Modal verbs are also called auxiliary verbs, helping verbs and modal auxiliaries. They are special auxiliary verbs that express the degree /of certainty of the action in the sentence, attitude or opinion of the writer concerning the action. These auxiliary verbs are can, could ,may, might, must, ought to, shall, should, will, would and had better. Modality is one of the most difficult aspects of learning English, because the form of modals does not follow the conventional rules of grammar, and there are so many meanings of modals that students often get confused about which modal to use. Also, many EFL learners face difficulty in choosing the proper modal verb that fit certain situations because each modal verb has many functions. The pr

This investigation is a study of the length of time where drops can exist at an oil-water interface before coalescence take place with a bulk of the same phase as the drops. Many factors affecting the time of coalescence were studied in is investigation which included: dispersed phase flow rate, continuous phase height, hole size in distributor, density difference between phases, and viscosity ratio of oil/water systems, employing three liquid/liquid systems; kerosene/water, gasoil/water, and hexane/water. Higher value of coalescence time was 8.26 s at 0.7ml/ s flow rate, 30cm height and 7mm diameter of hole for gas oil/water system, and lower value was 0.5s at 0.3ml/s flow rate, 10 cm height and 3mm diameter of hole for  hexane

Abstract

            Sovereign wealth funds are an important tool for achieving economic stability and avoiding the local economy from external shocks, including the shocks of international oil prices. The spread of these funds is the result of large current account surpluses in many Asian and oil-exporting economies. These surpluses are due to higher commodity prices Has led to a rapid accumulation of foreign assets in central banks. Many countries with rent economies face the problem of their dependence on non-renewable natural resources, especially the oil countries, including Iraq. Oil revenues are more than 97% of oil exports, so they suffer from structural imbal

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

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

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database