检索结果-内蒙古大学图书馆

Physical Review Letters 2024年第14期133卷 146902页

作者： Ethan R. Hansen Vasileios Niaouris Bethany E. Matthews Christian Zimmermann Xingyi Wang Roman Kolodka Lasse Vines Steven R. Spurgeon Kai-Mei C. Fu Department of Physics Energy and Environment Directorate Department of Electrical and Computer Engineering Department of Physics and Centre for Materials Science and Nanotechnology National Security Directorate Physical Sciences Division

The shallow donor in zinc oxide (ZnO) is a promising semiconductor spin qubit with optical access. Single indium donors are isolated in a commercial ZnO substrate using plasma focused ion beam (PFIB) milling. Quantum emitters are identified optically by spatial and frequency filtering. The indium donor assignment is based on the optical bound exciton transition energy and magnetic dependence. The emission stability of these single donors in terms of both intensity and frequency, alongside their transition linewidths less than twice the lifetime limit, highlight the promise of single In donors as optically accessible spin qubits. The optical stability of single donors after FIB fabrication is promising for optical device integration required for scalable quantum technologies based on single donors in direct band gap semiconductors.

关键词： Defects Excitons Impurities Quantum information with solid state qubits Radiation damage II-VI semiconductors Wide band gap systems Wurtzite Confocal imaging Focused ion beam Photoluminescence Time-resolved photoluminescence

来源：评论

学校读者我要写书评

暂无评论

Molecular-field-coefficient modeling of temperature-dependent ferrimagnetism in a complex oxide

引用

Physical Review Applied 2024年第1期21卷 014060-014060页

作者： Miela J. Gross Tingyu Su Jackson J. Bauer Caroline A. Ross Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA

The temperature-dependent magnetic moment of a magnetically ordered material is fundamental to all aspects of its technological applications. In ferrimagnetic materials with multiple sublattices containing different magnetic ions, the magnetization can vary nonmonotonically with temperature. Computational modeling of these materials provides insight into their sublattice occupancy and prediction of their behavior as a function of composition. Here we develop a python computer code called dionne that models the magnetism of rare earth (RE) iron garnets (RE3Fe5O12, REIGs) using molecular field coefficient theory. The program calculates the exchange interactions and the magnetic moment of each sublattice to determine the net magnetization and angular momentum as a function of temperature. dionne accounts for site occupancy on each sublattice, including the effects of nonmagnetic and magnetic substitutions, vacancies, Fe2+, and deviations from the ideal RE:Fe stoichiometry by considering their effects on the magnetization and exchange coupling. Unlike previous iterative methods, dionne recursively solves for the moment at each temperature, yielding an excellent match to magnetization versus temperature data for a range of bulk garnets. This work predicts magnetic properties of REIGs with a variety of compositions and point defect levels and enables design of ferrimagnets with useful properties.

关键词： Magnetic interactions Temperature Complex oxides Ferrimagnets Magnetic insulators Magnetic thin films Magnetic moment Micromagnetic modeling

来源：评论

学校读者我要写书评

暂无评论

On the Impact of Knowledge Distillation for Model Interpretability 40

On the Impact of Knowledge Distillation for Model Interpreta...

引用

40th International Conference on Machine Learning, ICML 2023

作者： Han, Hyeongrok Siwon, Kim Choi, Hyun-Soo Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul Korea Republic of ZIOVISION Inc. Chuncheon Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

Several recent studies have elucidated why knowledge distillation (KD) improves model performance. However, few have researched the other advantages of KD in addition to its improving model performance. In this study, we have attempted to show that KD enhances the interpretability as well as the accuracy of models. We measured the number of concept detectors identified in network dissection for a quantitative comparison of model interpretability. We attributed the improvement in interpretability to the class-similarity information transferred from the teacher to student models. First, we confirmed the transfer of class-similarity information from the teacher to student model via logit distillation. Then, we analyzed how class-similarity information affects model interpretability in terms of its presence or absence and degree of similarity information. We conducted various quantitative and qualitative experiments and examined the results on different datasets, different KD methods, and according to different measures of interpretability. Our research showed that KD models by large models could be used more reliably in various fields. The code is available at https://***/Rok07/KD_***. © 2023 Proceedings of Machine Learning Research. All rights reserved.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Unmanned Aerial Vehicles Navigation: An Overview

引用

SN computer science 2024年第2期5卷 256页

作者： Fagundes-Junior, Leonardo A. de Carvalho, Kevin B. Ferreira, Ricardo S. Brandão, Alexandre S. Núcleo de Especialização em Robótica Department of Electrical Engineering Graduate Program in Computer Science Federal University of Viçosa-UFV Av. Petter Henry Rolfs MG Viçosa 36570-900 Brazil

Unmanned aerial vehicles (UAVs) are a valuable source of data for a wide range of real-time applications, due to their functionality, availability, adaptability, and maneuverability. Working as mobile sensors, they can provide a cost-effective solution for extremely complex tasks, such as inspection, air-to-ground communications, search and rescue, surveillance, among others. Nevertheless, the robots needs to navigate in quite distinct environments and in different dynamism levels, usually facing unpredicted situations, very often using limited sensing and computing capabilities. A large number of solutions to this problem has been featured by the scientific community in the last years, some of them based on machine-learning (ML) methods. Due to its great capability to deal with big data and complexity, as well as its speedy and high-accuracy processing, the ML framework has been used to improve existing technologies and control techniques. In this context, its adoption in several UAV navigation strategies is expected to provide solutions for various problems where UAVs are used in real-time applications. Thus, in order to contextualize the most recent advances, this work provides a detailed survey of relevant researches in which ML techniques have been used in UAV navigation to improve some functional aspects, such as energy-efficiency, communication, execution time, resource management, obstacle avoidance, and path planning. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Autonomous navigation Path planning UAV-based solutions Visual-based navigation

来源：评论

学校读者我要写书评

暂无评论

Current-induced Néel order switching facilitated by magnetic phase transition

Current-induced Néel order switching facilitated by magneti...

引用

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

作者： Wu, Hao Zhang, Hantao Wang, Baomin Guo, Yaqin Cheng, Ran Wang, Kang L. Songshan Lake Materials Laboratory Dongguan523808 China University of California Department of Electrical and Computer Engineering Los AngelesCA90095 United States University of California Department of Electrical and Computer Engineering RiversideCA92521 United States Ningbo University School of Physical Science and Technology Ningbo315211 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Cas Key Laboratory of Magnetic Materials and Devices Ningbo315201 China

ISBN: (纸本)9798350338362

Antiferromagnetic materials (AFMs), which have zero-stray field and the THz-range magnetic resonance frequency, are promising candidates for the next-generation magnetic memory technology. Here, we report an electrical writing of antiferromagnetic orders through a record-low current density on the order of 106 A cm-2 facilitated by the unique AFM-ferromagnetic (FM) phase transition in FeRh. The spin-orbit torque can switch the AFM order parameter by 90° with a reduced writing current density by introducing a transient FM state via current-induced Joule heating. This work demonstrates the exciting possibility of writing operations in AFM-based devices with a lower current density, opening a new pathway toward pure AFM memory applications. © 2023 IEEE.

关键词： Magnetic resonance

来源：评论

学校读者我要写书评

暂无评论

Energy Consumption Prediction for Home Appliances with Recurrent Neural Networks 4

Energy Consumption Prediction for Home Appliances with Recur...

引用

4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Aancy, H. Mickle Mary, S. Anitha Janet Manikumar, T. Saravanan, G. Mohanavel, V. Gupta, Rahul Dev Panimalar Engineering College Department of Management Studies Tamil Nadu Chennai600123 India Noorul Islam Centre for Higher Education Department of Electrical and Electronics Engineering Tamil Nadu Kumaracoil629180 India Kalasalingam Academy of Research and Education Deemed to be University Department of Computer Science and Engineering Tamil Nadu 626126 India KPR Institute of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore641407 India Centre for Materials Engineering and Regenerative Medicine Bharath Institute of Higher Education and Research Tamil Nadu Chennai600073 India Department of Mechanical Engineering Haryana 133207 India

ISBN: (纸本)9798350385793

Efficient energy management requires a thorough understanding of individual appliance energy consumption in both residential and business environments. Because of the growing number of Internet of Things (loT) devices in smart homes, household appliances are a significant source of total energy consumption. Commonly used equipment such as heating systems, washing machines, and vacuum cleaners have a substantial impact on daily energy consumption. Significant energy savings can only be realized by careful management and forecasting of these appliances' energy consumption. This research employs Recurrent Neural Network (RNN) models for energy forecasting of housing appliances, with Long Short-Term Memory (LSTM) and a hybrid model known as Bi-LSTM-Attention Network. A Kaggle dataset with 28 features is used in this study, which is then reduced to 17 using a correlation plot. The processed data is used in both the training and testing phases of the RNN models. Many metrics are used to evaluate the performance of the models, including R-squared (R2), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The Bi- LSTM-Attention Network achieves excellent performance, with training and testing R2 values of 0.9978 and 0.9835, respectively. In addition, lower MSE and RMSE values demonstrate that Bi-LSTM-Attention Network constantly outperforms LSTM. The findings show that the proposed Bi-LSTM-Attention Network is capable of accurately predicting the amount of energy household appliances will consume. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Ultrastrong Light-Matter and Matter-Matter Coupling

Ultrastrong Light-Matter and Matter-Matter Coupling

引用

2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022

作者： Kono, Junichiro Department of Electrical and Computer Engineering Department of Physics and Astronomy Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

This talk will describe our recent studies of light-matter and matter-matter coupling phenomena in condensed matter in the ultrastrong coupling regime. © IEEE 2022.

ISBN: (纸本)9798350350012

This talk will describe our recent studies of light-matter and matter-matter coupling phenomena in condensed matter in the ultrastrong coupling regime. © IEEE 2022.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Evaluation of time-series database on microservice architecture for health monitoring system

Evaluation of time-series database on microservice architect...

引用

2022 International Symposium on Electronics and Smart Devices, ISESD 2022

作者： Simanjuntak, Eko Surantha, Nico Isa, Sani Muhamad Bina Nusantara University Binus Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia Tokyo City University Electronic and Communication Engineering Faculty of Engineering Department of Electrical Tokyo Japan

ISBN: (数字)9798350396607

ISBN: (纸本)9798350396607

Recently, the research on daily health monitoring using a wearable sensor has been continually evolving. In the future, when this system is actually implemented, a vast amount of data transmission will be conducted from multiple sensors to the cloud server. A system capable of transmitting, storing, processing, and visualizing massive volumes of data is necessary for health monitoring. This research aims to develop a health monitoring system that can accommodate a high amount of data with high performance. The proposed techniques include numerous modifications to system architecture and technology. In the system architecture, a multi-database is proposed to enhance the reliability of the system. As an enhancement to the technology aspect, a time series database and MQTT server are proposed. As the result, the proposed system achieves significantly better performance in terms of throughput, database-writing speed, and database-reading speed compared to the existing system. © 2022 IEEE.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

Boxcar gating for time-resolved mid-infrared photothermal imaging of axon-bundle water boundaries

Boxcar gating for time-resolved mid-infrared photothermal im...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Samolis, Panagis D. Zhu, Xuedong Sander, Michelle Y. Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BrooklineMA02446 United States

ISBN: (纸本)9781957171258

关键词： Infrared devices

来源：评论

学校读者我要写书评

暂无评论

Efficient Automatic External Defibrillator Using the Slope of Hilbert Transformed ECG Signals 11

Efficient Automatic External Defibrillator Using the Slope o...

引用

11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Elsagheer, Samir A. Sayed, Mohammed S. Hassan, Mohsen A. Egypt-Japan University of Science and Technology Computer Science and Information Technology Alexandria21934 Egypt Aswan Universty Facurlty of Engineering Aswan Egypt Egypt-Japan University of Science and Technology Department of Electronics and Communications Engineering Alexandria21934 Egypt Zagazig University Department of Electronics and Communications Engineering Zagazig Egypt Egypt-Japan University of Science and Technology Materials science and engineering program IDE Alexandria21934 Egypt

ISBN: (纸本)9798350369328

Sudden cardiac arrest (SCA) is a life-threatening condition that demands immediate intervention. The key to survival often lies in the timely and precise analysis of electrocardiogram (ECG) signals to determine the necessity of a shock from an Automatic External Defibrillator (AED). In this paper, we address the critical need for improved accuracy in AED decision-making by presenting a novel approach that leverages the Hilbert Transform to calculate the slope of ECG signals by harnessing the analytical power of Hilbert Transformed ECG signals. By scrutinizing the heart's electrical activity through this method, we aim to enhance the AED's ability to differentiate between cases of ventricular fibrillation and other non-shockable rhythms, ultimately leading to more efficient and effective treatment. Our research explores two distinct approaches for signal analysis and correlates their findings to achieve higher precision in defibrillation decisions. To validate the effectiveness of our approach, we employ a diverse and publicly available dataset containing various heart conditions, allowing us to demonstrate the robustness of our method across a wide spectrum of cases. This study represents a significant advancement in the field of automatic external defibrillation, with the potential to save countless lives through more accurate and timely interventions. © 2023 IEEE.

关键词： Defibrillators

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：