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.

Genetic algorithm for satellite customer assignment

The problem of assigning customers to satellite channels is considered. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of this approach with the standard optimization method is presented to show the advantages of this approach in terms of computation time

Diversity of DNA methyltransferases that recognize asymmetric target sequences

DNA methyltransferases (MTases) are a group of enzymes that catalyze the methyl group transfer from S-adenosyl-L-methionine in a sequence-specific manner. Orthodox Type II DNA MTases usually recognize palindromic DNA sequences and add a methyl group to the target base (either adenine or cytosine) on both strands. However, there are a number of MTases that recognize asymmetric target sequences and differ in their subunit organization. In a bacterial cell, after each round of replication, the substrate for any MTase is hemimethylated DNA, and it therefore needs only a single methylation event to restore the fully methylated state. This is in consistent with the fact that most of the DNA MTases studied exist as monomers in solution. Multiple lines of evidence suggest that some DNA MTases function as dimers. Further, functional analysis of many restriction-modification systems showed the presence of more than one or fused MTase genes. It was proposed that presence of two MTases responsible for the recognition and methylation of asymmetric sequences would protect the nascent strands generated during DNA replication from cognate restriction endonuclease. In this review, MTases recognizing asymmetric sequences have been grouped into different subgroups based on their unique properties. Detailed characterization of these unusual MTases would help in better understanding of their specific biological roles and mechanisms of action. The rapid progress made by the genome sequencing of bacteria and archaea may accelerate the identification and study of species- and strain-specific MTases of host-adapted bacteria and their roles in pathogenic mechanisms.

Comparative study on damage identification from lso-Eigen-Value-Change contours and smeared damage model

The paper proposes two methodologies for damage identification from measured natural frequencies of a contiguously damaged reinforced concrete beam, idealised with distributed damage model. The first method identifies damage from Iso-Eigen-Value-Change contours, plotted between pairs of different frequencies. The performance of the method is checked for a wide variation of damage positions and extents. The method is also extended to a discrete structure in the form of a five-storied shear building and the simplicity of the method is demonstrated. The second method is through smeared damage model, where the damage is assumed constant for different segments of the beam and the lengths and centres of these segments are the known inputs. First-order perturbation method is used to derive the relevant expressions. Both these methods are based on distributed damage models and have been checked with experimental program on simply supported reinforced concrete beams, subjected to different stages of symmetric and un-symmetric damages. The results of the experiments are encouraging and show that both the methods can be adopted together in a damage identification scenario.

Identification and expression of the 20 kd structural protein gene of colitis bacteriophage

The 2.3 kb BamHI fragment from the colitis bacteriophage DNA was transcribed and translated into a 20 kd structural protein P6, in a coupled transcription-translation system derived from Escherichia coli. This protein was expressed in vivo by the 2.3 kb DNA cloned in pBR322. The gene with the regulatory elements for this protein was located on the 680 bp AvaII fragment of the insert DNA. It hybridized with two RNAs of sizes 520 and 1630 nucleotides indicating that both are messengers for the 20 kd protein. Dot-blot hybridization showed that the transcripts for P6 reached a maximum level at 12 min after phage infection.

Identification of corona discharge-induced SF6 oxidation mechanisms using SF6/18O2/H216O and SF6/16O2/H218O gas mixtures

The absolute yields of gaseous oxyfluorides SOF2, SO2F2, and SOF4 from negative, point-plane corona discharges in pressurized gas mixtures of SF6 with O2 and H2O enriched with18O2 and H2 18O have been measured using a gas chromatograph-mass spectrometer. The predominant SF6 oxidation mechanisms have been revealed from a determination of the relative18O and16O isotope content of the observed oxyfluoride by-product. The results are consistent with previously proposed production mechanisms and indicate that SOF2 and SO2F2 derive oxygen predominantly from H2O and O2, respectively, in slow, gas-phase reactions involving SF4, SF3, and SF2 that occur outside of the discharge region. The species SOF4 derives oxygen from both H2O and O2 through fast reactions in the active discharge region involving free radicals or ions such as OH and O, with SF5 and SF4.