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Volume 12, Issue 2 (June & July 2021 (Articles in Persian) 2021)
Abstract

The antiquity of stylistic studies in Iran is seriously owed as an independent field due to the persistent and research efforts of the Malek osh-Sho'arā Bahar. By studying the research literature, we find that Bahar's Stylistics has not been properly studied and his theoretical stylistic approach has not been discovered and extracted yet. Therefore, the aim of the authors was to acquire the theory or theoretical approach of Bahar, and discover and recognize the variables and components of the stylistic theory of him, categorization, hypothesized, and presenting a model based on it by the method and technique of qualitative-deep content analysis. According to the purpose, the works of the Malek osh-Sho'arā Bahar in the field of stylistics were studied based on purposeful sampling and theoretical saturation criteria. From the content of these works by deleting , adding,  modifying, and summarizing, 409 basic codes were obtained. Finally, during the three coding steps, a model of code was extracted that represents the two blocks "texture and context", and "stylistics"; It also shows the main hypothesis of how “texture and context" affect "style". The findings of this study showed that according to Bahar's view, "texture and context" has a significant impact on "style" and "stylistics", that this connection and influence has been neglected. Finally, the variables and concepts of his approach, as well as the relationships of these variables with each other are discovered and eventually lead to modeling, and reinforcing the assumption that he was a connoisseur in this field.
 
  1.  Introduction
Contemporary Iranian literature and research should be a logical and rational continuation of our literary, cultural, and philosophical traditions. Therefore, it is necessary to recognize and study the theories, theoretical approaches, and insights into the great and pioneers of literary research in various fields. Therefore, the aim of the authors about style was to acquire the theory or theoretical approach of Malek osh-Sho'arā Bahar, the prominent feature of modern Iranian stylistics. The antiquity of stylistic studies in Iran is seriously owed as an independent field due to the persistent and research efforts of the Malek osh-Sho'arā Bahar. Of course, in the biographies, texts of the past, and the poetry of the poets, we encounter synonymous and parallel words of "style", but this literature does not fully present the features and concepts hidden in the word "style". By studying the research literature, we find that Malek osh-Sho'arā Bahar's Stylistics has not been properly studied and his theoretical stylistic approach has not been discovered and extracted yet.
Objective
 The aim of this study is to discover and recognize the variables and components of the stylistic theory of the Malek osh-Sho'arā Bahar in order to categorize, hypothesize, and present a model based on it. This study also proposes the method of qualitative content analysis in literary studies, especially stylistic studies, in order to better understand the views, background of thought, as well as the methodology of Persian language and literature.
Research Question(s)
  • Is it possible to achieve his theoretical approach to style by analyzing the qualitative content of his works?
  • Is it possible to find a model that supports theories of style in Persian to compensates for the theoretical deficit and poverty of the research in this field?
  • Can the result of this research and related researches lead to a new method by scientific and research solution in literature?
 
  1.  Literature Review
Research in the field of stylistics of Malek osh-Sho'arā Bahar is either mixed with other literary techniques such as literary criticism, rhetoric and the history of literature or they do not match the standards of today's research. These studies have not yet introduced, defined and analyzed Bahar's theoretical approach to stylistics, and they have only referred to the whole book of Stylistics or without using a qualitative or even quantitative method, they have talked about only a few stylistic components. In this respect , it should refer to the article entitled "Style Theory in Iran" (2011) that only a limited part of it, is partially related to the subject of the present study. In this article, the author has tried to explain and critique the concept of style from the point of view of Iranian stylists. This brief analysis shows that the author has not made a qualitative or even quantitative analysis of Bahar's works on stylistics. Therefore, it cannot be expected that this article will fully express Bahar's theoretical approach to style. Other studies have not been written exactly in this field with the method of qualitative content analysis, and what has been written has not been done by the method of qualitative content analysis; articles such as “Stylistic of Maghamat-e Hamedani & Hariri Based on Buziman's Statistical Stylistics”(2015) and “Statistical Stylistics Mechanisms in Evaluation of Style”(2018) have used quantitative, descriptive and statistical methods for stylistics of texts, which is not the subject of discussion and opinion of this paper.
  1.  Methodology
After studying and reflecting on the methodological issues of language and literature, the authors came to the conclusion that description and counting frequency do not lead to accurate results, rather, one should seek help from the text itself to obtain categories and components of macro-concepts, including "style" and "stylistic approach". For this reason, the method and technique of qualitative-deep content analysis were chosen, which has not been used in text analysis, especially literary research. For this purpose, MAXQDA and SPSS content analysis software were used.
 
  1.  Conclusion
According to the purpose and method of research, the works of the Malek osh-Sho'arā Bahar in the field of stylistics were studied based on purposeful sampling and theoretical saturation criteria. 409 basic codes were obtained from the content of these works, by deletion, addition, modification, and summarization. Finally, during the three coding steps, a model of code was extracted that represents the two blocks "texture and context", and "stylistics"; It also shows the main hypothesis of how “texture and context" affect "style". The findings of this study showed that according to Bahar's view, "texture and context" has a significant impact on "style" and "stylistics" in Iran, that this connection and influence has been neglected or not explained logically and accurately in stylistic research so far. Finally, the variables and concepts of the theoretical stylistic approach of the Malek osh-Sho'arā Bahar, as well as the relationships of these variables with each other are discovered and eventually lead to modeling, and reinforcing the assumption that he was an expert in this field.

Volume 23, Issue 2 (5-2023)
Abstract

Core testing is the most direct method to assess the in-situ concrete compressive strength in an existing structure, generally related to suspected construction malpractice or deficiency of concrete supply, to carry out the condition assessment of buildings before taking up repair and upgrading work. Although this test is quite simple to conduct, the results obtained may sometimes contain considerable errors because of the great variety of parameters involved. The general problems of core testing are well known. The factors including core diameter, length-to-diameter ratio (L/D), concrete age, aggregate characteristics, direction of coring and the moisture condition at the time of testing are known which affect the relationship between core strength and the corresponding standard cube or cylinder strength are fully reported by researchers. Another potential factor influencing the testing of cores is the presence of reinforcing bars within the core. The effects of the presence of steel bars on the strength of cores have been investigated by only a few researchers. Reinforcement bars passing through a core will increase the uncertainty of results and should be avoided wherever possible. Regression analysis and generalized GMDH network, whose structure is investigated using genetic algorithm and single-particle number optimization method for predicting the compressive strength of concrete using the results of coring tests with and without fittings. The form and ability of the multivariate linear regression models and the importance of regression coefficients based on the experimental data obtained for samples in two different processing conditions, in order to predict the cubic compressive strength of the concrete and using the input parameters including (1) the length to diameter ratio Core, (2) core diameter, (3) diameter, (4) number and (5) axial axial axis of the rebar in the core, (6) reinforcement of the rebar, and (7) core compressive strength as independent and input variables, as well as resistance Concrete pressure is evaluated as the response variable (or output of the models). This method is used for the GMDH neural network. The objective of the GMDH neural network method is to obtain a polynomial function that can be used to retrieve the output parameter by the input of the considered variables. The GMDH neural network can, after training, estimate the relationship between inputs and outputs in a polynomial, which depends on the accuracy of this polynomial on the data and structure of the network. The single-particle decomposition (SVD) method in the GMDH structure for the case where the number of equations is greater than that of unknowns, uses the least squares error method to solve such devices. The results showed that the models used have high ability to express the problem, since more than 95% of variations of response variables with fitted models in regression models and about 99% of changes in the response variable values ​​in the GMDH model can be expressed. But in a comparative position, GMDH model with a general structure optimized with Genetic Algorithm and SVD has shown the best performance, with this superiority becoming noticeable, considering that about 75% of the data is involved in training the neural model. Subsequently, nonlinear regression models show a certain advantage over linear models.
 

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