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Detection of Granulocyte Chemotactic Protein 2 in Serum of Periodontitis Patients
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Background: Chronic periodontitis defined as “an infectious inflammatory disease within supporting tissues of the teeth, progressive attachment loss and bone loss". Aggressive periodontitis is rare which in most cases manifest themselves clinically during youth. It characterized by rapid rate of disease progression .Pro-inflammatory chemokines organized inflammatory responses. Granulocyte chemotactic protein 2 is involved in neutrophil gathering and movement. The purpose of the study is to detect serum of Granulocyte Chemotactic Protein 2 and correlate to periodontal condition in patients with chronic periodontitis, Aggressive periodontitis and Healthy Control subjects and measurement the count of neutrophils for the studied groups. Subjects and methods: Eighty four male and female were enrolled in this study .They were divided into three groups (18) patients with Aggressive periodontitis with age range (20-45) years, (33) chronic periodontitis patients and (33) Healthy control with an age range (30-50). Clinical periodontal parameters were recorded for each group. The concentration of granulocyte chemotactic protein- 2 in serum was quantified by a high-sensitivity enzyme linked immunosorbent assay. Blood neutrophils count were detect for five subjects from each group using light microscope Result: ANOVA analysis revealed high significant differences in Granulocyte chemotactic protein 2 means between aggressive, chronic and controls. Neutrophils count in aggressive periodontitis is higher than chronic and controls .No significant difference in neutrophils count between aggressive and chronic periodontitis, while significant difference when correlate them with controls Conclusion The concentration of granulocyte chemotactic protein 2 increased with the increase in severity of periodontitis. Higher neutrophils count was found in aggressive periodontitis than chronic and controls. As higher granulocyte chemotactic protein 2 that chemoattract more neutrophils recruitment to the site of inflammation

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Matching Algorithms for Intrusion Detection System based on DNA Encoding
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Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Sun Apr 01 2012
Journal Name
2012 International Conference On Future Communication Networks
Efficient method to find the multiplicative inverse in GF (2<sup>m</sup>) using FPGA by exponentiation to (2<sup>k</sup>)
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Publication Date
Sun Apr 01 2012
Journal Name
2012 International Conference On Future Communication Networks
Efficient method to find the multiplicative inverse in GF (2<sup>m</sup>) using FPGA by exponentiation to (2<sup>k</sup>)
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Multiplicative inverse in GF (2 m ) is a complex step in some important application such as Elliptic Curve Cryptography (ECC) and other applications. It operates by multiplying and squaring operation depending on the number of bits (m) in the field GF (2 m ). In this paper, a fast method is suggested to find inversion in GF (2 m ) using FPGA by reducing the number of multiplication operations in the Fermat's Theorem and transferring the squaring into a fast method to find exponentiation to (2 k ). In the proposed algorithm, the multiplicative inverse in GF(2 m ) is achieved by number of multiplications depending on log 2 (m) and each exponentiation is operates in a single clock cycle by generating a reduction matrix for high power of two ex

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Publication Date
Sat Jan 01 2022
Journal Name
Revista Iberoamericana De Psicologia Del Ejercicio Y El Deportethis Link Is Disabled.,
THE EFFECT OF EXERCISES WITHIN A FACTORY HIERARCHICAL STRUCTURE IN REDUCING THE DEGREE OF PAIN IN A SAMPLE OF BACK PATIENTS
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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Inflammatory role of some cytokines, immunoglobulins and complement proteins in immunopathogenesis of renal failure in a sample of Diyala province patients
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This study was conducted in Diyala province for renal failure patients during the periods August 2015 - April 2016. Hundred renal failure patients were enrolled in the study after diagnosis by the consultant physician at Ibn-Sina Center for Dialysis in Baquba Teaching Hospital according to criteria adopted by the World Health Organization for diagnosis of renal failure disease. The number of males in patient’s sample was 61 (61%) and females was 39 (39%) with an age range of 10 – 88 year (44.7 ± 22.1 year). In addition, the study included 50 apparently healthy individuals and considered as a group control, in which the number of males and females was similar (25 individual), with an age range of 18 – 88 year (51.7 ± 17.3 year). The

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