765 resultados para handover effectiveness


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Handover performance is critical to support real-time traffic applications in wireless network communications. The longer the handover delay is, the longer an Mobile Node (MN) is prevented from sending and receiving any data packet. In real-time network communication applications, such as VoIP and video-conference, a long handover delay is often unacceptable. In order to achieve better handover performance, Fast Proxy Mobile IPv6 (FPMIPv6) has been standardised as an improvement to the original Proxy Mobile IPv6 (PMIPv6) in the Internet Engineering Task Force (IETF). The FPMIPv6 adopts a link layer triggering mechanism to perform two modes of operation: predictive and reactive modes. Using the link layer triggering, the handover performance of the FPMIPv6 can be improved in the predictive mode. However, an unsuccessful predictive handover operation will lead to activation of a reactive handover. In the reactive mode, MNs still experience long handover delays and a large amount of packet loss, which significantly degrade the handover performance of the FPMIPv6. Addressing this problem, this thesis presents an Enhanced Triggering Mechanism (ETM) in the FPMIPv6 to form an enhanced FPMIPv6 (eFPMIPv6). The ETM reduces the most time consuming processes in the reactive handover: the failed Handover Initiate (HO-Initiate) delay and bidirectional tunnel establishment delay. Consequently, the overall handover performance of the FPMIPv6 is enhanced in the eFPMIPv6. To show the advantages of the proposed eFPMIPv6, a theoretical analysis is carried out to mathematically model the performance of PMIPv6, FPMIPv6 and eFPMIPv6. Extensive case studies are conducted to validate the effectiveness of the presented eFPMIPv6 mechanism. They are carried out under various scenarios with changes in network link delay, traffic load, number of hops and MN moving velocity. The case studies show that the proposed mechanism ETM reduces the reactive handover delay, and the presented eFPMIPv6 outperforms the PMIPv6 and FPMIPv6 in terms of the overall handover performance.

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International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

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This paper investigates the effectiveness of virtual product placement as a marketing tool by examining the relationship between brand recall and recognition and virtual product placement. It also aims to address a gap in the existing academic literature by focusing on the impact of product placement on recall and recognition of new brands. The growing importance of product placement is discussed and a review of previous research on product placement and virtual product placement is provided. The research methodology used to study the recall and recognition effects of virtual product placement are described and key findings presented. Finally, implications are discussed and recommendations for future research provided.

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The effectiveness of higher-order spectral (HOS) phase features in speaker recognition is investigated by comparison with Mel Cepstral features on the same speech data. HOS phase features retain phase information from the Fourier spectrum unlikeMel–frequency Cepstral coefficients (MFCC). Gaussian mixture models are constructed from Mel– Cepstral features and HOS features, respectively, for the same data from various speakers in the Switchboard telephone Speech Corpus. Feature clusters, model parameters and classification performance are analyzed. HOS phase features on their own provide a correct identification rate of about 97% on the chosen subset of the corpus. This is the same level of accuracy as provided by MFCCs. Cluster plots and model parameters are compared to show that HOS phase features can provide complementary information to better discriminate between speakers.