Reliability is an essential measure and important component of all power system planning and operation procedures. It is one of the key design factors when designing complex, critical and expensive systems. This paper presents a fuzzy logic approach for reliability improvement planning purposes. Evaluating the reliability of the complex and large planned Iraqi super grid ;as Al- Khairat generating station with its tie set is intended to be compact to that grid; and determination of the given reliability improvement project are the major goals of the paper. Results show that the Iraqi super grid reliability is improved by 9.64%. In the proposed technique, fuzzy set theory is used to include imprecise indices of different components in normal

An efficient combination of Adomian Decomposition iterative technique coupled with Laplace transformation to solve non-linear Random Integro differential equation (NRIDE) is introduced in a novel way to get an accurate analytical solution. This technique is an elegant combination of theLaplace transform, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has also been established that (LT

Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

      Manganese-zinc ferrite Mn_xZn_1-xFe₂O₄ (MnZnF) powder was prepared using the sol-gel method. The morphological, structural, and magnetic properties of MnZnF powder were studied using X-ray diffraction (XRD), atomic force microscopy (AFM), energy dispersive X-ray (EDX), field emission-scanning electron microscopes (FE-SEM), and vibrating sample magnetometers (VSM). The XRD results showed that the MnxZn1-xFe2O4 that was formed had a trigonal crystalline structure. AFM results showed that the average diameter of Manganese-Zinc Ferrite is 55.35 nm, indicating that the sample has a nanostructure dimension. The EDX spectrum revealed the presence of transition metals (Mn, Fe, Zn, and O) in Mang

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

This paper attempts to shed light on the most influential factors in the importance of religious buildings were destroyed because of the recent war due to the control of terrorist gangs of ISIS over the city of Mosul, and to prioritize their reconstruction and their role in reviving the historical center of Mosul.

The research’s problem emerged in the lack of knowledge about the identifying the most influential factors in the importance of religious buildings and utilizing them to prioritize their reconstruction. This study aims to analyze the factors influencing the importance of religious buildings using the Expert Choice software through the Analytic Hierarchy Process (AHP) to reach an analysis of their weights and propose p