Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy

Coronary heart disease (CHD) is the leading cause of cardiovascular death. This study aimed to propose an effective method for mining cardiac mechano-electric coupling information and to evaluate its ability to distinguish patients with varying degrees of coronary artery stenosis (VDCAS). Five minutes of electrocardiogram and phonocardiogram signals was collected synchronously from 191 VDCAS patients to construct heartbeat interval (RRI)–systolic time interval (STI), RRI–diastolic time interval (DTI), HR-corrected QT interval (QTcI)–STI, QTcI–DTI, Tpeak–Tend interval (TpeI)–STI, TpeI–DTI, Tpe/QT interval (Tpe/QTI)–STI, and Tpe/QTI–DTI series. Then, the cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), joint distribution entropy (JDistEn), magnitude-squared coherence function, cross power spectral density, and mutual information were applied to evaluate the coupling of the series. Subsequently, support vector machine recursive feature elimination and XGBoost were utilized for feature selection and classification, respectively. Results showed that the joint analysis of XSampEn, XFuzzyEn, and JDistEn had the best ability to distinguish patients with VDCAS. The classification accuracy of severe CHD—mild-to-moderate CHD group, severe CHD—chest pain and normal coronary angiography (CPNCA) group, and mild-to-moderate CHD—CPNCA group were 0.8043, 0.7659, and 0.7500, respectively. The study indicates that the joint analysis of XSampEn, XFuzzyEn, and JDistEn can effectively capture the cardiac mechano-electric coupling information of patients with VDCAS, which can provide valuable information for clinicians to diagnose CHD.     

Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary

Multi-focus image fusion is an important method used to combine the focused parts from source multi-focus images into a single full-focus image. Currently, to address the problem of multi-focus image fusion, the key is on how to accurately detect the focus regions, especially when the source images captured by cameras produce anisotropic blur and unregistration. This paper proposes a new multi-focus image fusion method based on the multi-scale decomposition of complementary information. Firstly, this method uses two groups of large-scale and small-scale decomposition schemes that are structurally complementary, to perform two-scale double-layer singular value decomposition of the image separately and obtain low-frequency and high-frequency components. Then, the low-frequency components are fused by a rule that integrates image local energy with edge energy. The high-frequency components are fused by the parameter-adaptive pulse-coupled neural network model (PA-PCNN), and according to the feature information contained in each decomposition layer of the high-frequency components, different detailed features are selected as the external stimulus input of the PA-PCNN. Finally, according to the two-scale decomposition of the source image that is structure complementary, and the fusion of high and low frequency components, two initial decision maps with complementary information are obtained. By refining the initial decision graph, the final fusion decision map is obtained to complete the image fusion. In addition, the proposed method is compared with 10 state-of-the-art approaches to verify its effectiveness. The experimental results show that the proposed method can more accurately distinguish the focused and non-focused areas in the case of image pre-registration and unregistration, and the subjective and objective evaluation indicators are slightly better than those of the existing methods.     

Using a pseudo-functionally graded interlayer in order to improve the static and dynamic behavior of wind turbine blade T-bolt root joints

The large wind turbines blades with multi-ton composite structures are mostly connected to the peach-bearings flanges using T-bolt joints which induce shear and bearing stress fields around the cross bolts. The significant differences between the modulus of elasticity of metallic bolts and composite surrounding materials cause stress concentration around interfaced zones and, also, limit the load capacity of the joints. In the present research, a pseudo functionally graded material (PFGM) as an interlayer is used around the cross bolts to examine the reduction of the stress concentration. Some radial variation of the mechanical properties would be considered for this interlayer. The finite element method is used to analyze the structures. Loadings are applied to the center of the cross bolts analogous to the real cases. Both the static and dynamic loadings are studied. For the finite element of the functionally graded material interlayer, a multilayer alternative material with constant properties in each layer is used. The results show that using an isotropic single layer with an average modulus of elasticity and specific thickness decreases the stress concentration of the composite part up to 47%. The various property models for the interlayer also show that an appropriated model can decrease the stress concentration up to 55%. Dynamic transient analyses would be implemented over the joint structure and improved considering to the practical cases. Using the PFGM interlayer decreases the constant and variable parts of the stresses up to 55% and also causes significant increasing of the joint fatigue life.     

基于小波-双马尔可夫随机场的纹理分割

传统高斯金字塔马尔可夫随机场模型仅仅捕捉图像低频信息,纹理分割效果不太理想.根据纹理图像小波分解后各频带的统计性质和层次关系,优化频带选取,提出了一种变形小波结构,建立了融合这种结构上尺度内部和尺度之间关系的双马尔可夫随机场模型,引入了一种近似最大联合概率分割算法,并从理论上分析了该算法的合理性.实验表明,与基于高斯金字塔马尔可夫随机场模型的分割方法相比,该算法分割质量明显提高;并且,对模型中自由参数的选取进行比较,证实它们在给定区间上的选择具有鲁棒性.     

人工扰动电离层仿真系统的设计与实现

设计并开发了一种人工扰动电离层仿真系统．建立了数值模型，规划出系统总体构造，在实现过程中引入VC、VF混合编程的概念，以达到两种语言优势互补的目的．文中详细论述了VC、VF混合编程对于数据的处理，生成Fortran的动态链接库，以及在VC中调用生成库的技术．通过仿真模拟，得出了电离层加热过程中电子密度、电子温度等随时间演化的规律，及发射电波频率、功率对加热效果的影响．试用证明，该系统有效地模拟了电离层人工扰动的状态，为在我国实施加热工程提供了可靠的科学依据．     

托卡马克真空室内线圈水冷管道接头强化二次流的数值研究

基于计算流体力学(CFD)理论,研究了不同曲率半径的螺旋导流片的托卡马克真空室内线圈水冷管道接头。利用湍流数值模拟方法,分析了线圈管道接头导流片曲率半径比、冷却水入口流速对线圈管道内流体平均雷诺数分布的影响。结果表明,不同导流片曲率半径比的线圈管道内的流体雷诺数分布曲线相似,平均雷诺数随入口流速的增加而增大,管道接头出口雷诺数随导流片曲率半径比的增大而减小,导流片曲率半径比小的管接头更适用于线圈水冷曲线管的二次流强化。此外,还为导流片曲率半径比为0.2的管接头拟合了管接头出口雷诺数与入口流速的关系式,为进一步研究类似于托卡马克真空室内线圈管道的曲线管接头的二次流强化提供理论基础。     

Rapprochement of artificial intelligence and dynamics

It is proposed that continuous time is in effect discretized in the brain by dynamic pattern recognition mechanisms in neurons. Time discretization is required to support formal computations in continuous time systems consisting of a large number of components. The ability to perform formal computations is necessary if the system is to execute high level algorithms of the type used in present day artificial intelligence. The weakness of such algorithms is that they work efficiently only when the forms of patterns and objects presented to them are highly constrained. The dynamic mechanisms which discretize the brain's time line also serve to code patterns into constrained forms suitable for high level processing.     

一种基于功率谱对数变换的联合变换相关器

联合功率谱的高频成份对相关峰识别具有重要作用,实验中记录的联合功率谱随着频率的增加其强度迅速降低。为增强联合功率谱的高频成分,改善其调制程度,可对功率谱进行对数变换,从而有效保留更多的高频成份,压低零级衍射光斑,提高联合变换相关器的识别能力。     

The Bell inequalities and the joint measurement of incompatible observables

A quantum-mechanical theory of joint nonideal measurement of incompatible polarization observables is applied to an EPR-like experiment. It is demonstrated that this experiment yields both information satisfying and information violating the Bell inequalities. The measurement is also discussed in the context of a local hidden-variables theory. It is argued that the violation of an additional assumption of reproducibility of the hidden variable rather than violation of locality may be responsible for the violation of the Bell inequalities.     

Deterministic Joint Remote Preparation of an Arbitrary Two-Qubit State Using the Cluster State

Recently, deterministic joint remote state preparation (JRSP) schemes have been proposed to achieve 100% success probability. In this paper, we propose a new version of deterministic JRSP scheme of an arbitrary two-qubit state by using the six-qubit cluster state as shared quantum resource. Compared with previous schemes, our scheme has high efficiency since less quantum resource is required, some additional unitary operations and measurements are unnecessary. We point out that the existing two types of deterministic JRSP schemes based on GHZ states and EPR pairs are equivalent.