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Modis Satellite Data Evaluation for Detecting the Dust Storm Using Remote Sensing Techniques Over Iraq
Abstract<p>The phenomena of Dust storm take place in barren and dry regions all over the world. It may cause by intense ground winds which excite the dust and sand from soft, arid land surfaces resulting it to rise up in the air. These phenomena may cause harmful influences upon health, climate, infrastructure, and transportation. GIS and remote sensing have played a key role in studying dust detection. This study was conducted in Iraq with the objective of validating dust detection. These techniques have been used to derive dust indices using Normalized Difference Dust Index (NDDI) and Middle East Dust Index (MEDI), which are based on images from MODIS and in-situ observation based on hourly wind speed and visibility during May 4-5 2022 and 25-26 June 2022. In this study, the appropriateness of two various MODIS-based techniques to discover dust in 13 stations in Iraq was examined. The results suggest NDDI index is the most appropriate index to identifying dust storms across Iraq. Also, the MEDI index has impairment to discover dust through multiple land-cover forms. Beside that MEDI consider an ineffective index to detect and discover dust storms throughout whole kinds of land cover over Iraq.</p>
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Publication Date
Tue Jan 01 2008
Journal Name
University Of Baghdad
Publication Date
Sat Nov 30 2019
Journal Name
Journal Of Engineering And Applied Sciences
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Publication Date
Thu Jan 01 2015
Journal Name
The 2d International Conference Of Buildings, Construction And Environmental Engineering (bcee2-2015)
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Publication Date
Sun Jul 02 2023
Journal Name
Iraqi Journal Of Science
Seismic Structural –Stratigraphic Study of Dhufria Area (Mid -Iraq) Using (3D) Techniques

This study deals with the seismic reflection interpretation of lower Cretaceous Formations in Dhufria area, including structural and stratigraphic techniques. In the interpretation process, the 3-D seismic data volume and well logs have been used. Based on well logs and synthetic traces two horizons were identified and picked which are the top and bottom of Zubair Formation. These horizons were followed over all the area in order to obtain structural setting as well as studying Kirkuk group Formation of Tertiary age which represents highstand progradational seismic facies.

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Thu Aug 30 2018
Journal Name
Journal Of Engineering
An Optimum Strategy for Producing Precise GPS Satellite Orbits using Double-Differenced Observations

Both the double-differenced and zero-differenced GNSS positioning strategies have been widely used by the geodesists for different geodetic applications which are demanded for reliable and precise positions. A closer inspection of the requirements of these two GNSS positioning techniques, the zero-differenced positioning, which is known as Precise Point Positioning (PPP), has gained a special importance due to three main reasons. Firstly, the effective applications of PPP for geodetic purposes and precise applications depend entirely on the availability of the precise satellite products which consist of precise satellite orbital elements, precise satellite clock corrections, and Earth orientation parameters. Secondly, th

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Image Processing Approaches as a Diagnostic Parameter to Determine Pollution by Using Satellite Imagery, Northern Iraq

     This work highlights the estimation of the Al-Khoser River water case that disposes of its waste directly into the Tigris River within Mosul city. Furthermore, the work studies the effects of environmental and climate change and the impact of pollution resulting from waste thrown into the Al-Khoser River over the years. Al-Khoser River is located in the Northern Mesopotamia of Mosul city. This study aims to detect the polluted water area and the polluted surrounding area. Temporal remote sensing data of different Landsat generations were considered in this work, specifically Enhanced Thematic Mapper Plus of 2000 and Operational Land Imager of 2015. The study aims to measure the amount of pollution in the study area over 15 years

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Calculation of the Time Interval of Radio Storm Emitted from Jupiter

A program in Visual Basic language was designed to calculate the time interval of radio storm by predict their type at specific Local Time (LT) from Baghdad location, such storms result from the Central Meridian Longitude (CML) of system ΙΙΙ for Jupiter and phase of Io’s satellite (ФIo). These storms are related to position of Io (Io- A,B,C,D). The input parameters for this program were the observer’s location (longitude), year, month and day. The output program results in form of tables provide the observer information about the date and the LT of beginning and end of each type of emitted storm. The year 2011 was taken to apply the results within twelve month; the results of the time interval of radio storm were between (0.08h-5

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Sun Nov 12 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Indirect lmunofluorescent Antibody Test for Detecting Chlamydial Infection

A total of 243 serum samples  were tested  for the presence of

Chlamydia antibodies by ind irect immunofluorescent antibody test.Ninety

nine females were suffering from abortions, 64 were infertile and other 80 were  none  aborted  women.  The  incidence of  Ch lamydia  were  (15%,

9.4%)   and   (3.8%)   in  abortion,   infertile   and   non   aborted   group,

respecti vely.  The  results  also  showed  a difference  in  prevalence rate between the age groups. The  highest  incidence was found  in the age group  20-39 &

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