Lattice-based group signature with verifier-local revocation

Among several post quantum primitives proposed in the past few decades, lattice-based cryptography is considered as the most promising one, due to its underlying rich combinatorial structure, and the worst-case to average-case reductions. The first lattice-based group signature scheme with verifier-local revocation(VLR) is treated as the first quantum-resistant scheme supported member revocation, and was put forward by Langlois et al. This VLR group signature(VLR-GS) has group public key size of O(nm log N log q), and a signature size of O(tm log N log q log β). Nguyen et al. constructed a simple efficient group signature from lattice, with significant advantages in bit-size of both the group public key and the signature. Based on their work, we present a VLR-GS scheme with group public key size of O(nm log q) and signature size of O(tm log q). Our group signature has notable advantages: support of membership revocation, and short in both the public key size and the signature size.     

Serum levels of RBP4 might not be determined by diabetes mellitus but by kidney function and renal replacement therapy

It has been reported that retinol-binding protein 4(RBP4) is associated to adiposity,insulin resistance,and type 2 diabetes.Meanwhile,circulating RBP4 levels are also affected by renal function.The aim of the present study is to investigate whether serum levels of RBP4 are primarily associated with different stages of chronic kidney disease(CKD) or type 2 diabetes,if there is more potential relevance between RBP4 and renal replacement therapy.The serum levels of RBP4 were assessed by commercial competitive enzyme-linked immunosorbent assay(ELISA)kit in 212 patients with the CKD stages 1—5 and in 24 healthy controls,while its correlation with clinical and metabolic parameters was analyzed.The serum level of RBP4 had a strong correlation with estimated glomerular filtration rate(e GFR)(P 0.001).Stratified by e GFR and treatment,no more differences in RBP4 serum concentration were detected between type 2 diabetic and non-diabetic subjects [CKD stages 1—5,non-dialysis(ND),hemodialysis(HD) and peritoneal dialysis(PD);P 0.05 for all].The elevation of RBP4 become higher in HD than in PD and ND in CKD5 patients(P = 0.008 and P = 0.04,respectively),while there was no significant difference between PD and ND groups.Multivariate linear regression analysis demonstrated three independent predictors of e GFR(β =-0.676,P 0.001),C-reactive protein(CRP)(β =-0.573,P 0.001) and creatine(β = 0.509,P = 0.024) in the study population.The study results demonstrated that the serum level of RBP4 was negatively related to the e GFR,whether diabetes mellitus(DM) affected the blood concentration of RBP4 or not.And the serum level of RBP4 exhibited significant difference in different renal replacement therapies.     

Electronic structures and magneto-transport properties of co-based Heusler alloy based magneto-resistance junctions

A direct link between band structure and the ballistic transport property of full-Heusler alloys based Co₂ YZ/Al/Co₂ YZ trilayers (Y = Sc, Ti, V, Cr, Mn and Fe; Z = Al, Si and Ge) has been studied by firstprinciples calculations. It is found that the transport efficiency is determined primarily by three factors related to band structure: the shape of the band crossing Fermi energy E _F, the distance d of the two intersection points of Co₂ YZ and Al at E _F, and the absolute maximum of the energy lying in the E _F-crossing band, |E_max|. The transmission coefficient distribution patterns imply that the affected factor of magneto-resistance (MR) ratio is attributed to the band features around E _F. In general, an intuitively illustrated diagram is proposed to clarify the relationship between the probability of electron transition and the current magnitude.     

Combustion optimization model for NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> reduction with an improved particle swarm optimization

Abstract: This paper focuses on the combustion optimization to cut down NO _x emission with a new strategy. Firstly, orthogonal experimental design (OED) and chaotic sequences are introduced to improve the performance of particle swarm optimization (PSO). Then, a predicting model for NO _x emission is established on support vector machine (SVM) whose parameters are optimized by the improved PSO. Afterwards, a new optimization model considering coal quantity and air quantity along with the traditional optimization variables is established. At last, the operating parameters are optimized by the improved PSO to cut down the NO _x emission. An application on 600MW unit shows that the new optimization model can cut down NO _x emission effectively and maintain the load balance well. The NO _x emission optimized by the improved PSO is lowest among some state-of-the-art intelligent algorithms. This study can provide important guides for the low NO _x combustion in the power plant.     

Research on Nonlinear Dynamic Simulation and Fatigue Reliability Life Prediction for Synthesis Transmission System of Self-Propelled Gun

Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain, a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear’s complicated torque provided by virtual prototype. The gear’s P-S_a-S_m-N curved cluster can be simulated based on material’s P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear’s fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear’s danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.     

Sliding mode robust fault-tolerant control for uncertain systems with time delay

Considering the modeling uncertainties and external disturbance, a kind of sliding mode robust H∞fault-tolerant control method for time delay system with actuator fault is proposed. The upper-bound of the uncertainties is considered as a known constant, while the upper-bound of the actuator fault is unknown. A sufficient condition for the existence of an integral sliding mode dynamics is given in terms of linear matrix inequality(LMI). A novel adaptive law is given to estimate the unknown upper-bound of faults. On this basis, a type of sliding mode robust H∞fault-tolerant control law is designed to guarantee the asymptotic stability and the H_∞ performance index of the system. Finally, the simulation on quad-rotor semi-physical platform demonstrates the reliability and validity of the method.     

Study on Oxidation Activity of CuCeZrO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> Doped with K for Diesel Engine Particles in NO/O<Subscript>2</Subscript>

CuCeZrO_x and KCuCeZrO_x catalysts were synthesized and coated on the blank diesel particulate filter (DPF) substrate and a particulate matter (PM) loading apparatus was used for soot loading. The catalytic performances of soot oxidation were evaluated by temperature programmed combustion (TPC) test and characterization tests were conducted to investigate the physicochemical properties of the catalysts. The reaction mechanism in the oxidation process was analyzed with diffuse reflectance infrared Fourier transform spectroscopy. The results demonstrated that CuCeZrO_x catalyst exhibited high activities of soot oxidation at low temperature and the best results have been attained with Cu_0.9Ce_0.05Zr_0.05O_x over which the maximum soot oxidation rate decreased to 410 °C. Characterization tests have shown that catalysts containing 90% Cu have uniformly distributed grains and small particle sizes, which provide excellent oxidation activity by providing more active sites and forming a good bond between the catalyst and the soot. The low-temperature oxidation activity of soot could be further optimized due to the excellent elevated NO’s conversion rate by partially substituting Cu with K. The maximum particle oxidation rate can be easily realized at such a low temperature as 347°C.     

Performance analysis of AF relaying based on water-filling power allocation over Nakagami-<Emphasis Type="Italic">m</Emphasis> fading

This paper investigates exact performance of an amplify-and-forward (AF) relay system based on water-filling power allocation in Nakagami-m fading environment, where m is a nonnegative integer plus one half. We first offer the cumulative distribution function (CDF) and probability density function (PDF) of the received signal-to-noise ratio (SNR) at a destination. Then outage probability, moments of SNR, higher-order statistics of the capacity are explicitly conducted. Especially, average symbol error rate (SER) under an additive white generalized Gaussian noise (AWGGN) is developed for water-filling power allocation scheme. While the average SER subjected by an additive white Gaussian noise (AWGN) can be regarded as a special case. Finally, all theoretical formulas are truly attested by various simulation results.     

Five-axis interpolation of continuous short linear trajectories for 3[PP]S-<Emphasis Type="Italic">XY</Emphasis> hybrid mechanism by dual Bezier blending

A novel five-axis real-time interpolation algorithm for 3[PP]S-XY hybrid mechanism is proposed in this paper. In the algorithm, the five-axis tool path for controlling this hybrid mechanism is separated into two sub-paths. One sub-path describes the movement of 3[PP]S parallel kinematic mechanism module, and the other one describes the movement of XY platform. A pair of cubic Bezier curves is employed to smooth the corners in those two sub-paths. Based on the homogenous Jacobian matrix of 3[PP]S mechanism, a relationship between the position errors of every driving joint in hybrid mechanism and the position deviation of the tool tip center point at the moving platform is established. This relationship is used to estimate the approximation error for the corners smoothing according to the accuracy requirement of tool tip center in interpolation. Due to the high computational efficiency of this corner smoothing method, it is integrated into the look-ahead module of computer numerical control (CNC) system to perform online tool path smoothing. By performing the speed planning based on a floating window scheme, a jerk limited S-shape speed profile can be generated efficiently. On this basis, a realtime look-ahead scheme, which is comprised of path-smoothing and feedrate scheduling, is developed to acquire a speed profile with smooth acceleration. A monotonic cubic spline is employed for synchronization between those two smoothed sub-paths in tool path interpolation. This interpolation algorithm has been integrated into our own developed CNC system to control a 3PRS-XY experimental instrument (P, R and S standing for prismatic, revolute and spherical, respectively). A club shaped trajectory is adopted to verify the smoothness and efficiency of the five-axis interpolator for hybrid mechanism control.     

Robust Fuzzy Sampled-Data Control for Dynamic Positioning Ships

A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system's asymptotical stability and achieve H∞performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.     

Micro-Grinding Performance of Hard-Brittle Chip Materials in Precision Micro-Grinding Microgroove

The micro-structure on hard-brittle chip materials (HBCMs) surface can produce predominant functions and features. The micro-grinding with diamond wheel micro-tip is an efficient method to machine microstructure on HBCMs. However, different HBCMs and crystal orientation may have a significant influence on the micro-grinding performance. In this paper, the micro-grinding performance along different crystal orientation of HBCMs is investigated. First, a dressed 600^# diamond grinding wheel is used to micro-grind micro-structure on HBCMs. Then, the experiment of micro-grinding force test is completed. Finally, the quality of microgroove, the grinding ratio and the micro-grinding force are investigated and they are related to the crystal orientation of HBCMs. It is shown that the stronger resistance to the micro-crack propagation has the best quality of microgroove and the smallest grinding ratio. Moreover, the hardest single-crystal SiC has the best machinability and the micro-grinding force is 38.9%, 10.8% and 46.8% less than the one of sapphire, single-crystal Si and quartz glass, respectively. The direction to micro-grind easily is the crystal orientation 〈10\(\overline 1 \)0〉 for single-crystal SiC and sapphire. In addition, the micro-grinding force increases with the increase of the micro-grinding depth and feed rate and decreases with the increase of the grinding wheel speed.     

A new buyer-seller watermarking protocol without double embedding

AbstractCopy deterrence is a digital watermarking application which enables a seller to identify the buyers who obtain digital content legally but illegally redistribute it. However, in many buyer-seller watermarking protocols proposed for copy deterrence, the seller has to embed two watermarks into each copy of the digital content before it is sold. In this paper, we propose a new buyer-seller watermarking protocol in which the seller can reduce the number of the embedded watermarks from two to one. The proposed protocol also provides a more efficient solution to the unbinding problem than that of Lei et al’s scheme.     

Calculation of 3D sensitivity matrix for electromagnetic tomography system using boundary elements and the perturbative approach

Electromagnetic tomography （EMT） is a non-invasive imaging technique capable of mapping the conductivity and permeability of an object. In EMT, eddy currents are induced in the object by the activation coils, and the receiving coils can measure the EMT voltages. When the activation frequency is significantly large, we can treat the metallic targets as electrically perfect conductors （EPCs）. In this situation, a thin skin approximation is reasonable and this type of scattering problem can be effectively treated by the boundary element method （BEM） formulated through integration equations. In this study, we compute three-dimensional （3D） sensitivity matrix between the sensors due to an EPC perturbation. Efficiency improvement is achieved through the utility of scalar magnetic potential. Two EPC objects, one sphere and one cube shaped, are simulated. The results agree well with the H dot H formula. Overall, we conclude that BEM can be used to calculate the 3D sensitivity matrix of an EMT system efficiently. This method is a general one for any shaped objects while the H dot H solution is only capable of producing the response for a small ball.     

Observer-based adaptive neural iterative learning control for a class of time-varying nonlinear systems

In this paper an adaptive iterative learning control scheme is presented for the output tracking of a class of nonlinear systems. An observer is designed to estimate the tracking errors. A mixed time domain and s-domain representation is constructed to derive an error model with relative degree one for our purpose. And time-varying radial basis function neural network is employed to deal with system uncertainty. A new signal is constructed by using a first-order filter, which removes the requirement of strict positive real (SPR) condition and identical initial condition of iterative learning control. Based on property of hyperbolic tangent function, the system tracing error is proved to converge to the origin as the iteration tends to infinity by constructing Lyapunov-like composite energy function, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.     

Intelligent Vehicle Human-Simulated Steering Characteristics Access and Control Strategy

As the traditional control algorithm is over-dependent on accurate vehicle model in intelligent vehicle steering control, a human-simulated intelligent control method is proposed based on experienced driver steering characteristics. Intelligent vehicle unmanned steering system dynamics model and the driver model are set up. Through experienced drivers’ trial run experiment, the analysis is mainly conducted on the double lanes condition. After the transformation of coordinates on global positioning system (GPS) derivative, the path information of local coordinates is accessed. The ideal driver steering path is obtained through fuzzy C-means clustering algorithm. The human-simulated intelligent controller is designed. Characteristic model is established according to the ideal and practical steering angle deviation and the deviation rate. Besides, the corresponding control rules and control modality set are designed. The joint simulation under CarSim joint/Simulink environment shows that the humanoid steering controller designed in this paper has better tracking performance than the model predictive control.     

A relaxed-PPA contraction method for sparse signal recovery

Sparse signal recovery is a topic of considerable interest, and the literature in this field is already quite immense. Many problems that arise in sparse signal recovery can be generalized as a convex programming with linear conic constraints. In this paper, we present a new proximal point algorithm (PPA) termed as relaxed-PPA (RPPA) contraction method, for solving this common convex programming. More precisely, we first reformulate the convex programming into an equivalent variational inequality (VI), and then efficiently explore its inner structure. In each step, our method relaxes the VI-subproblem to a tractable one, which can be solved much more efficiently than the original VI. Under mild conditions, the convergence of the proposed method is proved. Experiments with l ₁ analysis show that RPPA is a computationally efficient algorithm and compares favorably with the recently proposed state-of-the-art algorithms.     

Heuristics for the identical machine scheduling problem with preventive maintenances

In this paper, two mixed integer programming models integrating production scheduling and preventive maintenances are proposed to derive the optimal solutions for the identical machine scheduling problem with unavailability constraints. In the first model, the maintenance activities are performed periodically and the objective is to minimize the makespan. In the second model, the maintenance activities are flexible and the machines’ continuous working time cannot exceed a maximum allowed time T; the objective is to minimize the total completion time of jobs. For the first problem, we propose a heuristic longest batch time (LBT) and prove that the worst case error bound of LBT is 2. For the second problem, we develop a heuristic modified smallest processing time (MSPT) based on some properties of the optimal solutions. Computational experiments show that both of the heuristics are effective and efficient compared with the results obtained by CPLEX and the other algorithms.     

Polycrystalline behavior analysis of extruded magnesium alloy AZ31

Uniaxial tensile and compressive tests were performed at room temperature on extruded AZ31 Mg alloy specimens and distinct tensile-compressive anisotropy was detected. Deformed specimens were examined and the results indicate that the generation of {10 $\bar 1$ 2}〈10 $\bar 1$ 1〉 twin is responsible for the mechanical anisotropy. A rate independent crystal plasticity model, which accounts for both slip and twinning, was developed for polycrystalline hexagonal close packed (HCP) materials. Model predictions for the stress-strain curves and texture evolution were in reasonable agreement with the experimental results. Specifically, the model captured the three stages of strain hardening for uniaxial-compression. By comparing stress-strain curves and texture evolution between model predictions and experimental measures, information about the dominant slip and twinning systems active at room temperature was deduced.     

Hardware architecture design of block-matching and 3D-filtering denoising algorithm

Block-matching and 3D-filtering(BM3D) is a state of the art denoising algorithm for image/video,which takes full advantages of the spatial correlation and the temporal correlation of the video. The algorithm performance comes at the price of more similar blocks finding and filtering which bring high computation and memory access. Area, memory bandwidth and computation are the major bottlenecks to design a feasible architecture because of large frame size and search range. In this paper, we introduce a novel structure to increase data reuse rate and reduce the internal static-random-access-memory(SRAM) memory. Our target is to design a phase alternating line(PAL) or real-time processing chip of BM3 D. We propose an application specific integrated circuit(ASIC) architecture of BM3 D for a 720 × 576 BT656 PAL format. The feature of the chip is with 100 MHz system frequency and a 166-MHz 32-bit double data rate(DDR). When noise is σ = 25, we successfully realize real-time denoising and achieve about 10 d B peak signal to noise ratio(PSNR) advance just by one iteration of the BM3 D algorithm.     

Memory based scheme to monitor non-random small shift patterns in manufacturing process

Consistent high-quality and defect-free production is the demand of the day. The product recall not only increases engineering and manufacturing cost but also affects the quality and the reliability of the product in the eye of users. The monitoring and improvement of a manufacturing process are the strength of statistical process control. In this article we propose a process monitoring memory-based scheme for continuous data under the assumption of normality to detect small non-random shift patterns in any manufacturing or service process.The control limits for the proposed scheme are constructed. The in-control and out-of-control average run length(AVL) expressions have been derived for the performance evaluation of the proposed scheme. Robustness to non-normality has been tested after simulation study of the run length distribution of the proposed scheme, and the comparisons with Shewhart and exponentially weighted moving average(EWMA) schemes are presented for various gamma and t-distributions. The proposed scheme is effective and attractive as it has one design parameter which differentiates it from the traditional schemes. Finally, some suggestions and recommendations are made for the future work.