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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Hao Wu Hantao Zhang Baomin Wang Yaqin Guo Ran Cheng Kang L. Wang Songshan Lake Materials Laboratory Dongguan China Department of Electrical and Computer Engineering University of California Los Angeles CA USA Department of Electrical and Computer Engineering University of California Riverside CA USA School of Physical Science and Technology Ningbo University Ningbo China CAS Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

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 10 6 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.

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Graph Coordinates and Conventional Neural Networks - An Alternative for Graph Neural Networks

Graph Coordinates and Conventional Neural Networks - An Alte...

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IEEE International Conference on Big Data

作者： Zheyi Qin Randy Paffenroth Anura P. Jayasumana Electrical and Computer Engineering Colorado State University Fort Collins USA Department of Data Science Program Worcester Polytechnic Institute Worcester MA USA

Graph-based data present unique challenges and opportunities for machine learning. Graph Neural Networks (GNNs), and especially those algorithms that capture graph topology through message passing for neighborhood aggregation, have been a leading solution. However, these networks often require substantial computational resources and may not optimally leverage the information contained in the graph’s topology, particularly for large-scale or complex *** propose Topology Coordinate Neural Network (TCNN) and Directional Virtual Coordinate Neural Network (DVCNN) as novel and efficient alternatives to message passing GNNs, that directly leverage the graph’s topology, sidestepping the computational challenges presented by competing algorithms. Our proposed methods can be viewed as a reprise of classic techniques for graph embedding for neural network feature engineering, but they are novel in that our embedding techniques leverage ideas in Graph Coordinates (GC) that are lacking in current *** results, benchmarked against the Open Graph Benchmark Leaderboard, demonstrate that TCNN and DVCNN achieve competitive or superior performance to message passing GNNs. For similar levels of accuracy and ROC-AUC, TCNN and DVCNN need far fewer trainable parameters than contenders of the OGBN Leaderboard. The proposed TCNN architecture requires fewer parameters than any neural network method currently listed in the OGBN Leaderboard for both OGBN-Proteins and OGBN-Products datasets. Conversely, our methods achieve higher performance for a similar number of trainable parameters. These results hold across diverse datasets and edge features, underscoring the robustness and generalizability of our methods. By providing an efficient and effective alternative to message passing GNNs, our work expands the toolbox of techniques for graph-based machine learning. A significantly lower number of tunable parameters for a given evaluation metric makes TCNN and DVCNN especiall

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Supersymmetric Microring Laser Arrays in Higher-Dimensional Space

Supersymmetric Microring Laser Arrays in Higher-Dimensional ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Xingdu Qiao Bikashkali Midya Zihe Gao Zhifeng Zhang Haoqi Zhao Tianwei Wu Jieun Yim Ritesh Agarwal Natalia M. Litchinitser Liang Feng Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia USA Department of Materials Science and Engineering University of Pennsylvania Philadelphia USA Department of Electrical and Computer Engineering Duke University Durham USA

To achieve single fundamental supermode operation in coupled arrays, a two-dimensional supersymmetry formalism for mode control is developed and experimentally demonstrated with microring laser arrays.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Electric potential Three-dimensional displays Power lasers Aerospace electronics Laser modes Laser applications Electrooptical waveguides

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Ultrathin-shell epitaxial Ag@Au core-shell nanowires for high-performance and chemically-stable electronic, optical, and mechanical devices

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Nano Research 2021年第11期14卷 4294-4303页

作者： Yangzhi Zhu Sanggon Kim Xuezhi Ma Peter Byrley Ning Yu Qiushi Liu Xiaoming Sun Da Xu Sangshan Peng Martin C.Hartel Shiming Zhang Vadim Jucaud Mehmet R.Dokmeci Ali Khademhosseini Ruoxue Yan Department of Chemical and Environmental Engineering Bourns College of EngineeringUniversity of California-RiversideRiversideCA92521USA Terasaki Institute for Biomedical Innovation Los AngelesCA90064USA Department of Electrical and Computer Engineering University of California-RiversideRiversideCA92521USA State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical TechnologyBeijing100029China State Key Laboratory of Chemo/Biosensing and Chemometrics College of Chemistry and Chemical EngineeringHunan UniversityChangsha410082China Department of Bioengineering University of California-Los AngelesLos AngelesCA90095USA Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Material Science and Engineering Program University of California-RiversideRiversideCA92521USA

Silver nanowires (AgNWs) hold great promise for applications in wearable electronics, flexible solar cells, chemical and biological sensors, photonic/plasmonic circuits, and scanning probe microscopy (SPM) due to their unique plasmonic, mechanical, and electronic properties. However, the lifetime, reliability, and operating conditions of AgNW-based devices are significantly restricted by their poor chemical stability, limiting their commercial potentials. Therefore, it is crucial to create a reliable oxidation barrier on AgNWs that provides long-term chemical stability to various optical, electrical, and mechanical devices while maintaining their high performance. Here we report a room-temperature solution-phase approach to grow an ultra-thin, epitaxial gold coating on AgNWs to effectively shield the Ag surface from environmental oxidation. The Ag@Au core-shell nanowires (Ag@Au NWs) remain stable in air for over six months, under elevated temperature and humidity (80 °C and 100% humidity) for twelve weeks, in physiological buffer solutions for three weeks, and can survive overnight treatment of an oxidative solution (2% H2O2). The Ag@Au core-shell NWs demonstrated comparable performance as pristine AgNWs in various electronic, optical, and mechanical devices, such as transparent mesh electrodes, surface-enhanced Raman spectroscopy (SERS) substrates, plasmonic waveguides, plasmonic nanofocusing probes, and high-aspect-ratio, high-resolution atomic force microscopy (AFM) probes. These Au@Ag core-shell NWs offer a universal solution towards chemically-stable AgNW-based devices without compromising material property or device performance.

关键词： epitaxial growth core-shell nanowire plasmonic waveguides atomic force microscopy(AFM)probe transparent electrode wearable electronics

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Leveraging Voltage-Controlled Magnetic Anisotropy to Solve Sneak Path Issues in Crossbar Arrays

arXiv

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arXiv 2022年

作者： Yang, Kezhou Sengupta, Abhronil The Department of Materials Science and Engineering School of Electrical Engineering and Computer Science The Pennsylvania State University University ParkPA16802 United States

In crossbar array structures, which serves as an "In-Memory" compute engine for Artificial Intelligence hardware, write sneak path problem causes undesired switching of devices that degrades network accuracy. While custom crossbar programming schemes have been proposed, device level innovations leveraging non-linear switching characteristics of the crosspoint devices are still under exploration to improve the energy efficiency of the write process. In this work, a spintronic device design based on Magnetic Tunnel Junction (MTJ) exploiting the use of voltage-controlled magnetic anisotropy (VCMA) effect is proposed as a solution to the write sneak path problem. Additionally, insights are provided regarding appropriate operating voltage conditions to preserve the robustness of the magnetization trajectory during switching which is critical for proper switching probability manipulation. © 2022, CC BY.

关键词： Magnetic anisotropy

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Integrated proteomic profiling identifies amino acids selectively cytotoxic to pancreatic cancer cells

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The Innovation 2024年第3期5卷 138-145页

作者： Alfred Akinlalu Zachariah Flaten Komila Rasuleva Md Saimon Mia Aaron Bauer Santhalingam Elamurugan Nega Ejjigu Sudipa Maity Amara Arshad Min Wu Wenjie Xia Jia Fan Ang Guo Sijo Mathew Dali Sun Department of Electrical and Computer Engineering University of Denver2155 E Wesley AvenueDenverCO 80210USA Biomedical Engineering Program North Dakota State University1401 Centennial BoulevardEngineering AdministrationRoom 203FargoND 58102USA Department of Pharmaceutical Sciences School of PharmacyNorth Dakota State University1001 S.1401 Albrecht Boulevard Sudro HallFargoND 58102USA Materials and Nanotechnology Program North Dakota State University1410 North 14th AvenueCIE 201FargoND 58102USA Wenzhou Institute University of Chinese Academy of SciencesWenzhouZhejiang 325000China Department of Aerospace Engineering Iowa State UniversityAmesIA 50011USA Center for Cellular and Molecular Diagnostics Tulane University School of Medicine1430 Tulane AvenueNew OrleansLA 70112USA Department of Biochemistry and Molecular Biology Tulane University School of Medicine1430 Tulane AvenueNew OrleansLA 70112USA Knoebel Institute for Healthy Aging University of Denver2155 E Wesley AvenueDenverCO 80210USA

Pancreatic adenocarcinoma(PDAC)is one of the most deadly cancers,characterized by extremely limited therapeutic options and a poor prognosis,as it is often diagnosed during late disease *** and selective treatments are urgently needed,since current therapies have limited efficacy and significant side *** proteomics analysis of extracellular vesicles,we discovered an imbalanced distribution of amino acids secreted by PDAC tumor *** findings revealed that PDAC cells preferentially excrete proteins with certain preferential amino acids,including isoleucine and histidine,via extracellular *** amino acids are associated with disease progression and can be targeted to elicit selective toxicity to PDAC tumor *** in vitro and in vivo experiments demonstrated that supplementation with these specific amino acids effectively eradicated PDAC ***,we also identified XRN1 as a potential target for these amino *** high selectivity of this treatment method allows for specific targeting of tumor metabolism with very low toxicity to normal ***,we found this treatment approach is easy-to-administer and with sustained tumor-killing ***,our findings reveal that exocytosed amino acids may serve as therapeutic targets for designing treatments of intractable PDAC and potentially offer alternative treatments for other types of cancers.

关键词： finding identif selectivity

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Investigating the Impact of Data Augmentation for Fine-Grained Grocery Product Classification Based on Vision Transformer

Investigating the Impact of Data Augmentation for Fine-Grain...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Rissa Rahmania Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Group (CEG) Faculty of Engineering Universitas Katolik Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

The existence of fine-grained image classification supporting smart retail provides effectiveness in recognizing products with high similarity. However, the generic classification method performs poorly in identifying products from a subordinate category. This paper aims to identify augmentation techniques to leverage the Vision Transformer (ViT) model to classify the fine-grained grocery product, which involves embedding patches and transformer encoders to extract the main features. First, we develop a fine-grained image dataset with ColorJitter, CutOut, and combining both augmentations. Secondly, we perform experiments and analysis of ViT size, embedded patch size and image size in the patch embedding process. Lastly, the ViT model are evaluated according to the image sizes 224, 384, and 512 in accuracy, loss, and confusion matrix. The highest accuracy was obtained at 0.9922. The ColorJitter and CutOut improved the confusion matrix in ViT-B/16 and ViT-L/16 with an image size of 384 and 512. The results show that both augmentations in the ViT model are able to distinguish fine-grained grocery products.

关键词： Surveys computer vision Accuracy Image recognition Transformers Feature extraction Data augmentation Artificial intelligence Image classification

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A New Efficient Grain Growth Model Using a Random Gaussian-Sampled Mode Filter

SSRN

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SSRN 2023年

作者： Melville, Joseph Fremont Yadav, Vishal Yang, Lin Krause, Amanda R. Tonks, Michael R. Harley, Joel B. Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Department of Materials Science and Engineering University of Florida GainesvilleFL32611 United States University of Florida United States

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model anisotropic grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operations. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction. © 2023, The Authors. All rights reserved.

关键词： Anisotropy

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An ab initio framework for understanding and controlling quantum fluctuations in complex light-matter systems

An ab initio framework for understanding and controlling qua...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Rivera, Nicholas Uddin, Shiekh Zia Seyler, Devin Salamin, Yannick Sloan, Jamison Roques-Carmes, Charles Xu, Shutao Sander, Michelle Soljacic, Marin Department of Physics Harvard University CambridgeMA02138 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States E.L. Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BrooklineMA02446 United States Department of Biomedical Engineering Boston University BostonMA02215 United States

We develop a new general theory of quantum noise in photonics. As an example, we demonstrate strong quantum correlations and squeezing in supercontinuum generation. Our results enable overcoming quantum noise limits i... 详细信息

ISBN: (纸本)9781957171395

关键词： Supercontinuum generation

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Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Jamalipour, Abbas Mao, Shiwen Kim, Dong In The College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Auburn University Auburn United States The School of Electrical and Computer Engineering University of Sydney Australia The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

In the digital transformation era, Metaverse offers a fusion of virtual reality (VR), augmented reality (AR), and web technologies to create immersive digital experiences. However, the evolution of the Metaverse is slowed down by the challenges of content creation, scalability, and dynamic user interaction. Our study investigates an integration of Mixture of Experts (MoE) models with Generative Artificial Intelligence (GAI) for mobile edge computing to revolutionize content creation and interaction in the Metaverse. Specifically, we harness an MoE model's ability to efficiently manage complex data and complex tasks by dynamically selecting the most relevant experts running various sub-models to enhance the capabilities of GAI. We then present a novel framework that improves video content generation quality and consistency, and demonstrate its application through case studies. Our findings underscore the efficacy of MoE and GAI integration to redefine virtual experiences by offering a scalable, efficient pathway to harvest the Metaverse's full potential. © 2024, CC BY.

关键词： Augmented reality

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