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Synaptic Device for Neuromorphic Systems Integrating Ferroelectric-Gate Field Effect Transistor and Capacitor 31

Synaptic Device for Neuromorphic Systems Integrating Ferroel...

31st International Workshop on Active-Matrix Flatpanel Displays and Devices: TFT Technologies and FPD Materials, AM-FPD 2024

作者： Sawai, Kazuki Hirano, Taiga Matsuda, Tokiyoshi Kawanishi, Hidenori Miyasako, Takaaki Koh, Sanggyu Hosokura, Tadasu Kimura, Mutsumi Graduate School of Advanced Science and Technology Ryukoku University Seta Shiga Otsu520-2194 Japan Department of Electrical and Electronic Communication Engineering Kindai University Kowakae Higasliiosaka Osaka577-8502 Japan Innovative Materials and Processing Research Center Ryukoku University Seta Shiga Otsu520-2194 Japan Graduate School of Science and Technology Nara Institute of Science and Technology Takayama Ikoma630-0192 Japan Murata Manufacturing Co. Ltd. Nagaokakyo Kyoto617-8555 Japan

ISBN: (纸本)9784991216961

We have proposed a synaptic device for neuromorphic systems that integrates a Ferroelectric-gate Field-Effect Transistor (FeFET) and a capacitor. In this study, spike pulses were applied to this synaptic device to confirm its operation. The results showed that the membrane potential increased while the pulses were applied and was maintained while the pulses were not applied, and that this series of operations could be repeated. In addition, it was confirmed that signal transmission with different synaptic strengths can be achieved by controlling the polarization of the FeFET. Therefore, we believe that the proposed device integrating a FeFET and a capacitor can be used as a synapse in neural networks. © 2024 FTFMD.

关键词： Ferroelectricity

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Expert-level sleep staging using an electrocardiography-only feed-forward neural network

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Computers in Biology and Medicine 2024年 176卷 108545-108545页

作者： Jones, Adam M. Itti, Laurent Sheth, Bhavin R. Neuroscience Graduate Program University of Southern California Los AngelesCA United States Department of Electrical & Computer Engineering University of Houston HoustonTX United States Center for NeuroEngineering and Cognitive Systems University of Houston HoustonTX United States

Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomnography (PSG). Unfortunately, PSG is an expensive and cumbersome process involving numerous electrodes, often conducted in an unfamiliar clinic and annotated by a professional. Although commercial devices like smartwatches track sleep, their performance is well below PSG. To address these disadvantages, we present a feed-forward neural network that achieves gold-standard levels of agreement using only a single lead of electrocardiography (ECG) data. Specifically, the median five-stage Cohen's kappa is 0.725 on a large, diverse dataset of 5 to 90-year-old subjects. Comparisons with a comprehensive meta-analysis of between-human inter-rater agreement confirm the non-inferior performance of our model. Finally, we developed a novel loss function to align the training objective with Cohen's kappa. Our method offers an inexpensive, automated, and convenient alternative for sleep stage classification—further enhanced by a real-time scoring option. Cardiosomnography, or a sleep study conducted with ECG only, could take expert-level sleep studies outside the confines of clinics and laboratories and into realistic settings. This advancement democratizes access to high-quality sleep studies, considerably enhancing the field of sleep medicine and neuroscience. It makes less-expensive, higher-quality studies accessible to a broader community, enabling improved sleep research and more personalized, accessible sleep-related healthcare interventions. © 2024 Elsevier Ltd

关键词： Electrocardiography

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Ontology-Driven IoT System for Monitoring Hypertension 25

Ontology-Driven IoT System for Monitoring Hypertension

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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： de Souza, Pedro Lopes de Souza, Wanderley Lopes Pires, Luís Ferreira Moreira, João Luiz Rebelo da Silva Rodrigues, Ronitti Juner Ciferri, Ricardo Rodrigues Semantics Cybersecurity & Services Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente P.O. Box 217 Enschede Netherlands Ubiquitous Computing Group Graduate Program in Computer Science Computing Department Federal University of São Carlos P.O. Box 676 São Carlos Brazil

ISBN: (纸本)9789897586484

Hypertension is a noncommunicable disease (NCD) that causes global concern, high costs and a high number of deaths. Internet of Things, Ubiquitous Computing, and Cloud Computing enable the development of systems for remote and real-time monitoring of patients affected with NCDs like hypertension. This paper reports on a system for monitoring hypertension patients that was built by employing these techniques. This system allows the vital signs of a patient (blood pressure, heart rate, body temperature) to be captured via sensors built in a wearable device similar to a wristwatch. These signals are transmitted to the patient's mobile device for processing, and the generated clinical data are sent to the cloud to be properly presented and analysed by the health professionals responsible for the patient. To deal with semantic interoperability issues that arise when multiple different devices and system components must interoperate, a semantic model was conceived for this system in terms of ontologies for diseases and devices. This paper also presents the semantic module that we developed and implemented in the cloud to perform reasoning based on this model, demonstrating the potential benefits of incorporating semantic technologies in our system. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Ontology

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Development of Buffer Zone into Living Lab-Garuda Smart City Framework: Systematic Review 10

Development of Buffer Zone into Living Lab-Garuda Smart City...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Emmanuel, Gunadi Supangkat, Suhono Harso Gaol, Ford Lumban Ranti, Benny Bina Nusantara University Doctor of Computer Science Jakarta Indonesia Univ. Katolik Musi Charitas Fakultas Sains Dan Teknologi Palembang Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350339543

The phenomenon of urbanization in Indonesia is inevitable. The new residential and economic centers in suburban areas is also a problem in city development. The gradual planning and development of smart cities in a living lab require consideration of the right location for a living lab. This study wants to show that suburban areas as city buffer zones can become living laboratories for smart city development. The diversity of situations in cities and regencies across Indonesia, the potential for resources, and the problems faced are the challenges of developing a living lab-Garuda Smart City Framework. This research uses the method of reviewing the literature of research publications for the last five years (2019-2023) to obtain information on Smart City development in Indonesia. We collected selected articles from databases in Google Scholar, IEEE, and Scopus using the Publish and Perish 8. The search keywords used were garuda AND Smart city AND Framework. The findings show the potential and dynamics of buffer zones to become appropriate living laboratories. Smart city regional planning can more holistically involve neighborhoods and address urban issues. © 2023 IEEE.

关键词： Smart city

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The effects of growth environments on WS2 in electrocatalytic hydrogen evolution reaction

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Journal of Physics and Chemistry of Solids 2024年 185卷

作者： Chang, Yung-Huang Huang, Chien-Sheng Chen, Yuan-Tsung Chiang, Chia-Yu Bachelor Program in Industrial Technology National Yunlin University of Science and Technology Yunlin Taiwan Department of Electronic Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Materials Science National Yunlin University of Science and Technology Yunlin Taiwan

Transition metal dichalcogenides (TMDs) recently have attracted much attention because of their outstanding catalytic activity, low cost, and earth abundance in the hydrogen evolution reaction (HER). Among these TMDs, MoS2 and WS2 are recognized as promising HER electrocatalysts and have been explored to be one of the candidates for replacing precious metals. In this work, the electrocatalytic activity of WS2 grown in Ar-only, Ar + H2, and ambient environments were studied, where the WS2 was synthesized by thermolysis from (NH4)2WS4 precursor. Different surface morphologies are shown under the different growth atmospheres. The structures of pure WS2, WS2 and WO3 mixed, and almost WO3 were prepared in different growth atmospheres of Ar-only, Ar + H2, and ambient environment, respectively. All the materials prepared in these different environments exhibit high crystalline characteristic. Especially, the pure WS2 grown in an Ar-only environment presents the preferred (103) lattice plane. The pure WS2 performs the best H2 evolution efficiency, indicating that high crystallinity and preferred (103) lattice plane could be relative to the electrocatalytic activity. The studies provide fundamental insight for further design and preparation of electrocatalysts, useful in the development of clean energy. © 2023 Elsevier Ltd

关键词： Electrocatalysts

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Demonstration of a polarization-agnostic geometric phase in nonlocal metasurfaces

Demonstration of a polarization-agnostic geometric phase in ...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Overvig, Adam C. Kasahara, Y. Alu, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78712 United States Physics Program Graduate Center of the City University of New York New YorkNY10016 United States

We theoretically propose and experimentally demonstrate nonlocal metasurfaces rationally designed using symmetry-breaking principles to manipulate the optical wavefront with a geometric phase selective to custom ellip...

ISBN: (纸本)9781957171258

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Visual Control and Mapping for UAV-Based Platform Inspection

Visual Control and Mapping for UAV-Based Platform Inspection

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Leonardo A. Fagundes Carlos M. Soria Raquel F. Vassallo Alexandre S. Brandão Department of Electrical Engineering Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil Facultad de Ingeniería Instituto de Automática Universidad Nacional de San Juan Argentine Department of Electric Engineering Federal University of Espirito Santo Vitória ES Brazil

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety of landing platforms are required. In this context, this paper presents a servo-visual controller that uses pattern detection and color segmentation techniques to identify take-off/landing platforms and estimate their current orientation. The proposed system was subjected to experimental validation with four platforms positioned in different orientations, heights, and positions, demonstrating its versatility in various conditions. Our study addresses the Flying Robots Trial League challenge, which emulates mapping and inspection tasks in offshore platforms.

关键词： Visualization Offshore installations Navigation Color Inspection Autonomous aerial vehicles Aircraft Drones Aerospace control

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Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

arXiv

引用

arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China 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 University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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Sensing Beyond the Exceptional Point for High Detectivity

Sensing Beyond the Exceptional Point for High Detectivity

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Conference on Lasers and Electro-Optics (CLEO)

作者： Zhichao Li Ciril S. Prasad Xielin Wang Ding Zhang Gururaj V. Naik Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Electrical and Computer Engineering Rice University Houston TX USA Department of Physics and Astronomy Rice University Houston TX USA

Exceptional point (EP)-based optical sensors exhibit exceptional sensitivity but poor detectivity. Slightly off EP operation boosts detectivity without much loss in sensitivity. We experimentally demonstrate a high-de... 详细信息

ISBN: (纸本)9798350369311

关键词： Proteins Optical losses Sensitivity Optical device fabrication Measurement by laser beam Lasers and electrooptics Optical sensors Laser applications Electro-optical waveguides

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TreeXGNN: can gradient-boosted decision trees help boost heterogeneous graph neural networks?

TreeXGNN: can gradient-boosted decision trees help boost het...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ming-Yi Hong Shih-Yen Chang Hao-Wei Hsu Yi-Hsiang Huang Chih-Yu Wang Che Lin Graduate Program of Data Science National Taiwan University and Academia Sinica Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan Department of Electrical Engineering National Taiwan University Taiwan

Graph neural networks are a promising deep learning method that can apply graph structures to various tasks. In real-world scenarios, we often have heterogeneous graphs, wherein different node and edge types capture complex interactions between nodes. High-dimensional node features provide rich information about the target nodes. Conventional heterogeneous graph neural networks (HGNN) focus more on graph structures than node features and may have difficulties extracting knowledge from complex node features. In this study, we propose a novel framework, the tree-boosted heterogeneous graph neural network abbreviated as TreeXGNN, which could efficiently and automatically extract target node features via gradient-boosted decision trees (GBDT). It integrates community structure information with proper fusion modules and a shared feature space design on HGNN. We achieved state-of-the-art performance on the three well-known heterogeneous graph benchmark datasets, IMDB, DBLP, and ACM, and significantly improved performance compared to previous studies. Our work paves the foundation for integrating tree-based models to boost HGNNs for general community analysis.

关键词： Training Knowledge engineering Deep learning Signal processing Feature extraction Graph neural networks Decision trees

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