Panoramic Vision Transformer for Saliency Detection in 360{\deg} Videos

360$^\circ$ video saliency detection is one of the challenging benchmarks for 360$^\circ$ video understanding since non-negligible distortion and discontinuity occur in the projection of any format of 360$^\circ$ videos, and capture-worthy viewpoint in the omnidirectional sphere is ambiguous by nature. We present a new framework named Panoramic Vision Transformer (PAVER). We design the encoder using Vision Transformer with deformable convolution, which enables us not only to plug pretrained models from normal videos into our architecture without additional modules or finetuning but also to perform geometric approximation only once, unlike previous deep CNN-based approaches. Thanks to its powerful encoder, PAVER can learn the saliency from three simple relative relations among local patch features, outperforming state-of-the-art models for the Wild360 benchmark by large margins without supervision or auxiliary information like class activation. We demonstrate the utility of our saliency prediction model with the omnidirectional video quality assessment task in VQA-ODV, where we consistently improve performance without any form of supervision, including head movement.Comment: Published to ECCV202

Effect of Potential Energy Distribution on the Melting of Clusters

We find that the potential energy distribution of atoms in clusters can consistently explain many important phenomena related to the phase changes of clusters, such as the nonmonotonic variation of melting temperature with size, the dependence of melting, boiling, and sublimation temperatures on the interatomic potentials, the existence of a surface-melted phase, and the absence of a premelting peak in heat capacity curves. We also find a new type of premelting mechanism in double icosahedral Pd19 clusters, where one of the two internal atoms escapes to the surface at the premelting temperature.Peer reviewe

All-rounder: A flexible DNN accelerator with diverse data format support

Recognizing the explosive increase in the use of DNN-based applications, several industrial companies developed a custom ASIC (e.g., Google TPU, IBM RaPiD, Intel NNP-I/NNP-T) and constructed a hyperscale cloud infrastructure with it. The ASIC performs operations of the inference or training process of DNN models which are requested by users. Since the DNN models have different data formats and types of operations, the ASIC needs to support diverse data formats and generality for the operations. However, the conventional ASICs do not fulfill these requirements. To overcome the limitations of it, we propose a flexible DNN accelerator called All-rounder. The accelerator is designed with an area-efficient multiplier supporting multiple precisions of integer and floating point datatypes. In addition, it constitutes a flexibly fusible and fissionable MAC array to support various types of DNN operations efficiently. We implemented the register transfer level (RTL) design using Verilog and synthesized it in 28nm CMOS technology. To examine practical effectiveness of our proposed designs, we designed two multiply units and three state-of-the-art DNN accelerators. We compare our multiplier with the multiply units and perform architectural evaluation on performance and energy efficiency with eight real-world DNN models. Furthermore, we compare benefits of the All-rounder accelerator to a high-end GPU card, i.e., NVIDIA GeForce RTX30390. The proposed All-rounder accelerator universally has speedup and high energy efficiency in various DNN benchmarks than the baselines

Thermally activated flux flow in superconducting epitaxial FeSe0.6Te0.4 thin film

AbstractThe thermally activated flux flow effect has been studied in epitaxial FeSe0.6Te0.4 thin film grown by a PLD method through the electrical resistivity measurement under various magnetic fields for B//c and B//ab. The results showed that the thermally activated flux flow effect is well described by the nonlinear temperature-dependent activation energy. The evaluated apparent activation energy U0(B) is one order larger than the reported results and showed the double-linearity in both magnetic field directions. Furthermore, the FeSe0.6Te0.4 thin film shows the anisotropy of 5.6 near Tc and 2D-like superconducting behavior in thermally activated flux flow region. In addition, the vortex glass transition and the temperature dependence of the high critical fields were determined

Design Method for Negative Group Delay Circuits Based on Relations among Signal Attenuation, Group Delay, and Bandwidth

Typical negative group delay circuits (NGDC) are analyzed in terms of signal attenuation, group delay, and bandwidth using S-parameters. By inverting these formulations, we derive and present the design equations (for NGD circuit elements) for a desired specification of the two among the three parameters. The proposed design method is validated through simulation examples for narrow- and wide-band pulse inputs in the time and frequency domains. Moreover, an NGDC composed of lumped elements is fabricated at 1 GHz for measurement. As a function of frequency, the circuit-/EM-simulated and measured group delays are in good agreement. The provided simple NGDC design equations may be useful for many applications that require compensations of some signal delays

MONITORING NODE SELECTION ALGORITHM FOR INTRUSION DETECTION IN CONGESTED SENSOR NETWORK

Abstract: Since wireless resources are limited, an efficient way of utilizing wireless resources is needed in selecting IDSs. We propose a monitoring node selection scheme for intrusion detection in congested wireless sensor network. Network congestion is an important issue in mobile network. The network congestion does not guarantee a proper detection rate and congested networks should cause an unreliable network. We consider congested intrusion detection tasks by queuing theory. We confirm that proposed algorithm guarantee QoS of monitoring tasks and reliable sensor networks

Breathing silicon anodes for durable high-power operations

Silicon anode materials have been developed to achieve high capacity lithium ion batteries for operating smart phones and driving electric vehicles for longer time. Serious volume expansion induced by lithiation, which is the main drawback of silicon, has been challenged by multi-faceted approaches. Mechanically rigid and stiff polymers (e.g. alginate and carboxymethyl cellulose) were considered as the good choices of binders for silicon because they grab silicon particles in a tight and rigid way so that pulverization and then break-away of the active mass from electric pathways are suppressed. Contrary to the public wisdom, in this work, we demonstrate that electrochemical performances are secured better by letting silicon electrodes breathe in and out lithium ions with volume change rather than by fixing their dimensions. The breathing electrodes were achieved by using a polysaccharide (pullulan), the conformation of which is modulated from chair to boat during elongation. The conformational transition of pullulan was originated from its a glycosidic linkages while the conventional rigid polysaccharide binders have beta linkagesopen1

Acute myocarditis associated with non-typhoidal Salmonella gastroenteritis

Acute myocarditis is clinically rare in children, but poses a significant risk for morbidity and mortality. Children with myocarditis show a wide variety of clinical manifestations ranging from subclinical myocarditis to heart failure, hemodynamic compromise, arrhythmia, and even sudden death. Salmonella species are associated with clinical presentations including gastroenteritis, enteric fever, bacteremia, and extra-intestinal focal infections. Non-typhoidal Salmonella infections usually cause self-limiting gastroenteritis, but are rarely associated with myocarditis. In this report, we present a case of myocarditis associated with Salmonella serogroup B gastroenteritis in a previously healthy 15-year-old boy