Understanding how wing geometry and internal structural configuration influence vibration behavior is essential for ensuring the aeroelastic stability and structural integrity of modern aircraft. This study presents a comprehensive numerical investigation of the modal and deflection characteristics of aircraft wings with different geometries (symmetric tapered planform and swept-back) and spar configurations (box and I-section) using the finite element method (FEM) in ANSYS Mechanical APDL R.15. Six NACA airfoil profiles (0024, 2411, 2416, 2424, 4412, and 4421) with angle of attack 9° under 50 m/s speed and 1,100 kg pay load were analyzed under identical aerodynamic and material conditions using linear elasti

Objectives: Teenage pregnancy with gestational diabetes mellitus (GDM) offers a real challenge to the health system and needs a special care. We aimed to evaluate possible obstetrical and neonatal adverse events of different treatment protocols in adolescent GDM including lifestyle, metformin (MTF), and insulin. Methods: All teen pregnant women ≤ 19 years old visiting Baghdad Teaching Hospital throughout four years (from June 1, 2016 till May 31, 2020) diagnosed with GDM were included in this cohort study and followed-up closely throughout pregnancy and after delivery. Included adolescents were put on lifestyle alone during the first week of presentation. Adolescents who reached target glucose measurements were categorized i

Objective: To evaluate the antibacterial effect of mastic gum against the most common aerobic oral bacteria and
emphasized on oral streptococci.
Methodology: In this study 10 persons (males and females of 18-60 years old) were randomly assigned to chew
mastic gum (1.5 gm for 45 minutes). Mouth washes were collected before and after gum chewing .The two mouth
washes were diluted (10-1 – 10-6) and cultivated aerobically for 24 hours at 37C0 on BHI agar for total bacterial
count and on MSF agar for counting the oral streptococci.
Results: The results showed that the total bacterial count for staphylococci, Neisseria and oral streptococci on BHI
agar and MSF agar for oral streptococci after mastic chewing were highly r

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

We explore the transform coefficients of fractal and exploit new method to improve the compression capabilities of these schemes. In most of the standard encoder/ decoder systems the quantization/ de-quantization managed as a separate step, here we introduce new way (method) to work (managed) simultaneously. Additional compression is achieved by this method with high image quality as you will see later.

Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff