Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

Objective(s): To determine the prevalence of ADHD among elementary school pupils; identify the association between pupil's level of ADHD and age, etc., and investigate the differences in pupils ADHD based on gender, and grade.

Methodology: A descriptive study was conducted on elementary school pupils. The study started from the period of 16th of September 2019 to the 1st of October 2020. A cluster sample of 800 pupils was selected. The questionnaire was constructed and developed and include two parts: the first part includes the pupil's general information and the second part includes scale of ADHD prevalence.

Results: The results of the present study indicated that 38(4.

The digital camera which contain light unit inside it is useful with low illumination but not for high. For different intensity; the quality of the image will not stay good but it will have dark or low intensity so we can not change the contrast and the intensity in order to increase the losses information in the bright and the dark regions. . In this search we study the regular illumination on the images using the tungsten light by changing the intensities. The result appears that the tungsten light gives nearly far intensity for the three color bands(RGB) and the illuminated band(L).the result depend on the statistical properties which represented by the voltage ,power and intensities and the effect of this parameter on the digital

Thirty local fungal isolates according to Aspergillus niger were screened for Inulinase production on synthetic solid medium depending on inulin hydrolysis appear as clear zone around fungal colony. Semi-quantitative screening was performed to select the most efficient isolate for inulinase production. the most efficient isolate was AN20. The optimum condition for enzyme production from A. niger isolate was determined by busing a medium composed of sugar cane moisten with corn steep liquor 5;5 (v/w) at initial pH 5.0 for 96 hours at 30 0C . Enzyme productivity was tested for each of the yeast Kluyveromyces marxianus, the fungus A. niger AN20 and for a mixed culture of A. niger and K. marxianus. The productivity of A. niger gave the highest

A field experiment was conducted during the agricultural season 2017-2018. In the research station of the Ministry of Agriculture AL Rasheed side, and within the activities and researches of the national program to develop wheat cultivation in Iraq, Two factors were experienced in the cultivation of wheat, The first factor is the method of cultivation of five treatments were used: : Treatment of the cultivation of wheat in the plots (B), Treatment of wheat crops on bed with 50 cm width (S1), 60cm (S2), 70cm (S3) and 80cm (S4), The second factor is irrigation levels depletion of 40, 60 and 80% of available water coded as W1, W2 and W3, respectively, The experiment was designed under randomized complete block design (RCBD) with three replicat

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes