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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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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Inspection of blinks and real-time recognition of eye states is crucial for diagnosing ophthalmologic symptoms: dry eye, drowsiness, fatigue, etc. This work presents a new eye state recognition method using a VGG16-ba...
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This study proposes a rigorous strategy for addressing women's safety on public transit networks, leveraging advanced machine learning methodologies to create a secure and welcoming environment for all passengers....
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This study explores the application of YOLOv8, a state-of-the-art object detection algorithm, for human detection in open water using drones in Search and Rescue (SAR) operations. Open water environments present uniqu...
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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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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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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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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.
The large amounts of debris present in our ocean water poses a major threat to the flora and fauna of our marine ecosystem. The continuous increase in dumping of solid waste, and the very slow rate of degradation of m...
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