Accurate drought prediction plays a pivotal role in water resource management and agricultural planning. This study delves into the realm of machine learning algorithms to enhance the accuracy of such predictions. The...
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This research study analyzes Accessible Visual Information Retrieval (AVIR), an evolving domain at the crossroads of computer vision, accessibility, and information retrieval. This research study focuses on analyzing ...
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The Intelligent Surveillance Support System(ISSS) is an innovative software solution that enables real-time monitoring and analysis of security footage to detect and identify potential threats. This system incorporate...
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Skin diseases, also known as dermatological conditions or dermatoses, refer to a broad range of illnesses that affect the skin. The Global Burden of Disease Project reports that Skin diseases are still the fourth prim...
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A wide spread neurological condition called dementia is characterized by problems with day-to-day functioning, memoryloss, and cognitive ***'s diagnostic techniques usually rely too much on subjective evaluations,...
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The self-driving car industry is gaining attention for its role in motion planning technology. Deep learning approaches have been implemented to plan autonomous vehicles' motion, but their effectiveness depends on...
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The increasing spread of false information requires advanced detection methods. This study provides a thorough examination of the various strategies used to identify fake news, ranging from traditional approaches to c...
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The Internet-of-Healthcare-Systems technology is based on the Internet of Things. Numerous institutions' health records are integrated with a secure and decentralized blockchain-based storage system. This ensures ...
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Alzheimer's disease is a well-known illness characterized by memory loss and cognitive decline. Since current treatments work best in the early stages, early detection is vital for effective management. The Magnet...
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With the exponential developments of wireless networking and inexpensive Internet of Things(IoT),a wide range of applications has been designed to attain enhanced *** to the limited energy capacity of IoT devices,ener...
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With the exponential developments of wireless networking and inexpensive Internet of Things(IoT),a wide range of applications has been designed to attain enhanced *** to the limited energy capacity of IoT devices,energy-aware clustering techniques can be highly *** the same time,artificial intelligence(AI)techniques can be applied to perform appropriate disease diagnostic *** this motivation,this study designs a novel squirrel search algorithm-based energy-aware clustering with a medical data classification(SSAC-MDC)model in an IoT *** goal of the SSAC-MDC technique is to attain maximum energy efficiency and disease diagnosis in the IoT *** proposed SSAC-MDC technique involves the design of the squirrel search algorithm-based clustering(SSAC)technique to choose the proper set of cluster heads(CHs)and construct ***,the medical data classification process involves three different subprocesses namely pre-processing,autoencoder(AE)based classification,and improved beetle antenna search(IBAS)based parameter *** design of the SSAC technique and IBAS based parameter optimization processes show the novelty of the *** show-casing the improved performance of the SSAC-MDC technique,a series of experiments were performed and the comparative results highlighted the supremacy of the SSAC-MDC technique over the recent methods.
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