World War II has brought suffering for all people; it has led people to have a nostalgic feeling. The war has many faces all of them are ugly, like death, separation, loneliness, violence, crime, betrayal, and disconnection and many other meanings. Michael Ondaatje in his novel The English Patient (1992) portrays a picture of the effect of World War II on four different characters; Hana a Canadian nurse, The English patient who is Hungarian, Caravaggio a Canadian-Italitan thief, and Kip an Indian sapper. They live together in one house, share their secrets and memories about World War II. Ondaatje brings them together to reveal their secrets and to heal their wounds of the war experience.

World War II has brought suffering for all people; it has led people to have a nostalgic feeling. The war has many faces all of them are ugly, like death, separation, loneliness, violence, crime, betrayal, and disconnection and many other meanings. Michael Ondaatje in his novel The English Patient (1992) portrays a picture of the effect of World War II on four different characters; Hana a Canadian nurse, The English patient who is Hungarian, Caravaggio a Canadian-Italitan thief, and Kip an Indian sapper. They live together in one house, share their secrets and memories about World War II. Ondaatje brings them together to reveal their secrets and to heal their wounds of the war experience.

The study showed a significant rise in the proportion of the labor force in agriculture
activity among the detailed economic activities in 1997 with a rate (%28.9), and then
decreased to (%18.8) in 2011, and this belong to the deterioration of agriculture and the
transition to the other economic activities.
2- The highest percentage of male's participation in year 1997 obtained by the activity (A),
which is represented by agriculture , where was (%30.0) while the highest percentage of
female's participation has been brought by the activity (M) which is represented education
with a rate (% 47.9). while in 2011 that the highest proportion of males' concentration
obtained by the activity (L) with a rate (%23.1) while

Abstract

               The research aimed to prepare an audit program focusing on the activities of municipal institutions related to the environmental dimension as one of the dimensions of sustainable development, and applying the program for the purpose of preparing an oversight report related to assessing the impact of the activities of municipal institutions on the environmental reality as the main channel through which municipal institutions contribute to achieving the part related to it. Among the requirements of sustainable development, the proposed program was prepared and applied to the institutions affiliated to the Directorate of Mu

Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance