The object of the presented study was to monitor the changes that had happened
in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To
fulfill this goal, different satellite images had been used in different times, MSS
1973, TM 1990, ETM+ 2000 and MODIS 2010. K-Means which is unsupervised
classification and Neural Net which is supervised classification was used to classify
the satellite images 0Tand finally by use 0Tadaptive classification 0Twhich is0T3T 0T3Tapply
s0Tupervised classification on the unsupervised classification. ENVI soft where used
in this study.
The preparation and spectral characterization of complexes for Co(II), Ni(II), Cu(II), Cd(II), Zn(II) and Hg(II) ions with new organic heterocyclic azo imidazole dye as ligand 2-[(2`-cyano phenyl) azo ]-4,5-diphenyl imidazole ) (2-CyBAI) were prepared by reacting a dizonium salt solution of 2-cyano aniline with 4,5-diphenyl imidazole in alkaline ethanolic solution .These complexes were characterized spectroscopically by infrared and electronic spectra along with elemental analysis‚ molar conductance and magnetic susceptibility measurements. The data show that the ligand behaves a bidantate and coordinates to the metal ion via nitrogen atom of azo and with imidazole N3 atom. Octahedral environment is suggested for all metal complex
... Show MoreThe synthesis of [1,2-diaminoethane-N,N'-bis(2-butylidine-3- onedioxime)] [II2L] and its cobalt(II), nickel(II), copper(II), palladium(II), platinum(II, IV), zinc(II), cadmium(II) and mercury(II) complexes is reported. The compounds were characterised by elemental analyses, spectroscopic methods [I.R, UV-Vis, ('H NMR. and EI mass for H2L)], molar conductivities, magnetic moments. I.R. spectra show that (H2L) behaves as a neutral or mononegative ligand depending on the nature of the metal ions. The molar conductance of the complexes in (DMSO) is commensurate with their ionic character. On the basis of the above measurements, a square planar geometry is proposed for NOD, Pd(II), and Pt(II) complexes, and an octahedr-al structure with trans
... Show MoreNew bidentate Schiff base ligand (L) namely [(Z)-3-(2-oxoindolin-3ylildeneamino)benzoic acid] type (NO) was prepared via condensation of isatin and 3-amino benzoic acid in ethanol as a solvent in existence of drops of (glac. CH3COOH). The new ligand (L) was characterized base on elemental microanalysis, FT-IR, UV-Vis, 1H-NMR spectra along with melting point. Ligand complexes in general formula [M(L)2Cl2]. H2O, where: MII = Co, Cu, Cd, and Hg; L= C15H10 N2O3 were synthesized and identified by FT-IR, UV-Vis, 1H-NMR (for Cd complex only) spectra, atomic absorption, chloride content along with molar conductivity and magnetic susceptibility. It was found that the ligand behaves as bidentate on complexation via (N) atom of imine group an
... Show MoreIn the present paper, a simply* compact spaces was introduced it defined over simply*- open set previous knowledge and we study the relation between the simply* separation axioms and the compactness, in addition to introduce a new types of functions known as 𝛼𝑆 𝑀∗ _irresolte , 𝛼𝑆 𝑀∗ __𝑐𝑜𝑛𝑡𝑖𝑛𝑢𝑜𝑢𝑠 and 𝑅 𝑆 𝑀∗ _ continuous, which are defined between two topological spaces.
المستودع الرقمي العراقي. مركز المعلومات الرقمية التابع لمكتبة العتبة العباسية المقدسة
Grey system theory is a multidisciplinary scientific approach, which deals with systems that have partially unknown information (small sample and uncertain information). Grey modeling as an important component of such theory gives successful results with limited amount of data. Grey Models are divided into two types; univariate and multivariate grey models. The univariate grey model with one order derivative equation GM (1,1) is the base stone of the theory, it is considered the time series prediction model but it doesn’t take the relative factors in account. The traditional multivariate grey models GM(1,M) takes those factor in account but it has a complex structure and some defects in " modeling mechanism", "parameter estimation "and "m
... Show MoreThere is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into
... Show MoreIn this study, He's parallel numerical algorithm by neural network is applied to type of integration of fractional equations is Abel’s integral equations of the 1st and 2nd kinds. Using a Levenberge – Marquaradt training algorithm as a tool to train the network. To show the efficiency of the method, some type of Abel’s integral equations is solved as numerical examples. Numerical results show that the new method is very efficient problems with high accuracy.
This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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