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The morphological and syntactic grammes of the category of temporality: Морфолого-синтаксический состав категории темпоральности в русском языке
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The present paper discusses morphological and syntactic structures of time in Russian language. The morphological and syntactic structures are considered part component of time category in Russian language.

The morphological categories of time are formed through a various types of expressions .Tenses generally express time relative to the moment of speaking. In some contexts, however, their meaning may be relativized to a point in the past ,present or future which is established in the discourse .Some languages have different verb forms or constructions and that are opposed in meaning not in syntactic category. Hence, the present study traces and compares the syntactical and morphological categories of time that connects the sentence with the reality of the actual time.

Аннотация

В статье проанализированы морфологические и синтаксические граммемы категории темпоральности, определен их статус в составе этой категории. Отмечено, что морфологическую категорию времени формирует система формальних средств выражения настоящего, будущего и прошлого времени, особенный статус прошлого времени (давно минувшего) влияет на проблематичность его определения. Акцентировано внимание на том, что глагольные формы времени, противопоставляясь между собой временными значениями, при этом не противопоставляются по синтаксическими свойствам. Прослежена особенность синтаксической категории времени, состоящая в сравнении с морфологической категорией глагольного времени. Прослежено, что в синтаксисе, в структуре его основной единицы – предложении, категория времени одновременно с категориями особы и модальности является средством реализации предикативности, связывая высказывания с действительностью и реальным временем.

 

 

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Publication Date
Tue Dec 31 2019
Journal Name
Arab Science Heritage Journal
جهود جُهُودُ عُلَمَاءِ العِرَاقِ في تَدْوِينِ الف هَ ا رِسِ والكَ ش ا فَاتِ والمَ جَ ل تِ المعْ ن يةِ بال ت راثِ
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Mon Jan 23 2023
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Arab Science Heritage Journal
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Mon Aug 03 2020
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Publication Date
Mon Dec 26 2022
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قيود الختام او حرود المتن دراسة تطبيقية بالاستناد على نماذج مختارة من المخطوطات الاسلامية من القرن(10-13هـ/ 16-19م) في المكتبة المركزية بأربيل:
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Publication Date
Sun Jan 13 2019
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استخلاص عامل التلزن ( اللكتين ) من بكتريا لخلايا Enterococcus faecalis EM1 وتأثير العوامل البيئية المختلفة عليه ودوره في تلزن أنواع من البكتريا السالبة لملون غرام
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Publication Date
Fri Dec 15 2023
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Full Text Book Of Minar Congress10
مستوى الافصاح عن المعلومات المالية المتعلقة بالاستدامة على وفق معيار (IFRS-S1) وتأثير على أداء الشركة - بحث تطبيقي في عينة عن المصارف الاسلامية العراقية
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Tue Dec 05 2023
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An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Wed Dec 28 2022
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