An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In addition to that (negative) penalty items are also included such as surface area, evaporation rate.
In order to obtain precise results, an Artificial Neural Network (ANN) model was formulated and applied to correct the elevations of the Digital Elevation Model (DEM) map using real and DEM elevations of available selected control points.
The application of the model is tested using a case study of a catchment area in Diyala and Wasit Governorate. The DEM file was corrected for elevations, using the developed ANN model .This model is found using SPSS – software. The correlation coefficient of this model is found to be (0.97) , with 3- hidden nodes and hyperbolic tangent and identity activation functions. Different weight scenarios for the objective function of the optimization model were adopted. The results indicate that different optimum dam locations can be observed for each case. Results indicate also that sometimes equal objective can be obtained but each has different reservoir volume and surface area.
The statistical distributions study aimed to obtain on best descriptions of variable sets phenomena, which each of them got one behavior of that distributions . The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods like greatest ability, minimum squares method and Mixing method (suggested method).
The research
... Show MorePhase change materials (PCMs) such as paraffin wax can be used to store or release large amount of energy at certain temperature at which their solid-liquid phase changes occurs. Paraffin wax that used in latent heat thermal energy storage (LHTES) has low thermal conductivity. In this study, the thermal conductivity of paraffin wax has been enhanced by adding different mass concentration (1wt.%, 3wt.%, 5wt.%) of (TiO2) nano-particles with about (10nm) diameter. It is found that the phase change temperature varies with adding (TiO2) nanoparticles in to the paraffin wax. The thermal conductivity of the composites is found to decrease with increasing temperature. The increase in thermal conductivity ha
... Show MoreThis study suggests using the recycled plastic waste to prepare the polymer matrix composite (PMCs) to use in different applications. Composite materials were prepared by mixing the polyester resin (UP) with plastic waste, two types of plastic waste were used in this work included polyethylene-terephthalate (PET) and Polyvinyl chloride (PVC) with varies weight fractions (0, 5, 10, 15, 20 and 25 %) added as a filler in flakes form. Charpy impact test was performed on the prepared samples to calculate the values of impact strength (I.S). Flexural and hardness tests were carried out to calculate the values of flexural strength and hardness. Acoustic insulation and optical microscope tests were carried out. In general, it is found that UP/PV
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
In the current study, two sites were selected from the city of Adhamiya, central Baghdad. The first site is the Adhamiya Corniche, which includes a sample of river water and the second includes domestic sewage in the same area. The total density of benthic invertebrates was 775 ind/m2, which is divided into 15 taxa. Biological indices were found, such as the stability index, the abundance index, the biodiversity index (Shannon’s index), the homogeneity index, and the invader’s guide. The result showed an increase in the density of benthic invertebrates, as well as an increase in the diversity of these organisms.
This study aims to evaluate drinking water quality at the Al Wahda plant (WTP) in Baghdad city. A conventional water treatment plant with an average flow rate of 72.82 MLD. Water samples were taken from the influent and effluent of the treatment plant and analyzed for some physicochemical and biological parameters during the period from June to November 2020. The results of the evaluation indicate that treated water has almost the same characteristics as raw water; in other terms, the plant units do not remove pollutants as efficiently as intended. Based on this, the station appears to be nothing more than a series of water passage units. However, apart from Total dissolved solids, the mean values of all parameters in th
... Show MoreThe primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed
... Show MoreThe Hopfield network is one of the easiest types, and its architecture is such that each neuron in the network connects to the other, thus called a fully connected neural network. In addition, this type is considered auto-associative memory, because the network returns the pattern immediately upon recognition, this network has many limitations, including memory capacity, discrepancy, orthogonally between patterns, weight symmetry, and local minimum. This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of t
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