Background: For many decades, the ECG was the
workhorse of non-invasive cardiac test and today although
other techniques provide more details about the structural
anomalies in congenital heart diseases, ECG is likely to be
part of clinical evaluation of patients with such diseases
because it is inexpensive, easy to perform and in certain
situations may be both sensitive and specific.
Objective: this study carried out to identify the pattern of
ECG study in patients with TOF.
Methods: this is a retrospective study of 200 patients
with TOF, referred to Ibn Al-Bitar cardiac center from
April 1993 to May 1999. The diagnosis of TOF established
by echocrdiographic, catheterization and angiographic
study.

Two different composite materials were prepared by stir casting method of AA 6061 alloy as a matrix reinforced with two addition different ceramic materials Al₂O₃ and B₄C of grain size   20 µm by 2.5, 5, 7.5 and10% in weight. The composite material with aluminum alloy as a matrix possesses a unique mechanical properties such as: high specific strength and hardness, low density, and high resistance to corrosion and friction wear. This composite is widely used in automotive parts space and marine applications.

Pin-on-disc technique was used to calculate the wear rate for each addition of Al₂O₃ and B₄C particles. Rockwell hardness test and

In this study, tin oxide (SnO2) and mixed with cadmium oxide (CdO) with concentration ratio of (5, 10, 15, 20)% films were deposited by spray pyrolysis technique onto glass substrates at 300ºC temperature. The structure of the SnO2:CdO mixed films have polycrystalline structure with (110) and (101) preferential orientations. Atomic force microscopy (AFM) show the films are displayed granular structure. It was found that the grain size increases with increasing of mixed concentration ratio. The transmittance in visible and NIR region was estimated for SnO2:CdO mixed films. Direct optical band gap was estimated for SnO2 and SnO2 mixed CdO and show a decrease in the energy gap with increasing mixing ratio. From Hall measurement, it was fou

Polymer electrolytes were prepared using the solution cast technology. Under some conditions, the electrolyte content of polymers was analyzed in constant percent of PVA/PVP (50:50), ethylene carbonate (EC), and propylene carbonate (PC) (1:1) with different proportions of potassium iodide (KI) (10, 20, 30, 40, 50 wt%) and iodine (I₂) = 10 wt% of salt. Fourier Transmission Infrared (FTIR) studies confirmed the complex formation of polymer blends. Electrical conductivity was calculated with an impedance analyzer in the frequency range 50 Hz–1MHz and in the temperature range 293–343 K. The highest electrical conductivity value of 5.3 × 10^-3 (S/cm) was observed for electrolytes with 50 wt% KI concentration at room

N-type Tin dioxide thin films with thickness (350 nm) prepared by thermal evaporation method. The thin film SnO2 was doped with Ag by the rate (0.01, 0.02 and 0.03). Atomic Force Microscopic (AFM) was adopted to determine the grain size and roughness of the film surface. The electrical properties were determined by mean of Hall Measurement system and mobility was calculated. SnO2: Ag/P–Si photodetectors demonstration the highest described visible responsivity of (0.287 A/W) with the Ag ratio of (0.03). I–V characteristics with different power density were measured. The best sensitive value of the spectral response, specific detectivity and quantum efficiency at wavelength (422 nm).

Pure cadmium oxide films (CdO) and doped with zinc were prepared at different atomic ratios using a pulsed laser deposition technique using an ND-YAG laser from the targets of the pressed powder capsules. X-ray diffraction measurements showed a cubic-shaped of CdO structure. Another phase appeared, especially in high percentages of zinc, corresponding to the hexagonal structure of zinc. The degree of crystallinity, as well as the crystal size, increased with the increase of the zinc ratio for the used targets. The atomic force microscopy measurements showed that increasing the dopant percentage leads to an increase in the size of the nanoparticles, the particle size distribution was irregular and wide, in addition, to increase the surfac

A.C electrical conductivity and dielectric properties for poly
(vinyl alcohol) (PVA) /poly (ethylene oxide) (PEO) blends undoped
and doped with multi-walled carbon nanotube (MWCNTs) with
different concentrations (1, and 3 wt %) in the frequency range
(25x103 - 5x106 Hz) were investigated. Samples of (PVA/PEO)
blends undoped and doped with MWCNTs were prepared using
casting technique. The electrical conductivity measurements showed
that σA.C is frequency dependent and obey the relation σA.C =Aωs for
undoped and doped blends with 1% MWCNTs, while it is frequency
independent with increases of MWCNTs content to 3%. The
exponent s showed proceeding increase with the increase of PEO
ratio (≥50%) for undope

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.