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12 results for “spatio-temporal data”
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Research ArticleOpen accessPhrase in the titleGENERALIZED LINEAR MIXED MODELS WITH SPATIAL RANDOM EFFECTS FOR SPATIO-TEMPORAL DATA: AN APPLICATION TO DENGUE FEVER MAPPINGKrisada Lekdee, Lily IngsrisawangThe Generalized Linear Mixed Models (GLMMs) with spatial random effects for spatio-temporal data are proposed. A hierarchical Bayesian method is used for parameter estimation. The random effects are assumed to be normally distributed and the spatial random effects are assumed to be proper Conditional Autoregressive (CAR) models. The proposed models are applied to Dengue fever data in Northern Thailand, including … …Journal of Mathematics and Statistics, Vol. 9, Issue 2 · 13 May 2013 · 8,065 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Fuzzy Clustering Based Method for the Spatio-Temporal Data AnalysisAnahita Zolghadr, Afsaneh JalalianSpatiotemporal data is a type of data that is collected by the sensors. This type of data has two spatial and temporal dimensions. There are many challenges in analyzing spatiotemporal big data. Common evaluation metrics of clustering methods are not appropriate for spatiotemporal data. Previous clustering methods and the conventional evaluation metrics are efficient for data like time series with … …Journal of Computer Science, Vol. 18, Issue 6 · 13 Jun 2022 · 5,638 accessesView PDFCite
Research ArticleOpen accessIn the keywordsWireless Sensor Networks Fault Identification Using Data AssociationT. Abirami Kongu, P. Thangaraj, P. Priakanth KonguProblem statement: Wireless Sensor Networks (WSN) are formed by thousands of lightweight nodes equipped with transducers for capturing information. The captured data are transmitted using multi hop routes to a base station, also called a sink. They can be extensively deployed during emergency response, medical monitoring and missiion critical applications requiring extensive data capture from sensors.Wireless sensor network applications include … …Journal of Computer Science, Vol. 8, Issue 9 · 11 Aug 2012 · 6,942 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMathematical Genesis of the Spatio-Temporal Covariance FunctionsGema Fernández-Avilés, Jose-María Montero, Jorge MateuProblem statement: Obtaining new and flexible classes of nonseparable spatio-temporal covariances have resulted in a key point of research in the last years within the context of spatiotemporal Geostatistics. Approach: In general, the literature has focused on the problem of full symmetry and the problem of anisotropy has been overcome. Results: By exploring mathematical properties of positive definite functions and … …Journal of Mathematics and Statistics, Vol. 7, Issue 1 · 31 Jan 2011 · 7,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,048 accessesView PDFCite
Research ArticleOpen accessIn the abstractRelationship between Rice Yield and Apparent Electrical Conductivity of Paddy SoilsM.H. Ezrin, M.S.M. Amin, A.R. Anuar, W. AimrunProblem statement: Understanding the relationships between rice yield and soil properties such as bulk electrical conductivity is of critical importance in precision farming. The apparent Electrical Conductivity of soil (ECa) is influenced by a combination of physico-chemical properties including soluble salts, clay content and mineralogy, soil water content, bulk density, organic matter and soil temperature. Accordingly, ECa is considered as … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 8,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransforming Spatio-Temporal Yield Maps to Classified Management Zone Maps for Efficient Management of Oil PalmAbdul Rahim Anuar, Kah Joh Goh, Tee Bee Heoh, Osumanu Haruna AhmedOne of the major challenges in oil palm plantations today is proper interpretation of yield maps for site-specific management and development of classified management zone maps for its efficient management. A study was conducted on an on-going fertilizer response trial in Sabah, Malaysia to examine the possibility of converting spatio-temporal yield maps of oil palm to classified management zone maps … …American Journal of Applied Sciences, Vol. 5, Issue 10 · 31 Oct 2008 · 7,500 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparison of Spatio-Temporal Bayesian Models for Reconstruction of Rainfall Fields in a Cloud Seeding ExperimentSujit k. sahu, Giovanna Jona Lasinio, Arianna orasi, Kanti V. MardiaIn response to the drought experienced in Southern Italy a rain seeding project has been setup and developed during the years 1989-1994. The initiative was taken with the purpose of applying existing methods of rain enhancement technology to regions of south Italy including Puglia. The aim of this study is to provide statistical support for the evaluation of the experimental … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,810 accessesView PDFCite
Research ArticleOpen accessIn the abstractParsimonious Var Models For Air Pollution Dynamic AnalysisFontanella lara, Granturco mariagraziaWe discuss a framework to obtain temporal predictions for an evolving spatial field regularly sampled in time at arbitrary spatial locations. Difficulties caused by large data sets and the modelling of complicated spatio-temporal interactions limit the effectiveness of traditional space-time statistical models. In this study, we propose the use of a flexible approach to deal with large and small time-scale … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,181 accessesView PDFCite