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329 results for “Spatial”
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Research ArticleOpen accessEvery word in the titleExploratory Analysis of Rainfall Occurrence in South Sulawesi Region Using Spatial Point ProcessNurtiti Sunusi, Erna Tri Herdiani, Fachrul Nawawi, GiarnoThis paper study the probability of rainfall occurrence in round year in different segment in South Sulawesi region. In this research, rainfall occurrence in round year described by one line which has divided into 12 months. Each one of those months is assumed that the probability of a rainfall follow a homogeneous Poisson distribution. To modeling the rainfall occurrence in … …Journal of Mathematics and Statistics, Vol. 11, Issue 4 · 15 Feb 2016 · 7,450 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSpatial Pattern of Natural Spread of Rice False Smut (Ustilaginoidea virens) Disease in FieldsBodrun Nessa, Moin U. Salam, A.H.M. Mahfuzul Haque et al.Pattern of disease spread provides improved knowledge on how the pathogen introduces itself and interacts with environment in fields and expresses as a disease. It is especially significant when epidemiology of a disease, such as Rice False Smut (RFSm), is unclearly understood. Not reported before, this study attempted an analysis of spatial pattern of natural spread of RFSm in nine … …American Journal of Agricultural and Biological Sciences, Vol. 10, Issue 2 · 2 Jun 2015 · 8,644 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHABITAT SUITABILITY MODELING FOR EXPLORATION OF THE SPATIAL DISTRIBUTION OF KASHMIR MUSK DEER IN DACHIGAM NATIONAL PARK, KASHMIRMudasir AliMusk deer are highly important as a medicinal species that are severely exploited throughout their range of occurrence due to the medicinal value of the musk produced only by the male individuals. Methods used for studying the populations and distributions of other ungulates do not work well with musk deer and the presence of a unified methodology for studying musk … …American Journal of Environmental Sciences, Vol. 10, Issue 5 · 20 Aug 2014 · 7,861 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA MODIFIED SPATIAL FUZZY C-MEANS CLUSTERING ALGORITHM FOR DETECTING GLAUCOMAIN RETINAL FUNDUS IMAGESS. J. Grace Shoba, A. Brintha ThereseGlaucoma is a disease which affects the eye and causes blindness. It is an ophthalmologist disease characterized by an increase in Intraocular Pressure (IOP). The glaucoma usually affects the optic disc on the retina which increases the cup size. There are various parameters to identify and diagnose glaucoma. The clustering technique is introduced to detect the glaucoma from the optic … …Journal of Computer Science, Vol. 10, Issue 8 · 5 Mar 2014 · 7,027 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA NOVELTY APPROACH OF SPATIAL CO-OCCURRENCE AND DISCRETE SHEARLET TRANSFORM BASED TEXTURE CLASSIFICATION USING LPBOOSTING CLASSIFIERC. Vivek, S. AudithanRecently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial co-occurrence with discrete shearlet transformation through the LPboosting classification. It can be considered as a frame through … …Journal of Computer Science, Vol. 10, Issue 5 · 11 Jan 2014 · 6,602 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleChange Detection Performance in Naturalistic Scenes: The Influence of Visual Working Memory for Identity and Spatial LocationsBonnie L. Angelone, Melissa R. BeckThe present studies examined the roles of identity and spatial working memory in change detection. Observers completed a spatial or identity working memory task concurrently with a change detection task. In the change detection task, participants were presented naturalistic scenes that contained either a color or location change to one object. Concurrently, participants remembered either the colors or locations of … …Current Research in Psychology, Vol. 3, Issue 2 · 5 Jul 2013 · 10,601 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMAXIMUM LIKELIHOOD ESTIMATION FOR SPATIAL DURBIN MODELRokhana Dwi Bekti, Anita Rahayu, SutiknoSpatial Durbin Model (SDM) is one method of spatial autoregressive. This model was developed because the dependencies in the spatial relationships not only occur in the dependent variable, but also on the independent variables. In the assessment of parameter estimation, the process is carried out by Maximum Likelihood Estimation (MLE). This estimation can be approximation by Spatial Autoregressive Models (SAR). … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 15 Jun 2013 · 8,636 accessesView PDFCite
Research ArticleOpen accessEvery word 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 accessEvery word in the titleClassification Model for Hotspot Occurrences Using Spatial Decision Tree AlgorithmImas Sukaesih Sitanggang, Razali Yaakob, Norwati Mustapha, A. N. AinuddinDeveloping a predictive model for forest fires occurrence is an important activity in a fire prevention program. The model describes characteristics of areas where fires occur based on past fires data. It is essential as an early warning system for preventing forest fires, thus major damages because of fires can be avoided. This study describes the application of data mining … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 7,224 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Efficient Algorithm for Mining Spatially Co-located Moving ObjectsG. Manikandan, S. SrinivasanMining co-location patterns from spatial databases may disclose the types of spatial features which are likely located as neighbors’ in space. Accordingly, we present an algorithm previously for mining spatially co-located moving objects using spatial data mining techniques and Prim’s Algorithm. In the previous technique, the scanning of database to mine the spatial co-location patterns took much computational cost. In … …American Journal of Applied Sciences, Vol. 10, Issue 3 · 2 Mar 2013 · 6,649 accessesView PDFCite