Abstract: Tool Tracker is a client-server based application. It is essentially a catalogue of various network monitoring and management tools that are available online. There is a database maintained on the server side that contains the information about various tools. Several clients can access this information simultaneously and utilize this information. The various categories of tools considered are packet sniffers, port mappers, port scanners, encryption tools, and vulnerability scanners etc for the development of this application. This application provides a front end through which the user can invoke any tool from a central repository for the purpose of packet sniffing, port scanning, network analysis etc. Apart from the tool, its description and the help files associated with it would also be stored in the central repository. This facility will enable the user to view the documentation pertaining to the tool without having to download and install the tool. The application would update the central repository with the latest versions of the tools. The application would inform the user about the availability of a newer version of the tool currently being used and give the choice of installing the newer version to the user. Thus ToolTracker provides any network administrator that much needed abstraction and ease-ofuse with respect to the tools that he can use to efficiently monitor a network.
Abstract: This study is concerned with a new adaptive impedance control strategy to compensate for unknown time-varying environment stiffness and position. The uncertainties are expressed by Function Approximation Technique (FAT), which allows the update laws to be derived easily using Lyapunov stability theory. Computer simulation results are presented to validate the effectiveness of the proposed strategy.
Abstract: This paper proposes a specialized Web robot to automatically collect objectionable Web contents for use in an objectionable Web content classification system, which creates the URL database of objectionable Web contents. It aims at shortening the update period of the DB, increasing the number of URLs in the DB, and enhancing the accuracy of the information in the DB.
Abstract: Grid environments include aggregation of
geographical distributed resources. Grid is put forward in three types
of computational, data and storage. This paper presents a research on
data grid. Data grid is used for covering and securing accessibility to
data from among many heterogeneous sources. Users are not worry
on the place where data is located in it, provided that, they should get
access to the data. Metadata is used for getting access to data in data
grid. Presently, application metadata catalogue and SRB middle-ware
package are used in data grids for management of metadata. At this
paper, possibility of updating, streamlining and searching is provided
simultaneously and rapidly through classified table of preserving
metadata and conversion of each table to numerous tables.
Meanwhile, with regard to the specific application, the most
appropriate and best division is set and determined. Concurrency of
implementation of some of requests and execution of pipeline is
adaptability as a result of this technique.
Abstract: Nature conducts its action in a very private manner. To
reveal these actions classical science has done a great effort. But
classical science can experiment only with the things that can be seen
with eyes. Beyond the scope of classical science quantum science
works very well. It is based on some postulates like qubit,
superposition of two states, entanglement, measurement and
evolution of states that are briefly described in the present paper.
One of the applications of quantum computing i.e.
implementation of a novel quantum evolutionary algorithm(QEA) to
automate the time tabling problem of Dayalbagh Educational Institute
(Deemed University) is also presented in this paper. Making a good
timetable is a scheduling problem. It is NP-hard, multi-constrained,
complex and a combinatorial optimization problem. The solution of
this problem cannot be obtained in polynomial time. The QEA uses
genetic operators on the Q-bit as well as updating operator of
quantum gate which is introduced as a variation operator to converge
toward better solutions.
Abstract: In this study, we explore the use of information for inventory decision in the healthcare organization (HO). We consider the scenario when the HO can make use of the information collected from some correlated products to enhance its inventory planning. Motivated by our real world observations that HOs adopt RFID and bar-coding system for information collection purpose, we examine the effectiveness of these systems for inventory planning with Bayesian information updating. We derive the optimal ordering decision and study the issue of Pareto improvement in the supply chain. Our analysis demonstrates that RFID system will outperform the bar-coding system when the RFID system installation cost and the tag cost reduce to a level that is comparable with that of the barcoding system. We also show how an appropriately set wholesale pricing contract can achieve Pareto improvement in the HO supply chain.
Abstract: The least mean square (LMS) algorithmis one of the
most well-known algorithms for mobile communication systems
due to its implementation simplicity. However, the main limitation
is its relatively slow convergence rate. In this paper, a booster
using the concept of Markov chains is proposed to speed up the
convergence rate of LMS algorithms. The nature of Markov
chains makes it possible to exploit the past information in the
updating process. Moreover, since the transition matrix has a
smaller variance than that of the weight itself by the central limit
theorem, the weight transition matrix converges faster than the
weight itself. Accordingly, the proposed Markov-chain based
booster thus has the ability to track variations in signal
characteristics, and meanwhile, it can accelerate the rate of
convergence for LMS algorithms. Simulation results show that the
LMS algorithm can effectively increase the convergence rate and
meantime further approach the Wiener solution, if the
Markov-chain based booster is applied. The mean square error is
also remarkably reduced, while the convergence rate is improved.
Abstract: This paper deals with efficient quadrature formulas involving functions that are observed only at fixed sampling points. The approach that we develop is derived from efficient continuous quadrature formulas, such as Gauss-Legendre or Clenshaw-Curtis quadrature. We select nodes at sampling positions that are as close as possible to those of the associated classical quadrature and we update quadrature weights accordingly. We supply the theoretical quadrature error formula for this new approach. We show on examples the potential gain of this approach.