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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
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Calculations of Signal to Noise Ratio (SNR) for Free Space Optical Communication Systems
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In this paper, we calculate and measure the SNR theoretically and experimental for digital full duplex optical communication systems for different ranges in free space, the system consists of transmitter and receiver in each side. The semiconductor laser (pointer) was used as a carrier wave in free space with the specification is 5mW power and 650nm wavelength. The type of optical detector was used a PIN with area 1mm2 and responsively 0.4A/W for this wavelength. The results show a high quality optical communication system for different range from (300-1300)m with different bit rat (60-140)kbit/sec is achieved with best values of the signal to noise ratio (SNR).

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Publication Date
Mon Sep 04 2023
Journal Name
2023 International Conference On Advanced Mechatronic Systems (icamechs)
Performance Analysis of Finite-Time Generalized Proportional Integral Observer for Uncertain Brunovsky Systems
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This paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
The efficiency calibration for local manufacturing gamma scanning systems of radioactive waste drums
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The Local manufacturing scanning gamma system designed in Tuwaitha site for nondestructive assay method of radioactive waste drums, where it consist of two main parts with their belongings for controlling the of detector and drum movements up-down and rotation respectively. The volume of the used drum is 220 L with 85 cm height. The drum filled with Portland cement. Six cylindrical holes were made within cement drum and distributed in radial arrangement.The152Eu source inserted in these holes individually, to measure the average angular count rate of gamma radiation. The full energy efficiency value for geometry of drum and detector is computed for thirteen photo peaks. The average efficiency represented by the curve of these peaks indic

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Robust Optimization with practical application
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The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values ​​of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend buil

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Biofilm formation rate measurement in water and biomedical systems using photometric smartphones applications
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Publication Date
Sun Dec 02 2018
Journal Name
Journal Of The College Of Education For Women
The role of environmental governance in maintaining environmental systems and achieving urban sustainability
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The solution to the problems and challenges of the twenty-first century requires the absorption of many transformations, such as demographic change, poverty reduction, the expansion of safe and clean energy without affecting the environment, as well as reducing health risks and other transitions. It also requires greater cooperation than is possible in the current global system, because both of these constraints and challenges, even if addressed locally or nationally, are because of the potential for their transnational impact, that is, their impact on the lives of people at the global level, Which is necessary to be fully addressed unless it is guided by a comprehensive global vision. This is what environmental governance provides in te

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Publication Date
Wed Dec 27 2023
Journal Name
Journal Of Planner And Development
Beyond Individual Ownership: Women's and Men's Land Tenure Rights in Iraqi Heritage Systems
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This paper delves into the significant role played by local social and traditional structures in shaping Traditional Community Tenure (TCT) within Iraqi Land Tenure Legislation (ILTR), and examines their impact on gender inequalities, with a specific focus on women's land tenure rights. The methodological approach employed in this study identified the sources of barriers to gender equality within TCT as outlined in ILTR at two different bilateral levels, with input obtained from key stakeholders in a selected city in Iraq. The case study survey encompassed three districts, which served as local layers within the historic sectors of the Iraqi city of Al-Nasiriya. the study employed quantitative methods, including a household surveyو with

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inv

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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