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2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022

作者： Kirschner, Ravi Marangalou, Amin Hazrati Tsuno, Yusuke Guler, Ulkuhan Worcester Polytechnic Institute Department of Electrical and Computer Engineering WorcesterMA01609 United States Kanazawa University Department of Integrative Neurophysiology Ishikawa920-8640 Japan

ISBN: (数字)9781665469173

ISBN: (纸本)9781665469173

Simultaneously measuring several neurotransmitters will allow researchers to determine how these neurotransmitters influence each other before and during the development of neurological conditions. An example would be the monitoring of acetylcholine - a neurotransmitter that creates the cholinergic pathways responsible for cognitive health - and internal calcium concentration. In this work, we propose a tri-color wireless photometry application specific integrated circuit to measure multiple neurotransmitters simultaneously. The proposed optical excitation channel is fully time-multiplexed and can provide an excitation pulse of between 100 uA and 4 mA with a nominal pulse length of 6.66 Hz, whereas the proposed optical recorder is a fully-differential chopping integrator with three separate channels designed for a 250 μs integration window with a 10 nA current input as well as 2.21 pARMS of input-referred noise integrated from 0.5 Hz to 10 kHz. The presented design is simulated in TSMC 180 nm standard CMOS technology. © 2022 IEEE.

关键词： Application specific integrated circuits

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Evaluating the Efficiency of CuInGaSe2 Based Solar Cells: CuSCN Hole Transport Layer (HTL) Effect 3

Evaluating the Efficiency of CuInGaSe2 Based Solar Cells: Cu...

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2024 3rd International Conference on Advances in Modern Physics Sciences and engineering Technology, ICPSET 2024

作者： Zaidi, B. Mekhaznia, N. Ullah, M.S. Al-Dmour, H. Department of Physics Faculty of Material Sciences University of Batna 1 Batna Algeria Department of Material Sciences SESNV-Faculty Echahid Cheikh Larbi Tebessi University Tebessa Algeria Department of Electrical and Computer Engineering Florida Polytechnic University Lakeland United States Department of Physics Faculty of Science Mutah University Mutah61710 Jordan

Copper indium gallium disulfide (CuInGaSe2) or (CIGS) based solar cells are emerging solar cell structures that have attracted significant interest in recent years. In this research, a SCAPS-1D simulator was used to investigate the performance of the proposed CIGS based solar cell under the effect of a copper (I) thiocyanate (CuSCN) hole transport layer (HTL). Different photovoltaic parameters, such as the efficiency, short circuit current density (Jsc) and open-circuit voltage (Voc), are observed with respect to the doping concentration, temperature, and thickness. A comparative study is presented between a hole transport layer (HTL) and without an HTL. The simulation results demonstrate that the HTL has a significant impact and plays a major role in improving the performance of the proposed CIGS solar cell structure compared to that without the HTL. This research outlines a structured guide for both the manufacturing process and achievement of cost-effective, highly efficient solar cells. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Gallium compounds

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Wavefront engineering With Reconfigurable Intelligent Surfaces for Improved Sensing Capabilities in The THz Band

Wavefront Engineering With Reconfigurable Intelligent Surfac...

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IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

作者： Arjun Singh Priyansghu Sen Josep Miquel Jornet Department of Engineering SUNY Polytechnic Institute Utica NY Department of Electrical and Computer Engineering Northeastern University Boston MA

The terahertz (THz) band offers the advantages of mas-sive available bandwidth and small signal wavelengths with revolutionary potential in both communication and sensing applications. However, the increased noise power from the larger bandwidth, as well as the increased path losses due to smaller wavelengths severely restrict the signal-to-noise ratio (SNR). In this light, reconfigurable intelligent surfaces (RISs) have been proposed as breakthrough devices that can be readily scaled up to create high-gain aperture systems, which are likely to have near-field applications. Here, wavefronts specifically engineered within the near field provide opportunities for improved sensing capabilities. Specifically, in this paper, we highlight how the greater depth of focus through Bessel beams can be utilized to improve the resolution capability of THz-band sensing. We numerically derive and show that Bessel beams can help improve target classification due to increased SNR in detection and increase resolution through increased bandwidth exploitation as well.

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Human-as-advisor in the loop for autonomous lane-keeping

Human-as-advisor in the loop for autonomous lane-keeping

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American Control Conference (ACC)

作者： Rene Mai Sandipan Mishra Agung Julius Department of Mechanical Aerospace and Nuclear Engineering Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY

This paper presents a human-as-advisor architecture for shared human-machine autonomy in dynamic systems. In the human-as-advisor architecture, the human provides suggested control actions to the autonomous system; the system uses a model of the human controller to ascertain the system’s state as perceived by the human. The system combines this information with additional sensor measurements, yielding an improved state estimate. We apply this architecture to the problem of lane-centering an autonomous vehicle in the presence of conflicting lane markings that render the true lane center uncertain. We model conflicting lane markings with a multi-component Gaussian mixture model. The human-suggested course of action is interpreted as an additional sensor measurement, which a Kalman filter is designed to combine with a speedometer and camera for improving the state estimate. With human input from our human-as-advisor architecture, the vehicle centers itself in the lane; without human input, the vehicle does not center itself. We also demonstrate the human-as-advisor architecture is robust to additive output matrix uncertainty and non-linear perturbations in the human model used to interpret the human-suggested control actions.

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Alpha Mini Social Robot as a Fitness Trainer at Home

Alpha Mini Social Robot as a Fitness Trainer at Home

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Berardina De Carolis Giuseppe Palestra Mario Bochicchio Stefano Mazzoleni Department of Computer Science University of Bari A. Moro Italy Department of Electrical and Information Engineering of Polytechnic University of Bari (DEI-POLIBA)

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Engaging in regular exercise offers numerous mental and physical health benefits. Many people, after the Covid-19 pandemic, started to work out at home. However, performing exercises incorrectly can result in injuries. For this reason, technology can be an effective tool for encouraging physical activity at home, and social robots have emerged as a potential solution for providing fitness training in a safe and engaging manner. A physical robot is often perceived as more socially attractive compared to virtual agents. Despite the growing popularity and existing literature on social robotics-based fitness solutions, there is a lack of research examining the accuracy of these systems and interventions at home during physical exercise recognition. In this paper, we propose a novel approach utilizing the Ubtech alpha mini social robot, which possesses motor capabilities to demonstrate exercises. We endowed the robot with the capability to recognize exercise correctness and motivate users to engage in physical activities. In this project, first of all, a new dataset of physical exercises was created, including 1,500 videos of physical exercises. Then, a new approach to recognize physical exercises from image sequences was presented. This method was implemented in a personal social robot to recognize physical exercises using a deep learning model. The results of the study validate the effectiveness of the system in recognizing physical exercises through the camera onboard a personal social robot.

关键词： Training Deep learning Image recognition Pandemics Social robots Robot vision systems Motors Image sequences Injuries Videos

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Zero-shot cross-lingual name retrieval for low-resource languages 2

Zero-shot cross-lingual name retrieval for low-resource lang...

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2nd Workshop on Deep Learning Approaches for Low-Resource Natural Language Processing, DeepLo@EMNLP-IJCNLP 2019

作者： Blissett, Kevin Ji, Heng Computer Science Department Rensselaer Polytechnic Institute Department of Computer Science Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign

ISBN: (纸本)9781950737789

In this paper we address a challenging cross-lingual name retrieval task. Given an English named entity query, we aim to find all name mentions in documents in low-resource languages. We present a novel method which relies on zero annotation or resources from the target language. By leveraging freely available, cross-lingual resources and a small amount of training data from another language, we are able to perform name retrieval on a new language without any additional training data. Our method proceeds in a multi-step process: first, we pretrain a language-independent orthographic encoder using Wikipedia inter-lingual links from dozens of languages. Next, we gather user expectations about important entities in an English comparable document and compare those expected entities with actual spans of the target language text in order to perform name finding. Our method shows 11.6% absolute F-score improvement over state-of-the-art methods. © 2019 Association for Computational Linguistics

关键词： Zero-shot learning

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TeMPO: Efficient Time-Multiplexed Dynamic Photonic Tensor Core for Edge AI with Compact Slow-Light Electro-Optic Modulator

arXiv

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arXiv 2024年

作者： Zhang, Meng Yin, Dennis Gangi, Nicholas Begović, Amir Chen, Alexander Huang, Zhaoran Rena Gu, Jiaqi Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

Electronic-photonic computing systems offer immense potential in energy-efficient artificial intelligence (AI) acceleration tasks due to the superior computing speed and efficiency of optics, especially for real-time, low-energy deep neural network (DNN) inference tasks on resource-restricted edge platforms. However, current optical neural accelerators based on foundry-available devices and conventional system architecture still encounter a performance gap compared to highly customized electronic counterparts. To bridge the performance gap due to lack of domain specialization, we present a time-multiplexed dynamic photonic tensor accelerator, dubbed TeMPO, with cross-layer device/circuit/architecture customization. At the device level, we present foundry-compatible, customized photonic devices, including a slow-light electro-optic modulator with experimental demonstration, optical splitters, and phase shifters that significantly reduce the footprint and power in input encoding and dot-product calculation. At the circuit level, partial products are hierarchically accumulated via parallel photocurrent aggregation, lightweight capacitive temporal integration, and sequential digital summation, considerably relieving the analog-to-digital conversion bottleneck. We also employ a multi-tile, multi-core architecture to maximize hardware sharing for higher efficiency. Across diverse edge AI workloads, TeMPO delivers digital-comparable task accuracy with superior quantization/noise tolerance. We achieve a 368.6 TOPS peak performance, 22.3 TOPS/W energy efficiency, and 1.2 TOPS/mm2 compute density, pushing the Pareto frontier in edge AI hardware. This work signifies the power of cross-layer co-design and domain-specific customization, paving the way for future electronic-photonic accelerators with even greater performance and efficiency. Copyright © 2024, The Authors. All rights reserved.

关键词： Memory architecture

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Phase- and Angle-Sensitive Terahertz Hot-Electron Bolometric Plasmonic Detectors Based on Fets with Graphene Channel and Composite H-BN/Black-P/H-BN Gate Layer

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International Journal of High Speed Electronics and Systems 2024年第4期33卷

作者： Ryzhii, Victor Tang, Chao Otsuji, Taiichi Shur, Michael S. Ryzhii, Maxim Mitin, Vladimir Research Institute For Electrical Communication Tohoku University Miyagi Sendai980-8577 Japan Department Of Electrical Computer And Systems Engineering Rensselaer Polytechnic Institute TroyNY United States Department Of Computer Science And Engineering University Of Aizu Aizu-Wakamatsu Fukushima965-8580 Japan Department Of Electrical Engineering University At Buffalo Suny BuffaloNY United States

In this paper, we propose and analyze the terahertz (THz) bolometric vector detectors based on the graphene-channel field-effect transistors (GC-FET) with the black-P gate barrier layer or with the composite b-BN/black-P/b-BN gate layer. The phase difference between the signal received by the FET source and drain substantially affects the plasmonic resonances. This results in a resonant variation of the detector response on the incoming THz signal phase shift and the THz radiation angle of incidence. © 2024 World Scientific Publishing Company.

关键词： Graphene

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Determination of Parameters of Time-delayed Embedding Algorithm Using Koopman Operator-based Model Predictive Frequency Control

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CSEE Journal of Power and Energy Systems 2021年第6期7卷 1140-1151页

作者： Xiawen Li Chetan Mishra Shichao Chen Yajun Wang Jaime De La Ree Dominion Energy RichmondVAUSA Thorlabs Quantum Electronics. JessupMDUSA Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State UniversityBlacksburgVAUSA

Power systems around the world have been registering a degenerating inertial response in view of the growth of inverter-based resources along with the withdrawal of conventional coal ***,there is a need for swift frequency support and its control,preferably by means of power electronic-interfaced storage devices,owing to their beneficial *** being particularly efficient,pragmatically,the traditional model-based non-linear control techniques are not highly popular in power system control design,primarily due to the complications faced in obtaining accurately suitable models for certain power system ***,the modelfree Koopman operator-based model predictive control(KMPC)has proven to be highly conducive for data-driven non-linear control *** principle behind KMPC is to change the coordinates in a manner to get an approximately linear model,which can then be controlled using a linear model predictive *** this study,we employed time-delayed embedding of measurements to reconstruct a new set of preferable coordinates,thereby suggesting an approach for finding the optimal number of time lags and the embedding dimensions which are the key parameters of this *** efficacy of this KMPC framework is established by adopting a decentralized frequency control problem through a decoupled synchronous machine system,which we proposed for both the Kundur two-area system as well as the IEEE 39-bus test system.

关键词： False nearest neighbors koopman operator model predictive control non-linear control time-delayed embedding

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FAKEY: Fake Hashed Key Attack on Payment Channel Networks

FAKEY: Fake Hashed Key Attack on Payment Channel Networks

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IEEE Conference on Communications and Network Security (CNS)

作者： Alvi Ataur Khalil Mohammad Ashiqur Rahman Hisham A. Kholidy Department of Electrical and Computer Engineering Florida International University USA Department of Network and Computer Security SUNY Polytechnic Institute USA

Although blockchain’s immutability and decentralized capabilities make monetary transactions more secure than ever, its inherent scalability problem hinders its utilization in myriad applications. Payment channel networks (PCNs), one of the prominent solutions to blockchain’s scalability issue, reduce the load on the blockchain by performing the transactions offchain. However, malicious PCN participants can delay the block delivery by slightly misbehaving in the initialization phase. In this work, we introduce FAKEY, a fake hashed key-based attack on PCN that can block up a whole set of channels carrying a transaction for a certain period (via collateral lock), depending on the hashed timelock contract (HTLCs) in the attacked payment path. For the targeted attack setup, the effect of the FAKEY is more severe, as PCN throughput can be reduced significantly. Moreover, the attacker can gain direct monetary benefit by carefully choosing one or more victim nodes. We utilize one of the state-of-the-art PCN simulators, PCN sim, to perform multiple experiments with different attack strategies and calculate profit accumulation scenarios. To demonstrate the attack impacts in detail, we perform a couple of case studies using the simulator. Finally, to validate the attack effect and adversarial benefits in a real-world PCN, we utilize the Bitcoin Lightning Network snapshots spanning over a period of 18 months and calculate the exact monetary impact in satoshi units.

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