Adm 658 - Ratio

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CII started 2014 with its annual international flagship event – The Partnership Summit – now in its 20th year since its start in 1995, which was CII’s centenary year. Over the years the Partnership Summit has become a unique platform to exchange ideas and evolve solutions to the most urgent challenges confronting the world today. The summit highlighted investment opportunities emerging from rapid poverty alleviation in India and developing countries offered ideas for how a new class of consumers can become a new dynamic for growth. In this issue of the newsletter the focus story highlights the importance, role and opportunities for emerging Global Value Chains. In addition, the newsletter also provides an insight of some of key happenings in various multilateral institutions. We are putting in our best efforts to make the Multilateral Newsletter more knowledgeable, informative and industry oriented. We welcome your suggestions and feedback on the newsletter and thank you for the valuable support and the time you take out while going through the newsletter.

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This research paper proposes an algorithm to find association rules for incremental databases. Most of the transaction databases are often dynamic. Suppose consider super market customers daily purchase transactions. Day to day customer’s behaviour to purchase items may change and new products replace old products. In this scenario static data mining algorithms doesn't make good significance. If an algorithm continuously learns day to day, then we can get most updated knowledge. This is very much helpful in present fast updating world. Famous and benchmarked algorithms for Association rules mining are Apriory and FP- Growth. However, the major drawback in Appriory and FP-Growth is, they must be rebuilt all over again once the original database is changed. Therefore, in this paper we introduce an efficient algorithm called Binary Decision Tree (BDT) to process incremental data. To process continuously data we need so much of processing and storage resources. In this algorithm we scan data base only once by which we construct dynamic growing binary tree to find association rules with better performance and optimum storage. We can apply for static data also, but our main intension is to give optimum solution for incremental data.

BINARY DECISION TREE FOR ASSOCIATION RULES MINING IN INCREMENTAL DATABASES

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Global growth continues to remain tepid. In US, new data releases are pointing towards a mild recovery, but not compelling enough to force the Federal Reserve to change its monetary policy stance. Labour market is recovering slowly and unemployment rate has continued to decline. On the domestic front, inflation has continued to remain subdued. Given the downward trajectory of inflation and limited upside risks in the wake of benign global commodity prices, the Central Bank chose to cut interest rates by 50 bps in end-September 2015. In the current issue of Economy Matters, we analyse the growth prospects of Euro Area economies and US economy, in the section on Global Trends. In Domestic Trends, data trends in IIP, inflation, trade and monetary policy are analysed. Corporate Performance section analyses the corporate results for 1QFY16. The Sectoral Spotlight for this issue is on ‘Make in India and the Potential for Job Creation’. In Focus of the Month, the important issue of ‘Financial Inclusion’ has been covered.

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The nature and extent of stigma towards individuals with anorexia nervosa and muscle dysmorphia remains underexplored. This study investigated attitudes and beliefs likely to be conducive to stigmatisation of individuals with these conditions. Male and female undergraduate students (N = 361) read one of four vignettes describing a fictional male or female character with anorexia nervosa or muscle dysmorphia, after which they responded to a series of questions addressing potentially stigmatising attitudes and beliefs towards each character. Characters with anorexia nervosa were more stigmatised than characters with muscle dysmorphia, female characters were more stigmatised than male characters, and male participants were more stigmatising than female participants. A very large effect of character diagnosis on masculinity was observed, such that characters with anorexia nervosa were perceived as less masculine than characters with muscle dysmorphia, and this effect was more pronounced amongst male participants. However, no significant corresponding effects were observed for femininity. Females with anorexia nervosa may be particularly susceptible to stigmatisation, especially by males. Anorexia nervosa and muscle dysmorphia are perceived as “female” and “male” disorders respectively, in line with societal gender role expectations, and this stigmatisation is tied more strongly to perceptions of sufferers’ masculinity than femininity.

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