Data mining has many functionalities. One of the main functions of data mining is the classification that is used to predict the class and generate information based on historical data. In the classification, there is a lot of algorithms that can be used to process the input into the desired output, thus it is very important to observe the performance of each algorithm. The purpose of this rese...

The conceptual high-level design of a low cost neural network (NN) based autonomous vehicle is presented. Focus is on the domain of indoor as well as small outdoor applications such as mail delivery system among neighboring organizations. The design is based on four independent neural networks attached with ultrasonic rangefinders; Inertial Measuring Unit (IMU) and GPS receiver. The NN model is...

The iterative closest point (ICP) algorithm is one of the most popular approaches to shape registration currently in use. At the core of ICP is the computationally-intensive determination of nearest neighbors (NN). As of now there has been no comprehensive analysis of competing search strategies for NN. This paper compares several libraries for nearest-neighbor search (NNS) on both simulated an...

Usually the environmental parameters influence the sensor characteristics in a nonlinear manner. Therefore obtaining correct readout from a sensor under varying environmental conditions is a complex problem. In this paper we propose a neural network (NN)-based interface framework to automatically compensate for the nonlinear influence of the environmental temperature and the nonlinear-response ...

This writing presents a new way for classification of human age based on k-NN classifier. The hypothesis has been implemented to distribute input images into one of four age groups i.e kid, young, adult and senior adult. For implementation, first primitive features of face supported on craniofacial development is found. For subordinate features skin texture and wrinkle analysis is found. Images...

Inducing adaptive predictive models in real-time from high throughput data streams is one of the most challenging areas of Big Data Analytics. The fact that data streams may contain concept drifts (changes of the pattern encoded in the stream over time) and are unbounded, imposes unique challenges in comparison with predictive data mining from batch data. Several real-time predictive data strea...

Nearest Neighbor (NN) search has been in the core of spatial and spatiotemporal database research during the last decade. The literature on NN query processing algorithms so far deals with either stationary or moving query points over static datasets or future (predicted) locations over a set of continuously moving points. With the increasing number of Mobile Location Services (MLS), the need f...

In many situations, users would readily accept an approximate query result if evaluation of the query becomes faster. In particular, this holds true for Nearest-Neighbor Search (NN-Search), a typical implementation of similarity search. In this article, we investigate approximate NNquery evaluation techniques based on the VA-File. This data structure efficiently supports NNquery evaluation in h...

The structural and electronic properties of C24-2nBn Nn and M@ C24-2nBn Nn (M= alkaline and earth alkaline metals; n=3 and 6) molecules are studied using the Density Functional Theory (DFT). It was found that the most interaction is in M@ C24-2nBn Nn complexes (M=Be, Mg; n=3 and 6). The negative nucleus-independent chemical shifts confirm that C24-2nBn Nn (n=3 and 6) cages exhibit aromatic char...