Constant False Alarm Rate Target Detection in Synthetic Aperture Radar Imagery

Target detection plays a significant role in many synthetic aperture radar (SAR) applications, ranging from surveillance of military tanks and enemy territories to crop monitoring in agricultural uses. Detection of targets faces two major problems namely, first, how to remotely acquire high resolution images of targets, second, how to efficiently extract information regarding features of clutter-embedded targets. The first problem is addressed by the use of high penetration radar like synthetic aperture radar. The second problem is tackled by efficient algorithms for accurate and fast detection. So far, there are many methods of target detection for SAR imagery available such as CFAR, generalized likelihood ratio test (GLRT) method, multiscale autoregressive method, wavelet transform based method etc. The CFAR method has been extensively used because of its attractive features like simple computation and fast detection of targets. The CFAR algorithm incorporates precise statistical description of background clutter which determines how accurately target detection is achieved. The primary goal of this project is to investigate the statistical distribution of SAR background clutter from homogeneous and heterogeneous ground areas and analyze suitability of statistical distributions mathematically modelled for SAR clutter. The threshold has to be accurately computed based on statistical distribution so as to efficiently distinguish target from SAR clutter. Several distributions such as lognormal, Weibull, K, KK, G0, generalized Gamma (GGD) distributions are considered for clutter amplitude modeling in SAR images. The CFAR detection algorithm based on appropriate background clutter distribution is applied to moving and stationary target acquisition and recognition (MSTAR) images. The experimental results show that, CFAR detector based on GGD outmatches CFAR detectors based on lognormal, Weibull, K, KK, G0 distributions in terms of accuracy and computation time.

Screening of traditionally used medicinal plants for their antimicrobial efficacy against oral pathogens and GC-MS analysis of <em>Acacia nilotica </em>extract

162-168Oral diseases are one of the major public health issues. Due to acquisition of pathogenic resistance over conventional antimicrobials, the search for natural alternatives continues. In the present study, thirty two methanol and ethyl acetate extracts prepared from 14 different plant species were screened against oral pathogens. Principal Component Analysis indicated that methanol extract of Acacia nilotica twig was the most influential with highest F1 score and showed almost 2 fold higher antimicrobial activity in comparison to others. GC-MS analysis of Acacia nilotica twig revealed the presence of various bioactive such as limonene, stigmasterol, linoleic acid, ricinoleic acid, santalol, undecylenic acid. Evaluation of antimicrobial potential of medicinal plants may thrive a safe, inexpensive and efficient therapeutic in developing formulation for oral care products

Screening of antimicrobial efficacy of traditionally used Indian plants against microorganisms associated with dandruff

Dandruff is a clinical condition affecting the scalp causing itching and relapsing inflammation. Staphylococcus epidermidis, Propionibacterium acne and Malassezia furfur pathogens are found more and less respectively in the scalps of dandruff subjects. In the present study, a total of 32 plant extracts were screened for their anti-dandruff activity by agar well diffusion method. Among the selected plant extracts of methanol and ethyl acetate, 25 showed significant activity while 7 extracts have not showed activity at a particular concentration. Among all the extracts ethylacetate extract of Cinnamomum zeylanicum and Glycyrrhiza glabra showed very high activity i.e. 18-20 mm while methanolic extract of Punica granatum and Syzygium aromaticum showed moderate activity against all the three pathogens. Thus the active plant extracts can be a potential source for the formulation of natural anti-dandruff agents

Effect of Supplementation of Multigrain Laddo for Malnourished Children under 3–5 Years

Malnutrition is one of the greatest single threats to the world’s public health among children in developing countries according to the World Health Organization. It affects the child at the most crucial period, that is, stage of development, which can lead to permanent impairment in later life which includes reduced work capacity, growth retardation, and poor social and mental development. Half of all child deaths in India could be prevented if this one issue is tackled. Almost 11 million children die before they reach the age of five, four million of them in the 1st month of life. It is a significant public health problem described as a silent killer, silent emergency and invisible enemy affecting those who cannot express their voice and have to depend on others for their advocacy. The main objective of this study is to determine the effect of supplementation with the selected product on the nutritional status of the selected malnourished children. A baseline survey was conducted in four villages of Allahabad District, U.P. A total number of 382 respondents were selected (187 girls and 195 boys) for the present study. They belong to age group of 3–5 years. Four products were prepared with the help of incorporation composite flour. For each product, the basic recipes (control T0) have three variations T1, T2, and T3, respectively, were incorporated at different levels. The products such as Laddo, Biscuit; Mathri, and Chakli were developed. After supplementation, it is evident to note that there was a statistically significant improvement at 1% level and it was observed in the experimental and there was no increment in the weight of the selected subjects in the control group