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Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms
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Abstract<p>Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson correlation coefficient (PCC) are chosen from 10: Sex, Speech delay, Jaundice, Genetic disorders, and family history. Next, chosen ASD feature dataset through its paces using five ML techniques: Naive Bayes (NB), K-Nearest Neighbor (k-NN), Decision Tree (DT), Support Vector Machine (SVM), and AdaBoostM1 (ABM1). The proposed framework is assessed in the third phase utilizing five measurements such as accuracy, precision, predicting time, recall, and F1-score,. The findings revealed that: The NB and K-NN approaches exhibit superior accuracy rates of 99.2% and 97.2%, with minimal prediction times of approximately 0.3 seconds and 0.45 seconds, correspondingly. Conversely, the DT and AdBM1 methods demonstrate a minor decline in accuracy, achieving 94.8% and 87.6%, respectively, along with increased prediction times. Nonetheless, the SVM approach exhibits the least performance, achieving an accuracy of 80.4% with a highest prediction time of 0.84 seconds.</p>
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Publication Date
Wed Nov 02 2016
Journal Name
World Journal Of Pharmaceutical Research
HISTOGENESIS AND HISTOMORPHOMETRIC STUDY ON KIDNEY DISORDER BY LAMOTRIGINE IN POSTNATAL RAT
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Background: Lamotrigine is a second generation Anti-epileptic drug; it is widely used for the treatment of epilepsy and bipolar disorder. Sufficient data is not available concerning its teratogenicity. Aim of the study: The study has been carried out to evaluate the effect of lamotrigine on Rat kidney development. Materials and Methods: The study was conducted on 10 pregnant Albino Rats (Rattus rattus) divided equally into two groups, control and experiment groups. Experiment group received lamotrigne 10mg/kg/day orally using naso-gastric tube from the first day of gestation until the first week after birth, while the control group received distilled water. Newborn kidneys were collected at day 7 postnatal and fixated in bouin’s solution,

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Publication Date
Mon Mar 15 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Screening for Attention Deficit Hyperactivity Disorder at Elementary Schools in Baghdad City
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Objective(s): To determine the prevalence of ADHD among elementary school pupils; identify the association between pupil's level of ADHD and age, etc., and investigate the differences in pupils ADHD based on gender, and grade.

Methodology: A descriptive study was conducted on elementary school pupils. The study started from the period of 16th of September 2019 to the 1st of October 2020. A cluster sample of 800 pupils was selected. The questionnaire was constructed and developed and include two parts: the first part includes the pupil's general information and the second part includes scale of ADHD prevalence.

Results: The results of the present study indicated that 38(4.

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Publication Date
Tue Dec 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Application of Strategies about Pragmatic Language for Trainers who work at Autism Centers in Baghdad city
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Abstract

The study aimed: To assess the level of trainers' knowledge about the application of strategies and to find out the relationship between Trainer's knowledge and their socio-demographic characteristics.

Methodology: Using the pre-experimental design of the current study, for one group of 47 trainers working at the private Autism Centers in Baghdad, data was collected from 8/January / 2022 to 13 /February /2022. Using non-probability samples (convenient samples), self-management technology in which trainers fill out the questionnaire form themselves was used in the data collection process; it was analyzed through descriptive and inference statistics.

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Publication Date
Thu Apr 07 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF MICROBIAL CONTAMINATION IN SOME TYPES OF FLOUR THAT AVAILABLE IN LOCAL MARKETS USING BACTRAC DEVICE 3400: DETECTION OF MICROBIAL CONTAMINATION IN SOME TYPES OF FLOUR THAT AVAILABLE IN LOCAL MARKETS USING BACTRAC DEVICE 3400
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A microbial study conducted for a number of flour samples (30 samples) Uses in the bakery ovens in various areas of the city of Baghdad, by used the conventional methods used in laboratories in microbial tests and compared with the modern techniqueby usedof BacTrac Device 3400 equipped from SY-LAB Impedance analysersAustrian company.The results of two ways showed (The conventional way and BacTrac Device test)that the total counts of aerobic bacteria, coliform bacteria, StaphylococcusSpp. bacteria, Bacillus cereus bacteria and yeasts and molds,Most of them were within the permissible borders in the Iraqi standard for grain and its products With free samples from SalmonellaSpp. bacteria, and that the screening by BacTrac device are shorten

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Some Robust methods for Estimates the power Spectrum in ARMA Models Simulation Study
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Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

<

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Publication Date
Sun May 11 2025
Journal Name
Journal Of Information Systems Engineering And Management
The Effect of the Learning Mastery Strategy using Interactive Learning Techniques as a Therapeutic Method on the Achievement of Secondary School Students in Mathematics
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  The current research aims to identify the effect of the learning mastery strategy using interactive learning as a therapeutic method on the achievement of secondary school students in mathematics. To achieve the research objective, the researcher selected second-grade middle school students at Al-Haybah Intermediate School for Boys and determined his research sample, which consisted of (77) students distributed into two sections: Section (A) the experimental group, with (38) students, and Section (B) the control group, with (39) students. The statistical equivalence of the two research sample groups was confirmed in the variables (intelligence test, previous achievement, and previous knowledge test). The researchers chose the par

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Crossref
Publication Date
Sun Jan 01 2017
Journal Name
Spe
SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Scopus
Publication Date
Tue Jan 01 2013
Journal Name
Innovative Systems Design And Engineering
Automated Surface Defect Detection using Area Scan Camera
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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