Latex Stage Blending of Natural Rubber and Poly(Vinyl Chloride ) for Improved Mechanical Properties

A novel method of blending natural rubber with polyvinylchloride in the latex stage was developed, Dioctyl phthalate (DOP) and Amine terminated natural rubber (ATNR) were used as plasticisers, for improving the mechanical properties of these blends. Properties of the latex stage blends were compared with those of dry blends. Latex stage blends showed superior mechanical properties compared to the blends prepared in the dry state. The ageing resistance, oil resistance and processability were found to be improved by latex stage blending.

Thermal characterization of doped polyaniline and its composites with CoPc

Thermal diffusivity of the composites of camphor sulphonic acid (CSA) doped polyaniline (PANI) and its composites with cobalt phthalocyanine (CoPc) has been measured using open cell photoacoustic technique. Analysis of the data shows that the effective thermal diffusivity value can be tuned by varying the relative volume fraction of the constituents. It is seen that polaron assisted heat transfer mechanism is dominant in CSA doped PANI and these composites exhibit a thermal diffusivity value which is intermediate to that of CSA doped PANI and CoPc. The results obtained are correlated with the electrical conductivity and hardness measurements carried out on the samples

Thermal characterization of doped polyaniline and its composites with CoPc

Thermal diffusivity of the composites of camphor sulphonic acid (CSA) doped polyaniline (PANI) and its composites with cobalt phthalocyanine (CoPc) has been measured using open cell photoacoustic technique. Analysis of the data shows that the effective thermal diffusivity value can be tuned by varying the relative volume fraction of the constituents. It is seen that polaron assisted heat transfer mechanism is dominant in CSA doped PANI and these composites exhibit a thermal diffusivity value which is intermediate to that of CSA doped PANI and CoPc. The results obtained are correlated with the electrical conductivity and hardness measurements carried out on the samples.

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

FEATURE SELECTION AND COMPARISON OF TWO NAÏVE BAYES CLASSIFICATION METHODS IN THE CONTEXT OF SPAM FILTERING

Treating e-mail filtering as a binary text classification problem, researchers have applied several statistical learning algorithms to email corpora with promising results. This paper examines the performance of a Naive Bayes classifier using different approaches to feature selection and tokenization on different email corpora

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

Design and Programming of Cathodic Protection for SHIPS

In order to minimize the risk of failures or major renewals of hull structures during the ship's expected life span, it is imperative that the precaution must be taken with regard to an adequate margin of safety against any one or combination of failure modes including excessive yielding, buckling, brittle fracture, fatigue and corrosion. The most efficient system for combating underwater corrosion is 'cathodic protection'. The basic principle of this method is that the ship's structure is made cathodic, i.e. the anodic (corrosion) reactions are suppressed by the application of an opposing current and the ship is there by protected. This paper deals with state of art in cathodic protection and its programming in ship structure