Recovering 3D Hand Mesh Sequence from a Single Blurry Image: A New Dataset and Temporal Unfolding

Hands, one of the most dynamic parts of our body, suffer from blur due to their active movements. However, previous 3D hand mesh recovery methods have mainly focused on sharp hand images rather than considering blur due to the absence of datasets providing blurry hand images. We first present a novel dataset BlurHand, which contains blurry hand images with 3D groundtruths. The BlurHand is constructed by synthesizing motion blur from sequential sharp hand images, imitating realistic and natural motion blurs. In addition to the new dataset, we propose BlurHandNet, a baseline network for accurate 3D hand mesh recovery from a blurry hand image. Our BlurHandNet unfolds a blurry input image to a 3D hand mesh sequence to utilize temporal information in the blurry input image, while previous works output a static single hand mesh. We demonstrate the usefulness of BlurHand for the 3D hand mesh recovery from blurry images in our experiments. The proposed BlurHandNet produces much more robust results on blurry images while generalizing well to in-the-wild images. The training codes and BlurHand dataset are available at https://github.com/JaehaKim97/BlurHand_RELEASE.Comment: Accepted at CVPR 202

Non-linear dynamic analysis of reinforced concrete bridge columns under vehicle impact loadings

A 3D nonlinear impact analysis was performed for reinforced concrete bridge columns under truck impact loadings. Three different boundary conditions were considered to investigate the effect of superstructures on the integral column during impact. Fixed bottom conditions and restraints in the loading direction at the top of the column (Model I) showed the largest damaged area. The dominant failure mode of the column was shear. However, Model II, which is equivalent to Model I with the top released, showed less damage, and the dominant failure modes were flexure rather than shear. In Model III, in which the effect of featured the superstructure was considered, the shear and flexural damage to the column were reduced due to the movement of the superstructures

'Grey Galaxies' as an endpoint of the Kerr-AdS superradiant instability

Kerr-AdS$_{d+1}$ black holes for $d\geq 3$ suffer from classical superradiant instabilities over a range of masses above extremality. We conjecture that these instabilities settle down into Grey Galaxies (GGs) - a new class of coarse-grained solutions to Einstein's equations which we construct in $d=3$. Grey Galaxies are made up of a black hole with critical angular velocity $\omega=1$ in the `centre' of $AdS$, surrounded by a large flat disk of thermal bulk gas that revolves around the centre of $AdS$ at the speed of light. The gas carries a finite fraction of the total energy, as its parametrically low energy density and large radius are inversely related. GGs exist at masses that extend all the way down to the unitarity bound. Their thermodynamics is that of a weakly interacting mix of Kerr-AdS black holes and the bulk gas. Their boundary stress tensor is the sum of a smooth `black hole' contribution and a peaked gas contribution that is delta function localized around the equator of the boundary sphere in the large $N$ limit. We also construct another class of solutions with the same charges; `Revolving Black Holes (RBHs)'. RBHs are macroscopically charged $SO(d,2)$ descendants of AdS-Kerr solutions, and consist of $\omega=1$ black holes revolving around the centre of $AdS$ at a fixed radial location but in a quantum wave function in the angular directions. RBH solutions are marginally entropically subdominant to GG solutions and do not constitute the endpoint of the superradiant instability. Nonetheless, we argue that supersymmetric versions of these solutions have interesting implications for the spectrum of supersymmetric states in, e.g. ${\cal N}=4$ Yang-Mills theory.Comment: 110 pages, 7 figures, 41 pages Appendi

Defending Against Flush+Reload Attack With DRAM Cache by Bypassing Shared SRAM Cache

Cache side-channel attack is one of the critical security threats to modern computing systems. As a representative cache side-channel attack, Flush+Reload attack allows an attacker to steal confidential information (e.g., private encryption key) by monitoring a victim's cache access patterns while generating the confidential values. Meanwhile, for providing high performance with memory-intensive applications that do not fit in the on-chip SRAM-based last-level cache (e.g., L3 cache), modern computing systems start to deploy DRAM cache between the SRAM-based last-level cache and the main memory DRAM, which can provide low latency and/or high bandwidth. However, in this work, we propose an approach that exploits the DRAM cache for security rather than performance, called ByCA. ByCA bypasses the L3 shared cache when accessing cache blocks suspected as target blocks of an attacker. Consequently, ByCA eliminates the timing difference when the attacker accesses the target cache blocks, nullifying the Flush+Reload attacks. To this end, ByCA keeps cache blocks suspected as target blocks of the attacker and stores their states (i.e., flushed by clflush or not) in the L4 DRAM cache even with clflush instruction; ByCA re-defines and re-implements clflush instruction not to flush cache blocks from the L4 DRAM cache while flushing the blocks from other level caches (i.e., L1, L2, and L3 caches). In addition, ByCA bypasses L3 cache when the attacker or the victim accesses the target blocks flushed by clflush, making the attacker always obtain the blocks from L4 DRAM cache regardless of the victim's access patterns. Consequently, ByCA eliminates the timing difference, thus the attacker cannot monitor the victim's cache access patterns. For L4 DRAM cache, we implement Alloy Cache design and use an unused bit in a tag entry for each block to store its state. ByCA only requires a single bit extension to cache blocks in L1 and L2 private caches, and a tag entry for each block in the L4 DRAM cache. Our experimental results show that ByCA completely eliminates the timing differences when the attacker reloads the target blocks. Furthermore, ByCA does not show the performance degradation for the victim while co-running with the attacker that flushes and reloads target blocks temporally and repetitively.1

In situ elucidation of the active state of Co-CeOx catalysts in the dry reforming of methane: the important role of the reducible oxide support and interactions with cobalt

The dry reforming of methane was systematically studied over a series (2-30 wt%) of Co (~5nm in size) loaded CeO2 catalysts, with an effort to elucidate the behavior of Co and ceria in the catalytic process using in-situ methods. For the systems under study, the reaction activity scaled with increasing Co loading, and a 10 wt% Co-CeO2 catalyst exhibiting the best catalytic activity and good stability at 500 °C with little evidence for carbon accumulation. The phase transitions and the nature of active components in the catalyst were investigated during pretreatment and under reaction conditions by ex-situ/in-situ techniques including X-ray diffraction (XRD) and ambient-pressure X-ray photoelectron spectroscopy (AP-XPS). These studies showed a dynamical evolution in the chemical composition of the catalysts under reaction conditions. A clear transition of Co3O4 → CoO → Co, and Ce4+ to Ce3+, was observed during the temperature programmed reduction under H2 and CH4. However, introduction of CO2, led to partial re-oxidation of all components at low temperatures, followed by reduction at high temperatures. Under optimum CO and H2 producing conditions both XRD and AP-XPS indicated that the active phase involved a majority of metallic Co with a small amount of CoO both supported on a partially reduced ceria (Ce3+/Ce4+). We identified the importance of dispersing Co, anchoring it onto ceria surface sites, and then utilizing the redox properties of ceria for activating and then oxidatively converting methane while inhibiting coke formation. Furthermore, a synergistic effect between cobalt and ceria and the interfacial site are essential to successfully close the catalytic cycle.Peer ReviewedPostprint (author's final draft

ReplaceNet: real-time replacement of a biological neural circuit with a hardware-assisted spiking neural network

Recent developments in artificial neural networks and their learning algorithms have enabled new research directions in computer vision, language modeling, and neuroscience. Among various neural network algorithms, spiking neural networks (SNNs) are well-suited for understanding the behavior of biological neural circuits. In this work, we propose to guide the training of a sparse SNN in order to replace a sub-region of a cultured hippocampal network with limited hardware resources. To verify our approach with a realistic experimental setup, we record spikes of cultured hippocampal neurons with a microelectrode array (in vitro). The main focus of this work is to dynamically cut unimportant synapses during SNN training on the fly so that the model can be realized on resource-constrained hardware, e.g., implantable devices. To do so, we adopt a simple STDP learning rule to easily select important synapses that impact the quality of spike timing learning. By combining the STDP rule with online supervised learning, we can precisely predict the spike pattern of the cultured network in real-time. The reduction in the model complexity, i.e., the reduced number of connections, significantly reduces the required hardware resources, which is crucial in developing an implantable chip for the treatment of neurological disorders. In addition to the new learning algorithm, we prototype a sparse SNN hardware on a small FPGA with pipelined execution and parallel computing to verify the possibility of real-time replacement. As a result, we can replace a sub-region of the biological neural circuit within 22 μs using 2.5 × fewer hardware resources, i.e., by allowing 80% sparsity in the SNN model, compared to the fully-connected SNN model. With energy-efficient algorithms and hardware, this work presents an essential step toward real-time neuroprosthetic computation

Physiological impact of nanoporous acupuncture needles: Laser Doppler perfusion imaging in healthy volunteers

Background Recently, porous acupuncture (PA), which is anodized to increase its surface area for higher stimulation intensity, was developed and showed significantly improved therapeutic effects with more comfort as compared with original acupuncture (OA) in vivo. However, the impact of PA on the change of local blood flow as well as its efficacy and acceptability has not yet been confirmed in a clinical trial. In a randomized, controlled crossover clinical trial, we investigated the effects of PA on the change in local blood flow using laser Doppler perfusion imaging and considered the sensation of pain intensity and discomfort severity using a visual analogue scale (VAS) to explore its physiological impact and the possibility of PA in clinical use. Methods Twenty-one healthy participants were randomly treated with PA or OA on one side of Zusanli (ST36) and each participant served as his or her own control. Baseline local blood flow and galvanic skin response (GSR) were obtained for 5 min and acupuncture interventions were subsequently performed. Next, local blood flow and GSR were subsequently obtained for 10 min after insertion, 10 min after manipulation, and 5 min after the withdrawal of acupuncture. At the end of the experiment, participants were asked to indicate the sensation of pain intensity at each session of insertion, retention, manipulation, and withdrawal as well as the overall pain intensity and discomfort severity. Results PA significantly increased the local blood flow as compared with OA and there was no significant difference in GSR between patients treated with PA versus OA in each phase of insertion and manipulation. No significant difference in pain intensity or discomfort severity was found during manipulation, retention, or withdrawal of acupuncture. Conclusions These results indicate that PA increases local blood flow, which can be closely related to the observed enhanced performance, without any associated discomfort or pain, suggesting its applicability in clinical practice. © 2019 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.1