基于虚拟仪器的换热器智能控制系统设计

换热器广泛应用于建筑工程领域及工业过程中,其出口介质温度的有效控制是保证质量、节能和安全生产的重要条件,因此换热器出口水温的控制是过程控制中的重要课题。本文以西门子SMPT1000换热器温度控制系统为研究对象,建立基于虚拟仪器的智能温度控制平台。该平台在实现传统PID控制的基础上,又增加了智能控制算法,斯密斯控制和模糊控制。实验证明该智能控制平台具有修改参数简易方便、曲线准确的优点,具有良好的动静态特性,且市场应用价值高。     

Higher‐Dimensional Unification with continuous and fuzzy coset spaces as extra dimensions

We first review the Coset Space Dimensional Reduction (CSDR) programme and present the best model constructed so far based on the , 10‐dimensional E₈ gauge theory reduced over the nearly‐Kähler manifold with the additional use of the Wilson flux mechanism. Then we present the corresponding programme in the case that the extra dimensions are considered to be fuzzy coset spaces and the best model that has been constructed in this framework too. In both cases the best model appears to be the trinification GUT .     

Fabrication of Pascal-triangle Lattice of Proteins by Inducing Ligand Strategy

A protein Pascal triangle has been constructed as new type of supramolecular architecture by using the inducing ligand strategy that we previously developed for protein assemblies. Although mathematical studies on this famous geometry have a long history, no work on such Pascal triangles fabricated from native proteins has been reported so far due to their structural complexity. In this work, by carefully tuning the specific interactions between the native protein building block WGA and the inducing ligand R-SL , a 2D Pascal-triangle lattice with three types of triangular voids has been assembled. Moreover, a 3D crystal structure was obtained based on the 2D Pascal triangles. The distinctive carbohydrate binding sites of WGA and the intralayer as well as interlayer dimerization of RhB was the key to facilitate nanofabrication in solution. This strategy may be applied to prepare and explore various sophisticated assemblies based on native proteins.     

Distributed and multicore QuBiLS-MIDAS software v2.0: Computing chiral,fuzzy, weighted and truncated geometrical molecular descriptors based on tensor algebra

Advances to the distributed, multi-core and fully cross-platform QuBiLS-MIDAS software v2.0 ( http://tomocomd.com/qubils-midas ) are reported in this article since the v1.0 release. The QuBiLS-MIDAS software is the only one that computes atom-pair and alignment-free geometrical MDs (3D-MDs) from several distance metrics other than the Euclidean distance, as well as alignment-free 3D-MDs that codify structural information regarding the relations among three and four atoms of a molecule. The most recent features added to the QuBiLS-MIDAS software v2.0 are related (a) to the calculation of atomic weightings from indices based on the vertex-degree invariant (e.g., Alikhanidi index); (b) to consider central chirality during the molecular encoding; (c) to use measures based on clustering methods and statistical functions to codify structural information among more than two atoms; (d) to the use of a novel method based on fuzzy membership functions to spherically truncate inter-atomic relations; and (e) to the use of weighted and fuzzy aggregation operators to compute global 3D-MDs according to the importance and/or interrelation of the atoms of a molecule during the molecular encoding. Moreover, a novel module to compute QuBiLS-MIDAS 3D-MDs from their headings was also developed. This module can be used either by the graphical user interface or by means of the software library. By using the library, both the predictive models built with the QuBiLS-MIDAS 3D-MDs and the QuBiLS-MIDAS 3D-MDs calculation can be embedded in other tools. A set of predefined QuBiLS-MIDAS 3D-MDs with high information content and low redundancy on a set comprised of 20,469 compounds is also provided to be employed in further cheminformatics tasks. This set of predefined 3D-MDs evidenced better performance than all the universe of Dragon (v5.5) and PaDEL 0D-to-3D MDs in variability studies, whereas a linear independence study proved that these QuBiLS-MIDAS 3D-MDs codify chemical information orthogonal to the Dragon 0D-to-3D MDs. This set of predefined 3D-MDs would be periodically updated as long as new results be achieved. In general, this report highlights our continued efforts to provide a better tool for a most suitable characterization of compounds, and in this way, to contribute to obtaining better outcomes in future applications.     

关于Lucas三角形猜想的一个结果

运用初等方法,证明k=7时Lucas三角形不存在.     

110警车配置及巡逻方案

针对110警车调度问题,引入了图论中的最短路算法以及计算几何的相关理论,建立了车辆调配模型、巡逻路线模型以及基于模糊数学的评价指标模型.另外,用C++编写了一个可视化的软件,不仅实现了手动描点,自动求出覆盖线段集合的功能,同时利用计算机模拟警车的巡逻路线,最后通过计算机检验得到结果,其合理性和实用性都令人满意.针对问题一,通过人机结合,配置17辆警车就能实现D1的目标,很好地兼顾了警车巡逻的运行成本,减少公安部门车辆和人员等的投入.针对问题二,采用模糊数学相关理论使评价指标实现了从定性到定量的转变.针对问题三和六,在D1的基础上,兼顾了巡逻效果的显著性,采用最少被巡逻道路优先的贪心算法建立了动态巡逻模型,得到了合理的巡逻方案.在此方案中,我们动用了30辆警车完成了问题一的目标.另外还额外考虑了案发事件概率不均匀分布的情况,建立了改进模型.针对问题四,在完成问题三指标的基础上,为了尽可能提高巡逻车辆的隐蔽性和增强巡逻效果,采用轮盘赌算法来引入随机性.针对问题五,采用最远距离道路优先贪心策略,使模型尽可能满足条件D1,D2.针对问题七,提出了一些额外因素及其解决方案,进一步完善了模型,使模型更贴近现实.     

Exponential stability of Takagi-Sugeno fuzzy systems with impulsive effects and small delays

This paper deals with the exponential stability of impulsive Takagi-Sugeno fuzzy systems with delay. Impulsive control and delayed fuzzy control are applied to the system, and the criterion on exponential stability expressed in terms of linear matrix inequalities （LMIs） is presented.     

Numeral eddy current sensor modelling based on genetic neural network

This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network （GNN） according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method.