High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination by considering the traffic segment status when choosing the next intersection. RTISAR presents a new formula for assessing segment status based on connectivity, density, load segment, and cumulative distance toward the destination. A verity period mechanism is proposed to denote the projected period when a network failure is likely to occur in a particular segment. This mechanism can be calculated for each collector packet to minimize the frequency of RTISAR execution and to control the generation of collector packets. As a result, this mechanism minimizes the communication overhead generated during the segment status computation process. Simulations are performed to evaluate RTISAR, and the results are compared with those of intersection-based connectivity aware routing and traffic flow oriented routing. The evaluation results provided evidence that RTISAR outperforms in terms of packet delivery ratio, packet delivery delay, and communication overhead.
The role of the green areas lies in being one of the systems that plays the vital role in achieving the environmental dimension besides the socio-cultural body and the economic dimension in the hidden value of ecosystem services. However, many developing countries are characterized by a state of low community environmental awareness, which coincides with the basic need for land for housing and other uses, to take precedence over nature protection strategies. In the absence of clear planning and long-term planning strategies, all this led to abuses and violations of urban land use. In Iraq, the situation became more apparent due to the political, security and social conditions that followed the year 2003. Hence, the resea
... Show MoreThe study focused on explaining urban expansion and sustainable development of urban land and explaining the role of population expansion in Al Hillah city, Al Hillah city in the center of Babylion Governorate located. The study relied on analyzing the population data of the city of Al Hillah for a period of time (22 years) for the period (2000-2022). This data was analyzed and its role in planning and designing residential areas and neighborhoods in the Al Hillah city was analyzed based on the standards of urban planning and sustainable growth of cities. Landsat 5TM was used in the investigation, Landsat 8OLI satellite data to retrieve the NDVI, NDBI, and NDWI. The findings showed th
DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
... Show MoreThe insurance activity in the various countries of the world are important indicators of the strength of the country's economy, he came to study the stages compensation insurance settlement against fire and the importance of investing time risk in achieving the payment of compensation speed, and the implications for the continuation of the insured to carry out insurance with the insurance company, whether working within the public sector or the private sector. Hence the research problem in how quickly insurance companies to pay compensation as soon as possible and the return of the insured to carry out its work and make up for what he died from loss. Intentional sample was selected from branches and divisions and Their assistants manager
... Show MoreIn today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har
... Show MoreThe study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreAutomated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health
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