Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

A waveform concatenation technique for text-to-speech synthesis

Designing text-to-speech systems capable of producing natural sounding speech segments in different Indian languages is a challenging and ongoing problem. Due to the large number of possible pronunciations in different Indian languages, a number of speech segments are needed to be stored in the speech database while a concatenative speech synthesis technique is used to achieve highly natural speech segments. However, the large speech database size makes it unusable for small hand held devices or human computer interactive systems with limited storage resources. In this paper, we proposed a fraction-based waveform concatenation technique to produce intelligible speech segments from a small footprint speech database. The results of all the experiments performed shows the effectiveness of the proposed technique in producing intelligible speech segments in different Indian languages even with very less storage and computation overhead compared to the existing syllable-based technique.     

Geomorphology Based Semi-Distributed Approach for Modelling Rainfall-Runoff Process

This study presents a geomorphology based semi-distributed methodology for prediction of runoff of a catchment. In this proposed methodology, the catchment area is divided into a number of sub-catchments using the Thiessen polygon method. The rainfall records of particular rain-gauge station are considered as uniformly distributed over the entire sub-watershed. Four different weighting factors are proposed to obtain the sub-catchment’s contribution towards runoff. The weighting factors are calculated based on the geomorphological parameters of the catchment. The geomorphological parameters of the sub-watersheds are obtained from SRTM digital elevation data. The weighted contributions from all the sub-watersheds at current and previous time steps and the previous time step discharge are used to develop an Artificial Neural Network (ANN) for predicting the discharge at the basin outlet. A lump model considering average rainfall of the catchment is also developed using ANN for evaluating the performance of the proposed distributed model. For the lump model, average rainfall is calculated using Thiessen polygon method. The historic rainfall and runoff data recorded at the Dikrong basin, a sub-catchment of the river Brahmaputra is used to evaluate the efficiency of the developed methodology. The evaluation results show that the presented model is superior to the lump model and has the potential for field application. A comparative study is also carried out to obtain the most influential combination of geomorphological parameters in predicting the catchment’s runoff.     

Analyzing collective behavior from blogs using swarm intelligence

With the rapid growth of the availability and popularity of interpersonal and behavior-rich resources such as blogs and other social media avenues, emerging opportunities and challenges arise as people now can, and do, actively use computational intelligence to seek out and understand the opinions of others. The study of collective behavior of individuals has implications to business intelligence, predictive analytics, customer relationship management, and examining online collective action as manifested by various flash mobs, the Arab Spring (2011) and other such events. In this article, we introduce a nature-inspired theory to model collective behavior from the observed data on blogs using swarm intelligence, where the goal is to accurately model and predict the future behavior of a large population after observing their interactions during a training phase. Specifically, an ant colony optimization model is trained with behavioral trend from the blog data and is tested over real-world blogs. Promising results were obtained in trend prediction using ant colony based pheromone classier and CHI statistical measure. We provide empirical guidelines for selecting suitable parameters for the model, conclude with interesting observations, and envision future research directions.     

Optimal design of unit hydrographs using probability distribution and genetic algorithms

A nonlinear optimization model is developed to transmute a unit hydrograph into a probability distribution function (PDF). The objective function is to minimize the sum of the square of the deviation between predicted and actual direct runoff hydrograph of a watershed. The predicted runoff hydrograph is estimated by using a PDF. In a unit hydrograph, the depth of rainfall excess must be unity and the ordinates must be positive. Incorporation of a PDF ensures that the depth of rainfall excess for the unit hydrograph is unity, and the ordinates are also positive. Unit hydrograph ordinates are in terms of intensity of rainfall excess on a discharge per unit catchment area basis, the unit area thus representing the unit rainfall excess. The proposed method does not have any constraint. The nonlinear optimization formulation is solved using binary-coded genetic algorithms. The number of variables to be estimated by optimization is the same as the number of probability distribution parameters; gamma and log-normal probability distributions are used. The existing nonlinear programming model for obtaining optimal unit hydrograph has also been solved using genetic algorithms, where the constrained nonlinear optimization problem is converted to an unconstrained problem using penalty parameter approach. The results obtained are compared with those obtained by the earlier LP model and are fairly similar.     

On the Role of C Addition on α Precipitation in a β Titanium Alloy

The onset of α nucleation in a carbon containing β-titanium alloy has been investigated by coupling atom probe tomography (APT) with transmission electron microscopy. The analysis of the APT results indicates that in addition to ω precipitates that can act as potential α nucleation sites, carbon atoms tend to form clusters within the β-matrix, which in turn give rise to additional nucleation sites for α, resulting in finer scale α precipitates due to increased nucleation density.     

Experimental and theoretical investigations of the adhesion time of Penicillium spores to cedar wood surface

In this study, the adhesion of 4 Penicillium strains (Penicillium granulatum, Penicillium crustosum, Penicillium commune and Penicillium chrysogenum) on cedar wood was examined qualitatively and quantitatively by using the extended DLVO (XDLVO) approach and the environmental scanning electronic microscopy (ESEM) technique. A comparison between the XDLVO theories and the ESEM technique was also investigated. The adhesion tests revealed that P. chrysogenum was not able to adhere on the cedar wood substrata, as predicted by the XDLVO approach. We have also found by ESEM that the three Penicillium strains (P. granulatum, P. crustosum, P. commune) adhered on wood, as not predicted theoretically.Moreover, the time of adhesion (3 h and 24 h) was used not only to compare the capacity of adhesion according to contact time but also to explain the discrepancies between the XDLVO approach prediction and the adhesion experiments. A positive relationship between the XDLVO approach and adhesion experiments has been observed after 3 h of adhesion. In contrast, a contradiction between the XDLVO predictions and the adhesion test results has been noted after 24 h of adhesion of Penicillium strains to the wood surface.     

Evaluation of Optimal River Training Work Using GA Based Linked Simulation-Optimization Approach

Use of structural measures for controlling a river to minimize its devastating effect and to utilize it for the benefit of mankind is a common practice all over the world. Because of high investment, such measures require prior investigation through model study. As lab based physical model study is very expensive and time consuming, mathematical modeling is generally used for investigating different alternatives of river training works. In this study, a new approach is proposed for deciding appropriate river training measure in a particular reach of a river or channel. In this methodology, an optimization model is linked with the hydrodynamic model for obtaining cost effective combination of groynes which will maintain a user defined flow speed in a pre-decided portion of a river reach. The optimization model is developed using binary coded Genetic Algorithm (GA) and the flow simulation model uses the Beam and Warming scheme for solving the two dimensional (2D) hydrodynamic equations of unsteady flow. The performance of the model is tested by applying the methodology in a rectangular channel for attaining different target speed values at a pre-defined portion of the channel and logical results have been obtained for all the tested scenarios.