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Search Results: 1 - 10 of 5377 matches for " Mohammed Omari "
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Comparison of the Bayesian Methods on Interval-Censored Data for Weibull Distribution  [PDF]
Al Omari Mohammed Ahmed
Open Journal of Statistics (OJS) , 2014, DOI: 10.4236/ojs.2014.48053
Abstract: This study considers the estimation of Maximum Likelihood Estimator and the Bayesian Estimator of the Weibull distribution with interval-censored data. The Bayesian estimation can’t be used to solve the parameters analytically and therefore Markov Chain Monte Carlo is used, where the full conditional distribution for the scale and shape parameters are obtained via Metropolis-Hastings algorithm. Also Lindley’s approximation is used. The two methods are compared to maximum likelihood counterparts and the comparisons are made with respect to the mean square error (MSE) to determine the best for estimating of the scale and shape parameters.
Exponential Brute-Force Complexity of A Permutation Based Stream Cipher
Mohammed Omari,Hamdy S. Soliman
International Journal of Computer Network and Information Security , 2013,
Abstract: This paper introduces a permutation generation mechanism based on a shared secret key. The generated permutation vectors are used as encryption keys in a stream ciphering cryptosystem. We investigated various types of attacks on the known stream cipher RC4 and patched most of its loopholes, especially biased-byte and state-related attacks. Unique to our approach, we prove mathematically that the complexity of brute-forcing such a system is (2n), where n is the key size in bytes. This paper also presents a complete security model using permutation-based encryption, in order to handle privacy. In addition, our approach achieved higher performance than that of existing peer techniques, while maintaining solid security. Experimental results show that our system is much faster than the existing security mechanisms, such as AES and DES.
Application of Synchronous Dynamic Encryption System (SDES) in Wireless Sensor Networks
Hamdy S Soliman,Mohammed Omari
International Journal of Network Security , 2006,
Abstract: Inherent to the wireless sensor networks are the two major problems of the broadcasting vulnerability, the limited computational capability and power budget. Even though security is a must in most applications, current sophisticated security protocols are not amenable to the primitiveness of the sensors. In this paper, we introduce a novel security protocol for wireless network of sensors that is very secure, yet simple and efficient. At the core of our security protocol is a simple and fast stream cipher cryptosystem that utilizes permutation vectors as encryption keys, forcing an intruder to a brute-force time complexity of $Omega(2^n)$. In addition, our mechanism alleviates the effect of sensor capture, via its synchronized re-keying feature. In addition to the encryption efficiency, our system utilizes the group deployment of newly joining sensors for sensors power budgeting considerations. Experimental results show very promising future of our system in the wireless networks domain, excelling over other peers of modern cryptosystems (AES, DES, TripleDES), especially in the power budget arena.
Bayesian Survival Estimator for Weibull Distribution with Censored Data
Al Omari Mohammed Ahmed,Noor Akma Ibrahim
Journal of Applied Sciences , 2011,
Abstract: As the most useful distribution for modeling and analyzing life time data in the medical, paramedical and applied sciences among others, Weibull distribution stands out. Nowadays great attention has been given to Bayesian approach and is in contention with other estimation methods. This study explores and compares the performance of Maximum Likelihood and Bayesian using Jeffrey prior and the extension of Jeffrey prior information for estimating the survival function of Weibull distribution with right censored data. On the performance of these estimators with respect to the mean square error and mean percentage error, comparisons are made through simulation study. For all the varying sample size, several specific values of the scale parameter of the Weibull distribution and for the values given for the extension of Jeffrey prior, the estimate of survival function of maximum likelihood is the best compared to the others when the value of extension of Jeffrey prior is 0.4. But then, extension of Jeffrey prior result is the best compared to others when the value of extension of Jeffrey is 1.4.
Numerical Investigation of a Mixed Convection Flow in a Lid-Driven Cavity  [PDF]
Reyad Omari
American Journal of Computational Mathematics (AJCM) , 2016, DOI: 10.4236/ajcm.2016.63026
Abstract: This study is devoted to the computational fluid dynamics (CFD) modeling of steady laminar mixed convection flow and heat transfer in lid driven cavity (10 ≤ Re ≤ 1000). The ratio of the height to the width of the cavity is ranged over H/L = 0.5 to 1.5. The governing equations are solved using commercial finite volume package FLUENT to visualize the nature of the flow and estimate the heat transfer inside the cavity for different aspect ratio. The simulation results are presented in terms of average Nusselt number of the hot wall, velocity profile, and temperature contours. It was found that the average Nusselt number inside the cavity is strongly governed by the aspect ratio as well as the Reynolds number. A parametric study is conducted to demonstrate the effect of aspect ratio on the flow and heat transfer characteristics. It is found that heat transfer enhancement was obtained by decreasing the aspect ratio and/or increasing the Reynolds number.
Bayesian Estimation of Two-Parameter Weibull Distribution Using Extension of Jeffreys' Prior Information with Three Loss Functions
Chris Bambey Guure,Noor Akma Ibrahim,Al Omari Mohammed Ahmed
Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/589640
Abstract: The Weibull distribution has been observed as one of the most useful distribution, for modelling and analysing lifetime data in engineering, biology, and others. Studies have been done vigorously in the literature to determine the best method in estimating its parameters. Recently, much attention has been given to the Bayesian estimation approach for parameters estimation which is in contention with other estimation methods. In this paper, we examine the performance of maximum likelihood estimator and Bayesian estimator using extension of Jeffreys prior information with three loss functions, namely, the linear exponential loss, general entropy loss, and the square error loss function for estimating the two-parameter Weibull failure time distribution. These methods are compared using mean square error through simulation study with varying sample sizes. The results show that Bayesian estimator using extension of Jeffreys' prior under linear exponential loss function in most cases gives the smallest mean square error and absolute bias for both the scale parameter α and the shape parameter β for the given values of extension of Jeffreys' prior.
Clinicopathologic features of hepatic neoplasms in explanted livers : A single institution experience
Mourad Walid,Khalaf Hatem,Tulbah Asma,Al Omari Mohammed
Annals of Saudi Medicine , 2007,
Abstract: Background: Hepatic neoplasms can be the primary indication for hepatic transplantation. The tumors can also be incidentally identified in explanted livers. We explored the clinicopathologic features of hepatic neoplasms identified in explanted livers Materials and Methods: All explanted livers resected between 2001 and 2006 were evaluated for the presence of neoplasms and their clinicopathologic features were examined. Results: In 98 liver transplants, 15 neoplasms (15.3%) were identified. Patient ages ranged from 5 to 63 years (median, 56 years). The primary etiology of hepatic disease was hepatitis C virus in 12 cases, hepatitis B virus in 1 case, cryptogenic cirrhosis in 1 case and congenital hepatic fibrosis in 1 case. Serum alpha-fetoprotein was significantly elevated (>400 U/L) in only 2 cases. CA19-9 was not elevated in any of the cases. The tumors included hepatocellular carcinoma (HCC) in 13 cases, 1 case of cholangiocarcinoma and 1 case of combined HCC and hepatoblastoma. The tumors ranged in size from 0.5 to 5 cm (median 1.4 cm) and were multifocal in 5 of the cases (33%). Tissue alpha-fetoprotein expression was only seen in the cases associated with elevated serum levels. Conclusion: In our institution hepatic neoplasms are seen in more than 15% of explanted livers. They can be incidentally identified, are frequently not associated with elevated serum levels of alpha-fetoprotein and CA19-9, are commonly multifocal but small, and are associated with good prognosis. Elevated serum alpha-fetoprotein, albeit specific, is not a very sensitive marker in the detection of hepatic neoplasms.
Color image quality assessment measure using multivariate generalized Gaussian distribution
Mounir Omari,Abdelkaher Ait Abdelouahad,Mohammed El Hassouni,Hocine Cherifi
Computer Science , 2014,
Abstract: This paper deals with color image quality assessment in the reduced-reference framework based on natural scenes statistics. In this context, we propose to model the statistics of the steerable pyramid coefficients by a Multivariate Generalized Gaussian distribution (MGGD). This model allows taking into account the high correlation between the components of the RGB color space. For each selected scale and orientation, we extract a parameter matrix from the three color components subbands. In order to quantify the visual degradation, we use a closed-form of Kullback-Leibler Divergence (KLD) between two MGGDs. Using "TID 2008" benchmark, the proposed measure has been compared with the most influential methods according to the FRTV1 VQEG framework. Results demonstrates its effectiveness for a great variety of distortion type. Among other benefits this measure uses only very little information about the original image.
A statistical reduced-reference method for color image quality assessment
Mounir Omari,Mohammed El Hassouni,Abdelkaher Ait Abdelouahad,Hocine Cherifi
Computer Science , 2014,
Abstract: Although color is a fundamental feature of human visual perception, it has been largely unexplored in the reduced-reference (RR) image quality assessment (IQA) schemes. In this paper, we propose a natural scene statistic (NSS) method, which efficiently uses this information. It is based on the statistical deviation between the steerable pyramid coefficients of the reference color image and the degraded one. We propose and analyze the multivariate generalized Gaussian distribution (MGGD) to model the underlying statistics. In order to quantify the degradation, we develop and evaluate two measures based respectively on the Geodesic distance between two MGGDs and on the closed-form of the Kullback Leibler divergence. We performed an extensive evaluation of both metrics in various color spaces (RGB, HSV, CIELAB and YCrCb) using the TID 2008 benchmark and the FRTV Phase I validation process. Experimental results demonstrate the effectiveness of the proposed framework to achieve a good consistency with human visual perception. Furthermore, the best configuration is obtained with CIELAB color space associated to KLD deviation measure.
On color image quality assessment using natural image statistics
Mounir Omari,Mohammed El Hassouni,Hocine Cherifi,Abdelkaher Ait Abdelouahad
Computer Science , 2014,
Abstract: Color distortion can introduce a significant damage in visual quality perception, however, most of existing reduced-reference quality measures are designed for grayscale images. In this paper, we consider a basic extension of well-known image-statistics based quality assessment measures to color images. In order to evaluate the impact of color information on the measures efficiency, two color spaces are investigated: RGB and CIELAB. Results of an extensive evaluation using TID 2013 benchmark demonstrates that significant improvement can be achieved for a great number of distortion type when the CIELAB color representation is used.
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