Prony-Based Optimal Bayes Fault Classification of Overcurrent Protection

The development of deregulation and demand for high-quality electrical energy has lead to a new requirement in different fields of power systems. In the protection field, this means that high sensitivity and fast operation during the fault are required while maltripping of relay protection is not acceptable. One case that may lead to a maltrip of the high-sensitive overcurrent relay is the starting current of the induction motor or inrush current of the transformer. This transient current has the potential to affect the correct operation of protection relays close to the component being switched. In the case of switching events, such transients must not lead to overcurrent relay operation; therefore, a reliable and secure relay response becomes a critical matter. Meanwhile, proper techniques must be used to prevent maltripping of such relays, due to transient currents in the network. In this paper, the optimal Bayes classifier is utilized to develop a method for discriminating the fault from nonfault events. The proposed method has been designed based on extracting the modal parameters of the current waveform using the Prony method. By feeding the fundamental frequency damping and ratio of the 2nd harmonic amplitude over the fundamental harmonic amplitude to the classifier, the fault case is discriminated from the switching case. The suitable performance of this algorithm is demonstrated by simulation of different faults and switching conditions on a power system using PSCAD/EMTDC software.     

Coordinated design of TCSC and PSS controllers using VURPSO and Genetic algorithms for multi-machine power system stability

Thyristor controlled series capacitor (TCSC) can regulate line impedance and therefore increase transferred power of the system. On the other hand power system stabilizer (PSS) increases dynamic stability of generator. To enhance the stability, combination of TCSC and PSS can be applied, and in such a case coordination of TCSC and PSS is essential. This paper applies this combined controller in order to enhance the stability of multi-machine system. Parameters of these controllers are optimized by velocity update relaxation particle swarm optimization (VURPSO) algorithm and Genetic algorithm (GA). The simulation results show that the combination of VURPSO algorithm and GA leads to a better design and stability.     

A multi-objective strategy in genetic algorithms for gene selection of gene expression data

A microarray machine offers the capacity to measure the expression levels of thousands of genes simultaneously. It is used to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes relative to the small number of available samples, and the fact that many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to improved accuracy in the classification. Hence, this paper proposes a solution to the problems by using a multiobjective strategy in a genetic algorithm. This approach was tried on two benchmark gene expression data sets. It obtained encouraging results on those data sets as compared with an approach that used a single-objective strategy in a genetic algorithm. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Selecting informative genes from microarray data by using hybrid methods for cancer classification

Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

High responsivity silicon MOS phototransistors

We describe a metal-oxide silicon (MOS) phototransistor that relies on a novel lateral doping scheme that creates a p-i-n junction configuration for light detection. This is essentially a hybrid device with the horizontal structure of a p-i-n diode and the vertical structure of a MOS field-effect transistor. The lateral p-i-n diode detects light whereas the gate can be used to change the current flowing through the device; making it appear as a MOSFET. This feature makes it easy to integrate it with other conventional MOSFETs on a CMOS process flow. The device shows high optical responsivities that persist to wavelengths in the near-ultraviolet region. The fabrication of the device as well as its electrical and optical characteristics is described.     

PETOOL: MATLAB-based one-way and two-way split-step parabolic equation tool for radiowave propagation over variable terrain

A MATLAB-based one-way and two-way split-step parabolic equation software tool (PETOOL) has been developed with a user-friendly graphical user interface (GUI) for the analysis and visualization of radio-wave propagation over variable terrain and through homogeneous and inhomogeneous atmosphere. The tool has a unique feature over existing one-way parabolic equation (PE)-based codes, because it utilizes the two-way split-step parabolic equation (SSPE) approach with wide-angle propagator, which is a recursive forward–backward algorithm to incorporate both forward and backward waves into the solution in the presence of variable terrain. First, the formulation of the classical one-way SSPE and the relatively-novel two-way SSPE is presented, with particular emphasis on their capabilities and the limitations. Next, the structure and the GUI capabilities of the PETOOL software tool are discussed in detail. The calibration of PETOOL is performed and demonstrated via analytical comparisons and/or representative canonical tests performed against the Geometric Optic (GO) + Uniform Theory of Diffraction (UTD). The tool can be used for research and/or educational purposes to investigate the effects of a variety of user-defined terrain and range-dependent refractivity profiles in electromagnetic wave propagation.

Program summary

Program title: PETOOL (Parabolic Equation Toolbox)Catalogue identifier: AEJS_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJS_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 143 349No. of bytes in distributed program, including test data, etc.: 23 280 251Distribution format: tar.gzProgramming language: MATLAB (MathWorks Inc.) 2010a. Partial Differential Toolbox and Curve Fitting Toolbox requiredComputer: PCOperating system: Windows XP and VistaClassification: 10Nature of problem: Simulation of radio-wave propagation over variable terrain on the Earth?s surface, and through homogeneous and inhomogeneous atmosphere.Solution method: The program implements one-way and two-way Split-Step Parabolic Equation (SSPE) algorithm, with wide-angle propagator. The SSPE is, in general, an initial-value problem starting from a reference range (typically from an antenna), and marching out in range by obtaining the field along the vertical direction at each range step, through the use of step-by-step Fourier transformations. The two-way algorithm incorporates the backward-propagating waves into the standard one-way SSPE by utilizing an iterative forward–backward scheme for modeling multipath effects over a staircase-approximated terrain.Unusual features: This is the first software package implementing a recursive forward–backward SSPE algorithm to account for the multipath effects during radio-wave propagation, and enabling the user to easily analyze and visualize the results of the two-way propagation with GUI capabilities.Running time: Problem dependent. Typically, it is about 1.5 ms (for conducting ground) and 4 ms (for lossy ground) per range step for a vertical field profile of vector length 1500, on Intel Core 2 Duo 1.6 GHz with 2 GB RAM under Windows Vista.     

The effects of modified atmosphere gas composition on microbiological criteria, color and oxidation values of minced beef meat

This paper reports the effects of modified atmosphere gas compositions with different concentrations of CO(2)/O(2)/N(2) on color properties (L*, a* and b* values), oxidation stability (TBARS value) and microbiological properties of minced beef meat stored at +4 °C. Sampling was carried out on the 1st, 3rd, 5th, 7th, 9th, 11th and 14th day of storage. The gas mixtures used were as follows: (i) %30O(2) + %70CO(2) (MAP1), (ii) %50O(2) + %50CO(2) (MAP2), (iii) %70O(2) + %30CO(2) (MAP3), (iv) %50O(2) + %30CO(2) + %20N(2) (MAP4), and (v) %30O(2) + %30CO(2) + %40N(2) (MAP5). Control samples (AP) were packaged under atmospheric air. Pseudomonas, lactic acid bacteria, Brochothrix thermosphacta, and Enterobacteriaceae members were monitored. Among these five modified atmosphere gas compositions, the best preservation for minced beef meat was in MAP4 gas combination maintaining acceptable color together with oxidation stability and acceptable microbial loads until the end of storage period of fourteen days.     

Effect of cooling methods on residual compressive strength and cracking behavior of fly ash concretes exposed at elevated temperatures

This paper presents the effects of cooling methods on residual compressive strength and cracking behavior of concretes containing four different class F fly ash contents of 10%, 20%, 30% and 40% as partial replacement of cement at various elevated temperatures. The residual compressive strength of the aforementioned fly ash concretes is measured after being exposed to 200, 400, 600 and 800 °C temperatures and two different cooling methods, for example, slow cooling and rapid water cooling. Results show that the residual compressive strengths of all fly ash concretes decrease with increase in temperatures irrespective of cooling regimes, which is similar to that of ordinary concrete. Generally, control ordinary concrete and all fly ash concretes exhibited between 10% and 35% more reduction in residual compressive strength because of rapid cooling than slow cooling except few cases. Cracks are observed over concrete specimens after being exposed to temperatures ranging from 400 to 800 °C. Samples that are slowly cooled developed smaller cracks than those rapidly cooled. At 800 °C, all fly ash concretes that are exposed to rapid cooling showed the most severe cracking. X‐ray diffraction analysis shows reduction of Ca(OH)₂ peak and formation of new calcium silicate peak in concretes containing 20% and 40% fly ash when subjected to 800 °C in both cooling methods. Thermo gravimetric analysis and differential thermal analysis results show increase in thermal stability of concrete with increase in fly ash contents. The existing Eurocode also predicted the compressive strength of fly ash concretes with reasonable accuracy when subjected to the aforementioned elevated temperatures and cooling methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Swelling behavior of polystyrene networks in some aliphatic esters and linear polystyrene solutions

Summary Polystyrene networks were synthesized by free radical polymerization of styrene in the presence of dibenzoyl peroxide as an initiator, divinylbenzene as a crosslinker at 50 °C in toluene under nitrogen atmosphere. The swelling behavior of the synthesized polystyrene networks were studied at different temperatures in methyl acetate, ethyl acetate, propyl acetate, isopropyl acetate, butyl acetate, isobutyl acetate, tert-butyl acetate, and isopentyl acetate. Equations were given for the variation of the polymer-solvent interaction parameter, χ₁₂, as a function of reciprocal absolute temperature in the temperature range from 25 to 75 °C. Polystyrene networks were swollen in linear polystyrene solutions in toluene of different concentrations. Linear polystyrene samples were almost monodisperse and of high molecular weight. The equilibrium swelling degrees were evaluated using the Flory-Rehner theory. The relation of volume swelling ratio, q_v, to the volume fraction of the linear polymer in solution, φ, was evaluated and characterized by interaction parameter of crosslinked polystyrene with linear polystyrene, χ₂₃. The parameter χ₂₃ was found around zero as expected from mixtures of similar chemical structures by extrapolating the values of χ₂₃ at tested concentrations to zero solvent concentration.     

Preparation,characterization, and dynamic adsorption–desorption studies on polypyrrole encapsulated TiO2 nanoparticles

Binary doped polypyrrole (PPy) encapsulated Titania (TiO₂) nanoparticles were prepared by oxidative polymerization using FeCl₃ as oxidant in presence of camphorsulfonic acid (CSA) as surfactant. Both FeCl₃ (oxidant) and camphorsulfonic acid (surfactant) also act as dopant and hence thus prepared polypyrrole/Titania (TiO₂@PPy) is termed as binary doped nanocomposite i.e. FeCl₃ dopes polypyrrole by oxidation mechanism while camphorsulfonic acid dopes polypyrrole by protonic doping mechanism. The TiO₂@PPy coreshell nanocomposites were characterized by Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), thermogravimetry, differential scanning calorimetry (DSC), field emission‐scanning electron microscopy (FE‐SEM), and inductance‐capacitance‐resistance (LCR) measurements. The results indicated that the structural and electrical properties of the TiO₂@PPy coreshell nanocomposites were significantly influenced by the extent of TiO₂ nanoparticles loading of polypyrrole. The direct current (DC) electrical conductivity of the as‐prepared TiO₂@PPy coreshell nanocomposites was higher than that of PPy. As‐prepared TiO₂@PPy coreshell nanocomposites were also studied for their dielectric losses for alternating current (AC) which is useful characteristic for their application in the fabrication of charge storing devices. TiO₂@PPy coreshell nanocomposites showed synergistic effect of combining components in improving their alcohol sensing properties. This improvement may be attributed to the adsorption on and desorption from alcohols TiO₂@PPy interface of the nanocomposites and alcohol vapors causing decrease in depletion region. The TiO₂@PPy coreshell nanocomposites were observed to show better reproducibility of electrical conductivity and fast self‐recovery during the alcohol vapor sensing process. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43411.