6 resultados para Antiferromagnetic resonance
em Cochin University of Science
Resumo:
The arrow shaped microstrip antenna, which produces dual frequency dual polarisation operation with considera-ble size reduction compared to conventional patches has been reported [I]. These antennas provide greater area reduction and improved gain compared to drum shaped patches [2]. Prediction of the resonance frequency of drum shaped patches [3] and circular patches for broadband operation [4] are available in the literature. In this Letter, we propose empirical formulas for calculating the resonance frequencies of the arrow shaped microstrip antenna. These antennas can be employed for obtaining dual frequency with the same polarisation, bandwidth enhancement, circular polarisation etc. by varying its different parameters or by introducing slots. The proposed design equations provide an easier and simple way of predicting the resonant frequencies of these patches.
Resumo:
A simple technique for calculating the resonance frequencies of a compact arrow-shaped microstrip antenna is presented and discussed . The accuracy of the method is validated by experimental results
Resumo:
A simple and inexpensive linear magnetic field sweep generating system suitable for magnetic resonance experiments is described. The circuit, utilising a modified IC bootstrap configuration, generates field sweep over a wide range of sweep durations with excellent sweep linearity.
Resumo:
A laser produced plasma from the multielement solid target YBa2Cu3O7 is generated using 1.06 μm, 9 ns pulses from a Q-switched Nd:YAG laser in air at atmospheric pressure. A time resolved analysis of the profile of the 4554.03 Å resonance line emission from Ba II at various laser power densities has been carried out. It has been found that the line has a profile which is strongly self-reversed. It is also observed that at laser power densities equal to or exceeding 1.6×1011 W cm−2, a third peak begins to develop at the centre of the self-reversed profile and this has been interpreted as due to the anisotropic resonance scattering (fluorescence). The number densities of singly ionized barium ions evaluated from the width of the resonance line as a function of time delay with respect to the beginning of the laser pulse give typical values of the order of 1019 cm−3. The higher ion concentrations existing at smaller time delays are seen to decrease rapidly. The Ba II ions in the ground state resonantly absorb the radiation and this absorption is maximum around 120 ns after the laser pulse.
Resumo:
Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.
Resumo:
Silver silica nanocomposites were obtained by the sol–gel technique using tetraethyl orthosilicate (TEOS) and silver nitrate (AgNO3) as precursors. The silver nitrate concentration was varied for obtaining composites with different nanoparticle sizes. The structural and microstructural properties were determined by x-ray diffractometry (XRD), Fourier transform infrared spectroscopy (FTIR) and transmission electron microscopy (TEM). X-ray photoelectron spectroscopic (XPS) studies were done for determining the chemical states of silver in the silica matrix. For the lowest AgNO3 concentration, monodispersed and spherical Ag crystallites, with an average diameter of 5 nm, were obtained. Grain growth and an increase in size distribution was observed for higher concentrations. The occurrence of surface plasmon resonance (SPR) bands and their evolution in the size range 5–10 nm is studied. For decreasing nanoparticle size, a redshift and broadening of the plasmon-related absorption peak was observed. The observed redshift and broadening of the SPR band was explained using modified Mie scattering theory