Poultry farming plays a crucial part in fulfilling the need for animal protein worldwide, but the industry faces significant challenges in controlling infectious diseases that impact bird health and productivity. Prot...
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In recent years, there has been increased interest in the field of machine learning to develop accurate and efficient Indian Sign Language (ISL) classification models. This interest stems from the urgent need to overc...
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Elections are crucial in India as they reflect the democratic principles that underpin the country's governance. Since the general elections in 2004, Electronic Voting Machines (EVMs) have been used in India. EVMs...
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a botnet is a group of devices which are controlled by the Attacker and used for fraud, scam and *** attacker is also known as *** Bots are used to conduct many activities varies from stealing user credentials, sendin...
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Over a quarter of the global population suffers from ocular diseases and millions of people die every year due to them. It takes a lot of time and effort to diagnose such diseases and so over 2/3rd of the people suffe...
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Electricity price prediction is crucial for businesses reliant on heavy machinery or computing services, as it aids in cost management and energy optimization. Accurate predictions allow these businesses to forecast a...
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Alzheimer’s disease (AD) is a form of dementia that diminishes a patient’s cognition and memory. By predicting AD progression early, physicians can begin medication that may reduce the disease’s progression. AD det...
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Animal guardians frequently face the challenge of ensuring that the animals under their care receive timely and adequate nourishment when they are away from home for some period of time. Leaving food in a bowl may res...
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Images are essential for communicating ideas, feelings, and narratives in the era of digital media and content consumption. computers to produce textual data for an image that replaces humans. Image captioning is a fa...
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The traditional multi-access edge computing (MEC) capacity isoverwhelmed by the increasing demand for vehicles, leading to acute degradationin task offloading performance. There is a tremendous number ofresource-rich ...
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The traditional multi-access edge computing (MEC) capacity isoverwhelmed by the increasing demand for vehicles, leading to acute degradationin task offloading performance. There is a tremendous number ofresource-rich and idle mobile connected vehicles (CVs) in the traffic network,and vehicles are created as opportunistic ad-hoc edge clouds to alleviatethe resource limitation of MEC by providing opportunistic computing *** this basis, a novel scalable system framework is proposed in thispaper for computation task offloading in opportunistic CV-assisted *** this framework, opportunistic ad-hoc edge cloud and fixed edge cloudcooperate to form a novel hybrid cloud. Meanwhile, offloading decision andresource allocation of the user CVs must be ascertained. Furthermore, thejoint offloading decision and resource allocation problem is described asa Mixed Integer Nonlinear Programming (MINLP) problem, which optimizesthe task response latency of user CVs under various constraints. Theoriginal problem is decomposed into two subproblems. First, the Lagrangedual method is used to acquire the best resource allocation with the fixedoffloading decision. Then, the satisfaction-driven method based on trial anderror (TE) learning is adopted to optimize the offloading decision. Finally, acomprehensive series of experiments are conducted to demonstrate that oursuggested scheme is more effective than other comparison schemes.
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