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Статті в журналах з теми "Targeted sampling"
Zhang, Jun, Yi Isaac Yang, and Frank Noé. "Targeted Adversarial Learning Optimized Sampling." Journal of Physical Chemistry Letters 10, no. 19 (September 16, 2019): 5791–97. http://dx.doi.org/10.1021/acs.jpclett.9b02173.
Повний текст джерелаChen, Sue, James A. Cummings, Jerome M. Schmidt, Elizabeth R. Sanabia, and Steven R. Jayne. "Targeted ocean sampling guidance for tropical cyclones." Journal of Geophysical Research: Oceans 122, no. 5 (May 2017): 3505–18. http://dx.doi.org/10.1002/2017jc012727.
Повний текст джерелаWatters, John K., and Patrick Biernacki. "Targeted Sampling: Options for the Study of Hidden Populations." Social Problems 36, no. 4 (October 1989): 416–30. http://dx.doi.org/10.1525/sp.1989.36.4.03a00070.
Повний текст джерелаWatters, John K., and Patrick Biernacki. "Targeted Sampling: Options for the Study of Hidden Populations." Social Problems 36, no. 4 (October 1989): 416–30. http://dx.doi.org/10.2307/800824.
Повний текст джерелаWilliams, Michael S., Eric D. Ebel, and Scott J. Wells. "Population inferences from targeted sampling with uncertain epidemiologic information." Preventive Veterinary Medicine 89, no. 1-2 (May 2009): 25–33. http://dx.doi.org/10.1016/j.prevetmed.2008.12.008.
Повний текст джерелаAdamchuk, Viacheslav I., Raphael A. Viscarra Rossel, David B. Marx, and Ashok K. Samal. "Using targeted sampling to process multivariate soil sensing data." Geoderma 163, no. 1-2 (June 2011): 63–73. http://dx.doi.org/10.1016/j.geoderma.2011.04.004.
Повний текст джерелаBorges, Lisa, Alain F. Zuur, Emer Rogan, and Rick Officer. "Optimum sampling levels in discard sampling programs." Canadian Journal of Fisheries and Aquatic Sciences 61, no. 10 (October 1, 2004): 1918–28. http://dx.doi.org/10.1139/f04-138.
Повний текст джерелаCarlson, Robert H. "Cervical Cancer: Targeted Sampling Detects Involved Nodes in Unusual Places." Oncology Times 31, no. 16 (August 2009): 25. http://dx.doi.org/10.1097/01.cot.0000360404.44039.b8.
Повний текст джерелаChen, Fan, Yini Zhang, and Karl Rohe. "Targeted sampling from massive block model graphs with personalized PageRank." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 82, no. 1 (December 31, 2019): 99–126. http://dx.doi.org/10.1111/rssb.12349.
Повний текст джерелаNumao, N., M. Ito, Y. Uchida, S. Yoshida, T. Nakayama, M. Inoue, M. Tatokoro, et al. "211 Optimal number of sampling cores in MRI-targeted biopsy." European Urology Supplements 14, no. 2 (April 2015): e211. http://dx.doi.org/10.1016/s1569-9056(15)60212-3.
Повний текст джерелаДисертації з теми "Targeted sampling"
Isaac, Giorgis. "Development of Enhanced Analytical Methodology for Lipid Analysis from Sampling to Detection : A Targeted Lipidomics Approach." Doctoral thesis, Uppsala University, Analytical Chemistry, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-5810.
Повний текст джерелаThis thesis covers a wide range of analytical method development for lipid analysis in complex biological samples; from sample preparation using pressurized fluid extraction (PFE) and separation with reversed phase capillary liquid chromatography (RP-LC) to detection by electrospray ionization mass spectrometry (ESI/MS) and tandem MS.
The requirements for fast, reliable and selective extraction methods with minimal usage of solvents have accelerated the development of new extraction techniques. PFE is one of the new automated, fast and efficient liquid extraction techniques which use elevated temperature and pressure with standard liquid solvents. In this thesis the reliability and efficiency of the PFE technique was investigated for the extraction of total lipid content from cod, herring muscle and human brain tissue as well as for pesticides from fatty foodstuffs. Improved or comparable efficiencies were achieved with reduced time and solvent consumption as compared to traditional methods.
A RP-LC coupled online to ESI/MS for the analysis of phosphatidylcholine (PC) and sphingomyelin (SM) molecular species was developed and used for the analysis of brain lipids from eight groups of mice treated with vehicle and various neuroleptics. The effect of postnatal iron administration in lipid composition and behavior was investigated. Whether or not these effects could be altered by subchronic administration of the neuroleptics (clozapine and haloperidol) were examined. The results support the hypothesis that an association between psychiatric disorders, behavior abnormalities and lipid membrane constitution in the brain exists.
Finally, a tandem MS precursor ion scan was used to analyze the developmental profile of brain sulfatide accumulation in arylsulfatase A (ASA) deficient (ASA -/-) as compared to wild type control (ASA +/+) mice. The ASA -/- mice were developed as a model of the monogenic disease metachromatic leukodystrophy with an established deficiency of the lysosomal enzyme ASA. The results showed that an alteration in the composition of sulfatide molecular species was observed between the ASA -/- and ASA +/+ mice.
This thesis shows that modern analytical methods can provide new insights in the extraction and analysis of lipids from complex biological samples.
Holmberg, Edward A. IV. "Data Visualization to Evaluate and Facilitate Targeted Data Acquisitions in Support of a Real-time Ocean Forecasting System." ScholarWorks@UNO, 2014. http://scholarworks.uno.edu/td/1873.
Повний текст джерелаNguyen, Trang. "Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking." ScholarWorks@UNO, 2003. http://scholarworks.uno.edu/td/20.
Повний текст джерелаQian, Jiajie. "Nanofiber-enabled multi-target passive sampling device for legacy and emerging organic contaminants." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6487.
Повний текст джерелаFischell, Erin Marie. "Characterization of underwater target geometry from autonomous underwater vehicle sampling of bistatic acoustic scattered fields." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100161.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 153-156).
One of the long term goals of Autonomous Underwater Vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and expert image interpretation. This thesis proposes a vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target for lower cost-per-vehicle sensing and onboard, fully autonomous classification. The contributions of this thesis include the collection of novel high-quality bistatic data sets around spherical and cylindrical targets in situ during the BayEx'14 and Massachusetts Bay 2014 scattering experiments and the development of a machine learning methodology for classifying target shape and estimating orientation using bistatic amplitude data collected by an AUV. To achieve the high quality, densely sampled 3D bistatic scattering data required by this research, vehicle broadside sampling behaviors and an acoustic payload with precision timed data acquisition were developed. Classification was successfully demonstrated for spherical versus cylindrical targets using bistatic scattered field data collected by the AUV Unicorn as a part of the BayEx'14 scattering experiment and compared to simulated scattering models. The same machine learning methodology was applied to the estimation of orientation of aspect-dependent targets, and was demonstrated by training a model on data from simulation then successfully estimating the orientations of a steel pipe in the Massachusetts Bay 2014 experiment. The final models produced from real and simulated data sets were used for classification and parameter estimation of simulated targets in real time in the LAMSS MOOS-IvP simulation environment.
by Erin Marie Fischell.
Ph. D.
Moyer, Steven K. "Modeling challenges of advanced thermal imagers." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-02272006-144729/.
Повний текст джерелаDr. William T. Rhodes, Committee Co-Chair ; Dr. John Buck, Committee Member ; Dr. William Hunt, Committee Member ; Dr. Stephen P. DeWeerth, Committee Member ; Dr. Ronald G. Driggers, Committee Member ; Dr. Gisele Bennett, Committee Chair.
Lux, Johannes Thomas [Verfasser], and Ingeborg [Akademischer Betreuer] Levin. "A new target preparation facility for high precision AMS measurements and strategies for efficient 14CO2 sampling / Johannes Thomas Lux ; Betreuer: Ingeborg Levin." Heidelberg : Universitätsbibliothek Heidelberg, 2018. http://d-nb.info/1177252260/34.
Повний текст джерелаDixon, Wallace E. Jr, Robert M. Price, Michael Watkins, and Christine Brink. "Touchstat V. 3.00: A New and Improved Monte Carlo Adjunct for the Sequential Touching Task." Digital Commons @ East Tennessee State University, 2007. https://doi.org/10.3758/BF03193010.
Повний текст джерелаLamberti, Roland. "Contributions aux méthodes de Monte Carlo et leur application au filtrage statistique." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLL007/document.
Повний текст джерелаThis thesis deals with integration calculus in the context of Bayesian inference and Bayesian statistical filtering. More precisely, we focus on Monte Carlo integration methods. We first revisit the importance sampling with resampling mechanism, then its extension to the dynamic setting known as particle filtering, and finally conclude our work with a multi-target tracking application. Firstly, we consider the problem of estimating some moment of a probability density, known up to a constant, via Monte Carlo methodology. We start by proposing a new estimator affiliated with the normalized importance sampling estimator but using two proposition densities rather than a single one. We then revisit the importance sampling with resampling mechanism as a whole in order to produce Monte Carlo samples that are independent, contrary to the classical mechanism, which enables us to develop two new estimators. Secondly, we consider the dynamic aspect in the framework of sequential Bayesian inference. We thus adapt to this framework our new independent resampling technique, previously developed in a static setting. This yields the particle filtering with independent resampling mechanism, which we reinterpret as a special case of auxiliary particle filtering. Because of the increased cost required by this technique, we next propose a semi independent resampling procedure which enables to control this additional cost. Lastly, we consider an application of multi-target tracking within a sensor network using a new Bayesian model, and empirically analyze the results from our new particle filtering algorithm as well as a sequential Markov Chain Monte Carlo algorithm
Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.
Повний текст джерелаКниги з теми "Targeted sampling"
Ahrens, T. J. Planetary and primitive object strength measurements and sampling apparatus: NASA #NAGW 2439, final report; February 1, 1991 through January 31, 1997. Pasadena, Calif: California Institute of Technology, Seismological Laboratory, 1997.
Знайти повний текст джерела1963-, Mandrak Nicholas Edward, Canada. Dept. of Fisheries and Oceans., Great Lakes Laboratory for Fisheries and Aquatic Sciences., and Canada. Dept. of Fisheries and Oceans. Central and Arctic Region., eds. Targeted, wadeable sampling of fish species at risk in the Lake St. Clair watershed of southwestern Ontario, 2003. Burlington, Ont: Dept. of Fisheries and Oceans, 2006.
Знайти повний текст джерелаBerry, Justin, Youssef Chouhoud, and Jane Junn. Reaching Beyond Low-Hanging Fruit. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.1.
Повний текст джерелаTaberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. Sampling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0004.
Повний текст джерелаHankin, David, Michael S. Mohr, and Kenneth B. Newman. Sampling Theory. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198815792.001.0001.
Повний текст джерелаGimpel, James G. Sampling for Studying Context. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.23.
Повний текст джерелаBerinsky, Adam J. Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias. Cambridge University Press, 2020.
Знайти повний текст джерелаCaughey, Devin, Sara Chatfield, and Adam J. Berinskey. Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias. Cambridge University Press, 2020.
Знайти повний текст джерелаLapierre, Laurent M., and Alicia D. McMullan. A Review of Methodological and Measurement Approaches to the Study of Work and Family. Edited by Tammy D. Allen and Lillian T. Eby. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199337538.013.4.
Повний текст джерелаTaberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. Environmental DNA for functional diversity. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0010.
Повний текст джерелаЧастини книг з теми "Targeted sampling"
Zhang, Li-Chun. "Targeted random walk sampling." In Graph Sampling, 93–112. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003203490-6.
Повний текст джерелаChambaz, Antoine, Emilien Joly, and Xavier Mary. "Targeted Learning Using Adaptive Survey Sampling." In Springer Series in Statistics, 541–59. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-65304-4_29.
Повний текст джерелаTao, Jinglu, Xiaolong Zhang, and Xiaoli Lin. "A Targeted Drug Design Method Based on GRU and TopP Sampling Strategies." In Intelligent Computing Theories and Application, 423–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13829-4_37.
Повний текст джерелаPfahler, V., J. Adu-Gyamfi, D. O’Connell, and F. Tamburini. "Extraction Protocol." In Oxygen Isotopes of Inorganic Phosphate in Environmental Samples, 17–31. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97497-8_2.
Повний текст джерелаTian, Shikun, Xinyu Jin, and Yu Zhang. "An Adaptive Sampling Target Tracking Method of WMSNs." In Lecture Notes in Computer Science, 188–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13498-2_25.
Повний текст джерелаComitani, Federico, and Francesco L. Gervasio. "Modeling Ligand-Target Binding with Enhanced Sampling Simulations." In Biomolecular Simulations in Structure-Based Drug Discovery, 43–66. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2018. http://dx.doi.org/10.1002/9783527806836.ch3.
Повний текст джерелаXue, Jianru, Nanning Zheng, and Xiaopin Zhong. "Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking." In Lecture Notes in Computer Science, 330–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11538059_35.
Повний текст джерелаLiu, Weifeng, Zhong Chai, and Chenglin Wen. "A Multiple Shape-Target Tracking Algorithm by Using MCMC Sampling." In Lecture Notes in Computer Science, 563–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31020-1_67.
Повний текст джерелаLütkemeyer, D., I. Poggendorf, Thomas Scherer, J. Zhang, A. Knoll, and J. Lehmann. "Robot Automation of Sampling and Sample Management during Cultivation of Mammalian Cells in Pilot Scale." In Animal Cell Technology: From Target to Market, 459–62. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0369-8_111.
Повний текст джерелаXue, Shuqi, Guangshan Liao, Lifeng Tan, Yu Tian, Yuan Wu, Yan Fu, Zhixian Zhang, and Chunhui Wang. "Research on Human-Robot Cooperative Target Recognition for Spatial Sampling Task." In Man-Machine-Environment System Engineering, 434–41. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4786-5_60.
Повний текст джерелаТези доповідей конференцій з теми "Targeted sampling"
Jinpeng, Yuan, Cao Jihua, and Xiong Xing. "Low Sampling Rate Reconstruction of Medical Imaging: Application of Targeted Sampling Based on OMP." In 2012 5th International Conference on Intelligent Networks and Intelligent Systems (ICINIS). IEEE, 2012. http://dx.doi.org/10.1109/icinis.2012.27.
Повний текст джерелаSamsuzana Abd Aziz and Brian L Steward. "Targeted Sampling of Elevation Data Based on Spatial Uncertainty of Prior Measurements." In 2008 Providence, Rhode Island, June 29 - July 2, 2008. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2008. http://dx.doi.org/10.13031/2013.24786.
Повний текст джерелаBirch, J., R. Marin, T. O'Reilly, D. Pargett, S. Poulos, C. Preston, H. Ramm, et al. "Autonomous Targeted Sampling of the Deep Chlorophyll Maximum Layer in a Subtropical North Pacific Eddy." In OCEANS 2018 MTS/IEEE Charleston. IEEE, 2018. http://dx.doi.org/10.1109/oceans.2018.8604898.
Повний текст джерелаMartin, Peter R., Derek W. Cool, Cesare Romagnoli, Aaron Fenster, and Aaron D. Ward. "Optimizing MRI-targeted fusion prostate biopsy: the effect of systematic error and anisotropy on tumor sampling." In SPIE Medical Imaging, edited by Robert J. Webster and Ziv R. Yaniv. SPIE, 2015. http://dx.doi.org/10.1117/12.2081211.
Повний текст джерелаKõiv, Kristi, and Minni Aia-Utsal. "VICTIMIZED TEACHERS’ EXPERIENCES ABOUT TEACHER-TARGETED BULLYING BY STUDENTS." In International Psychological Applications Conference and Trends. inScience Press, 2021. http://dx.doi.org/10.36315/2021inpact036.
Повний текст джерелаHalliday, Peter J., and Karl Grosh. "Non-Linear Least-Squares Estimation of Material Properties and Structural Intensity in Non-Uniform Beams." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1620.
Повний текст джерелаShen, Yuecheng, Yan Liu, Cheng Ma, and Lihong V. Wang. "Applying sub-Nyquist sampling in optical time-reversal-based wavefront shaping to boost targeted light transport through opaque scattering media (Conference Presentation)." In Adaptive Optics and Wavefront Control for Biological Systems IV, edited by Thomas G. Bifano, Sylvain Gigan, and Joel Kubby. SPIE, 2018. http://dx.doi.org/10.1117/12.2287064.
Повний текст джерелаGernand, Jeremy M. "Evaluation of the Risk Reduction Effectiveness in OSHA’s Workplace Atmosphere Sampling Activities." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-65942.
Повний текст джерелаTagarieva, Larisa, Eduardo Chacon, David Olutusin, and Sneh Sindhu. "Through Drillpipe Formation Testing: Unlocking Bypassed Pay, A Case Study Onshore Kuwait." In Offshore Technology Conference. OTC, 2022. http://dx.doi.org/10.4043/32040-ms.
Повний текст джерелаDawod, H. "EVALUATION OF THE EFFECT OF GASTRIC TARGETED BIOPSY SAMPLING WITH I-SCAN OE TECHNOLOGY ON THE DIAGNOSTIC YIELD OF THE CLO TEST OF H. PYLORI INFECTION." In ESGE Days 2022. Georg Thieme Verlag KG, 2022. http://dx.doi.org/10.1055/s-0042-1744966.
Повний текст джерелаЗвіти організацій з теми "Targeted sampling"
LaFreniere, L. M. Final work plan for targeted sampling at Webber, Kansas. Office of Scientific and Technical Information (OSTI), May 2006. http://dx.doi.org/10.2172/925323.
Повний текст джерелаLaFreniere, L. M. Final work plan : targeted groundwater sampling and monitoring well installation for potential site reclassification at Barnes, Kansas. Office of Scientific and Technical Information (OSTI), July 2006. http://dx.doi.org/10.2172/890568.
Повний текст джерелаResearch, IFF. Small and Micro Food Business Operator (FBO) Tracking Survey: Wave 3 2021 - Technical Report. Food Standards Agency, May 2022. http://dx.doi.org/10.46756/sci.fsa.sty242.
Повний текст джерелаLandau, Sergei Yan, John W. Walker, Avi Perevolotsky, Eugene D. Ungar, Butch Taylor, and Daniel Waldron. Goats for maximal efficacy of brush control. United States Department of Agriculture, March 2008. http://dx.doi.org/10.32747/2008.7587731.bard.
Повний текст джерелаJenkins, Thomas F., Alan D. Hewitt, Thomas A. Ranney, Charles A. Ramsey, and Dennis J. Lambert. Sampling Strategies Near a Low-Order Detonation and a Target at an Artillery Impact Area. Fort Belvoir, VA: Defense Technical Information Center, November 2004. http://dx.doi.org/10.21236/ada428488.
Повний текст джерелаAdams, Terry R., Steven D. Nolen, Jeremy Ed Sweezy, and Tony P. Hasenack. THE FREE GAS THERMAL TREATMENT IN MCATK: Sampling the Thermal Motion of the Target Nucleus (U). Office of Scientific and Technical Information (OSTI), March 2013. http://dx.doi.org/10.2172/1053544.
Повний текст джерелаBeck, Aaron. RiverOceanPlastic: Land-ocean transfer of plastic debris in the North Atlantic, Cruise No. AL534/2, 05 March – 26 March 2020, Malaga (Spain) – Kiel (Germany). GEOMAR Helmholtz Centre for Ocean Research Kiel, 2020. http://dx.doi.org/10.3289/cr_al534-2.
Повний текст джерелаKamalvand, Ahmad, Paul MacDonald, and Thai-Duong Tran. Factored Sampling Tracking: Comparison of the Kalman and the Condensation Algorithms for Missile Tracking in a Defense Target Environment. Fort Belvoir, VA: Defense Technical Information Center, December 2004. http://dx.doi.org/10.21236/ada430271.
Повний текст джерелаSweezy, Jeremy Ed, Terry R. Adams, and Steven D. Nolen. REACTION SAMPLING IN MCATK: Using the Thermal Motion of the Target Nucleus to Perform Elastic and Inelastic Scattering (U). Office of Scientific and Technical Information (OSTI), March 2013. http://dx.doi.org/10.2172/1068961.
Повний текст джерелаHunter, Fraser, and Martin Carruthers. Iron Age Scotland. Society for Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.193.
Повний текст джерела