14 resultados para Binary Coding
em Cochin University of Science
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The dynamic mechanical properties such as storage modulus, loss modulus and damping properties of blends of nylon copolymer (PA6,66) with ethylene propylene diene (EPDM) rubber was investigated with special reference to the effect of blend ratio and compatibilisation over a temperature range –100°C to 150°C at different frequencies. The effect of change in the composition of the polymer blends on tanδ was studied to understand the extent of polymer miscibility and damping characteristics. The loss tangent curve of the blends exhibited two transition peaks, corresponding to the glass transition temperature (Tg) of individual components indicating incompatibility of the blend systems. The morphology of the blends has been examined by using scanning electron microscopy. The Arrhenius relationship was used to calculate the activation energy for the glass transition of the blends. Finally, attempts have been made to compare the experimental data with theoretical models.
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During 1990's the Wavelet Transform emerged as an important signal processing tool with potential applications in time-frequency analysis and non-stationary signal processing.Wavelets have gained popularity in broad range of disciplines like signal/image compression, medical diagnostics, boundary value problems, geophysical signal processing, statistical signal processing,pattern recognition,underwater acoustics etc.In 1993, G. Evangelista introduced the Pitch- synchronous Wavelet Transform, which is particularly suited for pseudo-periodic signal processing.The work presented in this thesis mainly concentrates on two interrelated topics in signal processing,viz. the Wavelet Transform based signal compression and the computation of Discrete Wavelet Transform. A new compression scheme is described in which the Pitch-Synchronous Wavelet Transform technique is combined with the popular linear Predictive Coding method for pseudo-periodic signal processing. Subsequently,A novel Parallel Multiple Subsequence structure is presented for the efficient computation of Wavelet Transform. Case studies also presented to highlight the potential applications.
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Department of Polymer Science and Rubber Technology, Cochin University of Science and Technology
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Department of Applied Chemistry, Cochin University of Science and Technology
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The surface acidity and basicity of binary oxides of Zr with Ce and La are determined using a series of Hammet indicators and Ho,,max values are reported. The generation of new acid sites habe been ascribed to the charge imbalance of M1-O-M2 bonds, where M1 and M2 are metal atoms. Both Bronsted and Lewis acid sites contribute to the acidity of the oxides
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The thesis entitled Study on Accelerators in Rubber Vulcanization with Special Reference to the Binary Systems Containing Substituted Dithiobiurets. It includes a detailed study on the binary accelerator systems containing substituted dithiobiurets in natural rubber and NR latex and dithiobiurets in SBR and NR-SBR blends vulcanization systems. It deals with the experimental procedure adopted for the preparation of DTB-II and DTB-III; the procedure for compounding and vulcanization and determination of physical properties like modulus, tensile strength, elongation at break, hardness, compression set, heat build up etc. The results indicate that there is efficient acceleration activity of the dithiobiurets in the vulcanization of natural rubber latex containing TMT. The study of dithiobiurets in natural rubber and NR latex reveal that they are having definite accelerating effect in SBR vulcanization systems.
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Catalysis research underpins the science of modern chemical processing and fuel technologies. Catalysis is commercially one of the most important technologies in national economies. Solid state heterogeneous catalyst materials such as metal oxides and metal particles on ceramic oxide substrates are most common. They are typically used with commodity gases and liquid reactants. Selective oxidation catalysts of hydrocarbon feedstocks is the dominant process of converting them to key industrial chemicals, polymers and energy sources.[1] In the absence of a unique successfiil theory of heterogeneous catalysis, attempts are being made to correlate catalytic activity with some specific properties of the solid surface. Such correlations help to narrow down the search for a good catalyst for a given reaction. The heterogeneous catalytic performance of material depends on many factors such as [2] Crystal and surface structure of the catalyst. Thermodynamic stability of the catalyst and the reactant. Acid- base properties of the solid surface. Surface defect properties of the catalyst.Electronic and semiconducting properties and the band structure. Co-existence of dilferent types of ions or structures. Adsorption sites and adsorbed species such as oxygen.Preparation method of catalyst , surface area and nature of heat treatment. Molecular structure of the reactants. Many systematic investigations have been performed to correlate catalytic performances with the above mentioned properties. Many of these investigations remain isolated and further research is needed to bridge the gap in the present knowledge of the field.
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In recent years, reversible logic has emerged as one of the most important approaches for power optimization with its application in low power CMOS, quantum computing and nanotechnology. Low power circuits implemented using reversible logic that provides single error correction – double error detection (SEC-DED) is proposed in this paper. The design is done using a new 4 x 4 reversible gate called ‘HCG’ for implementing hamming error coding and detection circuits. A parity preserving HCG (PPHCG) that preserves the input parity at the output bits is used for achieving fault tolerance for the hamming error coding and detection circuits.
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Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations
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While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting
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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
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The presence of microcalcifications in mammograms can be considered as an early indication of breast cancer. A fastfractal block coding method to model the mammograms fordetecting the presence of microcalcifications is presented in this paper. The conventional fractal image coding method takes enormous amount of time during the fractal block encoding.procedure. In the proposed method, the image is divided intoshade and non shade blocks based on the dynamic range, andonly non shade blocks are encoded using the fractal encodingtechnique. Since the number of image blocks is considerablyreduced in the matching domain search pool, a saving of97.996% of the encoding time is obtained as compared to theconventional fractal coding method, for modeling mammograms.The above developed mammograms are used for detectingmicrocalcifications and a diagnostic efficiency of 85.7% isobtained for the 28 mammograms used.