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Four Char DNA Encoding for Anomaly Intrusion Detection System
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Recent research has shown that a Deoxyribonucleic Acid (DNA) has ability to be used to discover diseases in human body as its function can be used for an intrusion-detection system (IDS) to detect attacks against computer system and networks traffics. Three main factor influenced the accuracy of IDS based on DNA sequence, which is DNA encoding method, STR keys and classification method to classify the correctness of proposed method. The pioneer idea on attempt a DNA sequence for intrusion detection system is using a normal signature sequence with alignment threshold value, later used DNA encoding based cryptography, however the detection rate result is very low. Since the network traffic consists of 41 attributes, therefore we proposed the most possible less character number (same DNA length) which is four-character DNA encoding that represented all 41 attributes known as DEM4all. The experiments conducted using standard data KDDCup 99 and NSL-KDD. Teiresias algorithm is used to extract Short Tandem Repeat (STR), which includes both keys and their positions in the network traffic, while Brute-force algorithm is used as a classification process to determine whether the network traffic is attack or normal. Experiment run 30 times for each DNA encoding method. The experiment result shows that proposed method has performed better accuracy (15% improved) compare with previous and state of the art DNA algorithms. With such results it can be concluded that the proposed DEM4all DNA encoding method is a good method that can used for IDS. More complex encoding can be proposed that able reducing less number of DNA sequence can possible produce more detection accuracy.

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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Use of cefoxitin as indicator for detection of Methicillin Resistant Staphylococcus aureus
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Rapid and accurate identification of Methicillin Resistant Staphylococcus aureus is essential in limiting the spread of this bacterium. The aim of study is the detection of Methicillin Resistant Staphylococcus aureus (MRSA) and determining their susceptibility to some antimicrobial agent. A total of fifty clinical Staphylococcus aureus, isolated from the nose of health work staff in surgery unit of Kalar general hospital and from ear of patients attended to the same hospital. The susceptibilities of isolates were determined by the disc diffusion method with oxacillin (1 ?g) and cefoxitin (30 ?g), and by the mannitol salt agar supplemented with cefoxitin (MSA-CFOX), susceptibilities of isolates to other antimicrobial agent were determined b

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images
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A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Gravity Field Interpretation for Major Fault Depth Detection in a Region Located SW- Qa’im / Iraq
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This research deals with the qualitative and quantitative interpretation of Bouguer gravity anomaly data for a region located to the SW of Qa’im City within Anbar province by using 2D- mapping methods. The gravity residual field obtained graphically by subtracting the Regional Gravity values from the values of the total Bouguer anomaly. The residual gravity field processed in order to reduce noise by applying the gradient operator and 1st directional derivatives filtering. This was helpful in assigning the locations of sudden variation in Gravity values. Such variations may be produced by subsurface faults, fractures, cavities or subsurface facies lateral variations limits. A major fault was predicted to extend with the direction NE-

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Publication Date
Tue Aug 01 2023
Journal Name
Dna Repair
The interactions between DNA methylation machinery and long non-coding RNAs in tumor progression and drug resistance
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DNA methylation is one of the main epigenetic mechanisms in cancer development and progression. Aberrant DNA methylation of CpG islands within promoter regions contributes to the dysregulation of various tumor suppressors and oncogenes; this leads to the appearance of malignant features, including rapid proliferation, metastasis, stemness, and drug resistance. The discovery of two important protein families, DNA methyltransferases (DNMTs) and Ten-eleven translocation (TET) dioxygenases, respectively, which are responsible for deregulated transcription of genes that play pivotal roles in tumorigenesis, led to further understanding of DNA methylation-related pathways. But how these enzymes can target specific genes in different malignancies;

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Publication Date
Mon Feb 10 2025
Journal Name
Journal Of Optics
Implementing quantum key distribution based on coincidence detection captured from two different single photon detection modules
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Quantum key distribution (QKD) provides unconditional security in theory. However, practical QKD systems face challenges in maximizing the secure key rate and extending transmission distances. In this paper, we introduce a comparative study of the BB84 protocol using coincidence detection with two different quantum channels: a free space and underwater quantum channels. A simulated seawater was used as an example for underwater quantum channel. Different single photon detection modules were used on Bob’s side to capture the coincidence counts. Results showed that increasing the mean photon number generally leads to a higher rate of coincidence detection and therefore higher possibility of increasing the secure key rate. The secure key rat

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