Thyroid disorder is a significant source of formulation in medical classification and prognosis, with onset being a challenging assumption in medical study. The thyroid gland is a vital organ of our body. Thyroid horm...
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This paper presents a micro architectural exploration of fault-tolerance and timing behavior on silicon on chip. Silicon on chip represents a full-size mission in designing reliable hardware with excessive timing accu...
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This study describes a broad endeavor to use cutting-edge technologies to empower deaf primary school students in Sri Lanka. Three key elements make up the study: a sound recognition and classification system, an Andr...
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In this ambitious agricultural project, cutting-edge technologies such as Machine Learning (ML) and Deep Learning (DL) are harnessed to revolutionize farming practices in India. The primary focus lies in automating vi...
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computer networks are used more frequently for time-sensitive applications like voice over internet protocol and other communications. In computer networks, quality of service (QoS) can be crucial since it makes it ea...
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Towards optimal k-prototype discovery,k-means-like algorithms give us inspirations of central samples collection,yet the unstable seed samples selection,the hypothesis of a circle-like pattern,and the unknown K are st...
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Towards optimal k-prototype discovery,k-means-like algorithms give us inspirations of central samples collection,yet the unstable seed samples selection,the hypothesis of a circle-like pattern,and the unknown K are still challenges,particularly for non-predetermined data *** propose an adaptive k-prototype clustering method(kProtoClust)which launches cluster exploration with a sketchy division of K clusters and finds evidence for splitting and *** behalf of a group of data samples,support vectors and outliers from the perspective of support vector data description are not the appropriate candidates for prototypes,while inner samples become the first candidates for instability reduction of *** from the representation of samples in traditional,we extend sample selection by encouraging fictitious samples to emphasize the representativeness of *** get out of the circle-like pattern limitation,we introduce a convex decomposition-based strategy of one-cluster-multiple-prototypes in which convex hulls of varying sizes are prototypes,and accurate connection analysis makes the support of arbitrary cluster shapes *** by geometry,the three presented strategies make kProtoClust bypassing the K dependence well with the global and local position relationship analysis for data *** results on twelve datasets of irregular cluster shape or high dimension suggest that kProtoClust handles arbitrary cluster shapes with prominent accuracy even without the prior knowledge K.
Accurate and timely analysis of chest CT images is crucial for effectively diagnosing and treating a wide range of respiratory, cardiovascular, and infectious diseases, making it a vital component of modern medicine. ...
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To achieve ultra-reliable and low-latency communication (URLLC) and support high density of wireless connections simultaneously, the sixth-generation industrial Internet of things (6G-IIoT) necessitates an expansion o...
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The integrity of product warranties stands as a critical concern, marked by challenges like data tampering and fabrication within traditional verification systems. This paper explores the transformative potential of b...
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Because of the growing number of cars and the inadequate parking infrastructure, urban parking management has become more and more crucial. To predict parking spot availability in IoT-enabled intelligent systems, this...
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