基于信息融合的车辆运行异常程度检测

研究使用GA-FNN算法实时提取车辆监控中运行异常的问题. 利用遗传算法对全局信息的搜索特性, 筛选出有效的传感器信息作为模糊神经网络的输入, 通过模糊神经网络训练出模糊矩阵, 实时检测车辆运行的异常程度. 仿真结果显示GA-FNN算法在车辆实时监控系统中, 可以快速的检测出车辆的异常程度.     

Formulating the template ILP consistency problem as a constraint satisfaction problem

Inductive Logic Programming (ILP) deals with the problem of finding a hypothesis covering positive examples and excluding negative examples, where both hypotheses and examples are expressed in first-order logic. In this paper we employ constraint satisfaction techniques to model and solve a problem known as template ILP consistency, which assumes that the structure of a hypothesis is known and the task is to find unification of the contained variables. In particular, we present a constraint model with index variables accompanied by a Boolean model to strengthen inference and hence improve efficiency. The efficiency of models is demonstrated experimentally.     

Limitations of a Mapping Algorithm with Fragmentation Mimics (MAFM) when modeling statistical data sources based on measured packet network traffic

Knowing the estimation of a statistical process’s parameters for measured network traffic is very important as it can then be further used for the statistical analyses and modeling of network traffic in simulation tools. It is for this reason that different estimation methods are proposed that allow estimations of the statistical processes of network traffic. One of them is our own histograms comparison (EMHC) based method that can be used to estimate statistical data-length process parameters from measured packet traffic. The main part of EMHC method is Mapping Algorithm with Fragmentation Mimics (MAFM).     

黄泛平原古城“环城湖”与城市防洪减灾

以黄泛平原为研究背景,以该地城内形态相似的“环城湖”为研究对象,通过对其构成要素、历史成因、演变过程、空间格局等方面的研究,探讨了“环城湖”在黄河洪水与泥沙作用下的生成机制与演变规律.认为:古城“环城湖”是特定自然条件下黄河泛滥引起生态环境改变与古代城市营建模式共同作用的结果,在古城营建过程中承担着泄洪、排涝等防洪减灾功能,并在当今城市建设中仍发挥着重要作用;只有充分了解古城“环城湖”的形成过程与演变机制,才能重新认识和定位“环城湖”的当代价值,从本质上把握古城“环城湖”的特色与精华.     

Cyclic moving average control approach to cylinder pressure and its experimental validation

Cyclic variability is a factor adversely affecting engine performance. In this paper a cyclic moving average regulation approach to cylinder pressure at top dead center （TDC） is proposed, where the ignition time is adopted as the control input. The dynamics from ignition time to the moving average index is described by ARMA model. With this model, a one-step ahead prediction-based minimum variance controller （MVC） is developed for regulation. The performance of the proposed controller is illustrated by experiments with a commercial car engine and experimental results show that the controller has a reliable effect on index regulation when the engine works under different fuel injection strategies, load changing and throttle opening disturbance.     

Eigenvalue analysis of size effect for cohesive crack model

The paper analyses the effect of structure size on the nominal strength of the structure that is implied by the cohesive (or fictitious) crack model proposed for concrete by Hillerborg et al. A new method to calculate the maximum load of geometrically similar structures of different sizes without calculating the entire load-deflection curves is presented. The problem is reduced to a matrix eigenvalue problem, in which the structure size for which the maximum load occurs at the given (relative) length of the cohesive crack is obtained as the smallest eigenvalue. Subsequently, the maximum load, nominal strength and load-point displacement are calculated from the matrix equilibrium equation. The nonlinearity of the softening stress-displacement law is handled by iteration. For a linear softening law, the eigenvalue problem is linear and independent of the matrix equilibrium equation, and the peak load can then be obtained without solving the equilibrium equation. The effect of the shape of the softening law is studied, and it is found that the size effect curve is not very sensitive to it. The generalized size effect law proposed earlier by Baant, which describes a transition between the horizontal and inclined asymptotes of strength theory and linear elastic fracture mechanics, is found to fit the numerical results very well. Finally some implications for the determination of fracture energy from the size effect tests are discussed. The results are of interest for quasibrittle materials such as concrete, rocks, sea ice and modern tough ceramics.     

Understanding Boosted Selective CO2-to-CO Photoreduction with Pure Water Vapor over Hierarchical Biomass-Derived Carbon Matrix

Solar-driven CO₂ reduction reaction (CO₂RR) with water into carbon-neutral fuels is of great significance but remains challenging due to thermodynamic stability and kinetic inertness of CO₂. Biomass-derived nitrogen-doped carbon (N-C_b) have been considered as promising earth-abundant photocatalysts for CO₂RR, although their activities are not ideal and the reaction mechanism is still unclear. Herein, an efficient catalyst is developed for CO₂-to-CO conversion realized on diverse N-C_b materials with hierarchical pore structures. It is demonstrated that the CO₂-to-CO conversion preferentially takes place on positively charged carbon atoms next to pyridinic-N using two representatives treated pollens with the largest difference in pyridinic-N density and N content as model photocatalysts. Systematic experimental results indicate that surface local electric field originating from charge separation can be boosted by hierarchical pore structures, doped N, as well as pyridinic-N. Mechanistic studies reveal that positively charged carbon atoms next to pyridinic-N serve as active sites for CO₂RR, reduce the energy barrier on the formation of CO*, and facilitate the CO₂RR performance. All these benefits cooperatively contribute to treated chrysanthemum pollen catalyst exhibiting excellent CO formation rate of 203.2 µmol h⁻¹ g⁻¹ with 97.2% selectivity in pure water vapor. These results provide a new perspective into CO₂RR on N-C_b, which shall guide the design of nature-based photocatalysts for high-performance solar-fuel generation.     

面向人体健康防护的光纤生化传感技术

光纤生化传感器因具有不受电磁干扰、绝缘性好、安全防爆、损耗低和耐腐蚀等优点,在人体健康防护领 域表现出了良好的应用价值:及时且有效地监测污染物可为环境污染物的有效控制提供数据支撑,从源头上减少疾病的发生;准确且灵敏地检测疾病标志物可诊断人体疾病的情况,从而使得疾病的预防和早期治疗成为可能.对应用于人体健康防护中的光纤生化传感器进行全方位地概述:首先,介绍其使用的光纤传感原理;然后,总结并分析应用于气体和水质污染物监测的光纤生化传感技术;接着,总结并分析应用于人体呼出气体和生物体液检测的光纤生化传感技术;最后,讨论光纤生化传感器在人体健康防护领域实际应用的一些限制因素以及未来的发展方向.