Micro-expression recognition algorithm based on the combination of spatial and temporal domains

Aiming at the problem of unsatisfactory effects of traditional micro-expression recognition algorithms,an efficient micro-expression recognition algorithm is proposed,which uses convolutional neural networks(CNN)to extract spatial features of micro-expressions,and long short-term memory network(LSTM)to extract time domain features.CNN and LSTM are combined as the basis of micro-expression recognition.In many CNN structures,the visual geometry group(VGG)using a small convolution kernel is finally selected as the pre-network through comparison.Due to the difficulty of deep learning training and over-fitting,the dropout method and batch normalization method are used to solve the problem in the VGG network.Two data sets CASME and CASME II are used for test comparison,in order to solve the problem of insufficient data sets,randomly determine the starting frame,and a fixedlength frame sequence is used as the standard,and repeatedly read all sample frames of the entire data set to achieve trayersal and data amplification.Finallv.a hieh recognition rate of 67.48% is achieved.

Amplitude phase control for electro-hydraulic servo system based on normalized least-mean-square adaptive filtering algorithm

The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.

An improved micro-expression recognition algorithm of 3D convolutional neural network

The micro-expression lasts for a very short time and the intensity is very subtle.Aiming at the problem of its low recognition rate,this paper proposes a new micro-expression recognition algorithm based on a three-dimensional convolutional neural network(3D-CNN),which can extract two-di-mensional features in spatial domain and one-dimensional features in time domain,simultaneously.The network structure design is based on the deep learning framework Keras,and the discarding method and batch normalization(BN)algorithm are effectively combined with three-dimensional vis-ual geometry group block(3D-VGG-Block)to reduce the risk of overfitting while improving training speed.Aiming at the problem of the lack of samples in the data set,two methods of image flipping and small amplitude flipping are used for data amplification.Finally,the recognition rate on the data set is as high as 69.11%.Compared with the current international average micro-expression recog-nition rate of about 67%,the proposed algorithm has obvious advantages in recognition rate.

Online calibration of laser-induced breakdown spectroscopy for detection of heavy metals in water

In order to reduce the fluctuation of LIBS detection spectrum of liquid sample,the full-spectrum sum method and the internal standardization method is adopted,using an equal-RSD normalization algorithm to calibrate the detection spectrum.Experiment result shows that the full-spectrum sum method reduced the RSD of parallel samples of Cd and Cr to 9.4% and 11.06% from 28.32% and 31.93% respectively,yielded better overall calibration than the singleelement internal standardization approach,thereby suggesting that the former method is convenient and effective for online calibration of LIBS for detection of aqueous heavy metals.

Efficient model building in active appearance model for rotated face

This paper proposes the efficient model building in active appearance model(AAM) for the rotated face.Finding an exact region of the face is generally difficult due to different shapes and viewpoints.Unlike many papers about the fitting method of AAM,this paper treats how images are chosen for fitting of the rotated face in modelling process.To solve this problem,databases of facial rotation and expression are selected and models are built using Procrustes method and principal component analysis(PCA).These models are applied in fitting methods like basic AAM fitting,inverse compositional alignment(ICA),project-out ICA,normalization ICA,robust normalization inverse compositional algorithm(RNIC)and efficient robust normalization algorithm(ERN).RNIC and ERN can fit the rotated face in images efficiently.The efficiency of model building is checked using sequence images made by ourselves.

Multi-modal face parts fusion based on Gabor feature for face recognition

A novel face recognition method, which is a fusion of muhi-modal face parts based on Gabor feature （MMP-GF）, is proposed in this paper. Firstly, the bare face image detached from the normalized image was convolved with a family of Gabor kernels, and then according to the face structure and the key-points locations, the calculated Gabor images were divided into five parts： Gabor face, Gabor eyebrow, Gabor eye, Gabor nose and Gabor mouth. After that multi-modal Gabor features were spatially partitioned into non-overlapping regions and the averages of regions were concatenated to be a low dimension feature vector, whose dimension was further reduced by principal component analysis （PCA）. In the decision level fusion, match results respectively calculated based on the five parts were combined according to linear discriminant analysis （LDA） and a normalized matching algorithm was used to improve the performance. Experiments on FERET database show that the proposed MMP-GF method achieves good robustness to the expression and age variations.

Second-order calibration applied to quantification of two active components of Schisandra chinensis in complex matrix

The effectiveness of traditional Chinese medicine (TCM) against various diseases urges more low cost, speed and sensitive analytical methods for investigating the phamacology of TCM and providing a theoretical basis for clinical use. The potential of second-order calibration method was validated for the quantification of two effective ingredients of Schisandra chinensis in human plasma using spectrofluorimetry. The results obtained in the present study demonstrate the advantages of this strategy for multi-target determination in complex matrices. Although the spectra of the analytes are similar and a large number of interferences also exist, second-order calibration method could predict the accurate concentrations together with reasonable resolution of spectral profiles for analytes of interest owing to its ‘second-order advantage’. Moreover, the method presented in this work allows one to simply experimental procedure as well as reduces the use of harmful chemical solvents.

A Method of Calculating the 3D Coordinates on a Micro Object in a Virtual Micro-Operation System

A simple method for calculating the 3D coordinates of points on a micro object in a multi camera system is proposed. It simplifies the algorithms used in traditional computer vision system by eliminating the calculation of the CCD (charge coupled device) camera parameters and the relative position between cameras, and using solid geometry in the calculation procedures instead of the calculation of the complex matrixes. The algorithm was used in the research of generating a virtual magnified 3D image of a micro object to be operated in a micro operation system, and the satisfactory results were obtained. The application in a virtual tele operation system for a dexterous mechanical gripper is under test.

Super-resolution microscopy based on parallel detection

Image scanning microscopy based on pixel reassignment can improve the confocal resolution limit without losing the image signal-to-noise ratio(SNR)greatly[C.J.R.Sheppard,"Super resolution in confocal imaging,"Optik 80(2)53-54(1988).C.B.Miller,E.Jorg,"Image scanning microscopy,"Phys.Reu.Lett.104(19)198101(2010).C.J.R.Sheppard,s.B.Mehta,R Heintzmann,"Superresolution by image scanning microscopy using pixel reassignment,"Opt.Lett.38(15)28892892(2013)].Here,we use a tailor-made optical fiber and 19 avalanche pho-todiodes(APDs)as parallel detectors to upgrade our existing confocal microscopy,termed as parallel-detection super resolution(PDSR)microscopy.In order to obtain the correct shift value,we use the normalized 2D cross correlation to calculate the shifting value of each image.We characterized our system performance by imaging fuorescence beads and applied this system to observing the 3D structure of biological specimen.

All-Digital Self-Interference Cancellation in Zero-IF Full-Duplex Transceivers

In this paper,a general scheme in digital self-interference cancellation at baseband for zero-IF full-duplex transceivers is presented. We model the self-interference signals specifically with only the nonlinear distortion signals falling in receiving band considered. A joint estimation algorithm is proposed for compensating the time delay and frequency offset taking into account the IQ amplitude and phase imbalances from mixers. The memory effect and nonlinear distortion are adaptively estimated by the de-correlated normalized least mean square(DNLMS) algorithm. Numerical simulation results demonstrate that the proposed self-interference cancellation scheme can efficiently compensate the self-interference and outperform the existing traditional solutions.

An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification

In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefcient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.

Application of system identification in a practical active noise control system

Noise pollution has become increasingly severe around the world due to fast urbanization. How to soundproof windows from outside noise is of significant interest for both academia and industry. This paper reports an experimental implementation of normalized minmax active noise control (ANC) algorithm on an open window system, where identifying the model of acoustic sound paths plays a central role. By doing this, traffic noise is attenuated by the ANC system, leading to a relatively quiet indoor environment, while the natural lighting and ventilation functions of a window are remained. Our experiments show that an average of 19 dB(A) noise reduction is achieved.

Weak Convergence Theorems for Strict Pseudo-contractions in Banach Spaces

In this paper, it is shown that there is a gap in the paper [Chidume, C. E., Shahzad, N.： Weak convergence theorems for a finite family of strict pseudo-contractions. Nonlinear Anal., 72, 1257–1265（2010）], consequently, the main results of the paper do not hold in uniformly smooth Banach spaces. Meanwhile, it is also shown that the main results（Lemma 3.4, Theorems 3.5–3.6, 3.8–3.9） in the paper [Cholamjiak, P., Suantai, S.： Weak convergence theorems for a countable family of strict pseudo-contractions in Banach spaces. Fixed Point Theory Appl., 2010, Article ID 632137, 16 pages（2010）] do not hold in Lpfor p 〉 3. Finally, some modified results are presented in the setting of uniformly smooth and uniformly convex Banach spaces which include Lpfor p ≥ 2 as special cases. Furthermore, our arguments are also different from the ones given by the authors above.