In the past several years, remarkable achievements have been made in the field of object detection. Although performance is generally improving, the accuracy of small object detection remains low compared with that of large object detection. In addition, localization misalignment issues are common for small objects, as seen in GoogLeNets and residual networks (ResNets). To address this problem, we propose an improved region-based fully convolutional network (R-FCN). The presented technique improves detection accuracy and eliminates localization misalignment by replacing positionsensitive region of interest (PS-RoI) pooling with position-sensitive precise region of interest (PS-Pr-RoI) pooling, which avoids coordinate quantization and directly calculates two-order integrals for position-sensitive score maps, thus preventing a loss of spatial precision. A validation experiment was conducted in which the Microsoft common objects in context (MS COCO) training dataset was oversampled. Results showed an accuracy improvement of 3.7% for object detection tasks and an increase of 6.0% for small objects.

Aim. This paper investigated the pathogenesis and treatment strategies of acute pancreatitis (AP) in pregnancy. Methods. We analyzed retrospectively the characteristics, auxiliary diagnosis, treatment strategies, and clinical outcomes of 26 cases of patients with AP in pregnancy. Results. All patients were cured finally. (1) Nine cases of 22 mild acute pancreatitis (MAP) patients selected automatic termination of pregnancy because of the unsatisfied therapeutic efficacy or those patients' requirements. (2) Four cases of all patients were complicated with severe acute pancreatitis (SAP); 2 cases underwent uterine incision delivery while one of them also received cholecystectomy, debridement and drainage of pancreatic necrosis, and percutaneous jejunostomy. One case had a fetal death when complicated with SAP; she had to receive extraction of bile duct stones and drainage of abdominal cavity after induced abortion. The other one case with hyperlipidemic pancreatitis was given induced abortion and hemofiltration. Conclusions. The first choice of MAP in pregnancy is the conventional therapy. Apart from the conventional therapy, we need to terminate pregnancy as early as possible for patients with SAP. Removing biliary calculi and drainage is supposed to be considered for acute biliary pancreatitis. Lowering blood lipids treatment should be applied to hyperlipidemic pancreatitis or given to hemofiltration when necessary.

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Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible to be contaminated with various noises, which affect the application value of ECG signals. In this paper, we propose an ECG signal de-noising method using wavelet energy and a sub-band smoothing filter. Unlike the traditional wavelet threshold de-noising method, which carries out threshold processing for all wavelet coefficients, the wavelet coefficients that require threshold de-noising are selected according to the wavelet energy and other wavelet coefficients remain unchanged in the proposed method. Moreover, The sub-band smoothing filter is adopted to further de-noise the ECG signal and improve the ECG signal quality. The ECG signals of the standard MIT-BIH database are adopted to verify the proposed method using MATLAB software. The performance of the proposed approach is assessed using Signal-To-Noise ratio (SNR), Mean Square Error (MSE) and percent root mean square difference (PRD). The experimental results illustrate that the proposed method can effectively remove noise from the noisy ECG signals in comparison to the existing methods.

The electrocardiogram (ECG) signal can easily be affected by various types of noises while being recorded, which decreases the accuracy of subsequent diagnosis. Therefore, the efficient denoising of ECG signals has become an important research topic. In the paper, we proposed an efficient ECG denoising approach based on empirical mode decomposition (EMD), sample entropy, and improved threshold function. This method can better remove the noise of ECG signals and provide better diagnosis service for the computer-based automatic medical system. The proposed work includes three stages of analysis: (1) EMD is used to decompose the signal into finite intrinsic mode functions (IMFs), and according to the sample entropy of each order of IMF following EMD, the order of IMFs denoised is determined; (2) the new threshold function is adopted to denoise these IMFs after the order of IMFs denoised is determined; and (3) the signal is reconstructed and smoothed. The proposed method solves the shortcoming of discarding the first-order IMF directly in traditional EMD denoising and proposes a new threshold denoising function to improve the traditional soft and hard threshold functions. We further conduct simulation experiments of ECG signals from the MIT-BIH database, in which three types of noise are simulated: white Gaussian noise, electromyogram (EMG), and power line interference. The experimental results show that the proposed method is robust to a variety of noise types. Moreover, we analyze the effectiveness of the proposed method under different input SNR with reference to improving SNR ( SNR imp ) and mean square error ( MSE ), then compare the denoising algorithm proposed in this paper with previous ECG signal denoising techniques. The results demonstrate that the proposed method has a higher SNR imp and a lower MSE . Qualitative and quantitative studies demonstrate that the proposed algorithm is a good ECG signal denoising method.

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We propose an improvement method for an asymmetric cryptosystem based on spherical wave illumination. Compared with the phase-truncated Fourier transform-based cryptosystem and the reported improving methods, the encryption process uses a spherical wave to illuminate the encryption system, rather than a uniform plane wave. As a result, the proposed method can avoid various types of the currently existing attacks and maintain the asymmetric characteristic of the cryptosystem. Moreover, due to only changing the illuminating mode, the proposed method can be easily implemented in optics compared with the reported improving methods. Simulation results are presented to demonstrate the feasibility and the security performance of the proposed method.

A fundamental ability for humans is to monitor and process multiple temporal events that occur at different spatial locations simultaneously. A great number of studies have demonstrated simultaneous temporal processing (STP) in human and animal participants, i.e., multiple ‘clocks’ rather than a single ‘clock’. However, to date, we still have no knowledge about the exact limitation of the STP in vision. Here we provide the first experimental measurement to this critical parameter in human vision by using two novel and complementary paradigms. The first paradigm combines merits of a temporal oddball-detection task and a capacity measurement widely used in the studies of visual working memory to quantify the capacity of STP (CSTP). The second paradigm uses a two-interval temporal comparison task with various encoded spatial locations involved in the standard temporal intervals to rule out an alternative, ‘object individuation’-based, account of CSTP, which is measured by the first paradigm. Our results of both paradigms indicate consistently that the capacity limit of simultaneous temporal processing in vision is around 3 to 4 spatial locations. Moreover, the binding of the ‘local clock’ and its specific location is undermined by bottom-up competition of spatial attention, indicating that the time-space binding is resource-consuming. Our finding that the capacity of STP is not constrained by the capacity of visual working memory (VWM) supports the idea that the representations of STP are likely stored and operated in units different from those of VWM. A second paradigm confirms further that the limited number of location-bound ‘local clocks’ are activated and maintained during a time window of several hundreds milliseconds.