Several efforts have been made to study the behavior of Total Electron Content (TEC) with many types of geomagnetic storm, the purpose of this research is to study the disturbances of the ionosphere through the TEC parameter during strong, severe and great geomagnetic storms and the validity of International Reference Ionosphere IRI model during these kinds of storms. TEC data selected for years 2000-2013 (descending solar cycle 23 to ascending cycle 24), as available from koyota Japan wdc. To find out the type of geomagnetic storms the Disturbance storm time (Dst) index was selected for the years (2000-2013) from the same website. Data from UK WDC have been taken for the solar indices sunspots number (SSN), radio flux (F10.7) and ionosphere index parameter (IG12). The predicted TEC are calculated from IRI model. From data analysis, it is found that there are (132) events happened in the tested years for the strong, severe and great geomagnetic storms, a largest number of solar storms appeared in years 2000 to 2005 at solar maximum from solar cycle 23 and the number of storms increases with increasing the SSN. In general, there is a good proportionality between disturbance storm time index (Dst) and the total electron contents, the values of TEC in daytime greater than nighttime, but there is anomaly when the storm continued for several hours from the day, there is a highly a broad increasing in TEC started from sunrise to sunset. Also two peaks or more appeared when two types of storms occurred remaining for one event or the storm remains for more than one day. Finally there is approximately sharp peak at noon, when the storm started in early morning. Concerning the validity of the IRI model during strong, great, and severe geomagnetic storm shows that there is a weak correlation between the observed and predicted TEC values, so that the model must be corrected during major storms.
The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
... Show MoreTo deduct the childhood status in Iraq, it was important manner to use statistical tools and approaches concerned with interpreting the causal relationships and their attitudes and use classification method for the important effects (variables) to draw an obvious picture of the phenomena under study in order to make it useful through investing, updating and improving it in by demographic studies in the future. Two statistical methods had been used in the field of analyzing data of multivariate analysis namely, Cluster Analysis and Factor Analysis.
The present study focuses on four fundamental axes .The nutrition axis, health axis, Educational axis, and the social axis. The study has ca
... Show MoreThe ground state densities of unstable neutron-rich 11Li and 12Be exotic nuclei are studied in the framework of the binary cluster model (BCM). The internal densities of the clusters are described by the single particle harmonic oscillator wave functions. The long tail performance is clearly noticed in the calculated neutron and matter density distributions of these nuclei. The structures of the two valence neutrons in 11Li and 12Be are found to be mixed configurations with dominant (1p1/2)2. Elastic electron scattering proton form factors for 11Li and 12Be are studied using the plane wave Born approximation (PWBA). It is found that the major difference between the calculated form factors of unstable nuclei [11Li, 12Be] and those of stab
... Show MoreThis study examines the factors that affect oral participation of six Arab postgraduate students (two Iraqis, two Jordanians, and two Libyans), namely, three male participants and three female participants. For this purpose, a semi-structured interview was employed. The results showed that female as well male interviewees share some factors that make oral participation in classroom disheartening. These factors include high levels of anxiety, lack of confidence, shyness, and lack of preparation. It was also that there is no difference between male and female interviewees in relation to the factors that make them feel disheartened from oral classroom participation.
The aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t
... Show MoreThe research aims to develop alternatives to transportation at the entrance to the Educational City (University of Baghdad) during the morning and evening peaks, which result from of the traffic congestion at the entrances to the educational city (the University of Baghdad), and affects the emotional, functional, and social performance of the whole city, and leads to hotbeds of confluence and congestion at the entrances in the morning and evening peaks. This movement was measured on the ground for pedestrians and vehicles. Some criteria were adopted to determine the density of road length to the area and density of roads for the number of users and the rate of the area served by roads. The research reviews the experiences of some
... Show MoreAcrylamide is a toxic chemical that is created when foods are heated; it is also available in foods containing different additives. The purpose of the study was to determine whether Bacillus spp. isolates could reduce the concentration of acrylamide in food, as well as to compare the different treatments of crude and pure L-asparaginase produced from the same bacteria in acrylamide reduction in potato slices. Our findings reveal that this bacterium could degrade acrylamide and reduce its concentration. Furthermore, the acrylamide content of potato slices reduced dramatically with increasing enzymatic treatment time, reaching the under detection limit (UDL) after 30 minutes of treatment with 84 U/ml of crude and purified
... Show MoreThis study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960–2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 °C for sixty years, have contributed to an increase in the number of dust storm
... Show MoreThe penalized least square method is a popular method to deal with high dimensional data ,where the number of explanatory variables is large than the sample size . The properties of penalized least square method are given high prediction accuracy and making estimation and variables selection
At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and
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