perform differently over a given obstacle, resulting in distinctive optimal paths. This study explored the effect of
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