Summary:This article discusses the topic of phraseological units with the names of wild animals in the Russian and Arabic languages in the aspect of their comparative semantic and cultural analysis, since a comparative analysis of the meanings of phraseological units of the Arabic and Russian languages, detection of coincidences and differences in the compared languages, is an important method for studying linguoculturology, since phraseological units represent a reflection of culture in the language

Language is an instrument, a tool of culture and a way of communication between the past and the present. No one can know the treasure of human thought and experience in the fields of history, poetry and prose without language as an instrument of communication between cultures and peoples. Language under this description faces many problems, the most important of which is linguistic globalization, which means the flow rate of the strongest language, which has elements of power, domination and control over other languages. In this article, we consider linguistic globalization as a serious problem faced by every language, and we consider its main shortcomings and advantages and its impact on the language and ways of protecting the Arabic lang

With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored

The goal of the study is to identify the components of sustainable development—economic, social, and cultural—as recommended by the United Nations Educational, Scientific, and Cultural Organization and how they apply to the foreign language instruction process at Iraqi universities. The development of sustainable development principles is considered while evaluating the importance of two fundamental components of high-quality education: the learning environment and the curriculum. The research employs a qualitative design and uses an observational instrument with a sample of fifty students at second-year English department/college of education (Ibn-Rushd) at Baghdad University. The survey's findings, which sought to learn how st

The reality of teaching the Arabic language rules is not satisfactory, as the pedagogical methods used do not help students develop their mental skills, especially critical thinking skills. They are often traditional in terms of teaching students, who are passive, passive, often passive, active, and often active, their listening task, and the teacher's task of narrating facts and judgments. It is a blind simulation student, a dependency on others, and a weak spirit of creativity, innovation, and opinion. The opinions of educators and teachers almost agree on the reasons for students' weakness in learning the rules of Arabic, and that the reason lies in the way of teaching. The difficulty or the ease of the rules of Arabic does not lie in th

Arabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T