A laboratory experiment was carried out according to a completely randomized design with four repetitions on the seeds resulting from a field experiment applied for the two seasons, 2020 and 2021, to find out the effect of the cultivars (Ambar 33, Yasamin, Dijlah, Ambar Al-Baraka and Furat 1) and the harvest dates (at physiological maturity and after 7 and 14, 21 and 28 days of physiological maturity) on the vigour of rice seeds. The results showed the superiority of the seeds of the cultivar Anbar Al-Baraka at first and final counting, dry weight of the seedling, seedling vigor index and electrical conductivity, and the superiority of the seeds of Dijla cultivar at accelerated aging test and cold test without significant difference with th

the behavior of the first-order black and gray solitons propagtedin optical fiber in the presence of frequency chirp is studied analytically and numerically results show that phase profile of black solitons changes abruptly

This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th

The current report dealt with the effect of pesticides on the ecosystem through their impact on soil, water, and microorganisms and their impact on human health. As well as this study dealt with the biodegradation process of pesticides and the organisms involved in this process, even some previous studies proved that Bacillus spp. And Pseudomonas sp. Bacteria is the most efficient in the biodegradation of pesticides, at the same time, other previous studies dealt with the environmental factors that affect the biodegradation process of pesticides. It proved that each of the incubation periods, pH, and temperature have different effects on biodegradation. Most of the studies indicated that the best incubation period for biodegradation is 7-8

Anticyclone of synoptic studies that influence weather and climate of Iraq, The aim of
the study is to clarify the effect variation of repetition of Anticyclone and effect on thermal
characteristic in Iraq were pressure level has been analyzed (1000) millibars and that because
of pressure level is the closet to the earth surface and the clarity of climatic phenomenon
based on a systematic analysis of synoptic seeking maps and observation and (12:00)
according to timing GMT for five climatic stations which is (Mosul, Kirkuk, Baghdad, Rutba,
and Basra) and so far three consecutive climatic cycles which is first climatic cycle for period
(1986-1976). and second climatic cycle for period (1997-1987) and third climatic cy

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi