NEIGHBORHOOD-BASED APPROACH OF COLLABORATIVE FILTERING TECHNIQUES FOR BOOK RECOMMENDATION SYSTEM

Recommendation System or Recommender System help the user to predict the "rating" or "preference" a user would give to an item. Recommender systems in general helps the users to find content, products, or services (such as digital products, books, music, movie, TV programs, and web sites) by combining and analyzing suggestions from other users, which mean rating from various people, and users. These recommendation systems use analytic technology to calculate the results that a user is willing to purchase, and the users will receive recommendations to a product of their interest. The aim of the System is to provide a recommendation based on users likes or reviews or ratings. Recommendation system comprises of content based and collaborative based filtering techniques. In this paper, collaborative based filtering has been used to get the expected outcome. The expected outcome has been achieved through collaborative filtering with the help of correlation techniques which in turn comprises of Pearson correlation, cosine similarity, Kendall’ s Tau correlation, Jaccard similarity, Spearman Rank Correlation, Mean-squared distance, etc. This paper tells about which similarity metrics such us Pearson correlation (PC), constrained Pearson correlation (CPC), spearman rank correlation (SRC) which is good in the context of book recommendation system and then applied with neighborhood algorithm

Standardization of optimum sieve size for maximizing seed quality in Amaranthus (Amaranthus tricolor L.)

Vegetables have a critical function in human health and nutritional security. Vegetables are considered an essential building block of any diet. Out of the leafy vegetables, Amaranthus is the most popular and salable vegetable consumed by people all over India. Seed processing experiment was undertaken in Amaranthus tricolor (CO 2) by using the sieves placed inside the mechanical seed shaker (Gyratory sieve shaker) to improve the quality of Amaranthus seeds. The seeds of Amaranthus were size graded with seed shaker attached with various sieve size of BSS 18 X18 (R), BSS 20 X 20 (R), BSS 22 X 22 (R) and BSP 22 X 22 (P). During processing, the machine could be adjusted for 2, 3, 4 and 5 minutes with an oscillating speed of 1440 rpm. The separated seeds were evaluated for seed quality characteristics such as seed germination percentage, shoot length, root length, dry matter production, 1000 seed weight and seed recovery percentage. The results revealed that the sieve size of BSS 22 X 22 (R=retained) mesh sieve had the better quality seeds with a maximum recovery of 67.41 g and when it is operated for a period of 5 minutes. The germination percentage was improved from 77 % to 95 % with  1000 seed weight of 73.21 mg, and the observed recovery was 56 per cent with the vigour index of 1145. Hence, BSS 22 X 22 retained mesh sieve with a duration of 5 minutes could be recommended as an optimum sieve size for grading Amaranthus seeds for improving the seed quality

Seed quality improvement with fruit extracts in blackgram

The present study was conducted to know the effect of extracts from parts of papaya and pomegranate fruits containing enormous amount of antioxidants on the seed quality parameters of blackgram (Vigna mungo L.). Blackgram seeds were soaked in papaya peel, pulp, seeds and pomegranate peel, seeds extracts viz., 2.5 %, 5 %, 7.5 % and 10 % concentration for 1 hour. The physiological parameters were evaluated under laboratory conditions. The results revealed that seeds treated with 2.5 % papaya seed extract recorded high physiological and biochemical changes in terms of field emergence, germination percentage, seedling length, dry matter production, vigour index and ?- amylase activity when compared to rest of treatments and control

NEIGHBORHOOD-BASED APPROACH OF COLLABORATIVE FILTERING TECHNIQUES FOR BOOK RECOMMENDATION SYSTEM

Recommendation System or Recommender System help the user to predict the "rating" or "preference" a user would give to an item. Recommender systems in general helps the users to find content, products, or services (such as digital products, books, music, movie, TV programs, and web sites) by combining and analyzing suggestions from other users, which mean rating from various people, and users. These recommendation systems use analytic technology to calculate the results that a user is willing to purchase, and the users will receive recommendations to a product of their interest. The aim of the System is to provide a recommendation based on users likes or reviews or ratings. Recommendation system comprises of content based and collaborative based filtering techniques. In this paper, collaborative based filtering has been used to get the expected outcome. The expected outcome has been achieved through collaborative filtering with the help of correlation techniques which in turn comprises of Pearson correlation, cosine similarity, Kendall’ s Tau correlation, Jaccard similarity, Spearman Rank Correlation, Mean-squared distance, etc. This paper tells about which similarity metrics such us Pearson correlation (PC), constrained Pearson correlation (CPC), spearman rank correlation (SRC) which is good in the context of book recommendation system and then applied with neighborhood algorithm

Coupling dye degradation and biodiesel production by Geitlerinema sp TRV27

In this study, the dye degrading the ability of marine cyanobacteria, Geitlerinema sp TRV27 was tested against the textile dye Acid black 52. Optimum conditions like pH, temperature, dye concentration for acid black 52 dye degradation were studied and were found to be pH 7, 25±2°C. More than 50% of degradation was observed for the tested maximum dye concentration, 100 ppm. The degraded dye intermediate was found to be naphthalene by GC-MS analysis and their toxicity on seed germination was studied. The dye treated biomass was used for the production of biodiesel and the physicochemical properties of biofuel were found to be within the standard limits

Enhancement of Naringenin Bioavailability by Complexation with Hydroxypropoyl-β-Cyclodextrin

The abundant flavonoid aglycone, naringenin, which is responsible for the bitter taste in grapefruits, has been shown to possess hypolipidemic and anti-inflammatory effects both in vitro and in vivo. Recently, our group demonstrated that naringenin inhibits hepatitis C virus (HCV) production, while others demonstrated its potential in the treatment of hyperlipidemia and diabetes. However, naringenin suffers from low oral bioavailability critically limiting its clinical potential. In this study, we demonstrate that the solubility of naringenin is enhanced by complexation with β-cyclodextrin, an FDA approved excipient. Hydroxypropoyl-β-cyclodextrin (HPβCD), specifically, increased the solubility of naringenin by over 400-fold, and its transport across a Caco-2 model of the gut epithelium by 11-fold. Complexation of naringenin with HPβCD increased its plasma concentrations when fed to rats, with AUC values increasing by 7.4-fold and Cmax increasing 14.6-fold. Moreover, when the complex was administered just prior to a meal it decreased VLDL levels by 42% and increased the rate of glucose clearance by 64% compared to naringenin alone. These effects correlated with increased expression of the PPAR co-activator, PGC1α in both liver and skeletal muscle. Histology and blood chemistry analysis indicated this route of administration was not associated with damage to the intestine, kidney, or liver. These results suggest that the complexation of naringenin with HPβCD is a viable option for the oral delivery of naringenin as a therapeutic entity with applications in the treatment of dyslipidemia, diabetes, and HCV infection.National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (K01DK080241)Harvard Clinical Nutrition Research Center (P30-DK040561)European Research Council (Starting Grant (TMIHCV 242699))Massachusetts General Hospital (BioMEMS Resource Center (P41 EB-002503))Alexander Silberman Institute of Life Science