81 research outputs found
Wavenumber-frequency spectrum estimation of ambient seismic noise
No full textIn oil and gas exploration, seismic arrays are deployed by geophycisists to image the subsurface. For passive seismic applications, the data recorded by the sensor array may contain velocity and angle information of the propagating seismic wave. This information can be used to infer the properties of material in different earth layers. In order to find the velocity and arrival angle, beamforming algorithms are applied to estimate the wavenumber-frequency spectrum for the seismic signals. The propagating seismic wave field consists of body waves and surface waves. In some applications, surface waves are interpreted as noise, thus filtering is required to remove the surface waves before or during the implemention of beamforming algorithms. In this thesis, we first introduce a data model. Then several beamforming algorithms based on the data model are discussed, and the performance of the different algorithms is evaluated. Capon beamforming as adopted in seismics has limitations. Robust Capon beamforming which can overcome these limitations is explained in the thesis. For filtering of the surface waves, we propose to first reconstruct the irregularly sampled spatial signal into a uniform array, then design a velocity filter to remove the unwanted low-speed noise (surface waves).TelecommunicationsElectrical Engineering, Mathematics and Computer Scienc
Localising speech, footsteps and other sounds using resource-constrained devices
No full textWhile a number of acoustic localisation systems have been proposed over the last few decades, these have typically either relied on expensive dedicated microphone arrays and workstation-class processing, or have been developed to detect a very specific type of sound in a particular scenario. However, as people live and work indoors, they generate a wide variety of sounds as they interact and move about. These human-generated sounds can be used to infer the positions of people, without requiring them to wear trackable tags. In this paper, we take a practical yet general approach to localising a number of human-generated sounds. Drawing from signal processing literature, we identify methods for resource-constrained devices in a sensor network to detect, classify and locate acoustic events such as speech, footsteps and objects being placed onto tables. We evaluate the classification and time-of-arrival estimation algorithms using a data set of human-generated sounds we captured with sensor nodes in a controlled setting. We show that despite the variety and complexity of the sounds, their localisation is feasible for sensor networks, with typical accuracies of a half metre or better. We specifically discuss the processing and networking considerations, and explore the performance trade-offs which can be made to further conserve resources
Constructing the Cool Wall: A tool to explore teen meanings of cool
No full textThis paper describes the development and exploration of a tool designed to assist in investigating ‘cool’ as it applies to the design of interactive products for teenagers. The method involved the derivation of theoretical understandings of cool from literature that resulted in identification of seven core categories for cool, which were mapped to a hierarchy. The hierarchy includes having of cool things, the doing of cool activities and the being of cool. This paper focuses on a tool, the Cool Wall, developed to explore one specific facet of the hierarchy; exploring shared understanding of having cool things. The paper describes the development and construction of the tool, using a heavily participatory approach, and the results and analysis of three studies. The first study was carried out over 2 days in a school in the UK. The results of the study both provide clear insights into cool things and enable a refined understanding of cool in this context. Two additional studies are then used to identify potential shortcomings in the Cool Wall methodology. In the second study participants were able to populate a paper cool wall with anything they chose, this revealed two potential new categories of images and that the current set of images covered the majority of key themes. In the third study teenagers interpretations of the meaning of the images included in the Cool Wall were explored, this showed that the majority of meanings were as expected and a small number of unexpected interpretations provided some valuable insights
Risk management system and intelligent decision-making for prefabricated building project under deep learning modified teaching-learning-based optimization.
No full textThis study establishes a model of prefabricated building project risk management system based on the Modified Teaching-Learning-Based-Optimization (MTLBO) algorithm and a prediction model of deep learning multilayer feedforward neural network (Backpropagation, BP neural network) to improve the requirements of risk management during the construction of large prefabricated building projects. First, we introduced the BP neural network algorithm based on deep learning. Second, the traditional Teaching-Learning-Based Optimization (TLBO) algorithm was modified by using information entropy, and the modified algorithm was simulated and tested in five test functions. Then, based on the BP neural network and MTLBO algorithm, we established the MTLBO-BP neural network prediction model and tested its performance. Finally, based on the MTLBO-BP neural network prediction model, MATLAB software was used to establish an intelligent model of the risk management system during the construction of prefabricated building projects, and the example verification was performed. In addition, the MTLBO algorithm was verified by test function simulation and established that global searchability is stronger than the TLBO algorithm. Of note, it is not easy to fall into a local optimum. The test results of the MTLBO-BP neural network prediction model revealed that the prediction model converges faster and exerts a better prediction effect. The example verification of the intelligent model of the risk management system during the construction of prefabricated building projects established in this study revealed that the algorithm proposed is more accurate in the reliability and cost prediction of the risk management of prefabricated building projects. Moreover, the algorithm proposed provides theoretical support for intelligent management and decision-making of prefabricated building projects. Overall, this study validates that this algorithm is essential for construction project management, decision-making, and quality assurance
The Effect of Social Economic Status and Parents’ Rearing Behavior on Social Creativity of Children in Mali
No full textPerformance Analysis of PA Coded Pulse-Position Modulation for Space Optical Communications
No full text
The impact of spatio-temporal travel distance on epidemics using an interpretable attention-based sequence-to-sequence model
No full textAmidst the COVID-19 pandemic, travel restrictions have emerged as crucial
interventions for mitigating the spread of the virus. In this study, we enhance
the predictive capabilities of our model, Sequence-to-Sequence Epidemic
Attention Network (S2SEA-Net), by incorporating an attention module, allowing
us to assess the impact of distinct classes of travel distances on epidemic
dynamics. Furthermore, our model provides forecasts for new confirmed cases and
deaths. To achieve this, we leverage daily data on population movement across
various travel distance categories, coupled with county-level epidemic data in
the United States. Our findings illuminate a compelling relationship between
the volume of travelers at different distance ranges and the trajectories of
COVID-19. Notably, a discernible spatial pattern emerges with respect to these
travel distance categories on a national scale. We unveil the geographical
variations in the influence of population movement at different travel
distances on the dynamics of epidemic spread. This will contribute to the
formulation of strategies for future epidemic prevention and public health
policies.Comment: 18 pages, 7 figure
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