In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route for the transmission of the packets of data in the direction of their destination by taking into consideration the status of the traffic segment when selecting the next intersection. Through this algorithm, a new formula for assessing the status of the segment is presented based on three elements: density, connectivity, and distance. To evaluate this routing algorithm, simulations are performed, once the results are obtained, they are compared with the existing routing algorithms. The evaluation of results offered evidence that our routing algorithm did well in terms of packet delivery ratio and packet delivery delay.
Notwithstanding the importance of international cooperation as the other facet of international interactions, a strategy of conflict resolution, a maintainer of international peace and security, its provision in the United Nations conventions, as an objective of the United Nations after the international peace and security, however, the recognition of international cooperation has not been underlined by global, intellectual think tanks. While realism emphasized on the state's role in achieving international cooperation to ensure mutual and multilateral interests, liberalism focused on the role of international organizations in building such cooperation. Additionally, constructivist approaches developed other sub-variables to contribute to t
... Show MoreThis paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll
... Show MoreFire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20
Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.
This study carry’s out the correlation and the effect of two main variables, these variables are Job Satisfaction included six sub: wages - salaries and justice and yield, working conditions and services, pattern of supervision and the relationship with the manger, Relationship with colleagues, the content of the work and the variety of tasks, development and promotion opportunities available to an individual, and Organizational Performance included two sub variables: Efficiency, Effectiveness. This research was conducted using a questioner as a main tool, This questioner was distributed randomly to a research community composed of
... Show MoreIn this investigative endeavor, a novel concrete variety incorporating sulfur-2,4-dinitrophenylhydrazine modification was developed, and its diverse attributes were explored. This innovative concrete was produced using sulfur-2,4-dinitrophenylhydrazine modification and an array of components. The newly created sulfur-2,4-dinitrophenylhydrazine modifier was synthesized. The surface texture resulting from this modifier was examined using SEM and EDS techniques. The component ratios within concrete, chemical and physical traits derived from the sulfur-2,4-dinitrophenylhydrazine modifier, chemical and corrosion resistance of concrete, concrete stability against water absorption, concrete resilience against freezing, physical and mechanical p
... Show MoreIn aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
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