Today every second the size of data (real world data) is increasing exponentially. Real world data means digital photographs, speech signals, scientific observations, statistic calculations etc. improvement in technology have also improved data quality and quantity. This improvement also helps in increasing the features or dimensions of observed data. As the dimensions increases the size of data increases. Second, introduction of interdisciplinary fields motivating students from diverse fields to work together and develop new road maps in different research areas this also increase the size of data as the accuracy increases with new mile stones. The challenge is to store data in minimum space and retrieve it adequately and accurately. For minimizing the space reduction of dimensionality is needed. The goal of reduction of dimension is to make low dimension representation of high dimension data so that the structure or geometry of data will be preserved. The dimension of data means the cardinality of variables that are compute on each observation to define this observation uniquely. Reduction of dimensionality helps minimize space, fast information retrieval, image processing, easy visualization, good classification of data set easily etc. Actually reduced dimensional representation should have a dimensionality that consists to intrinsic dimensionality of data. The intrinsic dimensionality means the least number of dimensions used for explanation of the observed properties of the data.

Heterogeneous Computing Environment is a novel platform which provides computing for rigorous applications. In this paper, we emphasized, in the quality of service optimization in Heterogeneous Computing Environment. For this purpose quantum mechanics inspired algorithm is develop and applied. To measure the effectiveness of the recommended algorithm, simulation experiment is performed and the output exhibits that the model performs much superior than state of art.

According to those defects of user behavior trust evaluation methods in subjective classification weight and dynamic adaptability, in this paper, the traditional Analytic Hierarchy Process has been optimized and improved, we research and presents a credible assessment of new improved user behavior model based on AHP. The method combines user behavior activity, incentive factor on a comprehensive assessment of user behavior, and demonstrates the feasibility of the method by an example. The results show that the evaluation model can adapt to the dynamic changes in user behavior trust, objectively determine the weight of each decision attribute, and can accurately and effectively assess the credibility of user behavior.

The clustering model most closely related to statistics is based on distribution models. Clusters can then easily be defined as objects belonging most likely to the same distribution. A convenient property of this approach is that this closely resembles the way artificial data sets are generated: by sampling random objects from a distribution. The word network in the term 'artificial neural network' refers to the inter-connections between the neurons in the different layers of each system. An example system has three layers. The first layer has input neurons which send data via synapses to the second layer of neurons, and then via more synapses to the third layer of output neurons. More complex systems will have more layers of neurons with some having increased layers of input neurons and output neurons. To gain this understanding, neuroscientists strive to make a link between observed biological processes (data), biologically plausible mechanisms for neural processing and learning (biological neural network models) and theory (statistical learning theory and information theory). Here we have proposed n new model based on semi fuzzy artificial neural.

By using AHP and TOPSIS, uncertainty and vagueness from subjective perception and the experiences of decision-maker can be effectively represented and reached to a more effective decision. In this study plant Species selection with AHP and TOPSIS method has been proposed. Although two methods have the same objective of selecting the best plant Species for the mine reclamation, they have differences. In TOPSIS decision-makers used the linguistic variables to assess the importance of the criteria and to evaluate the each alternative with respect to each criterion. These linguistic variables converted into triangular fuzzy numbers and decision matrix was formed. It is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, we are interested in getting high returns but at the same time reducing our risks. This paper presents a comparison of Fuzzy AHP and Fuzzy MCDA in Multi-Objective Behavior Comparison of Plants.

With the improved quality of life, people enjoy life increasingly. Film and television media play an important role in our life. People can absorb nutrition by film and television media and also achieve physical and mental relaxation. But the information on a video website that compares to other websites is ordinarily not complete. In this way, it probably cannot meet users' selection. To solve the above problem, we propose a Internet-facing information fusion algorithm for bi-source movies based on movies media. The algorithm aims to verify and fuse two pieces of data on the same movies from different websites and update the information of movies completely. In order to detect two movies accurately that their information points to the unique movie, we proposed three movie information validation algorithms (MIV) based users and content feature of movies. All of these methods can detect movies' information which needs to fuse. Finally, our experiments show that the methods we proposed generally outperforms single dimensional detection methods by different performance evaluation methods.

In present world there are many heterogeneous environment such as distributed systems, cloud computing etc. Because subsequent generation scientific researchers are being carried out big collaboration of researchers distributed around the world. Research groups are utilizing heterogeneous computing to share, accomplish and process the enormous computation intensive applications. The paper discusses about the key concepts of heterogeneous computing. The paper focuses on the Quality of service Parameters and wants to optimize those parameters. The planning and optimization in heterogeneous systems is a NP-hard problem. To solve this problem we use evolutionary computing techniques are used. The result is plotted, analyzed and compared with state of the art. According to proposal results found be comparable with state of the art.

Tuberculosis (TB) is one of the most primeval diseases of mankind, with molecular evidence going back to over 17,000 years. The genome of M. Tuberculosis (Mtb) have a family of MmpL protein, It has been reported this family play important role in transportation of the cell. Genomic studies have provided a clear understanding of the genetic diversity of MmpL proteins within the bacteria (gram positive) including Mycobacterium genus, and more specifically within Mycobacterium tuberculosis. These results have informed a new perspective on the macro- and micro-evolution. In the present study, we highlighted a comparative study of the MmpL protein family of Mycobacterium tuberculosis using evolutionary trace analysis technique with a statistical analysis of conserved amino acid bases. Our result shows the highest diversity of species as the level of similarity increases. We also found indicating the functional conservation and origin of diversity. Our work will be very useful for the understanding of functional relationship of MmpL family in Mycobacterium tuberculosis.

Voting algorithms are widely used for fault masking. These algorithms are used to increase the total reliability of those systems where safety is the major concern. Researchers have proposed many advanced voting algorithms in order to improve the existing voting algorithms over the period. In this paper, we present a critical survey of fuzzy voting algorithms. In addition, we propose a generalized and improved fuzzy voting algorithm.