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A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli-Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.

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Publication Date
Thu Dec 23 2021
Journal Name
Iraqi Journal Of Science
Noise Reduction, Enhancement and Classification for Sonar Images
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    Ultrasound imaging has some problems with image properties output. These affects the specialist decision. Ultrasound noise type is the speckle noise which has a grainy pattern depending on the signal. There are two parts of this study. The first part is the enhancing of images with adaptive Weiner, Lee, Gamma and Frost filters with 3x3, 5x5, and 7x7 sliding windows. The evaluated process was achieved using signal to noise ratio (SNR), peak signal to noise ratio (PSNR), mean square error (MSE), and maximum difference (MD) criteria. The second part consists of simulating noise in a standard image (Lina image) by adding different percentage of speckle noise from 0.01 to 0.06. The supervised classification based minimum di

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Telecommunication, Electronic And Computer Engineering
The critical success factors (CSFs) for IT projects
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Huge yearly investments were made by organizations for the development and maintenance. However, it has been reported that most of the IT projects fails as it is delayed, over budget and discontinued quality. A systematic literature review (SLR) was conducted to identify the critical success factors (CSFs) for the IT projects. Nine (9) CSFs was identified from the SLR. An online survey was conducted among 103 respondents from developers and IT managers. The data was analyzed using the Statistical Package for Social Science (SPSS 22). The findings showed that the highest CSFs of IT projects is commitment and motivation. Project monitoring was found the lowest score ranked by respondents.

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
Enhanced Supervised Principal Component Analysis for Cancer Classification
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In this paper, a new hybridization of supervised principal component analysis (SPCA) and stochastic gradient descent techniques is proposed, and called as SGD-SPCA, for real large datasets that have a small number of samples in high dimensional space. SGD-SPCA is proposed to become an important tool that can be used to diagnose and treat cancer accurately. When we have large datasets that require many parameters, SGD-SPCA is an excellent method, and it can easily update the parameters when a new observation shows up. Two cancer datasets are used, the first is for Leukemia and the second is for small round blue cell tumors. Also, simulation datasets are used to compare principal component analysis (PCA), SPCA, and SGD-SPCA. The results sh

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Publication Date
Fri Apr 01 2022
Journal Name
Symmetry
Fast Overlapping Block Processing Algorithm for Feature Extraction
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In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Theoretical Study of Thermal Cracking For Acenaphthylene Molecule
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Density Functional Theory (DFT) calculations were carried out to study the thermal cracking for acenaphthylene molecule to estimate the bond energies for breaking C8b-C5a , C5a-C5 , C5-C4 , and C5-H5 bonds as well as the activation energies. It was found that for C8b-C5a , C5-C4 , and C5-H5 reactions it is often possible to identify one pathway for bond breakage through the singlet or triplet states. The atomic charges , dipole moment and nuclear – nuclear repulsion energy supported the breakage bond .Also, it was found that the activation energy value for C5-H5 bond breakage is lower than that required for C8b-C5a , C5a-C5 , C5-C4 bonds which refer to C5-H5 bond in acenaphthylene molecule are weaker than C8b-C5a , C5a-C5 , C5-C

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Profiles and Geotechnical Properties for some Basra Soils
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 Abstract

Basra province is known for its logistic location for trading activity and oil industry. By geological point of view, Basra areas are believed to consist mainly of alternation of (clay, silty clay, clayey silt, silt and sand) type of soil. Any development of industry in this area should be affected by the occurrence of the clay soil. That is why the investigation to the soil is more than necessary. In this case, a vast testing program was carried out by the author to evaluate the various formations constituting the of some Basra soils. An attempt to characterize and discuss the nature, minerals, engineering behavior and field properties of soil samples extracted from more than one thousand and one

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Publication Date
Thu May 25 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Modulation Function Calculation For Optical Semiconductor Fractal Modulator
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   The research  includes the study and calculation of the modulation function of Optical Semiconductor Fractal  Modulator and spatial frequency for different values of Silicon modulator transmittance percentage(10%,35%,45%,58%),it found the relation between the modulation function of Silicon and spatial frequency, the exponential relation of all values of the transmittance , the best state of modulation function when the value of transmittance is T=58% ,also the research includes the study of the relation of transmittance with different values of refractive index of Silicon . So the research involves building a computer program of output data which would relate to fractal optical modulation made of semiconductor mate

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
System Identification Algorithm for Systems with Interval Coefficients
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In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Review on Hybrid Swarm Algorithms for Feature Selection
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    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedu

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