Carbon Nanotubes-Reinforced PET Nanocomposite by Melt-Compounding

Poly(ethylene terephthalate) (PET) nanocomposites with single-walled carbon nanotubes (SWNTs) have been prepared by a simple melt compounding method. With increasing concentration (0-3 wt %) of SWNTs, the mechanical and dynamic mechanical properties improved, corresponding to effective reinforcement. Melt rheological characterization indicated the effective entanglements provided by SWNTs in the melt state as well. Thermogravimetric analysis suggested no influence of SWNTs on the thermal stability of PET. Electrical conductivity measurements on the composite films pointed out that the melt compounded SWNTs can result in electrical percolation albeit at concentrations exceeding 2 wt %.

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Studies on new processing aids and other compounding ingredients in special purpose rubbers

In the first part of the study we probed the effectiveness of rice bran oil as a multipurpose compounding ingredient for nitrile (NBR) and chloroprene (CR) rubbers. This oil has already been successfully employed in the compounding of NR and SBR in this laboratory.In this context we thought it worthwhile to try this oil in the polar rubbers viz, NBR and CR also. The principle of like dissolves like as applicable to solvents is equally applicable while selecting a plasticiser, elastomer combination. Because of the compatibility considerations polar plasticisers are preferred for polar rubbers like NBR and CR. Although plasticisation is a physical phenomenon and no chemical reaction is involved, the chemical structure of plasticisers determines how much physical attraction there is between the rubber and the plasticiser. In this context it is interesting to note that the various fatty acids present in rice bran oil have a long paraffinic chain, characteristic of waxes, with an acid group at the end of the molecule. The paraffinic end of the molecule contributes lubricating effects and limits compatibility whereas the acid end group contributes some polarity and is also chemically reactive. Because of absorption of acid group on the surface of pigments, these acids will have active pigment wetting characteristics also. These factors justifies the role of rice bran oil as a co-activator and lubricating agent for NBR and CR. In fact in our study we successfully replaced stearic acid as co-activator and aromatic oillDOP as processing aid for CR and NBR with rice bran oil.This part of the study has got special significance in the fact that rubber industry now heavily depends on petroleum industry for process oils. The conventional process oils like aromatic, naphthenic and paraffinic oils are increasingly becoming costlier, as its resources in nature are fast depleting. Moreover aromatic process oils are reported to be carcinogenic because of the presence of higher levels of polycyclic aromatic compounds in these oils.As a result of these factors, a great amount research is going on world over for newer processing aids which are cost effective, nontoxic and performanance wise at par with the conventional ones used in the rubber industry. Trials with vegetable oils in this direction is worth trying.Antioxidants are usually added to the rubber compound to minimise ageing effects from heat, light, oxygen etc. As rice bran oil contains significant amount of tocopherols and oryzanol which are natural antioxidants, we replaced a phenolic antioxidant like styrenated phenol (SP) from the compound recipe of both the rubbers with RBO and ascertained whether this oil could function in the role of antioxidant as well.Preparation and use of epoxidised rice bran oil as plasticiser has already been reported.The crude rice bran oil having an iodine value of 92 was epoxidised in this laboratory using peracetic acid in presence of sulphuric acid as catalyst. The epoxy content of the epoxidised oil was determined volumetrically by treating a known weight of the oil with excess HCI and back titrating the residual HCI with standard alkali solution. The epoxidised oil having an epoxy content of 3.4% was tried in the compounding of NBR and CR as processing aids. And results of these investigations are also included in this chapter. In the second part of the study we tried how RBO/ERBO could perform when used as a processing aid in place of aromatic oil in the compounding of black filled NRCR blends. Elastomers cannot have all the properties required for a particular applications, so it is common practice in rubber industry to blend two elastomers to have desired property for the resulting blend.In this RBO/ERBO was tried as a processing aid for plasticisation, dispersion of fillers, and vulcanisation of black filled NR-CR blends.Aromatic oil was used as a control. The results of our study indicate that these oils could function as a processing aid and when added together with carbon black function as a cure accelerator also.PVC is compatible with nitrile rubber in all proportions, provided NBR has an acrylonitrile content of 25 to 40%. Lower or higher ACN content in NBR makes it incompatible with PVC.PVC is usually blended with NBR at high temperatures. In order to reduce torque during mixing, additional amounts of plasticisers like DOP are added. The plasticiser should be compatible both with PVC and NBR so as to get a homogeneous blend. Epoxidised soyaben oil is reported to have been used in the compounding of PVC as it can perfonn both as an efficient plasticiser and heat stabilizer.At present DOP constitute the largest consumed plasticiser in the PVC compounding. The migration of this plasticiser from food packaging materials made of PVC poses great health hazards as this is harmful to human body. In such a scenario we also thought it worthwhile to see whether DOP could be replaced by rice bran oil in the compounding of NBR-PVC blends Different blends of NBR-PVC were prepared with RBO and were vulcanized using sulphur and conventional accelerators. The various physical and mechanical properties of the vulcanisates were evaluated and compared with those prepared with DOP as the control plasticiser. Epoxidised rice bran oil was also tried as plasticiser for the preparation of NBR-PVC blends. A comparison of the processability and cure characteristics of the different blends prepared with DOP and ERBO showed that ERBO based blends have better processability and lower cure time values. However the elastographic maximum torque values are higher for the DOP based blends. Almost all of the physical properties evaluated are found to be slightly better for the DOP based blends over the ERBO based ones. However a notable feature of the ERBO based blends is the better percentage retention of elongation at break values after ageing over the DOP based blends. The results of these studies using rice bran oil and its epoxidised variety indicated that they could be used as efficient plasticisers in place of DOP and justifies their role as novel, nontoxic, and cheap plasticisers for NBR-PVC blends.

Influence of compounding and process variables on quality of condams made from natural rubber latex

Condoms are widely accepted as a contraceptive for family planning and population control. It is also accepted as the most effective barrier against sexually transmitted diseases, especially AIDS, the incurable disease. But presence of pinholes and low film strength of condoms make it unsuitable for the purpose. Quality improvement of condoms by reducing the pinhole formation and increasing the film strength is thus an essential requirement for population control as well as for preventing the spread of sexually transmitted diseases. Strict implementation of WHO specification of condoms further increases the rejection percentage. This causes higher rejection loss to condom manufacturers because the defects could be identified only at the final stage of processing. If the influence of various factors which cause these defects is known, manufacturers can take remedial measures to reduce the defectives so that rejection loss can be decreased and quality of condoms increased. In the present study, it was proposed to conduct experiments to improve the quality of condoms by reducing the pinhole rejection percentage and increasing the tensile properties, burst volume, and burst pressure. Ageing property improvement also was an important target among other parameters. Until a cure for AIDS is found, a high quality latex condom is the only effective device in the prevention of the spread of HIV, AIDS and STD's. Hence it is all the more necessary to have high quality condoms.

Studies on Latex Compounding

The main objective of the present study was to explore ways of making latex products more cost effective and versatile. Polyethylene glycol was identified as a surface active agent in latex compounds which improves the filler-polymer interaction and also distributes the filler more uniformly. The use of such surface active agents can develop filled latex products with improved mechanical properties at a lower cost. In this study dispersions of carbon black and silica were successfully added to NR latex under high speed stirring without destabilizing latex.

Investigations On The Development Of An Ann Model & Visual Manipulation Approach For 2-D Dft Computation In Image Processing

This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

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

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

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. 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). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks 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

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Content Based Image Retrieval System for Malayalam Handwritten Characters

Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images

Parallel Genetic Algorithm for Document Image Compression Optimization

This work proposes a parallel genetic algorithm for compressing scanned document images. A fitness function is designed with Hausdorff distance which determines the terminating condition. The algorithm helps to locate the text lines. A greater compression ratio has achieved with lesser distortion

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images