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Multilayers with robust post-annealing performance for spintronics device applications

Journal of Physics D: Applied Physics 2018年第46期51卷

作者： Gupta, S. Sbiaa, R. Al Bahri, M. Ghosh, A. Piramanayagam, S.N. Ranjbar, M. Akerman, J. Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Department of Physics Sultan Qaboos University PC 123 PO Box 36 Muscat Oman 2 Fusionopolis Way 08-01 Innovis 138634 Singapore Physics Department University of Gothenburg Gothenburg412 96 Sweden School of Computer Science and System Engineering Kyushu Institute of Technology Iizuka820-8502 Japan

The effect of annealing on the diffusion induced changes in the magnetic and magnetodynamic properties of (Co/Ni) multilayers were investigated. Here, we report, all aspects of post annealing induced effect on perpendicular magnetic anisotropy (PMA), domain morphology, switching mechanism and high frequency magnetization dynamics to understand spin relaxation. (Co/Ni) multilayers of this study exhibited a loop squareness of 95%, a slight drop in saturation magnetization from 650 emu/cc to 620 emu/cc and high magnetic anisotropy (K u ∼ 3 × 105 J m-3) even after annealing at temperatures as high as 400 °C. Successive domain mapping by magnetic force microscopy revealed characteristics of multi-domains stripe that feature at all stages of annealing except at 500 °C, attributed to the loss of PMA, driven by interfacial diffusion. High frequency broadband ferromagnetic resonance measurements showed little effect of annealing on intrinsic damping parameter (α = 0.019-0.024) while inhomogeneous linewidth broadening varied without a clear trend. These results are discussed considering crystallographic modifications and it was found that fcc (1 1 1) texture was retained in the samples until 400 °C post annealing. The retention of a high anisotropy, high magnetization and low damping constant after high temperature annealing makes these Co/Ni multilayers suitable for designing spin torque based memory devices. © 2018 IOP Publishing Ltd.

关键词： Ferromagnetism

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Structural optimization of autonomous energy networks by mathematical programming techniques

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2017年第8期137卷 1009-1014页

作者： Sakakibara, Kazutoshi Matsumoto, Takuya Taniguchi, Ittetsu Tamaki, Hisashi Department of Information Systems Engineering Toyama Prefectural University 5180 Kurokawa Imizu Toyama939-0398 Japan Information Science and Technology Center Kobe University 1-1 Rokkodai-cho Nada-ku Kobe Hyogo657-8501 Japan Department of Electronic and Computer Engineering Ritsumeikan University 1-1-1 Noji Higashi Kusatsu Shiga525-8577 Japan Graduate School of System Informatics Kobe University 1-1 Rokkodai Nada-ku Kobe Hyogo657-8501 Japan

The renewal of conventional energy systems is important countermeasures against global warming effects and natural hazards. A self-sustainable decentralized energy system is one of the promising solutions for future sustainable and resilient societies. In this paper, a mathematical programming model is formulated and design and utilization of the overall energy network is optimized based on the model, where stationary batteries are equipped. Through some numerical simulation results, the effectiveness and the potential, e.g. for clarifying the effect of the batteries, of the proposed model are investigated. © 2017 The Institute of Electrical Engineers of Japan.

关键词： Electric power transmission networks

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Boundary Value Analysis Testing on Augmented Reality of Indonesian Fruit Recognition at Mekarsari Tourist Park using Cloud Method on Android Mobile Devices

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Journal of Physics: Conference Series 2019年第1期1196卷

作者： R Dewi Agushinta Hustinawaty Ihsan Jatnika Henny Medyawati Information System Faculty of Computer Science and Information Technology Gunadarma University Jl. Margonda Raya No. 100 Pondok Cina Depok 16424 West Java Informatics Engineering Faculty of Industrial Technology Gunadarma University Jl. Margonda Raya No. 100 Pondok Cina Depok 16424 West Java

Software testing is a process of implementing a program with the aim of finding an error. A good test case is if the test has the possibility of finding an uncovered error. A successful test is if the test finds an error that was not initially found. One of the testing types available is black box testing. This paper proposes testing using black box testing technique. The black box testing method consists of several ways including equivalence partitioning, boundary value analysis, comparison testing, sample testing, robustness testing, and others. Among the many methods of testing, Boundary Value Analysis was chosen in this study. Boundary Value Analysis is a method of testing by determining the value of the lower limit and upper limit of the data that will be tested. This test is performed on the functions of Augmented Reality prototype of Indonesia fruit recognition by using the cloud method on Android mobile devices. From testing the distance of marker objects to Android mobile devices on cloud recognition using an Android camera shows that the higher the augmentable rating of the target image and the more the number of markers features detected, the easier the image will be tracked by AR. If the distance between the camera and the real object gets farther away, then the virtual object cannot be displayed. Testing with mobile devices using HSDPA, 3G and WIFI networks connecting a cloud database server to display virtual objects shows the average results of devices that use WIFI networks provide the fastest performance.

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RETRACTED: Estimation of the effect of catalyst physical characteristics on Fenton-like oxidation efficiency using adaptive neuro-fuzzy computing technique

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Measurement 2018年 125卷 704-704页

作者： Shima Rahim Pouran A.R. Abdul Aziz Wan Mohd Ashri Wan Daud Shahaboddin Shamshirband Chemical Engineering Department Faculty of Engineering University of Malaya 50603 Kuala Lumpur Malaysia Computer System and Technology Department Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

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Generating labeled samples for hyperspectral image classification using correlation of spectral bands

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Frontiers of computer science 2016年第2期10卷 292-301页

作者： Lu YU Jun XIE Songcan CHEN Lei ZHU Institute of Communications Engineering PLA University of Science and Technology Nanjing 210007 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 China College of Command Information System PLA University of Science and Technology Nanjing 210007 China

Because the labor needed to manually label a huge training sample set is usually not available, the problem of hyperspectral image classification often suffers from a lack of labeled training samples. At the same time, hyperspectral data represented in a large number of bands are usually highly correlated. In this paper, to overcome the small sample problem in hyperspectral image classification, correlation of spectral bands is fully utilized to generate multiple new sub-samples from each original sample. The number of labeled training samples is thus increased several times. Experiment results demonstrate that the proposed method has an obvious advantage when the number of labeled samples is small.

关键词： hyperspectral image remote sensing image classification small sample problem

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NuDE 2.0: A formal method-based software development, verification and safety analysis environment for digital I&Cs in NPPs

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Journal of Computing science and engineering 2017年第1期11卷 9-23页

作者： Kim, Eui-Sub Lee, Dong-Ah Jung, Sejin Yoo, Junbeom Choi, Jong-Gyun Lee, Jang-Soo Division of Computer Science and Engineering Konkuk University Seoul Korea Republic of Man-Machine Interface System Team Korea Atomic Energy Research Institute Daejeon Korea Republic of

NuDE 2.0 (Nuclear Development Environment 2.0) is a formal-method-based software development, verification and safety analysis environment for safety-critical digital I&Cs implemented with programmable logic controller (PLC) and field-programmable gate array (FPGA). It simultaneously develops PLC/FPGA software implementations from one requirement/design specification and also helps most of the development, verification, and safety analysis to be performed mechanically and in sequence. The NuDE 2.0 now consists of 25 CASE tools and also includes an in-depth solution for indirect commercial off-the-shelf (COTS) software dedication of new FPGA-based digital I&Cs. We expect that the NuDE 2.0 will be widely used as a means of diversifying software design/implementation and model-based software development methodology. © 2017. The Korean Institute of Information Scientists and Engineers. All right reserved.

关键词： Field programmable gate arrays (FPGA)

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Analysis of large fault trees based on simplified BDD algorithm

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International Journal of Performability engineering 2017年第6期13卷 796-806页

作者： Liu, Wei Zhou, Yong Xie, Hongmei Wei, Zhengxian College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China System Engineering Research Institute China State Shipbuilding Corporation Beijing100036 China

A simplified BDD analysis method (SimBDD) is proposed to solve the problem of temporal and spatial explosion and low computational efficiency of getting the fault tree's minimum cut sets in BDD method. On the basis of using SimBDD to get the minimum cutting sets, the failure paths of the fault tree are obtained by the hierarchical processing method. Tests are taken on large fault trees with this method. The results demonstrate that the method is efficient. © 2017 Totem Publisher, Inc. All rights reserved.

关键词： Computational efficiency

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Coarse-to-Fine Learning for Single-Image Super-Resolution

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IEEE Transactions on Neural Networks and Learning systems 2017年第5期28卷 1109-1122页

作者： Zhang, Kaibing Tao, Dacheng Gao, Xinbo Li, Xuelong Li, Jie School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an Shaanxi710119 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China

This paper develops a coarse-to-fine framework for single-image super-resolution (SR) reconstruction. The coarse-to-fine approach achieves high-quality SR recovery based on the complementary properties of both example learning-and reconstruction-based algorithms: example learning-based SR approaches are useful for generating plausible details from external exemplars but poor at suppressing aliasing artifacts, while reconstruction-based SR methods are propitious for preserving sharp edges yet fail to generate fine details. In the coarse stage of the method, we use a set of simple yet effective mapping functions, learned via correlative neighbor regression of grouped low-resolution (LR) to high-resolution (HR) dictionary atoms, to synthesize an initial SR estimate with particularly low computational cost. In the fine stage, we devise an effective regularization term that seamlessly integrates the properties of local structural regularity, nonlocal self-similarity, and collaborative representation over relevant atoms in a learned HR dictionary, to further improve the visual quality of the initial SR estimation obtained in the coarse stage. The experimental results indicate that our method outperforms other state-of-the-art methods for producing high-quality images despite that both the initial SR estimation and the followed enhancement are cheap to implement. © 2012 IEEE.

关键词： Optical resolving power

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Prediction and understanding of soft proton contamination in XMM-Newton: A machine learning approach

arXiv

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arXiv 2020年

作者： Kronberg, Elena A. Gastaldello, Fabio Haaland, Stein Smirnov, Artem Berrendorf, Max Ghizzardi, Simona Kuntz, K.D. Sivadas, Nithin Allen, Robert C. Tiengo, Andrea Ilie, Raluca Huang, Yu Kistler, Lynn University of Munich Theresienstr. 41 Munich80333 Germany Milano via A. Corti 12 MilanoI-20133 Italy Birkeland Centre for Space Science University of Bergen Allégaten 55 Bergen5007 Norway Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen Germany German Research Centre for Geosciences Albert-Einstein-Strae 42-46 Potsdam14473 Germany Geophysical Center of the Russian Academy of Sciences Molodezhnaya St. 3 Moscow119296 Russia Institute of Informatics University of Munich Oettingenstrae 67 Munich80538 Germany Henry A. Rowland Department of Physics & Astronomy Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States Department of Electrical and Computer Engineering Boston University 8 Saint Mary’s Street BostonMA02134 United States Johns Hopkins University Applied Physics Lab 11100 Johns Hopkins Rd LaurelMD20723 United States Scuola Universitaria Superiore IUSS Pavia piazza della Vittoria 15 PaviaI-27100 Italy INFN Sezione di Pavia via A. Bassi 6 PaviaI-27100 Italy University of Illinois at Urbana-Champaign ECEB 306 N. Wright Street 5054 UrbanaIL61801 United States Space Science Center University of New Hampshire Morse Hall Rm 408 DurhamNH03824 United States

One of the major and unfortunately unforeseen sources of background for the current generation of X-ray telescopes are few tens to hundreds of keV (soft) protons concentrated by the mirrors. One such telescope is the European Space Agency’s (ESA) X-ray Multi-Mirror Mission (XMM-Newton). Its observing time lost due to background contamination is about 40%. This loss of observing time affects all the major broad science goals of this observatory, ranging from cosmology to astrophysics of neutron stars and black holes. The soft proton background could dramatically impact future large X-ray missions such as the ESA planned Athena missiona). Physical processes that trigger this background are still poorly understood. We use a Machine Learning (ML) approach to delineate related important parameters and to develop a model to predict the background contamination using 12 years of XMM observations. As predictors we use the location of satellite, solar and geomagnetic activity parameters. We revealed that the contamination is most strongly related to the distance in southern direction, Z, (XMM observations were in the southern hemisphere), the solar wind radial velocity and the location on the magnetospheric magnetic field lines. We derived simple empirical models for the first two individual predictors and an ML model which utilizes an ensemble of the predictors (Extra Trees Regressor) and gives better performance. Based on our analysis, future missions should minimize observations during times associated with high solar wind speed and avoid closed magnetic field lines, especially at the dusk flank region in the southern hemisphere. Copyright © 2020, The Authors. All rights reserved.

关键词： Gamma rays

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A Time-aware POI Recommendation Method Exploiting User-based Collaborative Filtering and Location Popularity

A Time-aware POI Recommendation Method Exploiting User-based...

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2017 2nd International Conference on Communications, Information Management and Network Security (CIMNS2017)

作者： Ya-li SI Fu-zhi ZHANG Wen-yuan LIU School of Information Science and Engineering Yanshan University School of Liren Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province

Point-of-interest(POI) recommendation becomes an important research for location-based social networks, since it helps modern citizens to explore new locations in unvisited cites effectively according to their preferences. However, the current POI recommendation methods are lack of a deep mining in all time slots features and their effects on recommendation. To this end, in this paper we propose a POI recommendation method(called UPT) by combining time slot features, user-based collaborative filtering and spatial influence. Firstly, we extract time interval feature and time slot based popularity feature from history check-in datasets on LBSNs using probability statistical analysis method. Then, we devise a POI recommendation method based on the proposed temporal features to achieve better performance. In UPT, user-based collaborative filtering and smoothing technique are used by adding each time slot influence, and the overall popularity of a location is combined with each time slot feature. Our experimental results on Foursquare and Gowalla datasets show that UPT outperforms baseline POI recommendation methods in precision and recall.

关键词： Location-based social networks Point-of-interest recommendation User-based collaborative filtering Location popularity Temporal feature

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