ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, automation of drainage network extraction from DEMs is an efficient way and has received considerable attention. This study aims to extract drainage networks from Digital Elevation Model (DEM) for Lesser Zab River Basin. Composition parameters of the drainage network including the numbers of streams and the stream lengths are derived from the DEM beside the delineation of catchment areas in the basin. The results from this application can be used to create input files for many hydrologic models.
This paper will juxtapose the effectiveness of conventional methods of graphical cartography and GIS-interpolation methods in presenting the population distribution of the Baghdad Governorate in 2023. The study touches upon the efficiency of two types of cartographic techniques to present demographic data and is concerned with the speed and clearness of the visual perception. The analysis involves the use of traditional techniques (square, triangle, column and divided circle) and the GIS techniques (Kernel Smoothing, Kriging and Inverse Distance weighting) to describe the male, female and aggregate population. Fifty respondents used their comprehension speed on the maps as the sample. The findings demonstrate that the traditional te
... Show MoreIn this study two types of extraction solvents were used to extract the undesirable polyaromatics, the first solvent was furfural which was used today in the Iraqi refineries and the second was NMP (N-methyl-2-pyrrolidone).
The studied effecting variables of extraction are extraction temperature ranged from 70 to 110°C and solvent to oil ratio in the range from 1:1 to 4:1.
The results of this investigation show that the viscosity index of mixed-medium lubricating oil fraction increases with increasing extraction temperature and reaches 107.82 for NMP extraction at extraction temperature 110°C and solvent to oil ratio 4:1, while the viscosity index reaches to 101 for furfural extraction at the same extraction temperature and same
In the present work studies were carried out to extract a cationic dye (Methylene Blue MB) from an aqueous solution using emulsion liquid membrane process (ELM). The organic phase (membrane phase) consists of Span 80 as emulsifier, sulfuric acid solution as stripping agent and hexane as diluent.
In this study, important factors influencing the extraction of methylene blue dye were studied. These factors include H2SO4 concentration in the stripping phase, agitation speed in the dye permeation stage, Initial dye concentration and diluent type.
More than (98%) of Methylene blue dye was extracted at the following conditions: H2SO4 concentration (1.25) M, agitation
... Show MoreThe aim of the research is the detection of heavy metals using (Inductively coupled Plasma ICP) for samples in Tigris river at intakes of water treatment plants Baghdad (Sharq dejla, Al-Wathba, Al-Wahda, and Al-Dora) and samples at Tigris banks near (Al-Adhamya, Al-Shuhda bridge and al-Jadrya).
All the recorded results were fitted with Iraqi standers No. 25 in 1967 for all samples with heavy metals (arsenic Ar, Cadmium Cd, Chromium Cr, Zinc Zn, Lead Pb, Copper Cu, Nickel Ni, Manganese Mn, Ferrous Fe) where all concentration were lower than standard values except Cadmium (0.01- 0.014) in plants intakes and (0.027- 0.048) in river samples while the standard value is (0.005).
Other tests such as chemical oxygen demand and oil &
Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
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