In multimedia databases, k-nearest neighbor queries are popular and frequently contain non-spatial predicates. Among the available techniques for such queries, the incremental nearest neighbor algorithm proposed by Hjaltason and Samet is known as the most useful algorithmm15]. The reason is that if k 0 > k neighbors are needed, it can provide the next neighbor for the upper operator without res...

In this research, two techniques of pixel-based and object-based image analysis were investigated and compared for providing land use map in arid basin of Mokhtaran, Birjand. Using Landsat satellite imagery in 2015, the classification of land use was performed with three object-based algorithms of supervised fuzzy-maximum likelihood, maximum likelihood, and K-nearest neighbor. Nine combinations...

In this paper, we develop a novel Distance-weighted k -nearest Neighbor rule (DWKNN), using the dual distance-weighted function. The proposed DWKNN is motivated by the sensitivity problem of the selection of the neighborhood size k that exists in k -nearest Neighbor rule (KNN), with the aim of improving classification performance. The experiment results on twelve real data sets demonstrate that...

Nearest neighbor algorithms can be implemented on content-based image retrieval (CBIR) and classification problems for extracting similar images. In k-nearest neighbor (k-NN), the winning class is based on the k nearest neighbors determined by comparing the query image against all training samples. In this paper, a new nearest neighbor search (NNS) algorithm is proposed using a two-step process...

High-dimensional data are by their very nature often difficult to handle by conventional machine-learning algorithms, which is usually characterized as an aspect of the curse of dimensionality. However, it was shown that some of the arising high-dimensional phenomena can be exploited to increase algorithm accuracy. One such phenomenon is hubness, which refers to the emergence of hubs in high-di...

A visible k nearest neighbor (Vk NN) query retrieves k objects that are visible and nearest to the query object, where “visible”means that there is no obstacle between an object and the query object. Existing studies on the Vk NN query have focused on static data objects. In this paper we investigate how to process the query on moving objects continuously. We queries. We exploit spatial proximi...

A cognitive radio network (CRN) intelligently utilizes the available spectral resources by sensing and learning from environment to maximize spectrum utilization. In CRNs, secondary users (SUs) opportunistically access primary (PUs) spectrum. Therefore, unambiguous detection of PU channel occupancy is most critical aspect operations CRNs. Cooperative (CSS) rated as best choice for making reliab...

land cover information is one of the most important prerequisite in urban management system. in this way remote sensing, as the most economic technology, is mainly used to produce land cover maps. considering the complicated and dense urban areas in third world countries, object based approaches are suggested as an effective image processing technique. the purpose of this paper are the introduc...

Heart disease is the number one killer in world. Someone who has potential to experience heart a person with Diabetes Mellitus (DM). that detected early can reduce risk of and various other complications. This study aims analyze performance model expected be an alternative for screening DM by using machine learning method, namely Fuzzy K-Nearest Neighbour Every Class (FKNNC) algorithm. The inpu...