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In this paper, we investigate a backward problem of 1D multi-term time–space fractional diffusion equation, which is ill-posed. With the help of quasi-reversibility regularization method, we give the regularization solution, based on some properties of Fourier transform and Mittag-Leffler functions. Besides, we establish a-priori and a-posteriori convergence estimates, respectively. Finally, we illustrate two numerical examples to verify the effectiveness and feasibility of our proposed method. • We firstly give the quasi-reversibility method to multi-term fractional equations. • We give the error estimates for the proposed method by a priori and a posteriori parameter choice rules, respectively. • We display two typical numerical examples to show the efficiency and accuracy of the method. [ABSTRACT FROM AUTHOR]

• A differential privacy-based nonnegative matrix factorization is proposed. • An objective perturbation is designed to limit the effect of noise. • Robustness of items with few ratings is improved by an imputation-based scheme. • The effectiveness of the proposed schemes on large datasets is theoretically analyzed. Nonnegative matrix factorization (NMF)-based models have been proven to be highly effective and scalable in addressing collaborative filtering (CF) problems in the recommender system (RS). Since RS requires tremendous user data to provide personalized information services, the issue of data privacy has gained prominence. Although the differential privacy (DP) technique has been widely applied to RS, the requirement of nonnegativity makes it difficult to successfully incorporate DP into NMF. In this paper, a differentially private NMF (DPNMF) method is proposed by perturbing the coefficients of the polynomial expression of the objective function, which achieves a good trade-off between privacy protection and recommendation quality. Moreover, to alleviate the influence of the noises added by DP on the items with sparse ratings, an imputation-based DPNMF (IDPNMF) method is proposed. Theoretic analyses and experimental results on several benchmark datasets show that the proposed schemes have good performance and can achieve better recommendation quality on large-scale datasets. Therefore, our schemes have high potential to implement privacy-preserving RS based on big data. [ABSTRACT FROM AUTHOR]

• Four inerter-based suppression mechanisms are designed and used in the vehicle suspension to restrain the vehicle shimmy. • The vehicle shimmy model using inerter-based suppression mechanism is established. • The effect of inerter-based suppression mechanism on the vehicle shimmy performance is analyzed to show its benefit. • The structural parameter optimization of the inerter-based suppression mechanism is investigated. Shimmy may occur in the vehicle normal driving process, which is a harmful motion and should be controlled in practical engineering. In order to improve the vehicle driving and handling stability, four kinds of passive inerter-based suppression mechanisms are proposed and applied in the vehicle suspension to improve its shimmy performance. The configurations S1 and S2 are composed of one inerter and one damper, which are in parallel-connected and series-connected, respectively, furthermore, an auxiliary spring is added to constitute configurations S3 and S4. Combined with the magic nonlinear tire model, the vehicle shimmy model with four inerter-based suppression mechanisms is established using Lagrange theory, its shimmy performance is studied using bifurcation analysis method, the stable area and limit cycle oscillation (LCO) magnitude of the system are obtained and compared with those of the original suspension system. The effect of the structural parameters of the inerter-based suppression mechanisms on the vehicle shimmy performance is analyzed, and the structural parameter optimization of the inerter-based suppression mechanism is investigated. The results show that the only parallel-connected and series-connected configurations S1 and S2 have little improvement effect on the vehicle shimmy performance. As the configurations S3 and S4 are used, the unstable area dominated by left and right steering shimmy reduces, the shimmy occurred vehicle velocity range becomes narrower and the maximum LCO magnitude of the front wheel swing motion becomes smaller, which suppresses the vehicle shimmy effectively and clarifies the benefits of the inerter and the necessity of adding the auxiliary spring. In addition, larger inertance of the inerter and smaller stiffness of the auxiliary spring is beneficial to improve the vehicle shimmy performance. The optimized structural parameters of the configurations S3 and S4 are obtained, which maintain the vehicle shimmy system stable, and further shorten the time for the vehicle shimmy system to reach stability. Therefore, the inerter-based suppression mechanism can effectively restrain the vehicle shimmy motion and give guiding significance for the design of vehicle shimmy suppression mechanism. [ABSTRACT FROM AUTHOR]

The issue of adaptive detection for double subspace (DOS) signals under the Gaussian noise background is investigated in this paper. The DOS signal has the special structure where the rows and columns of the matrix-valued signal lie in known subspaces with unknown coordinates. To deal with the DOS signal detection problem, two kinds of Gradient tests are proposed in homogeneous environments and partially homogeneous environments. Remarkably, the Durbin test, as well as its two-step version, is also used for the detector design, which is consistent with the existing methods. To evaluate the performance of the proposed methods, both simulated data and real data collected by IPIX radar are used. The results indicate that the Gradient tests ensure the constant false alarm rate property. Furthermore, the proposed detectors obtain relatively robust characteristics and achieve superior performance to existing competitors in some scenarios. [ABSTRACT FROM AUTHOR]

• The membership function of ratings is devised to build fuzzy profile of ratings. • Fuzzy profiles of users and items are proposed based on fuzzy profile of rating. • The new criteria of detecting natural noise in recommender system is given. • The noisy ratings are corrected based on maximum membership degree principle. A high-quality recommender system (RS) can effectively alleviate information overload by producing recommendations. The quality of the recommender system not only depends on the recommendation algorithm but also on the quality of collected data. Since users are often affected by environmental and accidental factors during the rating process, natural noise is probably brought into the data of RS by non-malicious users, which will lead to deviations in prediction results. In this paper, we propose a scheme based on fuzzy theory to manage the natural noise in RS. We first classify the ratings into three fuzzy categories with variable boundaries. Then, the fuzzy profiles of users and items are built to detect the natural noise in ratings. Finally, once the noisy ratings are detected, we replace them with the rating threshold values according to the Maximum membership principle. The proposed scheme is tested in two benchmark datasets and experimental results verify that the scheme can significantly improve the recommendation quality and has higher efficiency than the schemes based on re-predication. [ABSTRACT FROM AUTHOR]

Substitution box (S-box) is one of the most important components in the design of block ciphers. In this work, different from traditional methods, we convert the construction of n × n S-box into a process of putting n Boolean functions one by one into a container. On this basis, we regard the Boolean function as the chromosome of the S-box and propose a novel genetic algorithm to construct bijective S-boxes with high nonlinearity. In this genetic algorithm, the optimization objective is the nonlinearity of the S-box, and the bijection requirement is converted to its optimization constraint. First, we use a chaotic system to generate the initial S-boxes since chaotic systems have excellent properties like nonlinearity, ergodicity and pseudo-randomness. These initial S-boxes lay a good foundation for subsequent optimization of our algorithm. Then, for the merit of bijectivity and nonlinearity, we elaborately design the crossover and mutation operator of the genetic algorithm to improve the capability of generating bijective S-boxes with high nonlinearity. Under the proposed framework, two theorems can be proven, which imply that the proposed solution ensures bijection and high nonlinearity of the generated S-box. Further experimental analyses corroborate that our method is an effective way for constructing bijective S-boxes with high nonlinearity. [ABSTRACT FROM AUTHOR]

• We design AnD as an alternative MaOEA, which has a simple structure, few parameters, and no complicated operators. More importantly, AnD is different from existing methods: it does not use dominance rules, weight vectors/reference points, and indicators. • To the best of our knowledge, it is the first attempt to effectively combine vector angle with shift-based density estimation for solving MaOPs, by making use of their complementary properties. • We compared AnD with other seven state-of-the-art MaOEAs on a variety of benchmark test problems with up to 15 objectives. The results provide evidence that AnD can achieve highly competitive performance. • AnD has been further extended to solve constrained MaOPs with promising performance. Evolutionary many-objective optimization has been gaining increasing attention from the evolutionary computation research community. Much effort has been devoted to addressing this issue by improving the scalability of multiobjective evolutionary algorithms, such as Pareto-based, decomposition-based, and indicator-based approaches. Different from current work, we propose an alternative algorithm in this paper called AnD, which consists of an an gle-based selection strategy and a shift-based d ensity estimation strategy. These two strategies are employed in the environmental selection to delete poor individuals one by one. Specifically, the former is devised to find a pair of individuals with the minimum vector angle, which means that these two individuals have the most similar search directions. The latter, which takes both diversity and convergence into account, is adopted to compare these two individuals and to delete the worse one. AnD has a simple structure, few parameters, and no complicated operators. The performance of AnD is compared with that of seven state-of-the-art many-objective evolutionary algorithms on a variety of benchmark test problems with up to 15 objectives. The results suggest that AnD can achieve highly competitive performance. In addition, we also verify that AnD can be readily extended to solve constrained many-objective optimization problems. [ABSTRACT FROM AUTHOR]

• Forecasting ENSO using 12 consecutive months of ocean data. • Recombining CMIP datasets using a genetic algorithm. • Improving attention mechanisms for regression problems. • Learning spatio-temporal data using a multi-module combined deep learning model. • Effective forecast ENSO can be up to 20 months. El Niño-Southern Oscillation (ENSO) has a profound impact on global climate, and the ability to forecast it effectively over the long term is essential. In recent years, deep learning methods have demonstrated superior prediction outcomes compared to conventional numerical models. However, due to limited observational data, most of these deep learning methods learn information from simulation data derived from physical models, and ensuring the quality of such simulation data can prove challenging. As a result, the models in CMIP5/6 were recombined using genetic algorithms (GAs) to create our training dataset. A deep learning model was then used to learn features from the output of these combined CMIP models so that these physical numerical models can complement each other. To address the issue of inadequate spatiotemporal feature extraction present in many deep learning methods, we devised an ENSO deep learning regression model. An improved self-attention mechanism was introduced into the convolutional LSTM (long short-term memory) network to enable our model to better extract local and global spatiotemporal features. With our method and model, we were able to obtain less erroneous forecast results, and our method surpassed other state-of-the-art deep learning methods in terms of its capability for long-term forecasting. [ABSTRACT FROM AUTHOR]

Constant beamwidth and robustness are two important features for broadband adaptive beamformers. In this paper, a robust broadband adaptive beamformer with a constant beamwidth for uniform linear arrays is proposed. Benefitting from the idea behind the frequency difference (FD) technique, the array observation in frequency bin f is first multiplied by the conjugate form of a reference array output in frequency bin f + f 0 , which is constructed with a given Gaussian random sequence from the looking direction. In this manner, a frequency-invariant property is obtained by mapping the frequency band of interest to a selected frequency bin f 0. To improve the robustness of the proposed method, an iterative method with adaptive uncertainty in the steering vector (SV) is applied to the equivalent array output after the FD operation. The convergence can be accelerated by scaling the uncertainty level of the SV. Due to the FD technique, the proposed method adaptively filters the signal of interest in the FD domain. The effectiveness of the proposed method is verified by numerical simulation. [ABSTRACT FROM AUTHOR]

This research examines the geometrically nonlinear free vibrations of a type of sandwich plate. This plate consists of an anisogrid lattice core and two nanocomposite face sheets. The lattice core is made up of a set of straight and oblique ribs with rectangular cross-sections that meet at nodes that are not all in the same place (anisogrid nodes). The nanocomposite skins are reinforced with carbon nanotubes (CNTs) based on the various functionally graded models. The displacement field of the sandwich plate is estimated based on the third-order shear deformation plate theory. Also, the nonlinear von-Kármán strain–displacement relations are used. Based on the Hooke and Hamilton laws, the motion equations of the system for nonlinear free vibrations are derived in a weak form. Then, the nodal weak formulation method based on the Lagrange interpolation functions and Gauss–Lobatto–Chebyshev node distribution, for the first time, is employed to calculate the time-dependent equations. The residuals of the obtained equations are minimized by the Galerkin method. Next, a displacement control iterative technique is applied to compute the nonlinear frequency of the sandwich plate. The effect of anisogrid lattice core characteristics and nanocomposite face sheets properties on the linear and nonlinear frequencies and also mode shapes are examined in the results. • Sandwich plate with an anisogrid lattice core and FG-CNTRC skins. • A Lagrangian-based weak formulation method. • Large-amplitude nonlinear free vibrations. • Galerkin minimization and iterative displacement control methods. [ABSTRACT FROM AUTHOR]

For computational fluid dynamics (CFD) applications with a large number of grid points/cells, parallel computing is a common efficient strategy to reduce the computational time. How to achieve the best performance in the modern supercomputer system, especially with heterogeneous computing resources such as hybrid CPU+GPU, or a CPU + Intel Xeon Phi (MIC) co-processors, is still a great challenge.An in-house parallel CFD code capable of simulating three dimensional structured grid applications is developed and tested in this study. Several methods of parallelization, performance optimization and code tuning both in the CPU-only homogeneous system and in the heterogeneous system are proposed based on identifying potential parallelism of applications, balancing the work load among all kinds of computing devices, tuning the multi-thread code toward better performance in intra-machine node with hundreds of CPU/MIC cores, and optimizing the communication among inter-nodes, inter-cores, and between CPUs and MICs.Some benchmark cases from model and/or industrial CFD applications are tested on the Tianhe-1A and Tianhe-2 supercomputer to evaluate the performance. Among these CFD cases, the maximum number of grid cells reached 780 billion. The tuned solver successfully scales up to half of the entire Tianhe-2 supercomputer system with over 1.376 million of heterogeneous cores. The test results and performance analysis are discussed in detail. [ABSTRACT FROM AUTHOR]

Nonparametric density estimation is studied for spherical data that may arise in many scientific and practical fields. In particular, nonparametric mixture models based on likelihood maximization are used. A nonparametric mixture has component distributions mixed together with a mixing distribution that is completely unspecified and needs to be determined from data. For mixture components, a two-parameter distribution family can be used, with one parameter as the mixing variable and the other to control the smoothness of the density estimator. For example, the popular von Mises-Fisher distributions can be readily used for this purpose. Numerical studies with various spherical data sets show that the resultant mixture-based density estimators are strong competitors with the best of the other density estimators. [ABSTRACT FROM AUTHOR]

In the neighborhood-based Collaborative Filtering (CF) algorithms, the user similarity has an important effect on the result of CF. In order to evaluate the user similarity comprehensively and objectively, we proposed a hybrid model. In the model, an item similarity measure is designed based on the Kullback–Leibler (KL) divergence, which is used as a weight to correct the output of an adjusted Proximity–Significance–Singularity model. Meanwhile, a user preference factor and an asymmetric factor are considered in our model to distinguish the rating preference between difference users and improve the reliability of the model output. The tests on different datasets show that the proposed user similarity model is suitable for the sparse data and effectively improves the prediction accuracy and the recommendation quality. [ABSTRACT FROM AUTHOR]

Many electrical systems can be characterized more authentically by fractional order dynamic systems. The Caputo–Fabrizio and the Atangana–Baleanu fractional derivatives have solved the singularity problem in the Caputo derivative. This work uses Caputo–Fabrizio and Atangana–Baleanu fractional derivatives to model the fractional order Buck-Boost converter in the time domain. On this basis, the mean values of output voltage and inductor current are calculated. The characteristics of Buck-Boost with different orders in different fractional derivatives are analyzed. The results indicate that the Caputo–Fabrizio and Atangana–Baleanu fractional derivatives can be applied to the Buck-Boost converter to increase the design degree of freedom, which provides more choices for describing the nonlinear characteristics of the system. • C–F and A–B derivatives are applied to Buck-Boost converters. • The effects of fractional order on output voltage and current are analyzed. • The differences between the two definitions of converters are analyzed. [ABSTRACT FROM AUTHOR]

Complex spatiotemporal dynamical behaviors of a diffusive predator–prey system with Michaelis–Menten type functional response and linear harvesting are investigated. Firstly, the critical conditions for the occurrence of Turing instability, which are necessary and sufficient, are derived in a novel way. Then, the existence conditions of codimension-1 Turing bifurcation, Hopf bifurcation, and codimension-2 Turing–Turing bifurcation, Turing–Hopf bifurcation are established. Furthermore, the detailed bifurcation set is given by calculating the amplitude equation with the method of the multiple time scale near the Turing–Hopf bifurcation. We find that the system may exhibit nonconstant steady-state solutions, spatially homogeneous periodic solutions, and spatially inhomogeneous periodic solutions, which can be verified by a series of numerical simulations. These investigations not only explain the effect of diffusion and harvesting on the dynamic behavior of the system, but also reveal the mechanism of spatiotemporal complexity in the diffusive predator–prey system. • Effects of harvesting rate and diffusion coefficient on dynamics are examined • The necessary and sufficient conditions for occurring Turing instability are derived • The existence of multiple bifurcations is established • The dynamics near Turing–Hopf bifurcation are explored [ABSTRACT FROM AUTHOR]

Nonlinear energy sink (NES) is a lightweight vibration absorber that is coupled to linear primary structure for passive vibration mitigation. In this work, we aim to investigate the effects of geometrically nonlinear damping on the capacity of multiple-degree-of-freedom (MDOF) NES to mitigate forced responses of the impulsively and harmonically loaded linear oscillator (LO). For the system under applied shock excitation, extensive simulation results show that the internal use of nonlinear damping enables the MDOF NES to rapidly and effectively absorb, transfer and dissipate the shock-induced energy for a broad range of initially imparted energies, particularly for the high or very high energy levels. The effectiveness of the optimized MDOF NES is further improved since the large-amplitude oscillations of the LO are reduced to a sufficiently low level during initial regime of motion. When the LO is subjected to harmonic excitations, the analytical study is performed to obtain the slow invariant manifold (SIM) by means of complexification-averaging (CX-A) method. The complex geometry of SIM reveals the energy transfer paths when the system reaches steady state. The global system behavior (strongly modulated response or periodic oscillation regimes) is analytically predicted by the singular points and ordinary equilibrium points, and a close match is achieved between theoretical analysis and numerical results. It is found that the proposed MDOF NES with nonlinear damping can eliminate the upper closed high-amplitude isolated branch, and the frequency bandwidth of multiple steady-state responses also decreases, the robustness and capacity of vibration attenuation by the proposed NES is dramatically enhanced. The findings in this work facilitate the design and broad applications in diverse engineering fields for the protection and safe operation of mechanical structures. • The dynamics of the MDOF system with geometrically nonlinear damping are investigated. • The mitigation performance of the proposed MDOF NES is enhanced for high energy levels. • The complex geometry of the SIM provides a general view of global system behavior. • The addition of nonlinear damping can completely eliminate the upper isolated high-amplitude branch. [ABSTRACT FROM AUTHOR]

Under investigation in this paper is an integrable equation which can describe the localized magnetization with spin torque under the long-wavelength approximation. In order to obtain the rogue wave solutions, a new Lax pair is derived. Infinitely-many conservation laws are also constructed. Based on the generalized Darboux transformation, the first-, second- and third-order rogue wave solutions are derived. Property of the rogue waves are analyzed and influence of parameters α, β and separating function f (ϵ) on the rogue waves and spatial-temporal structures are also discussed (the meaning of α and β can be found in the paper). For the case of f ( ϵ ) = 0 , the modulus of the k th-order rogue wave ( k = 1 , 2 , 3 ) is irrelevant to parameter α . Parameter β influences the spatial-temporal range where the rogue wave appears. Spatial-temporal range enlarges with the increase of β . In addition, β also produces a skew angle and the skew angle rotates in the counter clockwise direction with the increase of β. f (ϵ) influences the spatial-temporal structures of the second- and third-order rouge waves. If f (ϵ) ≠ 0, the second-order rogue wave will split into three single first-order rouge waves and the triangular pattern can be formed, while the third-order rogue wave will split into six ones and the triangular pattern and pentagon pattern can be formed. The linear stability analysis is carried out, which shows that the modulation instability process is influenced by the amplitude of the harmonic wave and the wave number. [ABSTRACT FROM AUTHOR]

Based on the data from the FY and GOES satellites, 44 anomalies of one Chinese geosynchronous satellite related to space environment that occurred from 2010 to 2015 are studied, mainly focusing on the time profiles of the anomalies, the accompanying environment phenomena and the characteristics of the space particle environment during the anomalies. Furthermore, the maximum electric field amplitude inside the dialectic using DICTAT model is calculated. The results show that; (1) The internal charge might be the reason of the anomalies on March 17. (2) Most anomalies accrue at day time (up to 79. 5% of the total anomalies). This is consistent with the local time distribution of the flux of the energetic electrons (>2MeV). (3) 25 of the 44 anomalies (57%) are accompanied by the energetic electron storm. The 50% quartile of the energetic electron (>2MeV) flux begins to increase significantly 3-4 days before the anomaly, and the hazard quotient of the internal charging ZIC becomes yellow two days before the anomaly. The 75% quartile of the energetic electron (>2MeV) flux begins to increase significantly 4 days before the anomaly, and the hazard quotient of the internal charging ZIC becomes red twice two days before the anomaly. (4) In categories II, III, and IV, the maximum electric field inside the dietetic simulated from DICTAT reaches and maintains larger than 106V.m-1 after 19.2, 50.4 and 9. 8 hours, which has the potential hazard of the internal discharging. The internal charging caused by the energetic electrons could be the main reason of the 44 anomalies. [ABSTRACT FROM AUTHOR]

We design a new improved signal space alignment scheme in MIMO Y channel where one of K source nodes sends K − 1 independent messages to the other nodes and each message achieves the degrees of freedom (DoF) of d . The key is to let the messages to be exchanged by applying improved signal space alignment for network coding and interference cancellation when antennas configuration extends to N > 2 M , where N and M denote the number of antennas at the relay and each source respectively. It is not feasible for the traditional signal space alignment to achieve the same DoF under this antenna number configuration. Moreover, we discuss the ill-conditioned channel to improve the system performance for Zero Forcing decoder. The simulations show that our proposed scheme achieves DoF of d K ( K − 1 ) and improves system performance reliability. [ABSTRACT FROM AUTHOR]

Least squares support vector machine (LS-SVM) for nonlinear regression is sensitive to outliers in the field of machine learning. Weighted LS-SVM (WLS-SVM) overcomes this drawback by adding weight to each training sample. However, as the number of outliers increases, the accuracy of WLS-SVM may decrease. In order to improve the robustness of WLS-SVM, a new robust regression method based on WLS-SVM and penalized trimmed squares (WLSSVM–PTS) has been proposed. The algorithm comprises three main stages. The initial parameters are obtained by least trimmed squares at first. Then, the significant outliers are identified and eliminated by the Fast-PTS algorithm. The remaining samples with little outliers are estimated by WLS-SVM at last. The statistical tests of experimental results carried out on numerical datasets and real-world datasets show that the proposed WLSSVM–PTS is significantly robust than LS-SVM, WLS-SVM and LSSVM–LTS. [ABSTRACT FROM AUTHOR]

In this paper, a frequency diverse array multi-input multi-output (FDA-MIMO) radar is used for moving target detection in unknown Gaussian noise. To solve the detection problem, we adopt the generalized likelihood ratio test (GLRT) and use the training data to estimate the unknown noise covariance matrix. We derive the GLRT both for the case of unknown target velocity and the case of known target velocity. We also derive the analytical expressions for the probabilities of detection (PDs) and the probabilities of false alarm (PFAs), which indicate that the proposed detectors have constant false alarm rate (CFAR) properties. Theoretical and simulation results show that the proposed detectors can provide higher PDs than the existing detectors which do not utilize training data. [ABSTRACT FROM AUTHOR]

To improve the numerical simulation accuracy of predicting the cavitating flow in centrifugal pumps, a new developed cavitating flow computational model, named two-phase three-component computational model, is proposed. To evaluate its performance, the comparisons are carried out among CFX default cavitating flow computational model, the optimal computational model and the proposed model, concerning a centrifugal pump. Meanwhile, the experiments are conducted to validate the calculations, including pump head drop test and cavitating flow visualization at the pump inlet. The results show that the two-phase three-component computational model has better performance both on predicting pump head drop and bubble structure. It is observed in the current work that the sheet cavity firstly occurs on the leading edge of the suction side of the impeller. With the cavitation number decreasing, the cavity length grows rapidly along the suction side towards impeller outlet. Simultaneously, the cavity starts to extend to the pressure side. Based on the analysis of the blade pressure load on the blade surface and total pressure coefficient distribution in the channel, it is found that the cavitation has great effect on blade pressure load. Besides, the total pressure coefficient drops mainly take place on the upstream, that is to say, the growth of cavitation affects downstream rarely. [ABSTRACT FROM AUTHOR]

Nonparametric mixture models are commonly used to estimate the number of unobserved species for their robustness of modelling heterogeneity. In particular, Poisson mixtures are popular in this regard, but they are also known to have the boundary problem that causes unstable estimation. A family of shape-restricted distributions known as discrete k -monotone distributions is proposed for species richness estimation. These distributions are in fact also nonparametric mixtures and can thus be fitted rapidly via some algorithms that are made available recently. As shown by empirical studies, as compared with Poisson mixtures, their use avoids the boundary problem and gives more stable and more accurate estimates. [ABSTRACT FROM AUTHOR]

Voice transformation, which has been integrated in many audio (speech) processing tools, is a common operation to change a person's voice and to conceal his or her identity. It can deceive human beings and automatic speaker verification (ASV) systems easily, and thus it presents threats to security. Until now, few efforts have been reported on the recognition of hidden speakers from such disguised voices. In this paper, we propose concrete countermeasures to erase the disguise effects and verify the speaker's identity from voice transformation disguised voices. The proposed system is tested by commonly used audio editors and voice transformation algorithms. The experimental results show that the performances of baseline ASV system without our proposed countermeasures are entirely destroyed by voice transformation disguise with equal error rates (EERs) higher than 40%; while with our proposed countermeasures, the verification performances are improved significantly with EERs lowered to 3%–4%. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to study the unsteady caivitating flows in centrifugal pump, especially for improving the turbulence model to obtain highly resolution results-capable of predicting the cavitation inception, shedding off and collapse procedures. Design/methodology/approach – Both numerical simulations and experimental visualizations were performed in the present paper. An improved RCD turbulence models was proposed by considering three corrected methods: the rotating corrected method, the compressible corrected method and the turbulent viscosity corrected method. Unsteady RANS computations were conducted to compare with the experiments. Findings – The comparison of pump cavitation performance showed that the RCD turbulence model obtained better performance both in non-cavitation and cavitation conditions. The visualization of the cavitation evolution was recorded to validate the unsteady simulations. Good agreement was noticed between calculations and visualizations. It is indicated the RCD model can successfully capture the bubbles detachment and collapse at the rear of the cavity region, since it effectively reduces the eddy viscosity in the multiphase region of liquid and vapor. Furthermore, the eddy viscosity, the instantaneous pressure and density distribution were investigated. The effectiveness of the compressibility was found. Meanwhile, the influence of the rotating corrected method on prediction was explored. It is found that the RCD model solved more unsteady flow characteristics. Originality/value – The current work presented a turbulence model which was much more suitable for predicting the cavitating flow in centrifugal pump. [ABSTRACT FROM AUTHOR]

In order to ensure a proper averaged temperature and a temperature gradient of an ultraviolet imaging spectrometer, the imaging spectrometer situated in space environment is analyzed. According to its optic-mechanical-electronic characteristics, both active thermal control scheme and passive thermal control scheme for imaging spectrometer are designed. Firstly, the thermal design guidelines of the imaging spectrometers are summarized, and both active thermal control scheme and passive thermal control scheme are introduced. The worst-case analysis method is used to analyze temperature measurement accuracy of temperature measurement circuit of the active thermal control system. Then according to the demand for the active thermal control scheme, both hardware and control strategy of the active thermal control system are designed and realized. Finally, a verification experiment of the active thermal control system is made . Experimental and analysis results indicate that the temperature measurement accuracy of the system is better than ≤ ±0. 5°C, and the active thermal control system can ensure 13° ~ 18°C averaged temperature of ultraviolet limb spectrometer and 8°C ~ 18°C averaged temperature of ultraviolet ring imager, thus meeting the thermal control system requirements. In conclusion, the active thermal control scheme is feasible and reasonable, and it can meet the requirement for high reliability. [ABSTRACT FROM AUTHOR]

Abstract: The fact that a -monotone density can be defined by means of a mixing distribution makes its estimation feasible within the framework of mixture models. It turns the problem naturally into estimating a mixing distribution, nonparametrically. This paper studies the least squares approach to solving this problem and presents two algorithms for computing the estimate. The resulting mixture density is hence just the least squares estimate of the -monotone density. Through simulated and real data examples, the usefulness of the least squares density estimator is demonstrated. [Copyright &y& Elsevier]

Aiming at practical requirements for the received sharply-attenuated weak signal process in space TT&C communication system, an implementation technique of low-complexity Turbo decoder for spacecraft is studied. A modified Turbo decoder structure implemented on FPGA is presented by adopting the Log-MAP algorithm based on approximation by broken line. First, much computation in branch metric of iterative decoding is simplified to save storage resources. Next, a semi-parallel processing is proposed to optimize the whole hardware architecture and raise decoding tate. Through the interleave and generator matrix recommend by CCSDS, simulation and measured results show that storage process complexity is cut by 29.6% without more slice resources and the coding gain reaches 9.9dB at the BER of 10-6. This decoder has been successfully applied to an aerospace engineering. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a parallelization for a large scale CFD application with mixed one-to-one multiblock/overset structured grid was implemented into our in-house TH-CFD code running on Tianhe-1A supercomputer system. Strategies at multiple software levels were employed in a mutually supportive way for overall performance enhancement, and they include grid repartition, MPI+OpenMP hybrid programming, use of multiple programming languages adaptively for different software components, and adaptive thread scheduling for load balancing. Numerical testing was carried out and the testing results have shown high efficiency of our parallel implementation, supporting the effectiveness of our parallelization strategies. [Copyright &y& Elsevier]

An H-mode ionization system was designed for the requirements of low power consumption and low electromagnetic interference of the passive spaceborne hydrogen maser, which adopting a planar rolled coil antenna to supply power. And a mathematic model of ionization was built. Firstly, the distribution model of electromagnetic field in the ionization bubble and the ionization mechanism of the certain method were deduced from the Maxwell equations. And then, the ionization puncture condition criterion and its mathematic model were acquired. Finally, parameters of ionization device were optimized by the criterion equation. Both simulation and measurement show that the ionization model is effective, and the optimized design parameters have improved the performance of power consumption and electromagnetic interference, and the total DC power can be less than 2 W. [ABSTRACT FROM AUTHOR]

To meet the testing requirements for the stability of the zero value about satellite-based spread-spectrum transponder and the TT&C earth station, the stabilization technique of zero value about spread-spectrum TT&C simulator is studied. A structure of TT&C simulator for correcting the zero value in the real-time by broadband self-closed-loop calibration channel is proposed. In this structure, output power of transmitting signal can be regulated by numerical control, the time delay of both power conditioning module and calibration channel is calibrated and stored in advance, and the stability of the zero value less than 0.1 m is achieved. The experimental results verify the validity of this study, and it has been successfully applied to an aerospace engineering. [ABSTRACT FROM AUTHOR]

The energy of DSSS signal cannot be accumulated effectively under the condition of long-term integration and high dynamic scenarios, to solve this problem, a Double Block Zero Padding (DBZP) based motion compensation algorithm is proposed. The Keystone transform is used to process the multiplication of the input data and the local PN code in the frequency domain, and the range walk of PN code autocorrelation peak is eliminated. Then segmentation dechirp is used to make compensation for Doppler expansion and PN code autocorrelation peak curvature simultaneously. Finally, signal is coherently accumulated. Simulation results show that the DBZP based motion compensation algorithm can eliminate dynamic effect effectively, significantly reduce the accumulated loss, and thereby improve the acquisition sensitivity. The algorithm can be widely used in high dynamic weak target acquisition based on DSSS signal. [ABSTRACT FROM AUTHOR]

Abstract: To overcome the main drawbacks of (μ + λ)-constrained differential evolution ((μ + λ)-CDE) [45], this paper proposes an improved version of (μ + λ)-CDE, named ICDE, to solve constrained optimization problems (COPs). ICDE mainly consists of an improved (μ + λ)-differential evolution (IDE) and a novel archiving-based adaptive tradeoff model (ArATM). Therein, IDE employs several mutation strategies and the binomial crossover of differential evolution (DE) to generate the offspring population. Moreover, a new mutation strategy named “current-to-rand/best/1” is proposed by making use of the current generation number in IDE. Since the population may undergo three situations during the evolution (i.e., the infeasible situation, the semi-feasible situation, and the feasible situation), like (μ + λ)-CDE, ArATM designs one constraint-handling mechanism for each situation. However, unlike (μ + λ)-CDE, in the constraint-handling mechanism of the infeasible situation, the hierarchical nondominated individual selection scheme is utilized, and an individual archiving technique is proposed to maintain the diversity of the population. Furthermore, in the constraint-handling mechanism of the semi-infeasible situation, the feasibility proportion of the combined population consisting of the parent population and the offspring population is used to convert the objective function of each individual. It is noteworthy that ICDE adopts a fixed tolerance value for the equality constraints. In addition, in this paper two criteria are used to compute the degree of constraint violation of each individual in the population, according to the difference among the violations of different constraints. By combining IDE with ArATM, ICDE has the capability to maintain a good balance between the diversity and the convergence of the population during the evolution. The performance of ICDE has been tested on 24 well-known benchmark test functions collected for the special session on constrained real-parameter optimization of the 2006 IEEE Congress on Evolutionary Computation (IEEE CEC2006). The experimental results demonstrate that ICDE not only overcomes the main drawbacks of (μ + λ)-CDE but also obtains very competitive performance compared with other state-of-the-art methods for constrained optimization in the community of constrained evolutionary optimization. [Copyright &y& Elsevier]

Abstract: Quadratic loss is predominantly used in the literature as the performance measure for nonparametric density estimation, while nonparametric mixture models have been studied and estimated almost exclusively via the maximum likelihood approach. In this paper, we relate both for estimating a nonparametric density function. Specifically, we consider nonparametric estimation of a mixing distribution by minimizing the quadratic distance between the empirical and the mixture distribution, both being smoothed by kernel functions, a technique known as double smoothing. Experimental studies show that the new mixture-based density estimators outperform the popular kernel-based density estimators in terms of mean integrated squared error for practically all the distributions that we studied, thanks to the substantial bias reduction provided by nonparametric mixture models and double smoothing. [Copyright &y& Elsevier]

In the course of the reentry of hypersonic vehicles, many difficulties such as strong coupling effects, drastic external disturbances, and large uncertainties of aerodynamic parameters make the design of guidance and control system very challenging. In response to that, the original nonlinear dynamics are transformed into the MIMO characteristic model in the form of two-order time-varying difference equations, and a decentralized adaptive attitude controller is designed. At last, the stability is proved and some simulations are presented. Because the closed-loop system is a very complex hybrid system, and a valid stability analysis has been absent in the characteristic modeling theory, the method proposed in this paper is used to absolutely handle the stability problem of MIMO system with a relative degree of two and without internal dynamics. [ABSTRACT FROM AUTHOR]

Rocket nozzle is a key structural part of high-thrust liquid rocket engine. There are a hundreds of cooling channels around the nozzle, to ensure the reliable cooling and preheat the fuel. However, it is very difficult to machine the cooling channel due to large size, complex profile, low rigidity, etc. In this article, an integrated digital method for cooling channel machining composed of profile measuring, data processing and channel milling is proposed. Because of large difference between the actual contour and the design model, the channel bottom should be redesigned by using the measured geometric information. Therefore, the varying-thickness and varying-depth cooling channel of nozzle with high order contour or parametric shapes can be machined. Further, a special digital machining system is developed based on an open numerical control platform for the dual-channel vertical milling machine. Finally, an experiment utilizing a typical rocket nozzle is implemented to verify the feasibility of the system. It has been proved that the digital machining system can meet the machining requirements for liquid rocket engine nozzle. [ABSTRACT FROM AUTHOR]

Abstract: The small sample size problem is often encountered in pattern recognition. Several algorithms for null space based linear discriminant analysis (NLDA) have been developed to solve the problem. However, these algorithms for NLDA have high computational cost. In this paper, we simplify the recently proposed algorithm for NLDA in Chu and Thye (2010) with the assumption that all the training data vectors are linearly independent and propose a new and fast algorithm for NLDA. Our main observation is that two steps of economic QR decomposition with column pivoting can be replaced by one step of economic QR decomposition without column pivoting if the related matrix is of full column rank. The main features of our algorithm for NLDA include: (i) our NLDA algorithm is carried out by only one step of economic QR decomposition and does not compute any singular value decomposition (SVD) when all the training data vectors are linearly independent; (ii) the main cost of our method is the cost of an economic QR decomposition of an m ×(n −1) matrix, here m is the dimension of the training data and n is the number of samples. Our method is a fast one. Experimental studies on ORL, FERET and PIE face databases demonstrate the effectiveness of our new algorithm for NLDA. [Copyright &y& Elsevier]

Abstract: Differential evolution (DE) is a class of simple yet powerful evolutionary algorithms for global numerical optimization. Binomial crossover and exponential crossover are two commonly used crossover operators in current popular DE. It is noteworthy that these two operators can only generate a vertex of a hyper-rectangle defined by the mutant and target vectors. Therefore, the search ability of DE may be limited. Orthogonal crossover (OX) operators, which are based on orthogonal design, can make a systematic and rational search in a region defined by the parent solutions. In this paper, we have suggested a framework for using an OX in DE variants and proposed OXDE, a combination of DE/rand/1/bin and OX. Extensive experiments have been carried out to study OXDE and to demonstrate that our framework can also be used for improving the performance of other DE variants. [Copyright &y& Elsevier]

Abstract: In this paper, the parallel structure of hash function is analyzed. Then, a parallel hash function based on coupled map lattices is proposed. The message is partitioned into blocks with fixed length. The message block is firstly processed by the hash round function. The final hash value is the mixed result of all the outputs of the hash round functions. The hash round functions are mainly implemented by the coupled map lattices and can work in a parallel mode, which guarantees good security and high efficiency. Theoretic analyses and numerical simulations both show that the proposed hash algorithm possesses good statistical properties, strong collision resistance and high efficiency. These properties make it a good candidate for hash on parallel computing platform. [Copyright &y& Elsevier]

It is known that the sugar chains of steroidal saponins play an important role in the biological and pharmacological activities. In order to synthesize steroidal saponins with novel sugar chains in one step for further studies on pharmacological activity, we here describe the glucosylation of steroidal saponins, and 5 compounds, timosaponin AIII (1), saponin Ta (2), saponin Tb (3), trillin (4) and cantalasaponin I (5), were converted into their glucosylated products by Toruzyme 3.0 L, a cyclodextrin glucanotransferase (CGTase). 12 glucosylated products were isolated and their structures elucidated on the basis of spectral data; they were all characterized as new compounds. The results showed that Toruzyme 3.0 L had the specific ability to add the α-D-glucopyranosyl group to the glucosyl group linked at the sugar chains of steroidal saponins, and the glucosyl group was the only acceptor. This is the first report of steroidal saponins with different degrees of glucosylation. The substrates and their glucosylated derivatives were evaluated for their cytotoxicity against HL-60 human promyelocytic leukemia cell by MTT assay. The substrates all exhibited high cytotoxicity (IC50 < 10 �mol/L), excluding compound 5 (IC50 > 150 �mol/L), and the cytotoxicity of most of the products showed no obvious changes compared with those of their substrates. [ABSTRACT FROM AUTHOR]

Abstract: The Fisher scoring method is widely used for likelihood maximization, but its application can be difficult in situations where the expected information matrix is not available in closed form or when parameters have constraints. In this paper, we describe an interpolation family that generalizes the Fisher scoring method and propose a general Monte Carlo approach that makes these generalized methods also applicable in such situations. With this approach, random samples are generated from the iteratively estimated models and used to provide estimates of the expected information. As a result, the likelihood function can be optimized by repeatedly solving weighted linear regression problems. Specific extensions of this general approach to fitting multivariate normal mixtures and to fitting mixed-effects models with a single discrete random effect are also described. Numerical studies show that the proposed algorithms are fast and reliable to use, as compared with the classical expectation–maximization algorithm. [Copyright &y& Elsevier]

Abstract: In this study, we shall be concerned with a non-autonomous second-order Hamiltonian system. Some criteria for guaranteeing the existence and uniqueness of T-periodic classical solution of this system are presented by employing the least action principle, the Saddle Point Theorem and some analysis techniques. [Copyright &y& Elsevier]

Abstract: A novel hash algorithm based on a spatiotemporal chaos is proposed. The original message is first padded with zeros if needed. Then it is divided into a number of blocks each contains 32bytes. In the hashing process, each block is partitioned into eight 32-bit values and input into the spatiotemporal chaotic system. Then, after iterating the system for four times, the next block is processed by the same way. To enhance the confusion and diffusion effect, the cipher block chaining (CBC) mode is adopted in the algorithm. The hash value is obtained from the final state value of the spatiotemporal chaotic system. Theoretic analyses and numerical simulations both show that the proposed hash algorithm possesses good statistical properties, strong collision resistance and high efficiency, as required by practical keyed hash functions. [Copyright &y& Elsevier]

Abstract: In recent years, a number of image encryption algorithms based on the permutation–diffusion structure have been proposed. However, the control parameters used in the permutation stage are usually fixed in the whole encryption process, which favors attacks. In this paper, a chaos-based image encryption algorithm with variable control parameters is proposed. The control parameters used in the permutation stage and the keystream employed in the diffusion stage are generated from two chaotic maps related to the plain-image. As a result, the algorithm can effectively resist all known attacks against permutation–diffusion architectures. Theoretical analyses and computer simulations both confirm that the new algorithm possesses high security and fast encryption speed for practical image encryption. [Copyright &y& Elsevier]

Abstract: In this paper, a block encryption scheme based on dynamic substitution boxes (S-boxes) is proposed. Firstly, the difference trait of the tent map is analyzed. Then, a method for generating S-boxes based on iterating the tent map is presented. The plaintexts are divided into blocks and encrypted with different S-boxes. The cipher blocks are obtained by 32 rounds of substitution and left cyclic shift. To improve the security of the cryptosystem, a cipher feedback is used to change the state value of the tent map, which makes the S-boxes relate to the plaintext and enhances the confusion and diffusion properties of the cryptosystem. Since dynamic S-boxes are used in the encryption, the cryptosystem does not suffer from the problem of fixed structure block ciphers. Theoretical and experimental results indicate that the cryptosystem has high security and is suitable for secure communications. [Copyright &y& Elsevier]

Abstract: An algorithm for constructing one-way hash function based on spatiotemporal chaos is proposed. A two-dimensional coupled map lattices (2D CML) with parameters leading to the largest Lyapunov exponent is employed. The state of the 2D CML is dynamically determined by its previous state and the message bit at the corresponding positions. The hash value is obtained by a linear transform on the final state of the 2D CML. Theoretical analysis and computer simulation indicate that our algorithm has good statistical properties, strong collision resistance and high flexibility. It is practical and reliable, with high potential to be adopted as a strong hash function for providing data integrity. [Copyright &y& Elsevier]

Abstract: A general technique is proposed for efficient computation of the nonparametric maximum likelihood estimate (NPMLE) of a survival function. The main idea is to include a new support interval that has the largest gradient value between inclusively every two neighbouring support intervals in the support set at each iteration. It is thus able to expand the support set exponentially fast during the initial stage of computation and tends to produce the same support set of the NPMLE afterward. The use of the proposed technique needs to be combined with an algorithm that can effectively find and remove redundant support intervals, for example, the constrained Newton method, the iterative convex minorant algorithm and the subspace-based Newton method. Numerical studies show that the dimension-reducing technique works very well, especially for purely interval-censored data, where a significant computational improvement via dimension reduction is possible. Strengths and weaknesses of various algorithms are also discussed and demonstrated. [Copyright &y& Elsevier]

Abstract: Minimum disparity estimation is appealing in that the estimates it provides are simultaneously robust and efficient. This paper presents a family of algorithms called iteratively reweighted least integrated squares for minimum disparity computation. This family of algorithms, indexed by a real parameter , approximates the disparity measure by quadratic functions, in a form of integrated weighted squared errors, and minimizes the quadratic functions conveniently by using weighted least squares linear regression algorithms. Among all potential values of , we advocate the use of from the consideration of robust estimation, which results in an algorithm similar in spirit to the Fisher scoring method for maximum likelihood computation. Numerical studies show that the new algorithms, especially the one that uses , give competitive or better performance over the other algorithms available in the literature. [Copyright &y& Elsevier]

Abstract: The Fisher scoring and Gauss–Newton methods are two known methods for maximum likelihood computation. This paper provides a generalization for each method in a unified manner so that they can be used for some difficult maximum likelihood computation, when, for example, there exist constraints on the parameters. A generalized method does not use directly the Newton-type iteration formulas of these methods, but, instead, uses the corresponding quadratic functions transformed from them. It proceeds by repeatedly approximating the log-likelihood function with the quadratic functions in the neighborhoods of the current iterates and optimizing each quadratic function within the parameter space. It is shown that each quadratic function has a weighted linear regression formulation, which can be conveniently solved. This generalization also extends the applicability of the Fisher scoring method to situations when the expected Fisher information matrices are unavailable in closed form. Fast computation can generally be anticipated, owing to their small rates of convergence and a rapid solution of each linear regression problem. While the generalized Gauss–Newton method may sometimes suffer for the so-called large residual problem, the generalized Fisher scoring method has performed consistently well in the numerical experiments we conducted. [Copyright &y& Elsevier]

To understand the relationship between fruit cracking and gene expression patterns, we identified two expansin genes from litchi (Litchi chinensis Sonn.) fruit and then examined their expression profiles in pericarp and aril at different stages of fruit development, using the cracking-resistant cultivar Huaizhi and the cracking-susceptible cultivar Nuomici. Two full-length cDNAs of 1087 and 1010 base pairs encoding expansin, named LcExp1 and LcExp2, were isolated from expanding fruit using RT-PCR and RACE-PCR (rapid amplification of cDNA ends) methods. LcExp1 mRNA could be detected from the early stage of fruit rapid growth (59 days after anthesis). The LcExp1 mRNA increased and reached to the highest level at the end of growth phase (80 days after anthesis) in pericarp of ‘Huaizhi’, while the mRNA could be detected at the stage of rapid fruit growth, then increased slightly and finally kept remained almost constant in the pericarp of ‘Nuomici’. Similar accumulation of LcExp2 mRNA was observed in fruit aril of ‘Nuomici’ and ‘Huaizhi’, whereas LcExp2 accumulated only in pericarp of ‘Huaizhi’ but did not appear in pericarp of ‘Nuomici’. The results indicate that expression of two expansin genes in litchi pericarp are closely associated with fruit growth and cracking. [ABSTRACT FROM AUTHOR]