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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Ding, Jinliang Cao, Ming Johansson, Karl H. Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201800 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint violation, existing distributed bandit online algorithms solving this problem directly use the clipped constraint function to replace its original constraint function. However, the use of the clipping operation renders Slater’s condition (i.e, there exists a point that strictly satisfies the inequality constraints at all iterations) ineffective to achieve reduced network cumulative constraint violation. To tackle this challenge, we propose a new distributed bandit online primal–dual algorithm. If local loss functions are convex, we show that the proposed algorithm establishes an O(T max{c,1−c})network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the total number of iterations and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds, the network cumulative constraint violation bound is reduced to O(T 1−c). In addition, if local loss functions are strongly convex, for the case where strongly convex parameters are unknown, the network regret bound is reduced to O(T1−c), and the network cumulative constraint violation bound is O(T1−c/2) and O(T1−c) without and with Slater’s condition, respectively. For the case where strongly convex parameters are known, the network regret bound is further reduced to O)(log(T)), and the network cumulative constraint violation bound is reduced to O(log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is among the first to establish reduced (network) cumulative constraint violation bounds for (distributed) bandit convex optimization with time-varying constraints under Slater’s condition. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2

关键词： Convex optimization

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Impact of External Magnetic Fields on STT-MRAM: An Application Note

IEEE Electron Devices Magazine

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IEEE Electron Devices Magazine 2024年第3期2卷 52-59页

作者： Bernard Dieny Sanjeev Aggarwal Vinayak Bharat Naik Sebastien Couet Thomas Coughlin Shunsuke Fukami Kevin Garello Jack Guedj Jean Anne C. Incorvia Laurent Lebrun Kyung-Jin Lee Daniele Leonelli Yonghwan Noh Siamak Salimy Steven Soss Luc Thomas Weigang Wang Daniel C. Worledge SPINTEC UGA/CEA/CNRS Grenoble France Everspin Technologies Chandler AZ USA GlobalFoundries Malta NY USA Imec Leuven Belgium Coughlin Associates Atascadero CA USA Tohoku University Sendai Japan NUMEM Sunnyvale CA USA Department of Electrical and Computer Engineering University of Texas at Austin Austin TX USA HPROBE Eybens France Department of Physics Korea Advanced Institute of Science and Technology (KAIST) Daejeon Korea Huawei Technologies R&D Belgium N.V. Leuven Belgium Netsol Hwaseong-si Gyeonggi-do Republic of Korea Applied Materials Santa Clara CA USA Department of Physics and Department of Electrical & Computer Engineering University of Arizona Tucson AZ USA IBM San Jose CA USA

This application note discusses the working principle of spin-transfer torque magnetoresistive random access memory (STT-MRAM) and the impact that magnetic fields can have on STT-MRAM operation. Sources of magnetic fi... 详细信息

关键词： Torque Millimeter wave devices Magnetoresistive devices Random access memory Permanent magnets Magnetic fields Magnetoresistance Probes Standards Magnetic shielding

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User Power Measurement Based IRS Channel Estimation via Single-Layer Neural Network

arXiv

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arXiv 2023年

作者： Sun, He Mei, Weidong Zhu, Lipeng Zhang, Rui Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore School of Science and Engineering Shenzhen Research Institute of Big Data China Chinese University of Hong Kong Guangdong Shenzhen518172 China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China 611731 China

One main challenge for implementing intelligent reflecting surface (IRS) aided communications lies in the difficulty to obtain the channel knowledge for the base station (BS)-IRS-user cascaded links, which is needed to design high-performance IRS reflection in practice. Traditional methods for estimating IRS cascaded channels are usually based on the additional pilot signals received at the BS/users, which increase the system training overhead and also may not be compatible with the current communication protocols. To tackle this challenge, we propose in this paper a new single-layer neural network (NN)-enabled IRS channel estimation method based on only the knowledge of users’ individual received signal power measurements corresponding to different IRS random training reflections, which are easily accessible in current wireless systems. To evaluate the effectiveness of the proposed channel estimation method, we design the IRS reflection for data transmission based on the estimated cascaded channels in an IRS-aided multiuser communication system. Numerical results show that the proposed IRS channel estimation and reflection design can significantly improve the minimum received signal-to-noise ratio (SNR) among all users, as compared to existing power measurement based designs. © 2023, CC BY.

关键词： Channel estimation

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Ameliorated Golden Jackal Optimization (Agjo) with Enhanced Movement and Multi-Angle Position Updating Strategy

SSRN

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SSRN 2023年

作者： Wahab, Magd Abdel Bai, Jianfu Khatir, Samir Abualigah, Laith Soete Laboratory Department of Electrical Energy Metals Mechanical Constructions and Systems Faculty of Engineering and Architecture Ghent University Belgium Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al al-Bayt University Mafraq25113 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia College of Engineering Yuan Ze University Taiwan

Golden jackal optimization (GJO), a lately published meta-heuristic optimization algorithm, is inspired by the foraging behavior of pairs of golden jackals and shows an acceptable optimization performance. However, GJO exists a shortage in balancing exploration and exploitation, as it completely focused on exploitation in the later iterations. This study proposes a new variant of GJO, named Ameliorated Golden jackal optimization (AGJO). AGJO uses three strategies to alleviate the imbalance between the exploration and exploitation of GJO: the enhanced movement strategy, the global search strategy, and the multi-angle position update strategy for prey. An environmental disturbance factor is added to the third strategy to strengthen GJO's ability to evade the local optimal solution. The performance of AGJO is tested and compared with GJO and seven well-known meta-heuristic algorithms for 23 classical benchmark functions, CEC 2017 and CEC 2019. These results determined that AGJO performs better over 90% of these functions compared to GJO. AGJO is also highly competitive in terms of optimization capability and convergence speed compared with other algorithms. Finally, AGJO is applied to optimize five engineering design problems with constraints. Results show that AGJO is a more potential algorithm for solving real problems with constraints than GJO and other algorithms. © 2023, The Authors. All rights reserved.

关键词： Optimization

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Mid-Wave Infrared Black Phosphorus Photodetector Enhanced by an Integrated Metasurface Grating

Mid-Wave Infrared Black Phosphorus Photodetector Enhanced by...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Max R. Lien Nan Wang Jiangbin Wu Alexander Soibel Sarath D. Gunapala Han Wang Michelle L. Povinelli Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA USA Mork Family Department of Chemical Engineering & Materials Science University of Southern California Los Angeles CA USA Jet Propulsion Laboratory California Institute of Technology Pasadena California USA

We designed, fabricated, and characterized mid-wave infrared black phosphorus photodetectors with integrated metal-insulator-metal metasurface gratings. We show that our metasurface grating increases responsivity by ~... 详细信息

ISBN: (纸本)9781957171258

关键词： Absorption spectroscopy Electric fields Infrared astronomy Photodetectors Remote sensing Resonant modes

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Hybrid metaphotonics for fast and efficient collection of photons from quantum emitters

Hybrid metaphotonics for fast and efficient collection of ph...

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Flat Optics: Components to Systems, FLATOPTICS 2021 - Part of OSA Optical Design and Fabrication 2021

作者： Jha, Pankaj K. Yang, Frank Akbari, Hamidreza Bauser, Haley Atwater, Harry A. Thomas J. Watson Laboratory of Applied Physics and Materials Science California Institute of Technology PasadenaCA91125 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States

We propose a hybrid nanophotonic device which enables faster emission and efficient collection of photons from quantum emitters in hexagonal Boron Nitride. Our proposal offers a modular platform for on chip quantum ph... 详细信息

ISBN: (纸本)9781557528209

关键词： Photons

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Using Aerial Videos for Natural Disaster Damage Assessment

Using Aerial Videos for Natural Disaster Damage Assessment

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International Youth Conference on Radio Electronics, electrical and Power engineering (REEPE)

作者： Moez Krichen Mohamed S. Abdalzaher Mostafa Shaaban Raafat Aburukba Al-Baha University Al-Baha Saudi Arabia ReD CAD Laboratory University of Sfax Sfax Tunisia Electrical Engineering Department American University of Sharjah Sharjah UAE Seismology Department National Research Institute of Astronomy and Geophysics Cairo Egypt Energy Water and Sustainable Environment Research Center American University of Sharjah Computer Science and Engineering Department American University of Sharjah Sharjah UAE

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Rapid damage assessment is crucial in the aftermath of natural disasters, enabling emergency responders to efficiently allocate resources and facilitate recovery efforts. This paper investigates the potential of utilizing satellite imagery and drone (UAV) technology to enhance the speed and accuracy of disaster damage assessment. We explore the various applications of satellite imagery, from pre-disaster risk assessment to post-disaster situational awareness and reconstruction monitoring. The advantages of UAV-captured data for detailed, on-the-ground damage evaluation are also discussed. The paper then delves into the role of advanced analytics, such as convolutional neural networks (CNNs) and semantic segmentation, in automating the analysis of satellite and UAV imagery for rapid damage mapping and classification. Additionally, we highlight the value of integrating crowdsourced data with remote sensing inputs to further improve situational awareness and damage reporting. The paper also examines the use of 3- D reconstruction techniques that leverage multiple data sources to create detailed models for damage assessment and recovery planning. By synthesizing the latest advancements in satellite technology, drone capabilities, and artificial intelligence, this paper presents a comprehensive framework for leveraging these tools to enable more effective and efficient disaster response and recovery operations. The findings and recommendations outlined in this work can inform both academic research and practical applications in the field of disaster management.

关键词： Disasters Soft sensors Semantic segmentation Disaster management Autonomous aerial vehicles Satellite images Resource management Remote sensing Image reconstruction Resilience

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An Insight Into Neurodegeneration: Harnessing Functional MRI Connectivity in the Diagnosis of Mild Cognitive Impairment

An Insight Into Neurodegeneration: Harnessing Functional MRI...

引用

17th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2024

作者： Han, Shuning Sun, Zhe Zhao, Kanhao Duan, Feng Caiafa, Cesar F. Zhang, Yu Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Catalonia Vic08500 Spain Image Processing Research Group RIKEN Center for Advanced Photonics Riken Saitama Wako-Shi Japan Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Bioengineering Lehigh University BethlehemPA18015 United States Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Instituto Argentino de Radioastronomía-CCT La Plata CONICET/ CIC-PBA/ UNLP V. Elisa 1894 Argentina Department of Electrical and Computer Engineering Lehigh University BethlehemPA18015 United States Department of Psychiatry University of Cambridge CambridgeCB20SZ United Kingdom

Alzheimer’s disease is a progressive form of memory loss that worsens over time. Detecting it early, when memory issues are mild, is crucial for effective interventions. Recent advancements in computer technology, specifically Graph Convolutional Networks (GCNs), have proven to be powerful tools for analyzing Magnetic Resonance Imaging (MRI) data comprehensively. In this study, we developed a GCN framework for diagnosing mild cognitive impairment (MCI) by examining the functional connectivity (FC) derived from resting-state functional MRI (rfMRI) data. Our research systematically explored various types and processing methods of FC, evaluating their performance on the OASIS-3 dataset. The experimental results revealed several key findings. On the one hand, the proposed GCN exhibited significantly superior performance over both the baseline GCN and the Support Vector Machine (SVM) models, with statistically significant differences. It attained the highest average accuracy of 80.3% and a peak accuracy of 88.2%. On the other hand, the GCN frame work obtained using individual FCs showed overall slightly better performance than the one using global FCs. However, it is important to note that GCNs using global networks with appropriate connectivity can achieve comparable or even better performance than individual networks in certain cases. Finally, our results also indicate that the connectivity within specific brain regions, such as VIS, DMN, SMN, VAN, and FPC, may play a more significant role in GCN-based MRI classification for MCI diagnosis. These findings significantly contribute to the understanding of neurodegenerative disorders and offer valuable insights into the diverse ap plications of GCNs in brain analysis and disease detection. © 2024 by SCITEPRESS– science and Technology Publications, Lda.

关键词： Neurodegenerative diseases

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Enhancing Flexibility of Smart Bioresorbable Vascular Scaffolds Through 3d Printing Using Polycaprolactone and Polylactic Acid

SSRN

引用

SSRN 2024年

作者： Wei, Jinlian Oyunbaatar, Nomin-Erdene Jeong, Yun-Jin Park, Jongsung Kim, Su-Hwan Kwon, Kyeongha Lee, Heonzoo Won, Yonggwan Kim, Dong-Su Lee, Dong-Weon School of Mechanical Engineering Chonnam National University Gwangju61186 Korea Republic of Department of Automatic System Chosun College of Science & Technology Gwangju61453 Korea Republic of Department of Precision Mechanical Engineering Kyungpook National University Gyeongsangbuk-do Sangju37224 Korea Republic of School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Intelligent Electronics and Computer Engineering Chonnam National University Gwangju61186 Korea Republic of Gwangju61012 Korea Republic of

With the growing use of stent implantations, the risk of in-stent restenosis represents a major concern for cardiovascular patients. Herein, we propose a hybrid bioresorbable vascular scaffold (H-BVS) integrated with a wireless sensor that could enable significant advances in cardiovascular therapeutics. The H-BVS was manufactured using a state-of-the-art customized 3D printer equipped with dual nozzles to ensure a synergistic combination of polycaprolactone and polylactic acid. Moreover, the H-BVS was integrated with a wireless, battery-less LC-type pressure sensor for real-time monitoring of in-stent restenosis. This wireless sensor was meticulously connected with the H-BVS framework through engineered microstructures, which not only ensured a robust bond but also significantly enhanced the overall integrity and functionality of the device. Furthermore, the combination of the H-BVS and sensor was optimized to exhibit superior bending flexibility and radial strength, which are key factors in ensuring effectiveness and patient safety. The feasibility of the smart H-BVS (SH-BVS) was verified through comprehensive testing within a phantom system designed to simulate real blood flow conditions. We believe that the potential of the SH-BVS system to revolutionize patient monitoring and treatment strategies in the cardiovascular healthcare domain cannot be overstated. © 2024, The Authors. All rights reserved.

关键词： Biodegradable polymers

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Refractive Index Sensor Based on Long-Range Surface Plasmon Polariton Waveguide 1

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8th International Multidisciplinary Conference on Optofluidics, IMCO 2018 and 9th International Multidisciplinary Conference on Optofluidics, IMCO 2019

作者： Sun, Xiaoqiang Xu, Yan Berini, Pierre Zhang, Daming State Key Laboratory of Integrated Optoelectronics College of Electronic Science and Engineering Jilin University Changchun China School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada Centre for Research in Photonics University of Ottawa Ottawa Canada Department of Physics University of Ottawa Ottawa Canada

ISBN: (数字)9789811333811

ISBN: (纸本)9789811333804

Straight long-range surface plasmon polariton (LRSPP) waveguides are demonstrated as liquid refractive index (RI) sensors (Barnes et al. in Nat Mater 424:824–830, 2003, [1]). The sensors consist of 5 μm-wide, 20 nm-thick straight Au stripes that are embedded in ultraviolet (UV) sensitive polymer SU-8. The double layer liftoff fabrication is adopted to fabricate the embedded rectangular and smooth Au stripes. An etched microfluidic channel allows the contact of analyte to Au surface for RI detection. Within the range from 1.576 to 1.596, a sensitivity of 821 dB/RIU can be obtained. The proposed device has potentials in the portable and compact refractometer application. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Refractometers

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