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Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Sun Jun 01 2014
Journal Name
Ibn Al-haitham Jour. For Pure & Appl. Sci.
Reducing False Notification in Identifying Malicious Application Programming Interface(API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Sat Mar 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Theoretical Study on Heat Transfer in the Presence of Fouling
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The fouling depositions of crude oil stream were studied theoretically in a shell and tube heat exchanger to investigate the effect of depositions on the heat transfer process. The employed heat exchanger was with steam flowing in the inner tubes and crude oil in the shell at different velocities and bulk temperatures. It is assumed that fouling occurs only on the heated stream side (crude oil). The analysis was carried out for turbulent flow heat transfer conditions with wide range of Reynolds number, bulk temperature and time. Many previously proposed models for fouling resistance were employed to estimate a new model for fouling rate. It is found that the fouling rate and consequently the heat transfer coefficient were affected by Rey

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Publication Date
Tue Jun 12 2018
Journal Name
Indian Journal Of Natural Sciences
Effect of Pomegranate Seed Oil on Glycemic Index in Diabetic Rabbits
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This study aimed to investigate the effect of oral administration of pomegranate seed oil on diabetic in male rabbits. A total of 32 adult male rabbits.6 months old weighting 1-2kg were divided in to four equal groups. G- Control (negative) Rabbits were received olive oil, G2- (control positive) Rabbits were received (30 mg/kg B.W/daily of the Pomegranate seed oil orally and daily for 45 day. G3-Rabbits were received (150mg/kg of Alloxan injected Intraperitonealy, G4-Rabbits were received the same dose orally of the Pomegranate seed oil four 45 days. There is significant increase (Insulin, Insulin resistance) and decreased glucose in group received Pomegranate seed oil (G4) as compared with G3 (diabetic group). On conclusion, the administra

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Computational Optimization of the Radial and Spiral Distortion Aberration Coefficients of Magnetic Deflector
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Abstract:The optimum design of the magnetic deflector with the lowest values of the radial and spiral distortion aberration coefficients was computed. The optimized calculations were made using three models, Glaser bell-shaped, Grivet-lenz and exponential models. By using the optimum axial field distribution, the pole pieces shape which gave rise to those field distributions was found by using the reconstruction method. The calculations show that the results of the three models coincide at the lower values of the excitation parameter. In general the Glaser- bell shaped model gives the optimum results at the whole range of the excitation parameter under investigation.The negative values of the spiral distortion aberration coefficient appears

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Publication Date
Mon Jan 01 2007
Journal Name
2007 Ieee International Conference On Signal Processing And Communications
Fast Multi-level Image Vector Quantization
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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
A Semi-Empirical Equation based on the Strut-and-Tie Model for the Shear Strength Prediction of Deep Beams with Multiple Large Web Openings
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

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Publication Date
Sun Oct 01 2017
Journal Name
Applied Energy
Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
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Publication Date
Tue Jun 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Neural Network in the Identification of the Cumulative Production from AB unit in Main pays Reservoir of South Rumaila Oil Field.
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A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

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Publication Date
Mon Dec 03 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Window Size Changing on Satellite Image Segmentation Using 2D Fast Otsu Method
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