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Changes in the EEG amplitude as a biomarker for early detection of Alzheimer's disease
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The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which can be quantified as a biomarker. The objective of the study reported in this paper is to develop robust EEG-based biomarkers for detecting AD in its early stages. We present a new approach to quantify the slowing of the EEG, one of the most consistent features at different stages of dementia, based on changes in the EEG amplitudes (ΔEEG A ). The new approach has sensitivity and specificity values of 100% and 88.88%, respectively, and outperformed the Lempel-Ziv Complexity (LZC) approach in discriminating between AD and normal subjects.

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Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Intrusion Detection System Techniques A Review
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With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Shared Congestion Detection: A Comparative Study
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Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noisin

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Biology, Agriculture And Healthcare
Histopathological Changes of Some Internal Organs of Mice Injected with Exotoxin a at Low Concentrations
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Abstract Exotoxin A is the most lethal virulence factor produced by Pseudomonas aeruginosa. It inhibits elongation factor-2 by ADP-ribosylation of EF2. This causes stop of the elongation of polypeptides. In recent study, the effect of low concentration of exotoxin A on some important internal organs of mice was studied. Four groups white mice were injected intraperitonialy with pure exotoxin A in the following manner 0.1, 0.2, 0.3, 0.4 ng\ animals. One mouse receives normal saline inrtaperitonialy as a control. After 72 hours the mice were killed and four organs were taken, liver, spleen, lung and heart from each killed mice. Histological sections were made from each organ and stained with hematoxylin and eosin stain then examined under mic

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Publication Date
Fri Dec 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Descriptive, Prospective Observational Study- Studying Possible Prediction Factors for Disease Severity and Progression among a Sample of COVD 19 Patients in Iraq
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Abstract

Coronavirus has affected many people around the world and caused an increase in the number of hospitalized patients and deaths. The prediction factor may help the physician to classify whether the patient needs more medical attention to decrease mortality and worsening of symptoms. We aimed to study the possible relationship between C reactive protein level and the severity of symptoms and its effect on the prognosis of the disease. And determine patients who require closer respiratory monitoring and more aggressive supportive therapies to avoid poor prognosis. The data was gathered using medical record data, the patient's medical history, and the onset of symptoms, as well as a blood sample to test the

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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Experimental Investigation for TiO2 nanoparticles as a Lubricant-Additive for a Compressor ofWindow Type Air-Conditioner
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The coefficient of performance of a window type Air-Conditioner system can be improved if a reduction in the work of compressor can be achieved by a suitable technique. The present study investigates the effect of dispersing a low concentration of TiO2 nanoparticles in the mineral oil based lubricant, as well as on the overall performance of a window type Air-Conditioner system using R22 as the working fluid. An enhancement in the COP of the refrigeration system has been observed and the existence of an optimum volume fraction noticed, with low concentrations of nanoparticles suspended in the mineral oil. Results showed that the average compressor work reduced by 13.3%, which ultimately resulted in an increase of 11.99% in the COP due to

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Publication Date
Tue Sep 24 2019
Journal Name
Journal Of Petroleum Research And Studies
Lithofacies Characterization of the Early – Middle Miocene Succession, Case-Study, South Iraq
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The Early – Middle Miocene Ghar and Lower Fars sedimentary succession at the representative oil-well Nu-18 of the Nahr Umr oil field south Iraq; is taken by this study to investigate the sedimentological to reservoir rock facies buildups and related reservoir zonation; as first rock-typing attempt for the both formations. The sedimentological characterization of the Early Miocene Ghar formation is mainly comprised by successive buildups of sands-gravels and sandstones, whereas; the Middle Miocene Lower Fars formation is started by limestone, limestone-marly/marl anhydritic, upgraded into interbedded-series of marl and anhydrite facies, with less-common occurrences of thin-sandstone interlayers, terminated by marl-sandy-secti

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Publication Date
Sat Jun 11 2022
Journal Name
International Journal Of Health Sciences
Prospective open pilot study on the use of cam oleum ointment for feline calicivirus disease in cats in Baghdad City
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Feline calicivirus (FCV) is a highly contagious virus that causes a mild to severe respiratory infection and oral disease in cats. It is especially common in shelters and breeding colonies, and often infects young cats, this study contained 50 different cats and samples were collected from September 2020 to January 2021. Samples taken by swabs from oropharyngeal and conjunctival area depending on the lesion of FCV infection to investigate viral nucleic acid from collected swabs, then extracting RNA from the swabs and converting it to a cDNA molecule, and last detecting the open reading template gene 2 using specific primer, these samples isolated from veterinary clinics, and shelters, all samples were collected from Baghdad city .Ra

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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