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.
Nonlinear regression models are important tools for solving optimization problems. As traditional techniques would fail to reach satisfactory solutions for the parameter estimation problem. Hence, in this paper, the BAT algorithm to estimate the parameters of Nonlinear Regression models is used . The simulation study is considered to investigate the performance of the proposed algorithm with the maximum likelihood (MLE) and Least square (LS) methods. The results show that the Bat algorithm provides accurate estimation and it is satisfactory for the parameter estimation of the nonlinear regression models than MLE and LS methods depend on Mean Square error.
The Internet of Things (IoT) is a network of devices used for interconnection and data transfer. There is a dramatic increase in IoT attacks due to the lack of security mechanisms. The security mechanisms can be enhanced through the analysis and classification of these attacks. The multi-class classification of IoT botnet attacks (IBA) applied here uses a high-dimensional data set. The high-dimensional data set is a challenge in the classification process due to the requirements of a high number of computational resources. Dimensionality reduction (DR) discards irrelevant information while retaining the imperative bits from this high-dimensional data set. The DR technique proposed here is a classifier-based fe
... Show MoreSemantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s
... Show MoreThe aim of this paper is to measure the characteristics properties of 3 m radio telescope that installed inside Baghdad University campus. The measurements of this study cover some of the fundamental parameters at 1.42 GHz. These parameters concentrated principally on, the system noise temperature, signal to noise ratio and sensitivity, half power beam width, aperture efficiency, and effective area. These parameters are estimated via different radio sources observation like Cas-A, full moon, sky background, and solar drift scan observations. From the results of these observations, these parameters are found to be approximately 64 K, 1.2, 0.9 Jansky, 3.7°, 0.54, and 3.8 m2 respectively. The parameters values have vital affect to quantitativ
... Show MoreIn this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
The purpose of this project is to build a scientific base and computational programs in an accelerator design work. The transfer of group of laws in alinear accelerator cavity to computer codes written in Fortran power station language is inorder to get a numerical calculation of an electromagnetic field generated in the cavities of the linear accelerator. The program in put contains mainly the following, the geometrical cavity constant, and the triangular finite element method high – order polynomial. The out put contains vertical and horizontal components of the electrical field together with the electrical and the magnetic field intensity.
In this paper the effects of the contact material on the photovoltaic (PV) characteristics of p-NiO:Au/n-Si solar cells fabricated by using the pulsed laser deposition (PLD) technique had been studied. It shown the p-NiO:Au/n-Si could be successfully used to construct and improve the performance of solar cells by using Au. The conversion efficiency was increased comparable with p-NiO/n-Si solar cells. In this case the NiO:Au layer acts as a hole collector as well as a barrier for charge recombination.
Coaxial (wire-cylinder) electrodes arrangements are widely used for electrostatic deposition of dust particles in flue gases, when a high voltage is applied to electrodes immersed in air and provide a strongly non-uniform electric field. The efficiency of electrostatic filters mainly depends on the value of the applied voltage and the distribution of the electric field. In this work, a two-dimensional computer simulation was constructed to study the effect of different applied voltages (20, 22, 25, 26, 28, 30 kV) on the inner electrode and their effect on the efficiency of the electrostatic precipitator. Finite Element Method (FEM) and COMSOL Multiphysics software were used to simulate the cross section of a wire cylinder. The results sh
... Show MoreThe development of a meaningful dissolution procedure for drug products with limited water solubility has been a challenge to both the pharmaceutical industry and the agencies that regulate them. Natural surfactants aid in the dissolution and subsequent absorption of drugs with limited aqueous solubility. In vitro, various techniques have been used to achieve adequate dissolution of the sparingly water – soluble or water insoluble drug products such as the use of mechanical methods (i.e., increased agitation and the disintegration method) or hydro alcoholic medium or large volumes of medium. The necessity of assuring the quality of drugs , especially those with low aqueous solubility and in vivo absorption , has led to the development and
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