4,918 research outputs found
Link dependent origin-destination matrix estimation : nonsmooth convex optimisation with Bluetooth-inferred trajectories
No full textThis thesis tackles the traditional transport engineering problem of urban traffic demand estimation by using Bluetooth data and advanced signal processing algorithms. It proposes a method to recover vehicles trajectories from Bluetooth detectors and combining vehicle trajectories with traditional traffic datasets, traffic is estimated at a city level using signal processing algorithms. Involving new technologies in traffic demand estimation gave an opportunity to rethink traditional approaches and to come up with new method to jointly estimate origin-destinations flows and route flows. The whole methodology has been applied and evaluated with real Brisbane traffic data
Gabriel Ajak Lat
Full text linkabstract: Gabriel was ten years old when he left his village.
“Lost Boys Found” is an ongoing, interdisciplinary project that is collecting, recording and archiving the oral histories of the Lost Boys/Girls of Sudan. The collection is a work-in-progress, seeking to record the oral history of as many Lost Boys/Girls as are willing, and will be used in a future book.Age: 27Region: Bahr al GhazalThis picture and bio was donated to the Lost Boys Found project from The Arizona Lost Boys Cente
Towards the retrieval of accurate OD matrices from Bluetooth data : lessons learned from 2 years of data
No full textThe Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the 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 extracted from the data. Finally, 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. \ud
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The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks
Providence College Faculty Author Series 2013-2014: Fr. Gabriel Pivarnik
Full text linkIn this installment, Fr. Gabriel Pivarnik discusses his book Toward a Trinitarian Theology of Liturgical Participation and his reflections on the history of active participation within the Catholic Church
Providence College Faculty Author Series 2013-2014: Fr. Gabriel Pivarnik
No full textIn this installment, Fr. Gabriel Pivarnik discusses his book Toward a Trinitarian Theology of Liturgical Participation and his reflections on the history of active participation within the Catholic Church
Manuscript Poem "John Keats" by Dante Gabriel Rossetti
No full textabstract: Concerning the manuscript for "John Keats".Publication Details: Not the same version as some published versions of "John Keats."Curator's Note: Handwriting in upper right corner reads "Rossetti's Handwriting." Writing on verso reads "Dante Gabriel Rossetti. Mss.
British Museum Reader's Ticket of Dante Gabriel Rossetti
No full textabstract: Concerning a Reader's Ticket of Dante Gabriel Rossetti.Transcription Details: Card reads:
Poet's article 8 {? Nap.} /661
{?dilk Gllucci}
Aug 10 DG RossettiCreation Date Details: Undated range is the author's lifespan. Date and month listed on ticket read "Aug 10.
Remaining-Useful-Life prognostics for opportunistic grouping of maintenance of landing gear brakes for a fleet of aircraft
No full textSeveral studies have proposed Remaining-Useful-Life (RUL) prognostics for aircraft components in the last years. However, few studies focus on integrating these RUL prognostics into maintenance planning frameworks. This paper proposes an optimization model for opportunistic maintenance scheduling of aircraft components that integrates RUL prognostics and that groups the maintenance of these components to reduce costs. We illustrate our approach for the maintenance of a fleet of aircraft, each equipped with multiple landinggear brakes. RUL prognostics for the landing gear brakes are obtained using a Bayesian regression model. Based on these RUL prognostics, we group the replacement of brakes using an integer linear program. As a result, we obtain a cost-optimal RUL-driven opportunistic-maintenance schedule for the brakes of a fleet of aircraft. Compared with traditional maintenance strategies, our approach leads to a reduction of up to 20% of the total maintenance costs.Air Transport & Operation
Novel metrics to evaluate probabilistic remaining useful life prognostics with applications to turbofan engines
No full textWell-established metrics such as the Root Mean Square Error or the Mean Absolute Error are not suitable to evaluate estimated distributions of the Remaining Useful Life (i.e., probabilistic prognostics). We therefore propose novel metrics to evaluate the quality of probabilistic Remaining Useful Life prognostics. We estimate the distribution of the Remaining Useful Life of turbofan engines using a Convolutional Neural Network with Monte Carlo dropout. The accuracy and sharpness of the obtained probabilistic prognostics are evaluated using the Continuous Ranked Probability Score (CRPS) and weighted CRPS. The reliability of the obtained probabilistic prognostics is evaluated using the α-Coverage and the Reliability Score. The results show that the estimated distributions of the Remaining Useful Life of turbofan engines are accurate, reliable and sharp when using a Convolutional Neural Network with Monte Carlo dropout. In general, the proposed metrics are suitable to evaluate the accuracy, sharpness and reliability of probabilistic Remaining Useful Life prognostics.Air Transport & Operation
Retrieving dynamic origin-destination matrices from Bluetooth data
No full textThe 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.\ud
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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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