After looking at the books of the first two grammarians, may God have mercy on them and reward them for what they have provided us with the rules of service to the Book of God and service to Arabic, we must highlight some of the things that the grammarians wanted to clarify, which did not come out of what they proved, but we are working on the statement of the issuance of the passport Provisions from the syntactic industry, and whether it is intended to prove a rule is not very added to the statement of speech, and we know that language, any language was the function of understanding; therefore they said: (speech is a useful word that indicates the benefit improves silence on them), and this concept between Grammatical controls and conte

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

A winglet is devices attached at the wing tips, used to improve aircraft wing efficiency by reduction influence wing tips vortices and induct drag, increasing lift force at the wing tips and effective aspect ratio without adding greatly to the structural stress and weight in the wing structure. This paper is presented three-dimensional numerical analysis to proposed modification swept back wing by adding Raked winglets devices at the main wing tips belong the two seat trainer aircraft type Aermacchi Siai S211 by using Fluent ANSYS 13 software. CFD numerical analysis process was performed at the same flight boundary conditions indifferent wing angle of attacks with constant air flow velocity V∞ =50 (m/sec), ambient pressure Po=101325 (P

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

3D geological model for each reservoir unit comprising the Yamama Formation revealed to that the formation is composed of alternating reservoirs and barriers. In Subba and Luhais fields the formation began with barrier YB-1 and four more barriers (YB-2, YB-3, YB-4, YB-5), separated five reservoirs (YR-A, YR-B, YR-C, YR-D, YR-E) ranging in thickness from 70 to 80 m for each of them deposited by five sedimentary cycles. In the Ratawi field the formation was divided into three reservoir units (YR-A, YR-B, and YR-C) separated by two barrier units (YB-2 and YB-3), the first cycle is missing in Ratawi field.  

The study involves 1 well in Luhais field (Lu-12), 3 wells in Subba field (Su-7, Su-8, and Su-9), and 5 wells in Ratawi fi