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Social Media and Academic Excellence
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The current research seeks to shed light on the role that social media can play, through the optimal use of it by students, in achieving academic excellence. The most prominent aims that constitute it are:Identifying the social sites most used by students; learning how students interact with the published study material on communication sites and benefit from them to achieve their academic excellence; and knowing the connection between using social media and achieving academic excellence, and the role that these sites play in achieving academic excellence.That incorrect use by students leads to adverse results, and thus affects their academic level. Failure of parents to monitor their student’ use of social media leads to the lack of benefit from them in achieving academic excellence. This means the lack of procetures for monitoring these networks makes them more harmful for Students. Moreover, the excessive use of social media by students has a negative impact on the student’s performance of his homework. It has negative effects on his health as well. In light of the results reached, the researchers presented a set of   recommendations, including:Parents should ensure that their children use social media as a tool to improve their children's educational level. Students should better manage their study time and prevent distortions that social media can provide. Students must strike a balance between using the means of communication and their study duties in a way that does not affect their studies. Students, during their use of social media, focus on the scientific importance of these sites instead of using them entertainment.                                                                          

 

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Mon Jul 01 2024
Journal Name
Civil Engineering Journal
The Effect of Oil Contaminated on Collapse Pattern in Gypseous Soil Using Particle Image Velocimetry and Simulation
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Gypseous soil covers approximately 30% of Iraqi lands and is widely used in geotechnical and construction engineering as it is. The demand for residential complexes has increased, so one of the significant challenges in studying gypsum soil due to its unique behavior is understanding its interaction with foundations, such as strip and square footing. This is because there is a lack of experiments that provide total displacement diagrams or failure envelopes, which are well-considered for non-problematic soil. The aim is to address a comprehensive understanding of the micromechanical properties of dry, saturated, and treated gypseous sandy soils and to analyze the interaction of strip base with this type of soil using particle image

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Publication Date
Mon Apr 03 2023
Journal Name
Polymer Composites
Effect of silver nanoparticles on structural, thermal, electrical, and mechanical properties of poly(vinyl alcohol) polymer nanocomposites
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Publication Date
Wed May 01 2019
Journal Name
Environmental Technology & Innovation
Biomineralization based remediation of cadmium and nickel contaminated wastewater by ureolytic bacteria isolated from barn horses soil
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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Fri May 28 2021
Journal Name
Journal Of Microbiology And Biotechnology
Bioactive Levan-Type Exopolysaccharide Produced by <i>Pantoea agglomerans</i> ZMR7: Characterization and Optimization for Enhanced Production
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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Ovonic Research
Effect of copper on physical properties of CdO thin films and n-CdO: Cu / p-Si heterojunction
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Publication Date
Mon Sep 11 2023
Journal Name
Applied Water Science
Hydrochemistry and water quality of shallow groundwater in the Tikrit area of Salah Al Din Province, Iraq
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Abstract<p>Salah Al-Din Provence is an active agriculture and population region. One of its primary water sources is groundwater, which suffers from a lack of information regarding water quality and hydrochemistry. In order to study those missing variables, 27 samples from wells of shallow tubes were collected for analyzing the relevant physicochemical indices that help to produce the Schoeller index, Piper diagram, and Gibbs plot. Piper diagram revealed a hydrochemistry behavior of different values along with the groundwater samples. The chemistry of wells was controlled primarily by the evaporation process according to the Gibbs plot. The values of the Schoeller index of the studied samples stated that 59% of</p> ... Show More
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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Thu Feb 01 2024
Journal Name
Russian Journal Of Bioorganic Chemistry
Synthesis, Identification, Antioxidant, Molecular Docking, and In Silico ADME Study for Some New Derivatives Containing Thiourea Moiety
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Objective: Synthesized a series of new thiourea (TU) derivatives, tested their antioxidant activity, and investigated their expected biological activity by theoretical study (computational methods). Methods: The derivatives were made using a one-pot reaction with two steps. Initially, succinyl chloride was mixed with KSCN to make succinyl isothiocyanate. Then, primary and secondary amines were used to make TU derivatives. The theoretical studies were done by Swiss ADME and molecular docking via Genetic Optimization of Linkage Docking (GOLD). Then evaluate antioxidant activity using the DPPH scavenging method. Results: FT-IR, 1H NMR, and 13C NMR spectroscopy show the verification of all the prepared derivatives. Compounds (II), (VIII),

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