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Identification of Pathogenic Fungi in Renal Transplant Patients by Conventional and Molecular Methods
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Opportunistic fungal infections due to the immune- compromised status of renal transplant patients are related to high rates of morbidity and mortality regardless of their minor incidence. Delayed in identification of invasive fungal infections (IFIs), will lead to delayed treatment and results in high mortality in those populations. The study aimed to assess the frequency of invasive fungal infection in kidney transplant recipients by conventional and molecular methods. This study included 100 kidney transplant recipients (KTR) (75 males, and 25 females), collected from the Centre of Kidney Diseases and Transplantation in the Medical City of Baghdad. Blood samples were collected during the period from June 2018 to April 2019. Twenty one out of 100 renal-transplanted patients were infected with pathogenic fungi, four of the patients were females and 17 were males. There is an observation of a high incidence of fungemia in patients with the abnormal value of blood urea according to PCR and culture results. Referring to fungal isolates the most prevalent was Saccharomyces cerevisiae, which account for 19 isolates out of 21 the other two isolates were Zygosaccharomyces rouxii and Aspergillus flavus. The results of the current study show significant correlation between PCR and culture methods at (P<0.0009).

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
The effect of Constructive Conflict on the Organizational Identification Applied Research in the Ministry of Planning
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This research deals with the effect of constructive conflict of the organizational identification .These relatively recent subjects have relative importance in the field of administration and they have strong effect in the success of organizations .The objective of this research is to detect the level of the constructive conflict and the organizational identification in the center of The Ministry of Planning. So, two major hypotheses were formulated The first are searched the correlation between the constructive conflict and the organizational identification and it emerged with four sub-hypotheses searched the correlation among every dimension of the constructive conflict with the organizational identification .The second major h

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Publication Date
Thu Aug 01 2019
Journal Name
2019 2nd International Conference On Engineering Technology And Its Applications (iiceta)
Human Gait Identification System Based on Average Silhouette
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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Proposed Hybrid Sparse Adaptive Algorithms for System Identification
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Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
System Identification Algorithm for Systems with Interval Coefficients
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In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Communications In Computer And Information Science
Automatic Identification of Ear Patterns Based on Convolutional Neural Network
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

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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
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Ordinary Methods (LS,IV) and Robust Methods (2SWLS,LTS,RA) to estimate the Parameters of ARX(1,1,1) Model for Electric Loads
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Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Physiological and Immunological Disturbance in Rheumatoid Arthritis Patients
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            Rheumatoid arthritis (RA) is a systematic autoimmune disorder with chronic inflammation changes of unknown etiology. Various synovial inflammatory and proliferative alterations may contribute to the cartilaginous tissues and invasive bony tissues, leading to destructive joints and malformed bones. This disease is mostly due to infective microorganisms or genetic susceptibility causing immune system disturbances through triggering both T-cells and B-cells. Furthermore, different immune cells may secret cytokines, which are responsible for some RA pathogenesis activity. From ninety individuals, serum sample was collected; thirty of them were normal and sixty cases were patients with RA attended a privet medical clin

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Publication Date
Thu Oct 01 2009
Journal Name
Journal
Perniosis: clinical and epidemiological study in Iraqi patients
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AN Adil A, F Basman M, 2009

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