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Search Results: 1 - 10 of 167774 matches for " E Pasha "
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Tuberculosis Surveillance Using a Hidden Markov Model
A Rafei,E Pasha,R Jamshidi Orak
Iranian Journal of Public Health , 2012,
Abstract: Background: Routinely collected data from tuberculosis surveillance system can be used to investigate and monitor the irregularities and abrupt changes of the disease incidence. We aimed at using a Hidden Markov Model in order to detect the abnormal states of pulmonary tuberculosis in Iran.Methods: Data for this study were the weekly number of newly diagnosed cases with sputum smear-positive pulmonarytuberculosis reported between April 2005 and March 2011 throughout Iran. In order to detect the unusual states of the disease, two Hidden Markov Models were applied to the data with and without seasonal trends as baselines.Consequently, the best model was selected and compared with the results of Serfling epidemic threshold which is typically used in the surveillance of infectious diseases.Results: Both adjusted R-squared and Bayesian Information Criterion (BIC) reflected better goodness-of-fit for the model with seasonal trends (0.72 and -1336.66, respectively) than the model without seasonality (0.56 and -1386.75).Moreover, according to the Serfling epidemic threshold, higher values of sensitivity and specificity suggest a higher validity for the seasonal model (0.87 and 0.94, respectively) than model without seasonality (0.73 and 0.68, respectively).Conclusion: A two-state Hidden Markov Model along with a seasonal trend as a function of the model parameters provides an effective warning system for the surveillance of tuberculosis.
A Note on the Characterization of Zero-Inflated Poisson Model  [PDF]
G. Nanjundan, Sadiq Pasha
Open Journal of Statistics (OJS) , 2015, DOI: 10.4236/ojs.2015.52017
Abstract: Zero-Inflated Poisson model has found a wide variety of applications in recent years in statistical analyses of count data, especially in count regression models. Zero-Inflated Poisson model is characterized in this paper through a linear differential equation satisfied by its probability generating function [1] [2].
Survey of Machine Learning Algorithms for Disease Diagnostic  [PDF]
Meherwar Fatima, Maruf Pasha
Journal of Intelligent Learning Systems and Applications (JILSA) , 2017, DOI: 10.4236/jilsa.2017.91001
Abstract: In medical imaging, Computer Aided Diagnosis (CAD) is a rapidly growing dynamic area of research. In recent years, significant attempts are made for the enhancement of computer aided diagnosis applications because errors in medical diagnostic systems can result in seriously misleading medical treatments. Machine learning is important in Computer Aided Diagnosis. After using an easy equation, objects such as organs may not be indicated accurately. So, pattern recognition fundamentally involves learning from examples. In the field of bio-medical, pattern recognition and machine learning promise the improved accuracy of perception and diagnosis of disease. They also promote the objectivity of decision-making process. For the analysis of high-dimensional and multimodal bio-medical data, machine learning offers a worthy approach for making classy and automatic algorithms. This survey paper provides the comparative analysis of different machine learning algorithms for diagnosis of different diseases such as heart disease, diabetes disease, liver disease, dengue disease and hepatitis disease. It brings attention towards the suite of machine learning algorithms and tools that are used for the analysis of diseases and decision-making process accordingly.
E. Rajanarendar, P. Ramesh, Firoz Pasha Shaik , M. Srinivas
Heterocyclic Letters , 2011,
Abstract: The Michel addition of styrylisoxazoles with ethyl benzoyl acetate in presence of ptoluene sulfonic acid (PTSA) catalyst supported on KSF solid furnished the Michael adducts in excellent yields in short time. The Michael adducts underwent reductive cyclization on treatment with SnCl2- MeOH to afford isoxazolo [4,5-b] azepines in high yields.
Modeling the Spread of Infectious Diseases Based the Bayesian Approach
R Jamshidi Orak,K Mohammad,E Pasha,W Sun
Journal of School of Public Health and Institute of Public Health Research , 2007,
Abstract: Background and Aim: Health surveillance systems are now paying more attention to infectious diseases, largely because of emerging and re-emerging infections. The main objective of this research is presenting a statistical method for modeling infectious disease incidence based on the Bayesian approach.Material and Methods: Since infectious diseases have two phases, namely epidemic and non-epidemic, joint distributions seem preferable for modeling disease incidence. We used a hidden Markov model - suitable for joint distributions- to arrive at a statistical model applicable to infectious diseases. Parameter estimation was done using a Bayesian method. The resulting model was then applied to monthly incidence rates for malaria to test the models applicability to real data.Results: The error sum of squares of the model fitted to monthly incidence rates for malaria was 190.59 and the coefficient of determination between observed and fitted values was 0.84. It appears that the hidden Markov model with a cyclic regression equation has a proper goodness of fit when applied to malaria incidence rates. Conclusion: The hidden Markov model is an efficient statistical tool for modeling infectious disease incidence rates.
Nusrat Pasha
The Professional Medical Journal , 2000,
Abstract: Carbon tetra chloride is a reference hepatotoxic compound, which is oxidized into highly reactive and toxicfree radicals in the body. These free radicals cause hepatic damage by hydropic and fatty degeneration.OBJECTIVES: Objective was to study the chronological pattern of hepatic injury induced by free radicalsand the process of auto recovery in male albino rats. It was prospective, interventional and observational study.Twenty four adult male albino rats were divided in two groups, A control (12) and B experimental (12). GroupB was administered carbon tetra chloride (0.05 mg/100 g body weight) as a single intraperitoneal dose. Theanimals were sacrificed by decapitation at 4 hours, 1,2,3,4 and 8th day after the intoxication. Morphologicaland histological changes were observed in liver on gross and light microscopic examination. Routine andspecial stains were employed. CONCLUSION: The first minimal histological effect was observed with in4 hours of introduction of carbon tetra chloride. The maximum fatty changes were observed in 48 hours, whichcontinued till 96 hours. The improvement in fatty changes began after 96 hours and normalization took morethan 8 days.
How Euler would compute the Euler-Poincaré characteristic of a Lie superalgebra
Pasha Zusmanovich
Mathematics , 2008, DOI: 10.1016/j.exmath.2011.06.002
Abstract: The Euler-Poincar\'e characteristic of a finite-dimensional Lie algebra vanishes. If we want to extend this result to Lie superalgebras, we should deal with infinite sums. We observe that a suitable method of summation, which goes back to Euler, allows to do that, to a certain degree. The mathematics behind it is simple, we just glue the pieces of elementary homological algebra, first-year calculus and pedestrian combinatorics together, and present them in a (hopefully) coherent manner.
Central extensions of current algebras
Pasha Zusmanovich
Mathematics , 2008, DOI: 10.1090/S0002-9947-10-05304-3
Abstract: This is an old paper put here for archeological purposes. We compute the second cohomology of current Lie algebras of the form $L\otimes A$, where $L$ belongs to some class of Lie algebras which includes classical simple and Zassenhaus algebras, and of some modular semisimple Lie algebras. The results are largely superseded by subsequent papers, though, perhaps, some tricks and observations used here remain of minor interest.
Invariants of Lie algebras extended over commutative algebras without unit
Pasha Zusmanovich
Mathematics , 2009, DOI: 10.1142/S1402925110000817
Abstract: We establish results about the second cohomology with coefficients in the trivial module, symmetric invariant bilinear forms and derivations of a Lie algebra extended over a commutative associative algebra without unit. These results provide a simple unified approach to a number of questions treated earlier in completely separated ways: periodization of semisimple Lie algebras (Anna Larsson), derivation algebras, with prescribed semisimple part, of nilpotent Lie algebras (Benoist), and presentations of affine Kac-Moody algebras.
Non-existence of invariant symmetric forms on generalized Jacobson-Witt algebras revisited
Pasha Zusmanovich
Mathematics , 2009, DOI: 10.1080/00927871003592023
Abstract: We provide a short alternative homological argument showing that any invariant symmetric bilinear form on simple modular generalized Jacobson-Witt algebras vanishes, and outline another, deformation-theoretic one, allowing to describe such forms on simple modular Lie algebras of contact type.
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