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At present, emotion recognition based on electroencephalograms (EEGs) has attracted much more attention. Current studies of affective brain-computer interfaces (BCIs) focus on the recognition of happiness and sadness using brain activation patterns. Fear recognition involving brain activities in different spatial distributions and different brain functional networks has been scarcely investigated. In this study, we propose a multifeature fusion method combining energy activation, spatial distribution, and brain functional connection network (BFCN) features for fear emotion recognition. The affective brain pattern was identified by not only the power activation features of differential entropy (DE) but also the spatial distribution features of the common spatial pattern (CSP) and the EEG phase synchronization features of phase lock value (PLV). A total of 15 healthy subjects took part in the experiment, and the average accuracy rate was 85.00% ± 8.13%. The experimental results showed that the fear emotions of subjects were fully stimulated and effectively identified. The proposed fusion method on fear recognition was thus validated and is of great significance to the development of effective emotional BCI systems.

With the continuous development of portable noninvasive human sensor technologies such as brain–computer interfaces (BCI), multimodal emotion recognition has attracted increasing attention in the area of affective computing. This paper primarily discusses the progress of research into multimodal emotion recognition based on BCI and reviews three types of multimodal affective BCI (aBCI): aBCI based on a combination of behavior and brain signals, aBCI based on various hybrid neurophysiology modalities and aBCI based on heterogeneous sensory stimuli. For each type of aBCI, we further review several representative multimodal aBCI systems, including their design principles, paradigms, algorithms, experimental results and corresponding advantages. Finally, we identify several important issues and research directions for multimodal emotion recognition based on BCI.

This paper addresses the problem of direction finding for bistatic MIMO radar in the presence of unknown spatially colored noise. Taking the stationary property of the colored noise into consideration, a covariance differencing-based method is presented. The proposed method has computational complexity very close to that of ESPRIT. besides, it can suppress the colored noise without any virtual aperture loss. Therefore, it improves the accuracy of angle estimation compared with the existing de-noising algorithms. Numerical experiments are provided to examine the effectiveness and improvement of our algorithm.

Marine risers play a key role in the deep and ultra-deep water oil and gas production. The vortex-induced vibration (VIV) of marine risers constitutes an important problem in deep water oil exploration and production. VIV will result in high rates of structural failure of marine riser due to fatigue damage accumulation and diminishes the riser fatigue life. In-service monitoring or full scale testing is essential to improve our understanding of VIV response and enhance our ability to predict fatigue damage. One marine riser fatigue acoustic telemetry scheme is proposed and an engineering prototype machine has been developed to monitor deep and ultra-deep water risers’ fatigue and failure that can diminish the riser fatigue life and lead to economic losses and eco-catastrophe. Many breakthroughs and innovation have been achieved in the process of developing an engineering prototype machine. Sea trials were done on the 6th generation deep-water drilling platform HYSY-981 in the South China Sea. The inclination monitoring results show that the marine riser fatigue acoustic telemetry scheme is feasible and reliable and the engineering prototype machine meets the design criterion and can match the requirements of deep and ultra-deep water riser fatigue monitoring. The rich experience and field data gained in the sea trial which provide much technical support for optimization in the engineering prototype machine in the future.

Rationale:Tumor-induced osteomalacia (TIO) is a rare, paraneoplastic syndrome featured with fibroblast growth factor 23 (FGF23) secretion primarily by benign mesenchymal tumors and sometimes by malignancies. TIO diagnosis and treatment is often delayed because TIO usually has nonspecific gen

The target orientation performance of time reversal by uniformed linear array is discussed over the ocean acoustic multi-path channel. Based on time reversal process, the signal detection system model is derived, and together with the self-adaptively beam-forming the algorithm is proposed. Comparing to the conventional array signal processing method, simulation result shows that time reversal could self-adaptively revise signal transmission delay due to multi-path channel, compensating the same phase correspond to each path wave-front, which reflects through target to each element of array, and strengthening receive signal absolute energy value which raises two orders of magnitude. Under conditions of the same max-SNR criterion whose level is −14.3dB, with the time reversal process combined with self-adaptively beam-forming method the ratio between main lobe and side lobe is improved by 2dB compared to conventional beam-forming. In a conclusion, the uniformed liner array under time reversal process improves the performance of target orientation compared to conventional beam-forming, especially under low signal to noise level

The widespread applications of wireless sensor network (WSN) and the advancement of the micro-electro-mechanical systems (MEMS) technology, and wireless communication develop the underwater wireless sensor network (UWSN). The passive source localization application which is an important application in underwater signal processing is focused on in this paper. We model that the underwater source radiates acoustic noise or energy isotropically and utilize the receiving signal energy (RSS) taken at individual sensors of the UWSN to estimate passively the location of the source. Firstly, we choose the node whose energy is maximal as the reference node to decrease the computational complexity compared to our previous work which use division between pairs of sensor energy output. Secondly, the one-step least-square (OS) method is reviewed and another description based on maximum likelihood source location estimator (MLE) is given. Thirdly, a semidefinite programming (SDP) method is developed to covert the nonconvex problem into the convex optimization problem (CVX). Compared to the least-square (LS) method, this CVX-SDP method based on RSS achieves more accurate results and has better robustness with less number of sensor nodes and with lower SNR.

Bayesian maximum a posteriori (BMAP) DOA estimation method has a better performance than MUSIC method at low signal to noise ratio (SNR) and few snapshots. However, it suffers a heavy computational complexity due to multi-dimensional search. Monte Carlo methods such as Markov Chain Monte Carlo (MCMC) method can effectively solve this problem. MCMC method may provide a local optimization for it is difficult to assess when the Markov Chain has reached the stationary state. Population Monte Carlo (PMC) which uses sequential techniques draws a set of particles and provides an unbiased estimate at each iteration. Thus provides a global optimization and can enhance the computational efficiency. In this paper, the PMC method is introduced and used for Bayesian DOA estimation in order to reduce the complexity. Simulation results show that it has better performance than MUSIC method at low SNR or few snapshots. Compared with BMAP, it can reduce the computation and keep high resolution performance at low SNR.

A acoustic cylinder array of passively omnibearing directivity is designed, including receiving element, transmission and control system, whose characters are: firstly there are N ×M signal receiving elements in the array, and N linear arrays well-proportioned arrangement, meanwhile the first element of each array lain at the top of acoustic cylinder array constitute a M elements uniform circle array; Secondly, located in the same transversal surface array elements connect with the input ports of selecting switch electrocircuit, simultaneously the output ports of latter connected with receiver electrocircuit; At last, electrocircuit generating beam forming weights link to output terminus of receiver electrocircuit by multiplier, whose output data going to processor through data output bus. The design achieves the capability of acoustic target location omnidirectional and tridimensional. It overcomes the default of location accuracy low caused by array aperture restriction of acoustic detection equipment, furthermore improves the three-dimensiona accuracy on target detection.