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.
Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a
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Cancer disease has a complicated pathophysiology and is one of the major causes of death and morbidity. Classical cancer therapies include chemotherapy, radiation therapy, and immunotherapy. A typical treatment is chemotherapy, which delivers cytotoxic medications to patients to suppress the uncontrolled growth of cancerous cells. Conventional oral medication has a number of drawbacks, including a lack of selectivity, cytotoxicity, and multi-drug resistance, all of which offer significant obstacles to effective cancer treatment. Multidrug resistance (MDR) remains a major challenge for effective cancer chemotherapeutic interventions. The advent of nanotechnology approach has developed the field of tumor diagnosis and treatment. Cancer nanote
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Background: The anterior knee pain is an important chief complaint of the patients with knee osteoarthritis due to patellofemoral pathology. The pain receptors denervation can be achieved by circumferential denervation of the patellar area by a process of electrocautery.
Objectives: The aim of current study is to assess the pain after total knee arthroplasty (TKA) by patelloplastywith and without circumferential denervation via electrocautery at a minimum follow up with 1 year separately for each patient.
Type of the study:Cross- sectional study.
Methods: Thirty five patients,with mean age of about (62.8) years, were enrolled in this pros
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In 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
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The Role of Japan in the Reconstruction of Iraq
Background: The goal of a root canal treatment is three dimensional obturation with a complete seal of the root canal system. The aim of this study was to evaluate and compare the effect of two warm obturation techniques, warm vertical compaction (WVC) and, carrier based obturation technique Gutta Core (GC), versus two cold obturation techniques, cold lateral compaction (CLC) and, single cone (SC) on push-out bond strength of bioceramic sealer (Total Fill) at three different root levels. Materials and Methods: Forty extracted maxillary first molars teeth with a straight round palatal root canal and mature apices were selected for this study. After sectioning the palatal roots to 11 mm from the root apex, the canals were prepared wit
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Background: The goal of a root canal treatment is three dimensional obturation with a complete seal of the root canal system. The aim of this study was to evaluate and compare the effect of two warm obturation techniques, warm vertical compaction (WVC) and, carrier based obturation technique Gutta Core (GC), versus two cold obturation techniques, cold lateral compaction (CLC) and, single cone (SC) on push-out bond strength of bioceramic sealer (Total Fill) at three different root levels. Materials and Methods: Forty extracted maxillary first molars teeth with a straight round palatal root canal and mature apices were selected for this study. After sectioning the palatal roots to 11 mm from the root apex, the canals were
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Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie
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Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.
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