Nonlinear cross Gramians and gradient systems

We study the notion of cross Gramians for non-linear gradient systems, using the characterization in terms of prolongation and gradient extension associated to the system. The cross Gramian is given for the variational system associated to the original nonlinear gradient system. We obtain linearization results that precisely correspond to the notion of a cross Gramian for symmetric linear systems. Furthermore, first steps towards relations with the singular value functions of the nonlinear Hankel operator are studied and yield promising results.

Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency

In this paper, we introduce a novel unsupervised domain adaptation technique for the task of 3D keypoint prediction from a single depth scan or image. Our key idea is to utilize the fact that predictions from different views of the same or similar objects should be consistent with each other. Such view consistency can provide effective regularization for keypoint prediction on unlabeled instances. In addition, we introduce a geometric alignment term to regularize predictions in the target domain. The resulting loss function can be effectively optimized via alternating minimization. We demonstrate the effectiveness of our approach on real datasets and present experimental results showing that our approach is superior to state-of-the-art general-purpose domain adaptation techniques.Comment: ECCV 201

Substitution induced pinning in MgB_2 superconductor doped with SiC nano-particles

By doping MgB_2 superconductor with SiC nano-particles, we have successfully introduced pinning sites directly into the crystal lattice of MgB_2 grains (intra-grain pinning). It became possible due to the combination of counter-balanced Si and C co-substitution for B, leading to a large number of intra-granular dislocations and the dispersed nano-size impurities induced by the substitution. The magnetic field dependence of the critical current density was significantly improved in a wide temperature range, whereas the transition temperature in the sample MgB_2(SiC)_x having x = 0.34, the highest doping level prepared, dropped only by 2.6 K.Comment: 4 pages, 6 figure

High quality factor copper inductors integrated in deep dry-etched quartz substrates

This paper reports on an inductor fabrication method capable to deliver high quality factor (Q) and high self-resonance frequency (SRF) devices using quartz insulating substrates and thick high-conductivity copper lines. Inductors are key devices in RF circuits that, when fabricated on traditional semiconductor substrates, suffer from poor RF performances due to thin metallization and substrate related losses. Many previous works revealed that RF performances are strongly dependent on the limited metallization thickness and on the conductivity of the substrate. In this paper we demonstrate a new fabrication process to improve the Q factor of spiral inductors by patterning thick high conductive metal layers directly in a dielectric substrate. Moreover, we develop and validate accurate equivalent circuit modeling and parameter extraction for the characterization of the fabricated device

Deep Autoencoder for Combined Human Pose Estimation and body Model Upscaling

We present a method for simultaneously estimating 3D human pose and body shape from a sparse set of wide-baseline camera views. We train a symmetric convolutional autoencoder with a dual loss that enforces learning of a latent representation that encodes skeletal joint positions, and at the same time learns a deep representation of volumetric body shape. We harness the latter to up-scale input volumetric data by a factor of $4 \times$, whilst recovering a 3D estimate of joint positions with equal or greater accuracy than the state of the art. Inference runs in real-time (25 fps) and has the potential for passive human behaviour monitoring where there is a requirement for high fidelity estimation of human body shape and pose

High quality factor copper inductors integrated in deep dry-etched quartz substrates

This paper reports on an inductor fabrication method capable to deliver high quality factor (Q) and high self-resonance frequency (SRF) devices using quartz insulating substrates and thick high-conductivity copper lines. Inductors are key devices in RF circuits that, when fabricated on traditional semiconductor substrates, suffer from poor RF performances due to thin metallization and substrate related losses. Many previous works revealed that RF performances are strongly dependent on the limited metallization thickness and on the conductivity of the substrate. In this paper we demonstrate a new fabrication process to improve the Q factor of spiral inductors by patterning thick high conductive metal layers directly in a dielectric substrate. Moreover, we develop and validate accurate equivalent circuit modeling and parameter extraction for the characterization of the fabricated device