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Change Detection between Landsat 8 images and Sentinel-2 images
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     The technology of change detection is a technique by which changes are verified in a certain time period. Remote sensing images are used to detect changes in agriculture land for the selected study area located south of Baghdad governorate in Agricultural Division of AL-Rasheed district because this method is very effective for assessing change compared to other traditional scanning techniques. In this research two remotely sensed images for the study area were taken by Landsat 8 and Sentinel-2, the difference between them is one month to monitor the change in the winter crops, especially the wheat crop, where the agriculture began for the wheat crop there in the Agricultural Division of AL-Rasheed district at 15/11/2018. The first preprocessing procedure was the extraction of the NDVI (Normalized Difference Vegetation Index) values for the two scenes of Landsat 8 and the two scenes of Sentinel-2B and then using the change detection between them to compare the changes in agriculture land. Also, change detection was implemented between NIR bands because they are most severely affected by biomass or the amount of available chlorophyll-containing in plant structures. The results of the change detection for Sentinel-2B were more accurate than for the Landsat 8 as demonstrated by field visits for the study area, where the changes in the distribution of vegetal cover (wheat and other winter crops) were clear and accurate in the image of Sentinel-2B, as opposed to Landsat's 8 image, where the variation in vegetation cover was not accurate, especially for the change detection between NIR bands.

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
Detection of Pan Braf in Thyroid Tumors in Iraqi Patients
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The B-type Raf kinase (BRAF) is a member of RAS\RAF\MEK\ERK pathway and this pathway can lead to increased cellular growth, invasion and metastasis. The mutated BRAF protein activates MAPK signaling pathway, results in abnormal cellular growth, apoptosis resistance, tumor progression and metastasis. Pan-BRAF is one of available BRAF monoclonal antibodies and shared by both the wild and mutant BRAF.BRAF status is mostly determined by DNA sequencing methods. In this investigation we assessed the monoclonal Pan BRAF specific antibody that can identify wild and mutant type proteins together in formalin-fixed paraffin-embedded thyroid tumor tissues by Immunohistochemistry (IHC). Archival thyroid samples from 43 iraqi patients were immunohisto

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Publication Date
Sun Dec 01 2019
Journal Name
Al-nahrain Journal Of Science
Enhancing Sparse Adjacency Matrix for Community Detection in Large Networks
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Practical Study for the Properties of Hueckel Edge Detection Operator
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Detection of Epstein Barr Virus Infection in Reactive Arthritis Patients
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Reactive arthritis (ReA) is an incendiary joint inflammation that occurs few days to weeks after a gastrointestinal or genitourinary infection. The etiology of the disease is not well-known. Therefore, the present study included 80 females and 25 males, divided into 51 patients with reactive arthritis and 54 healthy individuals as control group.  The study involved the detection of serum levels of anti-rheumatoid factor and anti-cyclic citrullinated peptide antibodies (anti-CCP) as well as those of CRP and C3 in all subjects. In addition, EBV levels were detected by Real Time-PCR technique. The results showed significantly increased levels (P < 0.05) of CRP, C3 and anti-CCP Ab in ReA patients’ group compared to th

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Publication Date
Wed Aug 25 2021
Journal Name
2021 7th International Conference On Contemporary Information Technology And Mathematics (iccitm)
Anomaly Detection in Flight Data Using the Naïve Bayes Classifier
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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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