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Introduction - Ayurveda a holistic system of medicine, originated in India more than  3000 yrs ago. The main objective of Ayurveda is to “Maintain the health of healthy  person and to pacify the disease of a diseased person”. Immunity is the ability of the  body to resist against the various foreign agents. The concept of immunity, in fact had  been rooted in Ayurvedic system of medicine much before 600 BC.  Material and Methods - In Ayurvedic classics Acharya’s has mentioned a lot of  immune boosters, both single drugs and formulations. Ashwagandha, is one among  them, which has got immense popularity recently, due to its ability to boost body  immunity and also, it can increases body’s natural ability to fight viruses.  Discussion- Ashwagandha, a special herb, used extensively in Ayurveda and is known  for its capacity to boost the immunity. The pharmacodynamic action of Aswagandha  itself proves the immunomodulatory effects. The herb is ushna in potency thereby  reduces Kapha Vata, providing more strength to the immune system of our body.  Being Madhura in rasa it provides ojas, bala and nourishment to the Dhatus.  Conclusion- An effort to compile the details about Aswagandha in relation to its  immune boosting power was done here.

Rasa shastra has given an auspicious position to Parada as it has been considered  as the physical essence of Lord Shiva. Vedas also consider Parada as a gift of  nature. The classical test Rasaratna Samucchaya states that “Siddhae rase  Karishyami Nirdraaridrayam agadam jagat” exposes the magical effect of  Parada. Even though, administration of Asudha Parada causes severe illness than  that of poison. As it is associated with a lot of impurities, it is advised to do both  Samanya Shodhana, and Visesha Shodhana (general and specific purificatory  methods before its internal administration. Otherwise these impurities may cause  various toxic effects in body ranging from mild fever to death. Hence Rasa  acharyas mentioned a number of purificatory procedures both general and specific  to eliminate the doshas associated with Parada. As per modern science Mercury  comes in three forms (Elemental, inorganic and organic), each with its own set of  symptoms. The brain is the primary target organ for breathed mercury vapor,  whereas mercurous and mercuric salts harm the gut lining and kidneys, confirming  persistent exposure and methyl mercury are widely disseminated throughout the  body. This article focuses on various doshas associated with Parada and its  purificatory procedures. P

Bankruptcy prediction is very important for all the organization since it affects the economy and rise many social problems with high costs. There are large number of techniques have been developed to predict the bankruptcy, which helps the decision makers such as investors and financial analysts. One of the bankruptcy prediction models is the hybrid model using Fuzzy C-means clustering and MARS, which uses static ratios taken from the bank financial statements for prediction, which has its own theoretical advantages. The performance of existing bankruptcy model can be improved by selecting the best features dynamically depend on the nature of the firm. This dynamic selection can be accomplished by Genetic Algorithm and it improves the performance of prediction model., Comment: Bankruptcy prediction, financial ratio models, Genetic Algorithm, Fuzzy c-means Clustering, MARS

This paper illustrates the Principal Direction Divisive Partitioning (PDDP) algorithm and describes its drawbacks and introduces a combinatorial framework of the Principal Direction Divisive Partitioning (PDDP) algorithm, then describes the simplified version of the EM algorithm called the spherical Gaussian EM (sGEM) algorithm and Information Bottleneck method (IB) is a technique for finding accuracy, complexity and time space. The PDDP algorithm recursively splits the data samples into two sub clusters using the hyper plane normal to the principal direction derived from the covariance matrix, which is the central logic of the algorithm. However, the PDDP algorithm can yield poor results, especially when clusters are not well separated from one another. To improve the quality of the clustering results problem, it is resolved by reallocating new cluster membership using the IB algorithm with different settings. IB Method gives accuracy but time consumption is more. Furthermore, based on the theoretical background of the sGEM algorithm and sequential Information Bottleneck method(sIB), it can be obvious to extend the framework to cover the problem of estimating the number of clusters using the Bayesian Information Criterion. Experimental results are given to show the effectiveness of the proposed algorithm with comparison to the existing algorithm., Comment: IEEE Publication format, ISSN 1947 5500, http://sites.google.com/site/ijcsis