This article is an endeavour to highlight the relationship between social media and language evolution. It reviews the current theoretical efforts on communication and language change. The descriptive design, which is theoretically based on technological determision, is used. The assumption behind this review is that the social media plays a significant role in language evolution. Moreover, different platforms of social media are characterized by being the easiest and fastest means of communication. It concludes that the current theoretical efforts have paid much attention to the relationship between social media and language evolution. Such efforts have highlighted the fact that social media platforms are awash with a lot of acronyms, cyber slangs, initialisms, morphological shortenings, etc. Much importantly, previous research has suggested that the larger the network size is, the more will be its effect on language evolution.
Contemporary life is racing against time in its temptations and variables, and it has become shaped and changed in an amazing way in its various aspects and fields. This was facilitated by intellectual and scientific communication between civilizations, and the rapid progression in successive inventions and discoveries in the fields of science and arts of knowledge. This contributed to a great economic and commercial renaissance. Then, these economic developments entered the world into a very strong competition, which forced producers to calculate all production costs, to reach the highest profits by reducing the price of the produced commodity on the one hand, and achieving quality in appearance (especially) on the other hand. Since the ma
... Show MoreThis research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri
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Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif
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Spergularia iraqensis sp. nov. is described as a new species from Iraq. This species has been collected from Diyala Province in the central east of Iraq; it is closely related to Spergularia rubra (L.) J. Presl & C. Presl, 1819 and Spergularia bocconei (Scheele) Graebn., 1919.
The distinguishing of the morphological characteristics of the new species alongside the two similar species are discussed with photographs, and an identification key is given for Spergularia iraqensis and other closely related species.
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Lifestyle Medicine is the application of evidence-based lifestyle approaches for the prevention, treatment, and even the reversal of lifestyle-related chronic diseases such as diabetes, hypertension, heart disease, obesity, polycystic ovarian diseases, dementia, arthritis, and cancers
Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.
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