A novel virtual samples-based sparse representation method for face recognition

A limited training set usually limits the performance of face recognition in practice. Even sparse representation-based methods which outperform in face recognition cannot avoid such situation. In order to effectively improve recognition accuracy of sparse representation-based methods on a limited training set, a novel virtual samples-based sparse representation (VSSR) method for face recognition is proposed in this paper. In the proposed method, virtual training samples are constructed to enrich the size and diversity of a training set and a sparse representation-based method is used to classify test samples. Extensive experiments on different face databases confirm that VSSR is robust to illumination variations and works better than many representative representation-based face recognition methods.     

Self-Stable Chaos Control of dc-dc Converter

A new concept related to self-stable chaos control is first put forward, and its theoretical basis and realization are presented from the frequency-domain perspective. With a new analogous-circuit realization of this control its applications in the voltage-mode Buck converter is discussed. The harmonic-balance method is applied to determine the control range of the control parameter. The experiment results given in the last part confirm the validity of the proposed control method.     

Accurate ab initio potential of CO(XΣ) at low cost via correlation scaling and extrapolation method

The potential energy curve (PEC) for the ground state of CO(X¹Σ⁺) has been investigated by the highly accurate valence internally contracted multi-reference configuration interaction with the Davidson correction (MRCI+Q) method in combination with a series of correlation-consistent basis sets of Dunning and co-workers. The scheme proposed by Varandas, which enables high-quality molecular potentials to be obtained from small basis set calculations via scaling and extrapolation of the electron correlation to the complete basis set limit plus extrapolation to the complete basis set limit of the complete-active-space self-consistent field energy, has been applied to the system under consideration here. The present results are compared with the other theoretical and experimental data, and show that the present methods are credible and accurate.     

Source detection in mechanoacoustic systems by the wave front inversion and time reversal methods

A combined experimental and theoretical method is proposed for finding the vibration sources in mechanoacoustic systems. The method is similar to the wave front inversion and time reversal focusing methods used in optics and acoustics. The method performs coherent measurements of the vibration field at a set of points and employs the reciprocity principle in its theoretical part. To enhance the stability of the method, modifications are proposed that perform nonlinear processing of vibration fields calculated by the finite element method. Possibilities of using the method in self-testing vibrating systems are discussed.     

中频声振耦合的波函数统计能量法

为了提高中频声振耦合的计算效率,提出了波函数-统计能量法的结构-声学耦合方法,该方法从波动理论的角度出发,将波函数法(WBM)和统计能量法(SEA)结合,通过在耦合面分别施加声压激励和速度边界条件,推导了耦合面参数理论计算公式。将该方法用到长方体声腔和钢板耦合的模型中,并对100~1000 Hz的计算结果进行了实验验证。WBM-SEA模型与参考FEM-SEA模型以及实验模型的频响曲线对比结果表明,WBM-SEA与FEM-SEA以及实验结果吻合很好,验证了混合WBM-SEA的有效性。通过收敛性分析发现混合WBM-SEA方法计算时间比混合FEM-SEA方法更少。从而可以得出结论:混合波函数-统计能量法方法对中频声振耦合预测是有效的,且比FEM-SEA更加高效。     

有限点方法研究

在二维散乱离散点集上研究一类无网格方法——有限点方法(Finite Point Method,简称FPM),建立方法的基础.采用方向微商和方向差商讨论有限点方法,建立各阶各方向微商间的关系式.利用这些关系式,根据被逼近点的邻点数目差异,分别建立数值方向微商的五点公式及少点(两点、三点、四点)公式;研究五点公式的可解性条件与可允许邻点集;获得典型微分算子的数值方向微商公式等.理论分析和数值试验表明,随着邻点数目的增加,相应数值公式的逼近精度随之提高.这类近似公式不仅为在散乱离散点集上构造各类偏微分方程的格式奠定了基础,同时,也可应用于偏微分方程非结构网格计算方法,提高方法的精度.     

Statistical properties of polarization image and despeckling method by multiresolution block-matching 3D filter

The theoretical and experimental investigations on the polarization imagery system of speckle statistical characteristics and speckle removing method are researched. A method to obtain two images encoded by polarization degree with a single measurement process is proposed. A theoretical model for polarization imagery system on Müller matrix is proposed. According to modern charge coupled device (CCD) imaging characteristics, speckles are divided into two kinds, namely small speckle and big speckle. Based on this model, a speckle reduction algorithm based on a dual-tree complex wavelet transform (DTCWT) and blockmatching 3D filter (BM3D) is proposed (DTBM3D). Original laser image data transformed by logarithmic compression is decomposed by DTCWT into approximation and detail subbands. Bilateral filtering is applied to the approximation subbands, and a suited BM3D filter is applied to the detail subbands. The despeckling results show that contrast improvement index and edge preserve index outperform those of traditional methods. The researches have important reference value in research of speckle noise level and removing speckle noise.     

Rigid finite element model of a cracked rotor

The article introduces a new mathematical model for the cracked rotating shaft. The model is based on the rigid finite element (RFE) method, which has previously been successfully applied for the dynamic analysis of many complicated, mechanical structures. In this article, the RFE method is extended and adopted for the modeling of rotating machines. An original concept of crack modeling utilizing the RFE method is developed. The crack is presented as a set of spring–damping elements of variable stiffness connecting two sections of the shaft. An alternative approach for approximating the breathing mechanism of the crack is introduced. The approach is simple and allows one to intuitively and systematically prepare and analyze the model of a cracked rotor.The proposed method is illustrated with numerical and experimental results. The experiments conducted for the uncracked free–free rotor as well as the numerical results obtained with other software confirm the accuracy of the RFE model. The numerical analysis conducted for a set of cracked rotors has shown that, depending on the eccentricity and its angular location, the breathing behavior of the crack may take different forms. In spite of this, the frequency spectra for different cracks are almost identical.Due to its simplicity and numerous advantages, the proposed approach may be useful for rotor crack detection, especially if methods utilizing the mathematical model of the rotor are applied.     

Optical image encryption based on diffractive imaging

In this Letter, we propose a method for optical image encryption based on diffractive imaging. An optical multiple random phase mask encoding system is applied, and one of the phase-only masks is selected and laterally translated along a preset direction during the encryption process. For image decryption, a phase retrieval algorithm is proposed to extract a high-quality plaintext. The feasibility and effectiveness of the proposed method are demonstrated by numerical results. The proposed method can provide a new strategy instead of conventional interference methods, and it may open up a new research perspective for optical image encryption.     

Multi-Source Information Fusion Based on Negation of Reconstructed Basic Probability Assignment with Padded Gaussian Distribution and Belief Entropy

Multi-source information fusion is widely used because of its similarity to practical engineering situations. With the development of science and technology, the sources of information collected under engineering projects and scientific research are more diverse. To extract helpful information from multi-source information, in this paper, we propose a multi-source information fusion method based on the Dempster-Shafer (DS) evidence theory with the negation of reconstructed basic probability assignments (nrBPA). To determine the initial basic probability assignment (BPA), the Gaussian distribution BPA functions with padding terms are used. After that, nrBPAs are determined by two processes, reassigning the high blur degree BPA and transforming them into the form of negation. In addition, evidence of preliminary fusion is obtained using the entropy weight method based on the improved belief entropy of nrBPAs. The final fusion results are calculated from the preliminary fused evidence through the Dempster’s combination rule. In the experimental section, the UCI iris data set and the wine data set are used for validating the arithmetic processes of the proposed method. In the comparative analysis, the effectiveness of the BPA determination using a padded Gaussian function is verified by discussing the classification task with the iris data set. Subsequently, the comparison with other methods using the cross-validation method proves that the proposed method is robust. Notably, the classification accuracy of the iris data set using the proposed method can reach an accuracy of 97.04%, which is higher than many other methods.     

Shrinkage-divergence-proximity locally linear embedding algorithm for dimensionality reduction of hyperspectral image

Existing manifold learning algorithms use Euclidean distance to measure the proximity of data points. However, in high-dimensional space, Minkowski metrics are no longer stable because the ratio of distance of nearest and farthest neighbors to a given query is almost unit. It will degrade the performance of manifold learning algorithms when applied to dimensionality reduction of high-dimensional data. We introduce a new distance function named shrinkage-divergence-proximity (SDP) to manifold learning, which is meaningful in any high-dimensional space. An improved locally linear embedding (LLE) algorithm named SDP-LLE is proposed in light of the theoretical result. Experiments are conducted on a hyperspectral data set and an image segmentation data set. Experimental results show that the proposed method can efficiently reduce the dimensionality while getting higher classification accuracy.     

Multivariate Versus Classical Univariate Calibration Methods for Spectrofluorimetric Data: Application to Simultaneous Determination of Olmesartan Medoxamil and Amlodipine Besylate in their Combined Dosage Form

Olmesartan medoxamil (OLM, an angiotensin II receptor blocker) and amlodipine besylate (AML, a dihydropyridine calcium channel blocker), are co-formulated in a single-dose combination for the treatment of hypertensive patients whose blood pressure is not adequately controlled on either component monotherapy. In this work, four multivariate and two univariate calibration methods were applied for simultaneous spectrofluorimetric determination of OLM and AML in their combined pharmaceutical tablets in all ratios approved by FDA. The four multivariate methods are partial least squares (PLS), genetic algorithm PLS (GA-PLS), principal component ANN (PC-ANN) and GA-ANN. The two proposed univariate calibration methods are, direct spectrofluorimetric method for OLM and isoabsorpitive method for determination of total concentration of OLM and AML and hence AML by subtraction. The results showed the superiority of multivariate calibration methods over univariate ones for the analysis of the binary mixture. The optimum assay conditions were established and the proposed multivariate calibration methods were successfully applied for the assay of the two drugs in validation set and combined pharmaceutical tablets with excellent recoveries. No interference was observed from common pharmaceutical additives. The results were favorably compared with those obtained by a reference spectrophotometric method.     

The momentum interpolation method based on the time-marching algorithm for All-Speed flows

The time-marching approach has clear physical meaning and strict mathematical nature and has been applied in computation of compressible flows widely and extended to many uniform algorithms for All-Speed flows. Remedy for its weakness in the problem of checkerboard decoupling of pressure field for incompressible flows is envisaged with the time-marching momentum interpolation method (MIM) taken into account in this paper. Existing preconditioning methods for suppressing decoupling and time-marching MIM are analyzed for this purpose, and algorithms of time-marching MIM are proposed for steady and unsteady flows and for All-Speed flows. Asymptotic analysis shows that the supposed time-marching MIM has at least a third-order accuracy, better than the existing time-marching coupling methods, which only have an accuracy of the same order as the adopted scheme has. Effects of the time step sizes on the ability of the time-marching MIM to suppress the checkerboard pressure decoupling are particularly discussed in terms of the dual-time stepping approach, and it is revealed how the decreased sizes of either the pseudo- or physical-time step increases the possibility of decoupling and how Choi’s modification, in which the history of the interface velocity is decided by itself instead of the arithmetic average of the velocities on its adjacent nodes, removes the unphysical pressure oscillation with small size of the physical time step but leads to divergence with the pseudo-time step as well. As a remedy for the pseudo-time step, such methods are recommended as implicit methods and the local-time step method with a proposed modification of the time-marching MIM preventing accuracy loss due to very large time step size. Numerical experiments support the theoretical analyses and show the validity of the time-marching MIM proposed.     

基于斑马鱼图像特征的鱼群检测算法北大核心CSCD

计算机视觉方法越来越多地应用于斑马鱼的群体行为研究;但是,由于斑马鱼游动过程形体变化大,遮挡多,准确与鲁棒地检测出斑马鱼仍然是一件非常具有挑战性的问题。为了解决该问题,提出一种基于斑马鱼图像特征的鱼群检测算法。首先通过分析目标特性,提出使用鱼头和鱼尾替代全鱼的检测方法,解决了传统整鱼检测在鱼群交叉遮挡时失效的难题;然后基于斑马鱼图像特征自动构建训练集,避免了深度学习手动标注的费时费力问题。通过对实际斑马鱼视频进行处理验证,与现有的算法相比,本文提出的方法在标注率、召回率(recall,R)与遮挡检测率(occlusion detection rate,ODR)等性能指标上有更好的实验效果。其中,在标注性能方面,本文提出的自动标注方法在总标注率上达到87.40%;在训练集效果方面,本文自动标注算法结合人工校正在标注时间上相比于人工标注方法减少93.11%,均值平均精度(mean average precision,mAP)达到79.80%;在目标检测方面,在目标遮挡率为42.72%的情况下,本文检测算法能够获得82.0%的召回率及58.02%的遮挡检测率。     

Accurate segmentation of leukocyte in blood cell images using Atanassov's intuitionistic fuzzy and interval Type II fuzzy set theory

In this paper automatic leukocyte segmentation in pathological blood cell images is proposed using intuitionistic fuzzy and interval Type II fuzzy set theory. This is done to count different types of leukocytes for disease detection. Also, the segmentation should be accurate so that the shape of the leukocytes is preserved. So, intuitionistic fuzzy set and interval Type II fuzzy set that consider either more number of uncertainties or a different type of uncertainty as compared to fuzzy set theory are used in this work. As the images are considered fuzzy due to imprecise gray levels, advanced fuzzy set theories may be expected to give better result. A modified Cauchy distribution is used to find the membership function. In intuitionistic fuzzy method, non-membership values are obtained using Yager's intuitionistic fuzzy generator. Optimal threshold is obtained by minimizing intuitionistic fuzzy divergence. In interval type II fuzzy set, a new membership function is generated that takes into account the two levels in Type II fuzzy set using probabilistic T co norm. Optimal threshold is selected by minimizing a proposed Type II fuzzy divergence. Though fuzzy techniques were applied earlier but these methods failed to threshold multiple leukocytes in images. Experimental results show that both interval Type II fuzzy and intuitionistic fuzzy methods perform better than the existing non-fuzzy/fuzzy methods but interval Type II fuzzy thresholding method performs little bit better than intuitionistic fuzzy method. Segmented leukocytes in the proposed interval Type II fuzzy method are observed to be distinct and clear.     

Advanced computational method for studying molecular vibrations and spectra for symmetrical systems with many degrees of freedom,and its application to fullerene

A computational method for studying molecular vibrations and spectra for symmetrical systems with many degrees of freedom was developed. The algorithm allows overcoming difficulties on the automation of calculus related to the symmetry determination of such oscillations in complex systems with many degrees of freedom. One can find symmetrized displacements and, consequently, obtain and classify normal oscillations and their frequencies. The problem is therefore reduced to the determination of eigenvectors by common numerical methods, and the algorithm simplifies the procedure of symmetry determination for normal oscillations. The proposed method was applied to studying molecular vibrations and spectra of the fullerene molecule C₆₀, and the comparison of theoretical results with experimental data is drawn. The computational method can be further extended to other problems of group theory in physics with applications in clusters and nanostructured materials.     

Shape and topology optimization for electrothermomechanical microactuators using level set methods

In this short note, a shape and topology optimization method is presented for multiphysics actuators including geometrically nonlinear modeling based on an implicit free boundary parameterization method. A level set model is established to describe structural design boundary by embedding it into the zero level set of a higher-dimensional level set function. The compactly supported radial basis functions (CSRBF) are introduced to parameterize the implicit level set surface with a high level of accuracy and smoothness. The original more difficult shape and topology optimization driven by the Hamilton–Jacobi partial differential equation (PDE) is transferred into a relatively easier parametric (size) optimization, to which many well-founded optimization algorithms can be applied. Thus the structural optimization is transformed to a numerical process that describes the design as a sequence of motions of the design boundaries by updating the expansion coefficients of the size optimization. Two widely studied examples are chosen to demonstrate the effectiveness of the proposed method.     

Gamma-distorted fringe image modeling and accurate gamma correction for fast phase measuring profilometry

In fast phase-measuring profilometry, phase error caused by gamma distortion is the dominant error source. Previous phase-error compensation or gamma correction methods require the projector to be focused for best performance. However, in practice, as digital projectors are built with large apertures, they cannot project ideal focused fringe images. In this Letter, a thorough theoretical model of the gamma-distorted fringe image is derived from an optical perspective, and a highly accurate and easy to implement gamma correction method is presented to reduce the obstinate phase error. With the proposed method, high measuring accuracy can be achieved with the conventional three-step phase-shifting algorithm. The validity of the technique is verified by experiments.     

Enhancement of efficiency of vibration suppression using piezoelectric elements and LR circuit by amplification of electrical resonance

This paper describes a vibration suppression method based on passive vibration suppression using a piezoelectric element and an LR circuit. The proposed method applies a voltage that is proportional to the displacement or acceleration of the host structure to the LR circuit in series. Because the applied voltage equivalently increases the voltage generated by the piezoelectric effect in the piezoelectric element, the effect of the vibration suppression is increased with an increase in the applied voltage. The proposed method is categorized as a hybrid vibration suppression method that involves only an analog circuit. The governing equations were formulated, and the optimum values of the inductance and resistance were theoretically derived using the two fixed point method as well as the passive method. The characteristic features of the proposed method were theoretically investigated by comparing the added stiffness and damping, amount of the applied voltage, and time-averaged power of the applied voltage with those of the conventional methods. In addition, the stability of the proposed method was theoretically analyzed. The effectiveness of the proposed method and the theoretical analysis were verified through experiments.     

A new method for accurately determining the modal equivalent stiffness ratio of bonded piezoelectric structures

This paper describes new methods for measuring the modal equivalent stiffness ratios and modal electromechanical coupling coefficients of piezoelectric elements attached to a host structure such as a beam. Modal equivalent stiffness ratios and modal electromechanical coupling coefficients are essential for estimating the performance and determining an optimum design of active vibration control and passive vibration suppression systems that use piezoelectric elements. Accurate determination of these modal parameters is also useful for other systems including piezoelectric sensors and energy generators. This paper not only describes the measurement methods but also presents the theoretical formulations derived by taking into account the effect of adhesive bonds. The formulations in this paper demonstrate the necessity of experimental measurements and the accuracy enhancements that the theoretical estimations can provide. Conventional methods for obtaining the modal equivalent stiffness ratios are sensitive to measurement errors, which result in the loss of accuracy, rendering these methods unreliable for many practical applications. The proposed methods use an inductor instead of an open circuit to address the abovementioned issue and, thereby, provide significant improvement in the accuracy. Because the loss factors of the experimental apparatus tend to compromise the accuracy of the proposed methods, a method using a negative resistor is proposed, theoretically analyzed, and confirmed to eliminate some of the errors introduced by loss factors. The advantages of the proposed methods and the effectiveness of theoretical analysis, considering the effect of adhesive bonds, are verified experimentally.