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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Tsung-Wei Lin Sofia Ormazabal Arriagada Che Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taiwan International Graduate Program AIoT NTU Research Center for Information Technology Innovation Academia Sinica Department of Electrical Engineering NTU Center for Advanced Computing and Imaging in Biomedicine NTU Smart Medicine and Health Informatics Program NTU

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a novel approach that combines multi-task learning (MTL) and graph neural networks (GNNs) to address this issue. By representing gene-gene interactions as a graph network, our approach leverages multi-task learning to effectively capture the relationships of genes relevant to the oncogenesis and progression of breast, lung, and colon cancer. We demonstrate that our approach improves the cancer prognosis prediction for cancers with fewer samples, such as colon adenocarcinoma, by leveraging the shared gene-gene interactions across different cancer types, obtaining increases in the area under the precision-recall curve (AUPRC) of 24%. Our work contributes to the field of smart healthcare by demonstrating the potential of MTL and GNNs for enhancing cancer prognosis prediction, even with limited data samples.

关键词： Lungs Genomics Medical services Colorectal cancer Breast Multitasking Oncology Graph neural networks Prognostics and health management Cancer

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Single-Phase Transformerless UPS with Interleaved Boost Converters for Battery Discharging

Single-Phase Transformerless UPS with Interleaved Boost Conv...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Alan R. A. Pinto Filipe A. C. Bahia Reuben P. R. Souza José R. Pinheiro Fabiano F. Costa Post-Graduate Program in Electrical Engineering PPGEE Federal University of Bahia Salvador Brazil Dept. of Electrical and Computer Engineering DEEC Federal University of Bahia Salvador Brazil Dept. of Electrical Engineering DEE Federal University of Campina Grande Campina Grande Brazil

This paper proposes a reconfiguration for a single-phase, double conversion uninterruptible power supply (UPS). With the addition of two static switches to the original circuit, the UPS mitigates the ripple in the current, through battery discharge performed by two legs. Other than these switches, the circuit topology is preserved. The preliminary results show a satisfactory level of ripples for the inductor current and suitable power quality for the output voltage.

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Optical Neuromorphic modulators based on Tamm Plasmon Resonators with PEDOT:PSS

Optical Neuromorphic modulators based on Tamm Plasmon Resona...

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IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

作者： Young Min Song Joo Hwan Ko Dong Hyun Seo Gwangju Institute of Science and Technology (GIST) School of Electrical Engineering and Computer Science Gwangju Korea GIST: AI Graduate School Gwangju Korea GIST: Department of Semiconductor Engineering Gwangju Korea

ISBN: (数字)9798350383263

ISBN: (纸本)9798350383270

Reconfigurable optical devices are increasingly recognized for their potential in enhancing high-density optical interconnects, photonic switching, and memory systems. While various optical modulators utilizing active materials have been successfully developed, achieving high modulation depth with low operating voltage in the near-infrared (NIR) spectrum remains a significant challenge. This spectrum is particularly important for free-space communication and imaging technologies. In this context, an electrically switchable device employing Tamm plasmon coupled with poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS) has been introduced. This innovative approach enables substantial modulation depth throughout the NIR spectrum, effectively absorbing incident light even under epsilon near zero conditions. The device boasts an impressive optical modulation efficiency of over 88% at a CMOS-compatible voltage of ±1 V, achieved through meticulous electrical manipulation of charge carrier density via an electrochemical doping/dedoping process. Moreover, this device opens new avenues for creating non-volatile optical memory storage solutions, exhibiting rewritable multi-memory states and demonstrating long-term potentiation/depression capabilities, akin to neuromorphic behavior.

关键词： Neuromorphics Optical switches Optical resonators Voltage Plasmons Optical imaging Sensor systems

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Temperature Dependent Anomalous Threshold Voltage Modulation of a-IGZO TFT by Incorporating Variant Gate Stresses

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ECS Journal of Solid State Science and Technology 2024年第6期13卷 065008-065008页

作者： Aslam, Muhammad Chang, Shu-Wei Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Lee, Wen-Hsi Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu 300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan 701401 Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 300093 Taiwan Institute of Pioneer Semiconductor Innovation Industry Academic Innovation School National Yang Ming Chiao Tung University Hsinchu 300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu 300093 Taiwan

Amorphous indium gallium zinc oxide (a-IGZO) has recently made significant advancement as a key material for electronic component design owing to its compatibility with complementary metal oxide semiconductor technologies. A comprehensive analysis of reliability-related issues is required to determine the true potential of a-IGZO-based devices for next-generation electronics applications. To address this objective, we electrically characterize scaled-channel a-IGZO thin film transistors (TFTs) under positive bias (temperature) stress (PB(T)S). Both PBS and PBTS are characterized by positive and negative V_th shift, respectively, during the various gate stresses. In particular, the negative V_th shift is explained by the generation of donor-like traps stimulated by ionization of oxygen vacancy/hydrogen at elevated temperature. The TFTs exhibit relatively decent stability during the PBS operation. The analysis of devices with variant channel dimensions implies that long-channel devices exhibit relatively higher stability and performance compared to the short-channel ones. We also observe that the V_th can be controllably adjusted by employing the top gate (TG) with bottom gate sweep. Moreover, the stress-induced partial recovery mechanism is experimentally observed owing to detrapping of charges. Generally, the reported results infer a perceptive understanding of scaled-channel a-IGZO-TFTs which helps with shaping performance-enhancement strategies. © 2024 The Author(s). Published on behalf of The Electrochemical Society by IOP Publishing Limited

关键词： amorphous IGZO-TFT electrical instabilities hydrogen-impact scaling impact on reliability

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Radar-Assisted Predictive Beamforming for UAV-Aided Networks: A Deep-Learning Solution

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IEEE Transactions on Vehicular Technology 2025年

作者： Yin, Rui Peng, Jingwei Cai, Yunlong Wu, Celimuge Champagne, Benoit Al-Dhahir, Naofal Hangzhou City University Laboratory for Microwave Spatial Intelligence and Cloud Platform Hangzhou310015 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of Electro-Communications Graduate School of Informatics & Engineering Japan McGill University Department of Electrical and Computer Engineering MontrealQCH3A 0E9 Canada The University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX75080 United States

In the realm of Sixth-Generation (6G) mobile communication systems, unmanned aerial vehicle (UAV) technologies have gained significant attention, particularly within UAV-assisted wireless networks. This paper explores radar-assisted predictive beamforming to enhance communication in such networks. A mobile UAV equipped with multiple antennas and radar functionality is deployed to serve a group of mobile users on the ground. The primary objective is to optimize communication performance, ensuring stable and efficient data transmission rates within a specified time frame, under practical power and flight range constraints. To address this challenging problem, we introduce a novel solution framework that integrates a deep reinforcement learning (DRL) network and a dual-layer deepunfolding network (DUN). By leveraging a two-timescale processing structure, the new framework enables and facilitates the joint optimization of mobile user tracking, transmit beamforming and UAV trajectory. Simulation results confirm the effectiveness of our proposed scheme, demonstrating improvements in movement tracking accuracy and transmission rates. © 1967-2012 IEEE.

关键词： Deep reinforcement learning

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Cyber Attacks Detection using Deep Learning Methods for Resilient Operation in DC Shipboard Microgrids

Cyber Attacks Detection using Deep Learning Methods for Resi...

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IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)

作者： Zulfiqar Ali Tahir Hussain Chun-Lien Su Anca Delia Jurcut Shazia Baloch Muhammad Sadiq Department of Electrical Engineering National Kaohsiung University of Science and Technology Kaohsiung city Taiwan Department of Informatics Graduate School of Informatics and Engineering The University of Electro-Communication Tokyo Japan School of Computer Science University College Dublin Belfield Dublin 4 Ireland Department of Electrical Engineering Balochistan University of Engineering and Technology Khuzdar Pakistan

ISBN: (数字)9798350352290

ISBN: (纸本)9798350352306

Cyber resilience has become paramount as a transition of maritime systems towards digitization, particularly within DC shipboard microgrids (SMGs). Adopting innovative communication technologies can enhance the resilience of SMGs for stable operation. However, challenges like false data injection and Man-in-The-Middle attacks pose significant threats to SMG operations when integrating these technologies into ship intelligent grids. In this regard, this paper proposes a reliable deep learning (DL) method, especially an Artificial neural network (ANN) with a deep encoder-decoder architecture, for the detection of cyber-intrusions and mitigating their effects, ensuring system control and stability for resilient operation of SMG. Detecting malicious data intrusions is crucial for maintaining optimal grid conditions and preventing disruptions in load dispatch. The proposed method utilizes a fusion of current and voltage data features for comprehensive DL model training, resulting in an adequate level of detection accuracy and providing cybersecurity analysis for SMGs, addressing component-level attacks, and devising defense strategies from aspects of detection, mitigation, and prevention. Furthermore, the deep ANN is fine-tuned with optimal hyperparameters to effectively counter cyberattacks, achieving an enhanced accuracy rate of 97.51% and minimal loss of 0.101%, surpassing conventional machine learning approaches. Rigorous test scenarios are performed to validate the robustness of the proposed method, emphasizing the cyber resilience of DC SMGs for enhanced security and operational integrity.

关键词： Training Accuracy Prevention and mitigation Artificial neural networks Microgrids Detectors Power system stability Stability analysis Cyberattack Resilience

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Modulated Noise Communication: Reading UHF RFID tags without a carrier

Modulated Noise Communication: Reading UHF RFID tags without...

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IEEE International Conference on RFID

作者： Shanti Garman Ali Saffari Daisuke Kobuchi Joshua R. Smith Zerina Kapetanovic Department of Electrical and Computer Engineering University of Washington Seattle WA USA Graduate School of Engineering University of Tokyo Tokyo Japan Department of Computer Science and Engineering University of Washington Seattle WA USA Department of Electrical Engineering Stanford University Stanford CA USA Microsoft Research Redmond WA USA

This paper demonstrates that UHF RFID tags can be read without a carrier. More specifically, using an alternative reader design that does not emit a carrier, we show that it is possible to read an RFID tag that was designed to be read by a conventional RFID reader that does emit a carrier. Typical RFID tags are designed to modulate a carrier; it turns out that, in addition to modulating a carrier, a backscatter modulator circuit also modulates tag circuit noise, including Johnson noise; Johnson and other noise is present in a tag even if a carrier is not. Modulated Noise Communication (MNC) can be read by an alternative reader design. The reader for modulated noise communication is simpler than a conventional backscatter reader because it does not have to contend with the problem of self-jamming. The absence of a carrier means that the tag needs an alternative power source; this could be an energy harvester such as a photovoltaic cell, or could be a time-multiplexed continuous wave signal from the reader. The use of time multiplexing means that the reader would still inherit the benefits of not needing to counteract self jamming.

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Dual Quaternion-Based Control for a Leader-Follower Formation of Two Quadrotors

Dual Quaternion-Based Control for a Leader-Follower Formatio...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Harrison Neves Marciano Daniel Khede Dourado Villa Mário Sarcinelli-Filho Juan Ignacio Giribet The Graduate Program on Electrical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil The Department of Engineering Universidad de San Andrés Victoria Buenos Aires Argentina

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper investigates the use of dual quaternions for controlling a leader-follower configuration of small Unmanned Aerial Vehicles (UAVs). The paper focuses on how the parameters of a non-linear kinematic control algorithm can be chosen to achieve a prescribed behavior. The paper provides theoretical support, refines existing methods, and validates results through experiments. The findings contribute to the understanding and optimization of dual quaternion-based control strategies for small UAVs formations.

关键词： Quaternions Kinematics Autonomous aerial vehicles Vehicle dynamics Aircraft Tuning Optimization

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Virtual Functional Mobility Assessment: A Pilot Study in People with Parkinson's Disease

Virtual Functional Mobility Assessment: A Pilot Study in Peo...

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IEEE International Conference on Serious Games and Applications for Health (SeGAH)

作者： Tanvir Irfan Chowdhury Júlia Araújo Moura John Quarles Felipe Augusto Dos Santos Mendes Computer Sciences and Electrical Engineering Marshall University Huntington WV USA Graduate Program in Rehabilitation Sciences University of Brasilia Brazil Computer Science The University of Texas at San Antonio San Antonio USA

At present, few validated clinical tests provide the assessment of mobility in patients with Parkinson's Disease (PD) during the execution of complex tasks. To verify the feasibility of a virtual environment based on a Microsoft Kinect sensor as a tool to evaluate the functional mobility of people with PD. An analytical, observational and transversal pilot study was held. The sample consisted of 12 patients with PD and 12 healthy young adults. All participants were evaluated on gait tests and in the virtual environment. The System Usability Scale (SUS) was applied to the PD group to evaluate the virtual environment usability. Significant differences were found in groups' performance in the virtual environment. Regular and strong relations were found on patients' performance on gait tests and virtual environment tests. The virtual environment usability was considered acceptable among patients with PD. The virtual environment developed is potentially viable as a functional mobility assessment tool for patients with PD.

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Development of 5G Cyber-Physical Production System

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International Journal of Networked and Distributed Computing 2023年第1期11卷 9-19页

作者： Huang, Hsuan-Chao Tsai, Chun-Hsien Lin, Hsiung-Cheng Department of Computer Science and Information Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan PhD program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan Department of Electronic Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan

The cyber-physical production system (CPPS) was developed for the interconnection between operational technology (OT) and information and communication technology (ICT) among the machines and decentralized production control. However, OT and ICT are now getting more complex in the modern industry. To enhance industrial management and production process, the CPPS based on the 5G architecture under production environments can provide a more comprehensive solution in the context of Industry 4.0. For this purpose, a 5G CPPS model to improve the interoperability of CPPS in ICT and OT is proposed to build a virtualized Industry 4.0 asset management shell system. First, real-time task artifacts and 5G communication modules are bound in a certain form of virtualization. Second, task artifacts are released to the production line in a real-time scheduling. Third, an order is placed on a production line and split into multiple tasks for production process. Single-machine single-workpiece and multi-machine and multi-workpiece processing cases are used for testing in the production line. Experimental results show that the proposed 5G CPPS can efficiently achieve multi-machine work piece processing. © 2022, The Author(s).

关键词： 5G Cyber-physical production system (CPPS) Digital twin (DT) Industry 4.0 Information technology Operational technology

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