Relevant bibliographies by topics / Range estimating

Contents

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

Academic literature on the topic 'Range estimating'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Range estimating"

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De Haan, L., and Sidney Resnick. "Estimating the home range." Journal of Applied Probability 31, no. 3 (September 1994): 700–720. http://dx.doi.org/10.2307/3215149.

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A proposal is given for estimating the home range of an animal based on sequential sightings. We assume the given sightings are independent, identically distributed random vectors X1,· ··, Xn whose common distribution has compact support. If are the polar coordinates of the sightings, then is a sup-measure and corresponds to the right endpoint of the distribution . The corresponding upper semi-continuous function l(θ) is the boundary of the home range. We give a consistent estimator for the boundary l and under the assumption that the distribution of R1 given is in the domain of attraction of an extreme value distribution with bounded support, we are able to give an approximate confidence region.
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Dallas, Tad, Shan Huang, Charles Nunn, Andrew W. Park, and John M. Drake. "Estimating parasite host range." Proceedings of the Royal Society B: Biological Sciences 284, no. 1861 (August 30, 2017): 20171250. http://dx.doi.org/10.1098/rspb.2017.1250.

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Estimating the number of host species that a parasite can infect (i.e. host range) provides key insights into the evolution of host specialism and is a central concept in disease ecology. Host range is rarely estimated in real systems, however, because variation in species relative abundance and the detection of rare species makes it challenging to confidently estimate host range. We applied a non-parametric richness indicator to estimate host range in simulated and empirical data, allowing us to assess the influence of sampling heterogeneity and data completeness. After validating our method on simulated data, we estimated parasite host range for a sparsely sampled global parasite occurrence database (Global Mammal Parasite Database) and a repeatedly sampled set of parasites of small mammals from New Mexico (Sevilleta Long Term Ecological Research Program). Estimation accuracy varied strongly with parasite taxonomy, number of parasite occurrence records, and the shape of host species-abundance distribution (i.e. the dominance and rareness of species in the host community). Our findings suggest that between 20% and 40% of parasite host ranges are currently unknown, highlighting a major gap in our understanding of parasite specificity, host–parasite network structure, and parasite burdens.
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Su, C. C., A. Bovik, and L. Cormack. "ESTIMATING RANGE FROM LUMINANCE." Journal of Vision 12, no. 9 (August 10, 2012): 278. http://dx.doi.org/10.1167/12.9.278.

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De Haan, L., and Sidney Resnick. "Estimating the home range." Journal of Applied Probability 31, no. 03 (September 1994): 700–720. http://dx.doi.org/10.1017/s0021900200045277.

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A proposal is given for estimating the home range of an animal based on sequential sightings. We assume the given sightings are independent, identically distributed random vectors X 1,· ··, Xn whose common distribution has compact support. If are the polar coordinates of the sightings, then is a sup-measure and corresponds to the right endpoint of the distribution . The corresponding upper semi-continuous function l(θ) is the boundary of the home range. We give a consistent estimator for the boundary l and under the assumption that the distribution of R 1 given is in the domain of attraction of an extreme value distribution with bounded support, we are able to give an approximate confidence region.
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Lipman, Harvey B., and J. Rex Astles. "Estimating the linear analytic range." Clinica Chimica Acta 282, no. 1-2 (April 1999): 15–34. http://dx.doi.org/10.1016/s0009-8981(98)00219-8.

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Fox, N. I., and C. G. Collier. "Estimating medium-range catchment flood potential." Journal of Hydrology 237, no. 1-2 (October 2000): 1–16. http://dx.doi.org/10.1016/s0022-1694(00)00285-7.

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Merz, A. W. "Estimating retrosensor position from range data." Journal of Guidance, Control, and Dynamics 14, no. 5 (September 1991): 1071–72. http://dx.doi.org/10.2514/3.20755.

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Zhao, Xiaofeng, Caglar Yardim, Dongxiao Wang, and Bruce M. Howe. "Estimating Range-Dependent Evaporation Duct Height." Journal of Atmospheric and Oceanic Technology 34, no. 5 (May 2017): 1113–23. http://dx.doi.org/10.1175/jtech-d-16-0125.1.

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AbstractThe refractivity from clutter (RFC) technique has been proved to be an effective way to estimate atmospheric duct structure. An important issue for RFC is how to make the estimate more robust, especially in range-dependent ducting conditions. Traditionally, statistical inversion methods need a large number of forward propagation model runs to obtain an acceptable result. Especially when the parameter search space is multidimensional, these methods are prone to being trapped into local optimal solutions. Recently published results (Zhao and Huang) indicate that the adjoint parabolic equation (PE) method holds promise for real-time estimation of one-dimensional refractive index structure from radar sea clutter returns. This paper is aimed at extending the adjoint PE method to range-dependent evaporation duct cases, with a log-linear relationship describing duct structures. Numerical simulations are used to test the performance of this method and the results are compared with that retrieved using a genetic algorithm. Both noise-free and 3-dB additive Gaussian noise clutter simulations are considered, as well as linearly and nonlinearly varying duct height with range.
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Shaheen, Ahmed A., Aminah Robinson Fayek, and S. M. AbouRizk. "Fuzzy Numbers in Cost Range Estimating." Journal of Construction Engineering and Management 133, no. 4 (April 2007): 325–34. http://dx.doi.org/10.1061/(asce)0733-9364(2007)133:4(325).

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Fredlund, Delwyn G., Daichao Sheng, and Jidong Zhao. "Estimation of soil suction from the soil-water characteristic curve." Canadian Geotechnical Journal 48, no. 2 (February 2011): 186–98. http://dx.doi.org/10.1139/t10-060.

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Soil-water characteristic curves (SWCCs) are routinely used for the estimation of unsaturated soil property functions (e.g., permeability functions, water storage functions, shear strength functions, and thermal property functions). This paper examines the possibility of using the SWCC for the estimation of in situ soil suction. The paper focuses on the limitations of estimating soil suctions from the SWCC and also suggests a context under which soil suction estimations should be used. The potential range of estimated suction values is known to be large because of hysteresis between drying and wetting SWCCs. For this, and other reasons, the estimation of in situ suctions from the SWCC has been discouraged. However, a framework is suggested in this paper for estimating the median value for in situ soil suction along with a likely range of soil suction values (i.e., maximum and minimum values). The percentage error in the estimation of soil suction from the SWCC is shown to be lowest for sand soils and highest for clay soils.
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Dissertations / Theses on the topic "Range estimating"

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Baird, Duncan L. (Duncan Lea). "Dynamically estimating mobile range camera pose from invariant feature measurements." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=26372.

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Complex robotic tasks such as autonomous exploration and grasping demand the co-operation of sensors and actuators. In order to integrate sensor measurements and actuator control schemes we must determine the rigid body transformations that relate the native co-ordinate frames of these devices. Equivalently, we need to estimate the relative pose of sensors and actuators in the systems.
We examine the problem of determining the pose of a robot-mounted range-finding camera, and present a class of solutions motivated by the idea that mobile camera calibration is best addressed by an ongoing dynamic estimation process. We use range measurements and known robot kinematics to provide the estimate of camera pose which is maximally consistent with the available data. Our scheme uses scene features that are often present in typical workcell scenes and that are easily and reliably extracted. We develop several formulations of the principles, and present experimental results for both simulated and real data sets.
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Henkel, Hartmuth. "Range-based parameter estimation in diffusion models." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2010. http://dx.doi.org/10.18452/16213.

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Wir studieren das Verhalten des Maximums, des Minimums und des Endwerts zeithomogener eindimensionaler Diffusionen auf endlichen Zeitintervallen. Zuerst beweisen wir mit Hilfe des Malliavin-Kalküls ein Existenzresultat für die gemeinsamen Dichten. Außerdem leiten wir Entwicklungen der gemeinsamen Momente des Tripels (H,L,X) zur Zeit Delta bzgl. Delta her. Dabei steht X für die zugrundeliegende Diffusion, und H und L bezeichnen ihr fortlaufendes Maximum bzw. Minimum. Ein erster Ansatz, der vollständig auf den elementaren Abschätzungen der Doob’schen und der Cauchy-Schwarz’schen Ungleichung beruht, liefert eine Entwicklung bis zur Ordnung 2 bzgl. der Wurzel der Zeitvariablen Delta. Ein komplexerer Ansatz benutzt Partielle-Differentialgleichungstechniken, um eine Entwicklung der einseitigen Austrittswahrscheinlichkeit für gepinnte Diffusionen zu bestimmen. Da eine Entwicklung der Übergangsdichten von Diffusionen bekannt ist, erhält man eine vollständige Entwicklung der gemeinsamen Wahrscheinlichkeit von (H,X) bzgl. Delta. Die entwickelten Verteilungseigenschaften erlauben es uns, eine Theorie für Martingalschätzfunktionen, die aus wertebereich-basierten Daten konstruiert werden, in einem parameterisierten Diffusionsmodell, herzuleiten. Ein Small-Delta-Optimalitätsansatz, der die approximierten Momente benutzt, liefert eine Vereinfachung der vergleichsweise komplizierten Schätzprozedur und wir erhalten asymptotische Optimalitätsresultate für gegen 0 gehende Sampling-Frequenz. Beim Schätzen des Drift-Koeffizienten ist der wertebereich-basierte Ansatz der Methode, die auf equidistanten Beobachtungen der Diffusion beruht, nicht überlegen. Der Effizienzgewinn im Fall des Schätzens des Diffusionskoeffizienten ist hingegen enorm. Die Maxima und Minima in die Analyse miteinzubeziehen senkt die Varianz des Schätzers für den Parameter in diesem Szenario erheblich.
We study the behavior of the maximum, the minimum and the terminal value of time-homogeneous one-dimensional diffusions on finite time intervals. To begin with, we prove an existence result for the joint density by means of Malliavin calculus. Moreover, we derive expansions for the joint moments of the triplet (H,L,X) at time Delta w.r.t. Delta. Here, X stands for the underlying diffusion whereas H and L denote its running maximum and its running minimum, respectively. In a first approach that entirely relies on elementary estimates, such as Doob’s inequality and Cauchy-Schwarz’ inequality, we derive an expansion w.r.t. the square root of the time parameter Delta including powers of 2. A more sophisticated ansatz uses partial differential equation techniques to determine an expansion of the one-barrier hitting time probability for pinned diffusions. For an expansion of the transition density of diffusions is known, one obtains an overall expansion of the joint probability of (H,X) w.r.t. Delta. The developed distributional properties enable us to establish a theory for martingale estimating functions constructed from range-based data in a parameterized diffusion model. A small-Delta-optimality approach, that uses the approximated moments, yields a simplification of the relatively complicated estimating procedure and we obtain asymptotic optimality results when the sampling frequency Delta tends to 0. When it comes to estimating the drift coefficient the range-based method is not superior to the method relying on equidistant observations of the underlying diffusion alone. However, there is an enormous gain in efficiency at the estimation for the diffusion coefficient. Incorporating the maximum and the minimum into the analysis significantly lowers the asymptotic variance of the estimators for the parameter in this scenario.
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Karanci, Huseyin. "A Comparative Study Of Regression Analysis, Neural Networks And Case." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612514/index.pdf.

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Construction cost estimating is essential for all of the stakeholders of a construction project from the beginning stage to the end. At early stages of a construction project, the design information and scope definition are very limited, hence
during conceptual (early) cost estimation, achieving high accuracy is very difficult. The level of uncertainty included in the cost estimations should be emphasized for making correct decisions throughout the dynamic stages of construction project management process, especially during early stages. By using range estimating, the level of uncertainties can be identified in cost estimations. This study represents integrations of parametric and probabilistic cost estimation techniques in a comparative base. Combinations of regression analysis, neural networks, case &ndash
based reasoning and bootstrap method are proposed for the conceptual (early) range cost estimations of mass housing projects. Practical methods for early range cost estimation of mass housing projects are provided for construction project management professionals. The methods are applied using bid offers of a Turkish contractor given for 41 mass housing projects. The owner of all projects is Housing Development Administration of Turkey (TOKI). The mass housing projects of TOKI are generally a mix of apartment blocks, social, health and educational facilities, and some projects may also have mosques. Results of the three different approaches are compared for predictive accuracy and predictive variability, and suggestions for early range cost estimation of construction projects are made.
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Vivero, Oskar. "Estimation of long-range dependence." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/estimation-of-longrange-dependence(65565876-4ec6-44b3-8181-51b13dca309c).html.

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A set of observations from a random process which exhibit correlations that decay slower than an exponential rate is regarded as long-range dependent. This phenomenon has stimulated great interest in the scientific community as it appears in a wide range of areas of knowledge. For example, this property has been observed in data pertaining to electronics, econometrics, hydrology and biomedical signals.There exist several estimation methods for finding model parameters that help explain the set of observations exhibiting long-range dependence. Among these methods, maximum likelihood is attractive, given its desirable statistical properties such as asymptotic consistency and efficiency. However, its computational complexity makes the implementation of maximum likelihood prohibitive.This thesis presents a group of computationally efficient estimators based on the maximum likelihood framework. The thesis consists of two main parts. The first part is devoted to developing a computationally efficient alternative to the maximum likelihood estimate. This alternative is based on the circulant embedding concept and it is shown to maintain the desirable statistical properties of maximum likelihood.Interesting results are obtained by analysing the circulant embedding estimate. In particular, this thesis shows that the maximum likelihood based methods are ill-conditioned; the estimators' performance will deteriorate significantly when the set of observations is corrupted by errors. The second part of this thesis focuses on developing computationally efficient estimators with improved performance under the presence of errors in the observations.
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Alleyne, Jason C. "Position estimation from range only measurements." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA386399.

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Thesis (M.S. in Mechanical Engineering) Naval Postgraduate School, September 2000.
Thesis advisor(s): Healey, Anthony J. "September 2000." Includes bibliographical references (p. 89). Also available online.
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Whaley, Dewey Lonzo. "The Interquartile Range: Theory and Estimation." Digital Commons @ East Tennessee State University, 2005. https://dc.etsu.edu/etd/1030.

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The interquartile range (IQR) is used to describe the spread of a distribution. In an introductory statistics course, the IQR might be introduced as simply the “range within which the middle half of the data points lie.” In other words, it is the distance between the two quartiles, IQR = Q3 - Q1. We will compute the population IQR, the expected value, and the variance of the sample IQR for various continuous distributions. In addition, a bootstrap confidence interval for the population IQR will be evaluated.
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Gal, Avner. "Passive range estimation using over sea multipath." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23344.

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This thesis suggests an unconventional, unique method for passive range and height estimation of a cruising missile, or other microwave transmitter. Based on multipath propagation, the method uses 5 receiving antennas in a ladder configuration. Ratios of received signal powers are compared with values from lookup tables to determine the correct location of the transmitter. Computer simulation results are presented, to verify the suggested method. (rh)
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Nygaard, John Charles. "Estimation of range error in bistatic sonar." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/30970.

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This thesis examines the range error propagation and uncertainties associated with bistatic sonar operations. An equation for determining range to the target from the receiver is explored for feasibility of practical applications. This particular equation does not require the separation distance between the source and receiver however, it does require an assumption of the mean sound speed over the two paths of the signal even though it could change drastically over a few miles. This thesis explores the contribution of eccentricity on the bistatic ellipse and the associated error. Examples demonstrate these effects by comparing cases of unequal mean sound speeds over the different paths at different values of eccentricity.
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Chuang, Ping Derg. "Range estimation by cepstral techniques in image processing." Thesis, Imperial College London, 1986. http://hdl.handle.net/10044/1/37973.

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Sand, Peter (Peter M. ). 1977. "Long-range video motion estimation using point trajectories." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38319.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (leaves 97-104).
This thesis describes a new approach to video motion estimation, in which motion is represented using a set of particles. Each particle is an image point sample with a long-duration trajectory and other properties. To optimize these particles, we measure point-based matching along the particle trajectories and distortion between the particles. The resulting motion representation is useful for a variety of applications and differs from optical flow, feature tracking, and parametric or layer-based models. We demonstrate the algorithm on challenging real-world videos that include complex scene geometry, multiple types of occlusion, regions with low texture, and non-rigid deformation.
by Peter Sand.
Ph.D.
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Books on the topic "Range estimating"

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N, Forrest R. Estimating search effectiveness with limited information. Monterey, Calif: Naval Postgraduate School, 1993.

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Nev.) Nevada Fiscal Forum (2000 Las Vegas. General fund long-range forecast: Presented at the Nevada Fiscal Forum, Las Vegas, Nevada, May 2000. Las Vegas, Nevada]: State of Nevada, Department of Administration, 2000.

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Davenport, J. C. Estimating Los Angeles degradation value using the Schmidt rebound hammer along the Front Range, Colorado. [Denver, CO]: U.S. Dept. of the Interior, U.S. Geological Survey, 1998.

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Projections, Convention on Long-range Transboundary Air Pollution Task Force on Emission Inventories and. Guidelines for estimating and reporting emission data under the Convention on Long-range Transboundary Air Pollution. New York: United Nations, 2003.

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Alleyne, Jason C. Position estimation from range only measurements. Monterey, Calif: Naval Postgraduate School, 2000.

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Gal, Avner. Passive range estimation using over sea multipath. Monterey, California: Naval Postgraduate School, 1988.

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Skifstad, Kurt D. High-speed range estimation based on intensity gradient analysis. New York: Springer-Verlag, 1991.

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Skifstad, Kurt D. High-Speed Range Estimation Based on Intensity Gradient Analysis. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3112-7.

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Skifstad, Kurt D. High-speed range estimation based on intensity gradient analysis. New York: Springer-Verlag, 1991.

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High-speed range estimation based on intensity gradient analysis. New York: Springer-Verlag, 1991.

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Book chapters on the topic "Range estimating"

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Dominguez-Jimenez, J. A., and Javier Campillo. "Object-Oriented Mathematical Modeling for Estimating Electric Vehicle’s Range Using Modelica." In Communications in Computer and Information Science, 444–58. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98998-3_34.

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Buccafurri, Francesco, Filippo Furfaro, and Domenico Saccà. "Estimating Range Queries Using Aggregate Data with Integrity Constraints: A Probabilistic Approach." In Database Theory — ICDT 2001, 390–404. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44503-x_25.

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Gu, Wenhao, Cong Gao, Robert Grupp, Javad Fotouhi, and Mathias Unberath. "Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients." In Machine Learning in Medical Imaging, 281–91. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59861-7_29.

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Domańska, Joanna, Adam Domański, and Tadeusz Czachórski. "Estimating the Intensity of Long-Range Dependence in Real and Synthetic Traffic Traces." In Computer Networks, 11–22. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19419-6_2.

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Mandolini, Marco, Federico Campi, Claudio Favi, Paolo Cicconi, Michele Germani, and Roberto Raffaeli. "Parametric Cost Modelling for Investment Casting." In Lecture Notes in Mechanical Engineering, 386–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70566-4_61.

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AbstractThis paper presents a parametric cost model for estimating the raw material cost of components realized employing the investment casting process. The model is built using sensitivity analysis and regression methods on data generated by an analytic cost model previously developed and validated by the same authors. This is the first attempt of developing a parametric cost model for investment casting based on activity-based costing. The proposed cost model accounts component volume, material density and material price. The error in estimating the raw material cost for components whose volume is within the common range of investment casting is around 11%.
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Sen, Arijit, and Amin Al-Habaibeh. "A Novel Approach for U-Value Estimation of Buildings’ Multi-layer Walls Using Infrared Thermography and Artificial Intelligence." In Springer Proceedings in Energy, 35–43. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_5.

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AbstractEstimating the U-value of walls of buildings is a key process to evaluate the overall thermal performance. Low U-value in buildings is desired in order to keep heat within the envelop and consume less energy in heating. Addressing the limitations in the currently used U-value estimation techniques, this paper proposes a novel approach for estimating the U-value of the envelop of buildings using infrared thermography and Artificial Neural Network (ANN) with the application of a point heat source. The novel system is calibrated by training the ANN in a lab environment using a wide range of samples with multi-layers to be able to estimate the in situ U-value of walls in real buildings during field work with relatively high accuracy.
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Tsai, Ping Chen, and Shou Huang Dai. "Estimating the Proportion of Informed Traders in BTC-USD Market Using Spread and Range." In Advanced Studies of Financial Technologies and Cryptocurrency Markets, 197–210. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4498-9_11.

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Bianco, Giovanni Lo, Xavier Lorca, and Charlotte Truchet. "Estimating the Number of Solutions of Cardinality Constraints Through $$\texttt {range}$$ and $$\texttt {roots}$$ Decompositions." In Lecture Notes in Computer Science, 317–32. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30048-7_19.

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Hlawatsch, Franz. "Range-Doppler Estimation." In The Kluwer International Series in Engineering and Computer Science, 173–94. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2815-6_8.

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Spies, Hagen, Horst Haußecker, Bernd Jähne, and John L. Barron. "Differential Range Flow Estimation." In Informatik aktuell, 309–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60243-6_36.

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Conference papers on the topic "Range estimating"

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Gueler, Richard, Craig Olson, and Andrew Sparks. "Estimating uncertainty in limiting resolution of full motion video." In Long-Range Imaging III, edited by Eric J. Kelmelis. SPIE, 2018. http://dx.doi.org/10.1117/12.2304052.

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Hådem, I. "Estimating approximate values before bundle adjustment in close-range photogrammetry: a review." In Close-Range Photogrammetry Meets Machine Vision. SPIE, 1990. http://dx.doi.org/10.1117/12.2294373.

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S. Martins, Saulo, Luis A. Peche, and Jandyr M. Travassos. "Estimating The Energy Range Along A Surficial Waveguide." In IV Simpósio Brasileiro de Geofísica. European Association of Geoscientists & Engineers, 2010. http://dx.doi.org/10.3997/2214-4609-pdb.197.sbgf_2149.

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S. Martins, Saulo, Luis A. Peche, and Jandyr M. Travassos. "Estimating the energy range along a surficial waveguide." In Simpósio Brasileiro de Geofísica. Sociedade Brasileira de Geofísica, 2010. http://dx.doi.org/10.22564/4simbgf2010.128.

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Borzino, Angelo M. C. R., Jose A. Apolinario, and Marcello L. R. de Campos. "Estimating direction of arrival of long range gunshot signals." In 2014 International Telecommunications Symposium (ITS). IEEE, 2014. http://dx.doi.org/10.1109/its.2014.6947995.

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Dogandzic, A., and A. Nehorai. "Estimating range, velocity, and direction with a radar array." In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258). IEEE, 1999. http://dx.doi.org/10.1109/icassp.1999.761319.

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Yang, Chun, and Erik Blasch. "Estimating target range-Doppler image slope for maneuver indication." In SPIE Defense and Security Symposium, edited by Ivan Kadar. SPIE, 2008. http://dx.doi.org/10.1117/12.776697.

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Hutchison, Matthew. "A Method for Estimating Range Requirements of Tactical Reconnaissance UAVs." In 1st UAV Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-3438.

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Rosales-Morales, Sergio A., and Luz A. Torres-Méndez. "A Statistical Analysis of Visual Cues for Estimating Dense Range Maps." In 2008 Seventh Mexican International Conference on Artificial Intelligence (MICAI). IEEE, 2008. http://dx.doi.org/10.1109/micai.2008.57.

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Landman, C., and A. J. Rix. "Using cloud cover forecasts for estimating a solar powered vehicles' range." In 2020 International SAUPEC/RobMech/PRASA Conference. IEEE, 2020. http://dx.doi.org/10.1109/saupec/robmech/prasa48453.2020.9041040.

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Reports on the topic "Range estimating"

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Harrod, Richy J., William L. Gaines, William E. Hartl, and Ann Camp. Estimating historical snag density in dry forests east of the Cascade Range. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1998. http://dx.doi.org/10.2737/pnw-gtr-428.

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Dime, Roselle, Juzhong Zhuang, and Edimon Ginting. Estimating Fiscal Multipliers in Selected Asian Economies. Asian Development Bank, August 2021. http://dx.doi.org/10.22617/wps210309-2.

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The surge of the coronavirus disease (COVID-19) pandemic has driven countries worldwide to launch substantial stimulus packages to support economic recovery. This paper estimates effects of fiscal measures on output using data from 2000 to 2019 for a panel of nine developing Asian economies and a vector autoregression model. Results show that (i) the 4-quarter and 8-quarter cumulative fiscal multipliers for general government spending range between 0.73 and 0.88 in baselines, in line with recent estimates for developed countries but larger than those for developing countries; (ii) government spending is more effective than tax cuts in boosting the economy; and (iii) an accommodative monetary policy regime can make fiscal measures more effective.
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Dickens, Brian, and Eric Byrd. Programs to Estimate UV Dosage and Damage. National Institute of Standards and Technology, September 1999. http://dx.doi.org/10.6028/nist.ir.7500.

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The system of programs described in this paper is concerned with estimating the damage ensuing from exposure of specimens in dry and humid atmospheres to UV and visible radiation covering the solar range. Damage is monitored quantitatively by changes in IR spectra. The dose is estimated from UV spectra of the lamps and the interference filters (used to isolate a particular wavelength range). The dosage is estimated from the dose and the UV absorption of the specimens themselves. These programs allow rapid estimation of dosage and damage from regions of data, and manipulation and processing of the massive amounts of data required to carry out such comprehensive tests in a complete yet user-friendly manner.
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Pietra, S. D., V. D. Pietra, J. Gillett, J. Lafferty, and H. Printz. Inference and Estimation of a Long-Range Trigram Model. Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada286057.

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Jackson, Douglas E., and Malcolm J. Ree. Tool for Studying the Effects of Range Restriction in Correlation Coefficient Estimation. Fort Belvoir, VA: Defense Technical Information Center, July 1990. http://dx.doi.org/10.21236/ada224035.

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Brandt, Michael, and Francis Diebold. A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations. Cambridge, MA: National Bureau of Economic Research, May 2003. http://dx.doi.org/10.3386/w9664.

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Erwin, R. S., and Dennis S. Bernstein. Spacecraft Trajectory Estimation Using a Sampled-Data Extended Kalman Filter with Range-Only Measurements. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada439012.

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Alizadeh, Sassan, Michael Brandt, and Francis Diebold. High- and Low-Frequency Exchange Rate Volatility Dynamics: Range-Based Estimation of Stochastic Volatility Models. Cambridge, MA: National Bureau of Economic Research, March 2001. http://dx.doi.org/10.3386/w8162.

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Downing, W. Logan, Howell Li, William T. Morgan, Cassandra McKee, and Darcy M. Bullock. Using Probe Data Analytics for Assessing Freeway Speed Reductions during Rain Events. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317350.

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Rain impacts roadways such as wet pavement, standing water, decreased visibility, and wind gusts and can lead to hazardous driving conditions. This study investigates the use of high fidelity Doppler data at 1 km spatial and 2-minute temporal resolution in combination with commercial probe speed data on freeways. Segment-based space-mean speeds were used and drops in speeds during rainfall events of 5.5 mm/hour or greater over a one-month period on a section of four to six-lane interstate were assessed. Speed reductions were evaluated as a time series over a 1-hour window with the rain data. Three interpolation methods for estimating rainfall rates were tested and seven metrics were developed for the analysis. The study found sharp drops in speed of more than 40 mph occurred at estimated rainfall rates of 30 mm/hour or greater, but the drops did not become more severe beyond this threshold. The average time of first detected rainfall to impacting speeds was 17 minutes. The bilinear method detected the greatest number of events during the 1-month period, with the most conservative rate of predicted rainfall. The range of rainfall intensities were estimated between 7.5 to 106 mm/hour for the 39 events. This range was much greater than the heavy rainfall categorization at 16 mm/hour in previous studies reported in the literature. The bilinear interpolation method for Doppler data is recommended because it detected the greatest number of events and had the longest rain duration and lowest estimated maximum rainfall out of three methods tested, suggesting the method balanced awareness of the weather conditions around the roadway with isolated, localized rain intensities.
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Manninen, Terhikki, and Pauline Stenberg. Influence of forest floor vegetation on the total forest reflectance and its implications for LAI estimation using vegetation indices. Finnish Meteorological Institute, 2021. http://dx.doi.org/10.35614/isbn.9789523361379.

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Recently a simple analytic canopy bidirectional reflectance factor (BRF) model based on the spectral invariants theory was presented. The model takes into account that the recollision probability in the forest canopy is different for the first scattering than the later ones. Here this model is extended to include the forest floor contribution to the total forest BRF. The effect of the understory vegetation on the total forest BRF as well as on the simple ratio (SR) and the normalized difference (NDVI) vegetation indices is demonstrated for typical cases of boreal forest. The relative contribution of the forest floor to the total BRF was up to 69 % in the red wavelength range and up to 54 % in the NIR wavelength range. Values of SR and NDVI for the forest and the canopy differed within 10 % and 30 % in red and within 1 % and 10 % in the NIR wavelength range. The relative variation of the BRF with the azimuth and view zenith angles was not very sensitive to the forest floor vegetation. Hence, linear correlation of the modelled total BRF and the Ross-thick kernel was strong for dense forests (R2 > 0.9). The agreement between modelled BRF and satellite-based reflectance values was good when measured LAI, clumping index and leaf single scattering albedo values for a boreal forest were used as input to the model.
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