Tekrarlar, anlamı kuvvetlendirmek, ifadeyi zenginleştirmek amacıyla kullanılan dil unsurlarıdır. Ural Batır destanı da tekrarlar, özellikle de ikilemeler açısından zengindir. Bu yazıda, Ural Batır destanındaki ikilemeler gruplandırılarak verilecek ve değerlendirmesi yapılacaktır.

Abstract

Word repeating is language items used for strengthen the meaning and riching the expression. By this view, Ural Batır epic is a good example for word repeating units. In this paper, Ural Batır epic’s word repeating has been presented by classification.

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

تكمن أهمية البحث من الاستفادة من تمرينات الخاصة بمساعدة استعمال أي جهاز تدريبي مثل استعمال جهاز (Vertimax) فإِنَّ هذهِ التدريبات تساعد في تطوير التحمل الخاص وفقًا لما يتطور من قدرات بدنية باستعمال هذا الجهاز، ومن هنا برزت مشكلة البحث انه من المهم  للاعب ان يعمل على الروافع الجسم للحصول على اداء افضل في عملية الرمي والحصول على افضل انجاز لهذة الفعالية باستعمال جهاز تدريبي جديد حيث يسلط مقاومات متعددة في ان وا

In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

This study aimed to extract, purify, and characterize the protease of local Okra Abelmoschus esculentus pods. The extraction process was conducted using ten extraction solutions with different pH and ionic strength values. Phosphate buffer solution with (pH 7, 0.05M, containing 2% sodium chloride) gave the highest activity which was (7.2 Unit/ml) as compared to other solutions, which ranged from 0.8-5.9 Unit/ml. The extracted enzyme purified by several stages. Being, precipitation by gradual addition of Ammonium sulphate from 20 to 85% saturation, then the precipitated enzyme was dialyzed and fractionated through DEAE-Cellulose (22X1.1cm), the enzymic fractions were pooled. The specific activity, purification fold and the enzyme yield value

The main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators  are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit  where linear operator from complete standard fuzzy normed space  into a standard fuzzy normed space  then  belongs to the set of all fuzzy bounded linear operators

The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto  type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for

 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to