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Ambient- and high-pressure studies of structural, electronic, and magnetic properties of single-crystal EuZn2P2

Physical Review B 2024年第1期110卷 014421-014421页

作者： Damian Rybicki Kamila Komędera Janusz Przewoźnik Łukasz Gondek Czesław Kapusta Karolina Podgórska Wojciech Tabiś Jan Żukrowski Lan Maria Tran Michał Babij Zbigniew Bukowski Ladislav Havela Volodymyr Buturlim Jiri Prchal Martin Divis Petr Kral Ilja Turek Itzhak Halevy Jiri Kastil Martin Misek Utpal Dutta Dominik Legut Faculty of Physics and Applied Computer Science al. A. Mickiewicza 30 30-059 Kraków Poland Mössbauer Spectroscopy Laboratory Faculty of Mathematics and Physics Department of Condensed Matter Physics Ke Karlovu 3 121 16 Prague 2 Czech Republic Unit of Nuclear Engineering Faculty of Engineering Science Na Slovance 1999/2 182 00 Prague 8 Czech Republic VŠB -

A thorough study of EuZn2P2 single crystals, which were grown from Sn flux, was performed using both bulk (heat capacity, ac susceptibility, dc magnetization, electrical resistivitivity, magnetoresistance) and microscopic (Mössbauer spectroscopy) techniques. Electrical resistance and magnetic susceptibility were measured also under high pressure conditions (up to 19 and 9.5 GPa, respectively). Further insight into electronic properties and phonons is provided by ab initio calculations. The results indicate that EuZn2P2 is an antiferromagnet with strong Eu-Eu exchange coupling of ferromagnetic type within the basal plane and weaker antiferromagnetic interaction along the c axis. The Eu magnetic moments are tilted from the basal plane. Hydrostatic pressure strongly affects both magnetic (increase of the Néel temperature) and electronic (suppression of the band gap and semimetallic behavior) properties, indicating a strong interplay of structure with magnetic and electronic degrees of freedom.

关键词： Antiferromagnetism Density of states Electronic structure of atoms & molecules First-principles calculations Antiferromagnets Rare-earth magnetic materials AC susceptibility measurements Crystal growth DC susceptibility measurements Magnetization measurements Mössbauer spectroscopy Pressure effects Pressure techniques Scanning electron microscopy Tight-binding model X-ray diffraction

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TacGNN: Learning Tactile-based In-hand Manipulation with a Blind Robot

arXiv

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arXiv 2023年

作者： Yang, Linhan Huang, Bidan Li, Qingbiao Tsai, Ya-Yen Lee, Wang Wei Song, Chaoyang Pan, Jia The Department of Mechanical and Energy Engineering Southern University of Science and Technology The Department of Computer Science University of Hong Kong Hong Kong Tencent Robotics X China The Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom The Hamlyn Centre for Robotic Surgery Department of Computing Imperial College London LondonSW7 2AZ United Kingdom The Department of Mechanical and Energy Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China The Department of Computer Science University of Hong Kong 999077 Hong Kong

In this paper, we propose a novel framework for tactile-based dexterous manipulation learning with a blind anthropomorphic robotic hand, i.e. without visual sensing. First, object-related states were extracted from the raw tactile signals by a graph-based perception model - TacGNN. The resulting tactile features were then utilized in the policy learning of an in-hand manipulation task in the second stage. This method was examined by a Baoding ball task - simultaneously manipulating two spheres around each other by 180 degrees in hand. We conducted experiments on object states prediction and in-hand manipulation using a reinforcement learning algorithm (PPO). Results show that TacGNN is effective in predicting object-related states during manipulation by decreasing the RMSE of prediction to 0.096cm comparing to other methods, such as MLP, CNN, and GCN. Finally, the robot hand could finish an in-hand manipulation task solely relying on the robotic own perception - tactile sensing and proprioception. In addition, our methods are tested on three tasks with different difficulty levels and transferred to the real robot without further training. https://***/view/tacgnn. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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UMAP and Tree Physiology Optimization for Effective Water Quality Management in Consumer Electronics

UMAP and Tree Physiology Optimization for Effective Water Qu...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Brij B. Gupta Akshat Gaurav Shavi Bansal Jinsong Wu Varsha Arya Kwok Tai Chui Department of Computer Science and Information Engineering Asia University Taichung Taiwan University of Economics and Human Science Warsaw Poland Ronin Institute Montclair NJ USA Insights2Techinfo India Department of Electrical Engineering Universidad de Chile Chile Hong Kong Metropolitan University (HKMU) Hong Kong

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Leveraging UMAP for feature selection and Tree Physiology Optimization (TPO) for hyperparameter tuning, we proposed model for efficient water quality control in consumer electronics. We balanced the data with SMOTE from a Kaggle water quality dataset and using UMAP to find important characteristics. The TPO method then was used to maximize the parameters of the deep learning model. With an eye on few false positives, our algorithm was very accurate in spotting clean water. Still, the confusion matrix shows that there are difficulties precisely identifying dangerous water.

关键词： Deep learning Electric potential Accuracy Water quality Feature extraction Physiology Safety Consumer electronics Optimization Tuning

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Recent advances in mobile edge computing and content caching

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Digital Communications and Networks 2020年第2期6卷 189-194页

作者： Sunitha Safavat Naveen Naik Sapavath Danda B.Rawat Data Science and Cybersecurity Center(DSC2) Department of Electrical Engineering and Computer ScienceHoward UniversityWashingtonDC20059USA

The demand for digital media services is increasing as the number of wireless subscriptions is growing *** order to meet this growing need,mobile wireless networks have been advanced at a tremendous pace over recent ***,the centralized architecture of existing mobile networks,with limited capacity and range of bandwidth of the radio access network and low bandwidth back-haul network,can not handle the exponentially increasing mobile ***,we have seen the growth of new mechanisms of data caching and delivery methods through intermediate caching *** this paper,we present a survey on recent advances in mobile edge computing and content caching,including caching insertion and expulsion policies,the behavior of the caching system,and caching optimization based on wireless *** of the important open challenges in mobile edge computing with content caching are identified and *** have also compared edge,fog and cloud computing in terms of *** of this paper will get a thorough understanding of recent advances in mobile edge computing and content caching in mobile wireless networks.

关键词： Mobile edge computing Content caching MEC

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Objective diagnosis of ADHD through movement analysis by using a smart chair with piezoelectric material

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Pediatrics and Neonatology 2023年第1期64卷 46-52页

作者： Chang, Tung-Ming Wu, Rong-Ching Yang, Rei-Cheng Chiang, Ching-Tai Chiu, Yi-Hung Ouyang, Chen-Sen Wang, Yun-Ming Wu, Ming-Hsu Lin, Guang-Chung Lin, Lung-Chang Department of Pediatric Neurology Changhua Christian Children's Hospital Changhua Taiwan Department of Electrical Engineering I-Shou University Taiwan Departments of Pediatrics Kaohsiung Medical University Hospital Kaohsiung Medical University Taiwan Department of Computer and Communication National Pingtung University Taiwan Department of Information Engineering I-Shou University Taiwan Department of Biological Science and Technology Institute of Molecular Medicine and Bioengineering Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B) National Yang Ming Chiao Tung University Taiwan Department of Pediatrics School of Medicine College of Medicine Kaohsiung Medical University Taiwan Department of Biological Science and Technology College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan

Background: Attention-deficit/hyperactivity disorder (ADHD) is the most common neuropsychiatric disorder in schoolchildren. ADHD diagnoses are generally made based on criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. The diagnosis is made clinically based on observation and information provided by parents and teachers, which is highly subjective and can lead to disparate results. Considering that hyperactivity is one of the main symptoms of ADHD, the inaccuracy of ADHD diagnosis based on subjective criteria necessitates the identification of a method to objectively diagnose ADHD. Methods: In this study, a medical chair containing a piezoelectric material was applied to objectively analyze movements of patients with ADHD, which were compared with those of patients without ADHD. This study enrolled 62 patients—31 patients with ADHD and 31 patients without ADHD. During the clinical evaluation, participants’ movements were recorded by the piezoelectric material for analysis. The variance, zero-crossing rate, and high energy rate of movements were subsequently analyzed. Results: The results revealed that the variance, zero-crossing rate, and high energy rate were significantly higher in patients with ADHD than in those without ADHD. Classification performance was excellent in both groups, with the area under the curve as high as 98.00%. Conclusion: Our findings suggest that the use of a smart chair equipped with piezoelectric material is an objective and potentially useful method for supporting the diagnosis of ADHD. © 2022 Taiwan Pediatric Association

关键词： Attention-deficit/hyperactivity disorder piezoelectric material smart chair

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A generative model for surrogates of spatial-temporal wildfire nowcasting

arXiv

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arXiv 2023年

作者： Cheng, Sibo Guo, Yike Arcucci, Rossella Data Science Institute Department of computing Imperial College LondonSW7 2AZ United Kingdom Department of Computer Science and Engineering The Hong Kong University of Science and Technology 999077 Hong Kong Department of Earth Science and Engineering Imperial College LondonSW7 2AZ United Kingdom

—Recent increase in wildfires worldwide has led to the need for real-time fire nowcasting. Physics-driven models, such as cellular automata and computational fluid dynamics can provide high-fidelity fire spread simulations but they are computationally expensive and time-consuming. Much effort has been put into developing machine learning models for fire prediction. However, these models are often region-specific and require a substantial quantity of simulation data for training purpose. This results in a significant amount of computational effort for different ecoregions. In this work, a generative model is proposed using a three-dimensional Vector-Quantized Variational Autoencoders to generate spatial-temporal sequences of unseen wildfire burned areas in a given ecoregion. The model is tested in the ecoregion of a recent massive wildfire event in California, known as the Chimney fire. Numerical results show that the model succeed in generating coherent and structured fire scenarios, taking into account the impact from geophysical variables, such as vegetation and slope. Generated data are also used to train a surrogate model for predicting wildfire dissemination, which has been tested on both simulation data and the real Chimney fire event. © 2023, CC BY-NC-SA.

关键词： Chimneys

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Applying the noiseless extrapolation error mitigation protocol to calculate real-time quantum field theory scattering phase shifts

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Physical Review D 2024年第1期109卷 014505-014505页

作者： Zachary Parks Arnaud Carignan-Dugas Erik Gustafson Yannick Meurice Patrick Dreher Department of Computer Science North Carolina State University Raleigh North Carolina 27695 USA Keysight Technologies Canada Kanata Ontario K2K 2W5 Canada Fermi National Accelerator Laboratory Batavia Illinois 60510 USA Department of Physics and Astronomy The University of Iowa Iowa City Iowa 52242 USA Department of Electrical and Computer Engineering North Carolina State University Raleigh North Carolina 27695 USA

Real-time scattering calculations on a noisy intermediate scale quantum (NISQ) quantum computer are disrupted by errors that accumulate throughout the circuits. To improve the accuracy of such physics simulations, one can supplement the application circuits with a recent error mitigation strategy known as noiseless output extrapolation (NOX). We tested these error mitigation protocols on a transverse field Ising model and improved upon previous phase shift calculations. Our proof-of-concept 4-qubit application circuits were run on several IBM quantum computing hardware architectures. We introduce metrics that show between 22% and 73% error reduction for circuit depths ranging from 13 to 37 hard cycles, confirming that the NOX technique applies to circuits with a broad range of failure rates. We also observed an approximate 28% improvement in the accuracy of the time delay calculation of the scattering phase shift. These observations on different cloud-accessible devices confirm that NOX improves performance even when circuits are executed in substantially time-separated batches. Finally, we provide a heuristic method to obtain systematic error bars on the mitigated results, compare them with empirical errors and discuss their effects on phase shift estimates.

关键词： Phase shift Quantum benchmarking Quantum circuits Quantum computation Quantum simulation Scattering amplitudes

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Towards the Adoption of Industry 4.0 Technologies in the Digitalization of Manufacturing Supply Chain

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Procedia computer science 2024年 232卷 337-347页

作者： Oluseyi Afolabi Adeyemi Pedro M.G. Pinto Funlade Sunmola Abiodun Musa Aibinu Julius .O. Okesola Esther .O. Adeyemi School of Physics Engineering and Computer Sciences University of Hertfordshire Hatfield. AL10 9AB United Kingdom. Summit University Offa. 23402. Nigeria Department of Computer Science First Technical University Ibadan. 23402. Nigeria Department of Logistics and IT MyBnK London. EC2A 3DR United Kingdom.

The study used multiple case studies to explore the findings from literature review on adoption of industry 4.0 technologies in manufacturing supply chains. It displays a digitalized supply chain as one of the best options for optimization of manufacturing companies processes and provides insights and some guidance on the industry 4.0 technologies for manufacturing companies to prioritize when starting the digitalization journey; to improve decision making, maximize efficiency and minimize costs. The main objective of the study is to explore various industry 4.0 technologies used in manufacturing supply chains and two propositions were suggested based on the three case companies investigated. The digitalization of manufacturing supply chains has an overall positive impact on how the supply chains operates and improves productivity and growth. It was concluded that industry 4.0 technologies are valuable tools from a managerial perspective, because they provide better process visibility and tracking of requisitions, improved efficiency, optimization of resources, easy to use templates, improved access to ordering data and reporting, improved decision making, and the supply chains are more autonomous.

关键词： Supply Chains Security Manufacturing Integration, Digitalization Case Studies

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Editorial

IEEE Transactions on Biometrics, Behavior, and Identity Scie...

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IEEE Transactions on Biometrics, Behavior, and Identity science 2024年第3期6卷 289-289页

作者： Liao, Shengcai Liu, Xiaoming Tistarelli, Massimo Chellappa, Rama Kittler, Josef United Arab Emirates University College of Information Technology Al Ain United Arab Emirates Michigan State University Department of Computer Science and Engineering East LansingMI48824 United States University of Sassari Computer Vision Laboratory Sassari07100 Italy Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218 United States Johns Hopkins University Department of Biomedical Engineering BaltimoreMD21218 United States University of Surrey Centre for Vision Speech and Signal Processing GuildfordGU2 7XH United Kingdom

The 2022 International Joint Conference on Biometrics (IJCB 2022) was held at Abu Dhabi, United Arab Emirates, from October 10 to October 13, 2022. This marked the first biometrics conference held in the Middle East. The IJCB 2022 conference combined two major biometrics conferences: the IEEE Biometrics Theory, Applications, and Systems (BTAS) conference and the International Conference on Biometrics (ICB). The IJCB 2022 conference was technically co-sponsored by both IAPR TC4 (Technical Committee on Biometrics) and the IEEE Biometrics Council. © 2019 IEEE.

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WheatNet: Attentional Path Aggregation Feature Pyramid Network for Precise Detection and Counting of Dense and Arbitrary-Oriented Wheat Spikes

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2024年第2期2卷 606-616页

作者： Jiao, Lin Liu, Qihuang Liu, Haiyun Chen, Peng Wang, Rujing Liu, Kang Dong, Shifeng Anhui University School of Internet Hefei230031 China Chinese Academy of Sciences National Engineering Research Center for Agro-Ecological Big Data Analysis and Application Hefei230031 China Chinese Academy of Sciences Institute of Intelligent Machines Hefei Institutes of Physical Science Hefei230031 China University of Science and Technology of China Hefei230031 China Anhui University National Engineering Research Center for Agro-Ecological Big Data Analysis and Application Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Internet Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Chinese Academy of Science Institute of Intelligent Machines Hefei Institutes of Physical Science Hefei230031 China University of Sheffield Department of Computer Science SheffieldS10 2TN United Kingdom Institute of Dataspace Hefei230093 China

Achieving the precise and real-time detection of wheat spikes play a crucial role in wheat growth monitoring for precision agriculture community. Machine-learning methods are commonly introduced to automatically detect and count the wheat spikes, which need carefully selected hand-crafted feature descriptors, leading to time-consuming and poor performance. The deep learning has become a promising technology for the accurate detection wheat spikes, owing to its powerful ability of feature extraction. However, the obtained wheat spike images from UAV still have serious overlap, dense distribution, various orientations, and large aspect ratios, leading to poor performance of recent wheat spike detection method. To address the demand of precise and fast detection and counting of wheat spike with dense distribution and arbitrary-orientation, a novel deep learning-based method, WheatNet, has been proposed. The attention mechanism has been introduced the process of feature fusing to highlight the important features of wheat spike as well as inhibit the useless information. Additionally, to optimize the parameters of the network, a loss function with soft dynamic label assignment is adopted to reduce the number of low-quality matches, which provides significant performance gains over other wheat spike detectors. Furthermore, to achieve the precise detection of wheat spike with multi-orientations, a large-scale oriented wheat spike dataset has been constructed, named RoWheat, including 900 images and 50419 annotations with dense distribution and various orientation. Experimental studies demonstrate that the proposed WheatNet achieves a recall of 99.7% and mAP of 91.8%, showing its promising performance gain compared to other state-of-the-art methods. © 2023 IEEE.

关键词： Image annotation

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