Change detection in synthetic aperture radar images based on unsupervised artificial immune systems

In this paper, we propose a novel change detection method for synthetic aperture radar images based on unsupervised artificial immune systems. After generating the difference image from the multitemporal images, we take each pixel as an antigen and build an immune model to deal with the antigens. By continuously stimulating the immune model, the antigens are classified into two groups, changed and unchanged. Firstly, the proposed method incorporates the local information in order to restrain the impact of speckle noise. Secondly, the proposed method simulates the immune response process in a fuzzy way to get an accurate result by retaining more image details. We introduce a fuzzy membership of the antigen and then update the antibodies and memory cells according to the membership. Compared with the clustering algorithms we have proposed in our previous works, the new method inherits immunological properties from immune systems and is robust to speckle noise due to the use of local information as well as fuzzy strategy. Experiments on real synthetic aperture radar images show that the proposed method performs well on several kinds of difference images and engenders more robust result than the other compared methods.     

A probabilistic load shedding concept considering highly volatile local generation

Automatic load shedding is the ultimate countermeasure against imbalance in a power system and can effectively help preventing large blackouts. Taking into account a high penetration of renewable energy sources (RES) in the distribution grid, a clear distinction between load and generation at the PCC becomes increasingly more difficult. For that reason an adaptation of frequency relay parameters and their locations of installation are necessary. In Europe this is rest on a multi-step plan based on values such as the yearly peak load. In this paper a novel probabilistic method for automatic load shedding is presented that uses the average values instead of peak values for load shedding. Its applicability is verified by a dynamic power system model that was developed to compare the classical and novel probabilistic load shedding principle. The method is verified using data from a German TSO.     

Study of MW-scale biogas-fed SOFC-WGS-TSA-PEMFC hybrid power technology as distributed energy system: Thermodynamic,exergetic and thermo-economic evaluation

Advanced biogas power generation technology has been attracting attentions, which contributes to the waste disposal and the mitigation of greenhouse gas emissions. This work proposes and models a novel biogas-fed hybrid power generation system consisting of solid oxide fuel cell, water gas shift reaction, thermal swing adsorption and proton exchange membrane fuel cell (SOFC-WGS-TSA-PEMFC). The thermodynamic, exergetic, and thermo-economic analyses of this hybrid system for power generation were conducted to comprehensively evaluate its performance. It was found that the novel biogas-fed hybrid system has a gross energy conversion efficiency of 68.63% and exergy efficiency of 65.36%, indicating high efficiency for this kind of hybrid power technology. The market sensitivity analysis showed that the hybrid system also has a low sensitivity to market price fluctuation. Under the current subsidy level for the distributed biogas power plant, the levelized cost of energy can be lowered to 0.02942 $/kWh for a 1 MW scale system. Accordingly, the payback period and annual return on investment can reach 1.4 year and about 20%, respectively. These results reveal that the proposed hybrid system is promising and economically feasible as a distributed power plant, especially for the small power scale (no more than 2 MW).     

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.     

基于学生群体心理测试系统的设计

心理测试的根本目的是为了让人们在测试过程中，产生某些特定行为，即个体对测试题目的反应，并根据这些行为反应来推论其相应的心理特性。在一定程度上帮助我们了解人类的心理活动，并从中得到帮助。因此，本文对基于学生群体心理测试系统的设计进行深入研究。     

Application of chitosan–alginate microspheres for the sustained release of bacteriophage in simulated gastrointestinal conditions

This study was designed to evaluate the acid stability, release property and antimicrobial efficacy of Escherichia coli O157:H7 bacteriophages encapsulated in chitosan–alginate microspheres under the simulated gastrointestinal conditions. The bacteriophages belonging to Myoviridae family were stable at the pH above 4 in trypticase soy broth. The chitosan–alginate microspheres exhibited protective effect on the viability of bacteriophages in the simulated gastric conditions at pH 2.0 and pH 2.5, showing 4.8 and 5.6 log PFU mL^‐1, respectively, after 1 h of incubation at 37 °C. The release per cent of bacteriophages from microspheres gradually increased up to 65% in the simulated intestinal condition (pH 7.5) at 37 °C for 6 h. The lytic efficacy of chitosan‐ and alginate‐encapsulated bacteriophages against E. coli O157:H7 was significantly maintained in the simulated intestinal conditions to 10 h of incubation (1.3 log reduction). The results suggest that the chitosan–alginate microspheres can be used as a reliable delivery system for bacteriophages.     

嵌入式盲文单手输入系统设计与实现

计算机录入编辑盲文是信息处理的特殊应用领域，是特殊教育中的重要研究课题。文中将盲文制作为特殊符号，通过制作字库，编写个性化码表，然后嵌入到主流输入法，从而实现盲文与汉字混排以及实现单手盲文输入。该系统具有易学易记性、盲文编码多样性、嵌入性强等优点，并通过实验证明输入盲文效率能提高5~6倍，在盲文出版、盲文印刷、盲文教学等领域有重要的应用价值。但盲文字符在不同平台(如智能手机)与不同操作系统兼容性问题还有待进一步研究开发。     

基于状态观测器的电镀液温度状态反馈控制系统

针对电镀液温度控制系统,引入状态反馈控制。相对于传统的反馈控制,本方法可以获得更优异的性能。另外,考虑到镀液温度控制具有纯迟延的特点,提出了一种消去纯迟延的方法。仿真验证结果显示,控制效果良好。     

Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

叠合盆地凸起区多期复杂断裂特征及形成机制——以准噶尔盆地车排子凸起为例

以高精度三维地震资料为基础,结合构造演化恢复和区域构造背景,系统研究了准噶尔盆地车排子凸起断裂分布和形成机制。结果表明,车排子凸起发育深部和浅部2套断裂体系,深部断裂体系和浅部断裂体系分别发育3种断裂样式。车排子凸起共经历5个构造演化阶段,其中,晚二叠世挤压-逆冲控制了深部断裂体系的初始形成,晚侏罗世逆冲-走滑控制了深部断裂体系的最终定型,新近纪叠加掀斜、局部伸展控制了浅部断裂体系的形成。不同断裂体系在油气成藏过程中均起到了重要作用。其中:深部断裂体系的红车断裂是重要的油源断裂,低序级断层控制形成了石炭系火山岩优质储集体;浅部断裂体系使得油气向浅部层系运移调整,同时形成了断块圈闭、断鼻圈闭和断层-岩性圈闭等丰富的圈闭类型。