Sleep apnea is the most prevalent sleep disorder. In severe cases, it can even lead to sudden death. To diagnose sleep apnea, it is critical to measure the number of sleep arousal times per hour. Current clinical stan...
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ISBN:
(纸本)9781665480468
Sleep apnea is the most prevalent sleep disorder. In severe cases, it can even lead to sudden death. To diagnose sleep apnea, it is critical to measure the number of sleep arousal times per hour. Current clinical standard procedures require patients to visit a sleep center or hospital for polysomnography (PSG), in which the patient's physiological signals are recorded during the night, and a sleep technician then interprets these signals manually to determine the sleep-wake pattern. With the rising number of sleep disorders, sleep technologists cannot afford such a high workload, which makes the development of an automated sleep arousal detection system critical to reducing medical costs. When PSG is recorded, a large number of wires will also interfere with the patient and cause measurement distortion. In this study, a spatial-channel attention (SCA) U-Net for automatic sleep arousal detection was proposed, which was trained and tested on PhysioNet 2018 sleep PSG dataset. Considering clinical applicability and reducing patient disturbance when recording physiological signals, only five physiological signal channels were required for our proposed model. It is much lower than other methods in the literature. The A AUPRC of our proposed model was and 39%. The results showed the proposed method is highly accurate and requires fewer channel signals, that also demonstrated the clinical applicability and robustness of the proposed method.
This paper proposes a semi-Markov model of telecommunication network (TCN). The variant of dynamic traffic adaptive control of queuing system as a special case of TCN is considered. The main purpose of control is to m...
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ISBN:
(数字)9798350393316
ISBN:
(纸本)9798350393323
This paper proposes a semi-Markov model of telecommunication network (TCN). The variant of dynamic traffic adaptive control of queuing system as a special case of TCN is considered. The main purpose of control is to minimize the average cost per unit of time to service the incoming flow of information (packets). This takes into account the different bandwidth of the channels, the processing speed of information in the channel and the information capacity of the buffers. The approach to the organization of dynamic control taking into account noise immunity (information reliability) and information security is discussed.
The environmental influence is inevitable but often ignored in the study of electronic transport properties of small-scale systems. Such an environment-mediated interaction can generally be described by a parity-time ...
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We present a theoretical study of the transition energies ω and the oscillator strengths gf for the C-like ions (with Z from 14–36) subject to plasma environment for atomic transitions, which meet the spatial and te...
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We present a theoretical study of the transition energies ω and the oscillator strengths gf for the C-like ions (with Z from 14–36) subject to plasma environment for atomic transitions, which meet the spatial and temporal criteria of the Debye-Hückel (DH) approximation. Two strong dipole-allowed transitions, viz., the intrashell transition 2s2p33D1→2s22p23P0, and the intershell transition 2s22p3d3D1→2s22p23P0 are investigated in detail. We found that both ω and gf increase for the intrashell transition under the Debye-Hückel screening potential VDH in terms of the Debye length D, which is linked to the ratio between the plasma density Ne and its temperature kT. In contrast, both ω and gf decrease for the intershell transition. Our theoretically estimated data have led to a general scaling feature for the change in ω of both intershell and intrashell transitions for ions with different nuclear charge Z. A similar general feature for the change in gf is also found for the intrashell transition. However, due to the change of the electron correlations between electrons in different shells with respect to the relativistic spin-orbit interaction as Z varies, the variation of gf subject to the surrounding plasma is more complicated for the intershell transition. The results presented in this work may facilitate the plasma diagnostic to determine the plasma temperature and density for the astrophysical objects and the controlled fusion facilities.
We consider the collective field theory description of the singlet sector of a free and massless matrix field in d dimensions. The k-local collective fields are functions of (d - 1)k + 1 coordinates. We provide a map ...
Abstract: The direct measurements of the adiabatic temperature change under cyclic conditions have been carried out for Fe48Rh52 alloys obtained by different heat treatment protocols. Furthermore, the magnetocaloric l...
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In this paper we consider the collective field theory description of the singlet sector of a free matrix field in 2+1 dimensions. This necessarily involves the study of k-local collective fields, which are functions o...
Higher-order topological states extend the power of nontrivial topological states beyond the bulk-edge correspondence. Here we study the higher-order topological states (corner states) in an open-boundary two-dimensio...
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In the fast-paced and volatile financial markets, accurately predicting stock movements based on financial news is critical for investors and analysts. Traditional models often struggle to capture the intricate and dy...
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In the fast-paced and volatile financial markets, accurately predicting stock movements based on financial news is critical for investors and analysts. Traditional models often struggle to capture the intricate and dynamic relationships between news events and market reactions, limiting their ability to provide actionable insights. This paper introduces a novel approach leveraging Explainable Artificial Intelligence (XAI) through the development of a Geometric Hypergraph Attention Network (GHAN) to analyze the impact of financial news on market behaviours. Geometric hypergraphs extend traditional graph structures by allowing edges to connect multiple nodes, effectively modelling high-order relationships and interactions among financial entities and news events. This unique capability enables the capture of complex dependencies, such as the simultaneous impact of a single news event on multiple stocks or sectors, which traditional models frequently overlook. By incorporating attention mechanisms within hypergraphs, GHAN enhances the model's ability to focus on the most relevant information, ensuring more accurate predictions and better interpretability. Additionally, we employ BERT-based embeddings to capture the semantic richness of financial news texts, providing a nuanced understanding of the content. Using a comprehensive financial news dataset, our GHAN model addresses key challenges in financial news impact analysis, including the complexity of high-order interactions, the necessity for model interpretability, and the dynamic nature of financial markets. Integrating attention mechanisms and SHAP values within GHAN ensures transparency, highlighting the most influential factors driving market predictions. Empirical validation demonstrates the superior effectiveness of our approach over traditional sentiment analysis and time-series models. Our framework not only improves prediction accuracy but also provides detailed insights into how financial news impacts diff
In this paper we consider the collective field theory description of a single free massless scalar matrix theory in 2+1 dimensions. The collective fields are given by k-local operators obtained by tracing a product of...
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