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Proactive Load Balancing Mechanism for Fog Computing Supported by Parked Vehicles in IoV-SDN

China Communications 2021年第2期18卷 271-289页

作者： Ahmed Jawad Kadhim jaber ibrahim naser Ministry of Education General Directorate for Education in Al-QadisiyahAl-Qadisiyah 58002Iraq

Internet of Vehicles(IoV)is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles’sensors through the *** sensors generate different tasks that should be analyzed and processed in some given period of *** send the tasks to the cloud servers but these sending operations increase bandwidth consumption and *** computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing *** some situations,fog computing cannot execute some tasks due to lack of ***,in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation ***,several fog servers may be fuelled while other servers are *** implies an unfair distribution of *** this research study,we shall merge the software defined network(SDN)with IoV and fog computing and use the parked vehicle as assistant fog computing *** can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud *** increases the ratio of time sensitive tasks that meet the *** addition,a new load balancing strategy is *** works proactively to balance the load locally and globally by the local fog managers and SDN controller,*** simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption,meeting the deadline,and resource utilization.

关键词： IoV parked vehicles SDN fog computing load balancing

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An Efficient Method for Heat Recovery Process and Temperature Optimization

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Computers, Materials & Continua 2023年第4期75卷 1017-1031页

作者： Basim Kareem naser Mohammed Dauwed Ahmed Alkhayyat Mustafa Musa jaber Shahad Alyousif Mohammed Hasan Ali Dentistry Department Al-Mustaqbal University CollegeHilla51001Iraq Medical Instrumentation Techniques Engineering Dijlah University CollegeBaghdad00964Iraq College of Technical Engineering The Islamic UniversityNajaf54001Iraq Department of Medical Instruments Engineering Techniques Al-Turath University CollegeBaghdad10021Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi UniversityBaghdad10021Iraq Research Centre University of MashreqBaghdad11001Iraq College of Engineering Department of Electrical&Electronic EngineeringGulf UniversityAlmasnad4363Kingdom of Bahrain Computer Techniques Engineering Department Faculty of Information TechnologyImam Ja’afarAl-Sadiq UniversityNajaf10023Iraq

Flue gas heat loss accounts for a significant component of theoverall heat loss for coal-fired boilers in power plants. The flue gas absorbsmore heat as the exhaust gas temperature rises, which reduces boiler efficiencyand raises coal consumption. Additionally, if the exhaust gas temperatureis too high, a lot of water must be used to cool the flue gas for the wetflue gas desulfurization system to function well, which has an impact onthe power plant’s ability to operate profitably. It is consequently vital totake steps to lower exhaust gas temperatures in order to increase boilerefficiency and decrease the amount of coal and water used. Desulfurizationperformance may be enhanced and water use can be decreased by reasonableflue gas characteristics at the entry. This study analyzed the unit’s energyconsumption, investment, and coal savings while proposing four couplingstrategies for regulating flue gas temperature and waste heat recovery. Agraded flue gas conditioning and waste heat recovery plan was presentedunder the condition of ensuring high desulfurization efficiency, along withthe notion of minimizing energy loss owing to energy inflow temperaturedifference. Numerical results show that the proposed methods improved thesystem performance and reduced the water consumption and regulated theboiler temperature.

关键词： Heat exchange system boiler energy optimization temperature control

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Stacked Gated Recurrent Unit Classifier with CT Images for Liver Cancer Classification

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Computer Systems Science & Engineering 2023年第3期44卷 2309-2322页

作者： Mahmoud Ragab jaber Alyami Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Department of Diagnostic Radiology Faculty of Applied Medical SciencesKing AbdulazizJeddah21589Saudi Arabia Imaging Unit King Fahd Medical Research CentreKing AbdulazizJeddah21589Saudi Arabia

Liver cancer is one of the major diseases with increased mortality in recent years,across the *** detection of liver cancer is a tedious and laborious task due to which Computer Aided Diagnosis(CAD)models have been developed to detect the presence of liver cancer accurately and classify its ***,liver cancer segmentation outcome,using medical images,is employed in the assessment of tumor volume,further treatment plans,and response ***,there is a need exists to develop automated tools for liver cancer detection in a precise *** this motivation,the current study introduces an Intelligent Artificial Intelligence with Equilibrium Optimizer based Liver cancer Classification(IAIEO-LCC)*** proposed IAIEO-LCC technique initially performs Median Filtering(MF)-based pre-processing and data augmentation ***,Kapur’s entropy-based segmentation technique is used to identify the affected regions in ***,VGG-19 based feature extractor and Equilibrium Optimizer(EO)-based hyperparameter tuning processes are also involved to derive the feature *** last,Stacked Gated Recurrent Unit(SGRU)classifier is exploited to detect and classify the liver cancer *** order to demonstrate the superiority of the proposed IAIEO-LCC technique in terms of performance,a wide range of simulations was conducted and the results were inspected under different *** comparison study results infer that the proposed IAIEO-LCC technique achieved an improved accuracy of 98.52%.

关键词： Liver cancer image segmentation artificial intelligence deep learning CT images parameter tuning

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