Projective Bundle Adjustment from Arbitrary Initialization Using the Variable Projection Method

Bundle adjustment is used in structure-from-motion pipelines as final refinement stage requiring a sufficiently good initialization to reach a useful local mininum. Starting from an arbitrary initialization almost always gets trapped in a poor minimum. In this work we aim to obtain an initialization-free approach which returns global minima from a large proportion of purely random starting points. Our key inspiration lies in the success of the Variable Projection (VarPro) method for affine factorization problems, which have close to 100% chance of reaching a global minimum from random initialization. We find empirically that this desirable behaviour does not directly carry over to the projective case, and we consequently design and evaluate strategies to overcome this limitation. Also, by unifying the affine and the projective camera settings, we obtain numerically better conditioned reformulations of original bundle adjustment algorithms

Correlated Electronic Structures and the Phase Diagram of Hydrocarbon-based Superconductors

We have investigated correlated electronic structures and the phase diagram of electron-doped hydrocarbon molecular solids, based on the dynamical mean-field theory. We have found that the ground state of hydrocarbon-based superconductors such as electron-doped picene and coronene is a multi-band Fermi liquid, while that of non-superconducting electron-doped pentacene is a single-band Fermi liquid in the proximity of the metal-insulator transition. The size of the molecular orbital energy level splitting plays a key role in producing the superconductivity of electron-doped hydrocarbon solids. The multi-band nature of hydrocarbon solids would boost the superconductivity through the enhanced density of states at the Fermi level.X11910sciescopu

Observation of a kink during the formation of the Kondo resonance band in a heavy-fermion system

We have shown that the kink behavior in the spectral function of a heavy fermion can appear during the formation of the Kondo resonance (KR) band and the hybridization gap. We have investigated the heavy fermion compound CeCoGe2, using a combined approach of the density functional theory and the dynamical mean field theory. Low temperature T spectral functions show dispersive KR states, similarly to the recent experimental observation. During the evolution from the non-f conduction band state at high T to the dispersive KR band state at low T, which have topologically different band shapes, we have found the existence of kinks in the non-f spectral function near the Fermi level E-F. The observation of kink is clearly in correspondence with the multiple temperature scales of the formation of the KR band.X1186sciescopu

Structure and dielectric properties of cubic Bi<inf>2</inf>(Zn <inf>1/3</inf>Ta<inf>2/3</inf>)<inf>2</inf> O<inf>7</inf> thin films

Pyrochlore Bi2(Zn1/3Ta2/3)2 O7 (BZT) films were prepared by pulsed laser deposition on Pt/TiO2/SiO2/Si substrates. In contrast to bulk monoclinic BZT ceramics, the BZT films have a cubic structure mediated by an interfacial layer. The dielectric properties of the cubic BZT films [ε∼177, temperature coefficient of capacitance (TCC) ∼-170 ppm/°C] are much different from those of monoclinic BZT ceramics (ε∼61, TCC ∼+60 ppm/°C). Increasing the thickness of the BZT films returns the crystal structure to the monoclinic phase, which allows the dielectric properties of the BZT films to be tuned without changing their chemical composition. © 2009 American Institute of Physics

Quantitative analysis on electric dipole energy in Rashba band splitting

We report on quantitative comparison between the electric dipole energy and the Rashba band splitting in model systems of Bi and Sb triangular monolayers under a perpendicular electric field. We used both first-principles and tight binding calculations on p-orbitals with spin-orbit coupling. First-principles calculation shows Rashba band splitting in both systems. It also shows asymmetric charge distributions in the Rashba split bands which are induced by the orbital angular momentum. We calculated the electric dipole energies from coupling of the asymmetric charge distribution and external electric field, and compared it to the Rashba splitting. Remarkably, the total split energy is found to come mostly from the difference in the electric dipole energy for both Bi and Sb systems. A perturbative approach for long wave length limit starting from tight binding calculation also supports that the Rashba band splitting originates mostly from the electric dipole energy difference in the strong atomic spin-orbit coupling regime.1131Ysciescopu

Reversible change in electrical and optical properties in epitaxially grown Al-doped ZnO thin films

Aluminum-doped ZnO (AZO) films were epitaxially grown on sapphire (0001) substrates using pulsed laser deposition. As-deposited AZO films had a low resistivity of 8.01× 10-4 Ω cm. However, after annealing at 450 °C in air, the electrical resistivity of the AZO films increased to 1.97× 10-1 Ω cm because of a decrease in the carrier concentration. Subsequent annealing of the air-annealed AZO films in H2 recovered the electrical conductivity of the AZO films. In addition, the conductivity change was reversible upon repeated air and H2 annealing. A photoluminescence study showed that oxygen interstitial (Oi′) is a critical material parameter allowing for the reversible control of the electrical conducting properties of AZO films. © 2008 American Institute of Physics

An intent-based network virtualization platform for SDN

© 2016 IFIP. Currently, the Software Defined Networking (SDN) paradigm has attracted significant interests from industry and academia as a future network architecture. SDN brings many benefits to network operations and management including programmability, agility, elasticity, and flexibility. With SDN and OpenFlow, one of the promising SDN protocols, software defined Network Virtualization (NV) techniques can be designed and implemented via flow table segmentation to provision independent virtual networks (VNs). In this paper, we propose an intent based virtual network management platform based on software defined NV. The objective of the proposed NV platform is to automate the management and configuration of virtual networks based on high level tenant requirement specifications, called intents. The design and implementation of the platform is based on ONOS, an open-source SDN controller, and OpenVirteX, a network hypervisor. The platform is designed to provide multiple VNs over the same physical infrastructure to multiple tenants

Thermoelectric materials by using two-dimensional materials with negative correlation between electrical and thermal conductivity

In general, in thermoelectric materials the electrical conductivity sigma and thermal conductivity kappa are related and thus cannot be controlled independently. Previously, to maximize the thermoelectric figure of merit in state-of-the-art materials, differences in relative scaling between sigma and kappa as dimensions are reduced to approach the nanoscale were utilized. Here we present an approach to thermoelectric materials using tin disulfide, SnS2, nanosheets that demonstrated a negative correlation between sigma and kappa. In other words, as the thickness of SnS2 decreased, sigma increased whereas kappa decreased. This approach leads to a thermoelectric figure of merit increase to 0.13 at 300 K, a factor similar to 1,000 times greater than previously reported bulk single-crystal SnS2. The Seebeck coefficient obtained for our two-dimensional SnS2 nanosheets was 34.7mVK(-1) for 16-nm-thick samples at 300 K.114330Ysciescopu

Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database

Radiologists in their daily work routinely find and annotate significant abnormalities on a large number of radiology images. Such abnormalities, or lesions, have collected over years and stored in hospitals' picture archiving and communication systems. However, they are basically unsorted and lack semantic annotations like type and location. In this paper, we aim to organize and explore them by learning a deep feature representation for each lesion. A large-scale and comprehensive dataset, DeepLesion, is introduced for this task. DeepLesion contains bounding boxes and size measurements of over 32K lesions. To model their similarity relationship, we leverage multiple supervision information including types, self-supervised location coordinates and sizes. They require little manual annotation effort but describe useful attributes of the lesions. Then, a triplet network is utilized to learn lesion embeddings with a sequential sampling strategy to depict their hierarchical similarity structure. Experiments show promising qualitative and quantitative results on lesion retrieval, clustering, and classification. The learned embeddings can be further employed to build a lesion graph for various clinically useful applications. We propose algorithms for intra-patient lesion matching and missing annotation mining. Experimental results validate their effectiveness.Comment: Accepted by CVPR2018. DeepLesion url adde

Network adaptation improves temporal representation of naturalistic stimuli in drosophila eye: II Mechanisms

Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information