The purpose of the current investigation is to distinguish between working memory ( ) in five patients with vascular dementia ( ), fifteen post-stroke patients with mild cognitive impairment ( ), and fifteen healthy control individuals ( ) based on background electroencephalography (EEG) activity. The elimination of EEG artifacts using wavelet (WT) pre-processing denoising is demonstrated in this study. In the current study, spectral entropy ( ), permutation entropy ( ), and approximation entropy ( ) were all explored. To improve the  classification using the k-nearest neighbors ( NN) classifier scheme, a comparative study of using fuzzy neighbourhood preserving analysis with -decomposition ( ) as a dimensionality reduction technique an

The Logic of Freezers and Animals in the Holy Quran

A New Perspective About Masculinity and the Issue of Identity in Ernest Hemingway's The Old Man and The Sea and Michael Ondaatje's in The Skin of a lion

Multi-belled piles are piles with enlarged ends; these piles have one or further bells at the lower third part of the pile. These piles are suitable for many soils with problems such as softening clay, the variation of groundwater table, expansive soils, black cotton soil, and loose sand. The current study reviewed the behavior of belled piles in multi-layer soils subjected to axial compression and pullout loading. The review covered the experimental and theoretical works on belled piles in multi-layered soils. These piles were subjected to static and dynamic loadings in compression and pullout cases. Most theoretical results focused on software such as PLAXIS 3D. The axial load applied on the piles comes from the upper

The education, especially higher education, is an essentially factor in the progress of any society, if we consider the higher education, represents the top  of  the education`s  pyramid which take part in developing the human  resources and provide the human staff to raise the productive efficiency, and improve the social , economic level                                  

In order to face the increasing importance of higher education, great capabilities and expenditures must be available in a continous way, such expe

This paper deals with the ideological positioning of the English poet John Donne in a selected poems of his i.e Holy Sonnet X, as regards the theme of death found therein. The researchers adopt an emerging branch of stylistics, called Critical Stylistics, as proposed by Jeffries (2010) in order to uncover the ideologies of the author regarding the topic concerned and how linguistic choices are used to slant ideas. The model is comprised of ten tools of analysis which, upon being applied to the selected data, have shown how the poet exploits language resources in order to pass his ideology and influence his readers. In this paper, the workings of only one tool are presented as applied to a certain portion of the data.

Emotional blackmail is generally defined as manipulating others' emotions for personal gain. It is a type of manipulation that damages healthy relationships among people and turns them into toxic relations leaving the victim in a state of depression and under stress of losing something s/he holds dear. This study aims to identify the pragmatic techniques of emotional blackmail used by both blackmailers and victims in "No One Would Tell" (2018).  To do so, the researchers developed an eclectic model comprising Forward and Frazier's (1997) emotional blackmail, Searle’s speech acts (1979), Brown and Levinson’s politeness strategies (1987), Culpeper’s impoliteness strategies (1996, 2005), and Mayfield's taxonomy of fallacy (2007)

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p