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 economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

field of modern and contemporary Yemeni history, accomplished at Ibn Rushd College of Education, University of Baghdad. It was determined according to a time frame in the years 1989, which is the date of completion of the first master’s thesis in the field of modern and contemporary Yemeni history, which deals with the subject of “Iraqi-Yemeni relations 1932- 1962”, and the year 2020, which is the year of completion of a master’s thesis on the position of Iraqi public opinion on the Egyptian military intervention in Yemen (1962-1970). The study determined the nature of these studies, whether they were in the form of master’s theses or doctoral dissertations, or research and studies published in issues of the refereed scien

The study included general survey of some districts of Iraq in order to determinate new distribution areas for 33 species of the genus salvia L. ,new collections obtained , new locations for many species recorded. Observed specimens in most Iraqi herbaria were studies and identified. ,the flowering period were also studied

The study included general survey of some districts of Iraq in order to determinate new distribution areas for 33 species of the genus salvia L. ,new collections obtained , new locations for many species recorded. Observed specimens in most Iraqi herbaria were studies and identified. ,the flowering period were also studied