This study is marked by: The ignorant poem and body language
Its main objective is to reveal the manifestations of this language in the text mentioned, and accordingly, the sieve poem has been read semantic (semantic) and hermeneutic, revealing the poet's ability to employ symbols and signals (body language) in the poem chosen for this purpose; The existence of such language in pre-Islamic poetry. After a long reflection and reading, the signs and symbols of the physical movement of the body, and its feminine and aesthetic manifestations were identified, and this was achieved through the use of modern critical methodologies that directly affect this language. The study consisted of an introduction and three topics, followed by the conclusion of the most important results, and then a list of sources and references.
The most important results were as follows:
• This poem, and the like, is a non-rejection of contemporary theories of criticism, and this is proved by this study, the text ignorant text is committed to the technical and aesthetic standards required by human texts.
• In the poem there is a clear synergy between non-linguistic and linguistic signs, such as facial expressions, hand movements, head, tones, exhales, and dress. These ensuing bodily movements produced a series of symbols and connotations.
Reading the body language in the poem was based on some functional analysis of the members. Finally, the study recommends the need to intensify modern monetary efforts directed towards the ignorant text, because it is a text carrying a flood of signals that contribute to the reproduction of this text
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This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f
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