Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

I dealt with this study of one of the hadiths of the Prophet and judged him after studying his deed, especially one of his narrations for the similarity in his name and the name of his father (Abdul Rahman bin Ishaq) Is he a civil "Sadok" or Wasti "weak" and they are in one layer which is called in the science of Hadith (agreed And after a review of Kutkut translations and wound and amendment and other evidence and evidence that it was "weak" and not as he went to him and asserted by the updated Muhammad Nasser al-Din al-Albani may God have mercy on him that in Sindh is a civil rule for the hadeeth "Hassan" and not as said The hadeeth is “weak” because he showed that it is the weak Wasti.
I ask God to be successful in this work an

In this paper, we deal with the problem of general matching of two images one of them has experienced geometrical transformations, to find the correspondence between two images. We develop the invariant moments for traditional techniques (moments of inertia) with new approach to enhance the performance for these methods. We test various projections directional moments, to extract the difference between Block Distance Moment (BDM) and evaluate their reliability. Three adaptive strategies are shown for projections directional moments, that are raster (vertical and horizontal) projection, Fan-Bean projection and new projection procedure that is the square projection method. Our paper started with the description of a new algorithm that is low

The irony pushes us to inquire about what is in the text of contradiction, irony, suspense, and other acts of paradox, as well as a departure from what is logical, or familiar, that attracts the attention of the addressee, and this is what drives us to introspect the text and interrogate it in order to get to know the intended product of the text or its real or metaphorical intent. On the other hand, the irony is more in the literary text than in the scientific texts. Therefore, critics add the word literature to it in their definition.

 As it is represented by the paradox, we will seek to study the paradox of the title and the problematic that it may pose as the beginning of the text, and i

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M