The rapid growth of diverse information technology applications has increased the challenge of securing and efficiently managing large volumes of data. Innovative solutions like blockchain technology and distributed f...
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The study presents a predictive analysis approach for cyberbullying detection on Twitter, utilizing a multi-model supervised technique. The research aims to develop an effective strategy to identify and classify insta...
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Multilayer graphs are an effective framework for mode ling complex systems and have garnered significant research attention. Previous studies on dense structure decomposition in multilayer graphs have generally relied...
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This article describes a broadband common-mode filter for suppressing common-mode (CM) noise in high-speed differential signals. The filter used a novel defected corrugated reference plane (DCRP) structure. It used st...
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Convolutional neural network (CNN) is widely used for analyzing time series data as it allows for the rapid learning of inherent characteristics in the series with a small number of parameters through filter operation...
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Few-shot learning is becoming more and more popular in many fields,especially in the computer vision *** inspires us to introduce few-shot learning to the genomic field,which faces a typical few-shot problem because s...
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Few-shot learning is becoming more and more popular in many fields,especially in the computer vision *** inspires us to introduce few-shot learning to the genomic field,which faces a typical few-shot problem because some tasks only have a limited number of samples with *** goal of this study was to investigate the few-shot disease sub-type prediction problem and identify patient subgroups through training on small *** disease subtype classification allows clinicians to efficiently deliver investigations and interventions in clinical *** propose the SW-Net,which simulates the clinical process of extracting the shared knowledge from a range of interrelated tasks and generalizes it to unseen *** model is built upon a simple baseline,and we modified it for genomic *** initialization for the classifier and transductive fine-tuning techniques were applied in our model to improve prediction accuracy,and an Entropy regularization term on the query set was appended to reduce ***,to address the high dimension and high noise issue,we future extended a feature selection module to adaptively select important features and a sample weighting module to prioritize high-confidence *** on simulated data and The Cancer Genome Atlas meta-dataset show that our new baseline model gets higher prediction accuracy compared to other competing algorithms.
Flow field classification can help researchers understand flow field characteristics and facilitate flow field research. In this paper, we propose a flow field classification deep learning method based on long short-t...
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Due to its potential uses in a number of industries, including healthcare, security, and entertainment, human aberrant activity identification has attracted a lot of interest lately. Real-time detection and classifica...
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Traditional structured illumination microscopy techniques still face issues such as complex hardware structures, high optical path costs, low efficiency of optical sectioning reconstruction algorithms, and long image ...
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The immutability of blockchain systems makes the security of smart contracts particularly critical. This study presents SELLM, a novel smart contract vulnerability detection tool that integrates symbolic execution wit...
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