Automated system for characterization and classification of malaria‐infected stages using light microscopic images of thin blood smears

In this paper, we propose a comprehensive image characterization cum classification framework for malaria‐infected stage detection using microscopic images of thin blood smears. The methodology mainly includes microscopic imaging of Leishman stained blood slides, noise reduction and illumination correction, erythrocyte segmentation, feature selection followed by machine classification. Amongst three‐image segmentation algorithms (namely, rule‐based, Chan–Vese‐based and marker‐controlled watershed methods), marker‐controlled watershed technique provides better boundary detection of erythrocytes specially in overlapping situations. Microscopic features at intensity, texture and morphology levels are extracted to discriminate infected and noninfected erythrocytes. In order to achieve subgroup of potential features, feature selection techniques, namely, F‐statistic and information gain criteria are considered here for ranking. Finally, five different classifiers, namely, Naive Bayes, multilayer perceptron neural network, logistic regression, classification and regression tree (CART), RBF neural network have been trained and tested by 888 erythrocytes (infected and noninfected) for each features’ subset. Performance evaluation of the proposed methodology shows that multilayer perceptron network provides higher accuracy for malaria‐infected erythrocytes recognition and infected stage classification. Results show that top 90 features ranked by F‐statistic (specificity: 98.64%, sensitivity: 100%, PPV: 99.73% and overall accuracy: 96.84%) and top 60 features ranked by information gain provides better results (specificity: 97.29%, sensitivity: 100%, PPV: 99.46% and overall accuracy: 96.73%) for malaria‐infected stage classification.     

Study of Leaching of Multimetal Sulphides Through an Interdisciplinary Approach

The leaching of a real multimetal bulk concentrate cannot often be adequately understood on the basis of published literature on simpler and often ideal systems because the process is far too complex, Moreover, the data can become ambiguous in the absence of adequate information on raw materials. Thus any process development work requires a thorough knowledge of the raw material characteristics. This paper describes the use of an interdisciplinary study for a better understanding of ammonia leaching of multimetal sulphides. The techniques employed comprise of X-ray diffraction, thermal analysis, chemical analysis and microscopy.     

VHF propagation characterization during atmospheric disturbances

Abstract

The propagation of a television (TV) signal is usually perturbed during periods of atmospheric disturbance such as in thunderstorms. The region under investigation here is situated in the coastal area of the Bay of Bengal and has experienced frequent thunderstorm activities. An investigation to study their effects on VHF signal propagation transmitted from Satkhira in Bangladesh and received at the Indian Statistical Institute, Calcutta, has been undertaken. The depths of the atmospheric disturbances within a 1?km range have been recorded and measured by acoustic sounder (sodar) operated continuously at the receiving station. The inset of the storm is marked by the enhanced signal level with deep fluctuations characteristic during the periods of thunderstorms.     

Automating the refinement of specifications for distributed systems via syntactic transformations

The idea of successively refining an abstract specification until it contains enough detail to suggest an implementation has been investigated by numerous researchers. The emphasis to date has been on techniques that, unfortunately, lead to a large amount of manual formal labour for each refinement step. With such techniques, both the cost and the possibility of errors arising informal manipulation are high. Using a theorem prover can reduce the number of manipulation errors, but, given current technology, the amount of labour is still daunting. This research explores an alternative solution to the refinement problem, namely the use of syntactic transformations to realize each refinement step. We reduce formal labour by employing automatic transformations that guarantee the preservation of desirable properties—e.g., deadlock-freedom. Automatic transformations are particularly appealing for the development of large, complex distributed systems, where a manual approach to refinement would be prohibitively expensive. Distributed computations are, by nature, reactive and concurrent, so their correctness cannot be specified as a simple functional relationship between inputs and outputs. Instead, specifications must describe the time-varying behaviour of the system. Further difficulty is caused by the fact that such important characteristics of distributed systems as deadlock-freedom are global properties that cannot be achieved through considering local structures only. Transformations generally must encompass the entire system. This paper presents two syntactic transformations—the left-sequence introduction and the right-sequence introduction—and demonstrates that they preserve deadlock-freedom.     

A single-element controlled all-pass phase-shifter†

An all-pass transfer function has been realised here by combining the output of an asymmetrical twin-T network with a portion of its input in a differential amplifier. A continuous phase shift from ?π/2 to +π/2 of an incoming signal may be produced hero with the variation of a single element of the network without a change in amplitude with respect to phase.     

Textural pattern classification for oral squamous cell carcinoma

Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains to be widely researched. Studies on computer‐aided analysis of pathological slides of oral cancer contribute a lot to the diagnosis and treatment of the disease. Some researches in this direction have been carried out on oral submucous fibrosis. In this work an approach for analysing abnormality based on textural features present in squamous cell carcinoma histological slides have been considered. Histogram and grey‐level co‐occurrence matrix approaches for extraction of textural features from biopsy images with normal and malignant cells are used here. Further, we have used linear support vector machine classifier for automated diagnosis of the oral cancer, which gives 100% accuracy.     

Application of a stochastic modelling framework to characterize the influence of different oxide scales on the solid particle erosion behaviour of boiler grade steel

An earlier developed stochastic model has been applied to describe the relative rate of material loss from the steel surface subjected to simultaneous action of high temperature oxidation involving multiple oxides and mechanical erosion. Different oxide scale growths, namely, nickel, iron and chromium have been treated deterministically and erosion is described using a literature based probabilistic framework. Oxidation is described with a power law (parabolic) approach to quantify the rate of growth of all the three oxide scales. In consonance with the published model, erosion is treated using a probabilistic methodology as spatially random phenomena on the oxide surface. The concept of ‘erosion footprint’ has been incorporated in the present model to characterize the erosion-induced damage on the steel surface. The model has been applied to predict the relative material loss as a function of time resulted from erosion–oxidation interaction pertaining to nickel, iron and chromium oxides in dimensionless form. This investigation is expected to provide a quantitative understanding of relative material loss due to solid particle erosion for oxide scales, (composed of multiple oxides) formed on the steel components of coal-fired boilers.     

Machining characteristics of fine grained AZ91 Mg alloy processed by friction stir processing

AZ91 Mg alloy was considered and friction stir processing (FSP) was adopted to achieve grain refinement to investigate the effect of grain size and secondary phase on machining characteristics during drilling at various speeds and feeds. Super saturated AZ91 Mg alloy was obtained after FSP and the grain refinement was achieved from (166.5±8.7) µm to (21.7±13.5) µm. Surprisingly, hardness reduced for FSP AZ91 Mg alloy (88.95±6.1) compared with AZ91 alloy (108.2±15.6), which was attributed to the reduced secondary phase. However, the mean cutting force for FSP-treated (FSPed) AZ91 Mg alloy was marginally increased. The edge damage of the drilled holes was lower for FSPed AZ91 Mg alloy compared with unprocessed AZ91 Mg alloy. Hence, it can be understood that the grain refinement may slightly increase the cutting forces during drilling but better edge finishing can be achieved in machining of AZ91 Mg alloy.