Physics-Informed Neural Networks (PINNs) take advantage of physical constraints to improve the predictive performance of neural networks. They have demonstrated remarkable success in physics, chemistry, biology, and m...
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In ornamental fish cultivation, water conditions are one of parameters to control the water quality. Water quality is closely related to fish habitat in ponds or aquariums. Water is a medium that must be considered be...
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Our research demonstrates a discrete speech system that empowers those afflicted with speech impairments to convey ideas by internally articulating words without producing audible sound. This method harnesses the mini...
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In the application of network technology, a Web Server is needed that can run well, by providing data services that have the function to accept HTTP or HTTPS requests by maintaining the security of the Web Server from...
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Almost half of the vehicle accident fatalities occur at night. Driving at night is riskier. Even the most familiar roads can look distant in the dark. It becomes difficult to see other vehicles, pedestrians, and other...
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Indonesia has two seasons, namely the dry season and the rainy season. Floods occupy the first position in the sequence of natural disasters with a total of 1,067 floods in Indonesia. The flood caused a lot of losses ...
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The development of technology in the field of internet of things (IoT) increase the development of android applications that are used to practically control IoT systems, especially in the field of monitoring. The curr...
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The use of Unmanned Aerial Vehicles (UAVs) is growing at a fast pace, as they tend to play an important role in areas such as surveillance, delivery of goods, etc. This is mainly based on their ability to perform flig...
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This paper investigates the performance of various Electromagnetic Field Optimization (EFO) algorithms. Chaos maps are proposed to improve the performance of EFO algorithms. Ten chaotic maps are incorporated in EFO –...
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This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Pr...
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This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task *** Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task *** advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue *** Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative *** research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.
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