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Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was (26.24%), and (5.5%), and AA was (74%), and (94.5%), for cost and time model, respectively. The researcher concluded that the ANN model has a strong correlation and high accuracy, indicating that these models are characterized by high efficiency and good performance in predicting cost and time.

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of educational institutions and regulatory bodies to reduce the financial and administrative corruption
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This research seeks to clarify the regulatory and educational role of the regulatory and educational institutions in reducing the phenomenon of financial and administrative corruption as a dangerous phenomenon of the communities, as it touched search kinds of financial and administrative corruption and the causes and effects, as well as to the role of educational institutions in reducing this phenomenon, and finally between experiments some SAIs and accounting Arab and foreign countries on how to reduce the phenomenon of financial and administrative corruption.The research aims to several targets which shed light on the role of educational and supervisory institutions in reducing corruption, a statement origins and evolution of and justi

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The healthy personality and its relation to the academic achievement of school and university teacher
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Personality regard as one of the human soul pillars that has been built throughout the life of people, starting from the fertilizing process to different stages of people ages. Over time, numerous scientific studies have shown that fetus has the ability to hear and feel and he is being stereotyped since the first stages of formation. Accordingly, the process of forming human personality set up since that date. Besides, the socialization means that take different resources to enhance human personality such as holy Quran, school, social media, and social environment. The emergence of social media made the world as a small village which gives the chance for all people, over the world, to obtain the knowledge easily and limitless. Thus, the

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Publication Date
Thu Sep 29 2022
Journal Name
Al–bahith Al–a'alami
Digital media and linguistic evaluation between the need to stay and the idea of dispensing
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In spite of the contemporary development over the world in pertaining of modernization and its differences about the transformation of the knowledge but, the important instrument to transfer the thoughts and information did not have change except the language. So the evolutionary process became as a torrent or fusillade above the cliff which drifted anything. So that the objective inquiry and impressed with varieties of development the casement to evaluate the linguistic or re - correction highlight article in order to preserve on the origins of the language and its sobriety.
Today, we have different correspondence and social media as

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Publication Date
Sun May 01 2022
Journal Name
Optical Fiber Technology
Optical fiber sensor network integrating SAC-OCDMA and cladding modified optical fiber sensors coated with nanomaterial
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Publication Date
Mon Oct 01 2018
Journal Name
Ieee Transactions On Network Science And Engineering
A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept
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Publication Date
Sun Jul 26 2026
Journal Name
Discover Artificial Intelligence
Multi-classification of autism spectrum disorder behavior for children using explainable artificial intelligence techniques
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Precise and interpretable classification of autism-related behaviors is important for initial diagnosis, personalized intervention, and support arrangements. This study proposes an interpretable machine learning (ML) model using Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) to classify behavioral patterns into four categories (normal, mild, moderate, and severe) associated with Autism Spectrum Disorder (ASD) based on a custom 377-instance survey dataset from Iraqi parents and teachers of children aged 6-12. The model observes 16 key features across communication and social interaction, repetitive behaviors, language, and adaptive skills, preprocessed via interquartile range (IQR) outlier removal, me

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Effects of Artificial Aging on Some Properties of Room-Temperature-Vulcanized Maxillofacial Silicone Elastomer Modified by Yttrium Oxide Nanoparticles
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Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each paramet

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

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Publication Date
Mon Jun 20 2022
Journal Name
Nano Hybrids And Composites
Fabrication and Characterization of Functionalized Multi-Wall Carbon Nanotubes Flexible Network Modified by a Layer of Polypyrrole Conductive Polymer and Metallic Nanoparticles
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Short Multi-Walled Carbon Nanotubes functionalized with OH group (MWCNTs-OH) were used to synthesize flexible MWCNTs networks. The MWCNTs suspension was synthesized using Benzoquinone (BQ) and N, N Dimethylformamide alcohol (DMF) in specific values and then deposited on filter paper by filtration from suspension (FFS) method. Polypyrrole (PPy) conductive polymer doped with metallic nanoparticles (MNPs) prepared using in-situ chemical polymerization method. To improve the properties of the MWCNTs networks, a coating layer of (PPy) conductive polymer, PPy:Ag nanoparticles, and PPy: Cu nanoparticles were applied to the network. The fabricated networks were characterized using an X-ray diffractometer (XRD), UV-Vis. spectrometer, and Ato

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Publication Date
Tue Jun 04 2024
Journal Name
International Journal Of Operational Research
Pascal's triangle graded mean defuzzification approach for solving fuzzy assignment models by using pentagonal fuzzy numbers
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The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo

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