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Hurst Exponent and Tsallis Entropy Markers for Epileptic Detection from Children
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The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this disease in children. Generally, this study aims to provide an evident of a reliable biomarker to detect epilepsy in children to give them an additional chance to live a high quality life.

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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Serum Adropin and Apelin as Potential Markers PredictingAcute Heart Failure-associated Renal Dysfunction among Elderly Iraqi Patients
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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Alterations in some Physiological and Inflammatory Markers in Iron-Deficient Obese Adults in the Kurdistan Region, Iraq
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Background: Iron homeostasis is crucial to many physiological functions in the human body, such as cellular activity, erythropoiesis, and the innate immune response. Iron deficiency anemia may occur from obesity's ability to disturb iron homeostasis. Obesity may be seen as a pre-inflammatory condition with mild, ongoing systemic inflammation. Additionally, an increase in hepcidin levels by chronic inflammation causes iron insufficiency in obese people. For this reason, this current experiment is designed to investigate the iron profile and some hematological and inflammatory parameters in obese adults in the Kurdistan region-Iraq.

Subjects and Methods: The cross-sectional study w

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Publication Date
Mon Jul 07 2025
Journal Name
Oxidation Communication
ANAPLASTIC LYMPHOMA KINASE EXPRESSION AND OTHER MARKERS AS A PROGNOSTIC BIOMARKER IN FEMALE PATIENTS WITH BREAST CANCER
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Breast cancer is among the primary causes of death among Iraqi women and is a serious worldwide health concern. ALK or anaplastic lymphoma kinase, is connected to several cancers, including breast cancer.. The goal of this research was to assess the prevalence of anaplastic lymphoma kinase (ALK) with Alkaline phosphatise (ALP) and Lactate dehydrogenase (LDH) together as diagnostic markers. The study comprised 60 patients with metastatic breast cancer and 60 healthy volunteers. The blood levels of the enzymes (ALP), (LDH), and ALK in Iraqi breast cancer patients are compared to those of healthy controls. It was shown that compared to healthy people, patients had breast cancer noticeably greater levels of ALK, ALP, and NDH .These biomarkers m

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Publication Date
Fri Sep 30 2016
Journal Name
Iraqi Journal Of Science
Anti-Mullerian Hormone and Follicle Stimulating Hormone as Markers of Ovarian Agingin a Sample of Iraqi Women
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One-hundred and twenty Iraqi women (60 single women and 60 married women) with age ranges from (17-49) years have been involved in this study to estimate the levels of anti-mullerian hormone (AMH) and follicle stimulating hormone (FSH) as markers of ovarian aging. The descriptive data [age, body mass index (BMI), age at menarche, duration of menarche] have been recorded. Blood samples were collected from the studied women to determine the levels of AMH and FSH. The results revealed non-significant (p>0.05) differences in levels of AMH and FSH between single women and married women. A significant negative correlation was observed between AMH levels and age in single women (r=-0.519, p<0.05) and married women (r=-0.433, p<0.05). A no

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Tue Oct 01 2019
Journal Name
2019 International Conference On Electrical Engineering And Computer Science (icecos)
An Evolutionary Algorithm for Community Detection Using an Improved Mutation Operator
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Publication Date
Tue Sep 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Analytical Model for Detection the Tilt in Originally Oil Water Contacts
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Many carbonate reservoirs in the world show a tilted in originally oil-water contact (OOWC) which requires a special consideration in the selection of the capillary pressure curves and an understanding of reservoir fluids distribution while initializing the reservoir simulation models.
An analytical model for predicting the capillary pressure across the interface that separates two immiscible fluids was derived from reservoir pressure transient analysis. The model reflected the entire interaction between the reservoir-aquifer fluids and rock properties measured under downhole reservoir conditions.
This model retained the natural coupling of oil reservoirs with the aquifer zone and treated them as an explicit-region composite system

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Publication Date
Mon Jun 30 2025
Journal Name
Iraqi Journal Of Science
New Weighted Synthetic Oversampling Method for Improving Credit Card Fraud Detection
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The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
GIS as A Tool for Expansive Soil Detection at Sulaymaniyah City
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Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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