Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control

In this paper, the dynamic behaviors of a class of neural networks with time-varying delays are investigated. Some less weak sufficient conditions based on p-norm and ∞-norm are obtained to guarantee the existence, uniqueness of the equilibrium point for the addressed neural networks without impulsive control by applying homeomorphism theory. And then, by utilizing inequality technique, Lyapunov functional method and the analysis method, some new and useful criteria of the globally exponential stability with respect to the equilibrium point under impulsive control we assumed are derived based on p-norm and ∞-norm, respectively. Finally, an example with simulation is given to show the effectiveness of the obtained results.     

A novel thermo-pneumatic peristaltic micropump with low temperature elevation on working fluid

This work presents a novel thermo-pneumatic peristaltic micropump with low temperature elevation on working fluid. The proposed device, which consists of two separate zones for air-heating and fluid-squeezing, is realized by using micromachining techniques. Also, the device can be operated by using a small and simple actuation circuitry with low applied voltages. Under similar operational conditions, the proposed micropump shows similar fluid-pumping performance when compared with the conventional design of thermo-pneumatic micropumps. However, for the proposed design, the temperature elevation on the fluid-pumping area is as small as about 2.0 K, which is less than 8% of that generated by the conventional design. Furthermore, by applying higher voltages, larger flow rate can be achieved with relatively small increase in temperature elevation. Due to low temperature elevation on working fluid, the proposed device is suitable for the applications such as DNA chips or protein chips. In addition, because of its small size and simple actuation scheme, potentially the proposed device can be integrated into the devices for point-of-care applications.     

An adaptive surrogate model based on support vector regression and its application to the optimization of railway wind barriers

This study provides evidence supporting the use of the update strategies for the support vector regression (SVR) model. Firstly, the fitting and interpolation method (FIM) is presented to select SVR parameters, and three infill strategies are adopted to search for update points. Secondly, the infill strategy and parameter selection method are illustrated by test functions that illustrate their dependability. The distribution of update points, the sample density and the proportion of update points are discussed. Finally, the adaptive SVR surrogate model is applied to optimize the protective effect of railway wind barriers. The result shows that the parameter selection method has high stability. On the whole, the accuracy of the adaptive SVR model using a suitable infill strategy will be improved with an increasing proportion of update points if the final number of training points is identical. The optimization result shows an optimal porosity of 0.117 when the height of the railway wind barrier is 2.05 m (full scale).

     

Real time 3D simulation for nose surgery and automatic individual prosthesis design

This paper presents an intuitive nose surgery planning and simulation system, using 3D laser scan image and lateral X-ray image, to provide high quality prediction of the postoperative appearance, and design the patient specific prosthesis model automatically. After initial registration, the internal surface of soft tissue at the nose region was generated by the statistical data for soft tissue thickness adapted by the individual thickness information from the X-ray image. Then, the sketch contour of the 3D scan data on the lateral X-ray image was modified manually or adjusted automatically according to some aesthetic statistical data, to drive the simulation in real time by the state-of-the-art Laplacian surface deformation method. When satisfied with the 3D postoperative appearance, the deformation was mapped to the internal surface of soft tissue, and the change before and after simulation was utilized to generate the patient specific prosthesis model automatically. The surgeons who used the system confirmed that this planning system is attractive and has potential for daily clinical practice.     

C语言在化工原理离心泵特性曲线测定中的应用

离心泵特性曲线的测定是化工原理的重要内容,涉及到伯努利方程和连续性方程在流体流动中的实际应用,公式复杂,计算量大.本文利用C语言的强大结构化编程和计算功能,处理了“离心泵特性曲线的测定”实验数据,给出了程序设计的思路和方法,得到了离心泵的特性曲线.从曲线可以看出,随着流量的增大,离心泵的压头减少,轴功率升高,和教材完全一致.而离心泵的效率随流量增大而增大,并未出现先增大后减小的情况,可能是由于流量较小所导致.通过分析曲线可以得到离心泵操作相关的知识,离心泵必须在流量较小的区域工作才能获得较大的压头,大流量的离心泵需要配置大功率的电机,离心泵启动之前应关闭出口阀等.此外还发现压力表和真空表的读数随流量的增大而变小,解释了此现象.该程序结构简单,维护方便,通过简单修改可用于处理其它化工原理实验的数据,充分发挥了C语言的特长来解决化工原理计算复杂的特点.     

三对角对称矩阵逆特征问题

In this paper, four inverse eigenproblems with giventhree eigenvalues and corresponding eigenvectors are considered, somenecessary and sufficient conditions under which there exists a uniquesolution for these problems are given. Furthermore some numerical algorithmsand some numerical experiments are given.     

带微处理机的楔型流量计

介绍一种带压力、温度自动补偿的电远传楔型流量计,阐述了该流量计的工作原理、基本结构和性能特点。     

细胞分裂素6─BA合成新方法的研究

用医药工业的副产物乙酰基次黄嘌呤（Ⅰ）在弱酸条件下水解，生成次黄嘌呤（Ⅱ），经三氟氧磷在吡啶溶液中缩合，生成６－吡啶盐中间体（Ⅲ），再与苄胺反应，制得高效植物细胞分裂素６－ＢＡ（Ⅳ）。     

Procedural models for cartoon cracks and fractures animations

We present an approach for animating cracks and fractures in cartoon style. In our method we take a 2D hand-drawn object as input and then construct a 2.5D model of the object in order to approximate the object volume. Next, we generate the Voronoi textures on the 2.5D object model for visual abstraction of cartoon cracks. Further, cracking gaps on the Voronoi textures are widened progressively until Voronoi cells split apart and finally fall onto ground according to simplified physical rules. With minimum user intervention, our model is able to generate cartoon cracks and fractures animations procedurally, as demonstrated by examples given in the paper.     

Using immune genetic algorithm based hybrid techniques for short-term unit commitment problem

This paper presents a hybrid chaos search (CS), immune algorithm (IA)/genetic algorithm (GA), and fuzzy system (FS) method (CIGAFS) for solving short-term thermal generating unit commitment (UC) problems. The UC problem involves determining the start-up and shut-down schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve, and individual units. First, we combined the IA and GA, then we added the CS and the FS approach. This hybrid system was then used to solve the UC problems. Numerical simulations were carried out using three cases: 10, 20, and 30 thermal unit power systems over a 24 h period. The produced schedule was compared with several other methods, such as dynamic programming (DP), Lagrangian relaxation (LR), standard genetic algorithm (SGA), traditional simulated annealing (TSA), and traditional Tabu search (TTS). A comparison with an immune genetic algorithm (IGA) combined with the CS and FS was carried out. The results show that the CS and FS all make substantial contributions to the IGA. The result demonstrated the accuracy of the proposed CIGAFS approach.