This study examines the syntactic and semantic functions of the conscience of the chapter and the grammatical disagreement in its diagnosis between two famous linguists: Sibuyh and fur. Also, the conscience of the chapter occupies an important synthetic space in the construction of the Arabic sentence, identified by the Arab scientists, as linguistic analysts, have a strong sense of language and careful observation, they revealed it in their linguistic composition through the analysis of nominal structures, and found that it I come in specific syntactic patterns and grammatical templates that have certain characteristics that are unique to them because of the conscience of separation in their compositional space.

This study examined the imperative construction: the command, the interrogative, the prohibition, the call, and the wish. In the Diwan of Al-Shamakh bin Dirar; where the poetic verses were monitored in each of the topics of the student's creation, and the rhetorical meanings that he came out with. What is new in this study is that it is the first to study the demanded composition in the poetry of a glorious poet, Al-Shammakh bin Dirar Al-Dhubyani. As his poetry did not receive such a study, it sought to employ what was written by rhetoric scholars, in an attempt to explore the demanded composition in the poetry of Al-Shamakh. The study adopted the descriptive analytical approach, which is based on counting the number of times the poet us

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

Abstract

             This paper follows the growing interest and continuity of Islamic finance products worldwide, which has encouraged the formulation of financial institutions based on the concepts of Islamic Sharia in many countries of the world and is no longer limited to Islamic countries only, and  Not exclusive to Muslims which is due to Islamic finance services and their ability to apply in non-Islamic societies, and perhaps what encouraged the development and progress of this industry Islamic history, which was attended by many different models With the development of trade's share between different countries as well as trips carried out by Muslims

The article reflects the results of the analysis of the use of metaphors when creating the image of the main character of the story by D. Rubina "You and me under the peach clouds" - a pet, a dog named Kondraty. Through metaphorization, the image of the dog is filled by the author with purely human qualities, thus passing into the category of a full member of the family. The article is a continuation of the study of the work of D. I. Rubina.

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

Interval methods for verified integration of initial value problems (IVPs) for ODEs have been used for more than 40 years. For many classes of IVPs, these methods have the ability to compute guaranteed error bounds for the flow of an ODE, where traditional methods provide only approximations to a solution. Overestimation, however, is a potential drawback of verified methods. For some problems, the computed error bounds become overly pessimistic, or integration even breaks down. The dependency problem and the wrapping effect are particular sources of overestimations in interval computations. Berz (see [1]) and his co-workers have developed Taylor model methods, which extend interval arithmetic with symbolic computations. The latter is an ef

Includes search unemployment concept ... types, graduate unemployment a model introduction to the researcher tackled the problem of unemployment being dangerous to the community, it's also growing in size year after year is a waste of a clear human capabilities, also addressed the importance of the research being a touch on the problem of unemployment and its concept and try to find solutions to them , and then came the goals set by the search researcher identifies unemployment and their causes and consequences and to provide a true picture of the situation of unemployed graduates and disclosure about how they treat their graduates for jobs provide him with a decent life problem. And adopted a researcher on the use of a questionnaire add

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a