Choosing which fast Nearest Neighbour search algorithm to use depends on the task we face. Usually kd-tree search algorithm is selected when the similarity function is the Euclidean or the Manhattan distances. Generic fast search algorithms (algorithms that works with any distance function) are only used when there is not specific fast search algorithms for the involved distance function. In th...

This article proposed a novel human identification method based on retinal images. The proposed system composed of two main parts, feature extraction component and decision-making component. In feature extraction component, first blood vessels extracted and then they have been thinned by a morphological algorithm. Then, two feature vectors are constructed for each image, by utilizing angular an...

Since it was firstly introduced by Torra and Narukawa (The 18th IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, 2009, pp. 1378–1382), the hesitant fuzzy set has attracted more and more attention due to its powerfulness and efficiency in representing uncertainty and vagueness. This paper extends the classical VIKOR (vlsekriterijumska optimizacija i kompromisno resenje in serb...

BACKGROUND Several methodological approaches have been used to estimate distance in health service research. In this study, focusing on cardiac catheterization services, Euclidean, Manhattan, and the less widely known Minkowski distance metrics are used to estimate distances from patient residence to hospital. Distance metrics typically produce less accurate estimates than actual measurements, ...

In order to extract phylogenetic information from DNA sequences, the new normalized k-word average relative distance is proposed in this paper. The proposed measure was tested by discriminate analysis and phylogenetic analysis. The phylogenetic trees based on the Manhattan distance measure are reconstructed with k ranging from 1 to 12. At the same time, a new method is suggested to reduce the m...

Cluster analysis partitions a dataset into a reasonable number of disjoint groups, where each group contains similar patterns. Due to a high number of spectral channels hyper Remote Sensing are difficult to classify with high accuracy and efficiency. In this paper we propose a new image clustering method MD-AP( Manhattan Distance Based Affinity Propagation) for extract the Land cover Classifica...

| A bucket algorithm is proposed for zeroskew routing with linear time complexity on the average. Our algorithm is much simpler and more e cient than the best known algorithm which uses Delaunay triangulations for segments on Manhattan distance. Experimental results show that the linearity of our algorithm is accomplished. Our algorithm generates a zero-skew routing for 3000-pin benchmark data ...