In this study, the Earth's surface was studied in Razzaza Lake for 25 years, using remote sensing methods. Images of the satellites Landsat 5 (TM) and 8 (OLI) were used to study and determine the components of the land cover. The study covered the years 1995-2021 with an interval of 5 years, as this region is uninhabited, so the change in the land cover is slow. The land cover was divided into three main classes and seven subclasses and classified using the maximum likelihood classifier with the help of training sets collected to represent the classes that made up the land cover. The changes detected in the land cover were studied by considering 1995 as a reference year. It was found that there was a significant reduction in the water mass that made up the lake and its transformation into arid land. The vegetation cover was characterized by the relative stability of the crop class. Its constant percent ranged 60% to 80%, unlike the natural plant class, which fluctuates due to its dependence on environmental factors, which is characterized by change. The Kaju presence of continuous change between soil subclasses was due to the different environments affecting the study area. The most affected class was the shallow water class, which disappeared as a result of the drought experienced by the lake.
The operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.
In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of drought, normal flow, and during floods. Moreover, the cases of hypothetical op
... Show MoreThis deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values
The study aims to examine the problem of forced displacement and its social and economic problems in light of the Syrian crisis. Such an aim helps to know the difficulties and challenges facing the children of displaced families in learning, and the reasons for their lack of enrolment. It also clarifies whether there are significant statistical differences at among the attitudes of the children of the displaced families towards education regarding the following variables: (the work of the head of the family, the economic level of the family, and the work of the children). The study has adopted the descriptive-analytical approach; a questionnaire was adopted as a tool to collect information. The study was applied to a sample o
... Show MoreRemote sensing provide the best means to monitoring change in vegetation over a wide range of temporal scales over large areas. In this study, the vegetation index which has been applied known as the Stress Related Vegetation Index (STVI) on in the area around the Euphrates River and part of Al-Habbaniyah lake which located at western side of the river in Ramadi city, Al-Anbar province at Iraq to study the vegetation cover changes and detect the areas of changes, using two satellite sensors multispectral images such as TM and ALI, after geometric correction procedure to rectifying these images. The STVI-4 index result was the best than other vegetation indices (STVI-1 and STVI-3) to discriminate the vegetable cover distribution. The diff
... Show MoreThe multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg
... Show MoreThis study sought to give a general picture of the organizations and formations of the ground forces of the Abbasid army in its first era, in preparation and armament and continuous development of the mechanisms to help maintain the moral and spiritual morale in the fighting.
Therefore, the caliphs' interest in building the army, organizing it, arming it, choosing competent leaders, and providing them with various weapons in terms of production and storage, as well as taking care of fortifying the cities and gaps in determination and determination, and embarked on construction and restoration, where amazing speed and acted according to the circumstances. During the first Abbasid era, there were significant developments in the military
The child realize that the meals time provide golden opportunities to get the attention the child needs. However, many difficulties that may appear about eating food can be avoided, if the family used the right way in dealing with this problem. The study aims, in this case, at searching for the reasons that lies behind the child's obstinacy in eating his food and the attempt to study some variables that is related to the research topic.
The results are summed up as follows:
- The number of the sample children is 3 of both sexes between the ages of 3 to 6 years