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Drag Reduction Using Passive Methods on KIA PRIDE Car Model
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An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the average drag estimated on the baseline car for different Reynolds numbers was (0.381) and the drag force was reduced by adding a spoiler and a slice diffuser to (4.45%, 1.5%) respectively, whereas the amount of drag reduction was (5.46%) when all drag reduction modifications were added together on the base car. No effect was noticed as vortex generators when added separately. The deviation in the drag coefficient from the real car testing was about (6.2%) and shows a very good agreements between the real car test and that of the wind tunnel test.

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Usage of non-linear programming in building a mathematical model for production planning according to discount constraints put on bought amount
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Abstract

 This research deals will the declared production planning operation in the general company of planting oils, which have  great role in production operations management who had built mathematical model for correct non-linear programming according to discounting operation during raw materials or half-made materials purchasing operation which concentration of six main products by company but discount included just three products of raw materials, and there were six months taken from the 1st half of 2014 as a planning period has been chosen . Simulated annealing algorithm  application on non-linear model which been more difficulty than possible solution when imposed restric

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Renzulli Model on Achievement and Holistic Thinking among Fifth Grade Students in the Holy Quran and Islamic Education
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The present study aims at identifying the effect of Renzulli model on achievement and holistic thinking among the fifth grade students in the Holy Quran and Islamic Education. The experimental method with partial control was used, and the sample was chosen randomly. The sample consisted of (62) students distributed into experimental and control groups. 164 behavioral goals were formulated based on Bloom's first three levels taxonomy (knowledge and comprehension, application, analysis and installation, and evaluation). The researchers designed a post-test to measure the achievement of students in the subject of Holy Quran and Islamic Education which consisted of (40) objective items and a measure of holistic thinking which consisted of (3

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of Nonlinear PID Neural Controller for the Speed Control of a Permanent Magnet DC Motor Model based on Optimization Algorithm
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In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

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Publication Date
Mon May 19 2025
Journal Name
Retos
The effect of the cube model on visual-spatial intelligence and learning the skill of spiking in volleyball for female students
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Objective: To identify the effect of the cube model on visual-spatial intelligence and learning the skill of spikinging in volleyball for female students, The researchers used the experimental method by designing two equivalent groups with pre- and post-measurements. Research methodology: The main research sample of (30) female students was selected from the research community represented by second-stage students in the College of Physical Education and Sports Sciences - University of Baghdad for the academic year (2024-2025). The sample was divided equally into two control and experimental groups. The researchers conducted the sample homogenization process and the equivalence process between the two groups in the variables of visua

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Applied Science And Engineering
The effect of model scale, acceleration history, and soil condition on closed-ended pipe pile response under coupled static-dynamic loads
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This paper analyzes the effect of scaling-up model and acceleration history on seismic response of closed-ended pipe pile using a finite element modeling approach and the findings of 1 g shaking table tests of a pile embedded in dry and saturated soils. A number of scaling laws were used to create the numerical modeling according to the data obtained from 1 g shake table tests performed in the laboratory. The current study found that the behaviors of the scaled models, in general have similar trends. From numerical modeling on both the dry and saturated sands, the normalized lateral displacement, bending moment, and vertical displacement of piles with scale factors of 2 and 35 are less than those of the pile with a scale factor of 1 and the

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Scopus (18)
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Publication Date
Fri May 01 2026
Journal Name
Naunyn-schmiedeberg's Archives Of Pharmacology
Possible protective effects of tirzepatide on polycystic ovary syndrome in female rat model induced by testosterone propionate in comparison to metformin
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Polycystic ovary syndrome (PCOS) is a complex endocrine–metabolic disorder characterized by hyperandrogenism, ovulatory dysfunction, insulin resistance, and chronic inflammation resulting in reproductive and metabolic complications. Traditional metformin therapy improves insulin sensitivity, while newer dual incretin agonists, such as tirzepatide, may offer broader metabolic and ovarian protection. The objective of this study is to investigate whether tirzepatide could alter hormonal parameters, metabolism, inflammation, and histopathology of a testosterone propionate–induced PCOS rat model compared with metformin. Thirty prepubertal female Wistar rats were divided into five groups (n = 6). PCOS was induced by testosterone propionate (1

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Publication Date
Fri Mar 01 2024
Journal Name
Bahrain Medical Bulletin
Challenges Facing Nurses Toward Providing Care to Patients with Cerebrovascular Accidents: A Mixed Methods Study
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Background: Understanding the challenges facing nurses toward providing care to patients with cerebrovascular accidents is the initial step in developing strategies to address these challenges, thereby ensuring high-quality care. Aim: The study aimed to assess the challenges experienced by nurses in delivering care to patients with CVAs in neurological wards. Results: Of the 80 questionnaire participants in the qualitative part, (MS = 0.66) reported a "moderate" rating as an overall assessment. These challenges are divided into workload (MS = 0.53) at a moderate rate, the psychological burden (MS = 0.85) at a high rate, the supporting materials (MS = 0.85) at a high rate, the sense of responsibility (MS = 0.77) at a high rate, and the role

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Scopus
Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Indirect Flow Injection Spectrophotometric and Chromatographic Methods for the Determination of Mebendazole in Pharmaceutical Formulations
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Chromatographic and spectrophotometric methods for the estimation of mebendazole in
pharmaceutical products were developed. The flow injection method was based on the oxidation of
mebendazole by a known excess of sodium hypochlorite at pH=9.5. The excess sodium hypochlorite is then
reacted with chloranilic acid (CAA) to bleach out its color. The absorbance of the excess CAA was recorded
at 530 nm. The method is fast, simple, selective, and sensitive. The chromatographic method was carried out
on a Varian C18 column. The mobile phase was a mixture of acetonitrile (ACN), methanol (MeOH), water
and triethylamine (TEA), (56% ACN, 20% MeOH, 23.5% H2O, 0.5% TEA, v/v), adjusted to pH = 3.0 with
1.0 M hy

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Publication Date
Wed May 11 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods For A single Imputed A missing Observation In Estimating Nonparametric Regression Function
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In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

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