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2022 IEEE Symposium on VLSI Technology and Circuits, VLSI Technology and Circuits 2022

作者： Hong, Ming-Chun Chang, Yao-Jen Hsin, Yu-Chen Liu, Liang-Ming Chen, Kuan-Ming Su, Yi-Hui Chen, Guan-Long Yang, Shan-Yi Wang, I-Jung Rahaman, Sk Ziaur Lee, Hsin-Han Chiu, Shih-Ching Shih, Chen-Yi Wang, Chih-Yao Chen, Fang-Ming Wei, Jeng-Hua Sheu, Shyh-Shyuan Lo, Wei-Chung Lin, Minn-Tsong Wu, Chih-I Hou, Tuo-Hung Industrial Technology Research Institute Electronic and Optoelectronic System Research Laboratories Hsinchu Taiwan National Yang Ming Chiao Tung University Department of Electrical Engineering and Institute of Electronics Hsinchu Taiwan Graduate Institute of Photonics and Optoelectronics Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Physics National Taiwan University Taipei Taiwan

ISBN: (纸本)9781665497725

A universal MRAM technology is proposed to fulfill versatile applications ranging from quantum computing to automotive electronics across a wide operating temperature range of 4K to 400K. An ultrathin (1.4 nm) CoFeB composite free layer with an Mg spacer is designed to enlarge breakdown voltage and write margin, decrease switching current, and maintain thermal stability and magnetoresistance ratio at all temperatures. High endurance (>1011) and excellent reliability (write margin > 0.4 V) are achieved from 4K to 400K without compromising speed (10 ns) and retention (10 years at 300K). © 2022 IEEE.

关键词： Temperature

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Tuning Key Parameters of Electric Circuit Model for Application in Solid-State Supercapacitors 7

Tuning Key Parameters of Electric Circuit Model for Applicat...

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7th International Symposium on Instrumentation Systems, Circuits and Transducers, INSCIT 2023

作者： Ferreira, Paulo Saud, Hene Oliveira, Pedro Trigueiro, Joao Paulo Lavall, Rodrigo Salles, Luciana Universidade Federal de Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte Brazil Universidade Federal de Minas Gerais Electrical Engineering Department Belo Horizonte Brazil Universidade Federal de Minas Gerais Department of Chemistry Belo Horizonte Brazil Instituto Federal de Educação Ciência e Tecnologia de Minas Gerais Department of Chemistry/ICEx Betim Brazil Universidade Federal de Minas Gerais Department of Chemistry/ICEx Belo Horizonte Brazil

ISBN: (纸本)9798350326512

Supercapacitors have been widely studied and used on electrical and electronic circuits as energy storage devices. The potential of using supercapacitors in engineering is being continually explored and it is essential to use models compatible with Electronic Design Automation tools. The existing models do not fully comply with the modeled device and often their use requires adjustments to bring the modeled device closer to the real one. The two branches model is one of the simplest to-use parameter calculation methods found in the literature for modeling and specifying supercapacitors of capacitances in a range of up to 103 F. In this paper, it was adopted in the study of miniaturized and flexible solid-state devices with capacitances in the range of up to 10-3 F. The result is a method applicable in specifying and simulation of tens of millifarad supercapacitors used in IoT devices using SoC technology. © 2023 IEEE.

关键词： Supercapacitor

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3D Stackable Vertical Ferroelectric Tunneling Junction (V-FTJ) with on/off Ratio 1500x, Applicable Cell Current, Self-Rectifying Ratio 1000x, Robust Endurance of 10⁹ Cycles, Multilevel and Demonstrated Macro Operation Toward High-Density BEOL NVMs

3D Stackable Vertical Ferroelectric Tunneling Junction (V-FT...

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Symposium on VLSI Technology

作者： J.-Y. Lee F.-S. Chang K.-Y. Hsiang P.-H. Chen Z.-F. Luo Z.-X. Li J.-H. Tsai C. W. Liu M. H. Lee Institute and Undergraduate Program of Electro-Optical Engineering National Taiwan Normal University Taiwan Graduate School of Advance Technology National Taiwan University Taiwan Department of Electronics Engineering Institute of Electronics National Yang Ming Chiao Tung University Taiwan Department of Electrical Engineering National Taiwan Normal University Taiwan

A 1500x I LRS /I HRS with a high cell current of ~100 nA/ cell (J = 83 A/cm 2 ) is achieved by antiferroelectric (AFE) vertical ferroelectric tunnel junctions (V-FTJs) that demonstrates multilevel, a self-rectifying rate > 1000x, and macro operation. The stackable 3 D architecture integrating multiple layers of AFE V-FTJs with contact optimization further increases memory density. Robust endurance > 10 9 cycles at |4V| and stable nonvolatile data retention > 10 4 sec with extrapolation to 10 years are achieved. The proposed cell contact V-FTJ by AFE is a promising pathway toward BEOL NVMs by a NAND/NOR-based framework.

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A plug-in graph neural network to boost temporal sensitivity in fMRI analysis

arXiv

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arXiv 2023年

作者： Sivgin, Irmak Bedel, Hasan A. Öztürk, Şaban Çukur, Tolga Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Bilkent University Ankara06800 Turkey Department of Electrical-Electronics Engineering Amasya University Amasya05100 Turkey Neuroscience Program Bilkent University Ankara06800 Turkey

Learning-based methods have recently enabled performance leaps in analysis of high-dimensional functional MRI (fMRI) time series. Deep learning models that receive as input functional connectivity (FC) features among brain regions have been commonly adopted in the literature. However, many models focus on temporally static FC features across a scan, reducing sensitivity to dynamic features of brain activity. Here, we describe a plug-in graph neural network that can be flexibly integrated into a main learning-based fMRI model to boost its temporal sensitivity. Receiving brain regions as nodes and blood-oxygen-level-dependent (BOLD) signals as node inputs, the proposed GraphCorr method leverages a node embedder module based on a transformer encoder to capture temporally-windowed latent representations of BOLD signals. GraphCorr also leverages a lag filter module to account for delayed interactions across nodes by computing cross-correlation of windowed BOLD signals across a range of time lags. Information captured by the two modules is fused via a message passing algorithm executed on the graph, and enhanced node features are then computed at the output. These enhanced features are used to drive a subsequent learning-based model to analyze fMRI time series with elevated sensitivity. Comprehensive demonstrations on two public datasets indicate improved classification performance and interpretability for several state-of-the-art graphical and convolutional methods that employ GraphCorr-derived feature representations of fMRI time series as their input. Copyright © 2023, The Authors. All rights reserved.

关键词： Time series

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Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device

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Procedia Computer Science 2023年 227卷 1153-1162页

作者： Jason A. Wijaya Pauw D. Andersen Nico Surantha Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Electrical Electronic and Communication Engineering Tokyo City University Japan

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method.

关键词： sleep sleep quality actigraphy artificial intelligences fuzzy logic

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Machine Learning Enabled Sleep Time Estimation (MLE-STE) Architecture for Indoor Positioning in Energy-Efficient Mobile Internet of Things

Machine Learning Enabled Sleep Time Estimation (MLE-STE) Arc...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Alper Saylam Cüneyt Güzeliş Volkan Rodoplu Department of Electrical and Electronics Engineering Yaşar University Izmir Turkey Graduate School Yaşar University Izmir Turkey

ISBN: (数字)9798350311617

ISBN: (纸本)9798350311624

Indoor positioning and tracking systems require not only accurate position estimates of mobile IoT devices but also energy efficiency in order to maximize the battery life of the mobile IoT device. The contribution of this paper is the design of a machine learning enabled indoor positioning and tracking system in which artificial intelligence is utilized for the estimation of the duration for which a mobile IoT device needs to sleep in order to conserve energy. Our Machine Learning Enabled Sleep Time Estimation (MLE-STE) architecture is comprised of the following stages: First, it forms the forecast of the nearfuture trajectory of the mobile IoT device. Second, based on these forecasts, it determines the optimal sleep duration subject to the constraint of a maximum tolerable forecasting error. We demonstrate that our MLE-STE architecture outperforms both of the following state-of-the-art algorithms in this area: Positioning Interval based on Displacement (PID) and Dynamic Positioning Interval Based on Reciprocal Forecasting Error (DPI-RFE). This work represents a significant advance in the development of accurate indoor positioning and tracking algorithms that target the energy efficiency of mobile IoT devices.

关键词： Machine learning algorithms Target tracking Heuristic algorithms Estimation Machine learning Energy efficiency Trajectory

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An ANN-Based Electronic Nose for Monitoring Pollutant Gases in Landfills

An ANN-Based Electronic Nose for Monitoring Pollutant Gases ...

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IEEE Instrumentation and Measurement Technology Conference

作者： Juliene dos Santos Davi Muniz Francisco Auriberto Ferreira Marques Junior Cleonilson Protasio De Souza William De Paiva Post-Graduate Program of Electrical Engineering Federal University of Paraíba João Pessoa PB Brazil Post-Graduate Program of Environmental Science and Technology State University of Paraíba Campina Grande PB Brazil Department of Electrical Engineering Federal University of Paraíba João Pessoa PB Brazil Department of Sanitary and Environmental Engineering State University of Paraíba João Pessoa PB Brazil

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Biogas generated from urban solid waste degradation in landfills is composed of various types of gases, some of them are very toxic and harmful to the health of both humans and animals, and contribute directly to global warming as well. In this way, the monitoring of biogas concentration in landfills and their surroundings is very important because this can assess the air contamination around landfills, as well as to propose means to minimize it. In this work, an electronic nose for gas identification and measurement of gases present in landfill biogas using an Artificial Neural Network (ANN) is introduced. The ANN training data have been collected by the developed electronic nose, which consisted on a set of low-cost gas sensors and on a signal acquisition system controlled by the LabViewsoftware. After the ANN training, a neural architecture has been obtained and implemented in a microcontrolled digital system to measure different gas concentrations, mainly, methane. The main results of the proposed ANN-based Electronic Nose show that it was possible to measure the gases concentrations, with RMSE less than 1%, for the most of target gases, confirming the accuracy of the developed system.

关键词： Gases Semiconductor device measurement Accuracy Landfills Artificial neural networks Electronic noses Biogas

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Coordinated-axis Weight for Real-Time Trace Transform

Coordinated-axis Weight for Real-Time Trace Transform

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International electrical engineering Congress (iEECON)

作者： Nattapong Jundang Suchada Sitjongsataporn The Electrical Engineering Graduate Program Faculty of Engineering and Technology Mahanakorn University of Technology Bangkok Thailand Department of Electronic Engineering Faculty of Engineering and Technology Mahanakorn Institute of Innovation (MII) Mahanakorn University of Technology Bangkok Thailand

This paper presents a method for building Coordinated-axis Weight (CW) that has the advantage can be used to increase the speed for converting image data into the domain of real-time trace transforms. The main idea for this method is to use a feature reduction method for image data that must be used in cooperation with supervised machine learning outcome predictions. But the obtained result still retains the distinctive features of the data image in the form of a trace transform. Start by reducing the number of features from the image data, which will be used to reduce the size of the image to the appropriate image size, which in this article will reduce the image size to 45x45 pixels. The next step is to train the data using a Decision Tree (DT) method by aligning the reduced image data in a 1D model. In addition to the image data, two more features are added, i.e. the $\phi$ and $\rho$ positions, to inform the prediction that each position has a different value. And the last step is to bring the data to create a model for predicting the answer. The weights obtained from the model are called Coordinated-axis Weights (CW). The experiments within this paper were experimented using the Caltech-256 database, which was able to measure the MSE, RMSE, and PNSR of the images compared to the original trace transform response images at 4.1, 2.02, and 42.00, respectively, including the highest predictive speed of 0.2 ms per image.

关键词： Weight measurement Training Transforms Machine learning Predictive models Prediction algorithms Real-time systems

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Mitigation of torque oscillations caused by dc injection-based resistance estimation through resonant controllers 16

Mitigation of torque oscillations caused by dc injection-bas...

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16th Brazilian Power electronics Conference, COBEP 2021

作者： Da Silveira, Diogo Borges Farias, Joao Victor Matos Pereira, Heverton Augusto Luiz, Alex-Sander Amavel Stopa, Marcelo Martins Cupertino, Allan Fragner Federal University of Viçosa Department of Electrical Engineering Viçosa Brazil Federal University of Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte Brazil CEFET - MG Department of Electrical Engineering Belo Horizonte Brazil CEFET - MG Department of Materials Engineering Belo Horizonte Brazil

ISBN: (纸本)9781665421294

Stator on-line resistance estimation is often used, among others techniques, for thermal monitoring, flux and torque estimation in induction motor high performance drives. Dc current injection methods are some of the most well succeeded techniques found in literature for this purpose. In spite of this, the dc component added gives rise to oscillation in the electromagnetic torque, which can disturb the driven load and the industrial process controlled by the drive. In order to attenuate this component, a second-order current harmonic injection can be used. However, when proportional-integral controllers are employed, four additional transformations are required. This paper proposed a control scheme based on adaptive resonant control, that presents the advantage of reducing computational requirements, since additional transformations are not required. The results show that similar performance with reduced complexity are accomplished. © 2021 IEEE.

关键词： Induction motors

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Enhanced diabetic wound healing using platelet-derived extracellular vesicles and reduced graphene oxide in polymer-coordinated hydrogels

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Journal of Nanobiotechnology 2023年第1期21卷 1-17页

作者： Hao, Ping-Chien Burnouf, Thierry Chiang, Chih-Wei Jheng, Pei-Ru Szunerits, Sabine Yang, Jen-Chang Chuang, Er-Yuan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei10617 Taiwan Department of Orthopedics Taipei Medical University Hospital Taipei11031 Taiwan Univ. Lille CNRS Centrale Lille Univ. Polytechnique Hauts-de-France UMR 8520 IEMN LilleF- 59000 France Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei110-52 Taiwan Cell Physiology and Molecular Image Research Center Taipei Medical University-Wan Fang Hospital Taipei11696 Taiwan Precision Medicine and Translational Cancer Research Center Taipei Medical University Hospital Taipei11031 Taiwan

Impaired wound healing is a significant complication of diabetes. Platelet-derived extracellular vesicles (pEVs), rich in growth factors and cytokines, show promise as a powerful biotherapy to modulate cellular proliferation, angiogenesis, immunomodulation, and inflammation. For practical home-based wound therapy, however, pEVs should be incorporated into wound bandages with careful attention to delivery strategies. In this work, a gelatin-alginate hydrogel (GelAlg) loaded with reduced graphene oxide (rGO) was fabricated, and its potential as a diabetic wound dressing was investigated. The GelAlg@rGO-pEV gel exhibited excellent mechanical stability and biocompatibility in vitro, with promising macrophage polarization and reactive oxygen species (ROS)-scavenging capability. In vitro cell migration experiments were complemented by in vivo investigations using a streptozotocin-induced diabetic rat wound model. When exposed to near-infrared light at 2 W cm− 2, the GelAlg@rGO-pEV hydrogel effectively decreased the expression of inflammatory biomarkers, regulated immune response, promoted angiogenesis, and enhanced diabetic wound healing. Interestingly, the GelAlg@rGO-pEV hydrogel also increased the expression of heat shock proteins involved in cellular protective pathways. These findings suggest that the engineered GelAlg@rGO-pEV hydrogel has the potential to serve as a wound dressing that can modulate immune responses, inflammation, angiogenesis, and follicle regeneration in diabetic wounds, potentially leading to accelerated healing of chronic wounds. © 2023, BioMed Central Ltd., part of Springer Nature.

关键词： Platelets

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