977 resultados para Proximity detectors.


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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

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Purpose Commencing selected workouts with low muscle glycogen availability augments several markers of training adaptation compared with undertaking the same sessions with normal glycogen content. However, low glycogen availability reduces the capacity to perform high-intensity (>85% of peak aerobic power (V·O2peak)) endurance exercise. We determined whether a low dose of caffeine could partially rescue the reduction in maximal self-selected power output observed when individuals commenced high-intensity interval training with low (LOW) compared with normal (NORM) glycogen availability. Methods Twelve endurance-trained cyclists/triathletes performed four experimental trials using a double-blind Latin square design. Muscle glycogen content was manipulated via exercise–diet interventions so that two experimental trials were commenced with LOW and two with NORM muscle glycogen availability. Sixty minutes before an experimental trial, subjects ingested a capsule containing anhydrous caffeine (CAFF, 3 mg-1·kg-1 body mass) or placebo (PLBO). Instantaneous power output was measured throughout high-intensity interval training (8 × 5-min bouts at maximum self-selected intensity with 1-min recovery). Results There were significant main effects for both preexercise glycogen content and caffeine ingestion on power output. LOW reduced power output by approximately 8% compared with NORM (P < 0.01), whereas caffeine increased power output by 2.8% and 3.5% for NORM and LOW, respectively, (P < 0.01). Conclusion We conclude that caffeine enhanced power output independently of muscle glycogen concentration but could not fully restore power output to levels commensurate with that when subjects commenced exercise with normal glycogen availability. However, the reported increase in power output does provide a likely performance benefit and may provide a means to further enhance the already augmented training response observed when selected sessions are commenced with reduced muscle glycogen availability. It has long been known that endurance training induces a multitude of metabolic and morphological adaptations that improve the resistance of the trained musculature to fatigue and enhance endurance capacity and/or exercise performance (13). Accumulating evidence now suggests that many of these adaptations can be modified by nutrient availability (9–11,21). Growing evidence suggests that training with reduced muscle glycogen using a “train twice every second day” compared with a more traditional “train once daily” approach can enhance the acute training response (29) and markers representative of endurance training adaptation after short-term (3–10 wk) training interventions (8,16,30). Of note is that the superior training adaptation in these previous studies was attained despite a reduction in maximal self-selected power output (16,30). The most obvious factor underlying the reduced intensity during a second training bout is the reduction in muscle glycogen availability. However, there is also the possibility that other metabolic and/or neural factors may be responsible for the power drop-off observed when two exercise bouts are performed in close proximity. Regardless of the precise mechanism(s), there remains the intriguing possibility that the magnitude of training adaptation previously reported in the face of a reduced training intensity (Hulston et al. (16) and Yeo et al.) might be further augmented, and/or other aspects of the training stimulus better preserved, if power output was not compromised. Caffeine ingestion is a possible strategy that might “rescue” the aforementioned reduction in power output that occurs when individuals commence high-intensity interval training (HIT) with low compared with normal glycogen availability. Recent evidence suggests that, at least in endurance-based events, the maximal benefits of caffeine are seen at small to moderate (2–3 mg·kg-1 body mass (BM)) doses (for reviews, see Refs. (3,24)). Accordingly, in this study, we aimed to determine the effect of a low dose of caffeine (3 mg·kg-1 BM) on maximal self-selected power output during HIT commenced with either normal (NORM) or low (LOW) muscle glycogen availability. We hypothesized that even under conditions of low glycogen availability, caffeine would increase maximal self-selected power output and thereby partially rescue the reduction in training intensity observed when individuals commence HIT with low glycogen availability.

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In this paper, a framework for isolating unprecedented faults for an EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the recently introduced Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for an EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors.

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In this paper, a recently introduced model-based method for precedent-free fault detection and isolation (FDI) is modified to deal with multiple input, multiple output (MIMO) systems and is applied to an automotive engine with exhaust gas recirculation (EGR) system. Using normal behavior data generated by a high fidelity engine simulation, the growing structure multiple model system (GSMMS) approach is used to construct dynamic models of normal behavior for the EGR system and its constituent subsystems. Using the GSMMS models as a foundation, anomalous behavior is detected whenever statistically significant departures of the most recent modeling residuals away from the modeling residuals displayed during normal behavior are observed. By reconnecting the anomaly detectors (ADs) to the constituent subsystems, EGR valve, cooler, and valve controller faults are isolated without the need for prior training using data corresponding to particular faulty system behaviors.

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The effect of nutrient availability on the acute molecular responses following repeated sprint exercise is unknown. The aim of this study was to determine skeletal muscle cellular and protein synthetic responses following repeated sprint exercise with nutrient provision. Eight healthy young male subjects undertook two sprint cycling sessions (10 × 6 s, 0.75 N m torque kg -1, 54 s recovery) with either pre-exercise nutrient (24 g whey, 4.8 g leucine, 50 g maltodextrin) or non-caloric placebo ingestion. Muscle biopsies were taken from vastus lateralis at rest, and after 15 and 240 min post-exercise recovery to determine muscle cell signalling responses and protein synthesis by primed constant infusion of L-[ring- 13C 6] phenylalanine. Peak and mean power outputs were similar between nutrient and placebo trials. Post-exercise myofibrillar protein synthetic rate was greater with nutrient ingestion compared with placebo ( ? 48%, P<0.05) but the rate of mitochondrial protein synthesis was similar between treatments. The increased myofibrillar protein synthesis following sprints with nutrient ingestion was associated with coordinated increases in Akt-mTOR-S6KrpS6 phosphorylation 15 min post-exercise (?200-600%, P<0.05), while there was no effect on these signalling molecules when exercise was undertaken in the fasted state. For the first time we report a beneficial effect of nutrient provision on anabolic signalling and muscle myofibrillar protein synthesis following repeated sprint exercise. Ingestion of protein/carbohydrate in close proximity to high-intensity sprint exercise provides an environment that increases cell signalling and protein synthesis.

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We examined acute molecular responses in skeletal muscle to divergent exercise stimuli by combining consecutive bouts of resistance and endurance exercise. Eight men [22.9 ± 6.3 yr, body mass of 73.2 ± 4.5 kg, peak O2 uptake (V?O2peak) of 54.0 ± 5.7 ml·kg-1·min-1] were randomly assigned to complete trials consisting of either resistance exercise (8 x 5 leg extension, 80% 1 repetition maximum) followed by a bout of endurance exercise (30 min cycling, 70% V?O2peak) or vice versa. Muscle biopsies were obtained from the vastus lateralis at rest, 15 min after each exercise bout, and after 3 h of passive recovery to determine early signaling and mRNA responses. Phosphorylation of Akt and Akt1Ser473 were elevated 15 min after resistance exercise compared with cycling, with the greatest increase observed when resistance exercise followed cycling (?55%; P < 0.01). TSC2-mTOR-S6 kinase phosphorylation 15 min after each bout of exercise was similar regardless of the exercise mode. The cumulative effect of combined exercise resulted in disparate mRNA responses. IGF-I mRNA content was reduced when cycling preceded resistance exercise (-42%), whereas muscle ring finger mRNA was elevated when cycling was undertaken after resistance exercise (?52%; P < 0.05). The hexokinase II mRNA level was higher after resistance cycling (?45%; P < 0.05) than after cycling-resistance exercise, whereas modest increases in peroxisome proliferator-activated receptor gamma coactivator-1? mRNA did not reveal an order effect. We conclude that acute responses to diverse bouts of contractile activity are modified by the exercise order. Moreover, undertaking divergent exercise in close proximity influences the acute molecular profile and likely exacerbates acute "interference".

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Scanning electrochemical microscopy (SECM), in the substrate generation–tip collection (SG-TC) mode, has been used to detect the cuprous ion intermediate formed during the course of electrodeposition of Cu metal from aqueous solution. Addition of chloride is confirmed to strongly stabilize the ion in aqueous solution and enhance the rate of Cu electrodeposition. This SECM method in the SG-TC mode offers an alternative to the rotating ring disk electrode (RRDE) technique for in situ studies on the effect of plating bath additives in metal electrodeposition. An attractive feature of the SECM relative to the RRDE method is that it allows qualitative aspects of the electrodeposition process to be studied in close proximity to the substrate in a simple and direct fashion using an inexpensive probe, and without the need for forced convection.

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As teacher/researchers interested in the pursuit of socially-just outcomes in early childhood education, the form and function of language occupies a special position in our work. We believe that mastering a range of literacy competences includes not only the technical skills for learning, but also the resources for viewing and constructing the world (Freire and Macdeo, 1987). Rather than seeing knowledge about language as the accumulation of technical skills alone, the viewpoint to which we subscribe treats knowledge about language as a dialectic that evolves from, is situated in, and contributes to a social arena (Halliday, 1978). We do not shy away from this position just because children are in the early years of schooling. In ‘Playing with Grammar’, we focus on the Foundation to Year 2 grouping, in line with the Australian Curriculum, Assessment and Reporting Authority’s (hereafter ACARA) advice on the ‘nature of learners’ (ACARA, 2013). With our focus on the early years of schooling comes our acknowledgement of the importance and complexity of play. At a time where accountability in education has moved many teachers to a sense of urgency to prove language and literacy achievement (Genishi and Dyson, 2009), we encourage space to revisit what we know about literature choices and learning experiences and bring these together to facilitate language learning. We can neither ignore, nor overemphasise, the importance of play for the development of language through: the opportunities presented for creative use and practice; social interactions for real purposes; and, identifying and solving problems in the lives of young children (Marsh and Hallet, 2008). We argue that by engaging young children in opportunities to play with language we are ultimately empowering them to be active in their language learning and in the process fostering a love of language and the intricacies it holds. Our goal in this publication is to provide a range of highly practical strategies for scaffolding young children through some of the Content Descriptions from the Australian Curriculum English Version 5.0, hereafter AC:E V5.0 (ACARA, 2013). This recently released curriculum offers a new theoretical approach to building children’s knowledge about language. The AC:E V5.0 uses selected traditional terms through an approach developed in systemic functional linguistics (see Halliday and Matthiessen, 2004) to highlight the dynamic forms and functions of multimodal language in texts. For example, the following statement, taken from the ‘Language: Knowing about the English language’ strand states: English uses standard grammatical terminology within a contextual framework, in which language choices are seen to vary according to the topics at hand, the nature and proximity of the relationships between the language users, and the modalities or channels of communication available (ACARA, 2013). Put simply, traditional grammar terms are used within a functional framework made up of field, tenor, and mode. An understanding of genre is noted with the reference to a ‘contextual framework’. The ‘topics at hand’ concern the field or subject matter of the text. The ‘relationships between the language users’ is a description of tenor. There is reference to ‘modalities’, such as spoken, written or visual text. We posit that this innovative approach is necessary for working with contemporary multimodal and cross-cultural texts (see Exley and Mills, 2012). We believe there is enormous power in using literature to expose children to the richness of language and in turn develop language and literacy skills. Taking time to look at language patterns within actual literature is a pathway to ‘…capture interest, stir the imagination and absorb the [child]’ into the world of language and literacy (Saxby, 1993, p. 55). In the following three sections, we have tried to remain faithful to our interpretation of the AC:E V5.0 Content Descriptions without giving an exhaustive explanation of the grammatical terms. Other excellent tomes, such as Derewianka (2011), Humphrey, Droga and Feez (2012), and Rossbridge and Rushton (2011) provide these more comprehensive explanations as does the AC:E V5.0 Glossary. We’ve reproduced some of the AC:E V5.0 glossary at the end of this publication. Our focus is on the structure and unfolding of the learning experiences. We outline strategies for working with children in Foundation, Year 1 and Year 2 by providing some demonstration learning experiences based on texts we’ve selected, but maintain that the affordances of these strategies will only be realised when teaching and learning is purposively tied to authentic projects in local contexts. We strongly encourage you not to use only the resource texts we’ve selected, but to capitalise upon your skill for identifying the language features in the texts you and the children are studying and adapt some of the strategies we have outlined. Each learning experience is connected to one of the Content Descriptions from the AC:E V5.0 and contains an experience specific purpose, a suggested resource text and a sequence for the experience that always commences with an orientation to text followed by an examination of a particular grammatical resource. We expect that each of these learning experiences will take a couple if not a few teaching episodes to work through, especially if children are meeting a concept for the first time. We hope you use as much, or as little, of each experience as is needed. Our plans allow for focused discussion, shared exploration and opportunities to revisit the same text for the purpose of enhancing meaning making. We do not want the teaching of grammar to slip into a crisis of irrelevance or to be seen as a series of worksheet drills with finite answers. Strategies for effective practice, however, have much portability. We are both very keen to hear from teachers who are adopting and adapting these learning experiences in their classrooms. Please email us on b.exley@qut.edu.au or lkervin@uow.edu.au. We’d love to continue the conversation with you over time.

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Diagnostics of rolling element bearings is usually performed by means of vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. The aim is to monitor the integrity of the bearing components, in order to avoid catastrophic failures, or to implement condition based maintenance strategies. In particular, the trend in this field is to combine in a single algorithm different signal-enhancement and signal-analysis techniques. Among the first ones, Minimum Entropy Deconvolution (MED) has been pointed out as a key tool able to highlight the effect of a possible damage in one of the bearing components within the vibration signal. This paper presents the application of this technique to signals collected on a simple test-rig, able to test damaged industrial roller bearings in different working conditions. The effectiveness of the technique has been tested, comparing the results of one undamaged bearing with three bearings artificially damaged in different locations, namely on the inner race, outer race and rollers. Since MED performances are dependent on the filter length, the most suitable value of this parameter is defined on the basis of both the application and measured signals. This represents an original contribution of the paper.

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The Bluetooth technology is being increasingly used, among the Automated Vehicle Identification Systems, to retrieve important information about urban networks. Because the movement of Bluetooth-equipped vehicles can be monitored, throughout the network of Bluetooth sensors, this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. Some of the main challenges inherent to Bluetooth data are, first, that Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be estimated. Second, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold: to give an overview of the issues inherent to the Bluetooth technology, through the analysis of the data available from the Bluetooth sensors in Brisbane; and to propose a method for retrieving the itineraries of the individual Bluetooth vehicles. We argue that estimating these latent itineraries, accurately, is a crucial step toward the retrieval of accurate dynamic Origin Destination Matrices.

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At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

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The perceived desirability of water views continues to lead to increasing numbers relocating to coastal regions. Proximity to coastal water brings with it unique risks from rising sea levels; however, water can present a risk in any area, whether or not you have water views. Recent Australian and international disasters show that even inland populations not located in traditional flood areas are not immune from water risks. The author examines the nature of these risks and shows how the internet can be used as a tool in identifying risk areas. The author also highlights the need to ensure accuracy of the data for valuation and planning purposes and identifies flaws in the current data provision.

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This research is in the field of arts education. Eisner claims that ‘teachers rarely view themselves as artists’ (Taylor, 1993:21). Situating professional dance artists and teacher-artists (Mc Lean, 2009) in close proximity to classroom dance teachers, spatially, through a shared rehearsal studio and creatively, by engaging them in a co-artistry approach, allows participants to map unique and new creative processes, kinaesthetically and experientially. This pratice encourages teachers to attune and align themselves with artists’ states of mind and enables them to nurture both their teacher-self and their artist-self (Lichtenstein 2009). The research question was: can interactions between professional dance artists, teacher-artists (Mc Lean, 2009) and classroom dance teachers change classroom dance teachers’ self-perceptions? The research found that Artists in Residence projects provide up-skilling in situ for classroom dance teachers, and give credence to the act of art making for classroom dance teachers within their peer context, positively enhancing their self-image and promoting self-identification as ‘teacher-artists’ (Mc Lean, 2009). This project received an Artist in Residence Grant (an Australia Council for the Arts, Education Queensland and Queensland Arts Council partnership). The research findings were chosen for inclusion in the Queensland Performing Arts Complex program, Feet First: an invitation to dance, 2013 and selected for inclusion on the Creative Campus website, http://www.creative-campus.org.uk.

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Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand causal factors that contribute to these accidents, the Cooperative Research Centre for Rail Innovation is running a project entitled Baseline Level Crossing Video. The project aims to improve the recording of level crossing safety data by developing an intelligent system capable of detecting near-miss incidents and capturing quantitative data around these incidents. To detect near-miss events at railway level crossings a video analytics module is being developed to analyse video footage obtained from forward-facing cameras installed on trains. This paper presents a vision base approach for the detection of these near-miss events. The video analytics module is comprised of object detectors and a rail detection algorithm, allowing the distance between a detected object and the rail to be determined. An existing publicly available Histograms of Oriented Gradients (HOG) based object detector algorithm is used to detect various types of vehicles in each video frame. As vehicles are usually seen from a sideway view from the cabin’s perspective, the results of the vehicle detector are verified using an algorithm that can detect the wheels of each detected vehicle. Rail detection is facilitated using a projective transformation of the video, such that the forward-facing view becomes a bird’s eye view. Line Segment Detector is employed as the feature extractor and a sliding window approach is developed to track a pair of rails. Localisation of the vehicles is done by projecting the results of the vehicle and rail detectors on the ground plane allowing the distance between the vehicle and rail to be calculated. The resultant vehicle positions and distance are logged to a database for further analysis. We present preliminary results regarding the performance of a prototype video analytics module on a data set of videos containing more than 30 different railway level crossings. The video data is captured from a journey of a train that has passed through these level crossings.

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Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. No matter how good is the prediction modeling- the errors in estimation can significantly deteriorate the accuracy and reliability of the prediction. Models have been proposed to estimate travel time from loop detector data. Generally, detectors are closely spaced (say 500m) and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions few detectors malfunction, resulting in increase in the spacing between the functional detectors. Under such conditions, error in the travel time estimation is significantly large and generally unacceptable. This research evaluates the in-practice travel time estimation model during different traffic conditions. It is observed that the existing models fail to accurately estimate travel time during large detector spacing and congestion shoulder periods. Addressing this issue, an innovative Hybrid model that only considers loop data for travel time estimation is proposed. The model is tested using simulation and is validated with real Bluetooth data from Pacific Motorway Brisbane. Results indicate that during non free flow conditions and larger detector spacing Hybrid model provides significant improvement in the accuracy of travel time estimation.