This study deals with the role of compensation system in improving the quality of educational services (University of Halabja as a Model) also our problem was the following question ; What is the role of compensation system in its different dimensions in improving the quality of educational services? And what is the relationship and impact of using the dimensions of the compensation system to improve the quality of educational services? The hypothesis of the research included the correlation and the impacts between the compensation system and its combined variables in the quality of educational services. This was proved through a field study and the distribution of questionn

Altruism is one of good qualities of human being expressing his highness and triumph. Self control has A signifies in a lot of psychological, educational, Social, ethical and healing fields Where the higher self control relates with high degrees of carefulness accuracy, problem solving, choice. judgment and decision making. the present study aimos at measuring altruism among university students , self control among them , recognizing the statistically differences significance on self control among university students according to gender variable and recognizing the correlation between attruism and self control among university students . the sample consists of the basic application one (200) students (100) males and (100) males that had

Problem: Find dimensions of the problem by answering the following question: what the effect of using the Six Thinking Hats strategy to acquire the historical concepts and retain the fourth-grade students in the subject of literary history. Importance of research: current research is gaining importance in many ways, including: 1. Keep pace with the new in the field of education and modern educational strategies. 2. Shed light on innovative education strategy in the teaching of history, which is one of the materials that need to renew the tragedy of instruction methods for students. 3. Out of the monotony and traditional way of teaching to a method and a new strategy to develop the teacher and the learners thinking skills through various

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d