Deep learning model-aware regulatization with applications to Inverse Problems

There are various inverse problems – including reconstruction problems arising in medical imaging - where one is often aware of the forward operator that maps variables of interest to the observations. It is therefore natural to ask whether such knowledge of the forward operator can be exploited in deep learning approaches increasingly used to solve inverse problems. In this paper, we provide one such way via an analysis of the generalisation error of deep learning approaches to inverse problems. In particular, by building on the algorithmic robustness framework, we offer a generalisation error bound that encapsulates key ingredients associated with the learning problem such as the complexity of the data space, the size of the training set, the Jacobian of the deep neural network and the Jacobian of the composition of the forward operator with the neural network. We then propose a ‘plug-and-play’ regulariser that leverages the knowledge of the forward map to improve the generalization of the network. We likewise also use a new method allowing us to tightly upper bound the Jacobians of the relevant operators that is much more computationally efficient than existing ones. We demonstrate the efficacy of our model-aware regularised deep learning algorithms against other state-of-the-art approaches on inverse problems involving various sub-sampling operators such as those used in classical compressed sensing tasks, image super-resolution problems and accelerated Magnetic Resonance Imaging (MRI) setups

Tropical forest restoration: Fast resilience of plant biomass contrasts with slow recovery of stable soil C stocks

Due to intensifying human disturbance, over half of the world's tropical forests are reforested or afforested secondary forests or plantations. Understanding the resilience of carbon (C) stocks in these forests, and estimating the extent to which they can provide equivalent carbon (C) sequestration and stabilization to the old growth forest they replace, is critical for the global C balance. In this study, we combined estimates of biomass C stocks with a detailed assessment of soil C pools in bare land, Eucalyptus plantation, secondary forest and natural old-growth forest after over 50 years of forest restoration in a degraded tropical region of South China. We used isotope studies, density fractionation and physical fractionation to determine the age and stability of soil C pools at different soil depths. After 52 years, the secondary forests had equivalent biomass C stocks to natural forest, whereas soil C stocks were still much higher in natural forest (97.42 t/ha) than in secondary forest (58.75 t/ha) or Eucalyptus plantation (38.99 t/ha) and lowest in bare land (19.9 t/ha). Analysis of δ13C values revealed that most of the C in the soil surface horizons in the secondary forest was new C, with a limited increase of more recalcitrant old C, and limited accumulation of C in deeper soil horizons. However, occlusion of C in microaggregates in the surface soil layer was similar across forested sites, which suggests that there is great potential for additional soil C sequestration and stabilization in the secondary forest and Eucalyptus plantation. Collectively, our results demonstrate that reforestation on degraded tropical land can restore biomass C and surface soil C stocks within a few decades, but much longer recovery times are needed to restore recalcitrant C pools and C stocks at depth. Repeated harvesting and disturbance in rotation plantations had a substantial negative impact on the recovery of soil C stocks. We suggest that current calculations of soil C in secondary tropical forests (e.g. IPCC Guidelines for National Greenhouse Gas Inventories) could overestimate soil C sequestration and stabilization levels in secondary forests and plantations

RANS-based Aerodynamic Shape Optimization of a Blended-Wing-Body Aircraft

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106453/1/AIAA2013-2586.pd

Rural unemployment pushes migrants to urban areas in Jiangsu Province, China

© 2019, The Author(s). Migration is often seen as an adaptive human response to adverse socio-environmental conditions, such as water scarcity. A rigorous assessment of the causes of migration, however, requires reliable information on the migration in question and related variables, such as, unemployment, which is often missing. This study explores the causes of one such type of migration, from rural to urban areas, in the Jiangsu province of China. A migration model is developed to fill a gap in the understanding of how rural to urban migration responds to variations in inputs to agricultural production including water availability and labor and how rural population forms expectations of better livelihood in urban areas. Rural to urban migration is estimated at provincial scale for period 1985–2013 and is found to be significantly linked with rural unemployment. Further, migration reacts to a change in rural unemployment after 2–4 years with 1% increase in rural unemployment, on average, leading to migration of 16,000 additional people. This implies that rural population takes a couple of years to internalize a shock in employment opportunities before migrating to cities. The analysis finds neither any evidence of migrants being pulled by better income prospects to urban areas nor being pushed out of rural areas by water scarcity. Corroborated by rural–urban migration in China migration survey data for 2008 and 2009, this means that local governments have 2–4 years of lead time after an unemployment shock, not necessarily linked to water scarcity, in rural areas to prepare for the migration wave in urban areas. This original analysis of migration over a 30-year period and finding its clear link with unemployment, and not with better income in urban areas or poor rainfall, thus provides conclusive evidence in support of policy interventions that focus on generating employment opportunities in rural areas to reduce migration flow to urban areas

Comparative study of partitioned stator memory machines with series and parallel hybrid PM configurations

In this paper, the partitioned stator (PS) structure is extended to variable-flux memory machines, forming two newly emerged PS switched-flux memory machines (PS-SFMMs) with series and parallel hybrid magnet configurations. From the perspective of geometry, both two PS-SFMMs share identical outer stator and rotor segments, while two different types of permanent magnet (PM) arrangements are employed in the inner stationary part. Thus, the developed machines can inherent the geometric separation of the armature winding and PM excitations from the PS design, thus achieving acceptable torque capability, and excellent air-gap flux control. A comparative study between PS-SFMMs with series and parallel structures is established. First, the topologies and operating principle are introduced, respectively. In addition, the design tradeoffs and PM sizing of the two PS machines are revealed and optimized with a simplified magnetic circuit model. Then, the electromagnetic characteristics of PS-SFMMs with different magnetic circuits are investigated and compared with the finite-element (FE) method. The FE results are validated by the experiments on a parallel prototype

Comparative studies on wood structure and microtensile properties between compression and opposite wood fibers of Chinese fir plantation

The microtensile properties of mechanically isolated compression wood (CW) and opposite wood (OW) tracheids of Chinese fir (Cunninghamia lanceolata) were investigated and discussed with respect to their structure. Major differences in the tensile modulus and ultimate tensile stress were found between CW and OW fibers. Compared to OW, CW showed a larger cellulose microfibril angle, less cellulose content and probably more pits, resulting in lower tensile properties. These findings contribute to a further understanding of the structural–mechanical relationships of Chinese fir wood at the cell and cell wall level, and provide a scientific basis for better utilization of plantation softwood

Structure and electronic properties of the (3×3\sqrt{3}\times \sqrt{3})R30∘R30^{\circ} SnAu2_2/Au(111) surface alloy

We have investigated the atomic and electronic structure of the ($\sqrt{3}\times \sqrt{3}$)$R30^{\circ}$ SnAu$_2$/Au(111) surface alloy. Low energy electron diffraction and scanning tunneling microscopy measurements show that the native herringbone reconstruction of bare Au(111) surface remains intact after formation of a long range ordered ($\sqrt{3}\times \sqrt{3}$)$R30^{\circ}$ SnAu$_2$2/Au(111) surface alloy. Angle-resolved photoemission and two-photon photoemission spectroscopy techniques reveal Rashba-type spin-split bands in the occupied valence band with comparable momentum space splitting as observed for the Au(111) surface state, but with a hole-like parabolic dispersion. Our experimental findings are compared with density functional theory (DFT) calculation that fully support our experimental findings. Taking advantage of the good agreement between our DFT calculations and the experimental results, we are able to extract that the occupied Sn-Au hybrid band is of (s, d)-orbital character while the unoccupied Sn-Au hybrid bands are of (p, d)-orbital character. Hence, we can conclude that the Rashba-type spin splitting of the hole-like Sn-Au hybrid surface state is caused by the significant mixing of Au d- to Sn s-states in conjunction with the strong atomic spin-orbit coupling of Au, i.e., of the substrate.Comment: Copyright: https://journals.aps.org/authors/transfer-of-copyright-agreement; All copyrights by AP

Freight Operations Modelling for Urban Delivery and Pickup with Flexible Routing: Cluster Transport Modelling Incorporating Discrete-Event Simulation and GIS

Urban pickup and delivery (PUD) activities are important for logistics operations. Real operations for general freight involve a high degree of complexity due to daily variability. Discrete-event simulation (DES) is a method that can mimic real operations and include stochastic parameters. However, realistic vehicle routing is difficult to build in DES models. The objective is to create a DES model for realistic freight routing, which considers the driver’s routing decisions. Realistic models need to predict the delivery route (including time and distance) for variable consignment address and backhaul pickup. Geographic information systems (GIS) and DES were combined to develop freight PUD models. GIS was used to process geographical data. Two DES models were developed and compared. The first was a simple suburb model, and the second an intersection-based model. Real industrial data were applied including one-year consignment data and global positioning system (GPS) data. A case study of one delivery tour is shown, with results validated with actual GPS data. The DES results were also compared with conventional GIS models. The result shows the intersection-based model is adequate to mimic actual PUD routing. This work provides a method for combining GIS and DES to build freight operation models for urban PUD. This has the potential to help industry logistics practitioners better understand their current operations and experiment with different scenarios

Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics

Background: Logistics problems involve a large number of complexities, which makes the development of models challenging. While computer simulation models are developed for addressing complexities, it is essential to ensure that the necessary operational behaviours are captured, and that the architecture of the model is suitable to represent them. The early stage of simulation modelling, known as conceptual modelling (CM), is thus dependent on successfully extracting tacit operational knowledge and avoiding misunderstanding between the client (customer of the model) and simulation analyst. Objective: This paper developed a methodology for managing the knowledge-acquisition process needed to create a sufficient simulation model at the early or the CM stage to ensure the correctness of operation representation. Methods: A minimum viable model (MVM) methodology was proposed with five principles relevant to CM: iterative development, embedded communication, soliciting tacit knowledge, interactive face validity, and a sufficient model. The method was validated by a case study of freight operations, and the results were encouraging. Conclusions: The MVM method improved the architecture of the simulation model through eliciting tacit knowledge and clearing up communication misunderstandings. It also helped shape the architecture of the model towards the features most appreciated by the client, and features not needed in the model. Originality: The novel contribution of this work is the presentation of a method for eliciting tacit information from industrial clients, and building a minimally sufficient simulation model at the early modelling stage. The framework is demonstrated for logistics operations, though the principles may benefit simulation practitioners more generally.</jats:p