In recent years, English language teaching and second language acquisition has demonstrated a significant accentuation upon basic reasoning abilities improvement in the language capability advancement. Encouraging a point of view of duty to training basic intuition aptitudes in accordance with the English language courses, this paper gives an account of an investigation directed at theoretical meanings of basic deduction, drifts about the centrality of basic speculation for language educating and associations between critical thinking and language learning. The educators have the focal pretended by basic intuition in successful language teaching method, identified to Ennis’ (2011) critical thinking categories. The skill of thinking critic

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Abstract

This research’s goal is to  restore and to revive the jurisprudence of  Mother of Believers (Um alMuaamineen) “Um Salmah” "may God bless her", and to highlight her outstanding assimilation and understanding of religion and her conscious thought.  The current research is a comparative scientific theoretical study  represented in the comparison of  jurisprudence of “Um Salamah” with Hadiths  of  fasting  and pilgrimage rules as well as the duration  mentioned in jurisprudence  of  for doctrines( 4 schools of thought )to identify these hadiths with the inclusion and discussion of their evidence.

The current research included two topics: the first one is to identify and introduce

Abstract

This research attempt to explain the essential aspects of one important model in management of Bank risks , that is (stress testing) , which increase the concentrate on it resulting the negative affects of Global financial crisis that it accuar in 2008 to study the application possibilities in iraqian banks to enhancing the safety and financial soundness Becuase the classical tools  in Risk management don’t give clear image on Banks ability  in facing risks, hence the Basel committee on Banking supervision focusing in agreement of Basel 2,3 on stress testing when it doing the internal capital adequacy assessment process (ICAAP) .

To achieving the reseach obje

Agricultural loans play an important role in the growth and stimulation of agricultural investment opportunities in Iraq, as well as the sustainability and development of existing agricultural projects. The agricultural sector is characterized by the specific conditions of seasonal production and fluctuations in production conditions, which makes the situation of uncertainty more acute in this sector, the need for any agricultural project for financing is urgent and continuous if it wants to continue production and development at all stages. The study proved the impact of agricultural loans in increasing investment and agricultural production at specific times, However, the fluctuation of funding

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip