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edge detection using modification prewitt operators
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in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

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Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Hypertension among Cardiac Diseases Inpatients at Kirkuk City Hospitals
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Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise

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Publication Date
Mon Jun 07 2021
Journal Name
Jurnal Teknologi
MODELS, DETECTION METHODS, AND CHALLENGES IN DC ARC FAULT: A REVIEW
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The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Detection of blaKPC Gene in Some Clinical Klebsiella pneumoniae Isolates in Baghdad
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For the period from February 2014 till May 2014, one hundred and nine lactose fermenter clinical isolates from different samples (urine, stool, wound swab, blood, and sputum) were collected from Alyarmok, Alkadimiya, and Baghdad teaching hospitals at Baghdad governorate. Identification of all Klebsiella pneumoniae isolates were carried out depending on macroscopic, microscopic characterizations, conventional biochemical tests, and Api 20E system. Fifty-three (48.62%) isolates represented K. pneumoniae; however, 51.73% represented other bacteria. Susceptibility test was achieved to all fifty-three K. pneumoniae isolates using five antibiotic disks (Ceftazidime, Ceftriaxone, Cefotaxime, Imipenem, and Meropenem). Most of tested isolates (90

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Publication Date
Fri Mar 04 2022
Journal Name
Pakistan Journal Of Medical And Health Science
Detection of aadA1 and aac(3)-1V resistance genes in Acinetobacter baumannii
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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical And Cellular Archives
DETECTION OF BACTERIAL INFECTIONS AND THEIR RESISTANCE IN BURN WOUND OF SKIN
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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detection of Nutrients and Major Ions at Al Muthanna Storage Site Soil
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In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi

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Publication Date
Tue Jun 30 2020
Journal Name
Iraq Journal Of Market Research And Consumer Protection
DETECTION OF HEAVY METALS POLLUTION INTYPES OF MILK SAMPLES IN BAGHDAD MARKETS
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