计算机网络安全扫描技术研究

随着互联网技术的发展,网络安全问题日益突出。作为一种主动防御手段,网络安全扫描技术在保护网络安全方面发挥着越来越大的作用。本文主要对主机探测,端口扫描,操作系统探测以及漏洞扫描等四种主要的网络安全扫描技术做了研究。     

从“超级网银”看我国PKI交叉认证体系建设

"超级网银"是我国第一个大规模跨CA的交叉认证平台,采用的是桥接交叉认证模式。不同的领域,应根据其自身特点,采用不同形式的交叉认证模型。最终的目的,是要在全国范围内建立一个交叉认证、相互融合又相互独立、相互协调的PKI整体体系,在这个过程中,国家和政府应发挥更加积极的作用。     

MicroPort: A general simulation platform for seaport container terminals

Seaport container terminals are essential nodes in sea cargo transportation networks. As such, the operational efficiency of container terminals in handling containers passing through them plays a critical role in a globalized world economy. Many models and algorithms have been developed to address various decision problems in container terminals to help improve operational efficiency. These decision support tools are usually used separately for specific purposes. However, the problems they are trying to tackle are often interrelated. Therefore, in this regard, an evaluation tool which can capture as many operational conditions as possible for different decision problems is necessary. This paper introduces a general simulation platform, named MicroPort, which aims to provide an integrated and flexible modeling system for evaluating the operational capability and efficiency of different designs of seaport container terminals. The software structure of MicroPort comprises three programming layers: (1) the Functions layer; (2) the Applications layer; and (3) the Extensions layer. Different layers are bound by Application Programming Interfaces (APIs). Basic functions built in the Functions layer support the Applications layer in which major operation processes can be modeled by an agent-based method. External modules and decision support tools in the Extensions layer then use APIs to adjust the system to produce suitable simulation models for specific purposes.     

A Polynomial Algorithm for Computing Elementary Siphons in a Class of Petri Nets

A set of elementary siphons plays a key role in the development of deadlock prevention policies for automated manufacturing systems. This paper addresses the computation problem for elementary siphons in a subclass of Petri nets which are basic systems of simple sequential processes with resources (BS³PR) and can model many automated manufacturing systems. An algorithm for enumerating elementary siphons is established by the one‐to‐one relationship between maximal perfect resource‐transition circuits (MPCs) and strict minimal siphons. A set of MPCs is first computed, followed by a set of elementary siphons in a BS³PR. The presented algorithm is proved to have polynomial‐time complexity. An example is used to illustrate the algorithm.     

Direct adaptive fuzzy control with membership function tuning

In this paper, a direct self‐structured adaptive fuzzy control is introduced for the class of nonlinear systems with unknown dynamic models. Control is accomplished by an adaptive fuzzy system with a fixed number of rules and adaptive membership functions. The reference signal and state errors are used to tune the membership functions and update them instantaneously. The Lyapunov synthesis method is also used to guarantee the stability of the closed loop system. The proposed control scheme is applied to an inverted pendulum and a magnetic levitation system, and its effectiveness is shown via simulation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

An on-line learning neural controller for helicopters performing highly nonlinear maneuvers

This paper presents an on-line learning adaptive neural control scheme for helicopters performing highly nonlinear maneuvers. The online learning adaptive neural controller compensates the nonlinearities in the system and uncertainties in the modeling of the dynamics to provide the desired performance. The control strategy uses a neural controller aiding an existing conventional controller. The neural controller is based on a online learning dynamic radial basis function network, which uses a Lyapunov based on-line parameter update rule integrated with a neuron growth and pruning criteria. The online learning dynamic radial basis function network does not require a priori training and also it develops a compact network for implementation. The proposed adaptive law provides necessary global stability and better tracking performance. Simulation studies have been carried-out using a nonlinear (desktop) simulation model similar to that of a BO105 helicopter. The performances of the proposed adaptive controller clearly shows that it is very effective when the helicopter is performing highly nonlinear maneuvers. Finally, the robustness of the controller has been evaluated using the attitude quickness parameters (handling quality index) at different speed and flight conditions. The results indicate that the proposed online learning neural controller adapts faster and provides the necessary tracking performance for the helicopter executing highly nonlinear maneuvers.     

Estimation of elastic constant of rocks using an ANFIS approach

The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.     

Screening model for assessing ‘cost’ of minimum flow requirements in the Svartå River,Sweden

The minimum flow requirements in the Svartå River in Sweden are directed at maintaining fishlife and providing suitable dilution for waste flows. The implications of varying the minimum flow requirements in the river are examined using a mixed integer optimisation model. The model is formulated as a modified method-of-weights technique with the economic issues of hydro-electricity generation, irrigation and urban water supply placed in the objective function and the minimum flows specified within the constraint set. The integer component of the model is required to model the operating policy at the major flow regulation facility in the system and the restricted validity of the irrigation permits. Application of the model shows that in dry years where competition between minimum flow levels and the other economic uses, is most intense, the levels achieved by the various economic objectives are only slightly reduced even with significant increases in the minimum flow requirements. Variations in minimum flow requirements of up to 45% only produce changes of 10% or less in the economic objectives. The lack of sensitivity of the objective levels is due primarily to the level of control exerted indirectly on the whole system in dry years by the release regulation policy and the restricted validity of the irrigation permits. In normal to wet years these policies are not as restrictive and more choice is available. In such years, however, there is generally sufficient water to satisfy all requirements and allocation is not a critical issue. The model itself is formulated generally so that a range of scenarios beyond those examined specifically in the paper can be considered.     

A generalized equation for surface tension from the triple point to the critical point

A three-parameter generalized equation is proposed for surface tension from the triple point to the critical point. This equation not only fits the data well but also is good for interpolation between the normal boiling point and the critical point. This equation is also good for extrapolation to the triple point. This equation has been tested using the surface tension of water from the triple point to the critical point. The constants of this equation obtained using orthobaric surface tensions are given for a number of compounds. The isobaric surface tensions determined at a pressure of 1 atm do not differ significantly from the orthobaric surface tensions. Such data also have been used in obtaining equations from the triple to the critical point.Nomenclature T _c Critical temperature, K - T _t Triple point, K - T _m Melting point, K - T _r Reduced temperature, K - X (T _c-T)/T _c - Surface tension, dyne · cm^–1;10^–3N · m^–1 - _m Surface tension at the melting point - _f Surface tension at T _r=0.9 - _t Surface tension at the triple point - Relative deviation 100[ _obsd– _calcd]/ _obsd - Standard deviation [( _obsd– _calcd)²/(No. points—No. parameters)]^0.5