A Novel Framework For User Customizable Privacy Preserving Search

The objective of the Personalized web search (PWS) is to provide an effective and efficient search results, which are tailor mode for individual user needs. we build user profiles based on user preference and these profiles are then used to re-rank the search results and rank the order of user-examined results.User privacy can be protected without affecting the personalized search quality. However, users are troubled, with exposing personal preference information to search engines has become a major limitation for profile based personalized web search.The Privacy-preserving personalized web search framework is called UPS framework which can generalize profiles for each query according to user-specific privacy requirements. .In general, there is a tradeoff between the search quality and the level of privacy protection achieved from generalization. Effective generalization algorithms namely GreedyDP and GreedyIL are used to support the runtime profiling. Experiments are conducted on real web search data show that the algorithms are effective in enhancing the stability of the search quality and avoids the unnecessary exposure of the user profile. DOI: 10.17762/ijritcc2321-8169.150313

Multi‐response optimization of extrusion conditions of grain amaranth flour by response surface methodology

The study was designed to optimize extrusion processing conditions for production of instant grain amaranth flour for complementary feeding. Multi-response criteria using response surface methodology and desirability function analysis were employed during the study. The central composite rotatable design (CCRD) was used to determine the level of processing variables and to generate the experimental runs. The process parameters tested included extrusion temperature (110–158°C), screw speed (40–52 Hz), and feed moisture content (11%–16%), while response variable was protein digestibility, sensory acceptability, water absorption index, water solubility index, bulk density, and viscosity. Data obtained from extrusion were analyzed using response surface methodology. Data were fitted to a second-order polynomial model, and the dependent variables expressed as a function of the independent variables. Analysis of variance (ANOVA) revealed that extrusion parameters had significant linear, quadratic, and interactive effects on the responses. Numerical optimization indicated that the optimum extrusion parameters were extrusion temperature of 150°C, extrusion speed (screw speed) of 50 Hz, and feed moisture content of 14.41%. The responses predicted for optimization resulted in protein digestibility 81.87%, water absorption index 1.92, water solubility index 0.55, bulk density 0.59 gm/L, viscosity 174.56 cP (14.55 RVU), and sensory acceptability score of 6.69, with 71% desirability