Abstract:

The current research included " Diagnosis of the reality of the gap for the requirements of Business Continuity Management System According to International Standard (ISO 22301: 2012) in Midland Refineries Company (Daura Refinery) " , for development of an administrative system for Business Continuity is considered a priority in the present day, and in the light of the organizations dependence on computers and information technology in work and communication with others . the international legitimacy (represented by the international organization for standardization (ISO)) remains the basis for matching and commitment , and the importance of the application of Business Continuity Management Syst

Abstract:
This research aims to the importance of oil in achieving economic
security in the Arab. Oil is not an ordinary subject and returns it significance to
the followings:
1. The importance of skipping a source of energy.
2. The importance of oil as raw material for petrochemical industry.
3. The importance of the oil sector as an area of foreign investment
4. The importance of oil in the marketing activities, transport, insurance
and various services
In addition to the importance of oil in general and the Arab oil has
additional strategic advantages such as geographic location, And the
magnitude of reserves and production of heavy investment costs are relatively
simple, And the ability to meet the

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

Seeking pharmacist advice about minor ailments is a common practice among Iraqi patients because such advice is free and quick. Unfortunately, the assessment and management of minor ailments by Iraqi pharmacists were inappropriate. Therefore, this study aimed to develop a model for a mobile application that can assist community pharmacists in the diagnosis and management of minor ailments.

This research began by explaining its variables and dimensions especially the digital gap, which the authors explained it elaborately beginning with the concept, the reasons blind its emergence of its measurement, and how to treat it. The authors supposed the potentiality of relying on enforcing knowledge in general and the groups suffer from this gap in particular, especially the targeted knowledge to treat its subject.

As enforcing knowledge usually depends on some strategies or choices of organizational orientation among them is learning and training from one side, and communication, as an indicating factor for organizational effectiveness as the authors refer from the other side.

A mathematical eco-epidemiological model consisting of harvested prey–predator system involving fear and disease in the prey population is formulated and studied. The prey population is supposed to be separated into two groups: susceptible and infected. The susceptible prey grows logistically, whereas the infected prey cannot reproduce and instead competes for the environment’s carrying capacity. Furthermore, the disease is transferred through contact from infected to susceptible individuals, and there is no inherited transmission. The existence, positivity, and boundedness of the model’s solution are discussed. The local stability analysis is carried out. The persistence requirements are established. The global behavior of th

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

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases