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Synthesized pure cobalt oxide nanostructure and doped with yttrium by hydrothermal method for photodetector applications
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In this study, pure Co3O4 nano structure and doping with 4 %, and
6 % of Yttrium is successfully synthesized by hydrothermal method.
The XRD examination, optical, electrical and photo sensing
properties have been studied for pure and doped Co3O4 thin films.
The X-ray diffraction (XRD) analysis shows that all films are
polycrystalline in nature, having cubic structure.
The optical properties indication that the optical energy gap follows
allowed direct electronic transition calculated using Tauc equation
and it increases for doped Co3O4. The photo sensing properties of
thin films are studied as a function of time at different wavelengths to
find the sensitivity for these lights.
High photo sensitivity doped Co3O4 with 6% of Yttrium, is a
118.774% at wavelength 620 nm, while for pure Co3O4 films no
sensitivity at the same wavelength. So, higher sensitivity is found for
doping Co3O4 with fast rise and fall times less than 1s.

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Publication Date
Thu Dec 01 2011
Journal Name
Swarm And Evolutionary Computation
Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
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Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

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Publication Date
Thu Jan 01 2015
Journal Name
Aip Conference Proceedings
Numerical solution for weight reduction model due to health campaigns in Spain
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This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time t . The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method t

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Fabrication of Electrospun Nanofibers Membrane for Emulsified Oil Removal from Oily Wastewater
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The electrospun nanofibers membranes have gained considerable interest in water filtration applications. In this work, the fabrication and characterization of the electrospun polyacrylonitrile-based nonwoven nanofibers membrane are reported. Then, the membrane's performance and antifouling properties were evaluated in removing emulsified oil using a cross flow filtration system. The membranes were fabricated with different polyacrylonitrile (PAN) concentrations (8, 11, and 14 wt. %) in N, N-Dimethylformamide (DMF) solvent resulted in various average fiber sizes, porosity, contact angle, permeability, oil rejection, and antifouling properties. Analyses of surface morphology of the fabricated membranes before and after oil removal revealed

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Publication Date
Sun Nov 14 2021
Journal Name
2021 North American Power Symposium (naps)
Laplace Domain Modeling of Power Components for Transient Converter-Grid Interaction Studies
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This paper introduces a Laplace-based modeling approach for the study of transient converter-grid interactions. The proposed approach is based on the development of two-port admittance models of converters and other components, combined with the use of numerical Laplace transforms. The application of a frequency domain method is aimed at the accurate and straightforward computation of transient system responses while preserving the wideband frequency characteristics of power components, such as those due to the use of high frequency semiconductive switches, electromagnetic interaction between inductive and capacitive components, as well as wave propagation and frequency dependence in transmission systems.

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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
The Nuclear Structure for Exotic Neutron-Rich of 42, 43, 45,47K Nuclei
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In this paper the proton, neutron and matter density distributions and the corresponding root mean square (rms) radii of the ground states and the elastic magnetic electron scattering form factors and the magnetic dipole moments have been calculated for exotic nucleus of potassium isotopes K (A= 42, 43, 45, 47) based on the shell model using effective W0 interaction. The single-particle wave functions of harmonic-oscillator (HO) potential are used with the oscillator parameters b. According to this interaction, the valence nucleons are asummed to move in the d3f7 model space. The elastic magnetic electron scattering of the exotic nuclei 42K (J?T= 2- 2), 43K(J?T=3/2+ 5/2), 45K (J?T= 3/2+ 7/2) and 47K (J?T= 1/2+ 9/2) investigated t

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Publication Date
Thu Oct 01 2020
Journal Name
Wireless Communications And Mobile Computing
Developing a real time navigation for the mobile robots at unknown environments
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<p><span>This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the

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Publication Date
Wed Jul 30 2025
Journal Name
Accounting And Financial Sciences Journal
The Analyze of the Available Strategic Choices for External Borrowing (Futuristic Vision)
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يهدف البحث الى تحليل الخيارات الاستراتيجية للاقتراض الخارجي في العراق لاستشراف افضل الخيارات الاستراتيجية المستقبلية في مجال الاقتراض الخارجي في دائرة الدين العام في وزارة المالية ، وقد استخدم الباحث منهج دراسة الحالة وباستعمال اسلوب تحليل خوارزمية ال K-Means لتشخيص كفاءة الاقتراض الخارجي لعينة البحث البالغة (81) قرضا التي اقترضتها وزارة المالية للفترة 2007-2020 . ولقد كان الغرض الرئيسي للبحث المساهمة في تمكين وزا

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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