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RISS 인기검색어
- 검색키워드
- 저자 : Adil Rasheed (검색결과 3 건)
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Realization of VANET-Based Cloud Services through Named Data Networking
Hussain, Rasheed,Bouk, Safdar H.,Javaid, Nadeem,Khan, Adil M.,Lee, Jooyoung Institute of Electrical and Electronics Engineers 2018 IEEE communications magazine Vol.56 No.8
<P>Connected car technology (also referred to as VANET) has gradually paved its way to legislation in several countries and soon will be followed by mass-scale deployment. However, the race between the advancements in technologies and utilization of the available resources have left a question mark on the future of pure VANET. Therefore, the research community together with academia and industry have foreseen the evolution of VANET into VANET-based clouds. The data- or content-centric communication paradigm is the point of convergence in these technologies because the content is shared among different nodes in different forms such as infotainment or safety. However, the current IP-based networking is not an ideal choice for content-centric applications because of its larger overhead for establishing, maintaining, and securing the path, addressing complexity, non-scalability for content, routing and mobility management overhead, and so on. Therefore, the limitations and shortcomings of current IP-based networking and the need for efficient content delivery advocate for a paradigm shift. To this end, a new content-centric networking paradigm, namely NDN, has been employed to address the aforementioned issues related to content-centric networking while using IP-based networking. In this article, we foresee the integration of VANET-based clouds with NDN called NDN-VC for reliable, efficient, robust, and safe intelligent transportation systems. We particularly aim at the architecture and concise naming mechanism for NDN-VC. Furthermore, we also outline the unique future challenges faced by the NDN-VC.</P>
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M. Salman Siddiqui,Adil Rasheed,Trond Kvamsdal 한국풍공학회 2019 Wind and Structures, An International Journal (WAS Vol.29 No.6
Aerodynamic characteristic of a small scale wind turbine under the influence of an incoming uniform wind field is studied using k-ω Shear Stress Transport turbulence model. Firstly, the lift and drag characteristics of the blade section consisting of S826 airfoil is studied using 2D simulations at a Reynolds number of 1×105. After that, the full turbine including the rotational effects of the blade is simulated using Multiple Reference Frames (MRF) and Sliding Mesh Interface (SMI) numerical techniques. The differences between the two techniques are quantified. It is then followed by a detailed comparison of the turbine's power/thrust output and the associated wake development at three tip speeds ratios (λ = 3, 6, 10). The phenomenon of blockage effect and spatial features of the flow are explained and linked to the turbines power output. Validation of wake profiles patterns at multiple locations downstream is also performed at each λ. The present work aims to evaluate the potential of the numerical methods in reproducing wind tunnel experimental results such that the method can be applied to full-scale turbines operating under realistic conditions in which observation data is scarce or lacking.
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Streamlined semi-automatic data processing framework for ship performance analysis
Gupta Prateek,Kim Young-Rong,Steen Sverre,Rasheed Adil 대한조선학회 2023 International Journal of Naval Architecture and Oc Vol.15 No.-
The hydrodynamic performance of a sea-going ship can be analyzed using data from different sources, like onboard recorded in-service data, AIS data, and noon reports. Each of these sources is known to have its inherent problems. The current work highlights the most prominent issues, explained with examples from actual datasets. A streamlined semi-automatic approach to processing the data is finally outlined, which can be used to prepare a dataset for ship performance analysis. Typical data processing steps like interpolating metocean data, deriving additional features, estimating resistance components, data cleaning, and outlier detection are arranged in the best possible manner not only to streamline the data processing but also to obtain reliable results. A semiautomatic implementation of the data processing framework, with limited user intervention, is used to process the datasets here and present the example plots for various data processing steps, proving the effectiveness of the proposed approach.
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