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Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this research, need confirm the results of the preliminary study but also going forward in understanding the processes involved in these experiments. Two tracks are followed, first will concern with the development of classifiers based on statistical data already provided by the system "eye tracking", second will be more focused on finding new descriptors from the eye trajectories. In this paper, study used K-mean with Vector Measure Constructor Method (VMCM). In addition, briefly reflect used other method support vector machine (SVM) technique. The methods are playing important role to classify the people with and without autism specter disorder. The research paper is comparative study between these two methods.

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Publication Date
Sat Oct 29 2022
Journal Name
Current Trends In Geotechnical Engineering And Construction (pp.52-61)
Simulation of Residual Chlorine in Al-Yarmouk Drinking Water System Using WaterGEMS
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Abstract To ensure that the distribution system has safe drinking water. It is necessary to know the residual chlorine concentrations at various points in the network. A chlorine photometer device was used to measure twenty points taken every day for a week at a selected time in the distribution system. Both pressures and flows in the network were measured using bourdon gauge and Tuf-2000H Handheld Digital ultrasonic flow meters. WaterGEMS CONNECT Edition update one software was used to simulate the flow in the network. The Baghdad water department provided the data about the network, such as the lengths of pipes, the layout of the network, and pipes diameters. The network calibrated consists of 781 pipes of different lengths and 542 juncti

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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Phylogenetic Relationship of Iraqi Vespa orientalis Linnaeus 1771 Wasps Using Mitochondrial CO1
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Abstract<p>Oriental wasps are scavengers, and they have also represented an enormous issue for beekeepers, they destroy beehives and reduce the flight of bees. In addition, the sting of hornets may cause medical problems, which differ according to the response of the individuals, including severe sensitivity, swelling, and slight pain. This study provides the first molecular phylogeny of the oriental wasp <italic>Vespa orientalis</italic> L. in Iraq. Mitochondrial DNAs of the 547bp fragment cytochrome oxidase subunit 1 (CO1) area were sequenced and analyzed from 10 wasp specimens collected in the north, middle, and south of Iraq. The CO1 gene found in the Iraqi isolates was used to cre</p> ... Show More
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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
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Spatial Distribution of Heavy Element in Erbil's Municipal Landfills by Using GIS
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Untreated municipal solid waste (MSW) release onto land is prevalent in developing countries. To reduce the high levels of harmful components in polluted soils, a proper evaluation of heavy metal concentrations in Erbil's Kani Qrzhala dump between August 2021 and February 2022 is required. The purpose of this research was to examine the impact of improper solid waste disposal on soil properties within a landfill by assessing the risks of contamination for eight heavy elements in two separate layers of the soil by using geoaccumulation index (I-geo) and pollution load index (PLI) supported. The ArcGIS software was employed to map the spatial distribution of heavy element pollution and potential ecological risks. The I-geo values in summe

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Wed Jan 01 2014
Journal Name
Our Dermatology Online
Treatment of active acne vulgaris by chemical peeling using 88% lactic acid
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KE Sharquie, AA Noaimi, EA Al-Janabi, Our Dermatology Online, 2014 - Cited by 11

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Publication Date
Mon Oct 03 2016
Journal Name
Applied Research Journal
DETERMINATION OF THE GEOID HEIGHT (GEOID UNDULATION) BY USING MODERN SURVEYING TECHNOLOGIES
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In this work, a large part of Baghdad University campus has been selected. The determination of Geoidal height for the local area requires Ground Control Points which both Ellipsoidal and Orthometric heights are known to compute the difference between them. The first step of the leveling process began by selected the Ground Control Points (GCPs) around the area of the work, and then divided them into two groups of the network traverse stations. They were leveled and adjusted depend on the number of the Bench Marks (B.M.s). Total Station TS (Nikon Nivo 5C) and Global Positioning System (GPS-Garmin 78 map) are used to do this application. The aim of the proposed work was to determine the height of the Geoid surface in the study area. The Geoi

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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
In Vitro Regeneration of Pimpinella anisum L. Using Different Plant Growth Regulators
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Plant regeneration protocols were developed for medicinally important anise (Pimpinella anisum L.) that successfully achieved from seeds. Seeds were sterilized and inoculated on Murashige and Skoog (MS) medium with and without gibberellins (GA3) until full germination. The highest percentage of germination (100%) was recorded on MS medium treated with 2.0 mg/L GA3 after 7 days. For shoot proliferation, different concentrations of 6- benzyl adenine BA (1, 1.5, 2 mg/L) were used. To enhance shoot induction, 0.1 mg/L of naphthalene acetic acid (NAA) and 0.01 mg/L of thidiazuron (TDZ) were tested along with BA. Direct regenerated shoots were obtained on MS medium supplemented with BA alone (2mg/L) which gave (7shoot/explant), while the presence

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Wed Jan 01 2020
Journal Name
Aip Conference Proceedings
Corrosion behavior of mild-steel in cooling towers using high salinity solution
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Cooling towers is one of the most important unit in industry, they are used to dispose heat from cooling media used in the integrated units. The choice of the cooling media plays recently an important rule due to fresh-water scarcity. The use of saline as a cooling media become of growing interest, but the corrosion problem has to be taken in consideration. In this study the simultaneous effect of cooling tower operation parameters on the corrosion rate of mild-steel is considered. The role of NaCl content is found to be pronounced more than the working solution temperature and flowrate. The corrosion of mild-steel in these studied factors had shown an interesting result especially with the NaCl% content. Firstly, there was an increase in t

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