Cloud computing is currently dominated within the space of highperformance distributed computing and it provides resource polling and ondemand services through the ***,task scheduling problem becomes a very important ...
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Cloud computing is currently dominated within the space of highperformance distributed computing and it provides resource polling and ondemand services through the ***,task scheduling problem becomes a very important analysis space within the field of a cloud computing environment as a result of user’s services demand modification *** main purpose of task scheduling is to assign tasks to available processors to produce minimum schedule length without violating precedence *** heterogeneous multiprocessor systems,task assignments and schedules have a significant impact on system *** the heuristic-based task scheduling algorithm,the different processes will lead to a different task execution time(makespan)on a heterogeneous computing ***,a good scheduling algorithm should be able to set precedence efficiently for every subtask depending on the resources required to reduce(makespan).In this paper,we propose a new efficient task scheduling algorithm in cloud computing systems based on RAO algorithm to solve an important task and schedule a heterogeneous multiple processing *** basic idea of this process is to exploit the advantages of heuristic-based algorithms to reduce space search and time to get the best *** evaluate our algorithm’s performance by applying it to three examples with a different number of tasks and *** experimental results show that the proposed approach significantly succeeded in finding the optimal solutions than others in terms of the time of task implementation.
In recent years, there has been growing interest in utilizing technology to improve agricultural practices and optimize crop yield. One area of focus is the development of intelligent farm irrigation systems that inte...
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In this work, a prototype system has been designed with a 0.18-μm CMOS technology to capture perspiration rate in daily life. To calculate an amount of perspiration, a temperature sensor is necessary concurrently wit...
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A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,w...
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A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.
Road mishaps are more likely to be caused by tired drivers. Driving for extended periods of time, driving while sleep deprived, and driving while under the influence of drugs, alcohol, or medication are just a few of ...
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Optimal energy consumption in Wireless Sensor Networks (WSNs) is important. Previous research has shown that by organizing network nodes into a number of clusters, one can achieve greater energy efficiency leading to ...
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This comprehensive review starts with diving into the progress and real-world applications of combining multi-omics data analysis with machine learning techniques in cancer research. Multi-omics involves examining var...
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Brain tumor detection using machine learning techniques seems to be a promising approach to improve the accuracy and efficiency of the diagnosis process. This research proposes a hybrid brain tumor detection scheme us...
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Sentiment analysis within Online Social Networks (OSNs) becomes a major challenge. Mainly, because of the large amount of data on social networks and the mix of different languages that can be used in these environmen...
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As a result of the developments in the digital age, communication has become the primary route for modern business. Business discussions, profiles, seminars, transactions, and agreements were all conducted in person i...
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