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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Gao, Yang Choi, Seokheun State University of New York at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering BinghamtonNY United States State University of New York at Binghamton Center for Research in Advanced Sensing Technologies and Environmental Sustainability BinghamtonNY United States

ISBN: (纸本)9798331508890

We present a wearable, paper-based energy harvester that combines a sweat-driven microbial fuel cell (MFC) with an ambient moisture-enabled electric generator (MEG), capable of simultaneously or independently harnessing energy from both human sweat and the environment. Paper stands out as an ideal substrate for wearable applications, offering flexibility and easy integration through straightforward printing methods. Due to the simple design of the MFC and MEG, both devices can be seamlessly integrated into a single sheet of paper. The biocatalyst-embedded anode of the MFC is positioned directly against the skin for optimal sweat absorption, while the hygroscopic region of the MEG faces outward to efficiently capture ambient moisture. At low humidity levels, the energy harvesting is primarily driven by the MFC, while in the absence of sweat, the MEG takes over as the main power source. This dual functionality ensures continuous and sustainable power generation, making the system highly efficient and reliable for long-term wearable applications. © 2025 IEEE.

关键词： Microbial fuel cells

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Distributed time-varying formation control with uncertainties based on an event-triggered mechanism

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Science China(Information Sciences) 2021年第3期64卷 167-176页

作者： Xiaoduo LI Yumeng BAI Xiwang DONG Qingdong LI Zhang REN Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical EngineeringBeihang University Department of Electrical and Computer Engineering University of Wisconsin-Madison Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

This paper investigates the distributed time-varying formation(TVF) problems for general linear multi-agent systems(MASs) subject to matched bounded uncertainties based on an adaptive event-triggered mechanism. A TVF protocol was designed with an event-triggered mechanism by introducing adaptive weights into the formation control protocol and triggering condition, and the large chattering phenomenon was avoided by the σ-modification adaptive law. According to the Lyapunov stability theory, proof has been established that the MASs in the presence of uncertainties can realize the expected formation that satisfies the given feasible condition. Finally, an example is provided to verify the effectiveness of the proposed algorithm.

关键词： formation control multi-agent systems event-triggered adaptive control

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Design and Implementation of a Wide-Swing CMOS Multiplier for AC Source Signal Tracking and Modulation

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Circuits, Systems, and Signal Processing 2024年第9期43卷 5377-5400页

作者： Wang, Wei Xu, Sendren Sheng-Dong Chen, Chi-Lin Chiu, Huang-Jen Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei 106335 Taiwan Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei 106335 Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taipei 106335 Taiwan Himax Technologies Inc. Taipei 100507 Taiwan

The multiplier is a pervasive critical component today. However, most of them are difficult to be integrated into an integrated circuit. In this study, we proposed a novel analog multiplier for AC power application, using CMOS process to realize the analog voltage multiplication function of double-ended input and single-ended output. Under the working voltage of 3.3 V, the multiplier can operate with a wide input voltage range of 0–1.6 V (about 48.8% of the working voltage) and a wide output voltage range of 0–2.56 V (about 77.5% of the working voltage). The multiplier is implemented through the current difference between two NMOSs operating in the linear region and the saturation region, respectively. Compared with the existing technique, the proposed analog multiplier has a wider input and output range, and better linearity. It is suitable for AC power signal tracking and modulation. Finally, the United Microelectronics Corporation 0.18 μm 1P4M CMOS standard process was used for physical implementation. Moreover, there is not any BJT or special device used. It was measured that the analog multiplier circuit consumes about 0.56 mW at a working voltage of 3.3 V. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： AC power signal modulation AC source signal tracking Analog integrated circuit (IC) design Analog multipliers Circuits and systems

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3D-Printed Stainless Steel Electrodes for Advancing Mems Microbial Fuel Cells Toward Sustainable on-chip Energy 38

3D-Printed Stainless Steel Electrodes for Advancing Mems Mic...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Elhadad, Anwar Li, Guangfa Yang, Jiaqi Liu, Dehao Choi, Seokheun State University of New York at Binghamton Integrated Computational Materials Design Lab Department of Mechanical Engineering BinghamtonNY United States State University of New York at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering BinghamtonNY United States State University of New York at Binghamton Center for Research in Advanced Sensing Technologies and Environmental Sustainability BinghamtonNY United States

ISBN: (纸本)9798331508890

This study introduces a stainless steel microbial anode fabricated via advanced laser powder bed fusion, marking a transformative step in microbial fuel cell (MFC) technology. By leveraging this cutting-edge metal 3D printing approach, we achieve a 3D microporous structure with superior electrical conductivity, outstanding corrosion resistance in aquatic environments, robust mechanical strength, and adaptability for surface modification - essential attributes for sustainable, high-performance MFCs. The assembled MFC demonstrates unparalleled power output, along with exceptional durability and stability over multiple cycles, outperforming existing MFCs based on alternative 3D-printed substrates. This advancement not only solidifies the role of MFCs as a sustainable energy solution for powering on-chip electronics but also opens new avenues for scalable, cost-effective bioelectronic systems that align with the demands of next-generation technology. © 2025 IEEE.

关键词： Corrosion resistance

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A Buoyant Bio-Solar Cell Array with Long-Lasting High-Power Output: Energy Harvesting from Aquatic Environments 21

A Buoyant Bio-Solar Cell Array with Long-Lasting High-Power ...

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21st International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications, PowerMEMS 2022

作者： Elhadad, Anwar Rezaie, Maryam Choi, Seokheun at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering New York United States Center for Research in Advanced Sensing Technologies & Environmental Sustainability Suny BinghamtonNY United States

ISBN: (纸本)9781665493062

Miniaturized bio-solar cells have emerged as a potential sustainable power source for the Internet of Things (IoT) applications deployed in unattended, difficult-to-reach aquatic environments such as oceans, rivers, and lakes. Here, we create a scalable, high-power, long-lasting, and buoyant bio-solar cell stack that integrates significantly improved miniature bio-solar cells in an array. Each cell incorporates a symbiotic microbial consortium consisting of Synechocystis sp. PCC6803 and Bacillus subtilis. While Synechocystis sp. generates electricity through its photosynthetic and respiratory activities, it produces an organic fuel through its photosynthesis, which sustains B. subtilis in the consortium. Each cell was able to generate a sustainable maximum power density of ~70 μWcm-2. © 2022 IEEE.

关键词： Internet of things

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Automating Theory of Mind Assessment with a LLaMA-3-Powered Chatbot: Enhancing Faux Pas Detection in Autism 14

Automating Theory of Mind Assessment with a LLaMA-3-Powered ...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Fallah, Avisa Nazari, Mohammad Ali Keramati, Ali Mirfazeli, Fatemeh Sadat School of Mathematics Statistics and Computer Science University of Tehran Tehran Iran National Brain Centre Iran University of Medical Sciences Tehran Iran Department of Neuroscience Advanced Technologies in Medicine Iran University of Medical Sciences Image Brain Institute Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran Mental Health Research Center Department of Psychiatry School of Medicine Psychosocial Health Research Institute Advanced Technologies in Medicine National Brain Centre Iran University of Medical Sciences Tehran Iran

ISBN: (纸本)9798331511272

The Theory of Mind (ToM) is critical for social interactions, enabling individuals to understand and predict others’ mental states. Deficits in ToM, particularly in detecting faux pas, are common among individuals with Autism Spectrum Disorder (ASD). Traditional methods for assessing ToM, such as the Faux Pas Recognition Test (FPRT), require significant human involvement, which can limit accessibility and scalability. This study aims to explore how large language model (LLM)powered chatbots, specifically utilizing the LLaMA-3 model, can enhance the assessment of ToM by automating and improving the administration of the FPRT. The methodology involved creating a dual-phase process where the chatbot first assesses user responses and then provides rehabilitative guidance to correct misunderstandings. Additionally, the system employs a scoring mechanism combining automated evaluation with human oversight to ensure accuracy and consistency, with system prompts crafted based on chain-of-thought prompting to enhance the depth and reliability of the assessments. Our findings demonstrate the effectiveness of LLM-powered chatbots in delivering dynamic and supportive ToM assessments, suggesting its potential for broader application for both artificial intelligence and psychological practices. ©2024 IEEE.

关键词： Chain-of-thought Faux Pas Recognition Test Interactive Chatbot Language Models Theory of Mind

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Interpretation of ADRC in $Q$-Structure

Interpretation of ADRC in $Q$-Structure

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Jiapeng Xu Xiang Chen Ying Tan Kemin Zhou Department of Electrical and Computer Engineering University of Windsor Windsor Canada Department of Mechanical Engineering The University of Melbourne Melbourne Australia Center for Advanced Control and Smart Operations Nanjing University Suzhou China

ISBN: (数字)9798350356618

ISBN: (纸本)9798350356625

This paper presents a control structure featuring an operator $Q$ driven by the residual signal, which indicates the difference between the measurement output and the estimated output from an observer. The form of this observer is very general, as long as it can generate the estimated state or relevant information that will be incorporated into this control structure. The operator $Q$ introduces an extra design freedom to address uncertainties, such that linear active disturbance rejection control (LADRC) can be interpreted as a special case in the Q-structure when a linear extended state observer is used.

关键词： Robust control Q measurement Uncertainty Simulation Observers Robustness Artificial intelligence

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Network Analysis of Facial Behaviours for Non-Contact Driver Distraction Detection

SSRN

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SSRN 2023年

作者： Mohammdian, Amin Bahmani, Zahra Vosogh, Nilofar Research Center for Development of Advanced Technologies Tehran Iran Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

Distraction detection plays an important role in driver safety. We introduced a novel framework to identify the dynamic pattern of facial responses to distracted driving. For this purpose, facial expression signals were extracted from the driver’s video. Due to the cause-and-effect movement of different facial expressions time series, the connectivity analysis was used to extract correlation and causality features. The connectivity was quantified using functional and effective connectivity methods among each pair of facial expression signal. In order to improve the detection of distraction, the connectivity analysis between the time series extracted from facial expressions, has been combined with perinasal perspiration index (PP) extracted from the perinasal area of the face thermal images. Validation was performed using subject independent recognition manner, and the results demonstrated that the proposed method significantly improved distraction detection. The proposed system achieved accuracy of 60.96% in classification between distracted from normal driving. Moreover, the obtained graphs of facial expression flow are effectively visualized by different schemes to show the relationships. Results show that the difference between the sources and sinks relationships was a useful feature to distinguish between normal driving and distraction. © 2023, The Authors. All rights reserved.

关键词： Time series

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Stackable, Storable, Millimeter-Scale Biobatteries Having High Instantaneous Power Outputs 21

Stackable, Storable, Millimeter-Scale Biobatteries Having Hi...

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21st International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications, PowerMEMS 2022

作者： Rezaie, Maryam Elhadad, Anwar Choi, Seokheun at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering New York United States Suny Binghamton Center for Research in Advanced Sensing Technologies & Environmental Sustainability New York United States

ISBN: (纸本)9781665493062

We report a millimeter-sized bacteria-powered biobattery that can generate substantially high-power density (427 μW/cm2) only in 7 minutes after liquid introduction. The biobattery features (i) Bacillus subtilis endospores as a storable, dormant biocatalyst which are primed for quick germination, and (ii) a 3-D graphene hydrogel anode decorated with copper oxide particles for high-power generation. Individual biobattery units are easily stackable in series and three-biobattery pack produces more than enough energy to power a light-emitting diode (LED). This work can release microbial energy technology from its restriction to research settings and translate it to practical real-world applications. © 2022 IEEE.

关键词： Germination

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Multiresource allocation in dynamic MEC systems: a continual learning-based approach 3

Multiresource allocation in dynamic MEC systems: a continual...

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3rd International Conference on Electronic Information engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Zhan, Shutao Mao, Jin Chu, Zhipeng Xiong, Ke Fan, Pingyi Letaief, Khaled B. Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9781510680449

Recently, mobile edge computing (MEC) has been considered as a promising solution to address the challenges arising from the growing computationally intensive applications and limited computation capability of mobile devices. Thus, the resource allocation is crucial for ensuring the system performance of MEC. Recent deep learning-based resource allocation (DLRA) methods achieve preferable performance in real-time. However, in practical scenarios, the number of users often changes, which leads to a decrease in the performance of DLRA methods. Thus, once the number of users changes, the traditional DLRA methods need to retrain their neural networks, which consumes a lot of computing resources. To address this issue, this paper proposes a continual learning-based resource allocation (CLRA) method to jointly optimize multiple resource including offloading decision, power control, time slot assignment and computation resource distribution in MEC system. Our CLRA method is able to avoid forgetting previous knowledge when the number of users in the MEC system changes by selecting a small number of the most representative samples from the past and relearning. Experimental results show that, our proposed CLRA method achieves a better performance than the traditional DLRA method in terms of the higher quality of service's (QoS's) satisfaction rate and the less energy consumption. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Resource allocation

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