In augmented reality, the markers are noticeable by their simple design of rectangular image with black and white areas which disturb the reality of the overall view. As the markerless techniques are not usually robust enough, hiding the markers has a valuable usage which many researchers have focused on. Categorizing the marker hiding methods is the main motivation of this study which explains each of them in details and discusses the advantages and shortcomings of each. The main ideas, enhancements and future works of the well-known techniques are also comprehensively summarized and analyzed in depth. The main goal of this study is to provide researchers, who are interested in markerless or hiding marker methods, an easier approach to choose the method that best suited to their aims. This work reviews the different methods that hide the augmented reality marker by using information from its surrounding area. These methods have considerable differences in their smooth continuation of the texture that hide the marker area as well as their performance to hide the augmented reality marker in real-time. It is also hoped that our analysis helps researchers find solutions to the drawbacks of each method.

In image processing, computer vision and\npattern recognition, the Image retrieval is a most popular research area. In this paper, performance of various CBIR systems, based on combined feature i.e.\ncolor texture and shape, are compared.

In this article, we introduce the notion of AI(∆m)−statistical con-vergence and some newer kind of sequence spaces defined over a 2-normed spaces and give their characterization. The present work gen-eralizes the recent results of [1]. Further, necessary and sufficient condi-tion for the equality of AI(∆m)−statistical convergence and the above-mentioned sequence spaces have been established. The effectiveness ofour work is validated with the help of a suitable examples.

We report the intra organelle nano poration of multi layer osteoblast like cell placed in a 3D non uniform micro fluidic chip composed of bi metallic heterogeneous micro electrode under the influences of smart control FPGA based pico pulse generator and images of intra organelle nanoporation are recognized experimentally. It is observed that When the micro pulse is applied the cell starts to response but it is unable to penetrate the intra cellular nucleus- membrane where as the expected results will come when the Pico pulse is applied on the cell, a number of nano pores are generated on the intra organelle membranes and chemicals are entered into the cell. It is also exposed that the key parameter of nanoporation such as intra pore radius, density, surface tension and ion uptake are externally controlled by user defined hybrid 3D micro chip and FPGA based smart control pico pulse generator. The presented biochip is composed of thick bismuth-gold electrodes that are designed to deliver a maximum of energy to the biological medium containing osteoblast cell. The spectral distributions of the psPEF are considered for the design of the chip. In this research paper we explore the characterization of intraorganelle nanoporation for osteoblast cell at microfloudic environments like 3D hybrid micro bio chip under the influences of smart control FPGA based Pico electric field. We also focus on design of pico pulse exposer system and fabrication of that nanoporative devices. The related experiments carried on the developed 3D micro chip to address its intraorganelle membrane permeabilize capability. The report proposes an appealing attempt to model nanoporation in a biological system, and may pose a significant impact in the field of bone cancer treatment.

The aim of this paper to discuss about the history of kite flying in indo-Pak sub on the basis of news report also explore the this festival cause the human loses bear by the Asian country Pakistan. All data collection and analysis with the help of news reports.

This paper presents a novel feature selection based on association rule mining using reduced dataset. The key idea of the proposed work is to find closely related features using association rule mining method. Apriori algorithm is used to find closely related attributes using support and confidence measures. From closely related attributes a number of association rules are mined. Among these rules, only few related with the desirable class label are needed for classification. We have implemented a novel technique to reduce the number of rules generated using reduced data set thereby improving the performance of Association Rule Mining (ARM) algorithm. Experimental results of proposed algorithm on datasets from standard university of California, Irvine (UCI) demonstrate that our algorithm is able to classify accurately with minimal attribute set when compared with other feature selection algorithms.

This text presents a comprehensive view of the product evaluation of the two angles of view. The first view shows the quality of the product in terms of its characters and their levels, with regard to the fulfillment of the required functions. There will be used consumer tests for assessment. The second view is focused on the price at which a given quality is offered. Subsequently, the two dimensions of evaluation are standardized, i.e. they are converted to a dimensionless number which reaches values from zero to one. Then it is possible to create the overall evaluation OEC, respectively here called as “Index IQP”. The value of IQP index then shows overall benefit of product and it is a guide for producers - what to improve and for customers - “what to buy”.