Humans achieve contact-rich dexterous grasping through the synergy of visual and tactile information. However, the high-dimensional action space of high DoF multi-fingered hands poses significant challenges to this op...
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This paper proposes a Sierpinski fractal-based Microwave Metamaterial Absorber (MMA). Sierpinski fractal is a self-repetitive structure which can provide a dual-band operation. In the designed geometry, the sierpinski...
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Non-volatile memory(NVM) devices are of great interest because of their memory capacities in the form of charge storage, scalability and retention capabilities. A Metal-Oxide Semiconductor (MOS) structure with a tunne...
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This paper presents a low-profile quadrilateral-shaped fractal slot planar antenna using a novel fractal geometry where circular, triangular and regular hexagonal motifs are iterated to form antenna elements. It consi...
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Deep learning has now become an integral part of today's world and advancement in the field of deep learning has gained a huge development. Due to the extensive use and fast growth of deep learning, it has capture...
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The emergence of new media in various fields has continuously strengthened the social aspect of social *** tend to express emotions in social interactions,and many people even use satire,metaphors,and other techniques...
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The emergence of new media in various fields has continuously strengthened the social aspect of social *** tend to express emotions in social interactions,and many people even use satire,metaphors,and other techniques to express some negative emotions,it is necessary to detect sarcasm in social comment *** sarcasm,the more reference data modalities used,the better the experimental *** paper conducts research on sarcasm detection technology based on image-text fusion *** effectively utilize the features of each modality,a feature reconstruction output algorithm is *** algorithm is based on the attention mechanism,learns the low-rank features of another modality through cross-modality,the eigenvectors are reconstructed for the corresponding modality through weighted *** only the image modality in the dataset is used,the preprocessed data has outstanding performance in reconstructing the output model,with an accuracy rate of 87.6%.When using only the text modality data in the dataset,the reconstructed output model is optimal,with an accuracy rate of 85.2%.To improve feature fusion between modalities for effective classification,a weight adaptive learning algorithm is *** algorithm uses a neural network combined with an attention mechanism to calculate the attention weight of each modality to achieve weight adaptive learning purposes,with an accuracy rate of 87.9%.Extensive experiments on a benchmark dataset demonstrate the superiority of our proposed model.
作者：
Meenakshisundaram, N.Sajiv, G.
Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India
Cervical cancer remains a significant global health challenge due to late-stage diagnosis and limited access to advanced screening. Early detection can significantly improve outcomes. This study presents a Hybrid Neur...
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Traditional recipe instructions often lack personalization, impeding culinary exploration and causing confusion among home cooks. In response, we introduce an AI-powered recipe instructions generator and advisor aimed...
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The multi-modal speech enhancement method has improved performance due to the diverse sources of its input data, which includes low-distortion air-conducted (AC) signals and low-noise bone-conducted (BC) signals. In l...
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In permissioned blockchain networks,the Proof of Authority(PoA)consensus,which uses the election of authorized nodes to validate transactions and blocks,has beenwidely advocated thanks to its high transaction throughp...
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In permissioned blockchain networks,the Proof of Authority(PoA)consensus,which uses the election of authorized nodes to validate transactions and blocks,has beenwidely advocated thanks to its high transaction throughput and fault ***,PoA suffers from the drawback of centralization dominated by a limited number of authorized nodes and the lack of anonymity due to the round-robin block proposal *** a result,traditional PoA is vulnerable to a single point of failure that compromises the security of the blockchain *** address these issues,we propose a novel decentralized reputation management mechanism for permissioned blockchain networks to enhance security,promote liveness,and mitigate centralization while retaining the same throughput as traditional *** paper aims to design an off-chain reputation evaluation and an on-chain reputation-aided ***,we evaluate the nodes’reputation in the context of the blockchain networks and make the reputation globally verifiable through smart ***,building upon traditional PoA,we propose a reputation-aided PoA(rPoA)consensus to enhance securitywithout sacrificing *** particular,rPoA can incentivize nodes to autonomously form committees based on reputation authority,which prevents block generation from being tracked through the randomness of reputation ***,we develop a reputation-aided fork-choice rule for rPoA to promote the network’s ***,experimental results show that the proposed rPoA achieves higher security performance while retaining transaction throughput compared to traditional PoA.
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