Prediction of Brand Equity Determinants in Paints Industry
Debaleena Chatterjee, Protik Basu and Indranil Ghosh

Abstract
This research attempts to predict brand loyalty of contractors / painters in the commercial paints industry based on eight predictors. These predictors are identified as factors contributing to brand loyalty. Analytic Hierarchy Process (AHP) is used to rank the predictors. Factors having their priority vectors greater than 10% are selected for further analysis. This study uses Discriminant Analysis on primary data to examine whether the predictors are capable of classifying the respondents into two distinct groups – those who show signs of brand loyalty vis-a-vis those who do not. Five-point Likert scale was used to collect responses for each parameter. Five out of eight predictors are finally selected for Discriminant Analysis to determine if it is possible to distinguish the two groups significantly. Responses reveal that there exists a significant difference between the two groups based on the predictors. This is an ex-ante decision model that can be used for anticipating brand loyal behaviour of the consumers in future. This work is one of the very first studies performing research on the classification variables of brand loyalty in the paints industry and intends to bridge the gap between theory and practice to aid the practitioners decide on suitable strategies to augment their brand loyalty.
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A Novel Approach for Collaborative Spam Filtering to Protect Mail box
Haseeba Yaseen, Adithya D A, Ashwini M, Chandan S, Dhanesh P Kudalkar

Abstract
Spam has turned into the stage of decision utilized by digital law breakers to spread malignant payloads, for example, infections and Trojans. In view of this, the issue of early recognition of spam causes has been addressed. Communitarian spam location procedures can manage huge scale email information contributed by diverse sources, they have the prominent topic of requiring exposure of email content. Separation upkeep hashes are one of the normal arrangements applied for saving the security of email content while allowing message grouping for spam recognition. Anyhow, separate safeguarding hashes are not adaptable, along these lines making massive scale synergistic arrangements hard to represent. Spamdoop, a Big Data security safeguarding community oriented spam discovery stage based over a standard Map Reduce office has been projected. Spamdoop employs a very parallel encoding system that empowers the recognition of spam battles in aggressive circumstances. The outline has been judged by the execution, by utilizing a massive manufactured spam base and prove that the system performs positively against the creation and conveyance overhead of current spam age devices.
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