فهرست مطالب

International Journal of Information Science and Management
Volume:5 Issue: 2, Jul-Dec 2007

  • تاریخ انتشار: 1385/10/19
  • تعداد عناوین: 9
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  • J. Mehrad Pages 1-9
    Regional Library of Science and Technology (RLST), located in Fars State, is one of the international institutions of the Ministry of Science, Research and Technology which is active in the area of information production and dissemination. The following interview is aimed at providing the information societies as well as our respectable readers with useful information regarding RLST.
  • A. H. Jahangir, M. Keshtgary Pages 11-34
    Society is growing increasingly dependent upon large-scale, highly distributed systems that operate in unbounded open network environments. Unless safeguards are incorporated in the system, a failure of even a single component, e.g. a link or a node, can significantly impact the network performance and can cause highly expensive damages. The discipline of survivability attempts to ensure that network systems can deliver essential services and maintains inherent properties such as integrity, confidentiality, and performance, in the presence of attacks, failures or accidents. Optical networks based on Wavelength-Division Multiplexing (WDM) technology can potentially transfer hundreds of gigabits of data per second in the network. WDM networks are believed to be a promising candidate to meet the explosive increase of bandwidth demand in the Internet. However, the high capacity of a link has the drawback that a failure can potentially lead to the loss of a large amount of data. This is why the survivability performance of networks is an important research issue. The objective of this paper is to answer questions like “What does survivability mean?”, “Why is it important?”, “How does it differ from fault tolerance?” and “How is it being measured?” by surveying the concepts of information and network survivability, its relation to and its distinction from dependability, fault tolerance and security. The survivability of optical networks and protection techniques in WDM networks are reviewed as an example of techniques to improve the network survivability. The problem of survivability measures from network analysis and design point of view is also presented in the paper.
  • M. Mashinchi, H.R. Maleki Pages 35-45
    Generally, an engineering design problem has multiple objective functions. Some of these problems can be formulated as multiobjective geometric programming models. On the other hand,often in the real world, coefficients of the objective functions are not known precisely. Coefficients may be interpreted as fuzzy numbers, which lead to a multiobjective geometric programming with fuzzy parameters. In this paper, we solve the multiobjective geometric programming problem with fuzzy parameters by applying a linear ranking function. The linear ranking function is used to compare fuzzy numbers. Finally, a numerical example is given.
  • A. Kalantari Oskouee Pages 47-65
    Nowadays, standardized metadata for geospatial data is a key in sharing and finding information on the web and crucial in building Geospatial Data Infrastructure (GDI). The main objective of this paper was to develop a web-based metadata dissemination system for in-situ sensors based on, most importantly, interoperable, standard and open technologies introduced by Open GIS Consortium (OGC), namely Geography Markup Language (GML). In this research, at first a use case diagram was developed to demonstrate the user’s requirement. Then, an application XML schema based on user’s requirement was created. To build this schema, some GML schema documents (developed by Open GIS Consortium (OGC)) were imported into the application schema. System architecture was designed based on client/server model and a UML class diagram was also developed to present all classes and their attributes, operations and associations within the system. Implementation was conducted using GML, XML, XMLHTTP, DOM, ASP, and VBScript that brought out a web-network-based in-situ sensors metadata application. This application provided a user friendly interface to search and find sensor related information. Results showed that although GML and XML are powerful tools to build geo-metadata, it is important to note that GML document size may be a problem when dealing with huge amount of data.
  • M. Zamani, N. Najmaei, I. Shames, A. A. Safavi Pages 67-82
    In this paper, the advantage of reinforcement learning to develop a new traffic shaper is invoked in order to obtain a reasonable utilization of bandwidth while preventing traffic overload in other parts of the network. This leads to a reduction in the total number of packet droppings in the whole network. The method is implemented in a novel proposed intelligent simulation environment. Keeping dropping probability low while injecting as many packets as possible into the network, in order to utilize the available bandwidth, shows satisfactory behavior in simulation environment. On the other hand, the results show that the system can perform well even in situations that have not been previously introduced to the system.
  • S. K. Srivatsa, A. Ezil Sam Leni Pages 83-91
    As wireless networks with high data rate get widely deployed, improving the performance of TCP over these networks plays vital role. Wireless link losses have dramatic adverse impact on TCP performance due to the difficulty in distinguishing the congestion losses from wireless link losses. We first, studied the various existing Bandwidth Estimation Algorithms over the wireless networks. In this paper, we propose an enhanced bandwidth estimation technique with congestion control algorithms to improve TCP performance over wireless link with random loss. We propose, a new technique called TCP- BWIW to estimate the bandwidth and the congestion window is set accordingly. The performance of TCP-BWIW is analyzed, and it mitigates the Network congestion.
  • M. Yabandeh, A. Nayyeri, C. Lucas Pages 93-98
    Real Coded Genetic Algorithm, RCGA, is the type of GA which operates on chromosomes with real valued parameters. Different mutation and crossover operations are defined for RCGA. One usable crossover for this kind of GA is to consider its chromosomes simply as bit strings and utilize the same operations as Binary Coded GA. In this paper, we attempt to show that this kind of crossover can not hasten the convergence process unless the break points fall at the boundaries of parameters in the chromosome.
  • M. R. Jafari, K. Salahshoor Pages 99-121
    This paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (RBF) neural networks, i.e. growing and pruning radial basis function (GAP-RBF) and minimal resource allocation network (MRAN) to cater for on-line identification of non-linear systems. The original sequential learning algorithm is based on the repetitive utilization of sequential input-output data in order to accomplish the training phase. Some interesting modifications have been proposed in the growing and pruning neurons criteria of the original GAP-RBF neural network to make the resulting modified GAP-RBF (MGAP-RBF) neural network suitable for on-line system identification applications. The Unscented Kalman Filter (UKF) has been proposed as a new learning algorithm to update the parameters of MRAN, GAP-RBF and MGAP-RBF neural networks. Moreover, to keep the resulting parameter estimation routines more sensitive to track any possible time-varying system dynamics, a variable forgetting factor strategy has been included in the UKF learning algorithm. The proposed identification algorithms have been tested on a nonisothermal continuous stirred tank reactor (CSTR) and the chaotic Mackey Glass time-series as two different benchmark problems. The resulting performances of the MRAN, GAP-RBF and the proposed MGAP-RBF neural networks being estimated with the extended Kalman filter (EKF) or the UKF learning algorithm have been evaluated for comparison purposes. Simulation results show the superiority of the proposed MGAP-RBF neural network estimated with the UKF learning algorithm.
  • S. Rezazadeh, A. Zolghadrasli Pages 123-139
    In this paper, we introduce a multiresolution watermarking method for copyright protection of digital images. The method is based on the discrete wavelet transform. A noise type Gaussian sequence is used as watermark. To embed the watermark robustly and imperceptibly, watermark components are added to the significant coefficients of each selected subband by considering the human visual system (HVS) characteristics. Some small modifications are performed to improve the HVS model. The host image is needed in watermark extraction procedure, and Normalized Correlation Function (NCF) is used to measure similarities of extracted watermarks. It is shown that this method is robust against wide variety of attacks. Comparison with the existing methods shows the better performance of this suggested method.