Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS software. The regions located in Iraq, Saudi Arabia, Syria, and Jordan are the largest dust storm sources. New dust sources are identified in Iraq’s southwestern and western regions, such as Al-Nukhaib, Wadi Hauran, and Sinjar, along with new sources in Saudi Arabia, Jordan, and Syria. The most common sources are concentrated in Iraq (55.31%), mainly in the Tigris and Euphrates basin, western desert, and Al-Jazeera region, followed by Syria (19.55%), Saudi Arabia (12.29%), and Jordan (11.73%). The highest dust storm source frequency in Iraq is found in the Al- Samawa desert’s southern region (27.37%). Also, the highest frequency of dust sources from each country is determined. Knowing the origins and trajectories of dust storms will enhance treatments of these causes and their consequences on the environment and socio-economics of the region. It contributes to the support of specialised regional agencies to mitigate this phenomenon.
Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
... Show MoreThe study included the description of external body parts and the male genitalia for the male of rusty flour beetle Tribolium castaneum (Herbst,1797) and the studied was supported by illustrations
This investigation was designed to determine the occurrence of intestinal parasites in fresh
vegetables(Apium graveolense, Lepidium aucheri and Allium porrum), from different markets
as a primary effort in Iraq. Eight genera and species of intestinal parasites appear in
vegetables, they were as follow: Echinococcus sp. 50%,Oxyuris equi 45%,Habronema sp.
45%,Parascaris equroum 31.6%,Strongyloides westrei 30%,Toxocara sp. 18.3%,Ascaris
lumbricoides 11.6% and Hymenolepis sp. 8.3% .The scarcity of fresh water has meant that
urban gardeners are increasingly irrigating their plots with wastewater. This poses a threat to
public health in addition of roaming dogs in open farms. All studied areas showed high rates
of eggs
This research include building mathematical models for aggregating planning and shorting planning by using integer programming technique for planning master production scheduling in order to control on the operating production for manufacturing companies to achieve their objectives of increasing the efficiency of utilizing resources and reduce storage and improving customers service through deliver in the actual dates and reducing delays.
Background: Diabetes mellitus is a metabolic disorder affecting people worldwide, which require constant monitoring of their glucose levels. Commonly employed procedures include collection of blood or urine samples causing discomfort to the patients. Necessity arises to find alternative non invasive technique is required to monitor glucose levels. Saliva is one of most abundant secretions in the human body and its collection is easy, noninvasive and painless technique. Objective: The aim of this study was to determine the efficacy of saliva as a diagnostic tool by study the correlation between blood and salivary glucose levels and glycosylated hemoglobin (HbA1c%) in diabetes and non diabetes, and the comparison of salivary glucose level
... Show MoreFacial recognition has been an active field of imaging science. With the recent progresses in computer vision development, it is extensively applied in various areas, especially in law enforcement and security. Human face is a viable biometric that could be effectively used in both identification and verification. Thus far, regardless of a facial model and relevant metrics employed, its main shortcoming is that it requires a facial image, against which comparison is made. Therefore, closed circuit televisions and a facial database are always needed in an operational system. For the last few decades, unfortunately, we have experienced an emergence of asymmetric warfare, where acts of terrorism are often committed in secluded area with no
... Show MoreThis manuscript studied the effect of U-CFRP wrapped sheet anchorage on the flexural performance of unbonded post-tensioned PC members subjected to partial strand damage and strengthened using CFRP Near-Surface Mounting techniques. The program includes six girders as a control girder, a girder with strand damage of 14.2%, and four girders strengthened by CFRP laminates using the NSM technique with and without U-CFRP wrapped sheet anchorages. The testing results show that the strand damage of 14.2% has reduced the flexural strength of the girder by 5.71%. The NSM-CFRP laminate has a significant effect on flexural strength by 17.4%. On the other hand, the application of end U-CFRP wrapped sheet anchorages improves flexural
... Show MoreReal Time Extended (RTX) technology works to take advantage of real-time data comes from the global network of tracking stations together with inventor locating and compression algorithms to calculate and relaying the orbit of satellite, satellite atomic clock, and any other systems corrections to the receivers, which lead to real-time correction with high accuracy. These corrections will be transferred to the receiver antenna by satellite (where coverage is available) and by IP (Internet Protocol) for the rest of world to provide the accurate location on the screen of smartphone or tablet by using specific software. The purpose of this study was to assess the accuracy of Global Navig
The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in
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