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Discussion on techniques of data cleaning, user identification, and session identification phases of web usage mining from 2000 to 2022
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The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Recognizing Job Apathy Patterns of Iraqi Higher Education Employees Using Data Mining Techniques
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Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Tue Sep 21 2021
Journal Name
Journal Of Healthcare Engineering
Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs
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Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent

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Publication Date
Sat Apr 01 2017
Journal Name
Image & Video Processing
Enhancement of LBP-based face identification system by adopting preprocessing techniques
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Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap

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Publication Date
Fri Nov 25 2022
Journal Name
Tem Journal
Preparing of ECG Dataset for Biometric ID Identification with Creative Techniques
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The Electrocardiogram records the heart's electrical signals. It is a practice; a painless diagnostic procedure used to rapidly diagnose and monitor heart problems. The ECG is an easy, noninvasive method for diagnosing various common heart conditions. Due to its unique advantages that other humans do not share, in addition to the fact that the heart's electrical activity may be easily detected from the body's surface, security is another area of concern. On this basis, it has become apparent that there are essential steps of pre-processing to deal with data of an electrical nature, signals, and prepare them for use in Biometric systems. Since it depends on the structure and function of the heart, it can be utilized as a biometric attribute

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Publication Date
Mon Oct 31 2022
Journal Name
Biodiversitas Journal Of Biological Diversity
Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data
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Abstract. Hassan FM, Mahdi WM, Al-Haideri HH, Kamil DW. 2022. Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data. Biodiversitas 23: 5239-5246. The biodiversity and water quality of the Diyala River require screening water in terms of biological contamination, because it is the only water source in Diyala City and is used for many purposes. This study aimed to identify a new species record of Cynaophyceae and emphasize the importance of using molecular methods beside classic morphological approaches, particularly in the water-shrinkage-aqua system. Five different sites along Diyala River were selected for Cyanophyceae identification. Morphological examination and 16S rRNA sequen

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Publication Date
Thu Dec 01 2011
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
ISOLATION AND IDENTIFICATION OF INTESTINAL PARASITES FROM VEGETABLES FROM DIFFERENT MARKETS OF IRAQ.
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This investigation was designed to determine the occurrence of intestinal parasites in fresh
vegetables(Apium graveolense, Lepidium aucheri and Allium porrum), from different markets
as a primary effort in Iraq. Eight genera and species of intestinal parasites appear in
vegetables, they were as follow: Echinococcus sp. 50%,Oxyuris equi 45%,Habronema sp.
45%,Parascaris equroum 31.6%,Strongyloides westrei 30%,Toxocara sp. 18.3%,Ascaris
lumbricoides 11.6% and Hymenolepis sp. 8.3% .The scarcity of fresh water has meant that
urban gardeners are increasingly irrigating their plots with wastewater. This poses a threat to
public health in addition of roaming dogs in open farms. All studied areas showed high rates
of eggs

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Publication Date
Fri Aug 30 2024
Journal Name
Iraqi Journal Of Science
Isolation and Identification of Enterococcus spp. Resistant to Macrolides Antibiotics
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Gram-positive enterococciare opportunistic and resistant to many antibiotics. This study aimed to investigate the presence of Enterococcus spp. in our community and whether these isolates are resistant to the macrolides class of antibiotics. Fifty isolates from 112 clinical samples were recognized as Enterococcus spp. and confirmed using Vitek-2 system. The current study found that 50/112 (44.6%) represented the total isolates, 38/50 (76%) of which were Enterococcus faecalis, while 12/50 (24%) were Enterococcus faecium, twenty (40%) isolates from root canals and 30 (60%) isolates from urine were isolated. The sensitivity of the enterococcal isolates to various macrolides (erythromycin, azithromycin and clarithromycin) antibiotics wa

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Publication Date
Tue Oct 14 2025
Journal Name
Nigerian Journal Of Parasitology
Identification of intestinal parasite isolates from deer in Iraq
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In recent decades, breeding deer populations in Iraq have expanded significantly in size and distribution. Owing to their role in pathogen transmission, these deer populations pose a risk to the livestock industry. However, little is known about the parasitic infection status of the breeding deer and the surrounding environment in Iraq. Atotal of 150 deer faecal samples were collected from male and female deer of various ages from four regions of Iraq and examined microscopically for intestinal parasites. Microscopic analysis revealed the presence of seven intestinal parasite species: Entamoeba spp. (48%), Giardia duodenalis (17%), Toxocara spp. (12%), Balantidium coli(9%), Taenia spp. (9%), Strongyloides spp. (3%) and Trichostrongy

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
isolation and identification of cloves oil from eugenia caryophyllaa using Ultrasonic
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This research has been prepared to isolate and diagnose one of the most important vegetable oils from the plant medical clove is the famous with Alaeugenol oil and used in many pharmaceuticals were the isolation process using a technique ultrasonic extraction and distillation technology simple

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