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

作者： S. Shreya A. Jenkins T. Böhnert R. Ferreira F. Moradi H. Farkhani Electrical and Computer Engineering Department Aarhus University Aarhus Denmark International Iberian Nanotechnology Laboratory (INL) Braga Portugal

A new paradigm in sensing and communication is emerging with Radio Frequency Identification (RFID), RF detection, object identification, and sensing capabilities for future Internet of Things (IoT) applications, such as automobiles, logistics, healthcare, and smart living. For sensing and detecting the required frequency, complex, large, and highly energy-consuming circuits based on CMOS technologies are required. Hence, here we propose a granular vortex magnetic tunnel junction nano oscillator for a compact and energy- efficient frequency sensing system. The granularity present in the free layer of magnetic tunnel junction (MTJ) allows the identification of the natural frequency of the magnetic vortex core. Our study presents that as soon as the input frequency matches the natural frequency of the vortex core, the impact of grains on the vortex core is nullified. Otherwise, trapping of the vortex core in different grains produces varying output frequencies. The granular effect and the variation of the aspect ratio of the free layer are examined to determine natural frequency of the vortex core. Further, the frequency sensing and detection mechanism for a specific frequency are demonstrated.

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Efficiency Contingency Factors for Commercial EVs Optimal Centralized Charging Stations

Efficiency Contingency Factors for Commercial EVs Optimal Ce...

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IEEE General Meeting Power& Energy Society

作者： Antonio Avila Paras Mandai Department of Electrical and Computer Engineering Power and Renewable Energy Systems (PRES) Lab The University of Texas El Paso TX USA

This paper provides an Optimal Centralized Charging Station (OCCS) mechanism using an Optimal Commercialized Demand Response (OCDR) program coupled with three efficiency contingency factors (i.e., rolling resistance, aerodynamic drag, and traffic flow inertia) that are faced by commercial EVs. Additionally, this paper provides a detailed formulation for the optimal number of level chargers that can accommodate the system of operations for commercial and logistic businesses (CLBs). The methodology proposed contributes to curtail EV charging traffic congestion as well as shedding the load to avoid excess amount of charging loads. In this paper, three contingency factors are thoroughly examined by OCCS combined with OCDR for four case studies: high efficiency contingency, average efficiency contingency, low efficiency contingency, and ideal efficiency case studies. The results of the proposed methodology show an increase OCCS cost by approximately 141% and optimal number of charge level utilized.

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Evaluating Dry Electrodes and Bioinstrumentation for Wearable Arm ECG Acquisition

Evaluating Dry Electrodes and Bioinstrumentation for Wearabl...

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Challenges, Opportunities, Innovations and Applications in Electronic Textiles (E-Textiles), International Conference on the

作者： Suparna Veeturi Vignesh Ravichandran Alex Cerullo Shubham Chomal Yalda Shahriari Stephanie Carreiro Krishna Venkatasubramanian Kunal Mankodiya Dhaval Solanki Department of Electrical Computer and Biomedical Engineering University of Rhode Island USA Department of Emergency Medicine University of Massachusetts Chan Medical School USA Department of Mechanical Industrial and Systems Engineering University of Rhode Island Kingston RI USA Department of Computer Science and Statistics University of Rhode Island USA

ISBN: (数字)9783000804298

ISBN: (纸本)9798331516871

Arm-based electrocardiogram (ECG) offers a more comfortable and user-friendly alternative to traditional chest ECG for wearable cardiac monitoring in daily health applications. However, arm ECG faces challenges such as capturing extremely low-amplitude signals in the microvolt range and significant electromyogram (EMG) noise contamination. The aim of this study was to evaluate the performance of dry electrodes for arm and chest ECG monitoring using gold standard BIOPAC and proposed mDAQ systems. This study consisted of two phases. In Phase 1, we evaluated different dry electrode materials, including silver knit fabric and gold-plated electrodes, with six healthy adult participants ( $\mathrm{N}{=3}$ males and $\mathrm{N}{=3}$ females) having upper arm circumference ranging from 27 to 42 cm. We used a BIOPAC system as a gold standard to collect arm ECG, upper arm EMG, and reference chest ECG during standardized movement tasks. Results showed that silver knit electrodes demonstrated superior QRS energy ${(0.705}\pm {0.151)}$ , surpassing chest gel floating ECG QRS energy ${(0.328}\pm {0.026)}$ , with lower EMG interference across movement conditions. In Phase 2, we developed a bioinstrumentation system (mDAQ) optimized for dry electrodes, demonstrating reliable ECG acquisition in both chest Lead I and arm configurations. -We validated our bioinstrumentation with sixteen healthy adult participants ( $\mathrm{N}{=8}$ male and $\mathrm{N}= \text{female}$ ). The mDAQ system maintained high signal consistency with a skewness effect size of 0.963 and showed a mean heart rate bias of only −1.842 bpm compared to the BIOPAC system, confirming its viability for wearable ECG monitoring applications.

关键词： Electrodes Smart textiles Silver Technological innovation Noise Electrocardiography Reliability engineering Electromyography Biomedical monitoring Monitoring

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Stimulated generation of platicon frequency microcombs and their nonlinear dynamical evolution

Stimulated generation of platicon frequency microcombs and t...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Chu, Allen Liu, Hao Wang, Wenting Huang, Shu-Wei Yu, Mingbin Kwong, Dim-Lee Wong, Chee Wei Fang Lu Mesoscopic Optics and Quantum Electronics Laboratory University of California Los AngelesCA90095 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO United States Institute of Microelectronics A*STAR Singapore117865 Singapore

We generate a square platicon with a 17 ps pulse width and 21% pump-to-comb conversion efficiency in the normal dispersion regime. A 2 ps platicon pulse width can be accessed with auxiliary-laser-assisted thennal stab... 详细信息

ISBN: (纸本)9781957171258

关键词： Conversion efficiency

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Scalable and Independent Learning of Nash Equilibrium Policies in n-Player Stochastic Games with Unknown Independent Chains

arXiv

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arXiv 2023年

作者： Qin, Tiancheng Etesami, S. Rasoul The Department of Industrial and Systems Engineering Department of Electrical and Computer Engineering Coordinated Science Lab University of Illinois Urbana-Champaign UrbanaIL61801 United States

We study a subclass of n-player stochastic games, namely, stochastic games with independent chains and unknown transition matrices. In this class of games, players control their own internal Markov chains whose transitions do not depend on the states/actions of other players. However, players’ decisions are coupled through their payoff functions. We assume players can receive only realizations of their payoffs, and that the players can not observe the states and actions of other players, nor do they know the transition probability matrices of their own Markov chain. Relying on a compact dual formulation of the game based on occupancy measures and the technique of confidence set to maintain high-probability estimates of the unknown transition matrices, we propose a fully decentralized mirror descent algorithm to learn an ϵ-NE for this class of games. The proposed algorithm has the desired properties of independence, scalability, and convergence. Specifically, under no assumptions on the reward functions, we show the proposed algorithm converges in polynomial time in a weaker distance (namely, the averaged Nikaido-Isoda gap) to the set of ϵ-NE policies with arbitrarily high probability. Moreover, assuming the existence of a variationally stable Nash equilibrium policy, we show that the proposed algorithm converges asymptotically to the stable ϵ-NE policy with arbitrarily high probability. In addition to Markov potential games and linear-quadratic stochastic games, this work provides another subclass of n-player stochastic games that, under some mild assumptions, admit polynomial-time learning algorithms for finding their stationary ϵ-NE policies. Copyright © 2023, The Authors. All rights reserved.

关键词： Mirrors

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3D Tracking of Multiple Drones Based on Particle Swarm Optimization 23rd

3D Tracking of Multiple Drones Based on Particle Swarm Opt...

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23rd International Conference on Computational Science, ICCS 2023

作者： Krzeszowski, Tomasz Switonski, Adam Zielinski, Michal Wojciechowski, Konrad Rosner, Jakub Faculty of Electrical and Computer Engineering Rzeszow University of Technology al. Powstancow Warszawy 12 Rzeszow35-959 Poland Department of Computer Graphics Vision and Digital Systems Silesian University of Technology ul. Akademicka 16 Gliwice44-100 Poland Polish-Japanese Academy of Information Technology ul. Koszykowa 86 Warsaw02-008 Poland

ISBN: (纸本)9783031360268

This paper presents a method for the tracking of multiple drones in three-dimensional space based on data from a multi-camera system. It uses the Particle Swarm Optimization (PSO) algorithm and methods for background/foreground detection. In order to evaluate the developed tracking algorithm, the dataset consisting of three simulation sequences and two real ones was prepared. The sequences contain from one to ten drones moving with different flight patterns. The simulation sequences were created using the Unreal Engine and the AirSim plugin, whereas the real sequences were registered in the Human Motion Lab at the Polish-Japanese Academy of Information Technology. The lab is equipped with the Vicon motion capture system, which was used to acquire ground truth data. The conducted experiments show the high efficiency and accuracy of the proposed method. For the simulation data, tracking errors from 0.086 m to 0.197 m were obtained, while for real data, the error was 0.101–0.124 m. The system was developed for augmented reality applications, especially games. The dataset is available at http://***/drones/. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Drones

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Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning(RAPID)

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eLight 2023年第1期3卷 198-210页

作者： Ziling Wu Iksung Kang Yudong Yao Yi Jiang Junjing Deng Jeffrey Klug Stefan Vogt George Barbastathis Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Argonne National Laboratory LemontIL 60439USA Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 138602Singapore Present Address:Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 138602Singapore Present Address:University of California BerkeleyCA 94720USA

X-ray ptychographic tomography is a nondestructive method for three dimensional(3D)imaging with nanometer-sized resolvable *** size of the volume that can be imaged is almost arbitrary,limited only by the penetration depth and the available scanning *** we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned *** proposed 3D reconstruction method“RAPID”relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground *** is then trained to reproduce equal fidelity from much fewer *** training,it performs with similar fidelity on the hitherto unexamined portions of the object,previously not shown during training,with a limited set of *** our experimental demonstration,the nominal number of angles was 349 and the reduced number of angles was 21,resulting in a×140 aggregate speedup over a volume of 4.48×93.18×3.92μm^(3) and with(14 nm)^(3) feature size,i.e.-10^(8) ***’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic *** found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

关键词： X-ray ptychographic tomography Deep learning Reduced-angle Rapid imaging Atrous spatial pyramid pooling Anisotropic

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A Measurement-Referenced Error Vector Magnitude for Counterfeit Cellular Device Detection

A Measurement-Referenced Error Vector Magnitude for Counterf...

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ARFTG Conference

作者： Améya S Ramadurgakar Kate A Remley Dylan F Williams Jacob D Rezac Melinda Piket-May Robert D Horansky Department of Electrical Computer and Energy Engineering University of Colorado Boulder Communications Technology Laboratory National Institute of Standards and Technology

Standard formulations of error vector magnitude compare a wireless device's symbol constellation to an ideal reference constellation. In this work, we utilize the residual error vector magnitude, which uses measurements of a wireless device to define a reference constellation. We apply this formulation to the problem of identifying a device's manufacturer from over-the-air measurements of the wireless device and show that the residual error vector magnitude outperforms standard error vector magnitude formulation in this task.

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Interconnectedness of Circular Economy, Artificial Intelligence and Vertical Farming as a Technosignature Model for Sustainable Space Food Production 15

Interconnectedness of Circular Economy, Artificial Intellige...

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15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Ii, Ronnie Concepcion Cabaccan, Carlo Ducut, Jullian Dominic Relano, R-Jay Alejandrino, Jonnel Agulto, Ronnel Bandala, Argel Mohamad, Roslina Dadios, Elmer Culaba, Alvin Department of Manufacturing Engineering and Management De la Salle University Manila Philippines De la Salle University Center for Engineering and Sustainability Development Research Intelligent Systems Research Unit Manila Philippines De la Salle University Bio-energy Environment and Renewables Laboratory Center for Engineering and Sustainability Development Research Manila Philippines Plant and Soil Health Research Unit Center for Natural Sciences and Environmental Research De la Salle University Manila Philippines School of Electrical Electronics and Computer Engineering Mapua University Manila Philippines School of Electrical Engineering College of Engineering Universiti Teknologi Mara Shah Alam Malaysia De la Salle University Department of Electronics and Computer Engineering Manila Philippines De la Salle University Department of Mechanical Engineering Manila Philippines

ISBN: (纸本)9798350381177

The degradation of Earth's natural resources and environmental health due to improper anthropological activities, mainly through unoptimized food production, is manifested through climate change that negatively alters the productivity in the agricultural sector. Because of this challenge in open terrestrial agriculture, the concept of space farming is believed to be significant in delivering fresh and quality food for the people on top of providing for astronauts and making them healthy in space. However, another problem emerges in the view of circular economy (CE) which is a production and consumption idealism that avoids degradation of natural resources and environment in producing one food unit and despite the collaborative advances in space technology, particularly in astrobotany, the materialization of CE and the absolutism of artificial intelligence (AI) are still partly imaginary. This study employed a bibliometric, scientometric and systematic analysis to highlight the advantages, limitations, and connections of CE, AI, and vertical farming (VF) which led to establishing a technosignature model for sustainable space food production. Here, CE, AI and VF were singularized as a model for sustainable space food production and identified their potential interplay. Based on scientific correlations, it is undoubtedly true that CE, AI, and VF have existing mutualism in Earth-based systems, but the degree of its importance as a whole is not yet completely appreciated for space farming. The developed CE-AI-VF technosignature model is scalable and adaptable if the government and scientific community put it into action accompanied by science policies. © 2023 IEEE.

关键词： Climate change

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Edge Deployment of Vision-Based Model for Human Following Robot

Edge Deployment of Vision-Based Model for Human Following Ro...

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International Conference on Control, Automation and systems ( ICCAS)

作者： Sumaira Manzoor Eun-jin Kim Sang-Hyeon Bae Tae-Yong Kuc Creative Algorithms and Sensor Evolution Laboratory Suwon Korea Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea

Mobile robots are proliferating at a significant pace and the continuous interaction between humans and robots opens the doors to facilitate our daily life activities. Following the target person with the robot is an important human-robot interaction (HRI) task that leads to its applications in industrial, domestic, and medical assistant robots. To implement the robotic tasks, traditional solutions rely on cloud servers that cause significant communication overhead due to data offloading. In our work, we overcome this potential issue of cloud-based solutions, by implementing the task of a hum-following robot (HFR) at the Nvidia Jetson Xavier NX edge platform. To perform the HFR task, typical approaches track the target person only from behind. While, our work allows the robot to track the person from behind, front, and side views (left & right). In this article, we combine the latest advances of deep learning and metric learning by presenting two trackers: Single Person Head Detection-based Tracking (SPHDT) model and Single Person full-Body Detection-based Tracking (SPBDT) model. For both models, we leverage a deep learning-based single object detector called MobileNetSSD with a metric learning-based re-identification model, DaSiamRPN. We perform the qualitative analysis considering six major environmental factors: pose change, illumination variations, partial occlusion, full occlusion, wall corner, and different viewing angles. Based on the better performance of SPBDT, compared to SPHDT in the experimental results, we select SPBDT model for the robot to track the target. We also use this vision model to provide the relative position, location, distance, and angle of the target person to control the robot's movement for performing the human-following task.

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