Analysing patterns/trends and associations from heterogeneous data coming at varied speeds and formats require data structures which can handle large and dynamic data efficiently. Bloom Filter (BF), a probabilistic da...
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In the rapidly advancing era of self-driving cars, the imperative of ensuring robust cybersecurity measures to safeguard against evolving threats becomes paramount. This paper investigates the intricate cyber-physical...
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The existing 5G new radio (NR) numerology supports certain values of parameters like subcarrier spacing, symbol duration, and guard interval for vehicle-to-everything (V2X) communications. However, with ever evolving ...
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Dementia is an escalating global health challenge,with Alzheimer's disease(AD)at its *** evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent diss...
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Dementia is an escalating global health challenge,with Alzheimer's disease(AD)at its *** evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network,leading to disruptions in both individual brain regions and their *** a comprehensive understanding of the neurodegeneration-brain network link is lacking,it is undeniable that brain networks play a pivotal role in the development and progression of *** thoroughly elucidate the intricate network of elements and connections constituting the human brain,the concept of the brain connectome was *** based on the connectome holds immense potential for revealing the mechanisms underlying disease development,and it has become a prominent topic that has attracted the attention of numerous *** this review,we aim to systematically summarize studies on brain networks within the context of AD,critically analyze the strengths and weaknesses of existing methodologies,and offer novel perspectives and insights,intending to serve as inspiration for future research.
Digital microfluidic biochips (DMFBs) can effectively reduce the cost of biochemical analysis and improve experimental efficiency, as they are easy to carry, use fewer reagent samples and have high precision. Paper-ba...
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Studies aimed at detecting UAVs in real time using processer vision and deep learning are in their infancy. Although there are many possible advantages to using unmanned aerial vehicles (UAVs), some people are concern...
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Corona Virus caused a pandemic outbreak all over the world during 2020-2021. Identification of such diseases in the X-ray images needs help of deep learning methodologies involving classifiers. Achieving proficiency i...
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Globally,skin cancer is a prevalent form of malignancy,and its early and accurate diagnosis is critical for patient *** evaluation of skin lesions is essential,but several challenges,such as long waiting times and sub...
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Globally,skin cancer is a prevalent form of malignancy,and its early and accurate diagnosis is critical for patient *** evaluation of skin lesions is essential,but several challenges,such as long waiting times and subjective interpretations,make this task *** recent advancement of deep learning in healthcare has shownmuch success in diagnosing and classifying skin cancer and has assisted dermatologists in *** learning improves the speed and precision of skin cancer diagnosis,leading to earlier prediction and *** this work,we proposed a novel deep architecture for skin cancer classification in innovative *** proposed framework performed data augmentation at the first step to resolve the imbalance issue in the selected *** proposed architecture is based on two customized,innovative Convolutional neural network(CNN)models based on small depth and filter *** the first model,four residual blocks are added in a squeezed fashion with a small filter *** the second model,five residual blocks are added with smaller depth and more useful weight information of the lesion *** make models more useful,we selected the hyperparameters through Bayesian Optimization,in which the learning rate is *** training the proposed models,deep features are extracted and fused using a novel information entropy-controlled Euclidean Distance *** final features are passed on to the classifiers,and classification results are ***,the proposed trained model is interpreted through LIME-based localization on the HAM10000 *** experimental process of the proposed architecture is performed on two dermoscopic datasets,HAM10000 and *** obtained an improved accuracy of 90.8%and 99.3%on these datasets,***,the proposed architecture returned 91.6%for the cancer *** conclusion,the proposed architecture accuracy is compared with several pre-trained and state-of-the-art
IEC 61499 is an emerging standard for distributed automation which requires well-defined design practises to improve development efficiency. In this paper, we extend the one-line engineering design pattern and provide...
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Recommender systems play an essential role in decision-making in the information age by reducing information overload via retrieving the most relevant information in various applications. They also present great oppor...
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