Vehicular ad hoc network (VANET) is a distinctive form of Mobile Ad hoc Network (MANET) that has attracted increasing research attention recently. The purpose of this study is to comprehensively investigate the elements constituting a VANET system and to address several challenges that have to be overcome to enable a reliable wireless communications within a vehicular environment. Furthermore, the study undertakes a survey of the taxonomy of existing VANET routing protocols, with particular emphasis on the strengths and limitations of these protocols in order to help solve VANET routing issues. Moreover, as mobile users demand constant network access regardless of their location, this study seeks to evaluate various mobility models for vehi

This study aims at identifying the role played by Public Relations in the field of security awareness of the dangers of terrorism. The research is directed to the employees at the Directorate General of Public Relations and Media at the Ministry of Interior. And that on the basis that those who play an important role in the security awareness are the security institutions, primarily the Ministry of Interior, since this Directorate is responsible for all subjects related to the public security using public relations science. It aims at identifying the functions, methods and communication tools used by the Directorate to raise awareness about the dangers of terrorism. In order to achieve the research objectives, the researcher uses the sur

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Motives: Baghdad is the capital city and an important political, administrative, social, cultural and economic centre of Iraq. Baghdad’s growth and development has been significantly influenced by efforts to accommodate various needs of its steadily growing population. Uncontrolled population and urban growth have exerted negative effects in numerous dimensions, including environmental sustainability because urban expansion occurred in green spaces within the city and the surrounding areas.Aim: The aim of this study was to examine the planning solutions in Baghdad’s green areas in the past and at present, and to identify the key changes in the city’s green areas, including changes in the ratio of green urban spaces to the tota

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

The concrete industry consumes millions of tons of aggregate comprising of natural sands and gravels, each year. In recent years there has been an increasing trend towards using recycled aggregate to save natural resources and to produce lightweight concrete. This study investigates the possibility of using waste plastic as one of the components of lead-acid batteries to replace the fine aggregate by 50 and 70% by volume of concrete masonry units. Compared to the reference concrete mix, results demonstrated that a reduction of approximately 32.5% to 39.6% in the density for replacement of 50% to 70% respectively. At 28 days curing age, the compressive strength was decreased while the water absorption increased by increas

The influence of sensing element length of no-core fiber strain sensor has been studied and experimentally demonstrated, four different lengths of 125 μm diameter no-core fiber is fused between two standard single-mode fibers and bi-directionally strained, the highest obtained sensitivity was around 16.37 pm με -1 which was exhibited in the shortest no-core fiber segment, to the best of our knowledge this is the first study of the influence of no-core fiber strain sensors length on sensor sensitivity. The proposed sensor can be used in many opto-mechanical applications such as, structural health monitoring, aerospace vehicles and airplane components monitoring.

In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.