A System for Compressive Sensing Signal Reconstruction

An architecture for hardware realization of a system for sparse signal reconstruction is presented. The threshold based reconstruction method is considered, which is further modified in this paper to reduce the system complexity in order to provide easier hardware realization. Instead of using the partial random Fourier transform matrix, the minimization problem is reformulated using only the triangular R matrix from the QR decomposition. The triangular R matrix can be efficiently implemented in hardware without calculating the orthogonal Q matrix. A flexible and scalable realization of matrix R is proposed, such that the size of R changes with the number of available samples and sparsity level.Comment: 6 page

Impacts of integrated Blue-Green infrastructure on the urban design and urban ecosystem services

The city is the most complex human creation shaped over the centuries. The human-nature-city relationship is the basic principle of city development. The main scientific challenge of the current urban planning approach is recognized in a broken human-nature-city relationship whose degradation is amplified in 21st century by globalization and rapid climate change. This challenge is addressed in this thesis through the history of city transformation analyzed in literature review. The transformation impact on human-city-nature relationship helped to define the missed opportunities and proposed a new approach in the management of the natural resources and Ecosystem Services [ESS] in the city. The thesis is focused on the mitigation of the following ecosystem services: Urban Heat Island (UHI) and improvement of public amenities. Moreover, through addressing these ecosystem services, other ESS (water management and climate change adaptation and mitigation) are improved as well. The UHI is selected as one of the most significant principle that influences human comfort in open public spaces. In order to increase the amenities in a city, a new approach is focused on the level of city blocks – neighbourhood level. This thesis translates and synthesizes literature knowledge into a new approach, and uses computer-based models to test them on two case studies and one demo site. The new methodology follows the rules of nature and affirms the potential of ESS. The integration of the blue [urban waters] and green [urban greenery] infrastructures is quantified by the use of the computer-based analysis of ESS indicators. The combined effects of the blue-green infrastructure reduce the degradation of living environment and increase amenities of open public space. The implementation and the testing of the theoretical models in practice, supported by computer modelling, confirm the above-mentioned statement. The results of the new methodology were tested on the demo site – Imperial College South Kensington Campus – in order to increase the amenities of the space. The quantification of the amenities is presented through the Predicted Mean Vote (PMV) indicator obtained by computer base modelling. The PMV of the demo site was improved in average by cc. 25%. The main outputs of the thesis refer to the classification and the quantification of the integrated effects as new approaches that can improve the urban design process, especially in the aspect of sustainability. This should be applied in the early stage of planning – concept stage, which is one of the ideas presented in this thesis. The theoretical concept, modelling, and the computer-based experiment offer clear guidelines for the practice. This is an original scientific contribution. The benefits brought by BG infrastructure are expressed through the qualitative and quantitative parameters, showing the comfort level of human’s life in the city. The results of this thesis are shaped as the recommendations and guidelines for the reconstruction of urban settlements, offering new ways of integration. The most significant implications from work imply the interrelationship that promotes building with nature increases the resilience to climate extremes and the microclimate comfort of urban blocks. The integrative effect of the blue-green component is a new paradigm for sustainable design and the management of urban settlements in the 21st century. It presents an active effort to stop the anthropogenic separation of human beings and nature.Open Acces

Transferability of neural networks approaches for low-rate energy disaggregation

Energy disaggregation of appliances using non-intrusive load monitoring (NILM) represents a set of signal and information processing methods used for appliance-level information extraction out of a meter's total or aggregate load. Large-scale deployments of smart meters worldwide and the availability of large amounts of data, motivates the shift from traditional source separation and Hidden Markov Model-based NILM towards data-driven NILM methods. Furthermore, we address the potential for scalable NILM roll-out by tackling disaggregation complexity as well as disaggregation on houses which have not been 'seen' before by the network, e.g., during training. In this paper, we focus on low rate NILM (with active power meter measurements sampled between 1-60 seconds) and present two different neural network architectures, one, based on convolutional neural network, and another based on gated recurrent unit, both of which classify the state and estimate the average power consumption of targeted appliances. Our proposed designs are driven by the need to have a well-trained generalised network which would be able to produce accurate results on a house that is not present in the training set, i.e., transferability. Performance results of the designed networks show excellent generalization ability and improvement compared to the state of the art