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Assessment of diametral tensile strength and microhardness of Glass ionomer reinforced by different amounts of Hydroxyapatite
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Back ground: Glass ionomer materials lack resistance to wear and pressure and are susceptible to moisture during the initial stages of setting and dehydration. So this study was done to assess diametral tensile strength and microhardness of glass ionomer reinforced by different amounts of hydroxyapatite. Materials and methods: In this study a hydroxyapatite material was added to glass monomer cement at different ratios: 10%, 15%, 20%, 25% and 30% (by weight). The diametral tensile strength test described by the British standard specification for zinc polycarboxylate cement was used in this study and the microhardness test was performed using Vickers microhardness testing machine and the microhardness values were calculated and statistical comparison was performed on the tested groups. Results: The group of glass ionomer cement that contains 20% hydroxyapatite has higher diametral tensile strength and microhardness values than other groups of this study. Also the results showed that the group of glass ionomer cement without hydroxyapatite has the lowest values of diametral tensile strength and microhardness than other groups. The groups of glass ionomer cement with 10%, 15%, 25% and 30% hydroxyapatites also showed increasing in diametral tensile strength and microhardness values in comparison with group of glass ionomer cement without hydroxyapatite. Conclusion: The addition of hydroxyapatite to conventional glass ionomer cement will increase its diametral tensile strength and microhardness

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Mon Nov 06 2023
Journal Name
Eneurologicalsci
Dandy-Walker syndrome associated with a giant occipital meningocele: A case report and a literature review
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HTH Ahmed Dheyaa Al-Obaidi,", Ali Tarik Abdulwahid', Mustafa Najah Al-Obaidi", Abeer Mundher Ali', eNeurologicalSci, 2023

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Groundwater situation before production and after production stoppage in Al-Mishraq Sulfur field-1, northern Iraq
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This study dealt with the reality of groundwater before Sulfur production in the Al-Mishraq field-1 and after production stopped in the field, by measuring the groundwater table for (44) wells in 2021, and comparing it to the groundwater table measured by the Polish company Centrozap in 1971, the groundwater table was a range between (187.71-205.8)m in 1971, but in 2021 it ranged was between (188.51-196.55)m.
Maps of the groundwater movement and water table were created using these data. It turned out that there was little change in the direction of groundwater flow; in both cases, the flow is from the west and northwest towards the east with a slight slope toward the southeast and the Tigris River. As for hydraulic properties, it w

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Thu Mar 16 2023
Journal Name
Wireless Personal Communications
Technology Applications in Tracking 2019-nCoV and Defeating Future Outbreaks: Iraqi Healthcare Industry in IoT Remote
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Publication Date
Wed Apr 01 2020
Journal Name
Medico-legal Update
Knowledge and protective health behaviors concerning risk factors for coronary heart disease among baghdad university students
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Publication Date
Fri Aug 25 2023
Journal Name
Plos One
Organizational and behavioral attributes’ roles in adopting cloud services: An empirical study in the healthcare industry
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The need for cloud services has been raised globally to provide a platform for healthcare providers to efficiently manage their citizens’ health records and thus provide treatment remotely. In Iraq, the healthcare records of public hospitals are increasing progressively with poor digital management. While recent works indicate cloud computing as a platform for all sectors globally, a lack of empirical evidence demands a comprehensive investigation to identify the significant factors that influence the utilization of cloud health computing. Here we provide a cost-effective, modular, and computationally efficient model of utilizing cloud computing based on the organization theory and the theory of reasoned action perspectives. A tot

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
The Fear Effect on a Food Chain Prey-Predator Model Incorporating a Prey Refuge and Harvesting
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Abstract<p>In this paper, we investigate the impact of fear on a food chain mathematical model with prey refuge and harvesting. The prey species reproduces by to the law of logistic growth. The model is adapted from version of the Holling type-II prey-first predator and Lotka-Volterra for first predator-second predator model. The conditions, have been examined that assurance the existence of equilibrium points. Uniqueness and boundedness of the solution of the system have been achieve. The local and global dynamical behaviors are discussed and analyzed. In the end, numerical simulations are confirmed the theoretical results that obtained and to display the effectiveness of varying each parameter</p> ... Show More
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Publication Date
Thu Jun 01 2017
Journal Name
Nuclear Physics A
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd–odd heavy nuclei
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