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In this paper, the Star-Transformer model is improved to obtain more accurate direction of arrivals (DOA) estimation of underwater sonar uniform linear array (ULA) under low signal-to-noise ratio (SNR) conditions. The ideal real covariance matrix is divided into three channels: real part channel, imaginary part channel, and phase channel to obtain more input features. In training, the real covariance matrix is used under different SNRs. In testing, the covariance matrix of samples in the real environment is used as input. The on-grid form is used to estimate the DOA of multiple signal sources, which is modelled as a multilabel classification problem. The results show that the model can be effective and can still have a good DOA estimation performance under the conditions of trained and untrained SNRs, different snapshots, signal power mismatch, different separation angles, signal correlation, and so on. It shows that the model has excellent robustness. [ABSTRACT FROM AUTHOR]

Objectives To investigate the rates and influencing factors of transient ischaemic attack (TIA) inpatient admissions and outpatient visits in China. Setting A door-to- door survey of 178 059 families from 155 urban and rural areas in 31 provinces in China, 2013. Participants Total 596 536 people were assessed in the annual rate analysis, and 829 TIA patients were assessed in the influencing factor analysis. Main outcome measures The weighted annual rates of TIA inpatient admissions and outpatient visits and the factors influencing inpatient admissions and outpatient visits for TIA patients. Results The weighted annual inpatient admission rate per TIA patient was 25.8 (95% CI: 18.4 to 36.2) per 100 000 in the population, whereas the weighted annual inpatient admission rate for patients with TIAs was 32.5 (95% CI: 23.3 to 38.9) per 100 000 in the population. The weighted annual outpatient visit rate per TIA patient was 34.4 (95% CI: 26.2 to 45.1) per 100 000 in the population, whereas the weighted annual outpatient visit rate for patients with TIAs was 149.6 (95% CI: 127.0 to 165.5) per 100 000. The inpatient rate was higher for men than for women (OR: 2.24; 95% CI: 1.40 to 3.59; p=0.001), for TIA patients with stroke than for patients with isolated TIAs (2.93; 2.01 to 4.25; p<0.001), for TIA patients with hypertension than for TIA patients without hypertension (2.60; 1.65 to 4.11; p<0.001). The outpatient rate was higher for TIA patients with stroke than for patients with isolated TIAs (1.88; 1.33 to 2.64; p<0.001), for TIA patients with dyslipidaemia than for TIA patients without dyslipidaemia (1.92; 1.30 to 2.83; p=0.001). Conclusions The annual rates of TIA inpatient admissions and outpatient visits in population are low, probably due to the lack of access to inpatient and outpatient services experienced by the majority of TIA patients in the population, and individuals’ socio-demographic characteristics, disease histories and stroke prognosis may be associated with inpatient and outpatient TIAs. [ABSTRACT FROM AUTHOR]

In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise, which is called resonance-based time-frequency manifold (RTFM). This is suitable for analyzing signals with oscillatory, non-stationary and non-linear characteristics in a situation of serious noise pollution. Unlike the traditional methods which are sensitive to noise and just consider one side of oscillatory, non-stationary and non-linear characteristics, the proposed RTFM can provide the intact feature signature of all these characteristics in the form of a time-frequency signature by the following steps: first, RSSD is employed on the raw signal to extract the high-oscillatory component and abandon the low-oscillatory component. Second, PSR is performed on the high-oscillatory component to map the one-dimensional signal to the high-dimensional phase space. Third, TFD is employed to reveal non-stationary information in the phase space. Finally, manifold learning is applied to the TFDs to fetch the intrinsic non-linear manifold. A proportional addition of the top two RTFMs is adopted to produce the improved RTFM signature. All of the case studies are validated on real audio recordings of ship-radiated noise. Case studies of ship-radiated noise on different datasets and various degrees of noise pollution manifest the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

The epidemiological characteristics of transient ischemic attacks (TIAs) in China are unclear. In 2013, we conducted a nationally representative, door-to-door epidemiological survey on TIA in China using a complex, multistage, probability sampling design. Results showed that the weighted prevalence of TIA in China was 103.3 [95% confidence interval (CI): 83.9-127.2] per 100,000 in the population, 92.4 (75.0-113.8) per 100,000 among men, and 114.7 (87.2-151.0) per 100,000 among women. The weighted incidence of TIA was 23.9 (17.8-32.0) per 100,000 in the population, 21.3 (14.3-31.5) per 100,000 among men, and 26.6 (17.0-41.7) per 100,000 among women. No difference in average prognosis was found between TIA and stroke in the population. Weighted risk of stroke among TIA patients was 9.7% (6.5-14.3%), 11.1% (7.5-16.1%), and 12.3% (8.4-17.7%) at 2, 30, and 90 days, respectively. The risk of stroke was higher among male patients with a history of TIA than among female patients with a history of TIA (OR: 2.469; 95% CI: 1.172-5.201; P = 0.018), and higher among TIA patients with hypertension than among TIA patients without hypertension (OR: 2.671; 1.547-4.613; P < 0.001). It can be concluded that there are an estimated 1.35 million TIA patients nationwide, with 0.31 million new cases of TIA annually in China. TIA patients were not better managed prior to a stroke event. Early risk of stroke among TIA patients is high. Sex and hypertension may be stroke-associated prognostic factors among TIA patients. TIA clinics and surveillance should be integrated into the national health-care system. [ABSTRACT FROM AUTHOR]

Boosting has been a very successful technique for solving a two-class classification problem. This algorithm only requires that the performance of each weak classifier is better than the random guessing (rather than 1/2) by combining weak classifiers. But the process of selecting weak classifier was too much time-consuming. All the features are needed to traverse for the threshold that achieves minimal error rate. To reduce the computation complexity, a novel method is proposed. Face recognition experiments using local binary pattern (LBP) features are conducted. The results show that the same classifier and error rate are achieved using the proposed training algorithm, and 30% of training time or even more is reduced. [ABSTRACT FROM AUTHOR]

The conventional direction of arrival (DOA) estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF) algorithm is proposed with state space model of single acoustic vector sensor. Although the particle filtering (PF) algorithm has been introduced for acoustic vector sensor applications, it is not suitable for the case that one dimension angle of source is estimated with large deviation, the two dimension angles (pitch angle and azimuth angle) cannot be simultaneously employed to update the state through resampling processing of PF algorithm. To solve the problems mentioned above, the MPF algorithm is proposed in which the state estimation of previous moment is introduced to the particle sampling of present moment to improve the importance function. Moreover, the independent relationship of pitch angle and azimuth angle is considered and the two dimension angles are sampled and evaluated, respectively. Then, the MUSIC spectrum function is used as the "likehood" function of the MPF algorithm, and the modified PF-MUSIC (MPF-MUSIC) algorithm is proposed to improve the root mean square error (RMSE) and the probability of convergence. The theoretical analysis and the simulation results validate the effectiveness and feasibility of the two proposed algorithms. [ABSTRACT FROM AUTHOR]

There are plenty of weak audio analog signals in ocean, whose signal characteristic is usually an important basis for the target detection in ocean, therefore it is necessary to seek for approaches to detect the weak audio signal. Stochastic resonance, which is regarded as a novel method for detecting the weak signal, has been applied in many areas. However, the most researches concentrate on the single-frequency weak signal, and less research on the multi-frequency weak signal. Starting from the basic bistable stochastic resonance system, theoretical analysis on the multi-frequency analog signal with strong noise is carried out, and a method for detecting and recovering the multi-frequency analog signal is proposed, which is based on the average inversion and interpolation fitting. The analysis and simulation results present that, the multi-frequency analog signal is successfully detected and recovered in the condition that the input signal-to-noise ratio (SNR) is -22dB.Compared with the traditional filter method, the proposed method can effectively reduce the waveform distortion and phase delay of the multi-frequency signal, and it is especially suitable for the detection of multi-frequency weak signals whose frequencies are very close, which makes it possess good theoretical guidance and practical application value. [ABSTRACT FROM AUTHOR]

This paper presents a design of DFT-spread OFDM system applied to an underwater acoustic channel. It does not only combine all the advantages of a conventional OFDM system but also reduces the peak-to-average power ratio of the transmit signal. Besides, the scheme spreads the information over several subcarriers as a result of the application of an additional DFT operation and leads to a diversity gain in a frequency-selective fading channel, which is one of the many challenges of communicating data through an underwater acoustic channel. Simulation results show that our proposal possesses good bit-error-rate performance. The system has been tested in a real underwater acoustic channel-the experimental pool in Xiamen University. The experimental results show that the DFT-spread OFDM system can achieve better results than a simple OFDM system in a benign underwater channel. [ABSTRACT FROM AUTHOR]