Correction to: Comparative analysis of limit equilibrium and numerical methods for prediction of a landslide

Bulletin of Engineering Geology and the Environment - Landslides that occur due to the rapid motion of a rock-mass are a primary risk in mountainous terrains and are a danger to human life and...     

Genetic programming for simultaneous feature selection and classifier design.

This paper presents an online feature selection algorithm using genetic programming (GP). The proposed GP methodology simultaneously selects a good subset of features and constructs a classifier using the selected features. For a c-class problem, it provides a classifier having c trees. In this context, we introduce two new crossover operations to suit the feature selection process. As a byproduct, our algorithm produces a feature ranking scheme. We tested our method on several data sets having dimensions varying from 4 to 7129. We compared the performance of our method with results available in the literature and found that the proposed method produces consistently good results. To demonstrate the robustness of the scheme, we studied its effectiveness on data sets with known (synthetically added) redundant/bad features.     

Phase transformations in thermally exposed Au-Al ball bonds

Gold-aluminum ball bonds were thermally exposed at constant elevated temperatures, and the resultant phase transformations studied in detail. The as-bonded microstructure of a Au-Al ball bond essentially consisted of a reaction zone (termed “alloyed zone” (AZ) in the as-bonded condition) between the Au bump and the bonded Al metallization. It is the growth of the reaction zone between the Au bump and the bonded Al metallization and also the nonbonded Al metallization during thermal exposure that gave rise to the various phase transformations. Au₄Al, Au₈Al₃, and Au₂Al are the predominant phases that grew across the ball bond until the bonded Al metallization is available to take part in the interdiffusion reactions. After the complete consumption of the bonded Al metallization, the Au-Al phases reverse transformed resulting in the formation of the Au₄Al phase in the entire reaction zone across the ball bond (RZ-A). The lateral interdiffusion reactions resulted in the nucleation and the growth of all of the Au-Al phases given by the phase diagram. Kidson’s analysis and Tu et al.’s treatment were extended to a five-phase binary system to explain the phase transformations in thermally exposed Au-Al ball bonds. It is possible for all of the Au-Al phases to grow across a ball bond uninhibited as long as the bonded metallization is available. However, the supply limitation of the bonded metallization gives rise to reverse transformations where Al-rich phases transform to Au-rich phases and eventually result in the formation of the Au₄Al phase in the entire RZ-A. If infinite time is allowed, Au₄Al would dissolve; the extent of which is dependent on the solubility of Al in Au. No supply of Au lateral to the bond causes the reverse transformation of the Au₄Al phase, giving rise to the lateral growth of the remaining Au-Al phases. If infinite time is allowed, the lateral phase transformations would result in the formation of a phase that is dependant on the relative proportion of Au and Al present in the nonbonded metallization (NBM) and Au₄Al below the void line. Hence, the presence of a phase in a particular location of a ball bond is dependent on the time and temperature of thermal exposure.     

Probing the dynamics of nanoparticle growth in a flame using synchrotron radiation

Flame synthesis is one of the most versatile and promising technologies for large-scale production of nanoscale materials. Pyrolysis has recently been shown to be a useful route for the production of single-walled nanotubes, quantum dots and a wide variety of nanostructured ceramic oxides for catalysis and electrochemical applications. An understanding of the mechanisms of nanostructural growth in flames has been hampered by a lack of direct observations of particle growth, owing to high temperatures (2,000 K), rapid kinetics (submillisecond scale), dilute growth conditions (10(-6) volume fraction) and optical emission of synthetic flames. Here we report the first successful in situ study of nanoparticle growth in a flame using synchrotron X-ray scattering. The results indicate that simple growth models, first derived for colloidal synthesis, can be used to facilitate our understanding of flame synthesis. Further, the results indicate the feasibility of studies of nanometre-scale aerosols of toxicological and environmental concern.     

Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the original features. The gating mechanism also helps us to get a better insight into the folding process of proteins. For example, tracking the evolution of different gates we can find which characteristics (features) of the data are more important for the folding process. And, of course, it also reduces the computation time.     

Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles

Abstract

The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.     

Improved field emission from multiwall carbon nanotubes with nano-size defects produced by ultra-low energy ion bombardment

Multiwalled carbon nanotubes were irradiated with ultra-low energy (few eV) nitrogen and hydrogen ions using a microwave discharge. These ultra-low energy plasma-ions remain confined to the nanotube walls, transferring their maximum energy to the carbon atoms, and produce extraordinary structural changes to the carbon nanotube pillars as well as within the carbon nanotubes. Conical shaped emitters and nanotube structures with nano-defects are produced that exhibit remarkable field emission with ultra-low turn-on electric field (∼0.16 V/μm) and a >300-fold increase in the maximum emission current density compared to non-irradiated nanotubes. Doping of nitrogen is also identified due to such irradiation processes.     

Effect of cobalt-60 γ radiation on the physical and chemical properties of poly(ethylene terephthalate) polymer

The structural, optical, and morphological properties of Co⁶⁰ γ irradiation on poly(ethylene terephthalate) polymer samples were studied with X-ray diffraction (XRD), ultraviolet–visible spectroscopy, scanning electron microscopy (SEM), and Raman spectroscopy. The diffraction pattern of virgin sample showed that the polymer was semicrystalline in nature. However, because of irradiation, the crystallinity decreased up to a dose level of 110 kGy and increased up to 300 kGy. The crystallite size, strain, and dislocation were calculated from the XRD data, and the crystallite size decreased from 291.07 to 346.90 Å. The absorption edge shifted from 315 to 330 nm, and the band gap of the samples decreased from 3.79 to 3.66 eV. The SEM micrographs showed radial bulging along with inhomogeneous liner exfoliation, and also, a rocky shape pattern with different sizes was observed. A significant change was found in the Raman spectra of the γ-irradiated polymer at the highest dose. The results of the structural, optical, and morphological studies show recovery characteristics at the highest dose level of 300 kGy. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Chemical modification of metallocene‐based polyethylene–octene elastomer through solution grafting of acrylic acid and its effect on the physico‐mechanical properties

In the present work, the metallocene‐based polyethylene–octene elastomer (POE) was chemically modified by solution grafting of acrylic acid in presence of benzoyl peroxide. The relative proportions of graft and gel formation were optimized through %weight gain, Fourier Transform infrared spectroscopy, elemental analysis and proton nuclear magnetic resonance spectroscopy. The gel formation in the POE matrix was found to be the prime competitor. The effect of grafting at its maximum level on various physicomechanical properties was thoroughly investigated, using X‐ray diffraction analysis, differential scanning calorimetry, mechanical, dynamic mechanical, and thermogravimetric analysis. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007