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Journal articles on the topic 'Spatio-temporal random fields'

Author: Grafiati

Published: 13 April 2024

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1

Descombes, X., F. Kruggel, and D. Y. Von Cramon. "Spatio-temporal fMRI analysis using Markov random fields." IEEE Transactions on Medical Imaging 17, no. 6 (1998): 1028–39. http://dx.doi.org/10.1109/42.746636.

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2

De Iaco, S., and D. Posa. "Predicting spatio-temporal random fields: Some computational aspects." Computers & Geosciences 41 (April 2012): 12–24. http://dx.doi.org/10.1016/j.cageo.2011.11.014.

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3

Piatkowski, Nico, Sangkyun Lee, and Katharina Morik. "Spatio-temporal random fields: compressible representation and distributed estimation." Machine Learning 93, no. 1 (2013): 115–39. http://dx.doi.org/10.1007/s10994-013-5399-7.

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Ip, Ryan H. L., and W. K. Li. "Matérn cross-covariance functions for bivariate spatio-temporal random fields." Spatial Statistics 17 (August 2016): 22–37. http://dx.doi.org/10.1016/j.spasta.2016.04.004.

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5

Salvaña, Mary Lai O., and Marc G. Genton. "Nonstationary cross-covariance functions for multivariate spatio-temporal random fields." Spatial Statistics 37 (June 2020): 100411. http://dx.doi.org/10.1016/j.spasta.2020.100411.

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6

Fontanella, L., L. Ippoliti, R. J. Martin, and S. Trivisonno. "Interpolation of spatial and spatio-temporal Gaussian fields using Gaussian Markov random fields." Advances in Data Analysis and Classification 2, no. 1 (2008): 63–79. http://dx.doi.org/10.1007/s11634-008-0019-2.

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7

Das, Sonjoy, Roger Ghanem, and Steven Finette. "Polynomial chaos representation of spatio-temporal random fields from experimental measurements." Journal of Computational Physics 228, no. 23 (2009): 8726–51. http://dx.doi.org/10.1016/j.jcp.2009.08.025.

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8

Western, Luke M., Zhe Sha, Matthew Rigby, et al. "Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields." Geoscientific Model Development 13, no. 4 (2020): 2095–107. http://dx.doi.org/10.5194/gmd-13-2095-2020.

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Abstract. We present a method to infer spatially and spatio-temporally correlated emissions of greenhouse gases from atmospheric measurements and a chemical transport model. The method allows fast computation of spatial emissions using a hierarchical Bayesian framework as an alternative to Markov chain Monte Carlo algorithms. The spatial emissions follow a Gaussian process with a Matérn correlation structure which can be represented by a Gaussian Markov random field through a stochastic partial differential equation approach. The inference is based on an integrated nested Laplacian approximati

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Jadaliha, Mahdi, Jinho Jeong, Yunfei Xu, Jongeun Choi, and Junghoon Kim. "Fully Bayesian Prediction Algorithms for Mobile Robotic Sensors under Uncertain Localization Using Gaussian Markov Random Fields." Sensors 18, no. 9 (2018): 2866. http://dx.doi.org/10.3390/s18092866.

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In this paper, we present algorithms for predicting a spatio-temporal random field measured by mobile robotic sensors under uncertainties in localization and measurements. The spatio-temporal field of interest is modeled by a sum of a time-varying mean function and a Gaussian Markov random field (GMRF) with unknown hyperparameters. We first derive the exact Bayesian solution to the problem of computing the predictive inference of the random field, taking into account observations, uncertain hyperparameters, measurement noise, and uncertain localization in a fully Bayesian point of view. We sho

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Ghosh, Debraj, and Anup Suryawanshi. "Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition." Communications in Computational Physics 16, no. 1 (2014): 75–95. http://dx.doi.org/10.4208/cicp.201112.191113a.

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AbstractA new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known

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11

Frederiksen, Richard D., Werner J. A. Dahm, and David R. Dowling. "Experimental assessment of fractal scale-similarity in turbulent flows. Part 1. One-dimensional intersections." Journal of Fluid Mechanics 327 (November 25, 1996): 35–72. http://dx.doi.org/10.1017/s0022112096008452.

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Results are presented from an assessment of the applicability of fractal scale-similarity in the spatio–temporal structure of Sc [Gt ] 1 conserved scalar fields ζ(x, t) and scalar energy dissipation rate fields ∇(x, t) in turbulent flows. Over 2 million spatial and temporal intersections were analysed from fully resolved three-dimensional (256) spatial measurements as well as fully resolved four-dimensional spatio–temporal measurements containing up to 3 million points. Statistical criteria were used to assess both deterministic and stochastic fractal scale-similarity and to differentiate betw

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Roscher, Ribana, Bernd Uebbing, and Jürgen Kusche. "STAR: Spatio-temporal altimeter waveform retracking using sparse representation and conditional random fields." Remote Sensing of Environment 201 (November 2017): 148–64. http://dx.doi.org/10.1016/j.rse.2017.07.024.

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13

Bhole, Chetan, and Christopher Pal. "Fully automatic person segmentation in unconstrained video using spatio-temporal conditional random fields." Image and Vision Computing 51 (July 2016): 58–68. http://dx.doi.org/10.1016/j.imavis.2016.04.007.

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14

Khatoonabadi, S. H., and I. V. Bajic. "Video Object Tracking in the Compressed Domain Using Spatio-Temporal Markov Random Fields." IEEE Transactions on Image Processing 22, no. 1 (2013): 300–313. http://dx.doi.org/10.1109/tip.2012.2214049.

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15

Cecconi, Vittorio, Vivek Kumar, Alessia Pasquazi, Juan Sebastian Totero Gongora, and Marco Peccianti. "Nonlinear field-control of terahertz waves in random media for spatiotemporal focusing." Open Research Europe 2 (August 1, 2022): 32. http://dx.doi.org/10.12688/openreseurope.14508.2.

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Controlling the transmission of broadband optical pulses in scattering media is a critical open challenge in photonics. To date, wavefront shaping techniques at optical frequencies have been successfully applied to control the spatial properties of multiple-scattered light. However, a fundamental restriction in achieving an equivalent degree of control over the temporal properties of a broadband pulse is the limited availability of experimental techniques to detect the coherent properties (i.e., the spectral amplitude and absolute phase) of the transmitted field. Terahertz experimental framewo

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Cecconi, Vittorio, Vivek Kumar, Alessia Pasquazi, Juan Sebastian Totero Gongora, and Marco Peccianti. "Nonlinear field-control of terahertz waves in random media for spatiotemporal focusing." Open Research Europe 2 (March 8, 2022): 32. http://dx.doi.org/10.12688/openreseurope.14508.1.

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Controlling the transmission of broadband optical pulses in scattering media is a critical open challenge in photonics. To date, wavefront shaping techniques at optical frequencies have been successfully applied to control the spatial properties of multiple-scattered light. However, a fundamental restriction in achieving an equivalent degree of control over the temporal properties of a broadband pulse is the limited availability of experimental techniques to detect the coherent properties (i.e., the spectral amplitude and absolute phase) of the transmitted field. Terahertz experimental framewo

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Cecconi, Vittorio, Vivek Kumar, Alessia Pasquazi, Juan Sebastian Totero Gongora, and Marco Peccianti. "Nonlinear field-control of terahertz waves in random media for spatiotemporal focusing." Open Research Europe 2 (February 13, 2023): 32. http://dx.doi.org/10.12688/openreseurope.14508.3.

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Controlling the transmission of broadband optical pulses in scattering media is a critical open challenge in photonics. To date, wavefront shaping techniques at optical frequencies have been successfully applied to control the spatial properties of multiple-scattered light. However, a fundamental restriction in achieving an equivalent degree of control over the temporal properties of a broadband pulse is the limited availability of experimental techniques to detect the coherent properties (i.e., the spectral amplitude and absolute phase) of the transmitted field. Terahertz experimental framewo

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18

Ip, Ryan H. L., and W. K. Li. "A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields." Statistics & Probability Letters 130 (November 2017): 115–19. http://dx.doi.org/10.1016/j.spl.2017.07.019.

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19

Prevost, Paoline, Kristel Chanard, Luce Fleitout, et al. "Data-adaptive spatio-temporal filtering of GRACE data." Geophysical Journal International 219, no. 3 (2019): 2034–55. http://dx.doi.org/10.1093/gji/ggz409.

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SUMMARY Measurements of the spatio-temporal variations of Earth’s gravity field from the Gravity Recovery and Climate Experiment (GRACE) mission have led to new insights into large spatial mass redistribution at secular, seasonal and subseasonal timescales. GRACE solutions from various processing centres, while adopting different processing strategies, result in rather coherent estimates. However, these solutions also exhibit random as well as systematic errors, with specific spatial patterns in the latter. In order to dampen the noise and enhance the geophysical signals in the GRACE data, we

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Yuan, Wenjing, Lin Yang, Qing Yang, Yehua Sheng, and Ziyang Wang. "Extracting Spatio-Temporal Information from Chinese Archaeological Site Text." ISPRS International Journal of Geo-Information 11, no. 3 (2022): 175. http://dx.doi.org/10.3390/ijgi11030175.

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Archaeological site text is the main carrier of archaeological data at present, which contains rich information. How to efficiently extract useful knowledge from the massive unstructured archaeological site texts is of great significance for the mining and reuse of archaeological information. According to the site information (such as name, location, cultural type, dynasty, etc.) recorded in the Chinese archaeological site text, this paper combines deep learning and natural language processing techniques to study the information extraction method for automatically obtaining the spatio-temporal

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21

Bulthuis, Kevin, and Eric Larour. "Implementation of a Gaussian Markov random field sampler for forward uncertainty quantification in the Ice-sheet and Sea-level System Model v4.19." Geoscientific Model Development 15, no. 3 (2022): 1195–217. http://dx.doi.org/10.5194/gmd-15-1195-2022.

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Abstract. Assessing the impact of uncertainties in ice-sheet models is a major and challenging issue that needs to be faced by the ice-sheet community to provide more robust and reliable model-based projections of ice-sheet mass balance. In recent years, uncertainty quantification (UQ) has been increasingly used to characterize and explore uncertainty in ice-sheet models and improve the robustness of their projections. A typical UQ analysis first involves the (probabilistic) characterization of the sources of uncertainty, followed by the propagation and sensitivity analysis of these sources of

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22

Song, Tao, Wei Wei, Fan Meng, Jiarong Wang, Runsheng Han, and Danya Xu. "Inversion of Ocean Subsurface Temperature and Salinity Fields Based on Spatio-Temporal Correlation." Remote Sensing 14, no. 11 (2022): 2587. http://dx.doi.org/10.3390/rs14112587.

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Ocean observation is essential for studying ocean dynamics, climate change, and carbon cycles. Due to the difficulty and high cost of in situ observations, existing ocean observations are inadequate, and satellite observations are mostly surface observations. Previous work has not adequately considered the spatio-temporal correlation within the ocean itself. This paper proposes a new method—convolutional long short-term memory network (ConvLSTM)—for the inversion of the ocean subsurface temperature and salinity fields with the sea surface satellite observations (sea surface temperature, sea su

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23

Shi, Zhichao, and Xiaoguang Zhou. "Spatio-Temporal Dynamic Fields Estimating and Modeling of Missing Points in Data Sets Using a Flexible State-Space Model." Applied Sciences 11, no. 19 (2021): 9050. http://dx.doi.org/10.3390/app11199050.

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Modelling and estimating spatio-temporal dynamic field are common challenges in much applied research. Most existing spatio-temporal interpolation methods require massive prior calculations and consistent observational data, resulting in low interpolation efficiency. This paper presents a flexible state-space model for iteratively fitting time-series from random missing points in data sets, namely Flexible Universal Kriging state-space model(FUKSS). In this work, a recursive method similar to Kalman filter is used to estimate the time-series, avoiding the problem of increasing data caused by K

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24

Zhou, Shijie, Robert A. Campbell, and Simon D. Hoyle. "Catch per unit effort standardization using spatio-temporal models for Australia’s Eastern Tuna and Billfish Fishery." ICES Journal of Marine Science 76, no. 6 (2019): 1489–504. http://dx.doi.org/10.1093/icesjms/fsz034.

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Abstract The majority of catch per unit effort (cpue) standardizations use generalized linear models (GLMs) or generalized additive models (GAMs). We develop geostatistical models that model catch locations as continuous Gaussian random fields (GRFs) and apply them to standardizing cpue in Australia’s Eastern Tuna and Billfish Fishery (ETBF). The results are compared with the traditional GLMs currently used in ETBF assessments as well as GAMs. Specifically, we compare seven models in three groups: two GLMs, two GAMs, and three GRF models. Within each group, one model treats spatial and tempora

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25

Roberts, O. W., X. Li, and L. Jeska. "Validation of the <i>k</i>-filtering technique for a signal composed of random-phase plane waves and non-random coherent structures." Geoscientific Instrumentation, Methods and Data Systems 3, no. 2 (2014): 247–54. http://dx.doi.org/10.5194/gi-3-247-2014.

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Abstract. Recent observations of astrophysical magnetic fields have shown the presence of fluctuations being wave-like (propagating in the plasma frame) and those described as being structure-like (advected by the plasma bulk velocity). Typically with single-spacecraft missions it is impossible to differentiate between these two fluctuations, due to the inherent spatio-temporal ambiguity associated with a single point measurement. However missions such as Cluster which contain multiple spacecraft have allowed for temporal and spatial changes to be resolved, using techniques such as k filtering

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26

Sakuma, Asahi, and Hiroya Yamano. "Satellite Constellation Reveals Crop Growth Patterns and Improves Mapping Accuracy of Cropping Practices for Subtropical Small-Scale Fields in Japan." Remote Sensing 12, no. 15 (2020): 2419. http://dx.doi.org/10.3390/rs12152419.

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Mapping of agricultural crop types and practices is important for setting up agricultural production plans and environmental conservation measures. Sugarcane is a major tropical and subtropical crop; in general, it is grown in small fields with large spatio-temporal variations due to various crop management practices, and satellite observations of sugarcane cultivation areas are often obscured by clouds. Surface information with high spatio-temporal resolution obtained through the use of emerging satellite constellation technology can be used to track crop growth patterns with high resolution.

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27

Ahmad, Ola, and Christophe Collet. "Scale-space spatio-temporal random fields: Application to the detection of growing microbial patterns from surface roughness." Pattern Recognition 58 (October 2016): 27–38. http://dx.doi.org/10.1016/j.patcog.2016.03.034.

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28

Voloshko, V. A., and Yu S. Kharin. "Discrete-valued time series based on the exponential family with the multidimensional parameter and their probabilistic and statistical analysis." Proceedings of the National Academy of Sciences of Belarus. Physics and Mathematics Series 58, no. 3 (2022): 280–91. http://dx.doi.org/10.29235/1561-2430-2022-58-3-280-291.

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We propose herein a new parsimonious Markov model for a discrete-valued time series with conditional probability distributions of observations lying in the exponential family with the multidimensional parameter. A family of explicit consistent asymptotically normal statistical estimators is constructed for the parameters of the proposed model for increasing length of observed time series, and asymptotically effective estimator is found within this constructed family. The obtained results can be used for robust statistical analysis of discrete-valued time series,and for statistical analysis of

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29

Roberts, O. W., X. Li, and L. Jeska. "Validation of the <i>k</i>-filtering technique for a signal composed of random phase plane waves and non-random coherent structures." Geoscientific Instrumentation, Methods and Data Systems Discussions 4, no. 2 (2014): 435–54. http://dx.doi.org/10.5194/gid-4-435-2014.

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Abstract. Recent observations of astrophysical magnetic fields have shown the presence of fluctuations being wave-like (propagating in the plasma frame) and those described as being structure-like (advected by the plasma bulk velocity). Typically with single spacecraft missions it is impossible to differentiate between these two fluctuations, due to the inherent spatio-temporal ambiguity associated with a single point measurement. However missions such as Cluster which contain multiple spacecraft have allowed temporal and spatial changes to be resolved, with techniques such as the k-filtering

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30

Hengl, Tomislav, Madlene Nussbaum, Marvin N. Wright, Gerard B. M. Heuvelink, and Benedikt Gräler. "Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables." PeerJ 6 (August 29, 2018): e5518. http://dx.doi.org/10.7717/peerj.5518.

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Random forest and similar Machine Learning techniques are already used to generate spatial predictions, but spatial location of points (geography) is often ignored in the modeling process. Spatial auto-correlation, especially if still existent in the cross-validation residuals, indicates that the predictions are maybe biased, and this is suboptimal. This paper presents a random forest for spatial predictions framework (RFsp) where buffer distances from observation points are used as explanatory variables, thus incorporating geographical proximity effects into the prediction process. The RFsp f

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Stuhlmeier, R., and M. Stiassnie. "Evolution of statistically inhomogeneous degenerate water wave quartets." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 376, no. 2111 (2017): 20170101. http://dx.doi.org/10.1098/rsta.2017.0101.

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A discretized equation for the evolution of random surface wave fields on deep water is derived from Zakharov's equation, allowing for a general treatment of the stability and long-time behaviour of broad-banded sea states. It is investigated for the simple case of degenerate four-wave interaction, and the instability of statistically homogeneous states to small inhomogeneous disturbances is demonstrated. Furthermore, the long-time evolution is studied for several cases and shown to lead to a complex spatio-temporal energy distribution. The possible impact of this evolution on the statistics o

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Maniyar, Chintan B., Megha Rudresh, Ileana A. Callejas, et al. "Spatio-Temporal Dynamics of Total Suspended Sediments in the Belize Coastal Lagoon." Remote Sensing 15, no. 23 (2023): 5625. http://dx.doi.org/10.3390/rs15235625.

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Increased tourism in Belize over the last decade and the growth of the local population have led to coastal development and infrastructure expansion. Land use alteration and anthropogenic activity may change the sediment and nutrient loads in coastal systems, which can negatively affect ecosystems via mechanisms such as reducing photosynthetically active radiation fields, smothering sessile habitats, and stimulating eutrophication events. Accurate monitoring and prediction of water quality parameters such as Total Suspended Sediments (TSS), are essential in order to understand the influence of

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33

MELGANI, FARID. "CLASSIFICATION OF MULTITEMPORAL REMOTE-SENSING IMAGES BY A FUZZY FUSION OF SPECTRAL AND SPATIO-TEMPORAL CONTEXTUAL INFORMATION." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 02 (2004): 143–56. http://dx.doi.org/10.1142/s0218001404003083.

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A fuzzy-logic approach to the classification of multitemporal, multisensor remote-sensing images is proposed. The approach is based on a fuzzy fusion of three basic sources of information: spectral, spatial and temporal contextual information sources. It aims at improving the accuracy over that of single-time noncontextual classification. Single-time class posterior probabilities, which are used to represent spectral information, are estimated by Multilayer Perceptron neural networks trained for each single-time image, thus making the approach applicable to multisensor data. Both the spatial a

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34

Luo, Yilan, Deniz Sezer, David Wood, Mingkuan Wu, and Hamid Zareipour. "Estimation of the Daily Variability of Aggregate Wind Power Generation in Alberta, Canada." Energies 12, no. 10 (2019): 1998. http://dx.doi.org/10.3390/en12101998.

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This paper describes a hierarchy of increasingly complex statistical models for wind power generation in Alberta applied to wind power production data that are publicly available. The models are based on combining spatial and temporal correlations. We apply the method of Gaussian random fields to analyze the wind power time series of the 19 existing wind farms in Alberta. Following the work of Gneiting et al., three space-time models are used: Stationary, Separability, and Full Symmetry. We build several spatio-temporal covariance function estimates with increasing complexity: separable, non-s

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Verburg, Samuel A., and Efren Fernandez-Grande. "Sensor placement for sound field reconstruction in enclosures." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 1 (2021): 5424–32. http://dx.doi.org/10.3397/in-2021-3095.

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Sampling spatio-temporal acoustic fields is a challenging problem since it demands a large number of sensors. Typically, to characterize the pressure field inside an enclosure, the number of measurements required increases linearly with frequency and cubically with volume, becoming an intractable problem for rooms of moderate size even at low and mid frequencies. Sparse representation techniques, such as Compressed Sensing, rely on the sparsity of natural signals in certain representation domain to drastically reduce the number of measurements needed to sample such signals. In this study, we o

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Vannoppen, Astrid, Anne Gobin, Lola Kotova, et al. "Wheat Yield Estimation from NDVI and Regional Climate Models in Latvia." Remote Sensing 12, no. 14 (2020): 2206. http://dx.doi.org/10.3390/rs12142206.

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Wheat yield variability will increase in the future due to the projected increase in extreme weather events and long-term climate change effects. Currently, regional agricultural statistics are used to monitor wheat yield. Remotely sensed vegetation indices have a higher spatio-temporal resolution and could give more insight into crop yield. In this paper, we (i) evaluate the possibility to use Normalized Difference Vegetation Index (NDVI) time series to estimate wheat yield in Latvia and (ii) determine which weather variables impact wheat yield changes using both ALARO-0 and REMO Regional Cli

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Yamamoto, A., Y. Hasegawa, and N. Kasagi. "Optimal control of dissimilar heat and momentum transfer in a fully developed turbulent channel flow." Journal of Fluid Mechanics 733 (September 23, 2013): 189–220. http://dx.doi.org/10.1017/jfm.2013.436.

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AbstractSustained friction drag reduction and heat transfer augmentation are simultaneously achieved in a fully developed channel flow where the averaged transport equations and wall boundary conditions for momentum and heat have identical form. Zero-net-mass-flux wall blowing and suction is assumed as a control input and its spatio-temporal distribution is determined based on optimal control theory. When the root-mean-square value of the control input is 5 % of the bulk mean velocity, the friction drag is decreased by 24 % from the uncontrolled value, whereas the heat transfer is more than do

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Medina-Cetina, Zenon, Ahran Song, Yichuan Zhu, Alma Rosa Pineda-Contreras, and Amy Rechenmacher. "Global and Local Deformation Effects of Dry Vacuum-Consolidated Triaxial Compression Tests on Sand Specimens: Making a Database Available for the Calibration and Development of Forward Models." Materials 15, no. 4 (2022): 1528. http://dx.doi.org/10.3390/ma15041528.

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A comprehensive experimental database containing results of a series of dry vacuum-consolidated triaxial compression tests was populated. The tests were performed on sand specimens and conducted under similar experimental conditions, in which specimens’ boundary deformation was captured using a three-dimensional digital image correlation analysis (3D-DIC). The use of a standard triaxial device along with the 3D-DIC technology allowed the specimens’ global and local boundary displacement fields to be computed from start to end of the compression phase. By repeating each test under the same expe

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Zhang, Wenmin, Martin Brandt, Alexander V. Prishchepov, Zhaofu Li, Chunguang Lyu, and Rasmus Fensholt. "Mapping the Dynamics of Winter Wheat in the North China Plain from Dense Landsat Time Series (1999 to 2019)." Remote Sensing 13, no. 6 (2021): 1170. http://dx.doi.org/10.3390/rs13061170.

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Monitoring spatio-temporal changes in winter wheat planting areas is of high importance for the evaluation of food security. This is particularly the case in China, having the world’s largest population and experiencing rapid urban expansion, concurrently, it puts high pressure on food demands and the availability of arable land. The relatively high spatial resolution of Landsat is required to resolve the historical mapping of smallholder wheat fields in China. However, accurate Landsat-based mapping of winter wheat planting dynamics over recent decades have not been conducted for China, or an

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40

Bogaardt, Laurens, Romulo Goncalves, Raul Zurita-Milla, and Emma Izquierdo-Verdiguier. "Dataset Reduction Techniques to Speed Up SVD Analyses on Big Geo-Datasets." ISPRS International Journal of Geo-Information 8, no. 2 (2019): 55. http://dx.doi.org/10.3390/ijgi8020055.

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The Singular Value Decomposition (SVD) is a mathematical procedure with multiple applications in the geosciences. For instance, it is used in dimensionality reduction and as a support operator for various analytical tasks applicable to spatio-temporal data. Performing SVD analyses on large datasets, however, can be computationally costly, time consuming, and sometimes practically infeasible. However, techniques exist to arrive at the same output, or at a close approximation, which requires far less effort. This article examines several such techniques in relation to the inherent scale of the s

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Duecker, Daniel Andre, Andreas Rene Geist, Edwin Kreuzer, and Eugen Solowjow. "Learning Environmental Field Exploration with Computationally Constrained Underwater Robots: Gaussian Processes Meet Stochastic Optimal Control." Sensors 19, no. 9 (2019): 2094. http://dx.doi.org/10.3390/s19092094.

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Autonomous exploration of environmental fields is one of the most promising tasks to be performed by fleets of mobile underwater robots. The goal is to maximize the information gain during the exploration process by integrating an information-metric into the path-planning and control step. Therefore, the system maintains an internal belief representation of the environmental field which incorporates previously collected measurements from the real field. In contrast to surface robots, mobile underwater systems are forced to run all computations on-board due to the limited communication bandwidt

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Perrard, Stéphane, Adrián Lozano-Durán, Marc Rabaud, Michael Benzaquen, and Frédéric Moisy. "Turbulent windprint on a liquid surface." Journal of Fluid Mechanics 873 (June 28, 2019): 1020–54. http://dx.doi.org/10.1017/jfm.2019.318.

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We investigate the effect of a light turbulent wind on a liquid surface, below the onset of wave generation. In that regime, the liquid surface is populated by small disorganised deformations elongated in the streamwise direction. Formally identified recently by Paquier et al. (Phys. Fluids, vol. 27, 2015, art. 122103), the deformations that occur below the wave onset were named wrinkles. We provide here a theoretical framework for this regime, using the viscous response of a free liquid surface submitted to arbitrary normal and tangential interfacial stresses at its upper boundary. We relate

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Mytnyk, T. H., V. O. Manukalo, O. V. Dubrovina, and Mytnyk O.O. "ON THE ISSUE OF SPECIFYING RELIABILITY CRITERIA USED IN AUTOMATED SPACE-TIME CONTROL OF METEOROLOGICAL OBSERVATION DATA." Hydrology, hydrochemistry and hydroecology, no. 3 (69) (2023): 51–60. http://dx.doi.org/10.17721/2306-5680.2023.3.4.

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In order to ensure a reliability of data on a state of surface layer of atmosphere, data of meteorological observations conducted on the network of the Hydrometeorological Service of Ukraine are subject to regular multi-level technical and critical control. The entire set of errors in data of meteorological measurements, according to a nature of their manifestation, are divided into two groups: 1) random errors associated with instantaneous pulsations of measured meteorological valuables and their distortion during their further collection and processing; 2) systematic errors, which depend on

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Prasad, Kumar, Marco Ottinger, Chunzhu Wei, and Patrick Leinenkugel. "Assessment of Coastal Aquaculture for India from Sentinel-1 SAR Time Series." Remote Sensing 11, no. 3 (2019): 357. http://dx.doi.org/10.3390/rs11030357.

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Aquaculture is one of the fastest growing primary food production sectors in India and ranks second behind China. Due to its growing economic value and global demand, India’s aquaculture industry experienced exponential growth for more than one decade. In this study, we extract land-based aquaculture at the pond level for the entire coastal zone of India using large-volume time series Sentinel-1 synthetic-aperture radar (SAR) data at 10-m spatial resolution. Elevation and slope from Shuttle Radar Topographic Mission digital elevation model (SRTM DEM) data were used for masking inappropriate ar

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Zhyla, Simeon, Valerii Volosyuk, Vladimir Pavlikov, et al. "Statistical synthesis of aerospace radars structure with optimal spatio-temporal signal processing, extended observation area and high spatial resolution." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 1 (February 23, 2022): 178–94. http://dx.doi.org/10.32620/reks.2022.1.14.

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Using the statistical theory of optimization of radio engineering systems the optimal method of coherent radar imaging of surfaces in airborne synthetic aperture radar with planar antenna arrays is developed. This method summarizes several modes of terrain observation and it is fully consistent with current trends in the development of cognitive radars with the possibilities of radiation pattern restructuring in space and adaptive reception of reflected signals. Possible modifications of the obtained optimal method for the operation of high-precision airborne radars with a wide swath are prese

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Postle, Bradley R., Jeffrey S. Berger, Alexander M. Taich, and Mark D'Esposito. "Activity in Human Frontal Cortex Associated with Spatial Working Memory and Saccadic Behavior." Journal of Cognitive Neuroscience 12, supplement 2 (2000): 2–14. http://dx.doi.org/10.1162/089892900564028.

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We examined, with event-related fMRI, two hypotheses about the organization of human working memory function in frontal cortex: (1) that a region immediately anterior to the frontal eye fields (FEF) (superior frontal cortex, SFC) is specialized for spatial working memory (Courtney, et al., 1998); and (2) that dorsolateral prefrontal cortex (PFC) plays a privileged role in the manipulation of spatial stimuli held in working memory (Owen, et al., 1996; Petrides 1994). Our delayed-response task featured 2-D arrays of irregularly arranged squares that were highlighted serially in a random sequence

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Gitis, Valeri, Alexander Derendyaev, and Konstantin Petrov. "Analyzing the Performance of GPS Data for Earthquake Prediction." Remote Sensing 13, no. 9 (2021): 1842. http://dx.doi.org/10.3390/rs13091842.

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The results of earthquake prediction largely depend on the quality of data and the methods of their joint processing. At present, for a number of regions, it is possible, in addition to data from earthquake catalogs, to use space geodesy data obtained with the help of GPS. The purpose of our study is to evaluate the efficiency of using the time series of displacements of the Earth’s surface according to GPS data for the systematic prediction of earthquakes. The criterion of efficiency is the probability of successful prediction of an earthquake with a limited size of the alarm zone. We use a m

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Brewer, Kiara, Alistair Clulow, Mbulisi Sibanda, Shaeden Gokool, Vivek Naiken, and Tafadzwanashe Mabhaudhi. "Predicting the Chlorophyll Content of Maize over Phenotyping as a Proxy for Crop Health in Smallholder Farming Systems." Remote Sensing 14, no. 3 (2022): 518. http://dx.doi.org/10.3390/rs14030518.

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Smallholder farmers depend on healthy and productive crop yields to sustain their socio-economic status and ensure livelihood security. Advances in South African precision agriculture in the form of unmanned aerial vehicles (UAVs) provide spatially explicit near-real-time information that can be used to assess crop dynamics and inform smallholder farmers. The use of UAVs with remote-sensing techniques allows for the acquisition of high spatial resolution data at various spatio-temporal planes, which is particularly useful at the scale of fields and farms. Specifically, crop chlorophyll content

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FUNKE, KLAUS, and ULF T. EYSEL. "Inverse correlation of firing patterns of single topographically matched perigeniculate neurons and cat dorsal lateral geniculate relay cells." Visual Neuroscience 15, no. 4 (1998): 711–29. http://dx.doi.org/10.1017/s0952523898154111.

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Action potentials of single perigeniculate (PGN) cells and relay cells of the dorsal lateral geniculate nucleus (dLGN) with topographically matched or at least partially overlapping receptive fields (RF) were simultaneously recorded in the anesthetized and paralyzed cat during visual stimulation with moving gratings or flashing light spots of different size. In many cases, PGN cells showed an activity pattern which appeared like a mirror image of distinct periods of dLGN activity. Flashing spots evoked transient volleys of activity in PGN cells which increased in strength and shortened in late

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Akbari, Elahe, Ali Darvishi Boloorani, Jochem Verrelst, et al. "Biophysical Variable Retrieval of Silage Maize with Gaussian Process Regression and Hyperparameter Optimization Algorithms." Remote Sensing 15, no. 14 (2023): 3690. http://dx.doi.org/10.3390/rs15143690.

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Quantification of vegetation biophysical variables such as leaf area index (LAI), fractional vegetation cover (fCover), and biomass are among the key factors across hydrological, agricultural, and irrigation management studies. The present study proposes a kernel-based machine learning algorithm capable of performing adaptive and nonlinear data fitting so as to generate a suitable, accurate, and robust algorithm for spatio-temporal estimation of the three mentioned variables using Sentinel-2 images. To this aim, Gaussian process regression (GPR)–particle swarm optimization (PSO), GPR–genetic a

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