In the present study, semi – batch experiments were conducted to investigate the efficiency of ozone microbubbles (OMBs) in the treatment of aqueous dye solutions methylene orange under different reaction conditions such as  effect of initial solution pH , ozone generation rate and initial MO-concentration. The results showed that the removal of MO by OMBs were very high at the acidic and alkaline media and upon increasing the generation rate of ozone from 0.498 to 0.83 mg/s, the removal efficiency dramatically increased from 75to 100% within 15 min. The rate of oxidation reaction followed a pseudo first- order kinetic model. The results demonstrated that OMBs is efficient in terms of the decline of methylene orange c

     Concentrated research topic in addressing variable vital to the work of offices of inspectors general, construction and scale effectiveness and efficiency is the organizational structure, which are important as is obvious to any researcher in the management and organization and this variable would affect the exercise task supervision and inspection of financial and administrative corruption and combat efficiently, Thus this effect will be placed in the fold ability to achieve goals. That the creation of the organizational structure and requirements to achieve harmony between its properties is creating step towards success. This research aims to analyze the characteristics and style o

This research focused on clarifying the relationship strategic decisions for operations management & performance excellence organizational, The research emerges from a problem which explained by many application questions. Special questionnaire has been prepared for this purpose distributed (72) to sample of  management levels (Top, middle) in the General company for mining industries and aquatic Insullation & the General company of batteries industry, The research has tried to test a number hypotheses related to the relation and regression among the variables of the research, and the differences among the <

The purpose of this study is to measure the levels of quality control for some crude oil products in Iraqi refineries, and how they are close to the international standards, through the application of statistical methods in quality control of oil products in Iraqi refineries. Where the answers of the study sample were applied to a group of Iraqi refinery employees (Al-Dora refinery, Al-Nasiriyah refinery, and Al-Basra refinery) on the principles of quality management control, and according to the different personal characteristics (gender, age, academic qualification, number of years of experience, job level). In order to achieve the objectives of the study, a questionnaire that included (12) items, in order to collect preliminary inform

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

The present study aims at knowing the effect of discussion method for students of fifth grade in preparatory school.

Methodology of the Study:

          In order to achieve the objective of the study, the researcher chooses non-randomly the preparatory school affiliated to the District Chamchamal \ Suliemnaniya. The sample attained 64 students in 32 per group (control and experimental) groups. The researcher used the discussion method which was applied on experimental group. She uses the traditional method on the control group.

The researcher matched the two group in ago, intelligence, marks at the Kurdish Language in the previous year , pretest and posts for the indepe

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121