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Collaborative Filtering and Artificial Neural Network Based Recommendation System for Advanced Applications  [PDF]
Bharadwaja Krishnadev Mylavarapu
Journal of Computer and Communications (JCC) , 2018, DOI: 10.4236/jcc.2018.612001
Abstract: To make recommendation on items from the user for historical user rating several intelligent systems are using. The most common method is Recommendation systems. The main areas which play major roles are social networking, digital marketing, online shopping and E-commerce. Recommender system consists of several techniques for recommendations. Here we used the well known approach named as Collaborative filtering (CF). There are two types of problems mainly available with collaborative filtering. They are complete cold start (CCS) problem and incomplete cold start (ICS) problem. The authors proposed three novel methods such as collaborative filtering, and artificial neural networks and at last support vector machine to resolve CCS as well ICS problems. Based on the specific deep neural network SADE we can be able to remove the characteristics of products. By using sequential active of users and product characteristics we have the capability to adapt the cold start product ratings with the applications of the state of the art CF model, time SVD++. The proposed system consists of Netflix rating dataset which is used to perform the baseline techniques for rating prediction of cold start items. The calculation of two proposed recommendation techniques is compared on ICS items, and it is proved that it will be adaptable method. The proposed method can be able to transfer the products since cold start transfers to non-cold start status. Artificial Neural Network (ANN) is employed here to extract the item content features. One of the user preferences such as temporal dynamics is used to obtain the contented characteristics into predictions to overcome those problems. For the process of classification we have used linear support vector machine classifiers to receive the better performance when compared with the earlier methods.
Multiple Architectural Approach for Urban Development Using Wearable IoT Devices: A Combined Machine Learning Approach  [PDF]
Raghu T Mylavarapu, Bharadwaja Krishnadev Mylavarapu
Advances in Internet of Things (AIT) , 2018, DOI: 10.4236/ait.2018.83003
Abstract: Machine Learning becomes a part of our life in recent days and everything we do in interlinked with machine learning. As a technocrat, we tried to implement machine learning with Internet of Things (IoT) for better implementation of technology in organizations for security. We designed an sample architecture which will carry the burden of safeguarding the organizational data with IoT using machine learning with an effective manner and in this case we were proposing utilization of cloud computing for better understanding of data storage and retrieval process. Machine learning is used for the prediction models based on which we need to perform high level analysis of data and using IoT we promote authorization mechanism based on which we recognize the appropriate recipient of data and cloud for managing the data services with the three-tier architecture. We present the architecture we are proposing for better utilization of machine learning and IoT with cloud architecture.
Interpolation of Generalized Functions Using Artificial Neural Networks  [PDF]
Raghu T Mylavarapu, Bharadwaja Krishnadev Mylavarapu, Uday Shankar Sekhar
Journal of Computer and Communications (JCC) , 2018, DOI: 10.4236/jcc.2018.67004
Abstract: In this paper we employ artificial neural networks for predictive approximation of generalized functions having crucial applications in different areas of science including mechanical and chemical engineering, signal processing, information transfer, telecommunications, finance, etc. Results of numerical analysis are discussed. It is shown that the known Gibb’s phenomenon does not occur.
The myxophyce？| of the United Provinces, India.a？？I
Yajnavalkya Bharadwaja
- , 1935,
Abstract:
AlignHUSH: Alignment of HMMs using structure and hydrophobicity information
Oruganty Krishnadev, Narayanaswamy Srinivasan
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-275
Abstract: We have assessed the performance of AlignHUSH using known evolutionary relationships available in SCOP. AlignHUSH performs better than the best HMM-HMM alignment methods and is observed to be even more sensitive at higher error rates. Accuracy of the alignments obtained using AlignHUSH has been assessed using the structure-based alignments available in BaliBASE. The alignment length and the alignment quality are found to be appropriate for homology modeling and function annotation. The alignment accuracy is found to be comparable to existing methods for profile-profile alignments.A new method to align HMMs has been developed and is shown to have better sensitivity at error rates of 10% and above when compared to other available programs. The proposed method could effectively aid obtaining clues to functions of proteins of yet unknown function.A web-server incorporating the AlignHUSH method is available at http://crick.mbu.iisc.ernet.in/~alignhush/ webciteAlignment between sequences is useful and ubiquitous in bioinformatics [1]. Many of the advances made in the field of bioinformatics can be attributed to advances in alignment of sequences. The performance of homology-based structural modeling methods in CASP over last several years is strongly correlated to the accuracy of the alignment between template and the target [2]. Alignments are also routinely generated for effective identification of remote homologues leading to function annotation of newly discovered proteins from genome sequence data [3,4]. The explosion of sequence data from genome sequencing projects has exposed the limitation of current methods to recognize homologues in the twilight region (<30% sequence identity) and beyond (the midnight region of sequence similarity).It was found quite early that profile methods, such as PSI-BLAST [5,6] can be more sensitive and accurate than single sequence-based methods. The starting point for deriving various kinds of profiles such as Position Specific Scoring
DEVELOPMENT OF GUM ARABIC EDIBLE COATING FORMULATION THROUGH NANOTECHNOLOGICAL APPROACHES AND THEIR EFFECT ON PHYSICO-CHEMICAL CHANGE IN TOMATO (Solanum lycopersicum L) FRUIT DURING STORAGE
GUNASEKARAN, K.,KRISHNADEV, PALADUGU
- , 2017,
Abstract: Coating of greenish tomato fruit with gum arabic nano formulations has been found to delay the ripening process and maintained the overall quality and prolonging life of the fruit. In this research, development of gum arabic nano formulations using low energy approach method was investigated. An optimum GA-Tween-80-NaCl ratio of 1:1.5:0.5, 1.5:1.5:0.5 and 2:1.5:0.5 formed nano range droplet size 62.1, 91 and 112.5 nm with ideal stability of -14.5 mV, -22.3 mV and -13.6 mV respectively. Gum arabic in aqueous solutions of 1, 1.5 and 2 % was applied as an edible coating to semi matured tomatoes which were stored at 32 °C and 35- 42 % RH for 28 d. Fruit coated with 1.5 % gum arabic nano formulation delayed the ripening process and significantly (P≤ 0.05) found in changes of physiological loss in weight, total soluble solids, ascorbic acid and titratable acidity content to uncoated control fruit. The results conclude that by using 1.5 % gum arabic nano formulation as an edible coating, can delay the ripening process and enhance the storage life of tomatoes at 32° C and at the matured greenish yellow stage can be extended upto 14 d without any negative effects on postharvest quality. Thus, gum arabic based nano formulations could introduce a kind of safe and effective manner for extending storage time and preserved the quality of fruits and vegetables
Construction of a more complete quantum fluid model from Wigner-Boltzmann Equation with all higher order quantum corrections
Anirban Bose,Mylavarapu S. Janaki
Physics , 2015,
Abstract: A semiclassical Quantum Hydrodynamic model has been derived by taking the moments of the Wigner-Boltzmann equation. For the first time, the closure has been achieved by the use of the momentum shifted version of all order quantum corrected solution of the Wigner-Boltzmann equation and that has considerably extended the applicability of the model towards the low temperature and high density limit. In this context, the importance of the correlation and exchange effects have been retained through the Kohn-Sham equation in the construction of the Wigner-Boltzmann equation. The validity of the approach is subject to the existence of the Taylor's expansion of the associated Kohn-Sham potential.
Micro-Modelling Approach to Predict the Influence of Hydrogen Pressure on Short Crack Behaviour  [PDF]
Claude Lincourt, Jacques Lanteigne, Madhavarao Krishnadev, Carl Blais
Modeling and Numerical Simulation of Material Science (MNSMS) , 2013, DOI: 10.4236/mnsms.2013.33A006
Abstract: A micromechanical model, based on the FEA (finite element analysis), was developed to estimate the influence of hydrogen pressure on short crack behaviour. Morphology of voids has important connotations in the development of the model. Stress intensity factor was calculated for different crack geometries under hydrogen pressure. The analysis indicates that the form factor of a crack emerging from a round void will be less affected by trapped hydrogen pressure-compared to an elongated void. This analysis reinforces the beneficial effect of inclusion shape control in reducing significantly the detrimental effect of hydrogen.
Calculation of the Stress Intensity Factor in an Inclusion-Containing Matrix  [PDF]
Claude Lincourt, Jacques Lanteigne, Madhavarao Krishnadev, Carl Blais
Modeling and Numerical Simulation of Material Science (MNSMS) , 2019, DOI: 10.4236/mnsms.2019.92002
Abstract: The intent of this paper is to propose an engineering approach to estimate the stress intensity factor of a micro crack emerging from an inclusion in relation with the morphology of the inclusion and its relative stiffness with the matrix. A micromechanical model, based on the FEA (finite element analysis) of the behavior of cracks initiated at micro structural features such as inclusions, has been developed using LEFM (Linear Elastic Fracture Mechanics) to predict the stress intensity factor of a micro crack emerging from an inclusion. Morphology of inclusions has important connotations in the development of the analysis. Stress intensity factor has been estimated from the FEA model for different crack geometries. Metallographic analysis of inclusions has been carried out to evaluate the typical inclusion geometry. It also suggests that micro cracks less than 1？μm behave differently than larger cracks.
Viscoelastic modes in a strongly coupled cold magnetized dusty plasma
Debabrata Banerjee,Janaki Sita Mylavarapu,Nikhil Chakrabarti
Physics , 2013, DOI: 10.1063/1.3515897
Abstract: A generalized hydrodynamical model has been used to study low frequency modes in a strongly coupled, cold, magnetized dusty plasma. Such plasmas exhibit elastic properties due to strong correlations among dust particles and the tensile stresses imparted by the magnetic field. It has been shown that longitudinal compressional Alfven modes and elasticity modified transverse shear mode exist in such a medium. The features of these collective modes are established and discussed.
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