Stochastic Investigations for the Fractional Vector-Host Diseased Based Saturated Function of Treatment Model

The goal of this research is to introduce the simulation studies of the vector-host disease nonlinear system (VHDNS) along with the numerical treatment of artificial neural networks (ANNs) techniques supported by Levenberg-Marquardt backpropagation (LMQBP), known as ANNs-LMQBP. This mechanism is physically appropriate, where the number of infected people is increasing along with the limited health services. Furthermore, the biological effects have fading memories and exhibit transition behavior. Initially, the model is developed by considering the two and three categories for the humans and the vector species. The VHDNS is constructed with five classes, susceptible humans , infected humans , recovered humans , infected vectors , and susceptible vector based system of the fractional-order nonlinear ordinary differential equations. To solve the number of variations of the VHDNS, the numerical simulations are performed using the stochastic ANNs-LMQBP. The achieved numerical solutions for solving the VHDNS using the stochastic ANNs-LMQBP have been described for training, verifying, and testing data to decrease the mean square error (MSE). An extensive analysis is provided using the correlation studies, MSE, error histograms (EHs), state transitions (STs), and regression to observe the accuracy, efficiency, expertise, and aptitude of the computing ANNs-LMQBP.     

光电跟踪系统非线性新息自适应卡尔曼滤波算法

为解决非线性部分状态卡尔曼滤波算法中由于线性化误差所导致的滤波精度下降问题,提出采用UT变换方法计算系统状态误差方差,及基于新息自适应调整系统噪声方差,进而构成一种新的非线性自适应部分状态卡尔曼滤波算法,并总结出详细算法结构.同时,将此方法应用到非线性测量光电跟踪系统中,并与U卡尔曼滤波和非线性部分状态卡尔曼滤波进行性...     

Intelligent Networks for Chaotic Fractional-Order Nonlinear Financial Model

The purpose of this paper is to present a numerical approach based on the artificial neural networks (ANNs) for solving a novel fractional chaotic financial model that represents the effect of memory and chaos in the presented system. The method is constructed with the combination of the ANNs along with the Levenberg-Marquardt backpropagation (LMB), named the ANNs-LMB. This technique is tested for solving the novel problem for three cases of the fractional-order values and the obtained results are compared with the reference solution. Fifteen numbers neurons have been used to solve the fractional-order chaotic financial model. The selection of the data to solve the fractional-order chaotic financial model are selected as 75% for training, 10% for testing, and 15% for certification. The results indicate that the presented approximate solutions fit exactly with the reference solution and the method is effective and precise. The obtained results are testified to reduce the mean square error (MSE) for solving the fractional model and verified through the various measures including correlation, MSE, regression histogram of the errors, and state transition (ST).     

An Intelligence Computational Approach for the Fractional 4D Chaotic Financial Model

The main purpose of the study is to present a numerical approach to investigate the numerical performances of the fractional 4-D chaotic financial system using a stochastic procedure. The stochastic procedures mainly depend on the combination of the artificial neural network (ANNs) along with the Levenberg-Marquardt Backpropagation (LMB) i.e., ANNs-LMB technique. The fractional-order term is defined in the Caputo sense and three cases are solved using the proposed technique for different values of the fractional order α. The values of the fractional order derivatives to solve the fractional 4-D chaotic financial system are used between 0 and 1. The data proportion is applied as 73%, 15%, and 12% for training, testing, and certification to solve the chaotic fractional system. The acquired results are verified through the comparison of the reference solution, which indicates the proposed technique is efficient and robust. The 4-D chaotic model is numerically solved by using the ANNs-LMB technique to reduce the mean square error (MSE). To authenticate the exactness, and consistency of the technique, the obtained performances are plotted in the figures of correlation measures, error histograms, and regressions. From these figures, it can be witnessed that the provided technique is effective for solving such models to give some new insight into the physical behavior of the model.     

基于分数阶滑模控制的高精度印刷机纠偏系统研究

目的 解决卷对卷印刷收卷不齐的问题，提高收卷精度。方法 对印刷机收卷纠偏原理进行分析，建立收卷纠偏系统数学模型，提出基于分数阶滑模控制的纠偏算法，分析其稳定性。在不同收卷线速度、不同跑偏干扰输入信号的条件下进行仿真。搭建收卷纠偏实验平台，对2种控制方法进行收卷纠偏控制实验。结果 仿真结果表明，分数阶滑模控制器比传统PID控制器具有较好的动态性能和稳态性能。实验结果表明，分数阶滑模控制算法比传统PID控制具有更高的纠偏精度。结论 分数阶滑模控制算法可以有效提高印刷机收卷纠偏精度，满足高精度印刷要求。     

Nonlinear processing and fractional-order filtering in a joint fractional fourier-transform correlator: performance evaluation in multiobject recognition

We investigated the correlation performance of a joint fractional Fourier-transform correlator (JFRTC) using computer simulation results. We present a mathematical analysis suggesting use of processing techniques based on a nonlinear transformation and fractional-order fractional-power fringe-adjusted filter to attain improved performance in terms of discrimination sensitivity and input space-bandwidth utilization. Optimal noise performance for the JFRTC is predicted in the presence of additive white Gaussian noise. An all-optical implementation scheme based on incoherent erasure in a photorefractive crystal is proposed.     

基于分数阶微分的金属橡胶迟滞非线性动力学模型

金属橡胶元件的应力应变关系为非线性滞回曲线,现有的金属橡胶动力学模型大多采用多参数、分段函数进行描述,增加了系统的复杂性。通过分析金属橡胶的弹性恢复力和阻尼力的组成,利用分数阶微分能够描述各种材料及过程记忆性的特点,提出一种含有分数阶微分的金属橡胶黏弹性本构模型,在此模型基础上建立了金属橡胶非线性动力学系统模型;通过正弦位移加载实验获取了典型金属橡胶隔振系统在多种激励幅值、频率作用下的恢复力;采用遗传算法对实验数据进行曲线拟合,识别出模型中所有参数;通过分析推导出系统模型中各参数与振幅及频率的函数关系。结果表明,所提出的含分数阶微分项的金属橡胶非线性动力学系统模型,具有连续的数学表达式,能够较准确地反映金属橡胶非线性系统的完整动力学性能,而且与现有金属橡胶动力学系统模型相比,参数较少,结构简单,为金属橡胶动力学系统的研究提供了新的思路。     

基于天牛须改进粒子群算法的平面度误差评定研究

基于天牛须改进粒子群算法(BAS-PSO)对平面度误差进行了评定研究.首先,建立基于最小区域的平面度误差评定的数学模型,并将目标函数转化为非线性最优化问题;接着,在粒子群算法(PSO)的基础上,引人局部搜索能力较强的天牛须算法(BAS),加速全局搜索和局部搜索的并行计算,避免算法早熟收敛并陷入局部最优,提高平面度误差评...     

Swarming Computational Techniques for the Influenza Disease System

The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using the differential form of each class of the IDS and then optimized by the PSOIPA. The correctness and accuracy of the scheme are observed to perform the comparative analysis of the obtained IDS results with the Adams solutions (reference solutions). An absolute error in suitable measures shows the precision of the proposed ANNs procedures and the optimization efficiency of the PSOIPA. Furthermore, the reliability and competence of the proposed computing method are enhanced through the statistical performances.     

Novel Computing for the Delay Differential Two-Prey and One-Predator System

The aim of these investigations is to find the numerical performances of the delay differential two-prey and one-predator system. The delay differential models are very significant and always difficult to solve the dynamical kind of ecological nonlinear two-prey and one-predator system. Therefore, a stochastic numerical paradigm based artificial neural network (ANN) along with the Levenberg-Marquardt backpropagation (L-MB) neural networks (NNs), i.e., L-MBNNs is proposed to solve the dynamical two-prey and one-predator model. Three different cases based on the dynamical two-prey and one-predator system have been discussed to check the correctness of the L-MBNNs. The statistic measures of these outcomes of the dynamical two-prey and one-predator model are chosen as 13% for testing, 12% for authorization and 75% for training. The exactness of the proposed results of L-MBNNs approach for solving the dynamical two-prey and one-predator model is observed with the comparison of the Runge-Kutta method with absolute error ranges between 10⁻⁰⁵ to 10⁻⁰⁷. To check the validation, constancy, validity, exactness, competence of the L-MBNNs, the obtained state transitions (STs), regression actions, correlation presentations, MSE and error histograms (EHs) are also provided.     

Nonlinear free vibration analysis of thermally post-buckled composite spherical shell panel

In this article, nonlinear free vibration behaviour of thermally post-buckled laminated composite spherical shallow shell panel is analyzed. The nonlinearity in geometry of the shell panel is considered in Green–Lagrange sense and the mathematical model is developed based on higher order shear deformation theory (HSDT). System of governing differential equations are derived using Hamilton’s principle. A direct iterative method in conjunction with nonlinear finite element approach is used to solve the system of equations. Effects of various geometries and material properties on the nonlinear free vibration frequencies are examined in detail and discussed. Results are obtained using the present model and are compared with those available in literature. The difference between the results speaks the necessity and the requirement of the present model for the prediction of actual nonlinear characteristics of the laminated structures having severe nonlinearity in thermal environment.     

Evaluation of osteoinduction and proliferation on nano-Sr-HAP: a novel orthopedic biomaterial for bone tissue regeneration

Hydroxyapatite (HAP), a CaP compound similar to the mineral phase present in bone, has excellent biocompatibility but little osseous inductivity. In this study, we evaluated the novel nano-Sr-HAP, in which the calcium of hydroxyapatite was substituted with strontium, which acts as a bone-forming agent. Its biocompatibility and osteoinduction were assayed using marrow mesenchymal stem cells (MSCs) and osteoblasts (OBs) in vitro. We were able to demonstrate that nano-Sr-HAP supported increased OB cell adhesion, proliferation and viability up to 4 days in culture when compared with nano-HAP. MSCs cultured with nano-Sr-HAP showed higher alkaline phosphatase (ALP) activity. More extracellular mineralized nodules were found with nano-Sr-HAP compared to nano-HAP, especially in images of ALP staining. We suggest that nano-Sr-HAP powders possess osteoconductive and osteoinductive properties and have the potential to be used in the repair of bone defects caused by osteoporotic fractures.     

基于CMAC的恒张力控制系统研究

针对张力控制系统的时变性和耦合性,通过卷辊和带材的动力学分析,建立了张力系统动力学模型,分析了影响张力的主要因素.为解决常规PID控制在张力控制过程中难以实现参数整定的问题,提出CMAC与常规PID并行控制方案,利用CMAC的非线性映射能力适应时变系统的要求.建立了控制系统模型,并进行了仿真.结果表明,该方法的控制效果优于常规PID,抑制扰动能力强、稳定性较好.     

Specific biofunctional performances of the hydroxyapatite–sodium maleate copolymer hybrid coating nanostructures evaluated by in vitro studies

The nanohybrid structures consisting of hydroxyapatite (HA) and sodium maleate-vinyl acetate copolymer (MP) deposited by Matrix Assisted Pulsed Laser Evaporation (MAPLE) technique on Ti surfaces were investigated for specific biological qualities required in bone implantology. The data from in vitro studies demonstrated that human primary osteoblasts (OBs) firmly adhered to Ti coated with HA–MP as indicated by cytoskeleton and vinculin dynamics. OBs spread onto biomaterial surface and formed groups of cells which during their biosynthetic activity expressed OB phenotype specific markers (collagen and non-collagenous proteins) and underwent controlled proliferation.     

一类分数阶非线性时滞系统的稳定性与镇定（英）

稳定性是控制系统分析与设计的基础．探索分数阶系统,特别是分数阶时滞非线性系统的稳定性条件是控制理论与工程领域中的难点问题．本文研究了一类分数阶非线性时滞系统的稳定性和镇定．通过将原系统转化成等价的分数阶积分系统,再借助不等式放缩技术,提出了一个有效且形式简单的确保该类系统稳定新的时滞无关稳定性准则．根据所得的稳定条件,提出了基于时滞线性反馈控制器的镇定控制方法．最后,数值实例验证了所得结果的有效性．此外,本文所使用的方法可以推广和应用于其他类型的分数阶系统的稳定性和镇定控制．     

Correlation of in vitro and in vivo results of vacuum plasma sprayed titanium implants with different surface topography

Research has proven that rough surfaces improve both biologic and biomechanical responses to titanium (Ti) implants. The purpose of this study was to evaluate the correlation between the expression of bone cell-associated proteins to Vacuum Plasma-Sprayed Titanium implants (VPS-Ti) with different surface textures in vitro and the bone integration in vivo. The biological performances of the surfaces were evaluated over a period of 8 weeks using human bone marrow cell cultures and Göttinger mini pigs. Cells were cultured on VPS-Ti with two respectively different surface-roughnesses (Ra). The level of Osteoprotegerin (OPG), Osteocalcin (OC) and alkaline phosphatase activity (ALP) were evaluated. The bone integration in vivo was evaluated by histomorphological analyses. A cancellous structured titanium (CS-Ti) construct was used as reference material in both study designs. Comparison of data was conducted using the Scheffé tests and the paired t-test with Bonferroni’s correction. A comparative analysis was done to measure the degree of association between the in vitro and in vivo data. A total amount of OC was significantly increased for VPS-Ti for cells cultured on both VPS-Ti and CS-Ti, while OPG was only detectable after 8 weeks without any significant differences. The ALP activity on all surfaces was not statistically increased. For VPS-Ti with Ra ranging from 0.025 mm up to 0.059 mm, bone integration response was increased, but there was no statistical difference between the VPS-Ti. Expression of OPG, OC and ALP correlated with the histomorphological data over the 8-week period. The in vitro data suggest the superiority of VPS-Ti over CS-Ti, but more importantly, the biocompatibility of testing an in vitro model to predict the outcome and possible integration of implants in vivo.     

Deriving operating characteristic equations for overcurrent protection devices based on eigensystem realization algorithm

Accurate representation of the operating characteristics of conventional inverse-time overcurrent (OC) protection devices plays an important role in protection coordination schemes. Based on the singular value decomposition of the Hankel matrix, this study uses the eigensystem realization algorithm to curve-fit the characteristic curves of OC protection devices under the digital state-space model and obtain the equations of their operating characteristics. This study applies the proposed method to four types of OC protection devices, including two electromechanical OC relays, one digital OC relay, and one power fuse. One characteristic curve from each protection device is selected for curve-fitting. For all four OC protection devices, the absolute error values for the hundreds of sample points between the actual characteristic curves and the corresponding curve-fitting equations are all less than 10 ms. The numbers of fitting components required are determined by the desired maximum absolute values of errors for the fitting equation. Finally, this study uses the derived equation to construct the characteristic curve of customized OC relay to solve the coordination problem of power system protection.     

An Error-Minimizing Approach to Regularization in Indirect Measurements

Indirect measurements often amount to the estimation of the parameters of a mathematical model that describes the object under investigation, and this process may numerically be ill conditioned. Various regularization techniques are used to solve the problem. This paper shows that popular regularization methods can be depicted as special cases of a generalized approach based on a penalty term in the minimized criterion function and how different kinds of a priori knowledge can be engaged into each of them. A new function, which depends on the estimate bias and variance, is proposed to find a regularization parameter that minimizes the error of estimation, as well as a novel approach for nonlinear estimation that results in the iterative minimization (IM) method. The superiority of IM with respect to the conventional Marquardt procedure is demonstrated. Based on analysis, it also follows that the regularization technique can be used even in the case of numerically well-conditioned indirect measurements, decreasing the total error of estimation.      

基于模型的工艺信息标识方法研究

实现工艺信息在三维模型上的标识是目前三维数字化工艺研究的热点.针对此问题,论文提出了一种基于MBD技术和GB/T 24734-2009的机加工工艺信息标识方法.该方法有效地规范了机加工工艺信息标识符号的构建和组合方法,并通过三维标注实现工艺信息与模型的关联,使工艺设计人员和制造人员能快速直观地浏览与获取加工工艺信息.在以上研究的基础上,基于Pro/E平台进行二次开发,并通过实例验证了该方法的可行性和实用性.     

Nonlinear multibody dynamics and finite element modeling of occupant response: part I—rear vehicle collision

With the rise in vehicle ownership, the need to reduce the risk of injury among vehicle occupants that arises from vehicle collisions is important to occupants, insurers, manufacturers and policy makers alike. The human head and neck are of special interest, due to their vulnerable nature and the severity of potential injury in these collisions. This work is divided into two parts: In Part I, we focus our attention to modeling rear collision that could lead to whiplash. Specifically, two multibody dynamics (MBD) models of the cervical spine of the 50th percentile male are developed using realistic geometries, accelerations and biofidelic variable intervertebral rotational stiffness. Furthermore, nonlinear finite element (FE) simulations of two generic compact sedan vehicles in rear collision scenario were performed. Using the acceleration profiles measured at the driver’s seat of the colliding vehicles, FE simulation of a seated and restrained occupant in rear collision was performed to determine the occupant response. The resultant accelerations, measured at the T1 vertebra of the occupant model, were used as an input to the MBD models to obtain their kinematic response. Validation of the MBD models shows great agreement with experimentally published data. Comparison between the MBD and FE simulations for a 32 km/h vehicle-to-vehicle impact shows similar trends in head trajectory. However, the MBD models reported less peak head displacements compared to the FE model. This is attributed to the failure of the anterior longitudinal ligament at the mid cervical spine leading to increased intervertebral rotation in the FE model.