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This paper addresses the complex challenge of parameter estimation in multi-component Linear Frequency Modulation (LFM) signals by introducing an innovative approach to high-resolution Fractional Fourier Transform (FrFT) parameter estimation, ...

Next-generation wireless networks necessitate large signal bandwidth to support the growing demands of high data rates, which poses significant challenges in the design of real-time radio platforms. We demonstrate SPEAR, a realtime wideband software-...

Next-generation wireless systems utilize large signal band-widths to meet the growing data rate demands of emerging applications and to provide enhanced resolution for wireless sensing and imaging. This poses significant challenges in the design of the ...

Deep learning models have significantly improved the accuracy of crop classification using multispectral temporal data. However, they have complex structures with numerous parameters, requiring large amounts of data and costly training. In low-...$$$$

In conventional cell-free (CF) systems, the scalability and feasibility are hindered by the fact that a single central processing unit (CPU) manages all access points and the stringent synchronization requirement for coherent transmission (CT) ...

Large language models (LLMs) have achieved impressive performance on code generation. Although prior studies enhanced LLMs with prompting techniques and code refinement, they still struggle with complex programming problems due to rigid solution plans. ...

With the rapid development of remote sensing data fusion technology, heterogeneous remote sensing image (HRSI) change detection (CD) has become a frontier field. The powerful nonlinear information processing capability of deep neural network ...

The State Grid has put forward the construction strategy of "ubiquitous power internet of things". Under the background of the state vigorously developing the block chain technology, blockchain technology will also become a key technology to be applied ...

In the context of long-tail classification on graphs, the vast majority of existing work primarily revolves around the development of model debiasing strategies, intending to mitigate class imbalances and enhance the overall performance. Despite the ...

Time series domain adaptation stands as a pivotal and intricate challenge with diverse applications, including but not limited to human activity recognition, sleep stage classification, and machine fault diagnosis. Despite the numerous domain adaptation ...

Masking is one of the most popular countermeasures to side-channel attacks, because it can offer provable security. However, depending on the adversary’s model, useful security guarantees can be hard to provide. At first, masking has been shown ...

To ensure the safe operation of high-end equipment, the three-stage maintenance strategy comprising unplanned shutdown, temporary shutdown, and scheduled shutdown is currently employed in nuclear power plants. However, this strategy hinders the ...

• The predictive maintenance framework and system are established.
• The system consists of anomaly detection, sensor selection, degradation trend prediction and RUL prediction.
• The system works under limited degradation knowledge.

This paper introduces the retrieval-augmented large language model with Definite Finite Automaton (DFA-RAG), a novel framework designed to enhance the capabilities of conversational agents using large language models (LLMs). Traditional LLMs face ...

Masking is one of the most well-established methods to thwart side-channel attacks. Many masking schemes have been proposed in the literature, and code-based masking emerges and unifies several masking schemes in a coding-theoretic framework. In this work,...

Investigating the intricate relationship between citation similarity and the citation interval offers vital insights for refining citation recommendation systems and enhancing citation evaluation models. This is also a new perspective for ...

In a theoretical context of side-channel attacks, optimal bounds between success rate, guessing entropy and statistical distance are derived with a simple majorization (Schur-concavity) argument. They are further theoretically refined for ...

Active reconfigurable intelligent surface (RIS) has attracted a lot of attention due to its ability to drastically change the communication environment by adjusting the phase shift and amplifying the amplitude of signals. In this paper, we consider to ...

The peak-valley time-of-use electricity pricing strategy serves as a robust approach to optimize the power load curve, thereby effectively guaranteeing the stability and cost-efficiency of the power system. This article develops a pricing model for peak-...

This study examines the emotional engagement of 8 adult EFL learners divided into two groups receiving either immediate or delayed corrective feedback. Utilizing deep learning-based facial recognition technology, the study quantifies the learners' ...

To preserve rich detail information and high contrast, a novel image fusion algorithm is proposed based on rolling-guided filtering combined with deep feature extraction. Firstly, input images are filtered to acquire various scales decomposed ...