The ionospheric characteristics exhibit significant variations with the solar cycle, geomagnetic conditions, seasons, latitudes and even local time. Representation of this research focused on global distribution of electron (Te) and ion temperatures (Ti) during great and severe geomagnetic storms (GMS), their daily and seasonally variation for years (2001-2013), variations of electron and ion temperature during GMS with plasma velocity and geographic latitudes. Finally comparison between observed and predicted Te and Ti get from IRI model during the two kinds of storm selected. Data from satellite Defense Meteorological Satellite Program (DMSP) 850 km altitude are taken for Te, Ti and plasma velocity for different latitudes during great

 In this research, analytical study for simulating a Fabry-Perot bistable etalon (F-P cavity) filled with a dispersive optimized nonlinear optical material (Kerr type) such as semiconductors Indium Antimonide (InSb). An optimization procedure using reflective (~85%) InSb etalon (~50µm) thick is described. For this etalon with a (50 µm) spot diameter beam, the minimum switching power is (~0.078 mW) and switching time is (~150 ns), leading to a switching energy of (~11.77 pJ) for this device. Also, the main role played by the temperature to change the etalon characteristic from nonlinear to linear dynamics.

This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

The current research includes a look at the participation of Iraqi women in the combat roles, which starts from the assumption of the democratic transition that must be led - in one of its aspect - until the army or the military foundation to become a "citizen army," the matter which is represented a demand increasingly needed in the experiences of Democratic transformation that facing serious security challenges such as in Iraq, this means that the army or security foundation - which is involved in counterterrorism - should not reflect a specific group in society , and hence embody the most important democratic principles, which are equality and equal opportunities, especially gender equality. On the other hand, the influence of armed conf

: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

Image Fusion Using A Convolutional Neural Network