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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
Wed Jul 19 2017
Journal Name
International Journal Of Advances In Chemical Engineering And Biological Sciences
Detection of Aflatoxin M1 in Pasteurized Canned Milk and Using of UV Radiation for Detoxification
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The current study was designed to investigate the presence of aflatoxin M1 in 25 samples of pasteurized canned milk which collected randomly from some Iraqi local markets using ELISA technique. Aflatoxin M1 was present in 21 samples, the concentration of aflatoxin M1 ranged from (0.25-50 ppb). UV radiation (365nm wave length) was used for detoxification of aflatoxin M1 (sample with highest concentration /50 ppb of aflatoxin M1 in two different volumes ((25 & 50 ml)) for two different time (15 & 30 min) and 30, 60, 90 cm distance between lamp and milk layer were used for this purpose). Results showed that distance between lamp and milk layer was the most effective parameter in reduction of aflatoxin M1, and whenever the distance increase the

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Publication Date
Wed Aug 01 2012
Journal Name
I-manger's Journal On Information Technology
A MODULE FOR ENHANCING RECOGNITION SYSTEM FOR QR CODE SCANNED IMAGE
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A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

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
Wed Jul 24 2024
Journal Name
Journal Of Plant Protection Research
Developing smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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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
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
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Enhancement of gas response of annealed ZnO film for hydrogen gas detection
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  The mechanism of hydrogen (H2) gas sensor in the range of 50-200 ppm of RF-sputtered annealed zinc oxide (ZnO) and without annealing was studied. The X-ray Diffraction( XRD) results showed that the Zn metal was completely converted to ZnO with a polycrystalline structure. The I–V characteristics of the device (PT/ZnO/Pt) measured at room temperature before and after annealing at 450 oC for4h, from which a linear relationship has been observed. The sensors had a maximum response to H2 at 350 oC for annealing ZnO and showed stable behavior for detecting H2 gases in the range of 50 to 200 ppm. The annealed film exhibited hig

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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
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 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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