Structural and catalytic investigation of vanadia supported on ceria promoted with high surface area rice husk silica

Rice husk silica was utilized as the promoter of ceria for preparing supported vanadia catalysts. Effect of vanadium content was investigated with 2–10 wt.% V2O5 loading over the support. Structural characterization of the catalysts was done by various techniques like energy dispersive X-ray (EDX), X-ray diffraction (XRD), BET surface area, thermal analysis (TGA/DTA), FT-infrared spectroscopy (FT-IR), UV–vis diffused reflectance spectroscopy (DR UV–vis), electron paramagnetic spectroscopy (EPR) and solid state magnetic resonance spectroscopies (29Si and 51V MASNMR). Catalytic activity was studied towards liquid-phase oxidation of benzene. Surface area of ceria enhanced upon rice husk silica promotion, thus makes dispersion of the active sites of vanadia easier. Highly dispersed vanadia was found for low V2O5 loading and formation of cerium orthovanadate (CeVO4) occurs as the loading increases. Spectroscopic investigation clearly confirms the formation of CeVO4 phase at higher loadings of V2O5. The oxidation activity increases with vanadia loading up to 8 wt.% V2O5, and further increase reduces the conversion rate. Selective formation of phenol can be attributed to the presence of highly dispersed active sites of vanadia over the support.

Influence of sulphate content on the physico-chemical properties and catalytic activity of some sulphated zirconia systems

The present work attempts a systematic examination of the effect of sulphate content on the physico-chemical properties and catalytic activity of sulphated zirconia and iron promoted sulphated zirconia systems. Sulphate content is estimated by EDX analysis. The amount of sulphate incorporated has been found to influence the surface area, crystal structure and the acid strength distribution. Ammonia TPD and adsorption studies using perylene have enabled the determination of surface acidic properties. The results are supported by the thermodesorption studies using pyridine and 2,6-dimethylpyridine. The catalytic activity towards benzoylation reaction has been correlated with the surface acidity of the systems.

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

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