Clustering by fast search and find of density peaks (DPC) (Since, 2014) has been proven to be a promising clustering approach that efficiently discovers the centers clusters finding peaks. The accuracy DPC depends on cutoff distance (dc), cluster number (k) selection clusters. Moreover, final allocation strategy is sensitive poor fault tolerance. shortcomings above make algorithm parameters onl...

Manifold learning based image clustering models are usually employed at local level to deal with images sampled from nonlinear manifold. Multimode patterns in image data matrices can vary from nominal to significant due to images with different expressions, pose, illumination, or occlusion variations. We show that manifold learning based image clustering models are unable to achieve well separa...

Currently, Nearest-Neighbor approaches (NN) have been applied to large scale real world image data mining. However, the following three disadvantages prevent them from wider application compared to other machine learning methods: (i) the performance is inferior on small datasets; (ii) the performance will degrade for data with high dimensions; (iii) they are heavily dependent on the chosen feat...

Travelling salesman problem (TSP) is one the problems of NP-complete family, which means finding shortest complete close tour in graph. This study seeks to solve this using Artificial Bee Colony (ABC) Algorithm along with proposed Discrete Nearest Neighborhood (DNNA). DNNA finds path among points by starting from an arbitrary point. In next steps links will be a guide make tour. other words par...

The N30 component of the somatosensory evoked potential is known to be modulated by sensory interference, motor action, movement ideation and observation. We introduce a new paradigm in which the observation task of another person's hand movement triggers the somatosensory stimulus, inducing the N30 response in participants. In order to identify the possible contribution of the mirror neuron ne...

Digital terrain models (DTM) typically contain large numbers of postings, from hundreds of thousands to billions. Many algorithms that run on DTMs require topological knowledge of the postings, such as finding nearest neighbors, finding the posting closest to a chosen location, etc. If the postings are arranged irregularly, topological information is costly to compute and to store. This paper o...

A growing number of studies have shown that adequate spatial access to healthy foods leads to increased fresh produce consumption and reduced risk of chronic diseases. Annual dynamics of spatial access to 1,539 vendors of fresh produce (including farmers markets and roadside farm stands) are analyzed in Massachusetts. Travel distance to the nearest fresh produce vendor was calculated for each c...

For classification of time series, the simple 1-nearest neighbor (1NN) classifier in combination with an elastic distance measure such as Dynamic Time Warping (DTW) distance is considered superior in terms of classification accuracy to many other more elaborate methods, including k-nearest neighbor (kNN) with neighborhood size k > 1. In this paper we revisit this apparently peculiar relationshi...

We explain MOEA/D and its slightly modified version with two neighborhood structures. We report some interesting observations on the behavior of MOEA/D with various settings of neighborhood size.