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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Teichmann, Marvin Weber, Michael Zöllner, Marius Cipolla, Roberto Urtasun, Raquel Department of Computer Science University of Toronto Canada FZI Research Center for Information Technology Karlsruhe Germany Department of Engineering University of Cambridge United Kingdom Uber Advanced Technologies Group United Kingdom

ISBN: (纸本)9781538644522

While most approaches to semantic reasoning have focused on improving performance, in this paper we argue that computational times are very important in order to enable real time applications such as autonomous driving. Towards this goal, we present an approach to joint classification, detection and semantic segmentation using a unified architecture where the encoder is shared amongst the three tasks. Our approach is very simple, can be trained end-to-end and performs extremely well in the challenging KITTI dataset. Our approach is also very efficient, allowing us to perform inference at more then 23 frames per second. Training scripts and trained weights to reproduce our results can be found here: https://***/MarvinTeichmann/MultiNet. © 2018 IEEE.

关键词： Autonomous vehicles

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Synthese an der Wasseroberfläche von Vinylen-Verbundenen Kationischen Zwei-Dimensionalen Polymerfilmen als Beschichtung für Anion-Selektive Elektroden

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Angewandte Chemie 2024年第24期136卷

作者： Ye Yang Davood Sabaghi Dr. Chang Liu Dr. Arezoo Dianat David Mücke Dr. Haoyuan Qi Dr. Yannan Liu Dr. Mike Hambsch Prof. Zhi-Kang Xu Dr. Minghao Yu Prof. Gianaurelio Cuniberti Prof. Stefan C. B. Mannsfeld Prof. Ute Kaiser Prof. Renhao Dong Dr. Zhiyong Wang Prof. Xinliang Feng Center for Advancing Electronics Dresden & Faculty of Chemistry and Food Chemistry Technische Universität Dresden 01069 Dresden Germany Diese Autoren haben gleichermaßen zu dieser Arbeit beigetragen. MOE Engineering Research Center of Membrane and Water Treatment and Key Lab of Adsorption and Separation Materials & Technologies of Zhejiang Province Department of Polymer Science and Engineering Zhejiang University 310058 Hangzhou China The “Belt and Road” Sino-Portugal Joint Lab on Advanced Materials International Research Center for X Polymers Zhejiang University 310058 Hangzhou China Max Planck Institute of Microstructure Physics 06120 Halle Germany Institute for Materials Science and Max Bergmann Center for Biomaterials Technische Universität Dresden 01069 Dresden Germany Central Facility for Electron Microscopy Electron Microscopy of Materials Science Universität Ulm 89081 Ulm Germany Center for Advancing Electronics Dresden & Faculty of Electrical and Computer Engineering Technische Universität Dresden 01062 Dresden Germany Dresden Center for Computational Materials Science (DCMS) Technische Universität Dresden 01062 Dresden Germany Key Laboratory of Colloid and Interface Chemistry of the Ministry of Education School of Chemistry and Chemical Engineering Shandong University 250100 Jinan China

Vinylen verbrückte zwei-dimensionale Polymere (V-2DPs) und deren schichtgestapelten kovalent organische Gerüstverbindungen (V-2D COFs) zeichnen sich durch ihre hohe π-Konjugation in der Ebene und ihre robuste Struktur als vielversprechnende Kanidaten für energiebezogene Anwendungen aus. Allerdings sind derzeitige syntheisische Ansätze auf die Herstellung von V-2D COF Pulver beschränkt, welche schlecht prozessierbar sind, was die Integration in Geräte, insbesondere für Membranthechnologien, welche auf dünnen Filmen beruhen erschwert. Im folgenden berichten wir über die neu-artige Synthese von kationischen 2DPs-Filmen an der Wasseroberfläche, die über Vinyleneinheiten verbrückt sind ( V-C2DP-1 und V-C2DP-2 ) mittels Knoevenagel-Polykondensation, diese dienen als anionenselektive Elektrodenbeschichtung für hochreversible und langlebige Zink-basierte Dual-Ionen-Batterien (ZDIBs). Modellreaktionen und theoretische Modellierung zeigen eine erhöte Reaktivität und Reversibilität der Knoevenagel-Reaktion an der Wasseroberfläche an. Basierend darauf zeigten wir die 2D Polykondensation hin zu V-C2DP-Filmen an der Wasseroberfläche, welche eine weitreichen-de laterale Größe, anpassbare Dicke und hohe chemischer Stabilität besitzen. Repräsentativ zeigt sich V-C2DP-1 als ein vollständig crystalliner und flächen-orientierter Film mit den in der Ebene liegenden Gitterparametern von a =b≈43.3 Å. Dank der gut definierten katinoischen Funktionalitäten, orientierten 1D-Kanälen und des sabilen Gerüstes besitzt der V-C2DP-1 Film eine herausragende Transportselektivität von Bis(trifluormethansulfon)imid-anion (TFSI − ) (Transferrate, t =0.85) für die Graphitkathode in Hochspannungs-ZDIBs. Die hohe Selektivität führt zu zusätzlichen TFSI − -Intercalationsstufen wodurch eine höhere spezifischen Kapazität (von ~83 bis 124 mAh g −1 ), sowie Zyklusdauer (>1000 Zyklen, 95 % Kapazitätserhaltung) gefördert wird.

关键词： Grenzflächen Chemie Vinylen-verbundene 2DP Filme Selektiver Iontransport Elektroden Beschicktung Zwei-Ionen Batterien

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Enhanced metric learning via dempster-shafer evidence theory 25th

Enhanced metric learning via dempster-shafer evidence theory

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25th International Conference on Neural Information Processing, ICONIP 2018

作者： Li, Ying Zhang, Yabo Peng, Yaxin School of Computer Engineering and Science Shanghai University Shanghai200444 China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China Department of Mathematics School of Science Shanghai University Shanghai200444 China

ISBN: (纸本)9783030041816

Metric learning is a hot topic in machine learning. A proper learned metric can measure the similarity between samples better and hence significantly improves the performance of machine learning algorithm. In this paper, we propose a novel enhanced distance metric learning method via Dempster-Shafer (D-S) evidence theory. We consider each instance as an independent source of evidence and combine these pieces of evidence by using Dempster’s rule. Firstly, with reference to the D-S theory, we construct the balanced weight function corresponding to each instance in the metric. Secondly, the novel competitive-cost function is given, which can improve classifier accuracy by narrowing the inner-class distance and increasing the inter-class distance. Finally, we implement a series of experiments on classification by using UCI and face recognition data sets. Experimental results validate that the proposed method can significantly improve the performance of the classifier and the robustness of the algorithm. © Springer Nature Switzerland AG 2018.

关键词： Classification (of information)

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Learning to Match 2D Images and 3D LiDAR Point Clouds for Outdoor Augmented Reality

Learning to Match 2D Images and 3D LiDAR Point Clouds for Ou...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Weiquan Liu Baiqi Lai Cheng Wang Xuesheng Bian Wentao Yang Yan Xia Xiuhong Lin Shang-Hong Lai Dongdong Weng Jonathan Li Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen China Photogrammetry and Remote Sensing Technical University of Munich Munich Germany Department of Computer Science National Tsing Hua University Hsinchu Taiwan Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Photonics Beijing Institute of Technology Beijing China Department of Geography and Environmental Management University of Waterloo Waterloo Canada

ISBN: (数字)9781728165325

ISBN: (纸本)9781728165332

Large-scale Light Detection and Ranging (LiDAR) point clouds provide basic 3D information support for Augmented Reality (AR) in outdoor environments. Especially, matching 2D images across to 3D LiDAR point clouds can establish the spatial relationship of 2D and 3D space, which is a solution for the virtual-real registration of AR. This paper first provides a precise 2D-3D patch-volume dataset, which contains paired matching 2D image patches and 3D LiDAR point cloud volumes, by using the Mobile Laser Scanning (MLS) data from the urban scene. Second, we propose an end-to-end network, Siam2D3D-Net, to jointly learn local feature representations for 2D image patches and 3D LiDAR point cloud volumes. Experimental results indicate the proposed Siam2D3D-Net can match and establish 2D-3D correspondences from the query 2D image to the 3D LiDAR point cloud reference map. Finally, an application is used to evaluate the possibility of the proposed virtual-real registration of AR in outdoor environments.

关键词： Three-dimensional displays Two dimensional displays Laser radar Cameras Feature extraction Augmented reality Remote sensing

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Frontoparietal connectivity neurofeedback training for promotion of working memory: An fNIRS study in healthy male participants

arXiv

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arXiv 2020年

作者： Xia, Meiyun Xu, Pengfei Yang, Yuanbin Jiang, Wenyu Wang, Zehua Gu, Xiaolei Yang, Mingxi Li, Deyu Li, Shuyu Dong, Guijun Wang, Ling Wang, Daifa School of Biological Science and Medical Engineering Beihang University Beijing100083 China College of Computer Science Sichuan Normal University Chengdu610101 China Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing100083 China State Key Laboratory of Virtual Reality Technology and System Beihang University Beijing100083 China Department of Rehabilitation Medicine Wangjing Hospital China Academy of Chinese Medical Sciences Beijing100102 China Department of Neurological Rehabilitation Guangxi Jiangbin Hospital Nanning530021 China School of Sports and Health Shandong Sport University Jinan250102 China

Neurofeedback cognitive training is a promising tool used to promote cognitive functions effectively and efficiently. In this study, we investigated a novel functional near-infrared spectroscopy (fNIRS)based frontoparietal functional connectivity (FC) neurofeedback training paradigm related to working memory, involving healthy adults. Compared with conventional cognitive training studies, we chose the frontoparietal network, a key brain region for cognitive function modulation, as neurofeedback, yielding a strong targeting effect. In the experiment, 10 participants (test group) received three cognitive training sessions of 15 min using fNIRS-based frontoparietal FC as neurofeedback, and another 10 participants served as the control group. Frontoparietal FC was significantly increased in the test group (p = 0.03), and the cognitive functions (memory and attention) were significantly promoted compared with the control group (accuracy of 3-back test: p = 0.0005, reaction time of 3-back test: p = 0.0009). After additional validations on long-term training effect and on different patient populations, the proposed method exhibited considerable potential to be developed as a fast, effective, and widespread training approach for cognitive function enhancement. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain

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Quantum technologies for climate change: Preliminary assessment

arXiv

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arXiv 2021年

作者： Berger, Casey Paolo, Agustin Di Forrest, Tracey Hadfield, Stuart Sawaya, Nicolas Stęchly, Michal Thibault, Karl Department of Physics Smith College NorthamptonMA01063 United States Boston University Rafik B Hariri Institute for Computing and Computational Science & Engineering BostonMA02215 United States Département de physique Institut quantique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Transformative Quantum Technologies University of Waterloo WaterlooON Canada USRA Research Institute for Advanced Computer Science Mountain ViewCA94043 United States Intel Labs Santa ClaraCA95054 United States Zapata Computing Canada Inc. 325 Front St W TorontoONM5V 2Y1 Canada

Climate change presents an existential threat to human societies and the Earth’s ecosystems more generally. Mitigation strategies naturally require solving a wide range of challenging problems in science, engineering, and economics. In this context, rapidly developing quantum technologies in computing, sensing, and communication could become useful tools to diagnose and help mitigate the effects of climate change. However, the intersection between climate and quantum sciences remains largely unexplored. This preliminary report aims to identify potential high-impact use-cases of quantum technologies for climate change with a focus on four main areas: simulating physical systems, combinatorial optimization, sensing, and energy efficiency. We hope this report provides a useful resource towards connecting the climate and quantum science communities, and to this end we identify relevant research questions and next steps. Copyright © 2021, The Authors. All rights reserved.

关键词： Climate change

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Search for leptoquark pair production decaying into or in multi-lepton final states in pp collisions at with the ATLAS detector

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The European Physical Journal C 2024年第8期84卷 1-40页

作者： Aad, G. Abbott, B. Abbott, D. C. Abeling, K. Abidi, S. H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Hoffman, A. C. Abusleme Acharya, B. S. Achkar, B. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Addepalli, S. V. Adelman, J. Adiguzel, A. Adorni, S. Adye, T. Affolder, A. A. Afik, Y. Agaras, M. N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahmad, A. Ahmadov, F. Ahmed, W. S. Ahuja, S. Ai, X. Aielli, G. Aizenberg, I. Akbiyik, M. Åkesson, T. P. A. Akimov, A. V. Khoury, K. Al Alberghi, G. L. Albert, J. Albicocco, P. Alderweireldt, S. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexopoulos, T. Alfonsi, A. Alfonsi, F. Alhroob, M. Ali, B. Ali, S. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B. M. M. Allport, P. P. Aloisio, A. Alonso, F. Alpigiani, C. Camelia, E. Alunno Estevez, M. Alvarez Alviggi, M. G. Aly, M. Coutinho, Y. Amaral Ambler, A. Amelung, C. Amerl, M. Ames, C. G. Amidei, D. Santos, S. P. Amor Dos Amoroso, S. Amos, K. R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J. K. Andrean, S. Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A. V. Annovi, A. Antel, C. Anthony, M. T. Antipov, E. Antonelli, M. Antrim, D. J. A. Anulli, F. Aoki, M. Aoki, T. Pozo, J. A. Aparisi Aparo, M. A. Bella, L. Aperio Appelt, C. Aranzabal, N. Ferraz, V. Araujo Arcangeletti, C. Arce, A. T. H. Arena, E. Arguin, J-F. Argyropoulos, S. Arling, J.-H. Armbruster, A. J. Arnaez, O. Arnold, H. Tame, Z. P. Arrubarrena Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N. A. Assamagan, K. Astalos, R. Atkin, R. J. Atkinson, M. Atlay, N. B. Atmani, H. Atmasiddha, P. A. Augsten, K. Auricchio, S. Auriol, A. D. Austrup, V. A. Avner, G. Avolio, G. Axiotis, K. Ayoub, M. K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A. J. Bailey, V. R. Baines, J. T. Bakalis, C. Baker, O. K. Bakker, P. J. Bakos, E. Gupta, D. Bakshi Balaji, S. Balasubramanian, R. Baldin, E. M. Balek, P. Ballabene, E. Balli, F. Baltes, L. M. Balunas, W. K. Balz, J. Banas, E. Ban CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA Department of Physics University of Massachusetts Amherst USA II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Physics Department Brookhaven National Laboratory Upton USA Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York USA Departamento de Física Pontificia Universidad Católica de Chile Santiago Chile INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London UK LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics University of Toronto Toronto Canada Department of Physics Brandeis University Waltham USA Department of Physics Northern Illinois University DeKalb USA Department of Physics Istanbul University Istanbul Türkiye Département de Physique Nucléaire et Corpusculaire Université de Genève Geneva Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot UK Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz USA CERN Geneva Switzerland Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Departamento de Física Teórica y del Cosmos Universidad de Granada Granada Spain Affiliated with an International Laboratory Covered by a Coo

A search for leptoquark pair production decaying into $$te^- \bar{t}e^+$$ or $$t\mu ^- \bar{t}\mu ^+$$ in final states with multiple leptons is presented. The search is based on a dataset of pp collisions at $$\sqrt{s}=13~\text {TeV} $$ recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb $$^{-1}$$ . Four signal regions, with the requirement of at least three light leptons (electron or muon) and at least two jets out of which at least one jet is identified as coming from a b-hadron, are considered based on the number of leptons of a given flavour. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No excess above the Standard Model background prediction is observed and 95% confidence level limits on the production cross section times branching ratio are derived as a function of the leptoquark mass. Under the assumption of exclusive decays into $$te^{-}$$ ( $$t\mu ^{-}$$ ), the corresponding lower limit on the scalar mixed-generation leptoquark mass $$m_{\textrm{LQ}_{\textrm{mix}}^{\textrm{d}}}$$ is at 1.58 (1.59) TeV and on the vector leptoquark mass $$m_{{\tilde{U}}_1}$$ at 1.67 (1.67) TeV in the minimal coupling scenario and at 1.95 (1.95) TeV in the Yang–Mills scenario.

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Nonreciprocal Willis Coupling in Zero-Index Moving Media

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Physical Review Letters 2019年第6期123卷 064301-064301页

作者： Li Quan Dimitrios L. Sounas Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Electrical and Computer Engineering Wayne State University Detroit Michigan 48202 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Mechanical motion can break the symmetry in which sound travels in a medium, but significant nonreciprocity is typically achieved only for large motion speeds. We combine moving media with zero-index acoustic propagation, yielding extreme nonreciprocity and induced bianisotropy for modest applied speeds. The metamaterial is formed by an array of waveguides loaded by Helmholtz resonators, and it exhibits opposite signs of the refractive index sustained by asymmetric Willis coupling for propagation in opposite directions. We use this response to induce nonreciprocal positive-to-negative sound refraction, and we propose a nonreciprocal metamaterial lens focusing only with excitation from one side based on asymmetric Willis coupling.

关键词： Acoustic metamaterials Acoustic wave phenomena Acoustics

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Modeling and analysis of energy harvesting and smart grid-powered wireless communication networks: A contemporary survey

arXiv

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arXiv 2019年

作者： Hu, Shuyan Chen, Xiaojing Ni, Wei Wang, Xin Hossain, Ekram School of Information Science and Technology Fudan University Shanghai200433 China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China SydneyNSW2122 Australia Shanghai Institute for Advanced Communication and Data Science Department of Communication Science and Engineering Fudan University Shanghai200433 China Department of Electrical and Computer Engineering University of Manitoba WinnipegMBR3T 5V6 Canada

—The advancements in smart power grid and the advocation of "green communications" have inspired the wireless communication networks to harness energy from ambient environments and operate in an energy-efficient manner for economic and ecological benefits. This article presents a contemporary review of recent breakthroughs on the utilization, redistribution, trading and planning of energy harvested in future wireless networks interoperating with smart grids. This article starts with classical models of renewable energy harvesting technologies. We embark on constrained operation and optimization of different energy harvesting wireless systems, such as point-to-point, multipoint-to-point, multipoint-to-multipoint, multi-hop, and multi-cell systems. We also review wireless power and information transfer technologies which provide a special implementation of energy harvesting wireless communications. A significant part of the article is devoted to the redistribution of redundant (unused) energy harvested within cellular networks, the energy planning under dynamic pricing when smart grids are in place, and two-way energy trading between cellular networks and smart grids. Applications of different optimization tools, such as convex optimization, Lagrangian dual-based method, subgradient method, and Lyapunov-based online optimization, are compared. This article also collates the potential applications of energy harvesting techniques in emerging (or upcoming) 5G/B5G communication systems. It is revealed that an effective redistribution and two-way trading of energy can significantly reduce the electricity bills of wireless service providers and decrease the consumption of brown energy. A list of interesting research directions are provided, requiring further investigation. Copyright © 2019, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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Neural Network Analysis of Dynamic Fracture in a Layered Material

Neural Network Analysis of Dynamic Fracture in a Layered Mat...

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MRS Advances

作者： Rajak, Pankaj Kalia, Rajiv K. Nakano, Aiichiro Vashishta, Priya Argonne Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Collaboratory for Advanced Computing and Simulations University of Southern California Los AngelesCA90089 United States Department of Physics University of Southern California Los Angeles90089CA United States Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Chemical Engineering and Material Science University of Southern California Los AngelesCA90089 United States Department of Biological Sciences University of Southern California Los AngelesCA90089 United States

Dynamic fracture of a two-dimensional MoWSe2 membrane is studied with molecular dynamics (MD) simulation. The system consists of a random distribution of WSe2 patches in a pre-cracked matrix of MoSe2. Under strain, the system shows toughening due to crack branching, crack closure and strain-induced structural phase transformation from 2H to 1T crystal structures. Different structures generated during MD simulation are analyzed using a three-layer, feed-forward neural network (NN) model. A training data set of 36,000 atoms is created where each atom is represented by a 50-dimension feature vector consisting of radial and angular symmetry functions. Hyper parameters of the symmetry functions and network architecture are tuned to minimize model complexity with high predictive power using feature learning, which shows an increase in model accuracy from 67% to 95%. The NN model classifies each atom in one of the six phases which are either as transition metal or chalcogen atoms in 2H phase, 1T phase and defects. Further t-SNE analyses of learned representation of these phases in the hidden layers of the NN model show that separation of all phases become clearer in the third layer than in layers 1 and 2. Copyright © Materials Research Society 2018Â This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (.

关键词： Neural network models

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