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Ultrasonic velocity, density, and viscosity of polyethylene glycol have been measured for the solution in water at concentration range of 0.3% to 1% at temperature 50oC. Ultrasonic velocity has been measured using ultrasonic interferometer at 1MHz frequency. By using the values of ultrasonic velocity, density, and viscosity, various acoustical parameters like adiabatic compressibility, acoustic impedance, intermolecular free length, and relaxation time have been calculated. The change in these acoustical parameters is explained in terms of solutesolvent interaction in a polymer solution.

In present study an attempt has been made to analyse the molecular interactions of aqueous solution of polyethylene glycol of molecular weight 200 at different concentration and at different temperature by determining density, viscosity, and ultrasonic velocity. Various parameters like, adiabatic compressibility acoustic impedance and intermolecular free length have been calculated at different temperatures and at 0.50% concentration. This study helps to understand the physio-chemical behavior of macro molecules with change in temperature and concentration.

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Data compression techniques plays a vital role in the research area of digital image processing. It involves the processing of digital images with the combined assistance of computer and mathematics. In digital image processing, one can manipulate the images by pre-processing, image enhancement and display. Here we proposed a technique ‘Discrete Wavelet Transform’ (DWT) for the compression of medical images. The images that adopted for compression are medical images. Medical images needs a lot of space to maintain the medical records of a patient in a hospital. In the presented work here the DWT compression technique is applied to the magnetic resonance imaging (MRI) image of brain. The number of wavelets of DWT family is employed for this purpose. First the image under consideration is decomposed by the sub-band coding technique of DWT, and then applied the Embedded Zerotree Wavelet (EZW) encoding scheme. A comparative study is also done on all the resultant images in terms of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR) and Bits Per Pixel (BPP). In the presented study, Haar wavelet gives the better compression of MRI image. All the processing is done by well-known mathematical tool MATLAB.