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bsj-3862
Real-Time Cloth Simulation on Virtual Human Character Using Enhanced Position Based Dynamic Framework Technique
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     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision with moving capsules is implemented to achieve realistic behavior cloth modelled on animated characters. This is to enable comparable incompressibility and convergence to raised cosine deformation (RCD) function solvers. On implementation, this research achieves optimized collision between clothes, syncing of the animation with the cloth simulation and setting the properties of the cloth to get the best results possible. Therefore, a real-time cloth simulation, with believable output, on animated VHC is achieved. This research perceives our proposed method can serve as a completion to the game assets clothing pipeline.

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Nonparametric Regression Function Using Canonical Kernel
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    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Assets Valuation Approaches & its Reflects on Financial Reporting Quality
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Abstract

   The model of financial reporting in  Iraq  Based on a specific set of accounting objectives & concepts, which require the application of the historical cost valuation approach due to the nature of the objectives of financial reporting in Iraq, established under the unified accounting system , which focuses on serving the needs of the state because it the most influential user in setting accounting objectives and concepts, which stems mainly from the nature of the economic system in Iraq, which focuses on the public sector versus the private sector as well as the nature of the ownership business that focuses on partnership versus corpor

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the continuity of the demand for money and its impact on the Iraqi dinar exchange rate for the period 1991-2013 function
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 Research Summary

It highlights the importance of assessing the demand for money function in Iraq through the understanding of the relationship between him and affecting the variables by searching the stability of this function and the extent of their influence in the Iraqi dinar exchange rate in order to know the amount of their contribution to the monetary policies of the Iraqi economy fee, as well as through study behavior of the demand for money function in Iraq and analyze the determinants of the demand for money for the period 1991-2013 and the impact of these determinants in the demand for money in Iraq.

And that the problem that we face is how to estimate the total demand for money in

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Effect Ti/AlTiN Multilayer Coating on the Crater Wear Process of Cutting Tool and Tribological Properties
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Tool wear is a major problem in machining operations because the resulting material loss gradually changes of the machine tool. There many factors may leads to material loss like; friction, corrosion, and also it’s happened by rubbing during machining processes between the work piece and the tool. Dimensional accuracy of the work piece, and also the surface finish will be reducing by tool wear. It can also increase cutting force. In this study, we focused on the effect of the coating process on crater wear problems. Crater wear is caused by the flow between the chip and the rake face of the tool, whereas flank wear is caused by the contact between the tool and the work piece. In reducing crater wear, aluminum titanium nitride (AlTiN) u

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Publication Date
Thu May 05 2016
Journal Name
Global Journal Of Engineering Science And Researches
EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
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The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

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Publication Date
Mon Jul 01 2013
Journal Name
Http://www.i-csrs.org/volumes/gisars/vol.3/vol.3.1.1.july.12.pdf
Remote sensing technique to monitoring the risk of soil degradation using NDVI
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In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

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Publication Date
Sun Dec 22 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Solubility and Dissolution Enhancement of Atorvastatin Calcium using Solid Dispersion Adsorbate Technique
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            Atorvastatin (ATR) is poorly soluble anti-hyperlipidemic drug; it belongs to the class II group according to the biopharmaceutical classification system (BCS) with low bioavailability due to its low solubility. Solid dispersions adsorbate is an effective technique for enhancing the solubility and dissolution of poorly soluble drugs.

          The present study aims to enhance the solubility and dissolution rate of ATR using solid dispersion adsorption technique in comparison with ordinary solid dispersion. polyethylene glycol 4000 (PEG 4000), polyethylene glycol 6000 (PEG 6000), Poloxamer188 and Poloxam

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of-Copper Ions-from Aqueous Solution Using Liquid-Surfactant-Membrane Technique
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Extraction of copper (Cu) from aqueous solution utilizing Liquid Membrane technology (LM) is more effective than precipitation method that forms sludge and must be disposed of in landfills. In this work, we have formulated a liquid surfactant membrane (LSM) that uses kerosene oil as the main diluent of LSM to remove copper ions from the aqueous waste solution through di- (2-ethylhexyl) phosphoric acid - D2EHPA- as a carrier. This technique displays several advantages including one-stage extraction and stripping process, simple operation, low energy requirement, and. In this study, the LSM process was used to transport Cu (II) ions from the feed phase to the stripping phase, which was prepared, using H2SO4. For LSM p

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Strengthening of Reinforced Concrete T- Section Beams Using External Post-Tensioning Technique
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This research is carried out to investigate the externally post-tensioning technique for strengthening RC beams. In this research, four T-section  RC beams having the same dimensions and material properties were casted and tested up to failure by applying two mid-third concentrated loads. Three of these beams are strengthened by using external tendons, while the remaining beam is kept without strengthening as a control beam. Two external strands of 12 mm diameter were fixed at each side of the web of the strengthened beams and located at depth of 200 mm from top fiber of the section (dps). So that the depth of strands to overall depth of the section ratio (dps

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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