Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Real-Time Simulation of Electrical Machines on FPGA Platform

This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software

An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Bacteria colonizing paper machines

Bacteria growing in paper machines can cause several problems. Biofilms detaching from paper machine surfaces may lead to holes and spots in the end product or even break the paper web leading to expensive delays in production. Heat stable endospores will remain viable through the drying section of paper machine, increasing the microbial contamination of paper and board. Of the bacterial species regularly found in the end products, Bacillus cereus is the only one classified as a pathogen. Certain B. cereus strains produce cereulide, the toxin that causes vomiting disease in food poisonings connected to B. cereus. The first aim of this thesis was to identify harmful bacterial species colonizing paper machines and to assess the role of bacteria in the formation of end product defects. We developed quantitative PCR methods for detecting Meiothermus spp. and Pseudoxanthomonas taiwanensis. Using these methods I showed that Meiothermus spp. and Psx. taiwanensis are major biofoulers in paper machines. I was the first to be able to show the connection between end product defects and biofilms in the wet-end of paper machines. I isolated 48 strains of primary-biofilm forming bacteria from paper machines. Based on one of them, strain K4.1T, I described a novel bacterial genus Deinobacterium with Deinobacterium chartae as the type species. I measured the transfer of Bacillus cereus spores from packaging paper into food. To do this, we constructed a green fluorescent protein (GFP) labelled derivative of Bacillus thuringiensis and prepared paper containing spores of this strain. Chocolate and rice were the recipient foods when transfer of the labelled spores from the packaging paper to food was examined. I showed that only minority of the Bacillus cereus spores transferred into food from packaging paper and that this amount is very low compared to the amount of B. cereus naturally occurring in foods. Thus the microbiological risk caused by packaging papers is very low. Until now, the biological function of cereulide for the producer cell has remained unknown. I showed that B. cereus can use cereulide to take up K+ from environment where K+ is scarce: cereulide binds K+ ions outside the cell with high affinity and transports these ions across cell membrane into the cytoplasm. Externally added cereulide increased the growth rate of cereulide producing strains in medium where potassium was growth limiting. In addition, cereulide producing strains outcompeted cereulide non-producing B. cereus in potassium deficient environment, but not when the potassium concentration was high. I also showed that cereulide enhances biofilm formation of B. cereus.

Easily Diagnosable Sequential Machines

This correspondence throws some light into the area of easily diagnosable machines. Given the behavior of a sequential machine in terms of a state table it explores the possibilities of designing a structure, that facilitates easy diagnosis of faults. The objective is achieved through structural decomposition which has already claimed to produce simpler physical realization.

Estimation of soil hydraulic properties and their uncertainty: comparison between laboratory and field experiment

Often the soil hydraulic parameters are obtained by the inversion of measured data (e.g. soil moisture, pressure head, and cumulative infiltration, etc.). However, the inverse problem in unsaturated zone is ill-posed due to various reasons, and hence the parameters become non-unique. The presence of multiple soil layers brings the additional complexities in the inverse modelling. The generalized likelihood uncertainty estimate (GLUE) is a useful approach to estimate the parameters and their uncertainty when dealing with soil moisture dynamics which is a highly non-linear problem. Because the estimated parameters depend on the modelling scale, inverse modelling carried out on laboratory data and field data may provide independent estimates. The objective of this paper is to compare the parameters and their uncertainty estimated through experiments in the laboratory and in the field and to assess which of the soil hydraulic parameters are independent of the experiment. The first two layers in the field site are characterized by Loamy sand and Loamy. The mean soil moisture and pressure head at three depths are measured with an interval of half hour for a period of 1 week using the evaporation method for the laboratory experiment, whereas soil moisture at three different depths (60, 110, and 200 cm) is measured with an interval of 1 h for 2 years for the field experiment. A one-dimensional soil moisture model on the basis of the finite difference method was used. The calibration and validation are approximately for 1 year each. The model performance was found to be good with root mean square error (RMSE) varying from 2 to 4 cm(3) cm(-3). It is found from the two experiments that mean and uncertainty in the saturated soil moisture (theta(s)) and shape parameter (n) of van Genuchten equations are similar for both the soil types. Copyright (C) 2010 John Wiley & Sons, Ltd.

A Hydraulic Micromanipulator

For biological experiments requiring manipulations under a microscope, it is necessary to have remote control for the manipulator. Available systems offer the required accuracy at a high cost. Passive micromanipulators are economical but are deficient in performance, the most serious defects being the inability to attenuate operator-induced vibrations and lack of speed control The manipulator described in this paper provides versatile remote control and may be constructed economically.

A Hydraulic Micromanipulator

For biological experiments requiring manipulations under a microscope, it is necessary to have remote control for the manipulator. Available systems offer the required accuracy at a high cost. Passive micromanipulators are economical but are deficient in performance, the most serious defects being the inability to attenuate operator-induced vibrations and lack of speed control The manipulator described in this paper provides versatile remote control and may be constructed economically.

Minimizing total completion time on batch processing machines

We study the problem of minimizing total completion time on single and parallel batch processing machines. A batch processing machine is one which can process up to B jobs simultaneously. The processing time of a batch is equal to the largest processing time among all jobs in the batch. This problem is motivated by burn-in operations in the final testing stage of semiconductor manufacturing and is expected to occur in other production environments. We provide an exact solution procedure for the single-machine problem and heuristic algorithms for both single and parallel machine problems. While the exact algorithms have limited applicability due to high computational requirements, extensive experiments show that the heuristics are capable of consistently obtaining near-optimal solutions in very reasonable CPU times.

Field evaluation of unsaturated hydraulic conductivity models and parameter estimation from retention data

Predictions of two popular closed-form models for unsaturated hydraulic conductivity (K) are compared with in situ measurements made in a sandy loam field soil. Whereas the Van Genuchten model estimates were very close to field measured values, the Brooks-Corey model predictions were higher by about one order of magnitude in the wetter range. Estimation of parameters of the Van Genuchten soil moisture characteristic (SMC) equation, however, involves the use of non-linear regression techniques. The Brooks-Corey SMC equation has the advantage of being amenable to application of linear regression techniques for estimation of its parameters from retention data. A conversion technique, whereby known Brooks-Corey model parameters may be converted into Van Genuchten model parameters, is formulated. The proposed conversion algorithm may be used to obtain the parameters of the preferred Van Genuchten model from in situ retention data, without the use of non-linear regression techniques.

An Approach for Distance Relay Co-ordination using Support Vector Machines

In this paper, an approach to enhance the Extra High Voltage (EHV) Transmission system distance protection is presented. The scheme depends on the apparent impedance seen by the distance relay during the disturbance. In a distance relay,the impedance seen at the relay location is calculated from the fundamental frequency component of the voltage and current signals. Support Vector Machines (SVMs) are a new learning-byexample are employed in discriminating zone settings (Zone-1,Zone-2 and Zone-3) using the signals to be used by the relay.Studies on 265-bus system, an equivalent of practical Indian Western grid are presented for illustrating the proposed scheme.