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ijcpe-317
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
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The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemical finishing proves an effective method to reduce the surface roughness (Ra) from 1.6μm to 0.1μm in 4 min. Finally, the observed relationships were used to predicate the diameter of blank, tool diameter and flow rate by neural network modeling ANN which has inputs defined by the finished hole diameter, surface roughness, and finishing time. Three of hidden layers and their neurons were found by an integration procedure. The design charts observed from this study utilize the designers in predication of diameter for blank and design of electrode.

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Publication Date
Sun Feb 22 2026
Journal Name
Pakistan Journal Of Pharmaceutical Sciences
Optimization And Development Of Ondansetron HCl Nanocrystals By Using D-Optimal Design Expert® And In-Vitro Characterization
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Background: Over the last few years, nanocrystal technology has expanded to improve the bioavailability of poorly water-soluble drugs, which is challenging. Nanocrystals (NCs) exhibit many properties, such as enhancing drug solubility, dissolution, oral absorption, and high drug loading. Ondansetron hydrochloride (ONH) is an antiemetic drug that antagonizes a serotonin 5-HT3 receptor in the peripheral and central nervous system and is widely prescribed for the management of chemotherapy and radiotherapy-induced vomiting and nausea, as well as for postoperative nausea. ONH exhibits approximately 60% bioavailability due to its poor solubility and first-pass metabolism in the liver. Its solubility is pH-dependent, its precipitates abov

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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
River Water Salinity Impact on Drinking Water Treatment Plant Performance Using Artificial neural network
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The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
Modeling and optimum design band pass filter for mid IR region
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In this study, we design narrow band pass filter for window (3_5) ?m dependent on the needle optimization method , and a comparison with global designs published -Also, the effect of change parameter design on the optical performance of filter was studded and being able to overcome the difficulties of the design.In this study, the adoption of homogeneous optical properties materials as thin film depositing on a substrate of germanium at wavelength design (? = 4 ?m). For design this kind of filters we used advanced computer program (Matlab )to build a model design dependent both matrix characteristic and Needle technique. In this paper we refer to the type of Mert function , which is used for correct optical performance acces

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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
Indirect Method for Optimal Control Problem Using Boubaker Polynomial
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In this paper, a computational method for solving optimal problem is presented, using indirect method (spectral methodtechnique) which is based on Boubaker polynomial. By this method the state and the adjoint variables are approximated by Boubaker polynomial with unknown coefficients, thus an optimal control problem is transformed to algebraic equations which can be solved easily, and then the numerical value of the performance index is obtained. Also the operational matrices of differentiation and integration have been deduced for the same polynomial to help solving the problems easier. A numerical example was given to show the applicability and efficiency of the method. Some characteristics of this polynomial which can be used for solvin

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Thu Sep 28 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System
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The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Under that paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field. In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use les

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