Small torsional vibration superposed on finitely deformed state of a circular cylindrical rod of transversely isotropic elastic material

Starting with a class of small deformations superposed on a finitely deformed state of a transversely isotropic elastic solid, we study a problem of small torsional vibration superposed on homogeneous finitely deformed state of a circular cylindrical rod made of transversely isotropic elastic material. It has been found that free vibration is possible and, due to anisotropy, the speed of propagation of waves of torsion along the cylinder is increased or decreased according as the initial stressed state is under tension or compression.     

Chemical,rheological and parotta making characteristics of flourmill streams

Chemical, rheological and parotta-making characteristics of wheat-milling flour streams were studied with the main aim of developing a speciality flour for parotta. Important quality characteristics such as ash, flour colour, dry gluten content, sedimentation value, free and bound lipid content, farinograph and alveograph characteristics of the mill streams were determined. The studies showed an increase in ash, gluten content and sedimentation value with increasing numbers of breaks in the flour streams. An increase in percentage whiteness and bound lipids was observed in the first five reduction passages (C1 to C5). The alveograph characteristics indicated that the average abscissa at rupture (L) length of the curve increased with increasing reduction streams from C1 to C5, and also that the curves were better balanced when compared to 1 BK to 5 BK. The parottas made from the first five break passages had a decreased spread ratio, dull brown colour, and fused layers and lower overall quality score (43–79). The initial reduction streams (C1 to C5) produced good quality parottas in terms of appearance, spread, layers and texture. The shear force values indicating the texture of the product ranged from 1,120 to 1,250 g. The speciality flour made by combining C1 to C5 streams had 0.45% ash, 9.63% dry gluten, 45 ml sodium dodecyl sulphate sedimentation value, 0.7% free lipid and 1.8% bound lipid and produced parottas having creamish white colour, excellent pliability, thin, transparent and distinct layers, soft texture and moderate chewiness. In the mouth the parottas broke down easily, without leaving any residue. The overall quality score of parotta was highest (93.5) for the speciality flour when compared to break and reduction streams (43–77 and 56–92 respectively).     

Accuracy of self-reported data for estimating crash severity

Estimated traveling speed and speed limit have typically been used in population-based surveillance data to estimate crash severity. The accuracy of these measures in predicting crash severity is unknown. The Partners for Child Passenger Safety (PCPS) surveillance system offers a unique opportunity to compare these measures, as well as a novel measure of crash severity, “self-report” delta-V, to the accepted measure of delta-V estimated during detailed crash-investigations in 118 crashes. This “self-report” delta-V was computed from the estimated traveling speeds and direction of impact obtained from telephone interviews with drivers. These “self-reported” delta-V estimates are modestly associated with crash-investigation delta-V estimates, with the degree of association a function of the direction of impact: when the respondent was struck from the rear, the degree of association is strong; frontal, side, and single-vehicle crashes yield weaker associations. This “self-reported” delta-V measure, however, is a substantial improvement over use of estimated traveling speed or speed limit only.     

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.     

Asymptotic Stability of a Rate Control System With Communication Delays

We study the issue of asymptotic stability of a family of rate control algorithms with communication delays between network elements and extend our earlier results: First, we derive delay-dependent stability conditions with a family of well-known utility and resource price functions when a finite upper bound is known on the feedback delay. These conditions are shown to be consistent with known stability conditions in two extreme cases-no delay or an arbitrarily large delay. Secondly, we provide a lower bound on the convergence rate with the same utility and resource price functions when delay-independent stability conditions hold.     

GIS Approach of Delineation and Risk Assessment of Areas Affected by Arsenic Pollution in Drinking Water

The objective of this study is to analyze health effects of arsenic pollution of drinking water using a geographical information system (GIS). The paper reports the regional impact of arsenic contamination in six administrative blocks of the central part of the Murshidabad district, West Bengal, India. In this area about 1,248,580 people are exposed to arsenic pollution out of whom 388,316 people are exposed to arsenic concentrations above 0.05?mg/L, the WHO maximum permissible level of arsenic in drinking water. The study estimates that 65% of the total area of the six blocks has arsenic concentrations below 0.05?mg/L, 26.12% of the area has arsenic concentrations above 0.05?mg/L, and for the rest of the area no arsenic distribution data available. The total number of expected death cases has been estimated considering the percent of risk involved in a concentration range and corresponding total population using such water for drinking purpose. The analysis forecasts that 11,890 people may risk death due to arsenic pollution in the whole life span. The maximum number of death cases is expected in Domkal and Beldanga 1 blocks and the minimum number of death cases is expected in Block Bhagabangola 2. This study also reports a comparison between the theoretical expectation of death cases and actual reported arsenicosis cases for the Domkal block. The areas of theoretical expectation and the areas of actually reported cases match fairly well except in a few cases. The present study helps planning and implementing of priority-based arsenic mitigation options.     

An integrated framework for managing sensor data uncertainty using cloud computing

In recent years, an increasing number of data-intensive applications deal with continuously changing data objects (CCDOs), such as data streams from sensors and tracking devices. In these applications, the underlying data management system must support new types of spatiotemporal queries that refer to the spatiotemporal trajectories of the CCDOs. In contrast to traditional data objects, CCDOs have continuously changing attributes. Therefore, the spatiotemporal relation between any two CCDOs can change over time. This problem can be more complicated, since the CCDO trajectories are associated with a degree of uncertainty at every point in time. This is due to the fact that databases can only be discretely updated. The paper formally presents a comprehensive framework for managing CCDOs with insights into the spatiotemporal uncertainty problem and presents an original parallel-processing solution for efficiently managing the uncertainty using the map-reduce platform of cloud computing.     

Fuzzy modeling of system behavior for risk and reliability analysis

The main objective of the article is to permit the reliability analyst's/engineers/managers/practitioners to analyze the failure behavior of a system in a more consistent and logical manner. To this effect, the authors propose a methodological and structured framework, which makes use of both qualitative and quantitative techniques for risk and reliability analysis of the system. The framework has been applied to model and analyze a complex industrial system from a paper mill. In the quantitative framework, after developing the Petrinet model of the system, the fuzzy synthesis of failure and repair data (using fuzzy arithmetic operations) has been done. Various system parameters of managerial importance such as repair time, failure rate, mean time between failures, availability, and expected number of failures are computed to quantify the behavior in terms of fuzzy, crisp and defuzzified values. Further, to improve upon the reliability and maintainability characteristics of the system, in depth qualitative analysis of systems is carried out using failure mode and effect analysis (FMEA) by listing out all possible failure modes, their causes and effect on system performance. To address the limitations of traditional FMEA method based on risky priority number score, a risk ranking approach based on fuzzy and Grey relational analysis is proposed to prioritize failure causes.     

Hybrid NSCT domain multiple watermarking for medical images

Multimedia Tools and Applications - Medical image watermarking is a challenging area of research. High bandwidth, secure transmission of patient’s data among hospitals and hiding capacity are...