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Intellectual and Religious Characteristics Andalusion Societ Image Beni Al-Ahmar Era Poetry as a model
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The intellectual and religious characteristics were an influential presence in the same Andalusian poet, especially among the poets of Beni El-Ahmar because they are part of the heritage of poets, and that is to push them towards the glory of this heritage and to take care of it and benefit from its inclusion, inspiration and similarity.

That this inflection on the poetic heritage is justified by the poets of the sons of the Red were inclined to preserve the inherited values, especially as it was related to their poetry, especially that the Andalusian poet did not find embarrassment in the inspiration of heritage and emerged when he mentioned the homes and the ruins and the camel and the journey, although the community Andalusian society is also urban and the religious aspect has a strong correlation in the language of the Koran, which made the Andalusian poet revolves in the orbit of holiness because of his religious culture has led stories and stories played a prominent role in lighting the text of poetry and clarify to the recipient, was a quote from the Quranic texts, Many all that took place in and around the text based on those images portrayed by the poet and he drew from the cultural and religious covenantal. With reference recently to the sources and references that included everything related to the research and its course.

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. 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

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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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 acc

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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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

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Publication Date
Tue Apr 01 2025
Journal Name
Journal Of Economics And Administrative Sciences
Spatial Quantile Autoregressive Model: A Review
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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

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Mathematical Model for BOD in Waste Water Discharges from Al Dora Refinery in Baghdad
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This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there
is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Mathematical Model for BOD in Waste Water Discharges from Al Dora Refinery in Baghdad
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This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The Relationship between Religious Beliefs and Job Burnout among Nurses Working in Hospitals in Gonabad City in 2017
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Introduction and Aims: Job burnout such as occupational hazards that have been considered in recent years. This research aimed to investigate the relationship between religious beliefs and job burnout among nurses working in hospitals in Gonabad city in 2017. Materials and Methods: This study is cross-sectional and correlational study. The sample consisted of 100 nurses in Gonabad city who were selected using stratified randomized method. Using the Maslach job burnout and Alport religious beliefs Inventories, data were collected and were analyzed with SPSS version 16 and Pearson, Spearman and independent sample T tests were analyzed. Significant level was considered less than 0.05. Results: Average job burnout in nurses working in hospit

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Publication Date
Wed Jan 01 2020
Journal Name
Indian Journal Of Forensic Medicine And Toxicology
Color stability of different aesthetic resin composite materials: A digital image analysis
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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Gray-Scale Image Compression Method Based on a Pixel-Based Adaptive Technique
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     Today in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,

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