The use of deep learning.

Pollution of the aquatic environment and the depletion of the natural resource cause imbalance in the natural balance of the river environment and contributes to the deterioration of life and the killing of living organisms. Most of the old and modern cities and urban centers were set up close to the rivers because water enters the main lifeblood and all its facilities. The proximity of cities to rivers caused environmental problems resulting from the dumping of residues of these cities to a large and continuous, these wastes include all uses of the city (industrial, agricultural, residential and commercial) and others. The accumulation of these wastes inside the rivers water kills life and makes them unsuitable for various uses to bury

The aim of this study to identify patterns of cerebral control (right and left) for second grade students in the collage of physical education and sports science of the University of Baghdad, as well as identify the definition of theThe Effect of Using the Bybee Strategy(5ES) according to Brain Control Patterns in Learning a Kinetic Series on Floor exercises in Artistic Gymnastics for menمجلة الرياضة المعاصرةالمجلد 19 العدد 1 عام 2020effect using the (Bybee) strategy (5ES) according to brain control patterns inlearning a Kinetic series on floor exercises In artistic gymnastics for men, andidentify the best combination between the four research groups learn, use Finderexperimental method research sample consi

The aim of the study was to identify the use of the strategies of numbered heads and brainstorming in learning handspring on the Vault table in artistic gymnastics for Men for the third grade students in the collage of Physical Education and Sport Sciences, as well as to identify the best group among the three research groups (number of heads numbered,, brainstorming strategies And the traditional style group) to learn the skill under study. Using the experimental method, the research subject included the third grade students in the collage of Physical Education and Sports Sciences / University of Baghdad, and randomly by lot, 12 students were selected for each of the three research groups. The study consisted of the arithmetic mean

في هذا البحث نحاول تسليط الضوء على إحدى طرائق تقدير المعلمات الهيكلية لنماذج المعادلات الآنية الخطية والتي تزودنا بتقديرات متسقة تختلف أحيانا عن تلك التي نحصل عليها من أساليب الطرائق التقليدية الأخرى وفق الصيغة العامة لمقدرات K-CLASS. وهذه الطريقة تعرف بطريقة الإمكان الأعظم محدودة المعلومات "LIML" أو طريقة نسبة التباين الصغرى"LVR

This work aimed to estimate the frequency of mitochondrial inborn errors of metabolism (MIEMs) in patients presenting with family history and IEM-picture who referred for advance IEM assay in Mosul province and Kurdistan region. This study was observational study conducted on 364 cases referred from different general /or private pediatric clinics with unexplained sign and symptoms and suspension of mitochondrial dysfunction. The study included 364 children with an age ranging from 1 month to 1 year. Started from January 2018 to January 2020. All patients referred with their full history review, notes about their clinical examination, and laboratory investigations including blood ammonia, serum lactate/ pyruvate, arterial blood gases. In

An isolate of Leishmania major was grown on the semisolid medium and incubated at 26ºC. The isolate was irradiated by He: Ne laser (632.8 nm, 10 mW) at exposure times (5, 10, 15, 20, 25, 30) minutes in their respective order. The unirradiated groups represent control group. Growth rate and percentage of viability were examined during six days after irradiation. The change in these two parameters reflects the effect of irradiation on the parasite. The results refers that the general growth effected by irradiation in comparison with un irradiation group, The growth rate of parasite decrease with increasing the exposure time in comparison with control group. Parasite viability decrease with irradiation and the percentage of living cell dec

The Migration is one of the important dynamic population movement phenomena in population studies because of its great impact in changing many demographic characteristics between the region of origin and arrival. And the multiplicity of forms and types according to the different reasons for it and the motives that prompted the population to move, as well as the currents and their size are also different according to the different causes, and here there are many types of migration, and many of them have been studied at the local and regional levels, and as long as the population is in a continuous dynamic movement, other types of migration are generated. (Al Douri, 2015, 230)          &nbs

Embracing digital technological advancements in media and communication has led government entities to adopt communication practices fully aligned with the digital and networked system in government communication. Traditional media practices within the government environment increasingly rely on the ability to utilize digital tools and systems for content creation, communication, evaluation, and the management of the entire communication process within an electronic and intelligent framework for government services. Naturally, this transformation has caught the attention of communication and public relations researchers worldwide, as the digital and networked aspects of government communication now form an intelle

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and