The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
Simulation of the Linguistic Fuzzy Trust Model (LFTM) over oscillating Wireless Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network
... Show MoreLung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreFinancial markets play an important role in the economy, as it contributes to the financial and economic system of the state stability, as it reduces the adoption of the companies on the loans granted by the banks, as financial markets contribute to attracting and channeling savings to small savers who will be able to buy a number of shares proportional to their savings, It also provides them the place of exchange, and play technology and information systems an important role in facilitating exchanges and increased market activity, in this research touched on the importance of information technology in effect on the activity of the financial markets. Research is divided into three demands of the first concept of eating and the importance
... Show MoreIn this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
... Show MoreThe study aimed to survey mushroom species from fields among herbs, palm trunks, and trees in central Iraq and to identify them on the basis of morphological and molecular characteristics. As a molecular identification result with polymerase chain reaction six species were recorded (with eight isolates): Agaricus bitorquis (Quéllt) Saccardo. 1887 (SHA14); Candolleomyces candolleanus (Fr.) D. Wächter & Melzer, 2020 (SHA15); Cyclocybe cylindracea (D.C.) Vizzini & Angelini, 2014 (SHA13); Leucoagaricus hesperius Vellinga, 2010 (SHA16); Volvariella sp. (SHA17), and Volvopluteus gloiocephalus (D. C.) Vizzini, Contu & Justo, 2011 (SHA10, SHA101 and SHA12), belonging to four families of Basidiomycetes: Agaricaceae, Pluteaceae,
... Show MoreThe process of composting which involves the treatment of organic wastes to obtain a stable clean product, has become an increasingly desirable choice, at any scale from home to large waste treatment plants. Composting serves as an alternative to landfilling for managing biodegradable waste while also increasing or preserving soil organic matter, decreasing solid waste, and reducing disposal costs. The compost product improves the condition of the soil, reduces erosion, and helps reduce plant diseases without having adverse impacts on the environment. This study aims to manufacture high-quality compost as a solid waste management method by converting organic waste into a useful resource for the community in a financially and ecologi
... Show MoreThis study shows how the structural and dielectric properties of (SnO2)1-x(Mn2O3)x, (where x=0.00, 0.03, 0.05,0.07, and 0.09) prepared using the solid state reaction technique, are affected by the doping of semiconducting metal oxide Mn2O3. Structural analysis of the composites was carried out using information from the composite samples obtained from X-ray diffraction (XRD). The diffraction peak shifting in XRD patterns indicated that Mn ions were successfully incorporated into the SnO2 crystal lattice. Mn ions were successfully doped in the Tin oxide matrix lattice with the subsequent increase of doping levels. The average crystal size evaluated using Scherrer's equation was found to vary from 33 to 37 nm, and the lattice constant
... Show MoreBumpiness in the atmosphere is the vertical movement of air, whether
upward or downward movement and the bumpiness is accompanied by areas
of unrest in the air and wind. And contribute to each of the coups thermal
fronts, wind, wind and thunderstorms. Moreover, bumpiness is net of the
reasons that lead to circumstances is appropriate to cut the wind, and this
contributes to the formation of bumpiness in the atmosphere. The study found
that the noon of the times, which is expected to occur where clear-air
bumpiness during flights because of the warmth of the earth's surface. The
study found increased incidence of air hole during the summer, especially
July, due to increased incidence of coup surface, while the s
Background: Gasoline constituents and its derivatives had many hazardous effects on the general health of humans. Thus, gasoline stations workers may be affected by different types of related diseases.This study was conducted to assess selected salivary elements and their relation with dental caries, oral hygiene status and periodontal diseases among gasoline stations workers in comparison with individuals have no regular exposure to gasoline. Materials and methods: The study group consists of thirty male subjects with an age range (33-39) years who worked in different gasoline stations in different areas of Baghdad city and thirty persons that matching in age and gender and not exposed to gasoline were selected as a control group. Dental c
... Show More