The conventional procedures of clustering algorithms are incapable of overcoming the difficulty of managing and analyzing the rapid growth of generated data from different sources. Using the concept of parallel clustering is one of the robust solutions to this problem. Apache Hadoop architecture is one of the assortment ecosystems that provide the capability to store and process the data in a distributed and parallel fashion. In this paper, a parallel model is designed to process the k-means clustering algorithm in the Apache Hadoop ecosystem by connecting three nodes, one is for server (name) nodes and the other two are for clients (data) nodes. The aim is to speed up the time of managing the massive sc

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 The article critically analyzes traditional translation models. The most influential models of translation in the second half of the 20th century have been mentioned, among which the theory of formal and dynamic equivalence, the theory of regular correspondences, informative, situational-denotative, functional-pragmatic theory of communication levels have been considered. The selected models have been analyzed from the point of view of the universality of their use for different types and types of translation, as well as the ability to comprehend the deep links established between the original and the translation.

Аннотация

Deception is an inseparable facet of political discourse in attaining strategic political gains though compromising public opinion. However, the employment of discursive deception strategies by the policy-making institutions of think tanks has not received due attention in the literature. The current study aims at exploring how the ideologizing deception strategies are utilized by the conservative American think tank of the Washington Institute to reproduce socio-political realities and re-shape public opinion. To fulfill this task, van Dijk’s (2000) notion of ideological polarization which shows positive self-representation and negative other representation is adopted to conduct a critical discourse analysis of four Arabic texts relea

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

Climate change, together with terrorism, economic depressions, and mass-destructive weaponry, is a source of international phobia for many people. The advancement in technology increases the competition among world powers and economic systems to develop their industrial enterprises. The smoke that emits from the factories, the pollution caused by the industrial projects, the excessive use of green gas result in the increase of global warming and have catastrophic effects on the ecosphere of the planet. Besides, man’s wrong practices even in agricultural matters are exhausting the natural resources of the lands, and they badly affect the ecological diversity and the wellbeing of the humans and non-humans alike. Contemporary feminis