Green Paths - On the Space In-Between Buildings

This project focuses on the “leftovers” of our urban space after carving out what was required for buildings and transportation, and reintegrating them into a network that can be the habitat and paths for pollinators and small animals. This network overlaps and interacts with our existing urban structures. Integrating it into our life will undermine the hierarchy of space and commodification of land intensified by the existing grid systems of the city, and introduce a different understanding of coexistence with nature

Robustness and edge addition strategy of air transport networks : a case study of 'the Belt and Road'

Air transportation is of great importance in "the Belt and Road" (the B&R) region. The achievement of the B&R initiative relies on the availability, reliability, and safety of air transport infrastructure. A fundamental step is to find the critical elements in network performance. Considering the uneven distributions of population and economy, the current literature focusing on centrality measures in unweighted networks is not sufficient in the B&R region. By differentiating power and centrality in the B&R region, our analysis leads to two conclusions: (1) Deactivating powerful nodes causes a larger decrease in efficiency than deactivating central nodes. This indicates that powerful nodes in the B&R region are more critical than central nodes for network robustness. (2) Strategically adding edges between high powerful and low powerful nodes can enhance the network's ability to exchange resources efficiently. These findings can be used to adjust government policies for air transport configuration to achieve the best network performance and the most cost effective

Essays on the role of banking sector in transmission mechanism and business cycle

The financial friction is shown to depend on the corporate balance sheet condition, bank capital ratio, and liquidity premium. Given the banks' liability composition is constant, the higher the liquidity premium, the larger is the EFP.  Similarly, given the liquidity premium is constant, EFP is larger when higher proportion of loans is produced or financed with bank capital. Based on this framework, we are able to establish the link between the bank capital channel and the model's transmission mechanism subject to exogenous shocks.  Results indicate an active bank capital channel amplifies and propagates the monetary policy shocks (demand shock) while it attenuates and dampens the technology shocks (supply shock) when households' deposit is contracted in nominal term.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Essays on the role of banking sector in transmission mechanism and business cycle

The financial friction is shown to depend on the corporate balance sheet condition, bank capital ratio, and liquidity premium. Given the banks' liability composition is constant, the higher the liquidity premium, the larger is the EFP.  Similarly, given the liquidity premium is constant, EFP is larger when higher proportion of loans is produced or financed with bank capital. Based on this framework, we are able to establish the link between the bank capital channel and the model's transmission mechanism subject to exogenous shocks.  Results indicate an active bank capital channel amplifies and propagates the monetary policy shocks (demand shock) while it attenuates and dampens the technology shocks (supply shock) when households' deposit is contracted in nominal term

Transformation media that turn a narrow slit into a large window

Based on the transformation media theory, the authors propose a way to replace a wide window with a narrow slit filled with designed metamaterial to achieve the same transmittance as the one of the window. Numerical simulations for a two dimensional case are given to illustrate the ideas and the performance of the design.Comment: 10 pages, 3 figure

Multi-source adversarial transfer learning based on similar source domains with local features

Transfer learning leverages knowledge from other domains and has been successful in many applications. Transfer learning methods rely on the overall similarity of the source and target domains. However, in some cases, it is impossible to provide an overall similar source domain, and only some source domains with similar local features can be provided. Can transfer learning be achieved? In this regard, we propose a multi-source adversarial transfer learning method based on local feature similarity to the source domain to handle transfer scenarios where the source and target domains have only local similarities. This method extracts transferable local features between a single source domain and the target domain through a sub-network. Specifically, the feature extractor of the sub-network is induced by the domain discriminator to learn transferable knowledge between the source domain and the target domain. The extracted features are then weighted by an attention module to suppress non-transferable local features while enhancing transferable local features. In order to ensure that the data from the target domain in different sub-networks in the same batch is exactly the same, we designed a multi-source domain independent strategy to provide the possibility for later local feature fusion to complete the key features required. In order to verify the effectiveness of the method, we made the dataset "Local Carvana Image Masking Dataset". Applying the proposed method to the image segmentation task of the proposed dataset achieves better transfer performance than other multi-source transfer learning methods. It is shown that the designed transfer learning method is feasible for transfer scenarios where the source and target domains have only local similarities.Comment: Submitted to Information Fusio