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SENTIMENT RETRIEVAL OF HEALTH RECORDS USING NLP-BASED ALGORITHM
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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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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
Sun Jul 01 1990
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
KEY TO THE SPECIES OF THE GENUS STACHYS L. (LABIATAE) IN IRAQ WITH THREE NEW RECORDS
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A simplified parallel key was presented in this work for the Taxa of Stackys L. wildly grown in Iraq. Three records within this genus were newly recorded to our country in the present work and they are S. kermanshahansis Rech S. setifera C.A. Mey. subsp setifera, S. setifera ssp iranica (Reck.) The characteristics of these new records were also given with some representative specimens.

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of The Arkansas Academy Of Science
Geographic Distribution Records of Macracanthorhynchus ingens (Archiacanthocephala: Oligacanthorhynchidae) from the Raccoon, Procyon lotor in North America
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Publication Date
Sun Jan 05 2020
Journal Name
Annals Of Tropical Medicine And Public Health
[CITATION] Direct and deferred retrieval of basketball for student of the college of physical education and sport sciences
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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Thu Aug 01 2019
Journal Name
مجلة العلوم الاقتصادية والإدارية
Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application
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Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application

Publication Date
Sat Feb 11 2023
Journal Name
Applied Sciences
A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

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Publication Date
Sat Jul 01 2000
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
RECORDS OF HOST PLANTS OF PEA LEAF MINER, P1-f YTOMYZA HORTICOLA GOUREAU (DIPTERA: AGROMYZIDE) IN IRAQ
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It was found that Pkvtomyza horticola Goureau infested 36 plants belonging to 11 families of
dicotyledons. only two of which belong to Monocotyledons. Most of plants species are from
compositae and Cruciferae families.

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