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Real estate acquisition barrier and its impact on urban development projects" Study Area: Infrastructure project in the capital Baghdad (North East Sewage Line project AL khansaa)
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The increase the rates of natural growth, urbanization and continuous migration, this has generated constant pressure and, as a result, the capital city of Baghdad faces a number of challenges related to its urban environment, including the challenge of acquiring real estate.

 

 and this research examines the impact of these holdings, representing the main base from which the various projects originate Urban in all areas (economic, social, and recreational).

 

this leads us to the research problem of the obstacles that arise during the process of acquiring real estate to carry out development projects, and to achieve the objectives of research, namely (work to create a regulatory methodology (legal- Planning) for the acquisition of real estate, for easy handling and inventory of associated problems and constraints).

 

the city needs to overcome these barriers to help select the best solutions with more sustainable results, Finally, based on the concepts reached in the theoretical framework and the results Analysis of the study area in the chapter of the practical framework.

 

 and in order to benefit from research to solve the research problem, the research came out with a number of conclusions and recommendations.

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date
Sat Dec 01 2012
Journal Name
Advances In Bioresearch
Cytotoxicity of Miltefosine against Leishmania majorPromastigotes
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