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Extraction Drainage Network for Lesser Zab River Basin from DEM using Model Builder in GIS
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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.

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Publication Date
Mon Feb 22 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
MRI images series segmentation using the geodesic deformable model
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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to compare between parametric and nonparametric transfer function model
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In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Sun Aug 24 2025
Journal Name
Basrah Journal Of Agricultural Sciences
Histological Study of the Stomach of the North African Catfish Clariasgariepinus (Burchell, 1822) (Siluriformes, Clariidae) from the Tigris River, Iraq
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This study investigates the stomach morphology and histochemistry of Clarias gariepinus. Grossly, the stomach is a J-shaped organ with three distinct regions: cardiac, fundic, and pyloric. Histologically, its wall comprises four layers: mucosa, submucosa, muscularis externa, and serosa. The mucosa exhibits broad longitudinal folds lined by high columnar cells with basal oval nuclei. These cells contain apical mucosubstances that react positively with Periodic Acid Schiff (PAS) stain and negatively with Alcian Blue (AB). Gastric pits result from mucosal invaginations. Glands are present in the fundic and cardiac regions but absent in the pyloric. Oxynticopeptic cells exclusively line the fundic glands. Enteroendocrine cells are distr

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Publication Date
Sun Aug 24 2025
Journal Name
Basrah Journal Of Agricultural Sciences
Histological Study of the Stomach of the North African Catfish Clariasgariepinus (Burchell, 1822) (Siluriformes, Clariidae) from the Tigris River, Iraq
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This study investigates the stomach morphology and histochemistry of Clarias gariepinus. Grossly, the stomach is a J-shaped organ with three distinct regions: cardiac, fundic, and pyloric. Histologically, its wall comprises four layers: mucosa, submucosa, muscularis externa, and serosa. The mucosa exhibits broad longitudinal folds lined by high columnar cells with basal oval nuclei. These cells contain apical mucosubstances that react positively with Periodic Acid Schiff (PAS) stain and negatively with Alcian Blue (AB). Gastric pits result from mucosal invaginations. Glands are present in the fundic and cardiac regions but absent in the pyloric. Oxynticopeptic cells exclusively line the fundic glands. Enteroendocrine cells are distr

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Publication Date
Wed Jun 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Proposed model for data protection in information systems of government institutions
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Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of

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Publication Date
Wed May 01 2024
Journal Name
Journal Of Physics: Conference Series
A modified ARIMA model for forecasting chemical sales in the USA
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Abstract<p>model is derived, and the methodology is given in detail. The model is constructed depending on some measurement criteria, Akaike and Bayesian information criterion. For the new time series model, a new algorithm has been generated. The forecasting process, one and two steps ahead, is discussed in detail. Some exploratory data analysis is given in the beginning. The best model is selected based on some criteria; it is compared with some naïve models. The modified model is applied to a monthly chemical sales dataset (January 1992 to Dec 2019), where the dataset in this work has been downloaded from the United States of America census (www.census.gov). Ultimately, the forecasted sales </p> ... Show More
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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Robust Estimations for power Spectrum in ARMA(1,1) Model Simulation Study
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Simulation Study

 

Abstract :

Robust statistics Known as, Resistance to mistakes resulting of the deviation of Check hypotheses of statistical properties ( Adjacent Unbiased  , The Efficiency of data taken from a wide range of probability distributions follow a normal distribution or a mixture of other distributions with different standard deviations.

 power spectrum function lead to, President role in the analysis of Stationary random processes, organized according to time, may be discrete random variables or continuous. Measuring  its total capacity as frequency function.

Estimation methods Share with

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