Unsupervised Learning of Complex Articulated Kinematic Structures combining Motion and Skeleton Information

In this paper we present a novel framework for unsupervised kinematic structure learning of complex articulated objects from a single-view image sequence. In contrast to prior motion information based methods, which estimate relatively simple articulations, our method can generate arbitrarily complex kinematic structures with skeletal topology by a successive iterative merge process. The iterative merge process is guided by a skeleton distance function which is generated from a novel object boundary generation method from sparse points. Our main contributions can be summarised as follows: (i) Unsupervised complex articulated kinematic structure learning by combining motion and skeleton information. (ii) Iterative fine-to-coarse merging strategy for adaptive motion segmentation and structure smoothing. (iii) Skeleton estimation from sparse feature points. (iv) A new highly articulated object dataset containing multi-stage complexity with ground truth. Our experiments show that the proposed method out-performs state-of-the-art methods both quantitatively and qualitatively

Quantum Spin Hall and Quantum Anomalous Hall States Realized in Junction Quantum Wells

Both quantum spin Hall and quantum anomalous Hall states are novel states of quantum matter with promising applications. We propose junction quantum wells comprising II-VI, III-V or IV semiconductors as a large class of new materials realizing the quantum spin Hall state. Especially, we find that the bulk band gap for the quantum spin Hall state can be as large as 0.1 eV. Further more, magnetic doping would induce the ferromagnetism in these junction quantum wells due to band edge singularities in the band-inversion regime and to realize the quantum anomalous Hall state.Comment: 5 pages, 4 figure

Iterative Path Optimisation for Personalised Dressing Assistance using Vision and Force Information

We propose an online iterative path optimisation method to enable a Baxter humanoid robot to assist human users to dress. The robot searches for the optimal personalised dressing path using vision and force sensor information: vision information is used to recognise the human pose and model the movement space of upper-body joints; force sensor information is used for the robot to detect external force resistance and to locally adjust its motion. We propose a new stochastic path optimisation method based on adaptive moment estimation. We first compare the proposed method with other path optimisation algorithms on synthetic data. Experimental results show that the performance of the method achieves the smallest error with fewer iterations and less computation time. We also evaluate real-world data by enabling the Baxter robot to assist real human users with their dressing

The Missing Dimensions of the Human Capabilities Approach: Collective and Productive

In this paper we identify two missing dimensions of the Human Capabilities Approach (HCA)—the collective and the productive—and in doing so we advance a ‘productionist’ perspective on development, centred around the idea of ‘collective productive capabilities’. Bringing production back to the core of the development agenda calls for an integration of the HCA and those contributions which have focused their attention on the social, economic and institutional processes of learning, centred around productive organisations and systems. The lack of this focus on collective productive capabilities undermined the Millenium Development Goals Agenda and is still having negative impacts on the ways in which the Sustainable Development Goals Agenda is understood and implemented

Kicking away the financial ladder? German development banking under economic globalisation

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. While extensive literature exists on how economic globalisation has limited developing countries' policy space for industrial policy, the literature on how it has affected advanced economies remains scant. We utilise original archival material to analyse the activities of the German public development bank, the Kreditantstalt für Wiederaufbau (KfW), in order to shed light on an important, but neglected aspect of German industrial policy. We analyse how the KfW responded to multiple challenges after the rise of economic globalisation, including a funding crisis, international agreements to limit export subsidies and Europeanisation. We argue that KfW successfully managed to navigate these challenges in order to retain, and even increase, its ability to conduct selective industrial policy in the post-1980s era. This was possible because of Germany's hard currency and low sovereign credit risk, large market size, which was augmented by membership in the European Union, and Germany's position as regional hegemon within Europe. More broadly, this shows how, conditional on domestic politics, advanced economies are able to shape and exploit the rules of the international economic system to implement industrial policies to their advantage, even as developing countries are given the opposite policy recommendations

Crystal growth and quantum oscillations in the topological chiral semimetal CoSi

We survey the electrical transport properties of the single-crystalline, topological chiral semimetal CoSi which was grown via different methods. High-quality CoSi single crystals were found in the growth from tellurium solution. The sample's high carrier mobility enables us to observe, for the first time, quantum oscillations (QOs) in its thermoelectrical signals. Our analysis of QOs reveals two spherical Fermi surfaces around the R point in the Brillouin zone corner. The extracted Berry phases of these electron orbits are consistent with the -2 chiral charge as reported in DFT calculations. Detailed analysis on the QOs reveals that the spin-orbit coupling induced band-splitting is less than 2 meV near the Fermi level, one order of magnitude smaller than our DFT calculation result. We also report the phonon-drag induced large Nernst effect in CoSi at intermediate temperatures

Learning kinematic structure correspondences using multi-order similarities

We present a novel framework for finding the kinematic structure correspondences between two articulated objects in videos via hypergraph matching. In contrast to appearance and graph alignment based matching methods, which have been applied among two similar static images, the proposed method finds correspondences between two dynamic kinematic structures of heterogeneous objects in videos. Thus our method allows matching the structure of objects which have similar topologies or motions, or a combination of the two. Our main contributions are summarised as follows: (i)casting the kinematic structure correspondence problem into a hypergraph matching problem by incorporating multi-order similarities with normalising weights, (ii)introducing a structural topology similarity measure by aggregating topology constrained subgraph isomorphisms, (iii)measuring kinematic correlations between pairwise nodes, and (iv)proposing a combinatorial local motion similarity measure using geodesic distance on the Riemannian manifold. We demonstrate the robustness and accuracy of our method through a number of experiments on synthetic and real data, showing that various other recent and state of the art methods are outperformed. Our method is not limited to a specific application nor sensor, and can be used as building block in applications such as action recognition, human motion retargeting to robots, and articulated object manipulation

Determination of ultra-trace amounts of cadmium, cobalt and nickel in sea-water by electrothermal atomic absorption spectrometry with on-line preconcentration

[[abstract]]A miniature column packed with Muromac A-1 chelating resin and a laboratory-built automatic on-line preconcentration system for electrothermal atomic absorption spectrometry were used to determine Cd, Co and Ni in sea-water. The preconcentration system was modified from a Perkin-Elmer AS-40 autosampler by mounting a Muromac A-1 microcolumn near the tip of the autosampler capillary, and we replaced the pull-and-push pump of the autosampler with a peristaltic pump. Retention of the metal ions as a complex on the microcolumn was achieved by using Muromac A-1 as the chelating resin; 20% HNO3 was then used for elution. The procedures of preconcentration were performed by using a four-way distribution valve and a programmable controller. Detection limits (and sample volumes) were 1.2 x 10(-4) mu g l(-1) for Cd (400 mu l), 0.007 mu g l(-1) for Co (1800 mu l) and 0.033 mu g l(-1) for Ni (800 mu l). Relative standard deviations for the determination of Cd, Co and Ni in sea-water (CASS-3) were 2.9, 5.6 and 4.1%, respectively. The accuracy of the method was confirmed by the analysis of certified reference saline waters (NASS-4, CASS-3 and SLEW-1).[[fileno]]2010324010032[[department]]化學