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Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique
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The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlation equal to 0.99798. The sensitivity analysis for outputs of ANN signified that the relative importance of initial pH equal to 38 % and it is the influential parameter in the treatment process, followed by initial concentration, agitation speed, biosorbent dosage, time and temperature

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Indoor risk assessment of radon gas in the science college buildings-University of Mustansiriyah using RAD-7 detector
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In the present work, a set of indoor Radon concentration measurements was carried out in a number of rooms and buildings of Science College in the University of Mustansiriyah for the first time in Iraq using RAD-7 detector which is an active method for short time measuring compared with the passive method in solid state nuclear track detectors (SSNTD's). The results show that, the Radon concentrations values vary from 9.85±1.7 Bq.m-3 to 94.21±34.7 Bq.m-3 with an average value 53.64±26 Bq.m-3 which is lower than the recommended action level 200-300 Bq/m3 [ICRP, 2009].
The values of the annual effective dose (A.E.D) vary from 0.25 mSv/y to 2.38 mSv/y, with an average value 1.46±0.67 mSv/y which is lower than the recommended the rang

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Evaluation of Low Level Laser Therapy using 785 nm Diode Laser on the Enhancement of Chronic Wound Healing
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Low-intensity laser irradiation has been explored as an alternative, non-invasive method to encourage chronic wounds to heal. This study aimed to evaluate the effects of low level laser therapy (biostimulation) using semiconductor diode laser with wavelength (785 nm) on the enhancement of chronic wound healing. Fifty patients with chronic wounds were selected to be treated with Low Level Laser Therapy. Their ages ranged between 1 to 76 years. The wound sites were distributed in the lower limb, upper limb, trunk , perineum and head (70%,14%,12%,2%,2%, respectively). Application of laser therapy by noncontact method few millimeters from the skin for 15 minutes per one session twice weekly for two months ; ie,16 sessions for each patient. R

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Publication Date
Fri Dec 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Comparing the effectiveness of using three different re-mineralizing pastes on remineralisation of artificially induced white spot lesion
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Background: This study aimed to compare the surface microhardness (MH) and mineral content of white spot lesions(WSLs) after using bioactive glass (BAG)casein phosphopep-tides-amorphous calcium phosphate(CPP-ACP),and nanohydroxyapatite(Nano-HAP) under pHcycling. Material and method:18 sound maxillary first premolar were used for the study.10 were selected for the vickers microhardness test, For Energy-dispersive X-ray spectroscopy analysis (EDX), the remaining 8 premolar teeth were used, 40 sections of enamel blocks (Four from each tooth) were produced from the middle part of the buccal and palatal surfaces of teeth for MH test while 48 sections of enamel blocks (Six from each tooth) were produced for EDX analysis. Enamel slabs were

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Publication Date
Sat Dec 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Comparative evaluation of the radiographic density of GuttaFlow® 2 in different obturation techniques using Spiral Computed Tomography
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Background: Ideal root canal obturation depends on many factors; one of them is good sealing of root canal without pores. The aim of this study was to determine the radiographic density of GuttaFlow® 2 with different obturation techniques using spiral computed tomography. Materials and Methods: Forty palatal roots of permanent maxillary first molar were used in this study. Following working length determination, root canal was prepared using rotary PROTAPER universal system. They were randomly divided into four groups of 10 roots each, the groups are Conventional lateral condensation with Apexit Plus sealer, Conventional lateral condensation with GuttaFlow® 2 as a sealer, Soft Core Regular with GuttaFlow® 2 as a sealer and singl

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Publication Date
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Chaotic behaviour of the Rossler model and its analysis by using bifurcations of limit cycles and chaotic attractors
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The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Sun Dec 20 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Effect The behavior of workers in the insurance companies in achieving competitive advantage: An Applied research in a sample of the general insurance companies
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Service companies always working to increase their competitiveness and efficiency of the survival, growth and development in the present and the future, including insurance companies, so as to increase competition, especially after the emergence of the civil companies dramatically after 2003, has become the goal of recent studies carried out by the organizations is the human capital, because its success and excellence and achievement its objectives depends on the human, and this does not mean that the other components are not important, but also rely on the rights which has increased interest in the search for the way in which they can guide the behaviors and values ​​and their own language in line with the organization's strategy an

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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