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Materials Today: Proceedings 2021年 41卷 530-534页

作者： P. Nikhil Chandra K. Usha Mothi Krishna Mohan Post Graduate and Research Department of Chemistry Sree Narayana College Kollam 691001 India School of Environmental Studies Cochin University of Science and Technology Kochi Kerala 682022 India Kerala Department of Sciences and Humanities Christ University Faculty of Engineering Bangalore Karnataka 560074 India

The present work projects to modify the surface of commercially available microfiltration membranes using polyelectrolyte multilayer assembly. This polyelectrolytic modification changes the nature and properties of the membrane such as porosity, absorption capacity, charge etc. which can be used for potential environmental application such as herbicide removal from water. Chitosan (CHI) and polystyrene sulfonate (PSS) were incorporated into nanostructured polymeric films on polyamide membrane using layer-by-layer (LbL) technique. The developed polyelectrolyte multilayer assembly were characterized by using UV–vis spectroscopy, attenuated total reflectance fourier transform infrared (ATR-FTIR) spectroscopy, thermo gravimetric analysis (TGA) and atomic force microscopy (AFM).

关键词： LbL method Polymeric membranes Water purification Polystyrene sulphonate Polyelectrolyte Chitosan

Correction: A full privacy-preserving distributed batch-based certificate-less aggregate signature authentication scheme for healthcare wearable wireless medical sensor networks (HWMSNs)

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International Journal of Information Security 2024年第3期23卷 2489-2489页

作者： Rabie, Osama Bassam J. Selvarajan, Shitharth Hasanin, Tawfiq Mohammed, Gouse Baig Alshareef, Abddulrhman M. Uddin, Mueen Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Cybersecurity Center King Abdulaziz University Jeddah Saudi Arabia Department of Computer Science Kebri Dehar University Kebri Dehar Ethiopia School of Built Environment Engineering and Computing Leeds Beckett University Leeds UK Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad India College of Computing and Information Technology University of Doha for Science and Technology Doha Qatar

Blackhole-Inspired Thermal Trapping with Graded Heat-Conduction Metadevices

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arXiv 2022年

作者： Xu, Liujun Liu, Jinrong Jin, Peng Xu, Guoqiang Li, Jiaxin Ouyang, Xiaoping Li, Ying Qiu, Cheng-Wei Huang, Jiping Fudan University Shanghai200438 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Graduate School of China Academy of Engineering Physics Beijing100193 China School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China School of Materials Science and Engineering Xiangtan University Xiangtan411105 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University Haining314400 China

Black holes are one of the most intriguing predictions of general relativity. So far, metadevices have enabled analogous black holes to trap light or sound in laboratory spacetime. However, trapping heat in a conductive ambient is still challenging because diffusive behaviors are directionless. Inspired by black holes, we construct graded heat-conduction metadevices to achieve thermal trapping, resorting to the imitated advection produced by graded thermal conductivities rather than the trivial solution of using insulation materials to confine thermal diffusion. We experimentally demonstrate thermal trapping for guiding hot spots to diffuse towards the center. Graded heat-conduction metadevices have advantages in energy-efficient thermal regulation because the imitated advection has a similar temperature field effect to the realistic advection that is usually driven by external energy sources. These results also provide insights into correlating transformation thermotics with other disciplines such as cosmology for emerging heat control schemes. Copyright © 2022, The Authors. All rights reserved.

关键词： Advection

Day-ahead scheduling of CNG station and hybrid CNG and plug-in electric vehicles in the form of virtual power plant

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AIP Conference Proceedings 2023年第1期2795卷

作者： Mohammad Seyfi Mehdi Mehdinejad Behnam Mohammad-Ivatloo Heidarali Shayanfar Zulkurnain Abdul-Malek Center of Excellence for Power Systems Automation and Operation School of Electrical Engineering Iran University of Science and Technology Tehran Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran High Voltage & High Current Institute School of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia

Integrating plug-in hybrid electric vehicles (PHEV) with power systems and supplying their required energy is a challenging issue. Decentralized operation of the power systems can decrease the impacts of PHEVs on power systems. One of the high potential options for developing decentralized networks is the virtual power plant (VPP). In this paper, day-ahead scheduling of VPP consisting of PHEVs, which use compressed natural gas (CNG) as their alternative option for electrical energy, and CNG station is presented. VPP can supply the CNG needed by HPEVs by compressing the natural gas (NG) in the CNG station. Therefore, two sources of energy for HPEVs is provided by participating in the scheduling of the VPP. This structure can improve the flexibility and ability of HPEVs to participate in the scheduling. Also, because of using the CNG instead of gasoline, the developed model reduce the pollutant emissions of the transportation system.

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Multi-label classification via adaptive resonance theory-based clustering

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arXiv 2021年

作者： Masuyama, Naoki Nojima, Yusuke Loo, Chu Kiong Ishibuchi, Hisao Graduate School of Engineering Osaka Prefecture University 1-1 Gakuen-cho Naka-ku Sakai-Shi Osaka599-8531 Japan Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

—This paper proposes a multi-label classification algorithm capable of continual learning by applying an Adaptive Resonance Theory (ART)-based clustering algorithm and the Bayesian approach for label probability computation. The ART-based clustering algorithm adaptively and continually generates prototype nodes corresponding to given data, and the generated nodes are used as classifiers. The label probability computation independently counts the number of label appearances for each class and calculates the Bayesian probabilities. Thus, the label probability computation can cope with an increase in the number of labels. Experimental results with synthetic and real-world multi-label datasets show that the proposed algorithm has competitive classification performance to other well-known algorithms while realizing continual learning. © 2021, CC BY-NC-ND.

关键词： Classification (of information)

Dic deformation measurement in cracked cfrp cross-ply laminates 22

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Dic deformation measurement in cracked cfrp cross-ply lamina...

22nd International Conference on Composite Materials, ICCM 2019

作者： Mohammad Fikry, M.J. Ogihara, Shinji Vinogradov, Vladimir Dep. of Mechanical Engineering Graduate School of Science and Technology Tokyo University of Science Chiba Japan Dep. of Mechanical Engineering Faculty of Science and Technology Tokyo University of Science Chiba Japan School of Engineering Newcastle University Newcastle upon Tyne United Kingdom

Digital Image Correlation (DIC) is a non-contact method to analyse the deformation of materials that can measure displacement or strain behaviour during tensile loading. In this study, DIC is used to measure the deformation of cross-ply carbon fibre reinforced plastics (CFRP) laminates and for the detection of damages in them. The objective of this study is to measure the deformation around the damages in cross-ply CFRP laminates by using the DIC system from both width and thickness directions. For this purpose, thick CFRP [04/9024]s and thinner [0/906]s laminates were tested. In cross-ply laminates, usually a straight transverse crack will initially occur in 90 degree ply followed by the following damages such as delamination, fiber fracture, and etc. To start, straight transverse cracks are induced in the laminates by using an artificial crack method. Then, X-ray radiography is used to detect the location of the straight cracks in order to be used for DIC observation to examine the strain distribution around the existed cracks. The DIC observation from the surface of the laminate around the cracks area clearly showed how strain is distributed from one crack to another adjacent crack. From the result, secondary mode damages of matrix cracking such as oblique and curved cracks can also be observed and are being discussed in this paper. © 2019 International Committee on Composite Materials. All rights reserved.

关键词： Image correlation

Direct Measurement of the Cosmic-Ray Helium Spectrum from 40 GeV to 250 TeV with the Calorimetric Electron Telescope on the International Space Station

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Physical Review Letters 2023年第17期130卷 171002-171002页

作者： O. Adriani Y. Akaike K. Asano Y. Asaoka E. Berti G. Bigongiari W. R. Binns M. Bongi P. Brogi A. Bruno J. H. Buckley N. Cannady G. Castellini C. Checchia M. L. Cherry G. Collazuol G. A. de Nolfo K. Ebisawa A. W. Ficklin H. Fuke S. Gonzi T. G. Guzik T. Hams K. Hibino M. Ichimura K. Ioka W. Ishizaki M. H. Israel K. Kasahara J. Kataoka R. Kataoka Y. Katayose C. Kato N. Kawanaka Y. Kawakubo K. Kobayashi K. Kohri H. S. Krawczynski J. F. Krizmanic P. Maestro P. S. Marrocchesi A. M. Messineo J. W. Mitchell S. Miyake A. A. Moiseev M. Mori N. Mori H. M. Motz K. Munakata S. Nakahira J. Nishimura S. Okuno J. F. Ormes S. Ozawa L. Pacini P. Papini B. F. Rauch S. B. Ricciarini K. Sakai T. Sakamoto M. Sasaki Y. Shimizu A. Shiomi P. Spillantini F. Stolzi S. Sugita A. Sulaj M. Takita T. Tamura T. Terasawa S. Torii Y. Tsunesada Y. Uchihori E. Vannuccini J. P. Wefel K. Yamaoka S. Yanagita A. Yoshida K. Yoshida W. V. Zober Department of Physics University of Florence Via Sansone 1–50019 Sesto Fiorentino Italy INFN Sezione di Firenze Via Sansone 1–50019 Sesto Fiorentino Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo 162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Tsukuba Ibaraki 305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba 277-8582 Japan Institute of Applied Physics (IFAC) National Research Council (CNR) Via Madonna del Piano 10 50019 Sesto Fiorentino Italy Department of Physical Sciences Earth and Environment University of Siena via Roma 56 53100 Siena Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3–56127 Pisa Italy Department of Physics and McDonnell Center for the Space Sciences Washington University One Brookings Drive St. Louis Missouri 63130-4899 USA Heliospheric Physics Laboratory NASA/GSFC Greenbelt Maryland 20771 USA Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle Baltimore Maryland 21250 USA Astroparticle Physics Laboratory NASA/GSFC Greenbelt Maryland 20771 USA Center for Research and Exploration in Space Sciences and Technology NASA/GSFC Greenbelt Maryland 20771 USA Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton Rouge Louisiana 70803 USA Department of Physics and Astronomy University of Padova Via Marzolo 8 35131 Padova Italy INFN Sezione di Padova Via Marzolo 8 35131 Padova Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Sagamihara Kanagawa 252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama Kanagawa 221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University 3 Bunkyo Hirosaki Aomori 036-8561 J

We present the results of a direct measurement of the cosmic-ray helium spectrum with the CALET instrument in operation on the International Space Station since 2015. The observation period covered by this analysis spans from October 13, 2015, to April 30, 2022 (2392 days). The very wide dynamic range of CALET allowed for the collection of helium data over a large energy interval, from ∼40 GeV to ∼250 TeV, for the first time with a single instrument in low Earth orbit. The measured spectrum shows evidence of a deviation of the flux from a single power law by more than 8σ with a progressive spectral hardening from a few hundred GeV to a few tens of TeV. This result is consistent with the data reported by space instruments including PAMELA, AMS-02, and DAMPE and balloon instruments including CREAM. At higher energy we report the onset of a softening of the helium spectrum around 30 TeV (total kinetic energy). Though affected by large uncertainties in the highest energy bins, the observation of a flux reduction turns out to be consistent with the most recent results of DAMPE. A double broken power law is found to fit simultaneously both spectral features: the hardening (at lower energy) and the softening (at higher energy). A measurement of the proton to helium flux ratio in the energy range from 60 GeV/n to about 60 TeV/n is also presented, using the CALET proton flux recently updated with higher statistics.

关键词： Cosmic ray & astroparticle detectors Cosmic ray acceleration Cosmic ray composition & spectra Cosmic ray propagation Cosmic ray sources Cosmic rays & astroparticles

Controlling chaotic itinerancy in laser dynamics for reinforcement learning

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arXiv 2022年

作者： Iwami, Ryugo Mihana, Takatomo Kanno, Kazutaka Sunada, Satoshi Naruse, Makoto Uchida, Atsushi Department of Information and Computer Sciences Saitama University 255 Shimo-okubo Sakura-ku Saitama Saitama338-8570 Japan Faculty of Mechanical Engineering Institute of Science and Engineering Kanazawa University Kakuma-machi Ishikawa Kanazawa920-1192 Japan PRESTO 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

Photonic artificial intelligence has attracted considerable interest in accelerating machine learning;however, the unique optical properties have not been fully utilized for achieving higher-order functionalities. Chaotic itinerancy, with its spontaneous transient dynamics among multiple quasi-attractors, can be employed to realize brain-like functionalities. In this paper, we propose a method for controlling the chaotic itinerancy in a multi-mode semiconductor laser to solve a machine learning task, known as the multi-armed bandit problem, which is fundamental to reinforcement learning. The proposed method utilizes ultrafast chaotic itinerant motion in mode competition dynamics controlled via optical injection. We found that the exploration mechanism is completely different from a conventional searching algorithm and is highly scalable, outperforming the conventional approaches for large-scale bandit problems. This study paves the way to utilize chaotic itinerancy for effectively solving complex machine learning tasks as photonic hardware accelerators. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamics

Coronagraph Experiment on Dark-hole Control by Speckle Area Nulling Method

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arXiv 2022年

作者： Oya, Masahito Nishikawa, Jun Horie, Masaaki Sato, Kazuma Murakami, Naoshi Kotani, Takayuki Kumagai, Shiomi Tamura, Motohide Tanaka, Yosuke Kurokawa, Takashi Graduate School of Science and Technology Nihon University Kandasurugadai 1-8-14 Chiyoda Tokyo101-8308 Japan Division of Optical and Infrared Astronomy National Astronomical Observatory of Japan Osawa 2-21-1 Mitaka Tokyo181-8588 Japan Extra-Solar Planet Office National Astronomical Observatory of Japan Osawa 2-21-1 Mitaka Tokyo181-8588 Japan School of Physical Sciences The Graduate University for Advanced Studies Osawa 2-21-1 Mitaka Tokyo181-8588 Japan Graduate School of Engineering Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei Tokyo184-8588 Japan Facility of Engineering Hokkaido University Kita-13 Nishi-8 Kita-ku Hokkaido Sapporo060-8588 Japan Facility of Science and Technology Nihon University Kandasurugadai 1-8-14 Chiyoda Tokyo101-8308 Japan Faculty of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Faculty of Engineering Tokyo University of Agricalture and Technology Koganei Tokyo184-8588 Japan

In high-contrast imaging optical systems for direct observation of planets outside our solar system, adaptive optics with an accuracy of λ/10,000 root mean square is required to reduce the speckle noise down to 1 × 10−10 level in addition to the nulling coronagraph which eliminate the diffracted light. We developed the speckle area nulling (SAN) method as a new dark-hole control algorithm which is capable of controlling speckle electric field in a wide area quickly, in spite of an extension of speckle nulling, and is robust not relying upon an optical model. We conducted a validation experiment for the SAN method with a monochromatic light and succeeded in reducing the intensity of areal speckles by 4.4× 10−2 © 2022, CC BY.

关键词： Speckle

Reservoir computing with diverse timescales for prediction of multiscale dynamics

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arXiv 2021年

作者： Tanaka, Gouhei Matsumori, Tadayoshi Yoshida, Hiroaki Aihara, Kazuyuki International Research Center for Neurointelligence The University of Tokyo Tokyo113-0033 Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering The University of Tokyo Tokyo113-8656 Japan Department of Mathematical Informatics Graduate School of Information Science and Technology The University of Tokyo Tokyo113-8656 Japan Toyota Central Research and Development Laboratory Inc Tokyo112-0004 Japan

Machine learning approaches have recently been leveraged as a substitute or an aid for physical/mathematical modeling approaches to dynamical systems. To develop an efficient machine learning method dedicated to modeling and prediction of multiscale dynamics, we propose a reservoir computing (RC) model with diverse timescales by using a recurrent network of heterogeneous leaky integrator (LI) neurons. We evaluate computational performance of the proposed model in two time series prediction tasks related to four chaotic fast-slow dynamical systems. In a one-step-ahead prediction task where input data are provided only from the fast subsystem, we show that the proposed model yields better performance than the standard RC model with identical LI neurons. Our analysis reveals that the timescale required for producing each component of target multiscale dynamics is appropriately and flexibly selected from the reservoir dynamics by model training. In a long-term prediction task, we demonstrate that a closed-loop version of the proposed model can achieve longer-term predictions compared to the counterpart with identical LI neurons depending on the hyperparameter *** Codes 37M10, 68T07 © 2021, CC BY.

关键词： Neurons