903 resultados para WBAN Bluetooth Wearable Sensors Cupid RTOS RTX RL-ARM cortex-m4 WSN parkinson
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Travel time in an important transport performance indicator. Different modes of transport (buses and cars) have different mechanical and operational characteristics, resulting in significantly different travel behaviours and complexities in multimodal travel time estimation on urban networks. This paper explores the relationship between bus and car travel time on urban networks by utilising the empirical Bluetooth and Bus Vehicle Identification data from Brisbane. The technologies and issues behind the two datasets are studied. After cleaning the data to remove outliers, the relationship between not-in-service bus and car travel time and the relationship between in-service bus and car travel time are discussed. The travel time estimation models reveal that the not-in-service bus travel time are similar to the car travel time and the in-service bus travel time could be used to estimate car travel time during off-peak hours
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This report is the eight deliverable of the Real Time and Predictive Traveller Information project and the third deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. Brisbane arterial network is highly equipped with Bluetooth MAC Scanners, which can provide travel time information. Literature is limited with the knowledge on the Bluetooth protocol based data acquisition process and accuracy and reliability of the analysis performed using the data. This report expands the body of knowledge surrounding the use of data from Bluetooth MAC Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.
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In this paper, we report the development of novel Pt/nanostructured RuO2/SiC Schottky diode based sensors for hydrogen gas applications. The nanostructured ruthenium oxide thin films were deposited on SiC substrates using radio frequency sputtering technique. Scanning electron microscopy revealed the sputtered RuO2 layer consists of nano-cubular structures with dimensions ranging between 10 and 50 nm. X-ray diffraction confirmed the presence of tetragonal ruthenium (IV) oxide, with preferred orientation along the (101) lattice plane. The current-voltage characteristics of the sensors were investigated towards hydrogen gas in synthetic air at different temperatures from 25 °C to 240 °C. The dynamic responses of the sensors were studied at an optimum temperature of 240 °C and a voltage shift of 304 mV was recorded toward 1% hydrogen gas.
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In this paper, a comparative study of Pt/nanostructured MoO3/SiC Schottky diode based hydrogen gas sensors is presented. MoO3 nanostructured films with three different morphologies (nanoplatelets, nanoplateletsnanowires and nano-flowers) were deposited on SiC by thermal evaporation. We compare the current-voltage characteristics and the dynamic response of these sensors as they are exposed to hydrogen gas at temperatures up to 250°C. Results indicate that the sensor based on MoO3 nanoflowers exhibited the highest sensitivity (in terms of a 5.79V voltage shift) towards 1% hydrogen; while the sensor based on MoO3 nanoplatelets showed the quickest response (t90%- 40s).
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An oriented graphitic nanostructured carbon film has been employed as a conductometric hydrogen gas sensor. The carbon film was energetically deposited using a filtered cathodic vacuum arc with a -75 V bias applied to a stainless steel grid placed 1cm from the surface of the Si substrate. The substrate was heated to 400°C prior to deposition. Electron microscopy showed evidence that the film consisted largely of vertically oriented graphitic sheets and had a density of 2.06 g/cm3. 76% of the atoms were bonded in sp2 or graphitic configurations. A change in the device resistance of >; 1.5% was exhibited upon exposure to 1 % hydrogen gas (in synthetic, zero humidity air) at 100°C. The time for the sensor resistance to increase by 1.5 % under these conditions was approximately 60 s and the baseline (zero hydrogen exposure) resistance remained constant to within 0.01% during and after the hydrogen exposures.
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Pt/nanostructured ZnO/SiC Schottky contact devices were fabricated and characterized for hydrogen gas sensing. These devices were investigated in reverse bias due to greater sensitivity, which attributes to the application of nanostructured ZnO. The current-voltage (I-V) characteristics of these devices were measured in different hydrogen concentrations. Effective change in the barrier height for 1% hydrogen was calculated as 27.06 meV at 620°C. The dynamic response of the sensors was also investigated and a voltage shift of 325 mV was recorded at 620°C during exposure to 1% hydrogen in synthetic air.
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Objectives: Little is known about young adult women's experience of unintended pregnancy in Australia, nor the extent to which ineffective contraceptive use or contraceptive failure may lead to young women becoming pregnant. The CUPID study is the first in Australia to examine young adult Australian women's patterns of contraceptive use, their experience of unintended pregnancy, and their use (or not) of contraception at the time of conception. Methods: Australian women aged 18-23 years completed an online survey about contraceptive use and experience of unintended pregnancy. They were recruited through a range of methods including advertising on Facebook, and snowball sampling. Sample representativeness was established through comparison with Census data. Results: Of the 511 respondents, 403 women reported that they had ever had sex and were not currently pregnant. Among these women, the pill was the most common method of contraception used on the most recent occasion, used alone (30%) or with condoms (21%). Condoms (alone or with another method other than the pill) were used by a further 17%, and long-acting contraceptive methods by a further 16%. Other methods such as natural methods or partner vasectomy were used by 16%. The withdrawal method was surprisingly common and was mentioned by 15% of the women overall, usually in combination with another method. There were 63 women who had been pregnant, including 5 who were pregnant at the time of the survey, and of these 55 (87%) had become pregnant by accident. Of these 55 women, 69% reported using a range of contraception methods when they became pregnant by accident: Pill only (29%) and in combination with condoms (3%) and withdrawal (5%); condoms only (18%) and in combination with withdrawal (16%); emergency contraceptive pill only (3%) and in combination with withdrawal (3%) and withdrawal only (24%). Conclusions: This study highlighted the use of less effective methods of contraception among young Australian women. The withdrawal method was commonly used, often in combination with other methods, particularly before an unintended pregnancy. Among the women who had been pregnant, most reported that their pregnancy had been unintended. A third of the young women who had experienced an unintended pregnancy were using the withdrawal method. Further research is needed about the place of the withdrawal method in the contraceptive practices of young women.
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An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs). Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV. This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management.
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This article describes the architecture of a monitoring component for the YAWL system. The architecture proposed is based on sensors and it is realized as a YAWL service to have perfect integration with the YAWL systems. The architecture proposed is generic and applicable in different contexts of business process monitoring. Finally, it was tested and evaluated in the context of risk monitoring for business processes.
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The invited presentation was delivered at Queensland Department of Main Roads, Brisbane Australia, 17th June 2013
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Recently there has been significant interest of researchers and practitioners on the use of Bluetooth as a complementary transport data. However, literature is limited with the understanding of the Bluetooth MAC Scanner (BMS) based data acquisition process and the properties of the data being collected. This paper first provides an insight on the BMS data acquisition process. Thereafter, it discovers the interesting facts from analysis of the real BMS data from both motorway and arterial networks of Brisbane, Australia. The knowledge gained is helpful for researchers and practitioners to understand the BMS data being collected which is vital to the development of management and control algorithms using the data.
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Literature is limited in its knowledge of the Bluetooth protocol based data acquisition process and in the accuracy and reliability of the analysis performed using the data. This paper extends the body of knowledge surrounding the use of data from the Bluetooth Media Access Control Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.
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Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging. Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction. The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.
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In many bridges, vertical displacements are one of the most relevant parameters for structural health monitoring in both the short- and long-terms. Bridge managers around the globe are always looking for a simple way to measure vertical displacements of bridges. However, it is difficult to carry out such measurements. On the other hand, in recent years, with the advancement of fibre-optic technologies, fibre Bragg grating (FBG) sensors are more commonly used in structural health monitoring due to their outstanding advantages including multiplexing capability, immunity of electromagnetic interference as well as high resolution and accuracy. For these reasons, a methodology for measuring the vertical displacements of bridges using FBG sensors is proposed. The methodology includes two approaches. One of which is based on curvature measurements while the other utilises inclination measurements from successfully developed FBG tilt sensors. A series of simulation tests of a full-scale bridge was conducted. It shows that both approaches can be implemented to measure the vertical displacements for bridges with various support conditions, varying stiffness along the spans and without any prior known loading. A static loading beam test with increasing loads at the mid-span and a beam test with different loading locations were conducted to measure vertical displacements using FBG strain sensors and tilt sensors. The results show that the approaches can successfully measure vertical displacements.
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This thesis investigates condition monitoring (CM) of diesel engines using acoustic emission (AE) techniques. The AE signals recorded from a small size diesel engine are mixtures of multiple sources from multiple cylinders. Thus, it is difficult to interpret the information conveyed in the signals for CM purposes. This thesis develops a series of practical signal processing techniques to overcome this problem. Various experimental studies conducted to assess the CM capabilities of AE analysis for diesel engines. A series of modified signal processing techniques were proposed. These techniques showed promising results of capability for CM of multiple cylinders diesel engine using multiple AE sensors.