Relevant bibliographies by topics / Spatio-temporal space

Academic literature on the topic 'Spatio-temporal space'

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Published: 6 September 2023

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Journal articles on the topic "Spatio-temporal space"

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Guesgen, Hans W., and Stephen Marsland. "Spatio-Temporal Footprints." International Journal of Ambient Computing and Intelligence 2, no. 1 (January 2010): 52–58. http://dx.doi.org/10.4018/jaci.2010010104.

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The recognition of human behaviour from sensor observations is an important area of research in smart homes and ambient intelligence. In this paper, we introduce the idea of spatio-temporal footprints, which are local patterns in space and time that should be similar across repeated occurrences of the same behaviour. We discuss the spatial and temporal mapping requirements of these footprints, together with how they may be used.
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Liou, Shih-Ping, and Ramesh C. Jain. "Motion detection in spatio-temporal space." Computer Vision, Graphics, and Image Processing 45, no. 1 (January 1989): 131. http://dx.doi.org/10.1016/0734-189x(89)90079-0.

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Liou, Shih-Ping, and Ramesh C. Jain. "Motion detection in spatio-temporal space." Computer Vision, Graphics, and Image Processing 45, no. 2 (February 1989): 227–50. http://dx.doi.org/10.1016/0734-189x(89)90134-5.

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Baffelli, Erica, and Frederik Schröer. "Spatio-Temporal Translations." Anthropology in Action 28, no. 1 (March 1, 2021): 57–62. http://dx.doi.org/10.3167/aia.2021.280111.

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During the COVID-19 pandemic, access to space has been strictly regulated and restricted. Many of us feel acutely disconnected from our relationships, while at the same time new forms of (virtual) intimacies have become ubiquitous. In the pandemic present, nearly all interpersonal relations are now characterised by a double absence that is concrete and material, and also emotional and felt. This article offers a theoretical reflection on how conditions of absence create new practices of intimacy and new strategies of coping. It does so by discussing how pre-pandemic emotional repertoires are translated into new forms of intimacy that can synchronise or throw out of sync. It highlights the centrality of spatial and temporal relations under absence in uncovering new mediated practices.
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Ma, Chunsheng. "Spatio-temporal variograms and covariance models." Advances in Applied Probability 37, no. 3 (September 2005): 706–25. http://dx.doi.org/10.1239/aap/1127483743.

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Variograms and covariance functions are the fundamental tools for modeling dependent data observed over time, space, or space-time. This paper aims at constructing nonseparable spatio-temporal variograms and covariance models. Special attention is paid to an intrinsically stationary spatio-temporal random field whose covariance function is of Schoenberg-Lévy type. The correlation structure is studied for its increment process and for its partial derivative with respect to the time lag, as well as for the superposition over time of a stationary spatio-temporal random field. As another approach, we investigate the permissibility of the linear combination of certain separable spatio-temporal covariance functions to be a valid covariance, and obtain a subclass of stationary spatio-temporal models isotropic in space.
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Ma, Chunsheng. "Spatio-temporal variograms and covariance models." Advances in Applied Probability 37, no. 03 (September 2005): 706–25. http://dx.doi.org/10.1017/s0001867800000434.

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Variograms and covariance functions are the fundamental tools for modeling dependent data observed over time, space, or space-time. This paper aims at constructing nonseparable spatio-temporal variograms and covariance models. Special attention is paid to an intrinsically stationary spatio-temporal random field whose covariance function is of Schoenberg-Lévy type. The correlation structure is studied for its increment process and for its partial derivative with respect to the time lag, as well as for the superposition over time of a stationary spatio-temporal random field. As another approach, we investigate the permissibility of the linear combination of certain separable spatio-temporal covariance functions to be a valid covariance, and obtain a subclass of stationary spatio-temporal models isotropic in space.
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Jago, Roland, Raül Perea-Causin, Samuel Brem, and Ermin Malic. "Spatio-temporal dynamics in graphene." Nanoscale 11, no. 20 (2019): 10017–22. http://dx.doi.org/10.1039/c9nr01714c.

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van Inwagen, Peter. "Modes of Being and Quantification." Disputatio 6, no. 38 (May 1, 2014): 1–24. http://dx.doi.org/10.2478/disp-2014-0001.

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Abstract If Pegasus existed, he would indeed be in space and time, but only because the word ‘Pegasus’ has spatio-temporal connotations, and not because ‘exists’ has spatio-temporal connotations. If spatio-temporal reference is lacking when we affirm the existence of the cube root of 27, that is simply because a cube root is not a spatio-temporal kind of thing.
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Song, Bingbing, Yanlin Wang, and Fang Li. "The Visualization Representation of Space-Time-Path in The Space-Time-Cube." IOP Conference Series: Earth and Environmental Science 906, no. 1 (November 1, 2021): 012030. http://dx.doi.org/10.1088/1755-1315/906/1/012030.

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Abstract Map is a traditional visualization tool to represent distribution and interaction of spatial objects or spatial phenomenon. However, with the continuous development of acquisition and processing technologies for spatio-temporal data, traditional map can hardly meet the visualization requirement for this type of data. In other words, the dynamic information about spatial object or phenomenon cannot be expressed fully by traditional map. The Space-Time-Cube (STC), as a three-dimensional visualization environment, whose base represents the two-dimensional geographical space and whose height represents the temporal dimension, can simultaneously represent the spatial distribution as well as the temporal changes of spatio-temporal data. For some spatial object or phenomenon, its moving trajectory can be visualized in STC as a Space-Time-Path (STP), by which the speed and state of motion can be clearly reflected. Noticeably, the problem of visual clutter about STP is inevitably due to the complexity of three-dimensional visualization. In order to reduce the impact of visual clutter, this paper discusses different aspects about visualization representation of STP in the STC. The multiple scales representation and the multiple views display can promote interactive experience of users, and the application of different visual variables can help to represent different kinds of attribute information of STP. With the visualization of STP, spatio-temporal changes and attributive characters of spatial object or phenomenon can be represented and analysed.
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Tian, Miao, Xinxin Hu, Jiakai Huang, Kai Ma, Haiyan Li, Shuai Zheng, Liufeng Tao, and Qinjun Qiu. "Spatio-Temporal Relevance Classification from Geographic Texts Using Deep Learning." ISPRS International Journal of Geo-Information 12, no. 9 (September 1, 2023): 359. http://dx.doi.org/10.3390/ijgi12090359.

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The growing proliferation of geographic information presents a substantial challenge to the traditional framework of a geographic information analysis and service. The dynamic integration and representation of geographic knowledge, such as triples, with spatio-temporal information play a crucial role in constructing a comprehensive spatio-temporal knowledge graph and facilitating the effective utilization of spatio-temporal big data for knowledge-driven service applications. The existing knowledge graph (or geographic knowledge graph) takes spatio-temporal as the attribute of entity, ignoring the role of spatio-temporal information for accurate retrieval of entity objects and adaptive expression of entity objects. This study approaches the correlation between geographic knowledge and spatio-temporal information as a text classification problem, with the aim of addressing the challenge of establishing meaningful connections among spatio-temporal data using advanced deep learning techniques. Specifically, we leverage Wikipedia as a valuable data source for collecting and filtering geographic texts. The Open Information Extraction (OpenIE) tool is employed to extract triples from each sentence, followed by manual annotation of the sentences’ spatio-temporal relevance. This process leads to the formation of quadruples (time relevance/space relevance) or quintuples (spatio-temporal relevance). Subsequently, a comprehensive spatio-temporal classification dataset is constructed for experiment verification. Ten prominent deep learning text classification models are then utilized to conduct experiments covering various aspects of time, space, and spatio-temporal relationships. The experimental results demonstrate that the Bidirectional Encoder Representations from Transformer-Region-based Convolutional Neural Network (BERT-RCNN) model exhibits the highest performance among the evaluated models. Overall, this study establishes a foundation for future knowledge extraction endeavors.
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Dissertations / Theses on the topic "Spatio-temporal space"

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Fagerström, Daniel. "Spatio-Temporal Scale-Space Theory." Doctoral thesis, KTH, Datorseende och robotik, CVAP, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-33686.

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This thesis addresses two important topics in developing a systematic space-time geometric approach to real-time, low-level motion vision. The first one concerns measuring of image flow, while the second one focuses on how to find low level features. We argue for studying motion vision in terms of space-time geometry rather than in terms of two (or a few) consecutive image frames. The use of Galilean Geometry and Galilean similarity geometry for this  purpose is motivated and relevant geometrical background is reviewed. In order to measure the visual signal in a way that respects the geometry of the situation and the causal nature of time, we argue that a time causal Galilean spatio-temporal scale-space is needed. The scale-space axioms are chosen so that they generalize popular axiomatizations of spatial scale-space to spatio-temporal  geometries. To be able to derive the scale-space, an infinitesimal framework for scale-spaces that respects a more general class of Lie groups (compared to previous theory) is developed and applied. Perhaps surprisingly, we find that with the chosen axiomatization, a time causal Galilean scale-space is not possible as an evolution process on space and time. However, it is possible on space and memory. We argue that this actually is a more accurate and realistic model of motion vision. While the derivation of the time causal Galilean spatio-temporal scale-spaces requires some exotic mathematics, the end result is as simple as one possibly could hope for and a natural extension of  spatial scale-spaces. The unique infinitesimally generated scale-space is an ordinary diffusion equation with drift on memory and a diffusion equation on space. The drift is used for velocity  adaption, the "velocity adaption" part of Galilean geometry (the Galilean boost) and the temporal scale-space acts as memory. Lifting the restriction of infinitesimally generated scale spaces, we arrive at a new family of scale-spaces. These are generated by a family of fractional differential evolution equations that generalize the ordinary diffusion equation. The same type of evolution equations have recently become popular in research in e.g. financial and physical modeling. The second major topic in this thesis is extraction of features from an image flow. A set of low-level features can be derived by classifying basic Galilean differential invariants. We proceed to derive invariants for two main cases: when the spatio-temporal  gradient cuts the image plane and when it is tangent to the image plane. The former case corresponds to isophote curve motion and the later to creation and disappearance of image structure, a case that is not well captured by the theory of optical flow. The Galilean differential invariants that are derived are equivalent with curl, divergence, deformation and acceleration. These  invariants are normally calculated in terms of optical flow, but here they are instead calculated directly from the the  spatio-temporal image.
QC 20110518
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Apichayakul, Phisut. "Spatio-temporal State Space Model Estimation for Smart structures." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.522539.

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Baskaran, Savitha. "Visualization of spatio-temporal data in two dimensional space." Thesis, Purdue University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10246961.

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Spatio-temporal data is becoming very popular in the recent times, as there are large number of datasets that collect both location and temporal information in the real time. The main challenge is that extracting useful insights from such large data set is extremely complex and laborious. In this thesis, we have proposed a novel 2D technique to visualize the spatio-temporal big data. The visualization of the combined interaction between the spatial and temporal data is of high importance to uncover the insights and identify the trends within the data.

Maps have been a successful way to represent the spatial information. Additionally, in this work, colors are used to represent the temporal data. Every data point has the time information which is converted into relevant color, based on the HSV color model. The variation in the time is represented by transition from one color to another and hence provide smooth interpolation. The proposed solution will help the user to quickly understand the data and gain insights.

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Laptev, Ivan. "Local spatio-temporal image features for motion interpretation." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3797.

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Visual motion carries information about the dynamics of ascene. Automatic interpretation of this information isimportant when designing computer systems forvisualnavigation, surveillance, human-computer interaction, browsingof video databases and other growing applications.

In this thesis, we address the issue of motionrepresentation for the purpose of detecting and recognizingmotion patterns in video sequences. We localize the motion inspace and time and propose to use local spatio-temporal imagefeatures as primitives when representing and recognizingmotions. To detect such features, we propose to maximize ameasure of local variation of the image function over space andtime and show that such a method detects meaningful events inimage sequences. Due to its local nature, the proposed methodavoids the in.uence of global variations in the scene andovercomes the need for spatial segmentation and tracking priorto motion recognition. These properties are shown to be highlyuseful when recognizing human actions in complexscen es.

Variations in scale and in relative motions of the cameramay strongly in.uence the structure of image sequences andtherefore the performance of recognition schemes. To addressthis problem, we develop a theory of local spatio-temporaladaptation and show that this approach provides invariance whenanalyzing image sequences under scaling and velocitytransformations. To obtain discriminative representations ofmotion patterns, we also develop several types of motiondescriptors and use them for classifying and matching localfeatures in image sequences. An extensive evaluation of thisapproach is performed and results in the context of the problemof human action recognition are presented. I

n summary, this thesis provides the following contributions:(i) it introduces the notion of local features in space-timeand demonstrates the successful application of such featuresfor motion interpretation; (ii) it presents a theory and anevaluation of methods for local adaptation with respect toscale and velocity transformations in image sequences and (iii)it presents and evaluates a set of local motion descriptors,which in combination with methods for feature detection andfeature adaptation allow for robust recognition of humanactions in complexs cenes with cluttered and non-stationarybackgrounds as well as camera motion.

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Wu, Elizabeth. "Spatio-Temporal Data Mining and Analysis of Precipitation Extremes." Thesis, The University of Sydney, 2008. https://hdl.handle.net/2123/28120.

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The work in this thesis aimed to discover new ways to analyse and mine information about precipitation extremes in South America from spatio-temporal data. This was done in two ways. First, analysis was performed through the use of statistical measures that provided insight into the behaviour of precipitation extremes between regions. Second, a new spatio-temporal outlier detection algorithm was introduced to discover moving outliers from the data.
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Krishan, Kapilanjan. "Characterizations of spatio-temporal complex systems." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-05162005-071906/.

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Thesis (Ph. D.)--Physics, Georgia Institute of Technology, 2006.
Schatz, Michael, Committee Chair ; Cvitanovic, Predrag, Committee Member ; Uzer, Turgay, Committee Member ; Grigoriev, Roman, Committee Member ; Mischaikow, Konstantin, Committee Member.
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Noga, Jacek Leszek. "Bayesian state-space modelling of spatio-temporal non-Gaussian radar returns." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624278.

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Uhl, Philip J. "A Spatio-Temporal Data Model for Zoning." BYU ScholarsArchive, 2002. https://scholarsarchive.byu.edu/etd/1.

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Planning departments are besieged with temporal/historical information. While for many institutions historical information can be relegated to archives, planning departments have a constant need to access and query their historical information, particularly their historical spatial information such as zoning. This can be a cumbersome process fraught with inaccuracies due to the changing organizational methods and the extended historical legacies of most municipalities. Geographic Information Systems can be a tool to provide a solution to the difficulties in querying spatio-temporal planning data. Using a data model designed specifically to facilitate the querying of historical zoning information, queries can be performed to answer basic zoning questions such as "what is the zoning history for a specific parcel of land?" This work outlines this zoning data model, its implementation, and its testing using queries basic to the needs of planning departments.
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Samant, Gajanan Balkrishna. "Verification of the "Energy Accumulation in Waves Travelling through a Checkerboard Dielectric Material Structure in Space-time" Using Spice Simulations." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/1210.

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"Recently, there has been some good interest in the field of Dynamic Materials, also referred to as Spatio-Temporal Composites. These materials have been theoretically attributed to show ability to switch their electromagnetic properties in time, as contrast to the spatial variations shown by regular materials of non-dynamic nature, existing naturally. Though there is no exhibition of dynamic material in nature yet, there are suggestions for its synthesis. This paper follows the idea of using standard lossless transmission line model approximating a material substance. Such a material though not truly homogeneous, could be made to vary its properties in time. The aim of this work is to test this idea for its functional efficiency in comparison to analytical results obtained from earlier works on the subject. We make use of Spice simulation for this. An important aspect of this work is to facilitate the dynamic operations in a static environment. Almost all the simulators available today like Spice, ADS, etc intrinsically provide no ability for parameter variations in time. Nonetheless, we make use of certain popular tricks to implement circuits imitating the dynamic circuit components we need. Such implementations are separately tested to demonstrate their success in providing us with the dynamic environment we desire. Finally, within the limitations of the computing capabilities, we could successfully show an agreement between the results obtained and the existing theory. "
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Gabolde, Pablo. "Measurements of the spatio-temporal profiles of femtosecond laser pulses." Diss., Available online, Georgia Institute of Technology, 2007, 2007. http://etd.gatech.edu/theses/available/etd-06272007-101312/.

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Thesis (Ph. D.)--Physics, Georgia Institute of Technology, 2008.
Trebino, Rick, Committee Chair ; Kennedy, Brian, Committee Member ; Kuzmich, Alex, Committee Member ; Curtis, Jennifer, Committee Member ; Buck, John, Committee Member.
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Books on the topic "Spatio-temporal space"

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1948-, Aertsen Ad, ed. Brain theory: Spatio-temporal aspects of brain function. Amsterdam: Elsevier, 1993.

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L, Heres, ed. Time in GIS: Issues in spatio-temporal modelling. Delft: NCG, 2000.

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Frank, A. U., I. Campari, and U. Formentini, eds. Theories and Methods of Spatio-Temporal Reasoning in Geographic Space. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55966-3.

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U, Frank Andrew, Campari I, and Formentini U, eds. Theories and methods of spatio-temporal reasoning in geographic space. Berlin: Springer-Verlag, 1992.

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Hazarika, Shyamanta M. Qualitative spatio-temporal representation and reasoning: Trends and future directions. Hershey, PA: Information Science Reference, 2012.

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Spatial statistics and spatio-temporal data: Covariance functions and directional properties. Chichester, West Sussex, U.K: Wiley, 2011.

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Chenkun, Qi, and SpringerLink (Online service), eds. Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems: A Time/Space Separation Based Approach. Dordrecht: Springer Netherlands, 2011.

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Zhongguo chan ye ji qun shi kong fa zhan yan jiu: Spatio-temporal development study on industrial clusters in China. Beijing Shi: Jing ji guan li chu ban she, 2011.

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Shi jian yu zhong de shi jian bo mo xing: Shi kong shu ju de shi jue tan suo huan jing = The Time Wave in Time Space : A Visual Exploration Environment for Spatio-temporal Data. Beijing: Ce hui chu ban she, 2014.

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Cheng shi jing guan dong tai shi kong mo ni: Spatio-temporal dynamic and simulation of urban landscape. Beijing: Zhongguo huan jing ke xue chu ban she, 2009.

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Book chapters on the topic "Spatio-temporal space"

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Angulo, José M., María C. Bueso, and Francisco J. Alonso. "Space-Time Adaptive Sampling and Data Transformations." In Spatio-Temporal Design, 231–48. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118441862.ch10.

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Heuvelink, Gerard B. M., Daniel A. Griffith, Tomislav Hengl, and Stephanie J. Melles. "Sampling Design Optimization for Space-Time Kriging." In Spatio-Temporal Design, 207–30. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118441862.ch9.

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Lindeberg, Tony. "Linear spatio-temporal scale-space." In Scale-Space Theory in Computer Vision, 113–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63167-4_44.

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Neuhaus, Fabian. "Structuring Space." In Emergent Spatio-temporal Dimensions of the City, 189–236. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09849-4_7.

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Peinke, J., W. Clauss, R. P. Huebener, A. Kittel, J. Parisi, U. Rau, and R. Richter. "Spatio — Temporal Correlations in Semiconductors." In Spontaneous Formation of Space-Time Structures and Criticality, 145–76. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3508-5_11.

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Neuhaus, Fabian. "Urban Machine and Time-Space." In Emergent Spatio-temporal Dimensions of the City, 13–36. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09849-4_2.

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Neuhaus, Fabian. "Body Space and Spatial Narrative." In Emergent Spatio-temporal Dimensions of the City, 37–54. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09849-4_3.

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Anapolitanos, Dionysios A. "Space, Time, the Spatio-Temporal, and Monadic Reality." In Science and Philosophy, 94–173. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9147-8_3.

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Snodgrass, Richard T. "Temporal databases." In Theories and Methods of Spatio-Temporal Reasoning in Geographic Space, 22–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55966-3_2.

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Filipović, Luna, and Katarzyna M. Jaszczolt. "Introduction: Linguistic diversity in the spatio-temporal domain." In Space and Time in Languages and Cultures, 1–12. Amsterdam: John Benjamins Publishing Company, 2012. http://dx.doi.org/10.1075/hcp.36.01intro.

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Conference papers on the topic "Spatio-temporal space"

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Nuss, Martin C., Melissa Li, T. H. Chiu, and Afshin Partovi. "Spatio-Temporal Holograpy." In International Conference on Ultrafast Phenomena. Washington, D.C.: Optica Publishing Group, 1994. http://dx.doi.org/10.1364/up.1994.mc.3.

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There are quite a few examples of analogies between spatial problems and their corresponding temporal counterparts in optics. One example is the space-time duality between diffraction and dispersion, which has recently resulted in the concept of a “time lens” [1,2]. Another one is the similarity between holographic and photon-echo optical memories [3].
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Souto, Yania, Ana Maria Moura, and Fabio Porto. "Managing Uncertainty in Spatio-Temporal Series." In IX Brazilian e-Science Workshop. Sociedade Brasileira de Computação - SBC, 2015. http://dx.doi.org/10.5753/bresci.2015.7204.

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Uncertain time series analysis has recently become an important research topic, particularly when searching for features of natural phenomena using similarity functions. Natural phenomena are often modeled as time series, such as in weather forecast, in which temperature variation is monitored through space and time. In such a context, different models for weather forecast produce variations on predictions that can be interpreted as predictions uncertainty. One important problem is to represent the variations presented in predictions along space and time. In order to address a solution to this problem, this paper defines a new type of series, here named uncertain spatio-temporal series, and proposes a computational strategy to manage uncertainty in probabilistic database. Using this new series some analytical queries can be performed, leading to the discovery of interesting observation patterns.
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Sharabi, Yonatan, Alex Dikopoltsev, Eran Lustig, Yaakov Lumer, and Mordechai Segev. "Light Propagation in Spatio-Temporal Crystals." In CLEO: Applications and Technology. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cleo_at.2022.jw5a.1.

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We study light propagation in spatio-temporal photonic crystals: media whose electromagnetic properties vary periodically in both time and space. We find unique eigenmodes inside mixed energy-momentum gaps, extracting energy and momentum from the modulation.
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Budde, Matthias, Julio De Melo Borges, Stefan Tomov, Till Riedel, and Michael Beigl. "Leveraging Spatio-Temporal Clustering for Participatory Urban Infrastructure Monitoring." In The First International Conference on IoT in Urban Space. ICST, 2014. http://dx.doi.org/10.4108/icst.urb-iot.2014.257282.

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Jolly, Spencer W. "Vector-vortex beams with spatio-temporal couplings." In CLEO: Science and Innovations. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_si.2023.sf1r.3.

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Liu, Chang-hua, Hou-tian Zhang, and Shi-dong Wang. "Discussion on spatio-temporal data model of mining-land use change." In International Conference on Space Information Technology 2009, edited by Xingrui Ma, Baohua Yang, and Ming Li. SPIE, 2009. http://dx.doi.org/10.1117/12.855417.

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Sharma, Balaji R., Manish Kumar, and Kelly Cohen. "Spatio-Temporal Estimation of Wildfire Growth." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-4022.

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This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deploy ability.
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Segal, Ohad, Yonatan Plotnik, Eran Lustig, Moshe-Ishay Cohen, Alex Dikopoltsev, and Mordechai Segev. "Photonic Space-Time Topological Edge States." In CLEO: Fundamental Science. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_fs.2023.ftu4d.1.

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We introduce topological edge states in photonic space-time crystals. We show that photonic space-time crystals support propagating edge states and find a unique edge state that grows exponentially in energy whilst following the spatio-temporal edge.
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Ben Othmane, Amel, Andrea Tettamanzi, Serena Villata, and Nhan Le Thanh. "CARS - A Spatio-temporal BDI Recommender System: Time, Space and Uncertainty." In 10th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006590700480057.

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Aston, John, Federico Turkheimer, Vincent Cunningham, and Roger Gunn. "Wavelet variance components in image space for spatio-temporal neuroimaging data." In Optical Science and Technology, SPIE's 48th Annual Meeting, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 2003. http://dx.doi.org/10.1117/12.506118.

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Reports on the topic "Spatio-temporal space"

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Kularatne, Dhanushka N., Subhrajit Bhattacharya, and M. Ani Hsieh. Computing Energy Optimal Paths in Time-Varying Flows. Drexel University, 2016. http://dx.doi.org/10.17918/d8b66v.

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Autonomous marine vehicles (AMVs) are typically deployed for long periods of time in the ocean to monitor different physical, chemical, and biological processes. Given their limited energy budgets, it makes sense to consider motion plans that leverage the dynamics of the surrounding flow field so as to minimize energy usage for these vehicles. In this paper, we present two graph search based methods to compute energy optimal paths for AMVs in two-dimensional (2-D) time-varying flows. The novelty of the proposed algorithms lies in a unique discrete graph representation of the 3-D configuration space spanned by the spatio-temporal coordinates. This enables a more efficient traversal through the search space, as opposed to a full search of the spatio-temporal configuration space. Furthermore, the proposed strategy results in solutions that are closer to the global optimal when compared to greedy searches through the spatial coordinates alone. We demonstrate the proposed algorithms by computing optimal energy paths around the Channel Islands in the Santa Barbara bay using time-varying flow field forecasts generated by the Regional Ocean Model System. We verify the accuracy of the computed paths by comparing them with paths computed via an optimal control formulation.
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