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 continued acceleration in the business environment has led to the need for organizations great attention to quality applied in organizations to meet the needs of customers and stay in the market for as long as possible.
Search launched from the underlying problem is the presence of concentrations of defects and waste plaguing the company and to achieve the goal of the study detects the level of quality applied in the factory vessels and reservoirs of the General Company for Heavy Engineering Equipment, As well as calculate wastage rates occurring in the production process and find a relationship between the level of quality and ratios defective in each type of waste, it has been used quantitative meas
... Show MoreNanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper ions by technology of permeable reactive barrier (PRB). Sewage sludge was the source of the humic acid to prepare the coated sand by humic acid—iron oxide (CSHAIO) sorbent; so, this work is consistent with sustainable development. For 10 mg/L metal concentration, batch tests at speed of 200 rpm signified that the removal efficiencies are greater than 90% at sorbent dosage 0.25 g/ 50 mL, pH 6 and contact time 1 h. The kinetic data was well described by the Pseudo first-order model indicating that physicosorption is the predominant mechanism. The maximum adsorption capacities (qmax) were c
... Show MoreLiquid-crystalline organic semiconductors exhibit unique properties that make them highly interesting for organic optoelectronic applications. Their optical and electrical anisotropies and the possibility to control the alignment of the liquid-crystalline semiconductor allow not only to optimize charge carrier transport, but to tune the optical property of organic thin-film devices as well. In this study, the molecular orientation in a liquid-crystalline semiconductor film is tuned by a novel blading process as well as by different annealing protocols. The altered alignment is verified by cross-polarized optical microscopy and spectroscopic ellipsometry. It is shown that a change in alignment of the
The aim of the research is to determine the requirements for developing the technical capabilities of the agricultural extension service providers to face the effects of climatic changes in Baghdad Governorate, to achieve the goal of the research and in order to obtain the respondents’ approval of the requirements (28) requirements were identified in the light of the literature and studies related to the subject and the opinions of specialists to develop the technical capabilities of the agricultural extension service providers distributed on two axes (the ability to know the effects of climate changes, the ability to know the practices to reduce the effects of climate changes). The
Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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