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Search Results: 1 - 10 of 12 matches for " Madhavarao Krishnadev "
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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 1μm behave differently than larger cracks.
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.
Combined central membranous and anterior suture cataract in a family
Sundaresan K,Madhavarao G
Indian Journal of Ophthalmology , 1968,
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
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.
Study on the incidence of Salmonella enteritidis in Poultry and meat Samples by Cultural and PCR Methods
Putturu Ramya,Thirtham Madhavarao,Lakkineni Venkateswara Rao
Veterinary World , 2012, DOI: 10.5455/vetworld.2012.541-545
Abstract: Aim: To study the incidence of S.enteritidis in poultry and meat samples by cultural and PCR methods. Materials and Methods: A total of 130 samples (25 each of chicken, mutton, poultry faeces, cloacal samples and 10 each of liver, spleen and kidney) collected from different sources were subjected to cultural and PCR methods for the presence of Salmonella and Salmonella enteritidis. Primers for invA and sefA gene were used for Salmonella and S.enteritidis respectively. Results: Out of 130 samples, 87 were positive for Salmonella spp. i.e. chicken-16(64%), mutton-12(48%), faeces-23(92%), cloacal swabs-23(92%), liver-5(50%), spleen and kidney samples-4(40%) each by PCR methods, whereas 77 were positive by cultural method i.e. chicken-14(56%), mutton-10(40%), faeces-22(88%), cloacal swabs-21(84%), liver-4(40%), spleen and kidney-3(30% each). Out of 87 positive for Salmonella by PCR method, 59(chicken-12, mutton-7, faeces-17, cloacal swabs-15, liver-3, spleen-2, kidney-3) were positive for S.enteritidis. High incidence of S.enteritidis (68%) in all the above samples are indicative of unhygienic conditions in poultry farms. Selective enrichment with Rappaport-Vassilidias (RV) broths and Tetrathionate (TT) broths were superior over Selenite-F (SF) and Selenite cysteine (SC) broths. Conclusions: High incidence of S.enteritidis was seen in most of poultry samples like chicken, kidney, liver and it's faeces than mutton, which was indicative of contamination of S.enteritidis is more prevalent in poultry farms. [Vet World 2012; 5(9.000): 541-545]
Antimicrobial sensitivity and resistance of Salmonella Enteritidis isolated from natural samples
Ramya Putturu,Madhavarao Thirtham,Tirupati Reddy Eevuri
Veterinary World , 2013, DOI: 10.5455/vetworld.2013.185-188
Abstract: Aim: To test the sensitivity of S. Enteritidis for selected antibiotics. Materials and Methods: S. Enteritidis isolates obtained from different samples of chicken, mutton, turkey meat, faecal and cloacal samples of poultry and turkey, eggs, water and feed were subjected for sensitivity and resistance to selected antibiotics like- Chloramphenicol (30μg), Gentamicin (10 μg), Nalidixic Acid (30 μg), Tetracycline (30 μg), Ciprofloxacin (5 μg), Amikacin (30 μg), Amoxicillin (25 μg), Ampicillin (10 μg), Streptomycin (10 μg) and Sulfonamide (30 μg). Antimicrobial susceptibility of the isolates was established by the disk diffusion assay with MH (Muller-Hinton) agar in accordance with French National Antibiogram Committee Guidelines. Results: The sensitivity of S. Enteritidis was 100% for ciprofloxacin followed by chloramphenicol and amikacin (96%), gentamycin (90%), amoxicillin (82%), streptomycin (80%), tetracycline (76%), nalidixic acid (68%), ampicillin (58%) and sulfonamide (10%). The resistance was highest for sulfonamide (76%) followed by ampicillin (32%), nalidixic acid (30%) and 6-20% for gentamycin, amoxicillin and tetracycline. Conclusion: S. Enteritidis isolates were more sensitive to ciprofloxacin, chloramphenicol, amikacin, gentamycin, streptomycin,amoxicillin and tetracyclines and less sensitive to sulfonamides. Higher resistance was observed with sulfonamide followed by ampicillin and nalidixic acid. [Vet World 2013; 6(4.000): 185-188]
Interaction preferences across protein-protein interfaces of obligatory and non-obligatory components are different
Subhajyoti De, O Krishnadev, N Srinivasan, N Rekha
BMC Structural Biology , 2005, DOI: 10.1186/1472-6807-5-15
Abstract: A non-obligatory chain in a complex of known 3-D structure is recognized by its stable existence with same fold in the bound and unbound forms. On the contrary, an obligatory chain is detected by its existence only in the bound form with no evidence for the native-like fold of the chain in the unbound form. Various interfacial properties of a large number of complexes of known 3-D structures thus classified are comparatively analyzed with an aim to identify structural descriptors that distinguish these two types of interfaces. We report that the interaction patterns across the interfaces of obligatory and non-obligatory components are different and contacts made by obligatory chains are predominantly non-polar. The obligatory chains have a higher number of contacts per interface (20 ± 14 contacts per interface) than non-obligatory chains (13 ± 6 contacts per interface). The involvement of main chain atoms is higher in the case of obligatory chains (16.9 %) compared to non-obligatory chains (11.2 %). The β-sheet formation across the subunits is observed only among obligatory protein chains in the dataset. Apart from these, other features like residue preferences and interface area produce marginal differences and they may be considered collectively while distinguishing the two types of interfaces.These results can be useful in distinguishing the two types of interfaces observed in structures determined in large-scale in the structural genomics initiatives, especially for those multi-component protein assemblies for which the biochemical characterization is incomplete.Proteins interact with other proteins and bring about myriad of molecular activities in the cell. Interacting proteins are known to play key roles in almost all cellular and biological processes such as metabolism, endocrine, exocrine and paracrine signaling, protein synthesis and trafficking [1]. With the availability of genomic data in abundance, it is important to conceive protein-protein interactions
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