Abstract： The Internet used by 3.2 billion people in 2015. Nearly half of the global population will be using the internet by the end of this year, according to a new report. Enterprises today gain vast volumes of data from different sources and influence this information by means of data analysis to support effective decision-making and provide new functionality and services. The key requirement of data analytics is scalability, simply due to the immense volume of data that need to be extracted, processed, and analyzed in a timeline fashion. Possibly the most popular framework for current large-scale data analytics is Map-Reduce, mainly due to its salient features that include scalability, fault-tolerance, ease of programming, and edibility. However, despite its merits, MapReduce has evident performance limitations in miscellaneous analytical tasks, and this has given rise to a significant body of research that aim at improving its efficiency, while maintaining its desirable properties. The aims of this review the state-of-the-art in improving the performance of parallel query processing using MapReduce. A set of the most significant weaknesses and limitations of Map-Reduce is discussed at a high level, along with solving techniques. Taxonomy is presented for categorizing existing research on MapReduce improvements according to the specific problem they target. Based on the proposed taxonomy, a classification of existing research is provided focusing on the optimization objective. Concluding, this research article outlines interesting directions for future parallel data processing systems.

Abstract： In this paper a symmetric key (stream cipher mode/ block cipher mode) cryptosystem is proposed, involving chaotic maps and quasi group. The proposed cryptosystem destroys any existing patterns in the input, and also, it maximizes entropy. Moreover, the n-grams illustrate that the proposed cryptosystem is secure against the statistics analysis. Furthermore, Experimental results show that the ciphertext has good diffusion and confusion properties with respect to the plaintext and the key, also the results demonstrate that the block cipher mode gives higher entropy than the steam cipher mode.

Abstract： The purpose of this paper is to prove that the ant colony algorithm is an excellent mathematical modeling method and improve the production efficiency of the single drilling machine. The methods of mathematical induction and mathematical deduction and mathematical hypothesis are commonly used mathematical methods in scientific research. The ant colony algorithm to solve the TSP problem: algorithm design ideas: using the standard ant colony algorithm or its improved to achieve a traveling salesman problem TSP, find the shortest distance of the 51 City, the number of iterations is 1000 times, the final output of the optimal solution. Algorithm flow: (1) initialize ant colony: initialize ant colony parameter, set ant number, ant put in 51 vertices, initialize path pheromone. (2) Ant action: the ants leave their paths by the ants in front of the pheromone and their own judgments to complete a loop path. (3) Releasing pheromones: the path to releasing ants through a certain percentage of pheromones. (4) The evaluation of ants: the fitness is evaluated according to the objective function of each ant. (5) If the shortest path condition is satisfied, the optimal output is obtained. Otherwise, the algorithm continues. (6) Pheromones evaporate: pheromones continue to dissipate over time. The result of this paper is that the ant colony algorithm has high accuracy and efficiency; the TSP problem can be solved, to improve the production efficiency of the single drilling machine. The conclusion of this paper is that ant colony algorithm is an excellent algorithm, the TSP problem can be solved, for example, can improve the production efficiency of the single drilling machine.

Abstract： Exam anxiety is one of the most important reasons for academic failure in students, so finding related variables is an undeniable necessity. The aim of this study was to determine the role of emotion regulation and self-compassion strategies in predicting exam anxiety in undergraduate students. The statistical population of the present study included all undergraduate students of Islamic Azad University, Rasht Branch in the academic year 2009-2010, with an approximate number of 4500 people. From the study population, a sample of 312 people were selected according to Morgan table and using cluster random sampling method. The obtained data were analyzed using Pearson correlation coefficient and multiple regression. Findings showed that between the total score of emotional regulation strategies and the components of emotional reassessment and emotional inhibition; and there is a positive and significant relationship between the total score of self-compassion and the components of kindness with oneself, the feeling of human commonalities and mindfulness with the total score of test anxiety and the components of worry and excitement (P <0.05). In contrast, between the isolation component with the total test anxiety score and the anxiety and excitement components; And there is a negative and significant relationship between self-judgment component and total test anxiety score and excitement component (P <0.05). While between the component of self-judgment with the component of concern; There was no significant relationship between the component of similarity with the total score of test anxiety and the components of anxiety and excitement (P <0.05).