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 are increased for year 2000 comparing with 1990. Water, vegetation and barren land are increased, while alluvial soil and shallow water decreased for years 2015 comparing with 2000. The classification accuracy for the proposed method (MVQ) is 90.1%, 90.9% and 90.2% for years 1990, 2000 and 2015, respectively.
The research aims to prepare a preliminary feasibility study that shows the importance of preliminary feasibility study in investment decision making, carrying out of the local demand of service provided in accordance with international standards and statement of investment opportunities available to the private sector in several investment methods. In order to reach the objectives of the study was adopted as a method of partial analysis at the level of economic unity through the study demand, supply, costs, economic and social profitability.
The health sector in Iraq is one of the service sectors facing today a continuous deficiency
... Show MoreThe research is an article that teaches some classes of fully stable Banach - Å modules. By using Unital algebra studies the properties and characterizations of all classes of fully stable Banach - Å modules. All the results are existing, and they've been listed to complete the requested information.
The study aims at analyzing the inconsistent structural and semantic aspects found in the plays of N.A Ostrovsky. The analysis, that includes all the linguistics schools of thoughts in modern Russian language, is performed chronologically to clarify all the ambiguities that the Russian language learners may face. Such difficulties lie in the use of inconsistent aspects with complete declarative sentences and adverbial clauses. Hence, it constructs a new sentence category that consists of secondary clause and its syncretism semantic.
The study illustrates the wide scope of both studying the sentence inconsistent
... Show MoreThe primary purpose of this subject is to define new games in ideal spaces via set. The relationships between games that provided and the winning and losing strategy for any player were elucidated.
In this paper, a Bayesian analysis is made to estimate the Reliability of two stress-strength model systems. First: the reliability of a one component strengths X under stress Y. Second, reliability of one component strength under three stresses. Where X and Y are independent generalized exponential-Poison random variables with parameters (α,λ,θ) and (β,λ,θ) . The analysis is concerned with and based on doubly type II censored samples using gamma prior under four different loss functions, namely quadratic loss function, weighted loss functions, linear and non-linear exponential loss function. The estimators are compared by mean squared error criteria due to a simulation study. We also find that the mean square error is
... Show MoreThis paper concerns with deriving and estimating the reliability of the multicomponent system in stress-strength model R(s,k), when the stress and strength are identical independent distribution (iid), follows two parameters Exponentiated Pareto Distribution(EPD) with the unknown shape and known scale parameters. Shrinkage estimation method including Maximum likelihood estimator (MLE), has been considered. Comparisons among the proposed estimators were made depending on simulation based on mean squared error (MSE) criteria.
The aim of this research is to study some types of fibrewise fuzzy topological spaces. The six major goals are explored in this thesis. The very first goal, introduce and study the notions types of fibrewise topological spaces, namely fibrewise fuzzy j-topological spaces, Also, we introduce the concepts of fibrewise j-closed fuzzy topological spaces, fibrewise j-open fuzzy topological spaces, fibrewise locally sliceable fuzzy j-topological spaces and fibrewise locally sectionable fuzzy j-topological spaces. Furthermore, we state and prove several Theorems concerning these concepts, where j={δ,θ,α,p,s,b,β} The second goal is to introduce weak and strong forms of fibrewise fuzzy ω-topological spaces, namely the fibrewise fuz
... Show MoreExploration activities of the oil and gas industry generate loads of formation water called produced water (PW) up to thousands of tons each day. Depending on the geographic area, formation depth, oil production techniques, and age of oil supply wells, PW from different oil fields contain different chemical compositions. Currently, PW is also known as industrial waste water containing heavy metals that are toxic to humans and the environment, requiring special processing so that they can be disposed of in the environment. To determine the heavy metals content in PW from the Al-Ahdab oil field (AOF), the Ministry of Science and Technology/Agricultural Research Department determined som
The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca
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