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Modified Vegetation Detection Index Using Different-Spectral Signature
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The Normalization Difference Vegetation Index (NDVI), for many years, was widely used in remote sensing for the detection of vegetation land cover. This index uses red channel radiances (i.e., 0.66 μm reflectance) and near-IR channel (i.e., 0.86 μm reflectance). In the heavy chlorophyll absorption area, the red channel is located, while in the high reflectance plateau of vegetation canopies, the Near-IR channel is situated. Senses of channels (Red & Near- IR) read variance depths over vegetation canopies. In the present study, a further index for vegetation identification is proposed. The normalized difference vegetation shortwave index (NDVSI) is defined as the difference between the cubic bands of Near- IR and Shortwave infrared radiation (SWIR) divided by their sums. The radiances or reflectances are included in this index from the Near-IR channel and WSIR2 channel (2.1 μm). The NDVSI is less sensitivite to atmospheric effects as compared to NDVI. By comparing the one NDVSI index with the two indexes (NDVI, SAVI) of vegetation cover, good correlations were found between NDVI  and NDVSI (R2=0.917) and between SAVI and NDVSI (R2=0.809. Accordingly, the proposed index can be taken into consideration as an independent vegetation index

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Publication Date
Sun Oct 22 2023
Journal Name
Iraqi Journal Of Science
A Hybrid Estimation System for Medical Diagnosis using Modified Full Bayesian Classifier and Artificial Bee Colony
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This paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the

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Publication Date
Thu Oct 01 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Study the Ability of Pseudomonas Aeruginosa Isolated from Different Clinical Cases to Biofilm Formation and Detection of Algd Gene.
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98 samples were collected from various clinical sources included (Burns, wounds, urines, sputums, blood) From the city of Baghdad, After performing the biochemical and microscopic examination, 52 isolates were obtained for Pseudomonas aeruginosa, 17 (32.7%) isolates from burn infection, 12 (23%) isolates from Wound infection 11 (21.2%) isolates from urine infection, 7 (13.5%) isolates of sputum and 5 (9.6%) isolates from blood. Bacteria susceptibility to form biofilm has been detectedby microtiter plate method, The results showed that 80% of the bacterial isolates were produced the biofilm with different proportions, alg D gene (alginate production) has been detected by polymerase chain reaction (PCR) Which plays an essential role in the fo

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Publication Date
Wed Sep 20 2023
Journal Name
Journal Of Applied And Natural Science
Detection of some virulence genes (esp, agg, gelE, CylA) in Enterococcus faecalis isolated from different clinical cases at Baghdad
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The virulent genes are the key players in the ability of the bacterium to cause disease. The products of such genes that facilitate the successful colonization and survival of the bacterium in or cause damage to the host are pathogenicity determinants. This study aimed to investigate the prevalence of virulence factors (esp, agg, gelE, CylA) in E. faecalis isolated from diverse human clinical collected in Iraqi patient , as well as to assess their ability to form biofilm and to determine their haemolytic and gelatinase activities. Thirty-two isolates of bacteria Enterococcus faecalis were obtained, including 15 isolates (46.87%) of the urine, 6 isolates (18.75%) for each of the stool and uterine secretions, and 5 isolates (15.62%) of the wo

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Publication Date
Sun Dec 22 2024
Journal Name
Journal Of Baghdad College Of Dentistry
Shear bond strength of different lingual buttons bonded to wet and dry enamel surfaces with resin modified glass ionomer cement (in vitro comparative study)
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Background: This study was aimed to investigate the effect of three lingual button (Nickel free / rectangular base, Nickel free / round base and Composite) and bonding environment, wet and dry enamel surface, on: the shear bond strength (SBS) of light and self-cured Resin Modified Glass Ionomer Cements, and the debonding failure sites. Materials and method: One hundred twenty no-carious, free of cracks maxillary first premolar teeth were selected. Three types of orthodontic lingual buttons were used in this study: Nickel free / rectangular base, Nickel free / round base and Composite buttons. The teeth were divided into two groups of sixty teeth each. One group was used for testing the chemically cured GC Fuji Ortho Resin modified Glass Io

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Publication Date
Tue Nov 05 2013
Journal Name
Wit Transaction On Ecology And The Environments, Wit, Press No. 11
Remote sensing of water quality index for irrigation usability of the Euphrates River
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irrigation use at many stations along the Euphrates River inside the Iraqi lands and to try to correlate the results with the satellite image analyses for the purpose of making a colored model for the Euphrates that can be used to predict the quality classifications of the river for irrigation use at any point along the river. The Bhargava method was used to calculate the water quality index for irrigation use at sixteen stations along the river from its entrance to the Iraqi land at Al-Qaim in Anbar governorate to its union with the Tigris River at Qurna in Basrah governorate. Coordinates of the sixteen stations of the Euphrates River were projected at the mosaic of Iraq satellite image which was taken from LANDSAT satellite for bands 1, 2

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Publication Date
Tue Jan 29 2019
Journal Name
Frontiers In Cell And Developmental Biology
Hypoxia-Modified Cancer Cell Metabolism
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Publication Date
Sun Jan 01 2017
Journal Name
Spe
SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Detection of Respiratory Syncytial Virus infection in Clinical Samples Using Immunofluorescence Test
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Current study aimed to investigate the Respiratory Syncytial Virus (RSV) in nasal
secretion and throat swab samples of hospitalized patients with symptoms of
respiratory tract infection using Immunofluorescence test. Previously these samples
were tested for Respiratory Syncytial Virus infection by reverse transcriptase-PCR
assay. The positive samples were tested by Immunofluorescence assay in monolayer
confluent of Hep 2 cell line. The results showed that the positive samples using the
RT-PCR test were positive in this test. These results reveal that Immunofluorescence
test is sensitive method for detection the infection with RSV.

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm
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Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

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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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