基于倒排索引的密文数据库检索方法研究

针对实际密文数据库的应用,在全文检索倒排索引技术的基础上,设计了一种通过密文倒排索引文件对其进行快速检索的方法。密文索引文件中主要包含有索引项、相对应的记录主键等信息。检索时,通过用检索词匹配索引文件中的索引项,找到对应的记录主键集合,再根据记录主键集合查询密文数据库,获取相应的密文数据,进行解密即可获取明文数据信息。整个检索过程中不对数据库进行解密,从而实现了在不解密的情况下对密文数据库的快速检索。     

管理信息系统课程教改研究

本文针对当前管理信息系统课程所存在的教学内容陈旧落后、缺乏针对性,教学方法单一枯燥,教学实践环节薄弱等问题,根据笔者自身多年的教学经验,提出更新教学内容、改进教学方法以及优化实践环节的教学改革思路和方案。     

A two-layer architecture for economically optimal process control and operation

A two-layer architecture for dynamic real-time optimization (or nonlinear modelpredictive control (NMPC) with an economic objective) is presented, where the solution of the dynamic optimization problem is computed on two time-scales. On the upper layer, a rigorous optimization problem is solved with an economic objective function at a slow time-scale, which captures slow trends in process uncertainties. On the lower layer, a fast neighboring-extremal controller is tracking the trajectory in order to deal with fast disturbances acting on the process. Compared to a single-layer architecture, the two-layer architecture is able to address control systems with complex models leading to high computational load, since the rigorous optimization problem can be solved at a slower rate than the process sampling time. Furthermore, solving a new rigorous optimization problem is not necessary at each sampling time if the process has rather slow dynamics compared to the disturbance dynamics. The two-layer control strategy is illustrated with a simulated case study of an industrial polymerization process.     

复杂网络在传统经济系统上的模型研究

在当今社会,经济系统的模型研究一直是科学家研究的热点对象之一.许多自然界存在的经济系统都可以运用复杂网络建立出不同规模和不同拓扑结构的相关研究模型.在这些复杂的经济数学模型中,当研究复杂经济系统的相对特性时,必须针对性地考虑其复杂网络模型中的特性与模型结构.主要研究了复杂网络上的传统经济与部分社会系统,对于复杂网络上的社会经济系统的研究给出了一种新的思路.     

A fuzzy reasoning and fuzzy-analytical hierarchy process based approach to the process of railway risk information: A railway risk management system

Risk management is becoming increasingly important for railway companies in order to safeguard their passengers and employees while improving safety and reducing maintenance costs. However, in many circumstances, the application of probabilistic risk analysis tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents the development of a risk management system for railway risk analysis using fuzzy reasoning approach and fuzzy analytical hierarchy decision making process. In the system, fuzzy reasoning approach (FRA) is employed to estimate the risk level of each hazardous event in terms of failure frequency, consequence severity and consequence probability. This allows imprecision or approximate information in the risk analysis process. Fuzzy analytical hierarchy process (fuzzy-AHP) technique is then incorporated into the risk model to use its advantage in determining the relative importance of the risk contributions so that the risk assessment can be progressed from hazardous event level to hazard group level and finally to railway system level. This risk assessment system can evaluate both qualitative and quantitative risk data and information associated with a railway system effectively and efficiently, which will provide railway risk analysts, managers and engineers with a method and tool to improve their safety management of railway systems and set safety standards. A case study on risk assessment of shunting at Hammersmith depot is used to illustrate the application of the proposed risk assessment system.     

QoS约束的云经济资源管理模型研究

提供用户满意的、具有QoS约束的云计算应用是云计算面临的一大难题。提出了以商品市场为原型的云计算经济资源管理模型,其通过云用户与供应商的SLA协商,实现应用服务层QoS到资源设备层QoS的映射,最后利用效用函数的管理策略实现资源的优化调度。     

Relative importance,specific investment and ownership in interorganizational systems

Implementation and maintenance of interorganizational systems (IOS) require investments by all the participating firms. Compared with intraorganizational systems, however, there are additional uncertainties and risks. This is because the benefits of IOS investment depend not only on a firm’s own decisions, but also on those of its business partners. Without appropriate levels of investment by all the firms participating in an IOS, they cannot reap the full benefits. Drawing upon the literature in institutional economics, we examine IOS ownership as a means to induce value-maximizing noncontractible investments. We model the impact of two factors derived from the theory of incomplete contracts and transaction cost economics: relative importance of investments and specificity of investments. We apply the model to a vendor-managed inventory system (VMI) in a supply chain setting. We show that when the specificity of investments is high, this is a more critical determinant of optimal ownership structure than the relative importance of investments. As technologies used in IOS become increasingly redeployable and reusable, and less specific, the relative importance of investments becomes a dominant factor. We also show that the bargaining mechanism—or the agreed upon approach to splitting the incremental payoffs—that is used affects the relationship between these factors in determining the optimal ownership structure of an IOS.

Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch

At the central energy management center in a power system, the real time controls continuously track the load changes and endeavor to match the total power demand with total generation in such a manner that the operating cost is minimized while all the operating constraints are satisfied. However, due to the strict government regulations on environmental protection, operation at minimum cost is no longer the only criterion for dispatching electrical power. The idea behind the environmentally constrained economic dispatch formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and harmful emission levels are both simultaneously minimized for a given load demand. Conventional optimization techniques become very time consuming and computationally extensive for such complex optimization tasks. These methods are hence not suitable for on-line use. Neural networks and fuzzy systems can be trained to generate accurate relations among variables in complex non-linear dynamical environment, as both are model-free estimators. The existing synergy between these two fields has been exploited in this paper for solving the economic and environmental dispatch problem on-line. A multi-output modified neo-fuzzy neuron (NFN), capable of real time training is proposed for economic and environmental power generation allocation.This model is found to achieve accurate results and the training is observed to be faster than other popular neural networks. The proposed method has been tested on medium-sized sample power systems with three and six generating units and found to be suitable for on-line combined environmental economic dispatch (CEED).     

Evidence for transient composition variations at GaAs/Ga1−xAlxAs heterostructure interfaces prepared by metal-organic chemical vapour deposition

The composition profiles of GaAs/Ga_1?xAl_xAs heterostructures prepared in two different Metal-Organic Chemical Vapour Deposition (MOCVD) reactors have been studied. Transmission electron microscopy (TEM). and Auger and secondary ion mass spectrometry (SIMS) sputter profiling results are in good agreement and interface widths below 20 å have been achieved. Significant new results on transient phenomena have been obtained. showing that large and sometimes very sharp excursions in composition can be associated with valve switching actions. Direct evidence is presented that gas pressure or flow transients can occur during valve operations. and it is suggested that such instabilities are the cause of the effects observed.     

Effect of neighbouring village conditions and infrastructure interdependency on economic opportunity: A case study of the Yogyakarta region,Indonesia

To determine whether the inclusion of conditions in neighbouring villages and infrastructure interdependency are able to improve the performance of infrastructure–economy interaction models, we compare three related and progressive concepts. The first concept defines economic opportunity in a village as a function of available infrastructure within that village. The second concept includes the effect of economic opportunity in neighbouring villages in addition to available infrastructure within the village. In the third concept, we include the interdependency of infrastructures as another factor affecting the potential level of economic development in the village. We use Ordinary Least Squares (OLS) and a Geographic Information System (GIS) to model the first concept, and we add a spatial-lag model for the second. The third model expands on the second by introducing a Sugeno Fuzzy Inference System (FIS) and a rule-based OLS to capture the nature of infrastructure interdependency. The result of the three models is validated by a known spatial distribution of poverty levels and subjective well-being that serve as proxies for economic opportunity in the Yogyakarta region in Indonesia. The results demonstrate that the third model provides a more accurate prediction of the real conditions and performs consistently better than the other two models. We therefore conclude that conditions in neighbouring villages and infrastructure interdependency influence the economic opportunity of a village and should be considered in policy making regarding resource allocation in infrastructure development.