Microcavity supported lipid membranes: versatile platforms for building asymmetric lipid bilayers and for protein recognition

Microcavity supported lipid bilayers (MSLB) are contact-free membranes suspended across aqueousfilled pores that maintain the lipid bilayer in a highly fluidic state and free from frictional interactions with substrate. Such platforms offer the prospect of liposome-like fluidity with the compositional versatility and addressability of supported lipid bilayers and thus offer significant opportunity for modelling membrane asymmetry, protein-membrane interactions and aggregation at the membrane interface. Herein, we evaluate their performance by studying the effect of transmembrane lipid asymmetry on lipid diffusivity, membrane viscosity and cholera toxin- ganglioside recognition across six symmetric and asymmetric membranes including binary compositions containing both fluid and gel phase, and ternary phase separated membrane compositions. Fluorescence lifetime correlation spectroscopy (FLCS) was used to determine the lateral mobility of lipid and protein, and electrochemical impedance spectroscopy (EIS) enabled detection of protein-membrane assembly over the nanomolar range. Transmembrane leaflet asymmetry was observed to have profound impact on membrane electrochemical resistance where the resistance of a ternary symmetric phase separated bilayer was found to be at least 2.6 times higher than the asymmetric bilayer with analogous composition at the distal leaflet but where the lower leaflet comprised only 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC). Similarly, the diffusion coefficient for MSLBs was observed to be 2.5 fold faster for asymmetric MSLBs where the lower leaflet is DOPC alone. Our results demonstrate that interplay of lipid packing across both membrane leaflets and concentration of GM1 both affect the extent of cholera toxin aggregation and consequent diffusion of the cholera-GM1 aggregates. Given that true biomembranes are both fluidic and asymmetric, MSLBs offer the opportunity for building greater biomimicry into biophysical models and the approach described demonstrates the value of MSLBs in studying aggregation and membrane associated multivalent interactions prevalent in many carbohydrates mediated processes

Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

VALIDATING EFFECTIVE RESUME BASED ON EMPLOYER’S INTEREST WITH RECOMMENDATION SYSTEM

In current technological world, recruitment process of corporate has evolved to the greater extent. Both the candidates and the recruiters prefer resumes to be submitted as an e-document. Validating those resumes manually is not much flexible and effective and time saving. The team requires more man power to scrutinize the resumes of the candidates. The aim of our work is to help the recruiters to find the most appropriate resume that match all their requirements. The system allows the recruiter to post his/her requirement as query, and the system will recommend the relevant resume by calculating the similarity between the query and the resume using Vector Space Model (VSM)

A COMPARATIVE STUDY ON HEART DISEASE ANALYSIS USING CLASSIFICATION TECHNIQUES

As it is modern era where people use computers more for work and other purposes physical activities are reduced. Due to work pressure they are not worrying about food habits. This results in introduction of junk food. These junk foods in turn results in many health issues. Major issue is heart disease. It is the major cause of casualty all over the world. Prediction of such heart disease is a tough task. But Countless mining approaches overcome this difficulty. Nowadays data mining techniques play’s an important role in many fields such as business application, stock market analysis, e-commerce, medical field and many more. Previously many techniques like Bayesian classification, decision tree and many more are employed for heart disease prediction. In this proposal we are going to do a comparative study on three algorithms

A COMPARATIVE STUDY ON HEART DISEASE ANALYSIS USING CLASSIFICATION TECHNIQUES

As it is modern era where people use computers more for work and other purposes physical activities are reduced. Due to work pressure they are not worrying about food habits. This results in introduction of junk food. These junk foods in turn results in many health issues. Major issue is heart disease. It is the major cause of casualty all over the world. Prediction of such heart disease is a tough task. But Countless mining approaches overcome this difficulty. Nowadays data mining techniques play’s an important role in many fields such as business application, stock market analysis, e-commerce, medical field and many more. Previously many techniques like Bayesian classification, decision tree and many more are employed for heart disease prediction. In this proposal we are going to do a comparative study on three algorithms

VALIDATING EFFECTIVE RESUME BASED ON EMPLOYER’S INTEREST WITH RECOMMENDATION SYSTEM

In current technological world, recruitment process of corporate has evolved to the greater extent. Both the candidates and the recruiters prefer resumes to be submitted as an e-document. Validating those resumes manually is not much flexible and effective and time saving. The team requires more man power to scrutinize the resumes of the candidates. The aim of our work is to help the recruiters to find the most appropriate resume that match all their requirements. The system allows the recruiter to post his/her requirement as query, and the system will recommend the relevant resume by calculating the similarity between the query and the resume using Vector Space Model (VSM)