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Ultrathin active polarization-selective metasurface at X-band frequencies

Physical Review B 2019年第7期100卷 075131-075131页

作者： Josip Lončar Anthony Grbic Silvio Hrabar Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 10000 Zagreb Croatia Radiation Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor Michigan 48109-2122 USA

An ultrathin active polarization-selective metasurface is designed and optimized for operation in the X band. The metasurface leverages the design of a previously reported passive polarization converting metasurface. Similar to the passive polarization converter, the proposed active metasurface consists of three patterned metallic sheets. Its bottom sheet is modified and populated with ultrawideband, unconditionally stable amplifiers and corresponding biasing networks. The metasurface provides over 35 dB of input-output isolation achieved through orthogonal polarizations, which ensures stable operation. It was fabricated with a low-cost, printed-circuit-board and pick-and-place process. The performance of the metasurface was measured and its stability confirmed. The desired effects of amplification, polarization conversion, polarization selectivity, and nonreciprocal behavior were successfully demonstrated in both full-wave simulations and measurements. Due to its extremely small thickness (0.66 mm or 0.02λ at 10 GHz), the metasurface shows excellent performance for a wide range of incident angles, which exceeds ±30∘. It achieves a perfect (100%) polarization conversion ratio in simulation, and 98.4% in measurement.

关键词： Metamaterials Polarization

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Quantum circuit architecture search for variational quantum algorithms

arXiv

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arXiv 2020年

作者： Du, Yuxuan Huang, Tao You, Shan Hsieh, Min-Hsiu Tao, Dacheng Ubtech Sydney Ai Centre School of Computer Science Faculty of Engineering The University of Sydney NSW2008 Australia Jd Explore Academy Beijing101111 China SenseTime Beijing100080 China Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney NSW2007 Australia Hon Hai Quantum Computing Research Center Taipei114 Taiwan

Variational quantum algorithms (VQAs) are expected to be a path to quantum advantages on noisy intermediate-scale quantum devices. However, both empirical and theoretical results exhibit that the deployed ansatz heavily affects the performance of VQAs such that an ansatz with a larger number of quantum gates enables a stronger expressivity, while the accumulated noise may render a poor trainability. To maximally improve the robustness and trainability of VQAs, here we devise a resource and runtime efficient scheme termed quantum architecture search (QAS). In particular, given a learning task, QAS automatically seeks a near-optimal ansatz (i.e., circuit architecture) to balance benefits and side-effects brought by adding more noisy quantum gates to achieve a good performance. We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks. In the problems studied, numerical and experimental results show that QAS can not only alleviate the influence of quantum noise and barren plateaus, but also outperforms VQAs with pre-selected ansatze. © 2020, CC BY-NC-ND.

关键词： Timing circuits

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Preface

Green Energy and Technology

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Green Energy and Technology 2021年 v-vi页

作者： Balusamy, Balamurugan Chilamkurti, Naveen Kadry, Seifedine School of Computing Science and Engineering Galgotias University Greater Noida Delhi India Mathematics and Computer Science Faculty of Science Beirut Arab University Beirut Lebanon Computer Science and Information Technology La Trobe University MelbourneVIC Australia

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Advances in natural language question answering: A review

arXiv

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arXiv 2019年

作者： Ishwari, K.S.D. Aneeze, A.K.R.R. Sudheesan, S. Karunaratne, H.J.D.A. Nugaliyadde, A. Mallawarrachchi, Y. Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka College of Science Health Engineering and Education Australia

Question Answering has recently received high attention from artificial intelligence communities due to the advancements in learning technologies. Early question answering models used rule-based approaches and moved to the statistical approach to address the vastly available information. However, statistical approaches are shown to underperform in handling the dynamic nature and the variation of language. Therefore, learning models have shown the capability of handling the dynamic nature and variations in language. Many deep learning methods have been introduced to question answering. Most of the deep learning approaches have shown to achieve higher results compared to machine learning and statistical methods. The dynamic nature of language has profited from the nonlinear learning in deep learning. This has created prominent success and a spike in work on question answering. This paper discusses the successes and challenges in question answering question answering systems and techniques that are used in these challenges. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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From QoS distributions to qoe distributions: A system⇔s perspective

arXiv

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arXiv 2020年

作者： Hoßfeld, Tobias Heegaard, Poul E. Varela, Martín Skorin-Kapov, Lea Fiedler, Markus Department of Communication Networks University of Würzburg Germany NTNU Norwegian University of Science and Technology Trondheim Norway Oulu Finland Faculty of Electrical Engineering and Computing University of Zagreb Croatia Blekinge Institute of Technology Dept. of Technology and Aesthetics Karlshamn Sweden

In the context of QoE management, network and service providers commonly rely on models that map system QoS conditions (e.g., system response time, paket loss, etc.) to estimated end user QoE values. Observable QoS conditions in the system may be assumed to follow a certain distribution, meaning that different end users will experience different conditions. On the other hand, drawing from the results of subjective user studies, we know that user diversity leads to distributions of user scores for any given test conditions (in this case referring to the QoS parameters of interest). Our previous studies have shown that to correctly derive various QoE metrics (e.g., Mean Opinion Score (MOS), quantiles, probability of users rating "good or better", etc.) in a system under given conditions, there is a need to consider rating distributions obtained from user studies, which are often times not available. In this paper we extend these findings to show how to approximate user rating distributions given a QoS-to-MOS mapping function and second order statistics. Such a user rating distribution may then be combined with a QoS distribution observed in a system to finally derive corresponding distributions of QoE scores. We provide two examples to illustrate this process: 1) analytical results using a Web QoE model relating waiting times to QoE, and 2) numerical results using measurements relating packet losses to video stall pattern, which are in turn mapped to QoE estimates. Copyright © 2020, The Authors. All rights reserved.

关键词： Probability distributions

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Fast consensus clustering in complex networks

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Physical Review E 2019年第4期99卷 042301-042301页

作者： Aditya Tandon Aiiad Albeshri Vijey Thayananthan Wadee Alhalabi Santo Fortunato School of Informatics Computing and Engineering Indiana University Bloomington Indiana 47408 USA Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah 21589 Kingdom of Saudi Arabia Indiana University Network Science Institute (IUNI) Bloomington Indiana 47408 USA

Algorithms for community detection are usually stochastic, leading to different partitions for different choices of random seeds. Consensus clustering has proven to be an effective technique to derive more stable and accurate partitions than the ones obtained by the direct application of the algorithm. However, the procedure requires the calculation of the consensus matrix, which can be quite dense if (some of) the clusters of the input partitions are large. Consequently, the complexity can get dangerously close to quadratic, which makes the technique inapplicable on large graphs. Here, we present a fast variant of consensus clustering, which calculates the consensus matrix only on the links of the original graph and on a comparable number of additional node pairs, suitably chosen. This brings the complexity down to linear, while the performance remains comparable as the full technique. Therefore, our fast consensus clustering procedure can be applied on networks with millions of nodes and links.

关键词： Patterns in complex systems

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Network and Systems Medicine: Position Paper of the European Collaboration on science and Technology Action on Open Multiscale Systems Medicine

Network and Systems Medicine

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Network and Systems Medicine 2020年第1期3卷 67-90页

作者： Comte, Blandine Baumbach, Jan Benis, Arriel Basílio, José Debeljak, Nataša Flobak, Åsmund Franken, Christian Harel, Nissim He, Feng Kuiper, Martin Méndez Pérez, Juan Albino Pujos-Guillot, Estelle Reen, Tadeja Rozman, Damjana Schmid, Johannes A. Scerri, Jeanesse Tieri, Paolo Van Steen, Kristel Vasudevan, Sona Watterson, Steven Schmidt, Harald H.H.W. Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Université Clermont Auvergne INRAE UNH Clermont-Ferrand France Freising-Weihenstephan Germany Holon Institute of Technology Holon Israel Institute of Vascular Biology and Thrombosis Research Center for Physiology and Pharmacology Medical University of Vienna Vienna Austria Medical Centre for Molecular Biology Institute of Biochemistry Faculty of Medicine University of Ljubljana Ljubljana Slovenia Department of Clinical and Molecular Medicine Norwegian University of Science and Technology Trondheim Norway The Cancer Clinic St. Olav's University Hospital Trondheim Norway Digital Health Systems Einsingen Germany Department of Pharmacology and Personalised Medicine Faculty of Health Medicine and Life Science Maastricht University Maastricht Netherlands Department of Infection and Immunity Luxembourg Institute of Health Esch-sur-Alzette Luxembourg Institute of Medical Microbiology University Hospital Essen University of Duisburg-Essen Essen Germany Department of Biology Faculty of Natural Sciences Norwegian University of Science and Technology Trondheim Norway Department of Computer Science and Systems Engineering Universidad de la Laguna Tenerife Spain Centre for Functional Genomics and Bio-Chips Institute of Biochemistry Faculty of Medicine University of Ljubljana Ljubljana Slovenia Department of Physiology and Biochemistry Faculty of Medicine and Surgery University of Malta Msida Malta CNR National Research Council IAC Institute for Applied Computing Rome Italy GIGA-R Medical Genomics-BIO3 University of Liège Liège Belgium Georgetown University Medical Centre WashingtonDC United States Northern Ireland Centre for Stratified Medicine Ulster University Londonderry United Kingdom Department of Pharmacology and Personalised Medicine Faculty of Health Medicine and Life Science MeHNS Maastricht University Netherlands

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ-and symptom-based medical concepts toward network-and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management. © Blandine Comte et al. 2020;Published by Mary Ann Liebert, Inc. 2020.

关键词： Big data

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Uncertainty propagation analysis of dielectric elastomer with interval parameters

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science China(Physics,Mechanics & Astronomy) 2018年第5期61卷 61-64页

作者： YunLong Li XiaoJun Wang Chong Wang MengHui Xu Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign Institute of Solid Mechanics Beihang University Institute of Scientific Computing Technische Universit?t Braunschweig Faculty of Mechanical Engineering & Mechanics Ningbo University

In the recent years,dielectric elastomers（DEs） have become the most popular actuators owing to their special properties such as large deformation,light weight,flexibility,and chemical and biological compatibility in... 详细信息

关键词：弹性体绝缘繁殖特殊性质致动器轻重量软材料相容性

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DeepTrust: A Deep User Model of Homophily Effect for Trust Prediction

DeepTrust: A Deep User Model of Homophily Effect for Trust P...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Qi Wang Weiliang Zhao Jian Yang Jia Wu Wenbin Hu Qianli Xing Department of Computing Faculty of Science and Engineering Macquarie University Sydney Australia School of Computer Wuhan University Wuhan China

Trust prediction in online social networks is crucial for information dissemination, product promotion, and decision making. Existing work on trust prediction mainly utilizes the network structure or the low-rank approximation of a trust network. These approaches can suffer from the problem of data sparsity and prediction accuracy. Inspired by the homophily theory, which shows a pervasive feature of social and economic networks that trust relations tend to be developed among similar people, we propose a novel deep user model for trust prediction based on user similarity measurement. It is a comprehensive data sparsity insensitive model that combines a user review behavior and the item characteristics that this user is interested in. With this user model, we firstly generate a user's latent features mined from user review behavior and the item properties that the user cares. Then we develop a pair-wise deep neural network to further learn and represent these user features. Finally, we measure the trust relations between a pair of people by calculating the user feature vector cosine similarity. Extensive experiments are conducted on two real-world datasets, which demonstrate the superior performance of the proposed approach over the representative baseline works.

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Review and Analyzing RFID Technology Tags and Applications

Review and Analyzing RFID Technology Tags and Applications

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International Conference on Application of Information and Communication Technologies (AICT)

作者： Ag. Asri Ag. Ibrahim Kashif Nisar Yeoh Keng Hzou Ian Welch Faculty of Computing and Informatics Malaysia Sabah Malaysia School of Engineering and Computer Science Victoria University of Wellington New Zealand

This review paper is based on Radio Frequency Identification (RFID) technology, Wireless Sensor Networks (WSNs) and wireless information & communication networks. RFID technology use for tags and readers enclosed to shop-floor industrial stuffs such as operators, terminals, vessels, stocks and Smart Home (SH) architecture that includes sensors, data communication and data integration. The system collect movement based activities data from the objects using Radio Frequency Identification (RFID) technology. Passive RFID tags can be deliver at a gap and do not require a Line of Sight Antenna (LoSA) between tag and reader. Furthermore, RFID is an another expertise with a prospective to substitute old technology such as Universal Product Code (UPC) barcodes reader over network. In this review paper also discussed why RFID is chosen between other sensors.

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