We hereby propose a dual-polarized beam-deflecting metasurface that can double the scan-angle range of a phased-array antenna without compromising the directivity across all scan angles, including broadside. In partic...
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The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) was designed the enhance the livelihood of rural households all across India, providing opportunities for wage employment. In recent years the progr...
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In recent years, Side-Channel Attack (SCA) has been widely used in hardware security analysis. Such an attack uses the power characteristics generated by the switching of internal logic gates during chip operation to ...
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Large Language Models (LLMs) have shown impressive capabilities across various fields, including across social sciences. While research has explored LLMs’ emotion capabilities, studies on coping mechanisms are limite...
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We present BERTiMuS, an approach that uses CodeBERT to generate mutants for Simulink models. BERTiMuS converts Simulink models into textual representations, masks tokens from the derived text, and uses CodeBERT to pre...
Intrusion detection systems (IDS) play a crucial role in IoT and network security by monitoring system data and alerting to suspicious activities. Machine learning (ML) has emerged as a promising solution for IDS, off...
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The technology known as Block Chain is one of the technologies that is seeing one of the fastest increase rates around the world. The technique known as blockchain is used to guarantee the security of a variety of dat...
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While continuous-wave (CW) Doppler radar can be used to unobtrusively monitor human cardiopulmonary vital signs in uncontrolled settings, locomotion or other extraneous motion can sometimes obscure or distort such mea...
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ISBN:
(数字)9798331510473
ISBN:
(纸本)9798331510480
While continuous-wave (CW) Doppler radar can be used to unobtrusively monitor human cardiopulmonary vital signs in uncontrolled settings, locomotion or other extraneous motion can sometimes obscure or distort such measurements. This work examines the application of recurrent neural networks (RNNs) to classify sedentary and non-sedentary states, which would facilitate monitoring long-term variation of vital signs specifically limited to sedentary periods. Both Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) were applied to output signals from 2.4-GHz quadrature CW Doppler radar measurements of 12 subjects exhibiting sedentary and non-sedentary states. The findings indicate that applying RNNs directly to in-phase (I) and quadrature (Q) (not demodulated) radar outputs provided the most effective means of classifying subject state, acheiving accuracies greater than $\mathbf{9 6 \%}$ . These results clearly demonstrate the value of using RNNs for classifying physiological radar data for subjects that are free to move about, as well as their potential for analyzing quadrature radar without preliminary demodulation.
Deep learning has been widely adopted for human activity recognition (HAR) while generalizing a trained model across diverse users and scenarios remains challenging due to distribution shifts (DS). The inherent low-re...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Deep learning has been widely adopted for human activity recognition (HAR) while generalizing a trained model across diverse users and scenarios remains challenging due to distribution shifts (DS). The inherent low-resource challenge in HAR, i.e., collecting and labeling adequate human-involved data can be prohibitively costly, further raising the difficulty of tackling DS. We propose TACO, a novel transformer-based contrastive meta-learning approach for generalizable HAR. TACO addresses DS by synthesizing virtual target domains in training with explicit consideration of model generalizability. Additionally, we extract expressive feature with the attention mechanism of Transformer and incorporate the supervised contrastive loss function within our meta-optimization to enhance representation learning. Our evaluation demonstrates that TACO achieves notably better performance across various low-resource DS scenarios.
Over the last decade, Internet of Things (IoT) has permeated our daily life with a broad range of applications. However, a lack of adequate security in IoT devices renders IoT systems vulnerable to various network-bas...
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