In this paper Hermite interpolation method is used for solving linear and non-linear second order singular multi point boundary value problems with nonlocal condition. The approximate solution is found in the form of a rapidly convergent polynomial. We discuss behavior of the solution in the neighborhood of the singularity point which appears to perform satisfactorily for singular problems. The examples to demonstrate the applicability and efficiency of the method have been given.

The behavior of thinking is consider one of the modern concepts that appear in the last 20 years, this concept has attracted the attention of psychologists and researchers for thinking has a great role in many fields like teaching ,educational,economical,cultural and social fields.
One of thinking manner is imaginal thinking that has a great role in human civilization. imaginal thinking lead to innovation ,poems, inventions and arts. imaginal thinkingled to highscores in talented schools by escalating their thinking range and solving problems that consider one of organized and free assumption thinking.
The development of problems thinking strategies reflect the development of organized brain process ability.
That studies assumes

Hysterectomy is one of the most common gynecological operations done worldwide. Early diagnosis of the psychosexual effects of a hysterectomy and the fast application of appropriate treatment can prevent further worsening and persistence of symptoms, especially with respect to higher levels of anxiety, depression, lower self-esteem, and sexual impact after a hysterectomy. The aim of this study was to assess the psychological and sexual problems of women with hysterectomy. A descriptive study was carried out from March 1, 2023 to May 25, 2023 to determine the level of psychosexual problems experienced by women after hysterectomy. A purposive (non-probability) sample of 120 women who visited the outpatient clinic at Baghdad Teaching H

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving nonli