978 resultados para Flow Vector Tracking


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Double-pass counter flow v-grove collector is considered one of the most efficient solar air-collectors. In this design of the collector, the inlet air initially flows at the top part of the collector and changes direction once it reaches the end of the collector and flows below the collector to the outlet. A mathematical model is developed for this type of collector and simulation is carried out using MATLAB programme. The simulation results were verified with three distinguished research results and it was found that the simulation has the ability to predict the performance of the air collector accurately as proven by the comparison of experimental data with simulation. The difference between the predicted and experimental results is, at maximum, approximately 7% which is within the acceptable limit considering some uncertainties in the input parameter values to allow comparison. A parametric study was performed and it was found that solar radiation, inlet air temperature, flow rate and length have a significant effect on the efficiency of the air collector. Additionally, the results are compared with single flow V-groove collector.

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Diagnostics of rotating machinery has developed significantly in the last decades, and industrial applications are spreading in different sectors. Most applications are characterized by varying velocities of the shaft and in many cases transients are the most critical to monitor. In these variable speed conditions, fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In the past, this issue was often solved by synchronously sampling data by means of phase locked circuits governing the acquisition; however, thanks to the spread of cheap and powerful microprocessors, this procedure is nowadays rarer; sampling is usually performed at constant time intervals, and the conversion to the order domain is made by means of digital signal processing techniques. In the last decades different algorithms have been proposed for the extraction of an order spectrum from a signal sampled asynchronously with respect to the shaft rotational velocity; many of them (the so called computed order tracking family) use interpolation techniques to resample the signal at constant angular increments, followed by a common discrete Fourier transform to shift from the angular domain to the order domain. A less exploited family of techniques shifts directly from the time domain to the order spectrum, by means of modified Fourier transforms. This paper proposes a new transform, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

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Design of hydraulic turbines has often to deal with hydraulic instability. It is well-known that Francis and Kaplan types present hydraulic instability in their design power range. Even if modern CFD tools may help to define these dangerous operating conditions and optimize runner design, hydraulic instabilities may fortuitously arise during the turbine life and should be timely detected in order to assure a long-lasting operating life. In a previous paper, the authors have considered the phenomenon of helical vortex rope, which happens at low flow rates when a swirling flow, in the draft tube conical inlet, occupies a large portion of the inlet. In this condition, a strong helical vortex rope appears. The vortex rope causes mechanical effects on the runner, on the whole turbine and on the draft tube, which may eventually produce severe damages on the turbine unit and whose most evident symptoms are vibrations. The authors have already shown that vibration analysis is suitable for detecting vortex rope onset, thanks to an experimental test campaign performed during the commissioning of a 23 MW Kaplan hydraulic turbine unit. In this paper, the authors propose a sophisticated data driven approach to detect vortex rope onset at different power load, based on the analysis of the vibration signals in the order domain and introducing the so-called "residual order spectrogram", i.e. an order-rotation representation of the vibration signal. Some experimental test runs are presented and the possibility to detect instability onset, especially in real-time, is discussed.

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The transmission path from the excitation to the measured vibration on the surface of a mechanical system introduces a distortion both in amplitude and in phase. Moreover, in variable speed conditions, the amplification/attenuation and the phase shift, due to the transfer function of the mechanical system, varies in time. This phenomenon reduces the effectiveness of the traditionally tachometer based order tracking, compromising the results of a discrete-random separation performed by a synchronous averaging. In this paper, for the first time, the extent of the distortion is identified both in the time domain and in the order spectrum of the signal, highlighting the consequences for the diagnostics of rotating machinery. A particular focus is given to gears, providing some indications on how to take advantage of the quantification of the disturbance to better tune the techniques developed for the compensation of the distortion. The full theoretical analysis is presented and the results are applied to an experimental case.

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This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.

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Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

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While the study of foreign news flows has received considerable attention from communication scholars for quite some time, it has typically focused on political or ‘hard’ news, at the expense of other types of journalistic content. This article argues that, as the foreign news hole is shrinking, travel journalism is becoming an increasingly important source of information about foreign countries in the news media. It reports the results of a comparative study of newspaper travel sections in Australia, Canada, New Zealand, and the UK, and argues that travel journalism often replicates the imbalances found in foreign news flows. Well-known factors – such as regionalism, powerful nations, cultural proximity, the role played by big neighbours and the diversity of coverage – are also powerful determinants in travel journalism. At the same time, a country’s tourist behaviour also plays a role but is often overshadowed by other factors.

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Executive Summary Emergency Departments (EDs) locally, nationally and internationally are becoming increasingly busy. Within this context, it can be challenging to deliver a health service that is safe, of high quality and cost-effective. Whilst various models are described within the literature that aim to measure ED ‘work’ or ‘activity’, they are often not linked to a measure of costs to provide such activity. It is important for hospital and ED managers to understand and apply this link so that optimal staffing and financial resourcing can be justifiably sought. This research is timely given that Australia has moved towards a national Activity Based Funding (ABF) model for ED activity. ABF is believed to increase transparency of care and fairness (i.e. equal work receives equal pay). ABF involves a person-, performance- or activity-based payment system, and thus a move away from historical “block payment” models that do not incentivise efficiency and quality. The aim of the Statewide Workforce and Activity-Based Funding Modelling Project in Queensland Emergency Departments (SWAMPED) is to identify and describe best practice Emergency Department (ED) workforce models within the current context of ED funding that operates under an ABF model. The study is comprised of five distinct phases. This monograph (Phase 1) comprises a systematic review of the literature that was completed in June 2013. The remaining phases include a detailed survey of Queensland hospital EDs’ resource levels, activity and operational models of care, development of new resource models, development of a user-friendly modelling interface for ED mangers, and production of a final report that identifies policy implications. The anticipated deliverable outcome of this research is the development of an ABF based Emergency Workforce Modelling Tool that will enable ED managers to profile both their workforce and operational models of care. Additionally, the tool will assist with the ability to more accurately inform adequate staffing numbers required in the future, inform planning of expected expenditures and be used for standardisation and benchmarking across similar EDs. Summary of the Findings Within the remit of this review of the literature, the main findings include: 1. EDs are becoming busier and more congested Rising demand, barriers to ED throughput and transitions of care all contribute to ED congestion. In addition requests by organisational managers and the community require continued broadening of the scope of services required of the ED and further increases in demand. As the population live longer with more lifestyle diseases their propensity to require ED care continues to grow. 2. Various models of care within EDs exist Models often vary to account for site specific characteritics to suit staffing profile, ED geographical location (e.g. metropolitan or rural site), and patient demographic profile (e.g. paediatrics, older persons, ethnicity). Existing and new models implemented within EDs often depend on the target outcome requiring change. Generally this is focussed on addressing issues at the input, throughput or output areas of the ED. Even with models targeting similar demographic or illness, the structure and process elements underpinning the model can vary, which can impact on outcomes and variance to the patient and carer experience between and within EDs. Major models of care to manage throughput inefficiencies include: A. Workforce Models of Care focus on the appropriate level of staffing for a given workload to provide prompt, timely and clinically effective patient care within an emergency care setting. The studies reviewed suggest that the early involvement of senior medical decision maker and/or specialised nursing roles such as Emergency Nurse Practitioners and Clinical Initiatives Nurse, primary contact or extended scope Allied Health Practitioners can facilitate patient flow and improve key indicators such as length of stay and reducing the number of those who did not wait to be seen amongst others. B. Operational Models of Care within EDs focus on mechanisms for streaming (e.g. fast-tracking) or otherwise grouping patient care based on acuity and complexity to assist with minimising any throughput inefficiencies. While studies support the positive impact of these models in general, it appears that they are most effective when they are adequately resourced. 3. Various methods of measuring ED activity exist Measuring ED activity requires careful consideration of models of care and staffing profile. Measuring activity requires the ability to account for factors including: patient census, acuity, LOS, intensity of intervention, department skill-mix plus an adjustment for non-patient care time. 4. Gaps in the literature Continued ED growth calls for new and innovative care delivery models that are safe, clinically effective and cost effective. New roles and stand-alone service delivery models are often evaluated in isolation without considering the global and economic impact on staffing profiles. Whilst various models of accounting for and measuring health care activity exist, costing studies and cost effectiveness studies are lacking for EDs making accurate and reliable assessments of care models difficult. There is a necessity to further understand, refine and account for measures of ED complexity that define a workload upon which resources and appropriate staffing determinations can be made into the future. There is also a need for continued monitoring and comprehensive evaluation of newly implemented workforce modelling tools. This research acknowledges those gaps and aims to: • Undertake a comprehensive and integrated whole of department workforce profiling exercise relative to resources in the context of ABF. • Inform workforce requirements based on traditional quantitative markers (e.g. volume and acuity) combined with qualitative elements of ED models of care; • Develop a comprehensive and validated workforce calculation tool that can be used to better inform or at least guide workforce requirements in a more transparent manner.

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Covertly tracking mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms requires both visual and acoustic stealth. Whilst the use of robots for stealthy surveillance is not new, the majority only consider navigation for visual covertness. However, most fielded robotic systems have a non-negligible acoustic footprint arising from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. This time-varying acoustic signature can jeopardise any visual covertness and needs to be addressed in any stealthy navigation strategy. In previous work, we addressed the initial concepts for acoustically masking a tracking robot’s movements as it travels between observation locations selected to minimise its detectability by a dynamic natural target and ensuring con- tinuous visual tracking of the target. This work extends the overall concept by examining the utility of real-time acoustic signature self-assessment and exploiting shadows as hiding locations for use in a combined visual and acoustic stealth framework.

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This work is motivated by the desire to covertly track mobile targets, either animal or human, in previously unmapped outdoor natural environments using off-road robotic platforms with a non-negligible acoustic signature. The use of robots for stealthy surveillance is not new. Many studies exist but only consider the navigation problem to maintain visual covertness. However, robotic systems also have a significant acoustic footprint from the onboard sensors, motors, computers and cooling systems, and also from the wheels interacting with the terrain during motion. All these can jepordise any visual covertness. In this work, we experimentally explore the concepts of opportunistically utilizing naturally occurring sounds within outdoor environments to mask the motion of a robot, and being visually covert whilst maintaining constant observation of the target. Our experiments in a constrained outdoor built environment demonstrate the effectiveness of the concept by showing a reduced acoustic signature as perceived by a mobile target allowing the robot to covertly navigate to opportunistic vantage points for observation.

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This paper describes a novel optimum path planning strategy for long duration AUV operations in environments with time-varying ocean currents. These currents can exceed the maximum achievable speed of the AUV, as well as temporally expose obstacles. In contrast to most other path planning strategies, paths have to be defined in time as well as space. The solution described here exploits ocean currents to achieve mission goals with minimal energy expenditure, or a tradeoff between mission time and required energy. The proposed algorithm uses a parallel swarm search as a means to reduce the susceptibility to large local minima on the complex cost surface. The performance of the optimisation algorithms is evaluated in simulation and experimentally with the Starbug AUV using a validated ocean model of Brisbane’s Moreton Bay.

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A new wave energy flow (WEF) map concept was proposed in this work. Based on it, an improved technique incorporating the laser scanning method and Betti’s reciprocal theorem was developed to evaluate the shape and size of damage as well as to realize visualization of wave propagation. In this technique, a simple signal processing algorithm was proposed to construct the WEF map when waves propagate through an inspection region, and multiple lead zirconate titanate (PZT) sensors were employed to improve inspection reliability. Various damages in aluminum and carbon fiber reinforced plastic laminated plates were experimentally and numerically evaluated to validate this technique. The results show that it can effectively evaluate the shape and size of damage from wave field variations around the damage in the WEF map.

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We present a novel approach for multi-object detection in aerial videos based on tracking. The proposed method mainly involves three steps. Firstly, the spatial-temporal saliency is employed to detect moving objects. Secondly, the detected objects are tracked by mean shift in the subsequent frames. Finally, the saliency results are fused with the weight map generated by tracking to get refined detection results, and in turn the modified detection results are used to update the tracking models. The proposed algorithm is evaluated on VIVID aerial videos, and the results show that our approach can reliably detect moving objects even in challenging situations. Meanwhile, the proposed method can process videos in real time, without the effect of time delay.