977 resultados para Data Deduplication Compression


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In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.

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In public transport, seamless coordinated transfer strengthens the quality of service and attracts ridership. The problem of transfer coordination is sophisticated due to (1) the stochasticity of travel time variability, (2) unavailability of passenger transfer plan. However, the proliferation of Big Data technologies provides a tremendous opportunity to solve these problems. This dissertation enhances passenger transfer quality by offline and online transfer coordination. While offline transfer coordination exploits the knowledge of travel time variability to coordinate transfers, online transfer coordination provides simultaneous vehicle arrivals at stops to facilitate transfers by employing the knowledge of passenger behaviours.

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The 3D Water Chemistry Atlas is an intuitive, open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model (formation and aquifer strata). This paper firstly describes the results of evaluating existing virtual globe technologies, which led to the decision to use the Cesium open source WebGL Virtual Globe and Map Engine as the underlying platform. Next it describes the backend database and search, filtering, browse and analysis tools that were developed to enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about coal seam gas extraction, waste water extraction, and water reuse.

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To this point, the collection has provided research-based, empirical accounts of the various and multiple effects of the National Assessment Program – Literacy and Numeracy (NAPLAN) in Australian schooling as a specific example of the global phenomenon of national testing. In this chapter, we want to develop a more theoretical analysis of national testing systems, globalising education policy and the promise of national testing as adaptive, online tests. These future moves claim to provide faster feedback and more useful diagnostic help for teachers. There is a utopian testing dream that one day adaptive, online tests will be responsive in real time providing an integrated personalised testing, pedagogy and intervention for each student. The moves towards these next generation assessments are well advanced, including the work of Pearson’s NextGen Learning and Assessment research group, the Organization for Economic Co-operation and Development’s (OECD) move into assessing affective skills and the Australian Curriculum, Assessment and Reporting Authority’s (ACARA) decision to phase in NAPLAN as an online, adaptive test from 2017...

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High-stakes testing is changing what it means to be a ‘good teacher’ in the contemporary school. This paper uses Deleuze and Guattari's ideas on the control society and dividuation in the context of National Assessment Program Literacy and Numeracy (NAPLAN) testing in Australia to suggest that the database generates new understandings of the ‘good teacher’. Media reports are used to look at how teachers are responding to the high-stakes database through manipulating the data. This article argues that manipulating the data is a regrettable, but logical, response to manifestations of teaching where only the data counts.

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Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

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Resolving species relationships and confirming diagnostic morphological characters for insect clades that are highly plastic, and/or include morphologically cryptic species, is crucial for both academic and applied reasons. Within the true fly (Diptera) family Chironomidae, a most ubiquitous freshwater insect group, the genera CricotopusWulp, 1874 and ParatrichocladiusSantos-Abreu, 1918 have long been taxonomically confusing. Indeed, until recently the Australian fauna had been examined in just two unpublished theses: most species were known by informal manuscript names only, with no concept of relationships. Understanding species limits, and the associated ecology and evolution, is essential to address taxonomic sufficiency in biomonitoring surveys. Immature stages are collected routinely, but tolerance is generalized at the genus level, despite marked variation among species. Here, we explored this issue using a multilocus molecular phylogenetic approach, including the standard mitochondrial barcode region, and tested explicitly for phylogenetic signal in ecological tolerance of species. Additionally, we addressed biogeographical patterns by conducting Bayesian divergence time estimation. We sampled all but one of the now recognized Australian Cricotopus species and tested monophyly using representatives from other austral and Asian locations. Cricotopus is revealed as paraphyletic by the inclusion of a nested monophyletic Paratrichocladius, with in-group diversification beginning in the Eocene. Previous morphological species concepts are largely corroborated, but some additional cryptic diversity is revealed. No significant relationship was observed between the phylogenetic position of a species and its ecology, implying either that tolerance to deleterious environmental impacts is a convergent trait among many Cricotopus species or that sensitive and restricted taxa have diversified into more narrow niches from a widely tolerant ancestor.

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Background The use of compression garments during exercise is recommended for women with breast cancer-related lymphoedema, but the evidence behind this clinical recommendation is unclear. The aim of this randomised, cross-over trial was to compare the acute effects of wearing versus not wearing compression during a single bout of moderate-load resistance exercise on lymphoedema status and its associated symptoms in women with breast cancer-related lymphoedema. Methods Twenty-five women with clinically diagnosed, stable unilateral breast cancer-related lymphoedema completed two resistance exercise sessions, one with compression and one without, in a randomised order separated by a 14 day wash-out period. The resistance exercise session consisted of six upper-body exercises, with each exercise performed for three sets at a moderate-load (10-12 repetition maximum). Primary outcome was lymphoedema, assessed using bioimpedance spectroscopy (L-Dex score). Secondary outcomes were lymphoedema as assessed by arm circumferences (percent inter-limb difference and sum-of-circumferences), and symptom severity for pain, heaviness and tightness, measured using visual analogue scales. Measurements were taken pre-, immediately post- and 24 hours post-exercise. Results There was no difference in lymphoedema status (i.e., L-Dex scores) pre- and post-exercise sessions or between the compression and non-compression condition [Mean (SD) for compression pre-, immediately post- and 24 hours post-exercise: 17.7 (21.5), 12.7 (16.2) and 14.1 (16.7), respectively; no compression: 15.3 (18.3), 15.3 (17.8), and 13.4 (16.1), respectively]. Circumference values and symptom severity were stable across time and treatment condition. Conclusions An acute bout of moderate-load, upper-body resistance exercise performed in the absence of compression does not exacerbate lymphoedema in women with breast cancer-related lymphoedema.

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National pride is both an important and understudied topic with respect to economic behaviour, hence this thesis investigates whether: 1) there is a "light" side of national pride through increased compliance, and a "dark" side linked to exclusion; 2) successful priming of national pride is linked to increased tax compliance; and 3) East German post-reunification outmigration is related to loyalty. The project comprises three related empirical studies, analysing evidence from a large, aggregated, international survey dataset; a tax compliance laboratory experiment combining psychological priming with measurement of heart rate variability; and data collected after the fall of the Berlin Wall (a situation approximating a natural experiment).

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Compelling evidence demonstrates the importance of regular exercise following breast cancer, and this is particularly important for those who develop breast cancer-related lymphoedema. However, fear of lymphoedema exacerbation and the need to wear compression while exercising present as significant barriers for these women. This Master's research evaluated the need for wearing compression during exercise in women with breast cancer-related lymphoedema. Findings demonstrated that exercise performed without compression does not exacerbate lymphoedema or related symptoms. These findings are clinically relevant as they highlight that compression use during exercise should be prescribed on an individual basis, taking into consideration patient preferences and adherence issues.

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Current mobile devices and streaming video services support high definition (HD) video, increasing expectation for more contents. HD video streaming generally requires large bandwidth, exerting pressures on existing networks. New generation of video compression codecs, such as VP9 and H.265/HEVC, are expected to be more effective for reducing bandwidth. Existing studies to measure the impact of its compression on users’ perceived quality have not been focused on mobile devices. Here we propose new Quality of Experience (QoE) models that consider both subjective and objective assessments of mobile video quality. We introduce novel predictors, such as the correlations between video resolution and size of coding unit, and achieve a high goodness-of-fit to the collected subjective assessment data (adjusted R-square >83%). The performance analysis shows that H.265 can potentially achieve 44% to 59% bit rate saving compared to H.264/AVC, slightly better than VP9 at 33% to 53%, depending on video content and resolution.

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Since 2006, we have been conducting urban informatics research that we define as “the study, design, and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical and digital layers of people networks and urban infrastructures” [1]. Various new research initiatives under the label “urban informatics” have been started since then by universities (e.g., NYU’s Center for Urban Science and Progress) and industry (e.g., Arup, McKinsey) worldwide. Yet, many of these new initiatives are limited to what Townsend calls, “data-driven approaches to urban improvement” [2]. One of the key challenges is that any quantity of aggregated data does not easily translate directly into quality insights to better understand cities. In this talk, I will raise questions about the purpose of urban informatics research beyond data, and show examples of media architecture, participatory city making, and citizen activism. I argue for (1) broadening the disciplinary foundations that urban science approaches draw on; (2) maintaining a hybrid perspective that considers both the bird’s eye view as well as the citizen’s view, and; (3) employing design research to not be limited to just understanding, but to bring about actionable knowledge that will drive change for good.

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Big data analysis in healthcare sector is still in its early stages when comparing with that of other business sectors due to numerous reasons. Accommodating the volume, velocity and variety of healthcare data Identifying platforms that examine data from multiple sources, such as clinical records, genomic data, financial systems, and administrative systems Electronic Health Record (EHR) is a key information resource for big data analysis and is also composed of varied co-created values. Successful integration and crossing of different subfields of healthcare data such as biomedical informatics and health informatics could lead to huge improvement for the end users of the health care system, i.e. the patients.

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Huge amount of data are generated from a variety of information sources in healthcare while the data sources originate from a veracity of clinical information systems and corporate data warehouses. The data derived from the above data sources are used for analysis and trending purposes thus playing an influential role as a real time decision-making tool. The unstructured, narrative data provided by these data sources qualify as healthcare big-data and researchers argue that the application of big-data in healthcare might enable the accountability and efficiency.

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Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.