非水电解质浓溶液的热力学研究(Ⅰ)——用缔合模型关联、推算298.15K时HCL甲醇浓溶液的活度系数

利用HCl在甲醇中稀溶液的活度系数,通过Pitzer的缔合模型,关联出298.15K HCl在甲醇中的缔合常数Kx=1.7×10~2,然后利用HCl在甲醇中浓溶液的活度系数关联出近程作用单参数,进而推算溶剂甲醇的活度系数及溶液总压,均得到满意的结果,说明HCl甲醇浓溶液的热力学关联必须考虑HCl的部分离解效应。     

区域生态水利经济系统的初步探讨

根据生态经济学理论、 生态水利研究和区域水资源合理配置理论, 运用系统分析的方法, 结合我国区域生态水 利经济系统研究现状, 在分析区域生态水利经济系统的基本理念的基础上, 探讨了区域生态水利经济系统的组成要 素, 研究了区域生态水利经济系统的发展变化规律。以期为区域经济社会新的发展模式的建立提供理论基础和思 路, 对推动我国自然环境的保护和经济社会的发展起到一定的作用。     

The Importance of Shallow‐Low Velocity Habitats to Juvenile Fish in the Middle Mississippi River

Habitat management is a crucial aspect of fisheries management. Without knowledge of habitat associations, fisheries scientists are unable to effectively make habitat conservation or restoration recommendations. This becomes especially prominent when trying to manage commercially harvested populations and protect threatened or endangered species. To determine juvenile fishes habitat associations in the Middle Mississippi River, we analysed mini‐trawl catch data of six common juvenile fish species: blue catfish (Ictalurus furcatus), channel catfish (Ictalurus punctatus), channel shiner (Notropis wickliffi), freshwater drum (Aplodinotus grunniens), paddlefish (Polyodon spathula), and shovelnose sturgeon (Scaphirhynchus platorynchus). Overall, we conducted 2251 mini‐trawl sampling efforts between 2002 and 2013, resulting in the capture of 23,742 target specimens. Catch per unit effort was evaluated by structural habitat (i.e. velocity, depth, and substrate). Overall, these data suggest that juvenile fish species are more prevalent in shallow water and slower velocities. Ultimately the information garnered during this evaluation should be incorporated when considering habitat modifications, especially those modifications that impact the availability of shallow‐low velocity habitats. Copyright © 2016 John Wiley & Sons, Ltd.     

疏水缔合类聚丙烯酰胺溶液性质研究

综述了疏水缔合类聚丙烯酰胺溶液性质的影响因素以及测定溶液微观形态的研究方法。     

Smart pricing scheme: A multi-layered scoring rule application

Defining appropriate pricing strategy for smart environment is important and complex task at the same time. It holds the primal fraction in Demand Response (DR) program. In our work, we devise an incentive based smart dynamic pricing scheme for consumers facilitating a multi-layered scoring rule. The proposed strategy characterizes both incentive based DR and price based DR programs facilities. This mechanism is applied between consumer agents (CA) to electricity provider agent (EP) and EP to Generation Company (GENCO). Based on the Continuous Ranked Probability Score (CRPS), a hierarchical scoring system is formed among these entities, CA–EP–GENCO. As CA receives the dynamic day-ahead pricing signal from EP, it will schedule the household appliances to lower price period and report the prediction in a form of a probability distribution function to EP. EP, in similar way reports the aggregated demand prediction to GENCO. Finally, GENCO computes the base discount after running a cost-optimization problem. GENCO will reward EP with a fraction of discount based on their prediction accuracy. EP will do the same to CA based on how truthful they were reporting their intentions on device scheduling. The method is tested on real data provided by Ontario Power Company and we show that this scheme is capable to reduce energy consumption and consumers’ payment.     

Particle filtering for sensor fault diagnosis and identification in nonlinear plants

We propose a novel method for sensor monitoring and fault-tolerant estimation in systems described by general stochastic nonlinear and/or non-Gaussian state-space models. Faults are defined as abruptly occurring calibration errors, causing the sensor readings to be biased or scaled. Actuators and the process itself are assumed to be fault free. The main novelty of the work is an adaptive particle filter, whose configuration changes in order to diagnose sensor faults and to compensate for their effects. The presence, type and magnitude of sensor faults are determined through hypothesis testing and maximum likelihood estimation, based on the difference between the measurements and the particle filter estimates. The validity of the proposed approach was demonstrated through simulations on a drum-boiler model, although its effectiveness is not conditioned on any particular feature of the considered example.     

加权条件熵在异常检测中的应用

通过分析信息熵在异常检测中的应用和条件熵的固有特性, 提出了一种基于条件熵和加权熵理论的异常检测方法。分析网络流量特征, 选取具有内在相关性的网络特征属性, 给出了加权系数矩阵的公式和异常检测的具体实现方法。通过实验验证了该方法的有效性和实用性, 根据不同属性特征在加权条件熵理论中的应用效果, 分析了不同特征属性选择造成检测效果差异的原因。     

高速以太网中实时相似性匹配算法的研究

在高速以太网中, 针对用户行为的特殊性及数据流五元组的特点, 提出了一种自适应相似性匹配算法(ASMA-HN)。该算法充分考虑了数据流五元组的随机性分布特点, 通过一种改进的XOR-SHIFT算法将数据流分类索引, 并提出了同类数据库(SD)及异类数据库(HD)的概念, 基于距离测度分别设计了加权相似性比较函数, 使得特征值能更精准地匹配到符合要求的数据文件, 提高了整体的匹配效率。通过对校园网实际流量的现场测试, 证明该算法具有较高的精准性及可适用性, 且匹配时间较低, 能很好地满足高速网络中相似性匹配业务的需求。     

Web软件可信性的模糊评价方法

在对ISO/IEC 9126模型及Web软件属性图进行改进和扩充后,应用因子分析法构建了Web软件可信性评价指标体系,运用结构熵值法确定了各个可信指标的权重,并运用改进的证据合成方法构造专家评价信息的模糊评价矩阵;最后,运用置信度识别准则对软件可信性进行等级评价和得分计算,对应可信性决策规则集得出相应的策略。结合对Web软件中网上银行项目的实例分析说明了该方法的实用性和有效性。     

基于MPLS的VPN互访技术

针对VPN互访问题,根据IPSec-VPN互访方法的不足,提出动态MPLS-VPN方法.利用随机分配的标签,在需要互访的不同VPN网络节点之间构建MPLS通道,利用互访规则集检验节点的连接申请,根据过滤规则控制数据包的传输,通过设定传输时长限制节点互访的时间,实现VPN之间接节点、按方向、按时间的细粒度互访控制,确保数据传输的安全性和高效性.给出动态MPLS-VPN方法实现互访的步骤,对方法进行分析比较.