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Interpenetrating polymeric network hydrogel for stomach-specific drug delivery of clarithromycin: Preparation and evaluation
Gupta Anish,Siddiqui Abdul,Datta Maurya,Ramchand Dhakar
Asian Journal of Pharmaceutics , 2010,
Abstract: The aim of this study was to develop a controlled release system targeting antibiotic delivery to the stomach. The hydrogels were synthesized by using chitosan, poly (acrylic acid) and poly (vinyl pyrrolidone) polymers crosslinked with glutaraldehyde and N,N′-methylenebisacrylamide. Interpenetrating polymeric network (IPN) hydrogels were prepared by varying the concentration of crosslinking agent (glutaraldehyde). The amount of chitosan, poly (acrylic acid), poly (vinyl pyrrolidone) and N,N′-methylenebisacrylamide were kept constant in all formulations. The effect of glutaraldehyde concentration on the swelling and release characteristics were evaluated. Modalities used to assess the most optimal hydrogel formulation included high liquid chromatography, FTIR analysis, differential scanning calorimetry, swelling studies, in vitro drug release study, mucoadhesive study and scanning electron microscopy. The result showed that IPN hydrogels were greater in swelling, more mucoadhesive and released more drug at lower pH values. Thus, it is believed that the antibiotic concentration in the stomach might be sustained through this formulation.
Investigation of Probability Generating Function in an Interdependent M/M/1:(∞; GD) Queueing Model with Controllable Arrival Rates Using Rouche’s Theorem  [PDF]
Vishwa Nath Maurya
Open Journal of Optimization (OJOp) , 2012, DOI: 10.4236/ojop.2012.12006
Abstract: Present paper deals a M/M/1:(∞; GD) queueing model with interdependent controllable arrival and service rates where- in customers arrive in the system according to poisson distribution with two different arrivals rates-slower and faster as per controllable arrival policy. Keeping in view the general trend of interdependent arrival and service processes, it is presumed that random variables of arrival and service processes follow a bivariate poisson distribution and the server provides his services under general discipline of service rule in an infinitely large waiting space. In this paper, our central attention is to explore the probability generating functions using Rouche’s theorem in both cases of slower and faster arrival rates of the queueing model taken into consideration; which may be helpful for mathematicians and researchers for establishing significant performance measures of the model. Moreover, for the purpose of high-lighting the application aspect of our investigated result, very recently Maurya [1] has derived successfully the expected busy periods of the server in both cases of slower and faster arrival rates, which have also been presented by the end of this paper.

 

THEORY OF JOINT LIABILITIES, ADVERSE SELECTION, ASSORTATIVE MATCHING AND SELF-FINANCING
Ramu Maurya
International Journal of Economics and Research , 2011,
Abstract: Microfinance is seen to be a remedy of poverty eradication and globally it is perceived that microfinance can remove the problem of poverty. Basically microfinance works on joint liability model. Traditional theories of credit lending say that rural credit markets are imperfectly competitive and acquiring information about borrowers type that is who is risky and who is safe is not costless. This market imperfection leads to high interest rate and drives out safe borrower from the credit market. In economic literature this problem is considered as adverse selection problem. Joint liability model try to solve the problem of adverse selection through group lending.This paper explores the idea of joint liability model and tries to solve the problem of adverse selection through the positive assortative matching. Paper concludes that in positive assortative matching, the payoffs of borrowers would be more than the payoffs of negative assortative matching. Paper, also try to show that self financing can bring down the interest rate and size of penalty and improve the borrower’s expected payoffs
Spatial Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams
Abhinav Maurya
Computer Science , 2015,
Abstract: Many methods have been proposed for detecting emerging events in text streams using topic modeling. However, these methods have shortcomings that make them unsuitable for rapid detection of locally emerging events on massive text streams. We describe Spatially Compact Semantic Scan (SCSS) that has been developed specifically to overcome the shortcomings of current methods in detecting new spatially compact events in text streams. SCSS employs alternating optimization between using semantic scan to estimate contrastive foreground topics in documents, and discovering spatial neighborhoods with high occurrence of documents containing the foreground topics. We evaluate our method on Emergency Department chief complaints dataset (ED dataset) to verify the effectiveness of our method in detecting real-world disease outbreaks from free-text ED chief complaint data.
A Well Conditioned and Sparse Estimate of Covariance and Inverse Covariance Matrix Using a Joint Penalty
Ashwini Maurya
Statistics , 2014,
Abstract: We develop a method for estimating a well conditioned and sparse covariance matrix from a sample of vectors drawn from a sub-gaussian distribution in high dimensional setting. The proposed estimator is obtained by minimizing the squared loss function and joint penalty of $\ell_1$ norm and sum of squared deviation of the eigenvalues from a positive constant. The joint penalty plays two important roles: i) $\ell_1$ penalty on each entry of covariance matrix reduces the effective number of parameters and consequently the estimate is sparse and ii) the sum of squared deviations penalty on the eigenvalues controls the over-dispersion in the eigenvalues of sample covariance matrix. In contrast to some of the existing methods of covariance matrix estimation, where often the interest is to estimate a sparse matrix, the proposed method is flexible in estimating both a sparse and well-conditioned covariance matrix simultaneously. We also extend the method to inverse covariance matrix estimation and establish the consistency of the proposed estimators in both Frobenius and Operator norm. The proposed algorithm of covariance and inverse covariance matrix estimation is very fast, efficient and easily scalable to large scale data analysis problems. The simulation studies for varying sample size and number of variables shows that the proposed estimator performs better than graphical lasso, PDSCE estimates for various choices of structured covariance and inverse covariance matrices. We also use our proposed estimator for tumor tissues classification using gene expression data and compare its performance with some other classification methods.
Exterior Sourcing and Technology Distinctness as Indicators for Radical Innovations: Evidence from Patents in Information Technology Industry  [PDF]
Avimanyu Datta
Technology and Investment (TI) , 2011, DOI: 10.4236/ti.2011.23020
Abstract: We hypothesized and tested the role of looking beyond a firm’s focal industry on technology distinctness and both of their impacts on radicalness of innovations. We used patent filings from 1996 through 2009 (N = 192,070) from the IT industry within the S & P-500 database. We also classified exterior sourcing as high and low, and divided technology distinctness as high, medium, and low. We found that when innovations are primarily sourced exteriorly, there is a negative relationship with technology distinctness. We also found that the relationship between technology distinctness and radicalness is stronger at lower levels of exterior sourcing than at higher levels. Further, when exterior sourcing is unable to create highly distinct technologies, the relationship between technology distinctness and radicalness goes from sparsely significant to significantly negative.
Application of Bootstrap in Dose Apportionment of Nuclear Plants Via Uncertainty Modeling of the Effluent Released from Plants  [PDF]
Debabrata Datta
World Journal of Nuclear Science and Technology (WJNST) , 2012, DOI: 10.4236/wjnst.2012.21007
Abstract: Nuclear power plants are always operated under the guidelines stipulated by the regulatory body. These guidelines basically contain the technical specifications of the specific power plant and provide the knowledge of the discharge limit of the radioactive effluent into the environment through atmospheric and aquatic route. However, operational constraints sometimes may violate the technical specification due to which there may be a failure to satisfy the stipulated dose apportioned to that plant. In a site having multi facilities sum total of the dose apportioned to all the facilities should be constrained to 1 mSv/year to the members of the public. Dose apportionment scheme basically stipulates the limit of the gaseous and liquid effluent released into the environment. Existing methodology of dose apportionment is subjective in nature that may result the discharge limit of the effluent in atmospheric and aquatic route in an adhoc manner. Appropriate scientific basis for dose apportionment is always preferable rather than judicial basis from the point of harmonization of establishing the dose apportionment. This paper presents an attempt of establishing the discharge limit of the gaseous and liquid effluent first on the basis of the existing value of the release of the same. Existing release data for a few years (for example 10 years) for any nuclear power station have taken into consideration. Bootstrap, a resampling technique, has been adopted on the existing release data sets to generate the corresponding population distribution of the effluent release. Cumulative distribution of the population distribution obtained is constructed and using this cumulative distribution, 95th percentile (upper bound) of the discharge limit of the radioactive effluents is computed. Dose apportioned for a facility is evaluated using this estimated upper bound of the release limit. Paper de- scribes the detail of the bootstrap method in evaluating the release limit and also presents the comparative study of the dose apportionment using this new method and the existing adhoc method.
Construction of Zero Autocorrelation Stochastic Waveforms  [PDF]
Somantika Datta
Advances in Pure Mathematics (APM) , 2012, DOI: 10.4236/apm.2012.26065
Abstract: Stochastic waveforms are constructed whose expected autocorrelation can be made arbitrarily small outside the origin. These waveforms are unimodular and complex-valued. Waveforms with such spike like autocorrelation are desirable in waveform design and are particularly useful in areas of radar and communications. Both discrete and continuous waveforms with low expected autocorrelation are constructed. Further, in the discrete case, frames for Cd are constructed from these waveforms and the frame properties of such frames are studied.
Energy Conscious Dynamic Provisioning of Virtual Machines using Adaptive Migration Thresholds in Cloud Data Center
Khushbu Maurya,Richa Sinha
International Journal of Computer Science and Mobile Computing , 2013,
Abstract: The fast growing demand for computational power utilized by modern applications with rapidly changing Cloud computing technology have directed to the foundation of large-scale virtualized data centers.Such data centers consume massive amounts of electrical energy resulting in high operating costs and carbon dioxide (CO2) emissions. Dynamic consolidation of virtual machines (VMs) using Dynamicmigration and switching off idle nodes to the sleep mode provide better optimized resource usage, lower energy consumption, which provides high performance & better quality of service. However incompatibility between specification of physical machine and user requests in cloud, leads towards problems like poor load balancing, energy-performance trade-off and large power consumption etc. Also the VM placement should be optimized continuously in an online manner because of fast varying workloads in current application. Tounderstand the inferences of the online behaviour of the problem, we conduct competitive analysis of optimal online deterministic & Adaptive Migration Thresholds based algorithms for the single VM migration and dynamic VM consolidation problem.Concentrating at this issue, this paper presents an energy conscious, power aware load balancing strategy based on adaptive migration of virtual machines (VMs). This strategy will be applied to virtual machines on cloud, considering higher and lower thresholds for migration of virtual machines on the servers also here we consider RAM & Bandwidth for better performance & load balancing. If the load is greater or lower then defined upper & lower thresholds, VMs will be migrated respectively, boosting resource utilization of the cloud data center and reducing their energy consumption. To reduce number of migration we integrate minimum migration time policy which is capable of reducing the number of migration and the energy consumption of virtual machine migration also achieves load balancing and meet service level agreement (SLA) requirements. This document gives formatting instructions for authors preparing papers forpublication in the Proceedings of an IEEE conference. The authors must follow the instructions given in the document for the papers to be published. You can use this document as both an instruction set and as a template into which you can type your own text.
Comparison of Software Architecture Evaluation Methods for Software Quality Attributes
L. S. Maurya
Journal of Global Research in Computer Science , 2010,
Abstract: Since the architecture of a software system constrains the quality attributes, the decisions taken during architectural design have a large impact on the resulting system. An architectural design method is presented that applies iterative evaluation of the software architecture in order to the quality requirements. Architecture evaluation is performed by using scenarios, simulation, mathematical modeling and experience-based reasoning. The software architecture has been keyed as an important part of a software system. Further, the software architecture impacts the quality attributes of a system, e.g., performance and maintainability. Therefore, methods for evaluating the quality attributes of software architectures are important. In this paper, we present a survey of software architecture evaluation methods. We concentrate on methods for evaluating one or several of the quality attributes performance, maintainability, testability, and portability. Based on a literature search and review of 76 articles, we present and compare ten evaluation methods. We have found that most evaluation methods only address one quality attribute, and very few can evaluate several quality attributes simultaneously in the same framework or method. Further, only one of the methods includes trade-off analysis. Therefore, our results suggest an altered research focus on software architecture evaluation methods than can direct several quality attributes and the possible trade-offs between different quality attributes.
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