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2017 IEEE International Magnetics Conference, INTERMAG 2017

作者： Ribeiro, P.M. Alfhadel, A. Kosel, J. Franco, F. Cardoso, S. Bernardino, A. Jamone, L. Santos-Victor, J. INESC - Microssistemas e Nanotecnologias and in Lisbon Portugal Physics Department Instituto Superior Técnico Lisbon Portugal Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Instituto de Sistemas e Robótica Instituto Superior Técnico Lisbon Portugal Advanced Robotics Centre Queen Mary University London United Kingdom

The detection of low-magnitude forces (under 1mN) is essential in applications that require either a very high sensitivity and resolution acquisition (e.g. detection of microfluidic flows) [1] or very high reliability... 详细信息

ISBN: (纸本)9781538610862

关键词： Anthropomorphic robots

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LED Lights with Hidden Intensity-Modulated Blue Channels Aiming for Enhanced Subconscious Visual Responses

IEEE Photonics Journal

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IEEE Photonics Journal 2017年第3期9卷 8201009页

作者： Vartanian, Garen Wong, Kwoon Y. Ku, Pei-Cheng Macromolecular Science and Engineering Graduate Program University of Michigan Ann ArborMI48109 United States Department of Ophthalmology and Visual Sciences University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

A new form of light-emitting diode (LED) light suitable for general illumination is proposed to enhance subconscious, nonimage-forming visual responses, which are essential to our well-being. Pulsing light has been shown to reduce photoreceptor adaptation and elicit stronger subconscious visual responses at an indoor illumination level. Using the silent substitution technique, a melanopsin-selective flicker can be added into white light. A linear optimization algorithm was developed to suppress any perceivable fluctuation of light intensity and colors of illuminated objects. Two examples of lights are given to illustrate the potential applications of the proposed multi-LED light for general illumination and therapeutic purposes. © 2009-2012 IEEE.

关键词： Light emitting diodes

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Zinc‐Based Flow Batteries: Advanced Materials for Zinc‐Based Flow Battery: Development and Challenge (Adv. Mater. 50/2019)

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Advanced Materials 2019年第50期31卷

作者： Zhizhang Yuan Yanbin Yin Congxin Xie Huamin Zhang Yan Yao Xianfeng Li Division of Energy Storage Dalian National Laboratory for Clean Energy Dalian Institute of Chemical Physics Chinese Academy of Sciences 457 Zhongshan Road Dalian 116023 P. R. China Collaborative Innovation Center of Chemistry for Energy Materials (iChEM) Dalian 116023 P. R. China Department of Electrical and Computer Engineering and Materials Science and Engineering Program University of Houston Houston TX 77204 USA

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Hybrid approach of relation network and localized graph convolutional filtering for breast cancer subtype classification

arXiv

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arXiv 2017年

作者： Rhee, Sungmin Seo, Seokjun Kim, Sun Department of Computer Science and Engineering Seoul National University Bioinformatics Institute Seoul National University Seoul Korea Republic of Interdisciplinary Program in Bioinformatics Seoul National University

Network biology has been successfully used to help reveal complex mechanisms of disease, especially cancer. On the other hand, network biology requires in-depth knowledge to construct diseasespecific networks, but our current knowledge is very limited even with the recent advances in human cancer biology. Deep learning has shown an ability to address the problem like this. However, it conventionally used grid-like structured data, thus application of deep learning technologies to the human disease subtypes is yet to be explored. To overcome the issue, we propose a hybrid model, which integrates two key components 1) graph convolution neural network (graph CNN) and 2) relation network (RN). Experimental results on synthetic data and breast cancer data demonstrate that our proposed method shows better performances than existing methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Diseases

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Augmented Reality for Presenting Local Wisdom: Sumatera Utara Traditional House

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Journal of Physics: Conference Series 2019年第1期1235卷

作者： M F Syahputra R Aulia O S Sitompul U Andayani D Abdullah S Sriadhi R F Nanuru M D Utama R T Manurung H Djanggih E Mouw Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Faculty of Law Universitas Tompotika Luwuk Banggai Indonesia Faculty of Social and Human Sciences Universitas Halmahera Indonesia

Augmented Reality is a technology that allows users to see the real world, with virtual objects placed on it or combined with the real world. Augmented Reality itself can be applied to various things, including as an educational media. In the field of education, technology can be used a culture introduction to society. One part of Indonesian culture is traditional houses. Traditional house is a building that symbolizes the culture of the local community. In North Sumatra itself, there are several traditional houses that have different forms. The use of Vuforia SDK in the construction of this application can display augmented objects in the form of 3-dimentional objects and also provide information on the house. This application will run on the Android mobile platform to make it easier for users to access it. In addition, users can choose their own objects to be used as markers to make the application use much easier.

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Heat distribution in the deep drawing device components working by high temperatures

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IOP Conference Series: Materials science and engineering 2018年第1期393卷

作者： M Tropp F Brumerčík J Šteininger P Weis A Glowacz Univerzity of Žilina Faculty of Mechanical Engineering Department of Design and Mechanical Elements Univerzitná 1 Žilina 010 26 Slovakia AGHUniversity of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics Al. A. Mickiewicza 30 30-059 Kraków Poland

The subject of the article is a simulation of heat affected components of a device for deep drawing by extreme conditions in vacuum by high temperatures required for forming of crystallization containers made from thin molybdenum sheets. The simulation is focused on the distribution of heat in particular components in relation with their shape. There are presented the design of working components and the boundary conditions of transient thermal simulations with the results.

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Doubly Penalized LASSO for Reconstruction of Biological Networks

Doubly Penalized LASSO for Reconstruction of Biological Netw...

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作者： Asadi, Behrang Maurya, Mano Ram Tartakovsky, Daniel M. Subramaniam, Shankar Departments of Bioengineering and Mechanical and Aerospace Engineering University of California San Diego Danaher Labs la Jolla Santa ClaraCA United States San Diego Supercomputer Center Department of Bioengineering University of California San Diego San DiegoCA United States Department of Mechanical Aerospace Engineering University of California San Diego San DiegoCA United States Department of Bioengineering Departments of Computer Science and Engineering Cellular and Molecular Medicine and the Graduate Program in Bioinformatics University of California San Diego San DiegoCA United States

Reconstruction of biological and biochemical networks is a crucial step in extracting knowledge and causal information from large biological data sets. This task is particularly challenging when dealing with time-series data from dynamic networks. We have developed a new method, called doubly penalized least absolute shrinkage and selection operator (DPLASSO), for the reconstruction of dynamic biological networks. Our method consists of two components: statistical significance testing of model coefficients and penalized/constrained optimization. A partial least squares (PLS) with statistical significance testing acts as a supervisory-level filter to extract the most informative components of the network from a data set. Then, LASSO with extra weights on the smaller parameters identified in the first layer is employed to retain the main predictors and to set the smallest coefficients to zero. We present two case studies to compare the relative performance of DPLASSO and LASSO in terms of several metrics, such as sensitivity, specificity, and accuracy. The first case study employs a synthetic data set;it demonstrates that DPLASSO substantially improves network reconstruction in terms of accuracy and specificity. The second case study relies on simulated data sets for cell division cycle of fission yeast and shows that DPLASSO overall outperforms LASSO and PLS in terms of sensitivity, specificity, and accuracy. Combining PLS with statistical significance testing and LASSO provides good performance with respect to several metrics. DPLASSO is well suited for reconstruction of networks with low and moderate density. For high-density networks, high specificity is desired, making PLS a more suitable approach. © 1963-2012 IEEE.

关键词： Least squares approximations

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The HRC model set for human-robot collaboration research

arXiv

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arXiv 2017年

作者： Zeylikman, Sofya Widder, Sarah Roncone, Alessandro Mangin, Olivier Scassellati, Brian Center for Engineering Innovation and Design Yale University New HavenCT06511 United States Social Robotics Lab Computer Science Department Yale University New HavenCT06511 United States

In this paper, we present a model set for designing human-robot collaboration (HRC) experiments. It targets a common scenario in HRC, which is the collaborative assembly of furniture, and it consists of a combination of standard components and custom designs. With this work, we aim at reducing the amount of work required to set up and reproduce HRC experiments, and we provide a unified framework to facilitate the comparison and integration of contributions to the field. The model set is designed to be modular, extendable, and easy to distribute. Importantly, it covers the majority of relevant research in HRC, and it allows tuning of a number of experimental variables that are particularly valuable to the field. Additionally, we provide a set of software libraries for perception, control and interaction, with the goal of encouraging other researchers to proactively contribute to our work. Copyright © 2017, The Authors. All rights reserved.

关键词： Robots

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Towards an adaptive multi-power-source datacenter 16

Towards an adaptive multi-power-source datacenter

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30th International Conference on Supercomputing, ICS 2016

作者： Liu, Longjun Sun, Hongbin Li, Chao Hu, Yang Zheng, Nanning Li, Tao Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering University of Florida United States

ISBN: (纸本)9781450343619

Big data and cloud computing are accelerating the capacity growth of datacenters all over the world. Their energy costs and environmental issues have pushed datacenter operators to explore and integrate alternative energy sources, such as various renewable energy supplies and energy storage devices. Designing datacenters powered by multi-power supplies in the smart grid environment is becoming a promising trend in the next few decades. However, gracefully provisioning various power sources and efficiently manage them in datacenter is a significant challenge. In this paper, we explore an unconventional fine-grained power distribution architecture for multi-source powered datacenters. We thoroughly investigate how to deliver and manage multiple power sources from the power generation plant outside of the datacenter to datacenter inside. We then propose a novel Power Switch Network (PSN) for datacenters. PSN is a reconfigurable multi-power-source distribution architecture which enables datacenter to distribute various power sources with a fine-grained manner. Moreover, a tailored machine learning based power sources management framework is proposed for PSN to dynamically select different power sources and optimize user-demanded performance metrics. Compared with the conventional singleswitch system, evaluation results show that PSN could improve solar energy utilization by 39.6%, reduce utility power cost by 11.1% and improve workload performance by 33.8%, meanwhile enhancing battery lifetime by 9.3%. We expect that our work could provide valuable guidelines for the emerging multi-power-source datacenter to improve their efficiency, sustainability and economy. © 2016 ACM.

关键词： Smart power grids

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Anisotropic spin-orbit torque generation in epitaxial SrIrO3 by symmetry design

arXiv

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arXiv 2018年

作者： Nan, T. Anderson, T.J. Gibbons, J. Hwang, K. Campbell, N. Zhou, H. Dong, Y.Q. Kim, G.Y. Reynolds, N. Wang, X.J. Sun, N.X. Choi, S.Y. Rzchowski, M.S. Kim, Yong Baek Ralph, D.C. Eom, C.B. Department of Materials Science and Engineering University of Wisconsin-Madison MadisonWI53706 United States Laboratory of Atomic and Solid State Physics Cornell University IthacaNY14853 United States Department of Physics and Centre for Quantum Materials University of Toronto TorontoONM5S 1A7 Canada Department of Physics University of Wisconsin-Madison MadisonWI53706 United States Advanced Photon Source Argonne National Laboratory ArgonneIL60439 United States Department of Materials Science and Engineering POSTECH Pohang37673 Korea Republic of Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Canadian Institute for Advanced Research/Quantum Materials Program TorontoONM5G 1Z8 Canada School of Physics Korea Institute for Advanced Study Seoul130-722 Korea Republic of Kavli Institute at Cornell for Nanoscale Science IthacaNY14853 United States

Spin-orbit coupling (SOC), the interaction between the electron spin and the orbital angular momentum, can unlock rich phenomena at interfaces, in particular interconverting spin and charge currents. Conventional heavy metals have been extensively explored due to their strong SOC of conduction electrons. However, spin-orbit effects in classes of materials such as epitaxial 5d-electron transition metal complex oxides, which also host strong SOC, remain largely unreported. In addition to strong SOC, these complex oxides can also provide the additional tuning knob of epitaxy to control the electronic structure and the engineering of spin-to-charge conversion by crystalline symmetry. Here, we demonstrate room-temperature generation of spin-orbit torque on a ferromagnet with extremely high efficiency via the spin-Hall effect in epitaxial metastable perovskite SrIrO3. We first predict a large intrinsic spin-Hall conductivity in orthorhombic bulk SrIrO3 arising from the Berry curvature in the electronic band structure. By manipulating the intricate interplay between SOC and crystalline symmetry, we control the spin-Hall torque ratio by engineering the tilt of the corner-sharing oxygen octahedra in perovskite SrIrO3 through epitaxial strain. This allows the presence of an anisotropic spin-Hall effect due to a characteristic structural anisotropy in SrIrO3 with orthorhombic symmetry. Our experimental findings demonstrate the heteroepitaxial symmetry design approach to engineer spin-orbit effects. We therefore anticipate that these epitaxial 5d transition-metal oxide thin films can be an ideal building block for low-power spintronics. Copyright © 2018, The Authors. All rights reserved.

关键词： Magnetic moments

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