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Use sensitivity analysis in evaluating projects Investment under the conditions of risk and uncertainty Case study of glass bottles project in Anbar province
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This paper studies the investment project evaluation under the condition of uncertainty. Evaluation of investment project under risk and uncertainty is possible to be carried out through application of various methods and techniques. The best known methods are : Risk-adjusted discount rate , certainty equivalent method , Sensitivity analysis and Simulation method The objective of this study is using the sensitivity analysis in evaluation Glass Bottles project  in Anbar province under the condition of risk and uncertainty.

After applying sensitivity analysis we found that the glass bottles project  sensitive to the following factors (cash flow, the cost of investment, and the productive age), which requires attention to these factors, especially cash flow and cost of investment. If cost of investment has increased by more than 41% project has negative  present value, also if the cash flow dropped by more than 31% the project  will achieve a  negative present value .

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Publication Date
Thu Oct 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Design of an adaptive state feedback controller for a magnetic levitation system
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This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Synthesis of Functionalized Silica from Rice Husks Containing C-I End Group
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In this paper, we have extracted Silica from rice husk ash (RHA) by sodium hydroxide to produce sodium silicate. 3-(chloropropyl)triethoxysilane (CPTES) functionalized with sodium silicate via a sol-gel method in one pot synthesis to prepare RHACCl. Chloro group in compound RHACCl replacement in iodo group to prepere RHACI. The FT-IR clearly showed absorption band of C-I at 580 cm-1. Functionalized silica RHACI has high surface area (410 m2/g) and average pore diameter (3.8 nm) within mesoporous range. X-ray diffraction pattern showed that functionalized silica RHACI has amorphous phase .Thermogravemitric analysis (TGA) showed two decomposition stages and SEM morphology of RHACI showed that the particles have irregu

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Fri Jun 30 2017
Journal Name
Acta Crystallographica Section E Crystallographic Communications
Crystal structure of (<i>E</i>)-4-benzylidene-6-phenyl-1,2,3,4,7,8,9,10-octahydrophenanthridine
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The preparation of the title compound, C26H25N, was achieved by the condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 molar ratio. There are two crystallographically independent molecules in the asymmetric unit. The two cyclohexyl rings adopt ananti-envelope conformation with the benzyl moiety adopting acisconformation with respect to the nitrogen atom of the phenanthridine segment. In the crystal, molecules are linked through C—H...N interactions into hydrogen-bonded chains that are further arranged into distinct layers by weak offset π–π interactions.

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Publication Date
Thu Mar 01 2018
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
Information model of plastic products formation process duration by injection molding method
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Publication Date
Thu Mar 01 2018
Journal Name
2018 Tenth International Conference On Advanced Computational Intelligence (icaci)
On low-level control strategies of lower extremity exoskeletons with power augmentation
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

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Publication Date
Thu Nov 29 2018
Journal Name
Journal Of Electronic Materials
Numerical Modeling of 193-nm Excimer Laser Ablation on CR-39 Polymer
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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Biological Activity of Levan Produced from Rhizospheric Soil Bacterium Brachybacterium phenoliresistens KX139300
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Levan is an exopolysaccharide produced by various microorganisms and has a variety of applications. In this research, the aim was to demonstrate the biological activity of levan which produced from B. phenoliresistens KX139300. These were done via study the antioxidant, anti-inflammatory, anticancer and antileishmanial activities in vitro. The antioxidant levan was shown 80.9% activity at 1250 µg/mL concentration. The efficient anti-inflammatory activity of 88% protein inhibition was noticed with levan concentration at 35 µg/mL. The cytotoxic activity of levan at 2500 µg/mL concentration showed a maximum cytotoxic effect on L20B cell line and promastigotes of Leishmani tropica. Levan has dose-dependent anticancer and antileishmanial acti

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