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Micromagnetics Simulation of Highly Efficient Oscillation of Magnetization in a Ferromagnetic Local Areas via Spin Waves Induced by Spin-Orbit Torque

Micromagnetics Simulation of Highly Efficient Oscillation of...

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2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Koda, Tetsunori Muroga, Sho Endo, Yasushi Oshima College National Institute of Technology Department of Electronic Mechanical Engineering Suo-Oshima742-2193 Japan Akita University Graduate School of Engineering Science Department of Mathematical Science and Electrical-Electronic-Computer Engineering Akita010-8502 Japan Department of Electrical Engineering Graduate School of Engineering Tohoku University Sendai980-8579 Japan Tohoku University Center for Spintronics Research Network Sendai980-8577 Japan Sendai980-8577 Japan

ISBN: (纸本)9798350338362

We study numerical simulation of highly efficient oscillation of magnetization in a ferromagnetic local region using the spin-orbit torque. It is found that in the presence of multiple SOT regions, the precession motion can be excited at a lower current density through the interaction. This interaction is caused by spin waves, and as a result, phase control between the precession motions is possible through the gap between the areas. Our new finding indicates that the interaction between the wave source and the spin wave is very complex in devices that utilize the interference effects of spin waves. © 2023 IEEE.

关键词： Spin waves

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Extracting Stress-Related EEG Patterns from Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency

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IEEE Transactions on Neural Systems and Rehabilitation engineering 2024年 32卷 1817-1827页

作者： Su, Cheng-Hua Ko, Li-Wei Jung, Tzyy-Ping Onton, Julie Tzou, Shey-Cherng Juang, Jia-Chi Hsu, Chung-Yao Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Department of Biomedical Science and Environmental Biology Kaohsiung807 Taiwan University of California San Diego Swartz Center for Computational Neuroscience La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300 Taiwan University of California San Diego Institute for Neural Computation La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Biological Science and Technology Hsinchu300 Taiwan Kaohsiung Medical University Hospital Sleep Disorders Center Department of Neurology Kaohsiung807 Taiwan Kaohsiung Medical University College of Medicine Department of Neurology Kaohsiung807 Taiwan

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution. © 2001-2011 IEEE.

关键词： Entropy

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A New Lightweight Routing Protocol for Internet of Mobile Things Based on Low Power and Lossy Network Using a Fuzzy-Logic Method

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Pervasive and Mobile Computing 2024年 97卷

作者： Ghanbari, Zahra Navimipour, Nima Jafari Hosseinzadeh, Mehdi Shakeri, Hassan Darwesh, Aso Department of Computer Engineering Sabzevar Branch Islamic Azad University Sabzevar Iran Department of Computer Engineering Kadir Has University Istanbul Iran Future Technology Research Center National Yunlin University of Science and Technology Douliou64002 Taiwan Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Computer Engineering Mashhad Branch Islamic Azad University Mashhad Iran Information Technology Department University of Human Development Sulaimaniyah Iraq Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran

The IoT devices with embedded mobile devices create the Internet of Mobile Things (IoMT) paradigm. Mobility is not supported by the routing protocol for low-power and lossy networks (RPL) created for static networks. IoMT has raised routing challenges such as link failure, instability, energy depletion, packet loss, and handover delay in the network. In this context, IoMT Fuzzy-based RPL (IoMT-FRPL) is proposed in this paper to enhance routing performance. Receiving Signal Strength Indicator (RSSI), Euclidean distance, Hop Count, and Expected Transmission Count (ETX) metrics are built into the fuzzy interface system for the mobile nodes in the network to conserve energy. The IoMT-FRPL consists of the following three key steps: The first steps are data transmission and motion investigation, the second is fuzzy-based prediction of a new static parent for the mobile node, and the third is verifying the unique attachment point. When conventional RPL, mRPL, and EMA-RPL were compared to IoMT-performance FRPL's in Cooja/Contiki 2.7, the simulation results revealed improvements in energy consumption, handover delay, packet delivery rate (PDR), and signaling cost. © 2023 Elsevier B.V.

关键词： Fuzzy logic

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parallelism or Fairness? How to Be Friendly for SSDs in Cloud Environments

Parallelism or Fairness? How to Be Friendly for SSDs in Clou...

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IEEE International Conference on Cluster Computing

作者： Yang Zhou Fang Wang Zhan Shi Dan Feng Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of data storage systems and Technology Ministry of Education of China Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350358711

ISBN: (纸本)9798350358728

Modern SSDs achieve low latency and high throughput by utilizing multiple levels of SSD parallelism. Fairness is also a critical design consideration in cloud environments and has inspired great interest in recent years to study it. However, we find that excessive striving for SSD parallelism can inadvertently harm the SSD fairness due to the striped data layout. We observe from our experimental analysis that some common access patterns in cloud loads (e.g., high-intensity I/O) are not addressed by SSD parallelism, which can affect both SSD parallelism and fairness. In this paper, we analyze two address mapping policies with orthogonal characteristics from SSD parallelism and fairness perspectives. Based on extensive experiments and observations, we schedule a hybrid address mapping policy to achieve fairness of SSDs in cloud environments by distinguishing different I/O access modes and cold/hot data, while ensuring SSD performance. Experimental results on the latest block-level I/O traces show that our approach significantly improves performance and fairness by up to 77.3% and 62.8%, respectively, over the previous schemes with negligible cost. Meanwhile, it can also reduce the write amplification by 23.5% to 33.5%.

关键词： Schedules Layout Interference parallel processing Predictive models Throughput Data models Resource management Decision trees Low latency communication

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GradedDAG: An Asynchronous DAG-based BFT Consensus with Lower Latency

GradedDAG: An Asynchronous DAG-based BFT Consensus with Lowe...

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Reliable Distributed Systems

作者： Xiaohai Dai Zhaonan Zhang Jiang Xiao Jingtao Yue Xia Xie Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China School of Computer Science and Technology Hainan University China

To enable parallel processing, the Directed Acyclic Graph (DAG) structure is introduced to the design of asyn-chronous Byzantine Fault Tolerant (BFT) consensus protocols, known as DAG-based BFT. Existing DAG-based BFT protocols operate in successive waves, with each wave containing three or four Reliable Broadcast (RBC) rounds to broadcast data, resulting in high latency due to the three communication steps required in each RBC. For instance, Tusk, a state-of-the-art DAG-based BFT protocol, has a good-case latency of 7 communication steps and an expected worst latency of 21 communication steps. To reduce latency, we propose GradedDAG, a new DAG-based BFT consensus protocol based on our adapted RBC called Graded RBC (GRBC) and the Consistent Broadcast (CBC), with each wave consisting of only one GRBC round and one CBC round. Through GRBC, a replica can deliver data with a grade of 1 or 2, and a non-faulty replica delivering the data with grade 2 can ensure that more than 2/3 of replicas have delivered the same data. Meanwhile, through CBC, data delivered by different non-faulty replicas must be identical. In each wave, a block in the GRBC round will be elected as the leader. If a leader block has been delivered with grade 2, it and all its ancestor blocks can be committed. GradedDAG offers a good-case latency of 4 communication steps and an expected worst latency of 7.5 communication steps, significantly lower than the state-of-the-art. Experimental results demonstrate GradedDAG's feasibility and efficiency.

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Angularly Stable, Single-Layer Absorptive Metasurface for X-Band Applications

Angularly Stable, Single-Layer Absorptive Metasurface for X-...

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Microwave, Antennas & Circuits (ICMAC), International Conference on

作者： Muhammad Danial Shafi Ahsaan Gul Hassan Harun Ildeş Inam Ullah Nosherwan Shoaib Symeon Nikolaou School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Electrical and Electronics Engineering Hacettepe University Ankara Turkey Frederick Research Center Nicosia Cyprus Electrical Engineering Department Frederick University Nicosia Cyprus

ISBN: (数字)9798331518424

ISBN: (纸本)9798331518431

This work presents the design of a single-layer absorptive metasurface capable of achieving broadband absorption across the X -band over a wide range of incidence angles. The design introduces novelty through its unit cell configuration, angular stability, enhanced fractional bandwidth, and absorption without the use of an air gap. Both measured and simulated results are in strong agreement, underscoring the potential of the proposed metasurface for radar cross-section (RCS) reduction applications. Overall, the absorption ratio (AR) exceeds 80% for incidence angles up to 50°, highlighting its effectiveness for practical applications.

关键词： Electric potential Radar cross-sections Absorption Circuits Bandwidth Metasurfaces Stability analysis Broadband communication Circuit stability Electromagnetics

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SAR onboard Broadband C-band Circularly Polarized Antenna for In situ Volcanic Lava Observation 8

SAR onboard Broadband C-band Circularly Polarized Antenna fo...

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8th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2023

作者： Yoshimoto, Yuki Miyazaki, Takahiro Gao, Steven Pramono, Subuh Kashihara, Hisato Ito, Koichi Sumantyo, Josaphat Tetuko Sri Takahashi, Ayaka Santosa, Cahya Edi Naito, Motoyuki Sumitomo Metal Mining Co. Ltd. Computer Aided Engineering and Development Dept. Tokyo Japan Chiba University Dept. of Environmental Remote Sensing Chiba Japan The Chinese University of Hong Kong Dept. of Electronic Engineering Hong Kong Hong Kong Sebelas Maret University Dept. of Electrical Engineering Surakarta Indonesia Chiba University Center for Environmental Remote Sensing Chiba Japan Teikyo University Dept. of Aerospace Engineering Utsunomiya Japan National Research and Innovation Agency Research Center for Aeronautics Technology Bogor Indonesia

ISBN: (纸本)9798350393590

Estimating the volcanic eruption scale is important for mitigating eruption hazards. While the eruption scale can be explained by the eruption mode and its temporal variation, the dominant factor is expected to be the formation reaction of volcanic products, but there are still many unknowns, including the relationship with the thermal history. To solve this problem, we proposed a broadband circularly polarized microwave antenna for a synthetic aperture radar (SAR) sensor that is suitable for in situ observation of volcanic materials such as lava. As a result of fabricating the proposed antenna, the antenna characteristics were almost the same as the simulation one, with a center frequency of 5.394 GHz, IBW=32.6%, ARBW=23.7%, and Gain=12.0dBic. The measurement results indicate that the proposed antenna has loss and radiation characteristics suitable for the purpose. © 2023 IEEE.

关键词： Synthetic aperture radar

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Robin: A Novel Method to Produce Robust Interpreters for Deep Learning-Based Code Classifiers

Robin: A Novel Method to Produce Robust Interpreters for Dee...

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IEEE International Conference on Automated Software engineering (ASE)

作者： Zhen Li Ruqian Zhang Deqing Zou Ning Wang Yating Li Shouhuai Xu Chen Chen Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Cluster and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Hubei Engineering Research Center on Big Data Security Department of Computer Science University of Colorado Colorado Springs USA Center for Research in Computer Vision University of Central Florida USA School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Deep learning has been widely used in source code classification tasks, such as code classification according to their functionalities, code authorship attribution, and vulnerability detection. Unfortunately, the black-box nature of deep learning makes it hard to interpret and understand why a classifier (i.e., classification model) makes a particular prediction on a given example. This lack of interpretability (or explainability) might have hindered their adoption by practitioners because it is not clear when they should or should not trust a classifier's prediction. The lack of interpretability has motivated a number of studies in recent years. However, existing methods are neither robust nor able to cope with out-of-distribution examples. In this paper, we propose a novel method to produce Robust interpreters for a given deep learning-based code classifier; the method is dubbed Robin. The key idea behind Robin is a novel hybrid structure combining an interpreter and two approximators, while leveraging the ideas of adversarial training and data augmentation. Experimental results show that on average the interpreter produced by Robin achieves a 6.11% higher fidelity (evaluated on the classifier), 67.22% higher fidelity (evaluated on the approximator), and 15.87x higher robustness than that of the three existing interpreters we evaluated. Moreover, the interpreter is 47.31% less affected by out-of-distribution examples than that of LEMNA.

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Exciton-activated effective phonon magnetic moment in monolayer MoS2

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Physical Review B 2024年第15期109卷 155426-155426页

作者： Chunli Tang Gaihua Ye Cynthia Nnokwe Mengqi Fang Li Xiang Masoud Mahjouri-Samani Dmitry Smirnov Eui-Hyeok Yang Tingting Wang Lifa Zhang Rui He Wencan Jin Department of Electrical and Computer Engineering Auburn University Auburn Alabama 36849 USA Department of Physics Auburn University Auburn Alabama 36849 USA Department of Electrical and Computer Engineering Texas Tech University Lubbock Texas 79409 USA Department of Mechanical Engineering Stevens Institute of Technology Hoboken New Jersey 07030 USA National High Magnetic Field Laboratory Tallahassee Florida 32310 USA Phonon Engineering Research Center of Jiangsu School of Physics and Technology Nanjing Normal University Nanjing 210023 China

Optical excitation of chiral phonons plays a vital role in studying the phonon-driven magnetic phenomena in solids. Transition metal dichalcogenides host chiral phonons at high symmetry points of the Brillouin zone, providing an ideal platform to explore the interplay between chiral phonons and valley degree of freedom. Here, we investigate the helicity-resolved magneto-Raman response of monolayer MoS2 and identify a doubly degenerate Brillouin-zone-center chiral phonon mode at ∼270cm−1. Our wavelength- and temperature-dependent measurements show that this chiral phonon is activated through the resonant excitation of A exciton. Under an out-of-plane magnetic field, the chiral phonon exhibits giant Zeeman splitting, which corresponds to an effective magnetic moment of ∼2.5μB. Moreover, we carry out theoretical calculations based on the morphic effects in nonmagnetic crystals, which reproduce the linear Zeeman splitting and Raman cross section of the chiral phonon. Our study provides important insights into lifting the chiral phonon degeneracy in an achiral covalent material, paving a route to excite and control chiral phonons.

关键词： Excitons Light-induced magnetic effects Magneto-optical effect Valley degrees of freedom Transition metal dichalcogenides Density functional theory Photoexcitation Raman spectroscopy

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Network link prediction via deep learning method: A comparative analysis with traditional methods

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engineering Science and technology, an International Journal 2024年 56卷

作者： Zare, Gholamreza Jafari Navimipour, Nima Hosseinzadeh, Mehdi Sahafi, Amir Department of Computer Engineering Qeshm Branch Islamic Azad University Department of Computer Engineering Tabriz Branch Islamic Azad University Future Technology Research Center National Yunlin University of Science and Technology Research Center of High Technologies and Innovative Engineering Western Caspian University Institute of Research and Development Duy Tan University School of Medicine and Pharmacy Duy Tan University Department of Computer Engineering South Tehran Branch Islamic Azad University

In the domain of data-centric networks, Link Prediction (LP) is instrumental in discerning potential or absent connections among entities within complex networks. By employing graph data structures, LP techniques enable a detailed analysis of entity interactions across varied sectors, contributing significantly to overcoming challenges in data filtering and integrity restoration, primarily when the network does not provide embedded data. Although LP methods are widely applicable, especially in recommender systems, their efficacy in current social networks needs to be thoroughly investigated. This study introduces an innovative LP approach using Deep Neural Networks (DNNs). We compare our method against a comprehensive set of established techniques, including traditional score-based methods, classical baselines, and recent deep learning approaches like Graph Neural Networks (GNNs). Our DNN-based solution incorporates a robust feature extraction process and a binary classifier, optimized for accurate prediction of missing links within networks. We performed extensive experimental evaluations on diverse datasets, including co-authorship networks, e-commerce, and social media networks. The study encompasses a comparative analysis with traditional LP techniques, namely Common Neighbors, Resource Allocation Index, Jaccard's Coefficient, and Adamic/Adar Index, as well as other selected baseline and deep-learning methods. Our findings demonstrate that the DNN-based approach significantly enhances predictive accuracy, outperforming the conventional baseline methods in link prediction. © 2024

关键词： Deep Learning Graph Neural Network Link Prediction Machine Learning Recommender Systems Social Networks

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