[Bowel Sounds Detection Method and Experiment Based on Multi-feature Combination].

Bowel sounds is an important indicator to monitor and reflect intestinal motor function, and traditional manual auscultation requires high professional knowledge and rich clinical experience of doctors. In addition, long-time auscultation is time-consuming and laborious， which may lead to misjudgment caused by subjective error. To solve the problem, firstly, the wavelet transform is used to preprocess the bowel sounds signal for noise reduction and enhancement. Secondly, three typical features of intestinal sound were extracted. According to the combination of these features, a three-stage decision was designed to carry out multi-parameter and multi-feature joint threshold detection. This algorithm realized the detection of bowel sound signal and the location of its start and end points, making it possible that the complete bowel sound signal was extracted effectively. In this study, a large number of clinical data and label of bowel sounds were collected, and a new effective evaluation method was proposed to verify the proposed method. The accuracy rate is 83.51%. Results of this study will provide systematic support and theoretical guarantee for the diagnosis of intestinal diseases and the monitoring of postoperative intestinal function recovery of patients.

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p-center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.