Micro-blogging Sentimental Analysis on Twitter Data Using Na�ve Bayes Machine Learning Algorithm in Python

As the increase of social networking, people started to share information through different kinds of social media. Sentiment Analysis, a Natural Language processing helps in finding the sentiment or opinion hidden within a text. Sentiment analysis is an approach to analyze data and retrieve sentiment that it embodies. Twitter sentiment analysis is an application of sentiment analysis on data from Twitter (tweets), in order to extract sentiments conveyed by the user. It is an important source of decision making and can be extracted, identified, evaluated from the online sentiments reviews. The main goal of the proposed framework is to connect on Twitter and search for the tweets that contain a particular keyword and then evaluate the polarity of the tweets as positive and negative. In order to select the best features Chi Square test is used and Na�ve Bayes classifier is used for training and testing the features and also evaluating the sentimental polarity. The proposed system is implemented using Python

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

Fabrication of polycaprolactone/β-tricalciumphosphate based nano scaffolds using electrospinning method for biomedical applications

1292-1297In this study, we have focused on preparation, fabrication and characterization of polycaprolactone and beta tricalcium phosphate (PCL/β-TCP) composite scaffolds that are used for bone tissue engineering applications. The electrospun composites have been characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM). The developed scaffolds are effectively simulated the morphology, mechanical property and bioactivity for load-bearing tissue engineering applications. The bioactivity of the scaffolds has been evaluated with in vitro cell adhesion and growth studies. The results confirm the nontoxic behaviour of the composite biomaterials and developed scaffolds with MG-63 osteoblast-like cell line. The synthesized scaffolds have shown promising bioactivity with the growth as well as proliferation of new bone cells with considerable osteoconductive properties. The nanoscaffolds possess better physical properties and support high cell adhesion suggesting their application in bone tissue engineering field

Silver ferrite embellished graphene oxide heterogenous nanocomposite for efficient electrochemical detection of gallic acid

Ferrites have attracted the research community owing to their invincible properties corresponding to their magnetic recoverability, recycling efficacy, and environmentally friendly behaviour. They are gaining importance in catalysis, sensors, supercapacitors, batteries, magnetic tunnel ferrofluids, magnetic drug delivery, and information storage. By taking advantage of ferrites, in this study, we have developed a silver ferrite embellished graphene oxide (AgFe2O4/GO) nanocomposite by decorating AgFe2O4 on graphene oxide (GO) by a viable route. The crystal structure, size, morphology, and magnetic behaviour of the fabricated nanocomposites have been investigated with the assistance of fourier transform infrared (FTIR) spectroscopy, RAMAN spectroscopy, X-ray diffraction, and scanning electron microscopic (SEM) techniques. The composite has been examined for the electrocatalytic determination of gallic acid (GA) by cyclic voltammetry and differential pulse voltammetry by its modification of glassy carbon electrode. This modified glassy carbon electrode has shown excellent electrocatalytic behaviour toward the detection of GA. These results can be used as an electrochemical standard in the estimation of total polyphenol content in the foodstuffs and extended to pharmaceutical and industrial applications

W-shaped chirp free and chirped bright, dark solitons for perturbed nonlinear Schrödinger equation in nonlinear optical fibers

In the present investigation, we employed the Jacobi elliptic function (JEF) method to invoke the perturbed nonlinear Schrödinger equation with self-steepening (SS), self-phase modulation (SPM), and group velocity dispersion (GVD), which govern the propagation of solitonic pulses in optical fibres. The proposed algorithm proves the existence of the family of solitons in optical fibers. Consequently, chirped and chirp free W-shaped bright, dark soliton solutions are obtained from dn(ξ), cn(ξ) and sn(ξ) functions. The final results are displayed in three-dimensional plots with specific physical values of GVD, SPM and SS for an optical fiber