There has been a great deal of research into the considerable challenge of managing of traffic at road junctions; its application to vehicular ad hoc network (VANET) has proved to be of great interest in the developed world. Dynamic topology is one of the vital challenges facing VANET; as a result, routing of packets to their destination successfully and efficiently is a non-simplistic undertaking. This paper presents a MDORA, an efficient and uncomplicated algorithm enabling intelligent wireless vehicular communications. MDORA is a robust routing algorithm that facilitates reliable routing through communication between vehicles. As a position-based routing technique, the MDORA algorithm, vehicles' precise locations are used to establish the optimal route by which the vehicles may reach their desired destinations. By determining the route containing the maximum distance with the minimum number of hops, MDORA minimizes the control overhead. The final aspect of the paper is to compare gains of MDORA with those of existing protocols such as AODV, GPSR-L and HLAR in terms of throughput, packet delivery ratio and average delay. From the analysis, it will be evident that the performance of MDORA is far better than the other protocols.
In globalization, the world became open area to competition for the attractive of investment, and the abilities of each country to win the confidence of investors depend upon the preparation to optimize circumstances. The competitiveness is an essential means of expanding the capacity of developed to coexist in an international environment characterized by globalization. While competition describes the market structure, the behavior of investors and business, competitiveness is interested in the evaluation of business performance or countries and compare them in the conditions of competition available in these markets. Regarding Malaysia, which is depend on FDI-Export- Led Growth strategy, it has taking on diffe
... Show MoreThe current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreThis study was conducted in the botanical garden, Department of biology, College of Science/ Mustansiriyah University in from (15 February to 15 March, 2019) under the natural environmental conditions in the greenhouse in order to evaluate the effectiveness of parsley aqueous extract as a promoter for rooting. The study included the use of aqueous extract of a plant Parsley (Petroselinum crispum) extract was used in concentrations (1.25, 2.5 g / l), compare with IBA in concentration (100 mg / L) with dipping time 24 hour for all treatments. The cutting stems were included Rosmarinus officinalis, Nerium oleander, Olea europaea, Plumeria alba, Hibiscus rosa, Pelargonium graveolens, and Myrtus communis. The following measurements were
... Show MoreAquatic Oligochaeta is an important group of Macroinvertebrates that has been very remarkable as bioindicators for assessing water pollution and determining its degree in water bodies. Hence, the idea of the current study aims at studying the impact of Baghdad effluents on the Tigris River by using oligochaetes community as bioindicators . For this purpose, four sites along the inside of Baghdad has been chosen. Site S1 has been located upstream, site S2 and S3 has been at midstream and site S4 at the downstream of the River.This investigation has used different types of biological indicators, including the percentage of oligochaeta within benthic invertebrates, which ranged from 49.2-51.28%. The highest percentage of the tubificid w
... Show MoreA fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th
... Show MoreAlpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images