Dynamical Modelling and a Decentralized Adaptive Controller for a 12-Tetrahedral Rolling Robot

The 12-tetrahedral robot is an addressable reconfigurable technology (ART)-based variable geometry truss mechanism with twenty-six extensible struts and nine nodes arranged in a tetrahedral mesh. The robot has the capability of reconfiguring shape and dimension for environment sensing requirements, which makes it suitable for space exploration and environmental perception. In this paper, we have derived a dynamics model and presented a decentralized adaptive controller for a 12-tetrahedral robot. First, the robot is divided into the node and the strut subsystems, and the kinetic and the potential energy are calculated for the two subsystems. Then, the dynamics model is achieved by applying the Lagrangian formalism on the total energy of the robot. Since the dynamics is too complicated for implementing model-based controllers, a two-layer controller is presented to control the robot, in which the planning layer determines gait and trajectory of the robot, and the executive layer adopts the decentralized adaptive control strategy and consists of twenty-six strut controllers. Each strut controller regulates the movement of the corresponding strut without information exchange with other struts. Co-simulations based on ADAMS and Matlab have been conducted to verify the feasibility and effectiveness of the proposed controller

THE INFLUENCE OF CHROMATIC ABERRATION ON DEMOSAICKING

International audienceThe wide deployment of colour imaging devices owes much to the use of colour filter array (CFA). A CFA produces a mosaic image, and normally a subsequent CFA demosaick-ing algorithm interpolates the mosaic image and estimates the full-resolution colour image. Among various types of optical aberrations from which a mosaic image may suffer, chromatic aberration (CA) influences the spatial and spectral correlation through the artefacts such as blur and mis-registration, which demosaicking also relies on. In this paper we propose a simulation framework aimed at an investigation of the influence of CA on demosaicking. Results show that CA benefits de-mosaicking to some extent, however CA lowers the quality of resulting images by any means

Programmed Design of a Lithium–Sulfur Battery Cathode by Integrating Functional Units

Sulfur is considered to be one of the most promising cathode materials due to its high theoretical specific capacity and low cost. However, the insulating nature of sulfur and notorious “shuttle effect” of lithium polysulfides (LiPSs) lead to severe loss of active sulfur, poor redox kinetics, and rapid capacity fade. Herein, a hierarchical electrode design is proposed to address these issues synchronously, which integrates multiple building blocks with specialized functions into an ensemble to construct a self‐supported versatile cathode for lithium–sulfur batteries. Nickel foam acts as a robust conductive scaffold. The heteroatom‐doped host carbon with desired lithiophilicity and electronic conductivity serving as a reservoir for loading sulfur can trap LiPSs and promote electron transfer to interfacial adsorbed LiPSs and Ni3S2 sites. The sulfurized carbon nanofiber forest can facilitate the Li‐ion and electron transport and retard the LiPSs diffusion as a barrier layer. Sulfiphilic Ni3S2 acts as both a chemical anchor with strong adsorption affinity to LiPSs and an efficient electrocatalyst for accelerating kinetics for redox conversion reactions. Synergistically, all functional units promote the lithium ion coupled electron transfer for binding and redox conversion of LiPSs, resulting in high reversible capacities, remarkable cycle stability, and excellent rate capability

Coherent manipulation of spin wave vector for polarization of photons in an atomic ensemble

We experimentally demonstrate the manipulation of two-orthogonal components of a spin wave in an atomic ensemble. Based on Raman two-photon transition and Larmor spin precession induced by magnetic field pulses, the coherent rotations between the two components of the spin wave is controllably achieved. Successively, the two manipulated spin-wave components are mapped into two orthogonal polarized optical emissions, respectively. By measuring Ramsey fringes of the retrieved optical signals, the \pi/2-pulse fidelity of ~96% is obtained. The presented manipulation scheme can be used to build an arbitrary rotation for qubit operations in quantum information processing based on atomic ensembles

Discrete wavelet transform based multispectral filter array demosaicking

International audienceThe idea of colour filter array may be adapted to multi-spectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for mul-tispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking

CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models

Recently, large pretrained language models have achieved compelling performance on commonsense benchmarks. Nevertheless, it is unclear what commonsense knowledge the models learn and whether they solely exploit spurious patterns. Feature attributions are popular explainability techniques that identify important input concepts for model outputs. However, commonsense knowledge tends to be implicit and rarely explicitly presented in inputs. These methods cannot infer models' implicit reasoning over mentioned concepts. We present CommonsenseVIS, a visual explanatory system that utilizes external commonsense knowledge bases to contextualize model behavior for commonsense question-answering. Specifically, we extract relevant commonsense knowledge in inputs as references to align model behavior with human knowledge. Our system features multi-level visualization and interactive model probing and editing for different concepts and their underlying relations. Through a user study, we show that CommonsenseVIS helps NLP experts conduct a systematic and scalable visual analysis of models' relational reasoning over concepts in different situations.Comment: This paper is accepted by IEEE VIS, 2023. To appear in IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG). 14 pages, 11 figure

Quantum Interference of Stored Coherent Spin-wave Excitations in a Two-channel Memory

Quantum memories are essential elements in long-distance quantum networks and quantum computation. Significant advances have been achieved in demonstrating relative long-lived single-channel memory at single-photon level in cold atomic media. However, the qubit memory corresponding to store two-channel spin-wave excitations (SWEs) still faces challenges, including the limitations resulting from Larmor procession, fluctuating ambient magnetic field, and manipulation/measurement of the relative phase between the two channels. Here, we demonstrate a two-channel memory scheme in an ideal tripod atomic system, in which the total readout signal exhibits either constructive or destructive interference when the two-channel SWEs are retrieved by two reading beams with a controllable relative phase. Experimental result indicates quantum coherence between the stored SWEs. Based on such phase-sensitive storage/retrieval scheme, measurements of the relative phase between the two SWEs and Rabi oscillation, as well as elimination of the collapse and revival of the readout signal, are experimentally demonstrated

Anchorage: Visual Analysis of Satisfaction in Customer Service Videos via Anchor Events

Delivering customer services through video communications has brought new opportunities to analyze customer satisfaction for quality management. However, due to the lack of reliable self-reported responses, service providers are troubled by the inadequate estimation of customer services and the tedious investigation into multimodal video recordings. We introduce Anchorage, a visual analytics system to evaluate customer satisfaction by summarizing multimodal behavioral features in customer service videos and revealing abnormal operations in the service process. We leverage the semantically meaningful operations to introduce structured event understanding into videos which help service providers quickly navigate to events of their interest. Anchorage supports a comprehensive evaluation of customer satisfaction from the service and operation levels and efficient analysis of customer behavioral dynamics via multifaceted visualization views. We extensively evaluate Anchorage through a case study and a carefully-designed user study. The results demonstrate its effectiveness and usability in assessing customer satisfaction using customer service videos. We found that introducing event contexts in assessing customer satisfaction can enhance its performance without compromising annotation precision. Our approach can be adapted in situations where unlabelled and unstructured videos are collected along with sequential records.Comment: 13 pages. A preprint version of a publication at IEEE Transactions on Visualization and Computer Graphics (TVCG), 202

EmoCo: Visual analysis of emotion coherence in presentation videos

Emotions play a key role in human communication and public presentations. Human emotions are usually expressed through multiple modalities. Therefore, exploring multimodal emotions and their coherence is of great value for understanding emotional expressions in presentations and improving presentation skills. However, manually watching and studying presentation videos is often tedious and time-consuming. There is a lack of tool support to help conduct an efficient and in-depth multi-level analysis. Thus, in this paper, we introduce EmoCo, an interactive visual analytics system to facilitate efficient analysis of emotion coherence across facial, text, and audio modalities in presentation videos. Our visualization system features a channel coherence view and a sentence clustering view that together enable users to obtain a quick overview of emotion coherence and its temporal evolution. In addition, a detail view and word view enable detailed exploration and comparison from the sentence level and word level, respectively. We thoroughly evaluate the proposed system and visualization techniques through two usage scenarios based on TED Talk videos and interviews with two domain experts. The results demonstrate the effectiveness of our system in gaining insights into emotion coherence in presentations.Comment: 11 pages, 8 figures. Accepted by IEEE VAST 201