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Classical and Statistical Optimization by Response Surface Methodology For Enhancing Biomass and Bacteriocin Production by Lactobacillus Plantarum
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Response surface methodology (RSM) based on central composite design was successfully applied to redesign MRS media for maximizing both biomass and bacteriocin production from Lactobacillus plantarum NH40. First, glucose and yeast extract were chosen as the best carbon and nitrogen sources based on classical optimization results of one factor at time which also revealed the possibility of eliminating peptone and meat extract from the original composition of medium without affecting the growth and bacteriocin production. Statistical experimental design based on a regression model generated using the Design expert 7 software showed that the optimum concentrations of glucose, yeast extract, tween80, NH4Cr, CH3COONa and K2PO4 were 40, 19.9, 1, 3.06, 7, 1.25 g/L respectively for maximum production of biomass (15.87 mg/mL) and bacteriocin (634.74 U/mL). In addition, from the analysis of variance, yeast extract with F-value 77.2 and glucose with 185.4 were the most effective factors on biomass and bacteriocin production. Formulation of empirical model explained that the interaction among factors showed that the determination coefficient R2 of biomass and bacteriocin production were 0.8777 and 0.8539 respectively. Furthermore, the accuracy of model of the optimized MRS medium suggested by design expert 7 for both biomass and bacteriocin was verified and results showed that concentrations of biomass and bacteriocin were 15 mg/mL and 640AU/mL respectively, which were approximately closed to predicted values.

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
An Evolutionary Algorithm for Task scheduling Problem in the Cloud-Fog environment
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Abstract<p>The rapid and enormous growth of the Internet of Things, as well as its widespread adoption, has resulted in the production of massive quantities of data that must be processed and sent to the cloud, but the delay in processing the data and the time it takes to send it to the cloud has resulted in the emergence of fog, a new generation of cloud in which the fog serves as an extension of cloud services at the edge of the network, reducing latency and traffic. The distribution of computational resources to minimize makespan and running costs is one of the disadvantages of fog computing. This paper provides a new approach for improving the task scheduling problem in a Cloud-Fog environme</p> ... Show More
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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
Wed Jan 01 2014
Journal Name
Siam Journal On Control And Optimization
A Duality Approach for Solving Control-Constrained Linear-Quadratic Optimal Control Problems
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Publication Date
Sun May 17 2020
Journal Name
Iraqi Journal Of Science
Types of Fixed Points of Set-Valued Contraction Mappings for Comparable Elements
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This paper is concerned with the study of the fixed points of set-valued contractions on ordered metric spaces. The first part of the paper deals with the existence of fixed points for these mappings where the contraction condition is assumed for comparable variables. A coupled fixed point theorem is also established in the second part.

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Publication Date
Fri Jan 01 2021
Journal Name
Agrosystems, Geosciences &amp; Environment
Cover crop influence on soil water dynamics for a corn–soybean rotation
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Abstract<p>Crop production is reduced by insufficient and/or excess soil water, which can significantly decrease plant growth and development. Therefore, conservation management practices such as cover crops (CCs) are used to optimize soil water dynamics, since CCs can conserve soil water. The objective of this study was to determine the effects of CCs on soil water dynamics on a corn (<italic>Zea mays</italic> L.)–soybean [<italic>Glycine max</italic> (L.) Merr.] rotation at three soil depths over 3 yr. The study was conducted at the Chariton County Cover Crop Soil Health Research and Demonstration Farm (CCSH) in Missouri. Initial CC establishment occurred in 2012. Volumetric soil water </p> ... Show More
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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
Elderly Healthcare System for Chronic Ailments using Machine Learning Techniques – a Review
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     World statistics declare that aging has direct correlations with more and more health problems with comorbid conditions. As healthcare communities evolve with a massive amount of data at a faster pace, it is essential to predict, assist, and prevent diseases at the right time, especially for elders. Similarly, many researchers have discussed that elders suffer extensively due to chronic health conditions.  This work was performed to review literature studies on prediction systems for various chronic illnesses of elderly people. Most of the reviewed papers proposed machine learning prediction models combined with, or without, other related intelligence techniques for chronic disease detection of elderly patie

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Publication Date
Tue Jan 01 2019
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees19gr
Theoretical study for the calculation of some attenuation parameters of polymeric composites
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Publication Date
Tue Feb 28 2023
Journal Name
International Journal Of Safety And Security Engineering
The Safer City: A New Planning Perspective for the Traditional City Development
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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Climatic Water Balance Comparison for Selected areas in The Middle of Iraq
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     The climate parameters annual rainfall and average mean temperature are investigated from 2000 to 2019 for Kut, Hilla and Iskandaryia. Evidence of climate change is noticed by decreasing the mean annual rainfall and relative humidity with an increase in the annual mean temperature. The climate water balance has been calculated. Due to high temperature, increased evaporation, and low precipitation rates, there was a large water deficit. The total water surplus in the Kut area is 32.86 mm from November to February, and in  Hilla and Iskandaryia is 20.4 and 27.8 mm from December to February, respectively. The climate classification for the three stations was semi-dry to dry climates. The region has a significant water deficit of u

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