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Heuristic and Meta-Heuristic Optimization Models for Task Scheduling in Cloud-Fog Systems: A Review
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Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In this article, a summary of heuristic and meta-heuristic methods for solving the task scheduling optimization in cloud-fog systems is presented. The cost and time aware scheduling methods for both bag of tasks and workflow tasks are reviewed, discussed, and analyzed thoroughly to provide a clear vision for the readers in order to select the proper methods which fulfill their needs.

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Publication Date
Thu Jan 08 2026
Journal Name
Journal Of Baghdad College Of Dentistry
A Comparative Evaluation of the Centering Ability and Canal Transportation of Simulated S-Shaped Canals Instrumented with Different Nickel –Titanium Rotary Systems
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Background: The purpose of this study was to evaluate and compare centering ability and canal transportation of simulated S-shaped canals instrumented with four different types of rotary nickel-titanium systems. Materials and Methods: Forty simulated S-shaped canals in resin blocks were divided into four groups of ten each and were instrumented to an apical size 25 by different instrumentation technique using ProTaper Universal files (group A), ProTaperNext (group B), Reciproc (group C) and WaveOne (group D).Centering ability and canal transportation was measured at (11) measuring points from D0 to D10 bysuperimposion of the pre- and post-operative images obtained by using digital camera in standardized manner. An assessment of the canals

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Publication Date
Sat Sep 01 2012
Journal Name
Journal Of Irrigation And Drainage Engineering
Hydraulic and Statistical Analyses of Design Emission Uniformity of Trickle Irrigation Systems
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Sat Dec 21 2024
Journal Name
Edelweiss Applied Science And Technology
Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

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Publication Date
Tue Jan 12 2016
Journal Name
Spectral Physics Communications
Photobleaching Analysis of Binary Lasing Compound Systems
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Publication Date
Fri Jan 01 2016
Journal Name
Bulletin Of Mathematics And Statistics Research
New Approximation Operators Using Mixed Degree Systems
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This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra

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Publication Date
Fri Jun 02 2023
Journal Name
Alustath Journal For Human And Social Sciences
Review Study in Discourse Analysis and Appraisal Theory in Selected Prison Letters by Antonio Gramsci and other Scholars.
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Sun Mar 12 2017
Journal Name
Al-academy
The reality of interior design of Sharjah mosques and the possibility of development - selected models
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Observed mosques with the advent of Islam under the auspices of care being the houses of God Almighty, and I like parts of the ground to him, the center of radiation spiritual, intellectual and ideological in the lives of Muslims, was the most important cultural and architectural evidence built by Muslims voicing their deep faith and serenity Aqidthm.valmsadjad better reflecting the reality of communication between the person and his Lord, because he is the most important building of permanence and survival, making it imperative designed the best visual forms both externally and internally.Mosques have been characterized in the United Arab Emirates distinct characteristics in terms of building elements of construction in general, and the

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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