Base station (BS) sleeping is an effecting way to improve the energy-efficiency of cellular networks. Considering BS sleep mode operation under different scenarios, we focus on three wake-up policies: single vacation ...
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Base station (BS) sleeping is an effecting way to improve the energy-efficiency of cellular networks. Considering BS sleep mode operation under different scenarios, we focus on three wake-up policies: single vacation (SV) policy, multiple vacation (MV) policy and N policy. A hysteresis time is also considered to avoid frequent BS mode-changing operation. By modeling the systems.as M/G/1 vacation queues, we derive two performance measures of interest, expected system response time and energy consumption per bit. The impacts of sleep mode operation parameters and setup time are also studied. In order to determine the optimal parameter settings, which allows for a flexible tradeoff between energy-efficiency and mean delay, a two-step optimization method is proposed. We numerically analyze and investigate the energy-delay tradeoff for different policies, and find that both the MV policy and the N policy have better performance than the SV policy if the sniffing cost is not considered. However, these advantages diminish when the sniffing cost increases.
Is it possible to estimate some 'safety' metric to assess the effectiveness of Intelligent Transportation systems. In particular, we are interested in using Inter-Vehicle Communication (IVC) beaconing for incr...
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This paper presents a novel interactive domain-adaptation technique based on active learning for the classification of remote sensing (RS) images. The proposed method aims at adapting the supervised classifier trained...
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ISBN:
(纸本)9781467311595
This paper presents a novel interactive domain-adaptation technique based on active learning for the classification of remote sensing (RS) images. The proposed method aims at adapting the supervised classifier trained on a given RS source image to make it suitable for classifying a different but related target image. The two images can be acquired in different locations and/or at different times, but present the same set of land-cover classes. The proposed approach iteratively selects the most informative samples of the target image to be labeled by the user and included in the training set, while the source-image samples are re-weighted or possibly removed from the training set on the basis of their disagreement with the target image classification problem. In this way, the consistent information available from the source image can be effectively exploited for the classification of a target image and for guiding the user in the selection of the new samples to be labeled, whereas the inconsistent information is automatically detected and removed. Experimental results on a Very High Resolution (VHR) multispectral dataset confirm the effectiveness of the proposed method.
This paper considers cases where a specific number of nodes in an ad hoc network broadcast video and audio streams over the entire network. For the purpose, we have proposed Load and Battery Charge oriented Flooding (...
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We address the problem of efficient processing of count aggregate queries for spatial objects in OLAP systems. One of the main issues affecting the efficient spatial analysis is the, so called, distinct counting probl...
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Pervasive healthcare applications utilizing body sensor networks generate a vast amount of data that need to be managed and stored for processing and future usage. Cloud computing among with the Internet of Things (Io...
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Interface signs (e.g., navigation links, buttons, icons, thumbnail, etc.), i.e. any element of a user interface, are crucial components to achieve satisfactory usability for web applications. End users typically get t...
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E-learning without the constraints of time and space provide a flexible education environment. However, it leads the students to procrastinate in using the system. The purpose of this work is to find the factors that ...
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This paper shows how some fuzzy logic techniques applied to a recommender engine can be used in a Electronic Medical Records Repository. A Fuzzy Linguistic model based on three dimensions: intrinsic, contextual, perso...
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ISBN:
(纸本)1601322178
This paper shows how some fuzzy logic techniques applied to a recommender engine can be used in a Electronic Medical Records Repository. A Fuzzy Linguistic model based on three dimensions: intrinsic, contextual, personal is proposed. The contextual and personal dimensions are modeled using domain ontologies and a automatically built fuzzy ontology, respectively. The experiment results indicate that the presented approach is useful and warrants further research in recommending and retrieval information.
The rapid evolution of threat ecosystems.and the shifting focus of adversarial actions complicate efforts to assure security of an organization’s computer networks. Efforts to build a rigorous science of security, on...
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