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An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Thu Mar 24 2022
Journal Name
Arab World English Journal
Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study
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This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

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Publication Date
Fri Mar 01 2019
Journal Name
Iraqi Journal Of Physics
The dispersion in spherical statistical optical potential (SOM) from the interaction of fast neutrons with197Au nucle
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A statistical optical potential has been used to analyze and
evaluate the neutron interaction with heavy nuclei 197Au at the
neutron energy range (1-20 MeV). Empirical formulae of the optical
potentials parameters are predicted by using ABAREX Code with
minimize accuracy compared with experimental bench work data.
The total elastic, absorption, shape elastic and total compound crosssections are calculated for different target nuclei and different
incident neutron energies to predict the appropriate optical
parameters that suit the present interaction. Also the dispersion
relation linking between real and imaginary potential is analyzed
with more accuracy. The results indicate the behavior of the
dispersion c

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Publication Date
Sat Dec 28 2019
Journal Name
International Journal Of Environmental Research And Public Health
Predominant Mechanisms in the Treatment of Wastewater Due to Interaction of Benzaldehyde and Iron Slag Byproduct
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Iron slag is a byproduct generated in huge quantities from recycled remnants of iron and steel factories; therefore, the possibility of using this waste in the removal of benzaldehyde from contaminated water offers an excellent topic in sustainability field. Results reveal that the removal efficiency was equal to 85% for the interaction of slag and water contaminated with benzaldehyde at the best operational conditions of 0.3 g/100 mL, 6, 180 min, and 250 rpm for the sorbent dosage, initial pH, agitation time, and speed, respectively with 300 mg/L initial concentration. The maximum uptake capacity of iron slag was 118.25 mg/g which was calculated by the Langmuir model. Physical sorption may be the major mechanism for the removal of

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparing traditional estimators and the estimators of (PSO) algorithm for some growth models of gross domestic product in Iraq
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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Computer Science
Dropping down the Maximum Item Set: Improving the Stylometric Authorship Attribution Algorithm in the Text Mining for Authorship Investigation
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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Building the optimal portfolio for stock using multi-objective genetic algorithm - comparative analytical research in the Iraqi stock market
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Abstract:

The main objective of the research is to build an optimal investment portfolio of stocks’ listed at the Iraqi Stock Exchange after employing the multi-objective genetic algorithm within the period of time between 1/1/2006 and 1/6/2018 in the light of closing prices (43) companies after the completion of their data and met the conditions of the inspection, as the literature review has supported the diagnosis of the knowledge gap and the identification of deficiencies in the level of experimentation was the current direction of research was to reflect the aspects of the unseen and untreated by other researchers in particular, the missing data and non-reversed pieces the reality of trading at the level of compani

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Sun Dec 29 2024
Journal Name
Plant Protection
Efficacy of silver nanoparticles from Fusarium solani and mycorrhizal inoculation for biological control of Fusarium wilt in tomato
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The present study investigates the characterization of silver nanoparticles (AgNPs) synthesized using Fusarium solani and their impact on tomato seed germination, plant growth, and disease resistance. A visible color change from yellow to dark smoky indicated the formation of AgNPs, while UV-visible spectrophotometry revealed an absorbance peak at 437 nm, confirming their presence. Atomic force microscopy analysis showed that the AgNPs ranged from 0 to 39.27 nm in size, with an average height of 5.772 nm, while scanning electron microscopy highlighted their diverse surface morphology. The application of AgNPs and mycorrhizal fungi significantly improved tomato seed germination rates, plant height, and dry weight compared to untreate

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
SUBSTITUTION OF ANIMAL PROTEIN BY DIFFERENT ATION OF DRIED RUMEN MEAL IN COMMON CARP Cyprinus carpio DIETS: SUBSTITUTION OF ANIMAL PROTEIN BY DIFFERENT ATION OF DRIED RUMEN MEAL IN COMMON CARP Cyprinus carpio DIETS
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The study was conducted to show the effect of using dried rumen powder as a source of animal protein in the diets of common carp (Cyprinus carpio L.) on its performance, in the fish laboratory/College of Agricultural Engineering Sciences/University of Baghdad/ for a period of 70 d, 70 fingerlings were used with an average starting weight of 30±3 g, with a live mass rate of 202±2 g, randomly distributed among five treatments, two replicates for each treatment and seven fish for each replicate. Five diets of almost identical protein content and different percentages of addition of dried rumen powder were added. 25% was added to treatment T2 and 50% to treatment T3 and 75% of the treatment T4 and 100% of the treatment T5

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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