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Relevant bibliographies by topics / Spatio-Temporal navigation

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Academic literature on the topic 'Spatio-Temporal navigation'

Author: Grafiati

Published: 28 September 2022

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Journal articles on the topic "Spatio-Temporal navigation"

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Kawasaki, Yosuke, Shunsuke Mochizuki, and Masaki Takahashi. "ASTRON: Action-Based Spatio-Temporal Robot Navigation." IEEE Access 9 (2021): 141709–24. http://dx.doi.org/10.1109/access.2021.3120216.

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Liu, Yixiao, Lei Zhang, Yixuan Zhou, Qin Xu, Wen Fu, and Tao Shen. "Clustering-Based Decision Tree for Vehicle Routing Spatio-Temporal Selection." Electronics 11, no. 15 (July 29, 2022): 2379. http://dx.doi.org/10.3390/electronics11152379.

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The algorithm of the clustering-based decision tree, which is a methodology of multimodal fusion, has made many achievements in many fields. However, it is not common in the field of transportation, especially in the application of automobile navigation. Meanwhile, the concept of Spatio-temporal data is now widely used. Therefore, we proposed a vehicle routing Spatio-temporal selection system based on a clustering-based decision tree. By screening and clustering Spatio-temporal data, which is a collection of individual point data based on historical driving data, we can identify the routes and many other features. Through the decision tree modeling of the state information of Spatio-temporal data, which includes the features of the historical data and route selection, we can obtain an optimal result, that is, the route selection made by the system. Moreover, all the above calculations and operations are done on the edge, which is different from the vast majority of current cloud computing vehicle navigation. We have also experimented with our system using real vehicle data. The experiments show that it can output path decision results for a given situation, which takes little time and is the same as the approximated case of networked navigation. The experiments yielded satisfactory results. Our system could save a lot of cloud computing power, which might change the current navigation systems.

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Ueda, Naonori. "Proactive People-flow Navigation Based on Spatio-temporal Prediction." Japanese Journal of Applied Statistics 45, no. 3 (2016): 87–102. http://dx.doi.org/10.5023/jappstat.45.87.

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Ferri, Anthony, Monika Popp, and Gebhard Wulfhorst. "Digital Directions:." Interdisciplinary Journal of Signage and Wayfinding 5, no. 2 (December 23, 2021): 7–21. http://dx.doi.org/10.15763/issn.2470-9670.2021.v5.i2.a78.

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Wayfinding in spatially complex public transit environments poses unique navigational challenges. Transfers, delays, barriers, and user capacity all influence the usability of a system. Because of the smartphone, how we navigate through these systems, and interact with the surrounding environment, is changing. The smartphone provides a spatio-temporal strategy that removes the reliance on our immediate environment and personalizes the wayfinding process -- unlike that of transit schedules, signs, and maps. How does smartphone usage influence performance and the wayfinding experience? This paper looks at smartphone usage of twelve participants through a shadowed commented walk, known as a Destination-Task Investigation, in Munich’s public transit system. The study provides insights into the role and the influence of smartphones during the wayfinding process. Furthermore, it shows that Apps providing integrated spatio-temporal information, such as Google, were used most frequently, especially for confirmation during navigation.

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Han, Shi-Yuan, Qi-Wei Sun, Qiang Zhao, Rui-Zhi Han, and Yue-Hui Chen. "Traffic Forecasting Based on Integration of Adaptive Subgraph Reformulation and Spatio-Temporal Deep Learning Model." Electronics 11, no. 6 (March 9, 2022): 861. http://dx.doi.org/10.3390/electronics11060861.

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Traffic forecasting provides the foundational guidance for many typical applications in the smart city management, such as urban traffic control, congestion avoidance, and navigation guidance. Many researchers have focused on the spatio-temporal correlations under fixed topology structure in traffic network to improve the traffic forecasting accuracy. Despite their advantages, the existing approaches are not completely discussed that the association relationship among traffic network nodes are not invariable under different traffic conditions. In this paper, a novel traffic forecasting framework is proposed by integrating the dynamic association of traffic nodes with the spatio-temporal deep learning model. To be specific, an adaptive subgraph reformulation algorithm is designed first based on the specific forecasting interval to reduce the interference of irrelevant spatio-temporal information. After that, by enhancing the attention mechanism with the generative decoder, a spatio-temporal deep learning model with only one forward operation is proposed to avoid the degradation of accuracy in the long-term prediction, in which the spatio-temporal information and the external factors (such as weather and holiday) are fused together to be as an input vector. Based on the reformulated subgraph constructed of traffic nodes with closer spatio-temporal correlation, experiments show that the proposed framework consistently outperforms other GNN (Graph Neural Network)-based state-of-the-art baselines for various forecasting intervals on a real-world dataset.

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Cai, Yifan, Richard Droste, Harshita Sharma, Pierre Chatelain, Lior Drukker, Aris T. Papageorghiou, and J. Alison Noble. "Spatio-temporal visual attention modelling of standard biometry plane-finding navigation." Medical Image Analysis 65 (October 2020): 101762. http://dx.doi.org/10.1016/j.media.2020.101762.

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Samany, Najmeh Neysani, Mahmoud Reza Delavar, Nicholas Chrisman, and Mohammad Reza Malek. "Modelling Spatio-Temporal Relevancy in Urban Context-Aware Pervasive Systems Using Voronoi Continuous Range Query and Multi-Interval Algebra." Mobile Information Systems 9, no. 3 (2013): 189–208. http://dx.doi.org/10.1155/2013/284904.

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Space and time are two dominant factors in context-aware pervasive systems which determine whether an entity is related to the moving user or not. This paper specifically addresses the use of spatio-temporal relations for detecting spatio-temporally relevant contexts to the user. The main contribution of this work is that the proposed model is sensitive to the velocity and direction of the user and applies customized Multi Interval Algebra (MIA) with Voronoi Continuous Range Query (VCRQ) to introduce spatio-temporally relevant contexts according to their arrangement in space. In this implementation the Spatio-Temporal Relevancy Model for Context-Aware Systems (STRMCAS) helps the tourist to find his/her preferred areas that are spatio-temporally relevant. The experimental results in a scenario of tourist navigation are evaluated with respect to the accuracy of the model, performance time and satisfaction of users in 30 iterations of the algorithm. The evaluation process demonstrated the efficiency of the model in real-world applications.

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Putman, Nathan F., Erica S. Jenkins, Catherine G. J. Michielsens, and David L. G. Noakes. "Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon." Journal of The Royal Society Interface 11, no. 99 (October 6, 2014): 20140542. http://dx.doi.org/10.1098/rsif.2014.0542.

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Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye ( Oncorhynchus nerka ) and pink ( Oncorhynchus gorbuscha ) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species.

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Lan, Hai, He Yin, Ying-Yi Hong, Shuli Wen, David C. Yu, and Peng Cheng. "Day-ahead spatio-temporal forecasting of solar irradiation along a navigation route." Applied Energy 211 (February 2018): 15–27. http://dx.doi.org/10.1016/j.apenergy.2017.11.014.

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Shi, Qiang, Wujiao Dai, Rock Santerre, Zhiwei Li, and Ning Liu. "Spatially Heterogeneous Land Surface Deformation Data Fusion Method Based on an Enhanced Spatio-Temporal Random Effect Model." Remote Sensing 11, no. 9 (May 7, 2019): 1084. http://dx.doi.org/10.3390/rs11091084.

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The spatio-temporal random effect (STRE) model, a type of spatio-temporal Kalman filter model, can be used for the fusion of the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) data to generate high spatio-temporal resolution deformation series, assuming that the land deformation is spatially homogeneous in the monitoring area. However, when there are multiple deformation sources in the monitoring area, complex spatial heterogeneity will appear. To improve the fusion accuracy, we propose an enhanced STRE fusion method (eSTRE) by taking spatial heterogeneity into consideration. This new method integrates the spatial heterogeneity constraints in the STRE model by constructing extra-constrained spatial bases for the heterogeneous area. The effectiveness of this method is verified by using simulated data and real land surface deformation data. The results show that eSTRE can reduce the root mean square (RMS) of InSAR interpolation results by 14% and 23% on average for a simulation experiment and Los Angeles experiment, respectively, indicating that the new proposed method (eSTRE) is substantially better than the previous STRE fusion model.

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Dissertations / Theses on the topic "Spatio-Temporal navigation"

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Schmoll, Sebastian [Verfasser], and Matthias [Akademischer Betreuer] Schubert. "Navigation with uncertain spatio-temporal resources / Sebastian Schmoll ; Betreuer: Matthias Schubert." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2021. http://d-nb.info/1233200941/34.

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Oh, Chang-Geun. "The Effects of Proximity Compatibility and Graphics on Spatio-Temporal SituationAwareness for Navigation." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1453218915.

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Pignata, Aurora. "Study of the spatio-temporal dynamics of guidance receptors during commissural axon navigation in the spinal cord." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSE1286/document.

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Les commissures forment un ensemble de connexions nerveuses assurant la communication entre les neurones de chaque hémi partie du système nerveux central des bilatériens. Au cours du développement embryonnaire, les axones des neurones commissuraux sont guidés au travers de la ligne médiane délimitant ces deux parties. Plusieurs sources de signaux de guidage attractifs et répulsifs agissent de concert pour organiser les trajectoires de ces axones. Dans la moelle épinière, les axones commissuraux traversent la ligne médiane dans un territoire ventral, la plaque du plancher (PP). Au cours de la traversée de la PP, ils acquièrent une sensibilité à des signaux répulsifs exprimés par ce territoire qui leur empêchent de rebrousser le chemin et qui les poussent hors de la PP. Plusieurs couples ligands/récepteurs médient ces forces répulsives mais les mécanismes qui sous-tendent l'acquisition de la sensibilité aux signaux répulsifs restent encore peu connus. Par exemple on ignore si les axons se sensibilisent à tous les signaux répulsifs en même temps, quand précisément ce switch de réponse se fait, et les contributions précises de chacun de ces signaux. Une spécificité fonctionnelle est suggérée par l'analyse des phénotypes d'invalidation des gènes codant pour ces récepteurs chez la souris ou encore par des manipulations d'expression chez l'embryon de poulet. L'objectif de mes travaux de thèse a été de tester l'hypothèse selon laquelle la génération de spécificités fonctionnelles pourrait résulter de contrôles précis et distincts de la dynamique spatiale et temporelle des récepteurs de guidage à la surface du cône de croissance. J'ai tout d'abord développé un dispositif de vidéomicroscopie adapté à l'enregistrement de cônes de croissance accomplissant la traversée de la PP, sur des moelles épinières en configuration de «livre ouvert». Afin de visualiser l'adressage à la surface du cône de croissance, j'ai exploité une forme de GFP sensible au pH, dont les propriétés de fluorescence à pH neutre permettent un suivi spécifique du pool de surface des protéines (Nawabi et al., 2010; Delloye-Bourgeois et al, 2014). J'ai utilisé ce paradigme pour comparer la dynamique temporelle de 4 récepteurs médiant les réponses aux divers signaux répulsifs de la PP: Nrp2, Robo1, Robo2 et PlxnA1. Les vecteurs d'expression de ces formes pHLuo de récepteurs ont été introduits dans les neurones commissuraux de la moelle épinière d'embryon de poulet par électroporation in ovo. Par des approches de microscopie à super-résolution sur les livres-ouverts, j'ai aussi étudié la distribution spatiale des récepteurs répulsifs à la surface des cônes de croissances au cours de la traversée. L'ensemble de ces expériences a pu démontrer que les récepteurs sont adressés à la membrane à différents temps de la navigation de la PP et occupent, de plus, des domaines distincts du cône de croissance. J'ai ensuite adapté la technique d'électroporation à la moelle épinière d'embryon de souris. Ces expériences ont montré que les séquences temporelles observées chez le poulet sont conservées chez la souris. J'ai également réintroduit le récepteur Robo1 dans une lignée de souris présentant une invalidation des récepteurs Robo1/2 et montré que l'altération de la traversée de la PP caractéristique de cette lignée est abolie dans la population d'axones capables d'adresser le récepteur Robo1 à la membrane. Au final, mes résultats démontrent que les axones commissuraux ne sont pas sensibilisés aux signaux répulsifs par la mise en œuvre d'un programme général. Au contraire, les récepteurs de guidage possèdent des profils de dynamiques temporelles spécifiques, et des domaines de distribution distincts dans le cône de croissance. Le contrôle de la dynamique d'adressage représente ainsi un mécanisme permettant de discriminer des signaux concomitants, en les fonctionnalisant à différents temps de la navigation de la moelle épinière
During embryonic development, commissural axons are guided through the midline, crossing from one side of the CNS to the other one at specific time points and positions to project onto contralateral neurons. Several sources of attractive cues regulate their navigation. In addition, repulsive forces act at different steps to keep the axons along their path. In the developing spinal cord, commissural axons cross the midline in a ventral territory, the floor plate (FP). Commissural axons gain sensitivity to repellents present in the FP after their crossing. The setting of these novel properties is necessary for preventing the axons to cross back and also for pushing them towards FP exit. Various ligand/receptor couples have been reported to mediate these repulsive forces. Whether commissural axons gain response to all the repulsive cues at the same time is not known. Whether these repulsive cascades have specific functions is suggested by different outcome of their invalidation in mouse models, but how are set these differences also remains unknown. We hypothesized that the generation of functional specificities could be achieved though specific controls of the spatial and temporal dynamics of guidance receptors at the growth cone surface. During my PhD, I developed a set up for time-lapse imaging of “open book” spinal cords, to monitor the dynamics of guidance receptors in axons experiencing native guidance decisions across the midline. To visualize their cell surface sorting, receptors were fused to the pH-sensitive GFP, pHLuorin, whose fluorescence at neutral pH reports membrane protein pools (Nawabi et al, 2010; Delloye-Bourgeois et al, 2014), and were expressed in spinal commissural neurons through in ovo electroporation. This paradigm revealed striking differences in the temporal dynamics of Nrp2, Robo1, Robo2 and PlexinA1, the receptors known to mediate the responsiveness to the major midline repellents referenced in vertebrates: Slit-Ns, Slit-Cs and Semaphorin3B. Moreover, using super-resolution microscopy, I could evidence that PlexinA1 and Robo1 are sorted in distinct subdomains of commissural growth cones navigating the floor plate. I also introduced the pHLuo-tagged receptors in the mouse embryo. These experiments showed that the temporal sequences established in the chick are conserved in the mouse, and that FP crossing in Robo1/2 mutant embryos was rescued in growth cones that could achieve cell surface sorting of Robo1. Thus, my results show that guidance receptors for midline repellents have highly specific spatial and temporal dynamics. The generation of a temporal sequences of cell surface sorting thus represents a mechanism whereby commissural growth cones discriminate concomitant signals by functionalizing them at different timing of their spinal cord navigation

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Jaillot, Vincent. "3D, temporal and documented cities : formalization, visualization and navigation." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSE2026.

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L'étude et la compréhension de l'évolution des villes est un enjeu sociétal important, notamment pour améliorer la qualité de vie dans une ville toujours plus dense. Le numérique et en particulier les modèles 3D de villes peuvent être des éléments de réponse. Leur manipulation est parfois rendue complexe par la prise en compte de leurs dimensions thématique, géométrique et topologique ainsi que de leur structuration hiérarchique
The study and understanding of cities evolution is an important societal issue, particularly for improving the quality of life in an increasingly dense city. Digital technology and in particular 3D city models can be part of the answer. Their manipulation is however sometimes complex due to their thematic, geometric, topological dimensions and hierarchical structure.In this thesis, we focus on the integration of the temporal dimension and in the enrichment with multimedia documents of these 3D models of the city, in an objective of visualization and navigation on the web. Moreover, we take a particular interest in interoperability (based on standards), reusability (with a shared software architecture and open source components) and reproducibility (to make our experiments durable).Our first contribution is a formalization of the temporal dimension of cities for interactive navigation and visualization on the web. For this, we propose a conceptual model of existing standards for the visualization of cities on the web, which we extend with a formalization of the temporal dimension. We also propose a logical model and a technical specification of these proposals.Our second contribution allows the integration of multimedia documents into city models for spatial, temporal and thematic visualization and navigation on the web. We propose a conceptual model for the integration of heterogeneous and multidimensional geospatial data. We then use it for the integration of multimedia documents and 3D city models.Finally, this thesis took place in a multidisciplinary context via the Fab-Pat project of the LabEx IMU, which focuses on cultural heritage sharing and shaping. In this framework, a contribution combining social sciences and computer science has allowed the design of DHAL, a methodology for the comparative analysis of devices for sharing heritage via digital technology. Dans cette thèse, nous nous intéressons à l'intégration de la dimension temporelle et à l'enrichissement avec des documents multimédia de ces modèles 3D de la ville, dans un objectif de visualisation et de navigation sur le web. Nous portons un intérêt particulier à l'intéropérabilité (en s'appuyant sur des standards), à la réutilisabilité (avec une architecture logicielle partagée et des composants open source) et à la reproductibilité (permettant de rendre nos expérimentations pérennes).Notre première contribution est une formalisation de la dimension temporelle des villes pour une navigation et visualisation interactive sur le web. Pour cela, nous proposons un modèle conceptuel des standards existants pour la visualisation de villes sur le web, que nous étendons avec une formalisation de la dimension temporelle. Nous proposons également un modèle logique et une spécification technique de ces propositions.Notre deuxième contribution permet d'intégrer des documents multimédias aux modèles de villes pour une visualisation et une navigation spatiale, temporelle et thématique sur le web. Nous proposons un modèle conceptuel pour l'intégration de données géospatiales hétérogènes et multidimensions. Nous l'utilisons ensuite pour l'intégration de documents multimédias et de modèles 3D de villes.Enfin, cette thèse s'est déroulée dans un contexte pluridisciplinaire via le projet Fab-Pat, du LabEx IMU, qui s'intéresse au partage de la fabrique du patrimoine. Dans ce cadre, une contribution mêlant sciences sociales et informatique a permis de concevoir DHAL, une méthodologie pour l’analyse comparative de dispositifs pour le partage du patrimoine via le numérique

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Mahieux, Pierre. "Interactions tangibles pour naviguer spatialement et temporellement en environnements virtuels. : application à la médiation culturelle en histoire des sciences et techniques." Thesis, École nationale d'ingénieurs de Brest, 2022. https://nuxeo.enib.fr/nuxeo/nxpath/default/default-domain/workspaces/D%C3%A9p%C3%B4t%20des%20th%C3%A8ses@view_documents?tabIds=%3A&old_conversationId=0NXMAIN1.

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Les institutions de médiation culturelle, notamment les musées, utilisent de plus en plus les nouvelles technologies afin d'attirer les visiteurs. D'un côté, la Réalité Mixte permet aux visiteurs d'explorer des reconstitutions de lieux passés ou inaccessibles, mais aussi de naviguer spatialement et temporellement dans ces reconstitutions. D'un autre côté, les interfaces tangibles sont utilisées pour proposer des expériences interactives innovantes et engageantes.Dans cette thèse nous émettons l'hypothèse que l'utilisation d'interfaces tangibles faciliterait la navigation spatio-temporelle sur plusieurs échelles au sein d'Environnements Virtuels. Nos travaux ont deux objectifs : 1) proposer un modèle permettant de représenter l'espace et le temps sur plusieurs échelles ; 2) proposer une interface tangible permettant de naviguer sur ces différentes échelles.En réponse au premier objectif, notre proposition de représentation du temps et de l'espace s'appuie sur des notions utilisées en Histoire des Sciences & Techniques et propose quatre échelles. Nous nous appuyons sur notre modèle pour répondre au second objectif pour lequel nous avons mis en place une démarche de co-conception impliquant des experts en médiation culturelle. Le résultat de cette démarche est SABLIER, un interacteur tangible permettant de naviguer spatio-temporellement au sein d'un Environnement Virtuel
Cultural mediation institutions, especially museums, are increasingly using new technologies to attract visitors. On the one hand, Mixed Reality allows visitors to explore reconstructions of past or inaccessible places, but also to navigate spatially and temporally in these reconstructions. On the other hand, tangible interfaces are used to provide innovative and engaging interactive experiences.In this thesis we hypothesize that the use of tangible interfaces would facilitate spatio-temporal navigation on several scales within Virtual Environments. Our work has two objectives: 1) to propose a model to represent space and time on several scales; 2) to propose a tangible interface to navigate on these different scales.In response to the first objective, our proposition to represent time and space is based on notions used in the History of Science and Technology and proposes four layers. We rely on our model to respond to the second objective, for which we have set up a co-design process involving cultural mediation experts. The result of this approach is SABLIER, a tangible interactor allowing to navigate spatially and temporally within a Virtual Environment

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Mikšík, Ondřej. "Dynamické rozpoznávání scény pro navigaci mobilního robotu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219711.

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Diplomová práce se zabývá porozuměním dynamických scén pro navigaci mobilních robotů. V první části předkládáme nový přístup k "sebe-učícím" modelům - fůzi odhadu úběžníku cesty založeného na frekvenčním zpracování a pravděpodobnostních modelech využívající barvu pro segmentaci. Detekce úběžníku cesty je založena na odhadu dominantních orientací texturního toku, získáného pomocí banky Gaborových vlnek, a hlasování. Úběžník cesty poté definuje trénovací oblast, která se využívá k samostatnému učení barevných modelů. Nakonec, oblasti tvořící cestu jsou vybrány pomocí měření Mahalanobisovi vzdálenosti. Pár pravidel řeší situace, jako jsou mohutné stíny, přepaly a rychlost adaptivity. Kromě toho celý odhad úběžníku cesty je přepracován - vlnky jsou nahrazeny aproximacemi pomocí binárních blokových funkcí, což umožňuje efektivní filtraci pomocí integrálních obrazů. Nejužší hrdlo celého algoritmu bylo samotné hlasování, proto překládáme schéma, které nejdříve provede hrubý odhad úběžníku a následně jej zpřesní, čímž dosáhneme výrazně vyšší rychlosti (až 40x), zatímco přesnost se zhorší pouze o 3-5%. V druhé části práce předkládáme vyhlazovací filtr pro prostorovo-časovou konzistentnost predikcí, která je důležitá pro vyspělé systémy. Klíčovou částí filtru je nová metrika měřící podobnost mezi třídami, která rozlišuje mnohem lépe než standardní Euclidovská vzdálenost. Tato metrika může být použita k nejrůznějším úlohám v počítačovém vidění. Vyhlazovací filtr nejdříve odhadne optický tok, aby definoval lokální okolí. Toto okolí je použito k rekurzivní filtraci založené na podobnostní metrice. Celková přesnost předkládané metody měřená na pixelech, které nemají shodné predikce mezi původními daty a vyfiltrovanými, je téměř o 18% vyšší než u původních predikcí. Ačkoliv využíváme SHIM jako zdroj původních predikcí, algoritmus může být kombinován s kterýmkoliv jiným systémem (MRF, CRF,...), který poskytne predikce ve formě pravěpodobností. Předkládaný filtr představuje první krok na cestě k úplnému usuzování.

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Zeman, Philip Michael. "Feasibility of Multi-Component Spatio-Temporal Modeling of Cognitively Generated EEG Data and its Potential Application to Research in Functional Anatomy and Clinical Neuropathology." Thesis, 2009. http://hdl.handle.net/1828/5010.

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This dissertation is a compendium of multiple research papers that, together, address two main objectives. The first objective and primary research question is to determine whether or not, through a procedure of independent component analysis (ICA)-based data mining, volume-domain validation, and source volume estimation, it is possible to construct a meaningful, objective, and informative model of brain activity from scalpacquired EEG data. Given that a methodology to construct such a model can be created, the secondary objective and research question investigated is whether or not the sources derived from the EEG data can be used to construct a model of complex brain function associated with the spatial navigation and the virtual Morris Water Task (vMWT). The assumptions of the signal and noise characteristics of scalp-acquired EEG data were discussed in the context of what is currently known about functional brain activity to identify appropriate characteristics by which to separate the activities comprising EEG data into parts. A new EEG analysis methodology was developed using both synthetic and real EEG data that encompasses novel algorithms for (1) data-mining of the EEG to obtain the activities of individual areas of the brain, (2) anatomical modeling of brain sources that provides information about the 3-dimensional volumes from which each of the activities separated from the EEG originates, and (3) validation of data mining results to determine if a source activity found via the data-mining step originates from a distinct modular unit inside the head or if it is an artefact. The methodology incorporating the algorithms developed was demonstrated for EEG data collected from study participants while they navigated a computer-based virtual maze environment. The brain activities of participants were meaningfully depicted via brain source volume estimation and representation of the activity relationships of multiple areas of the brain. A case study was used to demonstrate the analysis methodology as applied to the EEG of an individual person. In a second study, a group EEG dataset was investigated and activity relationships between areas of the brain for participants of the group study were individually depicted to show how brain activities of individuals can be compared to the group. The results presented in this dissertation support the conclusion that it is feasible to use ICA-based data mining to construct a physiological model of coordinated parts of the brain related to the vMWT from scalp-recorded EEG data. The methodology was successful in creating an objective and informative model of brain activity from EEG data. Furthermore, the evidence presented indicates that this methodology can be used to provide meaningful evaluation of the brain activities of individual persons and to make comparisons of individual persons against a group. In sum, the main contributions of this body of work are 5 fold. The technical contributions are: (1) a new data mining algorithm tailored for EEG, (2) an EEG component validation algorithm that identifies noise components via their poor representation in a head model, (3) a volume estimation algorithm that estimates the region in the brain from which each source waveform found via data mining originates, (4) a new procedure to study brain activities associated with spatial navigation. The main contribution of this work to the understanding of brain function is (5) evidence of specific functional systems within the brain that are used while persons participate in the vMWT paradigm (Livingstone and Skelton, 2007) examining spatial navigation.
Graduate
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0622
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Book chapters on the topic "Spatio-Temporal navigation"

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Zhu, Le, Michael Mangan, and Barbara Webb. "Spatio-Temporal Memory for Navigation in a Mushroom Body Model." In Biomimetic and Biohybrid Systems, 415–26. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64313-3_39.

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Svecic, Andrei, Gilles Soulez, Frédéric Monet, Raman Kashyap, and Samuel Kadoury. "Multimodal Sensing Guidewire for C-Arm Navigation with Random UV Enhanced Optical Sensors Using Spatio-Temporal Networks." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 249–58. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87202-1_24.

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Wang, Ping, Tongtong Shi, Rui He, and Wubei Yuan. "Prediction of Large Scale Spatio-temporal Traffic Flow Data with New Graph Convolution Model." In Intelligent Electronics and Circuits - Terahertz, IRS, and Beyond [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101756.

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Prompt and accurate prediction of traffic flow is quite useful. It will help traffic administrator to analyze the road occupancy status and formulate dynamic and flexible traffic control in advance to improve the road capacity. It can also provide more precise navigation guidance for the road users in future. However, it is hard to predict spatiotemporal traffic flow data in large scale promptly with high accuracy caused by complex interrelation and nonlinear dynamic nature. With development of deep learning and other technologies, many prediction networks could predict traffic flow with accumulated historical data in time series. In consideration of the regional characteristics of traffic flow, the emerging Graph Convolutional Network (GCN) model is systematically introduced with representative applications. Those successful applications provide a possible way to contribute fast and proper traffic control strategies that could relieve traffic pressure, reduce potential conflict, fasten emergency response, etc.

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Robertson, Shanthi. "Introduction." In Temporality in Mobile Lives, 1–14. Policy Press, 2021. http://dx.doi.org/10.1332/policypress/9781529211511.003.0001.

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The chapter introduces how middling migrants now comprise the majority of regular migration flows to post-industrial countries where migrants with skills and educational capital are increasingly prioritized over unskilled migrant workers. While this middle space is one of relative privilege compared to low-skilled and undocumented labour migrants globally, it is also a space, particularly for those who are young and navigating early career and life transitions, of decidedly uneven experiences. Exploring these lived experiences of mobile temporality is highly significant to migration studies, largely because these experiences reflect the broader spatio-temporal changes migration has undergone in our current era of globalized modernity. The chapter explains that the book seeks to highlight the multifarious ways that temporality operates within the lives of young and middle-class migrants from Asia to Australia whose open-ended mobilities criss-cross multiple spaces, statuses and identities. It draws on the concept of chronomobilities, which it uses to describe the temporalities that structure mobile lives as well as emerge from them. It positions chronomobilities — which encompass the disjunctures, velocities, synchronizations and rhythms of everyday mobile lives and the meanings they entail — as fundamentally shaped by specific global and national 'time-regimes' of the early 21st century. It also argues that three 'time-logics' emerge as the primary ways in which time is 'lived' and understood within migrants' own meaning making and narrations of their lives under these broader temporal conditions. The focus on the three logics — sequence, tempo and synchronicity — allows time to be understood as multiply and simultaneously sequential, rhythmic and relational.

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Conference papers on the topic "Spatio-Temporal navigation"

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Mazuelas, Santiago, Yuan Shen, and Moe Z. Win. "Spatio-temporal information coupling in cooperative network navigation." In GLOBECOM 2012 - 2012 IEEE Global Communications Conference. IEEE, 2012. http://dx.doi.org/10.1109/glocom.2012.6503476.

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Ueda, Naonori, Futoshi Naya, Hitoshi Shimizu, Tomoharu Iwata, Maya Okawa, and Hiroshi Sawada. "Real-time and proactive navigation via spatio-temporal prediction." In the 2015 ACM International Joint Conference. New York, New York, USA: ACM Press, 2015. http://dx.doi.org/10.1145/2800835.2801624.

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Szatmari, Istvan, David Balya, Gergely Timar, Csaba Rekeczky, and Tamas Roska. "Multichannel spatio-temporal topographic processing for visual search and navigation." In Microtechnologies for the New Millennium 2003, edited by Angel Rodriguez-Vazquez, Derek Abbott, and Ricardo Carmona. SPIE, 2003. http://dx.doi.org/10.1117/12.501159.

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Saha, Homagni, Tianshuang Gao, Hamid Emadi, Zhanhong Jiang, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, and Sourabh Bhattacharya. "Autonomous Mobile Sensing Platform for Spatio-Temporal Plant Phenotyping." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5207.

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This paper presents the design, modeling, control and navigation for a novel ground-based mobile sensing platform that can collect multi-modal data in agricultural research farms for high throughput modular plant phenotyping. The platform will have the following capabilities (i) Navigate in a row-crop farm to collect data with minimal human intervention during operation (ii) Autonomous decision making i.e, it can take its own decisions for maximizing the value of information of the acquired data and (iii) Scalable in terms of the size of the farmland. The design requirements for such a platform or robot is formulated, and a detailed discussion on realizing such a design is presented. The dynamics of the robot is presented in the state space form and it is abstracted in the form of a control flow diagram for the automatic steering system. An adaptive sampling approach has been taken to generate an estimated belief-space which is leveraged in the proposed opportunistic sensing scheme to generate way-points for navigation.

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Phan, Connie, and Hugh H. Liu. "Kriged Kalman Filtering for Predicting the Spatio-Temporal Wildfire Temperature Process Evolution." In AIAA Guidance, Navigation, and Control (GNC) Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2013. http://dx.doi.org/10.2514/6.2013-4767.

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Wen, Rong, and Wenjing Yan. "Spatio-temporal Mining with Scene Data Integration for Urban Transportation Navigation." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622244.

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Nguyen, Vu Anh, Janusz A. Starzyk, Alex Leng Phuan Tay, and Wooi-Boon Goh. "Spatio-temporal sequence learning of visual place cells for robotic navigation." In 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, 2010. http://dx.doi.org/10.1109/ijcnn.2010.5596952.

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Yu, Xueqin, Tao Zhang, and Qigang Jiang. "Spatio-temporal data query of urban traffic navigation considering point of interest." In 2013 6th International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2013. http://dx.doi.org/10.1109/iciii.2013.6702931.

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Hirel, Julien, Philippe Gaussier, and Mathias Quoy. "Biologically inspired neural networks for spatio-temporal planning in robotic navigation tasks." In 2011 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2011. http://dx.doi.org/10.1109/robio.2011.6181522.

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Kobayashi, Shingo, Risako Aoki, Yuta Nakamura, Hiroki Ishida, and Ryusuke Miyamoto. "Noise Reduction of Segmentation Results Using Spatio-Temporal Filtering for Robot Navigation." In 2018 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE, 2018. http://dx.doi.org/10.1109/ispacs.2018.8923292.

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