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arXiv 2024年

作者： Liu, Qibang Cai, Pengfei Abueidda, Diab Koric, Seid Gomez-Bombarelli, Rafael Geubelle, Philippe National Center for Supercomputing Applications University of Illinois at Urbana–Champaign UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana–Champaign UrbanaIL61801 United States Department of Aerospace Engineering University of Illinois at Urbana–Champaign UrbanaIL61801 United States Department of Mechanical Science and Engineering University of Illinois at Urbana–Champaign UrbanaIL61801 United States Civil and Urban Engineering Department New York University Abu Dhabi United Arab Emirates Department of Industrial and Manufacturing Systems Engineering Kansas State University ManhattanKS66506 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

Rapid reaction-thermal diffusion during frontal polymerization (FP) with variations in initial and boundary conditions destabilizes the planar mode of front propagation, leading to spatially varying complex hierarchical patterns in polymeric materials. Although modern reaction-diffusion models can predict the patterns resulting from unstable FP, the inverse design of patterns, which aims to retrieve process conditions that produce a desired pattern, remains an open challenge due to the nonunique and nonintuitive mapping between process conditions and patterns. In this work, we propose a novel probabilistic generative model named univariate conditional variational autoencoder (UcVAE) for the inverse design of hierarchical patterns in FP-based manufacturing. Unlike the cVAE, which encodes both the design space and the design target, the UcVAE encodes only the design space. In the encoder of the UcVAE, the number of training parameters is significantly reduced compared to the cVAE, resulting in a shorter training time while maintaining comparable performance. Given desired pattern images, the trained UcVAE can generate multiple process condition solutions that produce high-fidelity hierarchical patterns. © 2024, CC BY.

关键词： Inverse problems

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Millisecond-Order Temporal-Resolution Synchrotron X-ray Tomography without Sample Rotation 14

Millisecond-Order Temporal-Resolution Synchrotron X-ray Tomo...

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14th International Conference on Synchrotron Radiation Instrumentation, SRI 2021

作者： Yashiro, Wataru Liang, Xiaoyu Voegeli, Wolfgang Arakawa, Etsuo Shirasawa, Tetsuroh Kajiwara, Kentaro Fujii, Katsuya Hashimoto, Koh Kudo, Hiroyuki Tohoku University 2-1-1 Katahira Aoba-ku Miyagi Sendai980-8577 Japan Tohoku University 2-1-1 Katahira Aoba-ku Miyagi Sendai980-8577 Japan Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Physics Tokyo Gakugei University 4-1-1 Nukuikita-Machi Tokyo184-8501 Japan National Metrology Institute of Japan National Institute of Advanced Industrial Science and Technology 5-2-2107 1-1-1 Higashi Ibaraki Tsukuba305-8565 Japan Sayo Hyogo679-5198 Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba305-8573 Japan

A multi-beam optics consisting of curved crystals with blades for a white synchrotron X-ray beam from a bending magnet was developed, and millisecond-order temporal-resolution X-ray tomography with a voxel size of 20 μm was successfully realized without sample rotation. The multi-beam optics opens the spatio-temporal frontier of X-ray tomography for unrepeatable and nonequilibrium systems and is expected to be applied to various fields in materials and life sciences. © Published under licence by IOP Publishing Ltd.

关键词： Imaging systems

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Nanoscale Cutting Using Self-Excited Microcantilever

Research Square

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Research Square 2021年

作者： Yang, Rui Ogura, Ichiro Jiang, ZhenYan An, LinJun Ashida, Kiwamu Yabuno, Hiroshi Graduate School of Systems and Information Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Advanced Manufacturing Research Institute National Institute of Advanced Industrial Science and Technology 1-2-1 Namiki Tsukuba305-0044 Japan

The application of self-excitation is proposed to improve the efficiency of the nanoscale cutting procedure based on use of a microcantilever in atomic force microscopy. The microcantilever shape is redesigned so that it can be used to produce vibration amplitudes with sufficient magnitudes to enable the excitation force applied by an actuator to be transferred efficiently to the tip of the microcantilever for the cutting process. A diamond abrasive that is set on the tip is also fabricated using a focused ion beam technique to improve the cutting effect. The natural frequency of the microcantilever is modulated based on the pressing load. Under conventional external excitation conditions, to maintain the microcantilever in its resonant state, it is necessary to vary the excitation frequency in accordance with the modulation. In this study, rather than using external excitation, the self-excitation cutting method is proposed to overcome this difficulty. The self-excited oscillation is produced by appropriate setting of the phase difference between the deflection signal of the microcantilever and the feedback signal for the actuator. In addition, it is demonstrated experimentally that the change in the phase difference enables us to control the amplitude of the self-excitation. As a result, control of the groove cutting depth is achieved via changes in the phase difference. © 2021, CC BY.

关键词： Actuators

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Influence of Prior General Knowledge on Older Adults’ Takeover Performance and Attitude Toward Using Conditionally Automated Driving systems

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2021年第1期65卷 1327 - 1331页

作者： Huiping Zhou Makoto Itoh Satoshi Kitazaki Faculty of Engineering Information and Systems University of Tsukuba Tsukuba-city Japan {zhou.huiping.ga itoh.makoto.ge} Automotive Human Factors Research Center National Institute of Advanced Industrial Science and Technology Tsukuba-city Japan

This study aims to investigate the influence of general knowledge, which denotes·driving automation’s taxonomy, definitions, function, driver role, and the request to intervene (RtI), on older adults’ takeover performance when using conditionally driving automation (DA), and to clarify the influence of knowledge on drivers’ attitudes toward DA. We introduced two types of DAs: full range and limited range. A driving simulator (DS) experiment was conducted to collect data, including driving behavior in taking over vehicle control and driver’s subjective evaluation of the DA. Data were collected from 36 elderly (mean age = 71.4±4.8 years) and 36 non-elderly (mean age = 40.8±9.5 years) participants. The results showed significant differences between the elderly and non-elderly, such that educating knowledge had a greater influence on the older adults, that is, instructing knowledge to the drivers contributed to a statistical increase in successful takeover rate from 0.66 to 0.80, but no effect was seen on either the response time or the maximum steering angular velocity. Furthermore, more frequent glance behavior of looking forward from a non-driving related task was observed in the educated groups. Self-rating scores of subjective evaluations revealed that older adults who were given the knowledge had a higher level of trust in and expectation from the DA, and more confidence in comprehending system functions. This study demonstrates the necessity of general knowledge instruction to enhance drivers’ positive attitudes toward DA.

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Narrow-area Bragg-edge transmission of iron samples using superconducting neutron sensor 34

Narrow-area Bragg-edge transmission of iron samples using su...

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34th International Symposium on Superconductivity, ISS 2021

作者： Vu, The Dang Shishido, Hiroaki Aizawa, Kazuya Oku, Takayuki Oikawa, Kenichi Harada, Masahide Kojima, Kenji M. Miyajima, Shigeyuki Soyama, Kazuhiko Koyama, Tomio Hidaka, Mutsuo Suzuki, Soh Y. Tanaka, Manobu M. Malins, Alex MacHida, Masahiko Ishida, Takekazu Division of Quantum and Radiation Engineering Osaka Prefecture University Osaka599-8570 Japan Materials and Life Science Division J-PARC Center Japan Atomic Energy Agency Ibaraki319-1195 Japan Department of Physics and Electronics Graduate School of Engineering Osaka Prefecture University Osaka599-8531 Japan NanoSquare Research Institute Osaka Prefecture University Osaka599-8570 Japan Centre for Molecular and Materials Science Triumf 4004 Wesbrook Mall VancouverBC2A3 Canada Advanced Ict Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Hyogo Kobe651-2492 Japan Advanced Industrial Science and Technology Tsukuba305-8568 Japan Tsukuba305-0801 Japan Tsukuba305-0801 Japan Center for Computational Science & E-Systems Japan Atomic Energy Agency 178-4-4 Wakashiba Chiba Kashiwa277-0871 Japan

This study investigates a current-biased kinetic inductance detector (CB-KID) performance by investigating Bragg-edge spectra from the restricted-area neuron transmission of materials. Iron samples with a size of 5 × 5 ×2 mm3 were used as typical test materials. The ergodic theorem was used to obtain a visible transmission spectrum so that a long-time averaging of a transmission spectrum can alternatively be evaluated using a space average of independently selected area spectra with the same ensemble size. The most visible edges were observed with a limited area sample of 0.43 mm2 using a minimum time bin of 25 μs in a time-of-flight (ToF) spectrum or a wavelength resolution of 0.0007 nm of each neutron pulse at beamline BL10 of the Japan Proton Accelerator Research Complex (J-PARC) center. The main Bragg edge of iron as a sum of random 100 ensembles (with an ensemble size of 3.1 × 2.3 μm2) thus obtained has a distinctive signal-to-noise ratio and can be fitted well with the Rietveld Imaging of Transmission Spectra (RITS) program with Miller indices. We consider that our CB-KID system is, in principle, able to analyze the Bragg edge of samples as small as 3.1 × 2.3 μm2. © Published under licence by IOP Publishing Ltd.

关键词： Iron

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A general bottom-up synthesis of CuO-based trimetallic oxide mesocrystal superstructures for efficient catalytic production of trichlorosilane

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Nano Research 2020年第10期13卷 2819-2827页

作者： Hezhi Liu Yongjun Ji Jing Li Yu Zhang Xueguang Wang Haijun Yu Dingsheng Wang Ziyi Zhong Lin Gu Guangwen Xu Yadong Li Fabing Su State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Light Industry Beijing Technology and Business UniversityBeijing 100048China State Key Laboratory of Advanced Special Steel Shanghai UniversityYanchang Road 149Zhabei DistrictShanghai 200072China College of Materials Sciences and Engineering Beijing Unriversity of TechnologyBejing 100124China Department of Chemistry Tsinghua UniversityBeijing 100084China Collee of Engineering Guangdong Technion-Israel Institute of Technology(GTIT)241 Daxue RoadShantou 515063China Department of Chemical Engineering Technion-Israel Institute of Technology(IT)Haifa 32000Israel Beijing National Laboratory for Condensed Matter PhysicsInstitute of PhysicsChinese Academy of SciencesBeijing 100190China Institute of Industrial Chemistry and Energy Technology Shenyang University of Chemical TechnologyShenyang 110142China Zhongke Langfang Institute of Process Engineering Fenghua Road No ILangfang Economic&Technical Development ZoneLangfang 065001China

Mesocrystals, the non-classical crystals with highly ordered nanoparticle superstructures, have shown great potential in many applications because of their newly collective properties. However, there is still a lack of a facile and general synthesis strategy to organize and integrate distinct components into complex mesocrystals, and of reported application for them in industrial catalytic reactions. Herein we report a general bottom-up synthesis of CuO-based trimetallic oxide mesocrystals (denoted as CuO-M1Ox-M2Oy, where M1 and M2 = Zn, In, Fe, Ni, Mn, and Co) using a simple precipitation method followed by a hydrothermal treatment and a topotactic transformation via calcination. When these mesocrystals were used as the catalyst to produce trichlorosilane (TCS) via Si hydrochlorination reaction, they exhibited excellent catalytic performance with much increased Si conversion and TCS selectivity. In particular, the TCS yield was increased 19-fold than that of the catalyst-free process. The latter is the current industrial process. The efficiently catalytic property of these mesocrystals is attributed to the formation of well-defined nanoscale heterointerfaces that can effectively facilitate the charge transfer, and the generation of the compressive and tensile strain on CuO near the interfaces among different metal oxides. The synthetic approach developed here could be applicable to fabricate versatile complicated metal oxide mesocrystals as novel catalysts for various industrial chemical reactions.

关键词： CuO-based trimetallic oxide mesocrystal superstructures catalytic production of trichlorosilane synthesis strategy

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mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations

arXiv

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arXiv 2022年

作者： Suzumura, Toyotaro Sugiki, Akiyoshi Takizawa, Hiroyuki Imakura, Akira Nakamura, Hiroshi Taura, Kenjiro Kudoh, Tomohiro Hanawa, Toshihiro Sekiya, Yuji Kobayashi, Hiroki Matsushima, Shin Kuga, Yohei Nakamura, Ryo Jiang, Renhe Kawase, Junya Hanai, Masatoshi Miyazaki, Hiroshi Ishizaki, Tsutomu Shimotoku, Daisuke Miyamoto, Daisuke Aida, Kento Takefusa, Atsuko Kurimoto, Takashi Sasayama, Koji Kitagawa, Naoya Fujiwara, Ikki Tanimura, Yusuke Aoki, Takayuki Endo, Toshio Ohshima, Satoshi Fukazawa, Keiichiro Date, Susumu Uchibayashi, Toshihiro Information Technology Center The University of Tokyo Japan Information Initiative Center Hokkaido University Japan Cyberscience Center Tohoku University Japan Faculty of Engineering Information and Systems University of Tsukuba Japan Division for Information and Communication Systems The University of Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Japan Center for Cloud Research and Development National Institute of Informatics Japan Research and Development Center for Academic Networks National Institute of Informatics Japan Research Center for Open Science and Data Platform National Institute of Informatics Japan Digital Architecture Research Center National Institute of Advanced Industrial Science and Technology Japan Global Scientific Information and Computing Center Tokyo Institute of Technology Japan Information Technology Center Nagoya University Japan Academic Center for Computing and Media Studies Kyoto University Japan Cybermedia Center Osaka University Japan Research Institute for Information Technology Kyushu University Japan

The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks. We have built such a nation-wide cloud platform, called "mdx" to meet this need. The mdx platform’s virtualization service, jointly operated by 9 national universities and 2 national research institutes in Japan, launched in 2021, and more features are in development. Currently mdx is used by researchers in a wide variety of domains, including materials informatics, geo-spatial information science, life science, astronomical science, economics, social science, and computer science. This paper provides an the overview of the mdx platform, details the motivation for its development, reports its current status, and outlines its future plans. © 2022, CC BY.

关键词： Internet of things

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An avoiding overlap method between acoustic shadow and organ for automated ultrasound diagnosis and treatment

An avoiding overlap method between acoustic shadow and organ...

引用

IEEE Global Conference on Consumer Electronics (GCCE)

作者： Momoko Matsuyama Norihiro Koizumi Yu Nishiyama Ryosuke Tsumura Hiroyuki Tsukihara Kazushi Numata Department of Mechanical and Intelligent Systems Engineering The University of Electro-Communications Chofu Japan Department of Computer and Network Engineering The University of Electro-Communications Chofu Japan Health and Medical Research Institute National Institute of Advanced Industrial Science and Technology line 4 Tsukuba Japan Department of Cardiothoracic Surgery The University of Tokyo Bunnkyo-Ku Japan Gastroenterological Center Yokohama City University Medical Center Yokohama Japan

ISBN: (纸本)9781665492331

Ultrasound diagnosis and treatment have attracted attention because they are noninvasive and allow real-time observation of lesions. However, it is difficult to accurately estimate the location of the treatment area because of information loss due to acoustic shadows caused by the reflection of sound waves from hard tissues such as bone. In this study, we propose a probe manipulation method that uses deep learning to avoid overlap between organs and shadows for automated diagnosis.

关键词： Deep learning Ultrasonic imaging Acoustics Real-time systems Reflection Reliability Lesions

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A Novel YJQR-LSTM Model for Nonparametric Probabilistic Sustainable Agriculture Wind Power Forecasting Based on Intelligent IoT

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IEEE Internet of Things Journal 2024年

作者： Wang, Jie Jiang, Junhui Chen, Xinlong Cai, Defu Wu, Yue Lu, Renzhi School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Harbin Engineering University College of Computer Science and Technology Harbin150001 China State Grid Hubei Electric Power Research Institute Hubei Wuhan430079 China School of Technology State Key Laboratory of Efficient Production of Forest Resources Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation Beijing Forestry University Beijing100083 China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China State Key Laboratory of Mechanical Transmission for Advanced Equipment Chongqing University Chongqing400044 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Energy costs associated with the consumption of non-renewable energy sources have become an important issue in improving the international competitiveness of agriculture. Wind power, as a renewable energy source, can replace non-renewable energy sources to reduce energy costs and improve the sustainability of agricultural. However, the inherent intermittency, randomness, and volatility within weather conditions and wind speed presents a substantial challenge in accurately predicting wind power generation. This work proposes a novel YJQR-LSTM algorithm that leverages Yeo-Johnson quantile regression (YJQR) with a long short-term memory (LSTM) network for nonparametric probabilistic forecasting of wind power generation via the Intelligent Internet of Things. First, an improved YJQR model based on the YJ transformation is designed to obtain a more precise characterization of wind uncertainty, providing a more flexible probability density function for wind power generation. Then, utilizing the unique structure of the LSTM network to learn the parameters of the YJQR model, temporal features can be extracted from time series data. To mitigate the impact of outliers in the raw data on accuracy and improve computational efficiency, a novel logarithmic likelihood function is developed as the loss function utilized in the training phase. The effectiveness of the proposed algorithm is validated using a real-world dataset from five wind farms from the Global Energy Forecasting Competition. Numerical results demonstrate that the algorithm provides more accurate wind power prediction results in complex wind power data environments, which is important for making full use of wind energy and thus reducing the consumption of non-renewable energy in agriculture. © 2024 IEEE.

关键词： Wind forecasting

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Development of multi-beam optics for time-resolved X-ray tomography: From π-polarization to σ-polarization 14

Development of multi-beam optics for time-resolved X-ray tom...

引用

14th International Conference on Synchrotron Radiation Instrumentation, SRI 2021

作者： Voegeli, Wolfgang Liang, Xiaoyu Shirasawa, Tetsuroh Arakawa, Etsuo Hyodo, Kazuyuki Kudo, Hiroyuki Yashiro, Wataru Department of Physics Tokyo Gakugei University 4-1-1 Nukuikita-Machi Tokyo184-8501 Japan Tohoku University 2-1-1 Katahira Aoba-ku Sendai Miyagi980-8577 Japan National Metrology Institute of Japan National Institute of Advanced Industrial Science and Technology 5-2-2107 1-1-1 Higashi Tsukuba Ibaraki305-8565 Japan Photon Factory Institute of Materials Structure Science KEK 1-1 Oho Tsukuba Ibaraki305-0801 Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba305-8573 Japan Tohoku University 2-1-1 Katahira Aoba-ku Sendai Miyagi980-8577 Japan Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan

A multi-beam X-ray optics that can image a sample from different directions in a large angular range simultaneously without sample rotation is reported. It consists of 28 thin silicon crystals that are arranged in a σ-polarization diffraction geometry so that the diffracted X-rays from an incident white synchrotron radiation beam pass through the sample. A tomogram of a simple test sample was calculated from projection images recorded with the optics, showing that an alignment accuracy sufficient for X-ray tomography can be achieved. © Published under licence by IOP Publishing Ltd.

关键词： Polarization

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