280 resultados para Cellular traffic offloading


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Product Ecosystem theory is an emerging theory that shows that disruptive “game changing” innovation is only possible when the entire ecosystem is considered. When environmental variables change faster than products or services can adapt, disruptive innovation is required to keep pace. This has many parallels with natural ecosystems where species that cannot keep up with changes to the environment will struggle or become extinct. In this case the environment is the city, the environmental pressures are pollution and congestion, the product is the car and the product ecosystem is comprised of roads, bridges, traffic lights, legislation, refuelling facilities etc. Each one of these components is the responsibility of a different organisation and so any change that affects the whole ecosystem requires a transdisciplinary approach. As a simple example, cars that communicate wirelessly with traffic lights are only of value if wireless-enabled traffic lights exist and vice versa. Cars that drive themselves are technically possible but legislation in most places doesn’t allow their use. According to innovation theory, incremental innovation tends to chase ever diminishing returns and becomes increasingly unable to tackle the “big issues.” Eventually “game changing” disruptive innovation comes along and solves the “big issues” and/or provides new opportunities. Seen through this lens, the environmental pressures of urban traffic congestion and pollution are the “big issues.” It can be argued that the design of cars and the other components of the product ecosystem follow an incremental innovation approach. That is why the “big issues” remain unresolved. This paper explores the problems of pollution and congestion in urban environments from a Product Ecosystem perspective. From this a strategy will be proposed for a transdisciplinary approach to develop and implement solutions.

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This paper reports profiling information for speeding offenders and is part of a larger project that assessed the deterrent effects of increased speeding penalties in Queensland, Australia, using a total of 84,456 speeding offences. The speeding offenders were classified into three groups based on the extent and severity of an index offence: once-only low-rang offenders; repeat high-range offenders; and other offenders. The three groups were then compared in terms of personal characteristics, traffic offences, crash history and criminal history. Results revealed a number of significant differences between repeat high-range offenders and those in the other two offender groups. Repeat high-range speeding offenders were more likely to be male, younger, hold a provisional and a motorcycle licence, to have committed a range of previous traffic offences, to have a significantly greater likelihood of crash involvement, and to have been involved in multiple-vehicle crashes than drivers in the other two offender types. Additionally, when a subset of offenders’ criminal histories were examined, results revealed that repeat high-range speeding offenders were also more likely to have committed a previous criminal offence compared to once only low-range and other offenders and that 55.2% of the repeat high-range offenders had a criminal history. They were also significantly more likely to have committed drug offences and offences against order than the once only low-range speeding offenders, and significantly more likely to have committed regulation offences than those in the other offenders group. Overall, the results indicate that speeding offenders are not an homogeneous group and that, therefore, more tailored and innovative sanctions should be considered and evaluated for high-range recidivist speeders because they are a high-risk road user group.

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This thesis presents an association rule mining approach, association hierarchy mining (AHM). Different to the traditional two-step bottom-up rule mining, AHM adopts one-step top-down rule mining strategy to improve the efficiency and effectiveness of mining association rules from datasets. The thesis also presents a novel approach to evaluate the quality of knowledge discovered by AHM, which focuses on evaluating information difference between the discovered knowledge and the original datasets. Experiments performed on the real application, characterizing network traffic behaviour, have shown that AHM achieves encouraging performance.

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BACKGROUND: About 1-5% of cancer patients suffer from significant normal tissue reactions as a result of radiotherapy (RT). It is not possible at this time to predict how most patients' normal tissues will respond to RT. DNA repair dysfunction is implicated in sensitivity to RT particularly in genes that mediate the repair of DNA double-strand breaks (DSBs). Phosphorylation of histone H2AX (phosphorylated molecules are known as gammaH2AX) occurs rapidly in response to DNA DSBs, and, among its other roles, contributes to repair protein recruitment to these damaged sites. Mammalian cell lines have also been crucial in facilitating the successful cloning of many DNA DSB repair genes; yet, very few mutant cell lines exist for non-syndromic clinical radiosensitivity (RS). METHODS: Here, we survey DNA DSB induction and repair in whole cells from RS patients, as revealed by gammaH2AX foci assays, as potential predictive markers of clinical radiation response. RESULTS: With one exception, both DNA focus induction and repair in cell lines from RS patients were comparable with controls. Using gammaH2AX foci assays, we identified a RS cancer patient cell line with a novel ionising radiation-induced DNA DSB repair defect; these data were confirmed by an independent DNA DSB repair assay. CONCLUSION: gammaH2AX focus measurement has limited scope as a pre-RT predictive assay in lymphoblast cell lines from RT patients; however, the assay can successfully identify novel DNA DSB repair-defective patient cell lines, thus potentially facilitating the discovery of novel constitutional contributions to clinical RS.

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A systematic literature review and a comprehensive meta-analysis that combines the findings from existing studies, was conducted in this thesis to analyse the impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to investigate the quality, publication bias and outlier bias of the various studies, and the time intervals used to measure traffic characteristics were considered. Based on this comprehensive and systematic review, and the results of the subsequent meta-analysis, major issues in study design, traffic and crash data, and model development and evaluation are discussed.

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Background The analysis of cellular networks and pathways involved in oncogenesis has increased our knowledge about the pathogenic mechanisms that underlie tumour biology and has unmasked new molecular targets that may lead to the design of better anti-cancer therapies. Recently, using a high resolution loss of heterozygosity (LOH) analysis, we identified a number of potential tumour suppressor genes (TSGs) within common LOH regions across cases suffering from two of the most common forms of Non-Hodgkin’s lymphoma (NHL), Follicular Lymphoma (FL) and Diffuse Large B-cell Lymphoma (DLBCL). From these studies LOH of the protein tyrosine phosphatase receptor type J (PTPRJ) gene was identified as a common event in the lymphomagenesis of these B-cell lymphomas. The present study aimed to determine the cellular pathways affected by the inactivation of these TSGs including PTPRJ in FL and DLBCL tumourigenesis. Results Pathway analytical approaches identified that candidate TSGs located within common LOH regions participate within cellular pathways, which may play a crucial role in FL and DLBCL lymphomagenesis (i.e., metabolic pathways). These analyses also identified genes within the interactome of PTPRJ (i.e. PTPN11 and B2M) that when inactivated in NHL may play an important role in tumourigenesis. We also detected genes that are differentially expressed in cases with and without LOH of PTPRJ, such as NFATC3 (nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 3). Moreover, upregulation of the VEGF, MAPK and ERBB signalling pathways was also observed in NHL cases with LOH of PTPRJ, indicating that LOH-driving events causing inactivation of PTPRJ, apart from possibly inducing a constitutive activation of these pathways by reduction or abrogation of its dephosphorylation activity, may also induce upregulation of these pathways when inactivated. This finding implicates these pathways in the lymphomagenesis and progression of FL and DLBCL. Conclusions The evidence obtained in this research supports findings suggesting that FL and DLBCL share common pathogenic mechanisms. Also, it indicates that PTPRJ can play a crucial role in the pathogenesis of these B-cell tumours and suggests that activation of PTPRJ might be an interesting novel chemotherapeutic target for the treatment of these B-cell tumours.

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A number of Intelligent Transportation Systems (ITS) were used with an advanced driving simulator to assess its influence on driving behavior. Three types of ITS interventions namely, Video in-vehicle (ITS1), Audio in-vehicle (ITS2), and On-road flashing marker (ITS3) were tested. Then, the results from the driving simulator were used as inputs for a developed model using a traffic micro-simulation (Vissim 5.4) in order to assess the safety interventions. Using a driving simulator, 58 participants were required to drive through a number of active and passive crossings with and without an ITS device and in the presence or absence of an approaching train. The effect of driver behavior changing in terms of speed and compliance rate was greater at passive crossings than at active crossings. The difference in speed of drivers approaching ITS devices was very small which indicates that ITS helps drivers encounter the crossings in a safer way. Since the current traffic simulation was not able to replicate a dynamic speed change or a probability of stopping that varies based on different ITS safety devices, some modifications of the current traffic simulation were conducted. The results showed that exposure to ITS devices at active crossings did not influence the drivers’ behavior significantly according to the traffic performance indicators used, such as delay time, number of stops, speed, and stopped delay. On the other hand, the results of traffic simulation for passive crossings, where low traffic volumes and low train headway normally occur, showed that ITS devices improved overall traffic performance.