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Statistical Device Simulation and Machine Learning of Process Variation Effects of Vertically Stacked Gate-All-Around Si Nanosheet CFETs

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IEEE Transactions on Nanotechnology 2024年 23卷 386-392页

作者： Kola, Sekhar Reddy Li, Yiming Butola, Rajat National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

In this study, we report the process variation effect (PVE) including the work function fluctuation (WKF) on the DC/AC characteristic fluctuation of stacked gate-all-around silicon complementary field-effect transistors (CFETs). The PVE affects characteristic fluctuation significantly;in particular, for the variability of off-state current. Owing to the bottom channel of a fin-type, the P-FET suffers from the worst off-state current fluctuation (more than 200% variation) compared to the N-FET. The device variability induced by the WKF is marginal because of amorphous-type metal grains. As input features to an artificial neural network (ANN) model, low and high work function values, as well as parameters of PVE that have prevalent effects on CEFT transfer characteristics are further considered and modeled. The estimated values of R2-score prove that the ANN model properly grasps information from the dataset successfully;thus, it can be used to model emerging CFETs for circuit simulation. © 2002-2012 IEEE.

关键词： Neural networks

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DASA: Delay-Adaptive Multi-Agent Stochastic Approximation

arXiv

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arXiv 2024年

作者： Dal Fabbro, Nicolò Adibi, Arman Poor, H. Vincent Kulkarni, Sanjeev R. Mitra, Aritra Pappas, George J. The Electrical and Systems Engineering Department University of Pennsylvania United States The Department of Electrical and Computer Engineering Princeton University United States The Electrical and Computer Engineering Department North Carolina State University United States

We consider a setting in which N agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume that the up-link transmissions to the server are subject to asynchronous and potentially unbounded time-varying delays. To mitigate the effect of delays and stragglers while reaping the benefits of distributed computation, we propose DASA, a Delay-Adaptive algorithm for multi-agent Stochastic Approximation. We provide a finite-time analysis of DASA assuming that the agents' stochastic observation processes are independent Markov chains. Significantly advancing existing results, DASA is the first algorithm whose convergence rate depends only on the mixing time τmix and on the average delay τavg while jointly achieving an N-fold convergence speedup under Markovian sampling. Our work is relevant for various SA applications, including multi-agent and distributed temporal difference (TD) learning, Q-learning and stochastic optimization with correlated data. © 2024, CC BY.

关键词： Markov chains

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ChatBCI: A P300 Speller BCI Leveraging Large Language Models for Improved Sentence Composition in Realistic Scenarios

arXiv

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arXiv 2024年

作者： Hong, Jiazhen Wang, Weinan Najafizadeh, Laleh Integrated Systems and NeuroImaging Laboratory Department of Electrical and Computer Engineering Rutgers University PiscatawayNJ08854 United States

P300 speller brain computer interfaces (BCIs) allow users to compose sentences by selecting target keys on a graphical user interface (GUI) through the detection of P300 component in their electroencephalogram (EEG) signals following visual stimuli. Most existing P300 speller BCIs require users to spell all or the first few initial letters of the intended word, letter by letter. Consequently, a large number of keystrokes are required to write a sentence, which can be time consuming, increasing user’s cognitive load and fatigue. Therefore, there is a need for more efficient and user-friendly methods for faster, and practical sentence composition. In this work, we introduce ChatBCI, a P300 speller BCI that leverages the zero-shot learning capabilities of large language models (LLMs) to suggest words from user-spelled initial letters or predict the subsequent word(s), reducing keystrokes and accelerating sentence composition. ChatBCI retrieves word suggestions through remote queries to the GPT-3.5 API. A new GUI, displaying GPT-3.5 word suggestions as extra keys is designed. Stepwise linear discriminant analysis (SWLDA) is used for the P300 classification. Seven subjects completed two online spelling tasks: 1) copy-spelling a self-composed sentence using ChatBCI, and 2) improvising a sentence using ChatBCI’s word suggestions. Results demonstrate that in Task 1, on average, ChatBCI outperforms letter-by-letter BCI spellers, reducing time and keystrokes by 62.14% and 53.22%, respectively, and increasing information transfer rate by 198.96%. In Task 2, ChatBCI achieves 80.68% keystroke savings and a record 8.53 characters/min for typing speed. Overall, ChatBCI by employing remote LLM queries enhances sentence composition in realistic scenarios, significantly outperforming traditional spellers without requiring local model training or storage. ChatBCI’s (multi-) word predictions, combined with its new GUI, pave the way for developing next-generation speller BCIs that are e

关键词： Electroencephalography

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The use of long short-term memory models to estimate soybean pricing: a regional climate data evaluation from Brazil

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IEEE Access 2025年 13卷 101869-101884页

作者： Oliva, Jefferson Tales Martelli, Otavio Pigozzo Barbosa, Marco Antonio De Castro Molin, Viviane Dal Casanova, Dalcimar Teixeira, Marcelo Federal University of Technology-Paraná Graduate Program in Electrical and Computer Engineering Pato Branco Brazil Federal University of Technology-Paraná Department of Academic Informatics Pato Branco Brazil Federal University of Technology-Paraná Graduate Program in Production and Systems Engineering Pato Branco Brazil

This work uses machine learning methods to analyze the influence of the Brazilian climate on international soybean price variability. For this purpose, climatic data, historical series of the extended national consumer price index, dollar price historical series, soybean harvest historical series, and international soybean price historical series are collected from different data sources. The data is then preprocessed and grouped by state. Afterward, data from the five most productive Brazilian states, Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS), which together correspond to 74.9% of total production, are chosen. Then, predictive models were built using the long short-term memory (LSTM) method, which is applied to each state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. These models are evaluated using 10-fold sequential split cross-validation, whose predictive results are used for performance comparison through statistical hypothesis testing. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest average values of root mean squared error (RMSE) and mean absolute error (MAE), which are 20.90 and 16.72, respectively. Regarding predictors trained without climate data, the RS and PR obtained the lowest averaged values of RMSE (20.84) and MAE (16.81), respectively. After performing statistical hypothesis tests, no significant differences were found between the models, stating, with certainty 95%, that the Brazilian climatic data did not influence soybean prices in our study. © 2013 IEEE.

关键词： Brazilian Climatic Data Long-Short Term Memory Machine Learning Soybean Time Series

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Optimally Scheduling Single-Arm Multicluster Tools for Manufacturing Hybrid-Type Wafers

Optimally Scheduling Single-Arm Multicluster Tools for Manuf...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Wang, Genghong Zhu, Qinghua Hou, Yan Qiao, Yan Wu, Naiqi Zhou, Mengchu School of Computer Science and Technology Guangdong University of Technology Guangzhou China Institute of Systems Engineering Macau University of Science and Technology Macau China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07920 United States

ISBN: (纸本)9798350337020

In semiconductor manufacturing, multicluster tools are widely employed for many wafer fabrication processes. With the demand for high-mix integrated circuit chips and shrinkage of circuit width, a scheme in which multiple wafer types are fabricated inside multicluster tools is adopted by wafer foundries to make more profits. Multiple wafer types, multiple robots, and wafer residency time constraints make the resulting scheduling problems challenging. This work focuses on scheduling a single-arm multicluster tool to process two wafer types concurrently subject to wafer residency time constraints in which a conventional one-wafer cycle and backward strategy are not efficient. With such properties, several necessary and sufficient conditions are presented to check the feasibility of a periodic schedule. Polynomial-time-complex algorithms are proposed to examine a tool's schedulability and coordinate multiple robots to handle wafers for schedulable scenarios. The cycle time of an obtained schedule can reach the lower bound. A practical example is used to show the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： hybrid-type wafers multicluster tools scheduling semiconductor manufacturing wafer fabrication

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Digital Self-Interference Cancellation in Wideband Star Radio Using an Auxiliary Receiver

Digital Self-Interference Cancellation in Wideband Star Radi...

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2025 IEEE Wireless and Microwave Technology Conference, WAMICON 2025

作者： Ullah, Kefayet Venkatakrishnan, Satheesh Bojja Volakis, John L. Radio-Frequency Communications and Terahertz Laboratory (RFCOM) Department of Electrical and Computer Engineering Florida International University Miami FL-33174 United States

ISBN: (纸本)9798331509606

This paper presents a novel digital self-interference cancellation (DSIC) technique in full-duplex radios supporting simultaneous transmission and reception (STAR). Key to the design approach is the development of a behavioral model of the full-duplex radio front-end at the digital baseband. An auxiliary receiver (RX) chain is deployed to capture the transmitter (TX) chain and the leakage channel response. The leaked signal is digitally reconstructed and analog cancellation is performed at the low-noise amplifier (LNA) input to prevent desensitization. The cancellation algorithm is developed on a 16-nm AMDXilinx radio frequency system-on-chip (RFSoC) incorporating gigasample speed data converters and field programmable gate array (FPGA) on the same chip. The architecture is directly implemented on the programmable logic (PL) and the model coefficients are calculated offline in the ARM processor of the SoC. The hardware demonstration employs a reduced number of off-The-shelf analog components that provide an impressive digital cancellation of 20 dB for a maximum modulation bandwidth of 400 MHz. © 2025 IEEE.

关键词： analog-To-digital converter FPGA full-duplex RFSoC self-interference cancellation STAR transmitter leakage

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Sources of nonlinearity and mitigation of phase noise in MUTC photodetectors at comb-line frequencies

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Optics express 2025年第11期33卷 24130-24140页

作者： Ishraq Md Anjum Ergun Simsek Seyed Ehsan Jamali Mahabadi Thomas F Carruthers Curtis R Menyuk Joe C Campbell David A Tulchinsky Keith J Williams Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 USA Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904 USA Naval Research Laboratory Washington DC 20375 USA

We calculate the phase noise for the first 100 comb line frequencies of two modified uni-traveling-carrier (MUTC) photodetectors. The frequency comb is generated by one-picosecond pulses with a 2-GHz repetition frequency. We observe a non-monotonic increase in the phase noise and investigate its origins. Our model identifies the interplay among the space charge effect, the heterostructure design, and the nonlinear relationship between the electric field and the electron drift current that leads to a complex variation of the phase noise as a function of the comb line frequency. Based on the findings, we present ways to reduce the phase noise of the photodetectors. While the optimal design depends on the desired frequency range of operation, we find a design that can reduce the phase noise over a wide range of comb-line frequencies.

关键词： computer simulation Frequency combs Phase noise Photodetectors Quantum efficiency Shot noise

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Insights into Household Energy Consumption: Disaggregating Cooling and Heating Profiles using Principal Component Analysis 3

Insights into Household Energy Consumption: Disaggregating C...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Loizidis, Stylianos Kourougianni, Fanourios Olympios, Andreas V. Kyprianou, Andreas Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus University of Cyprus Department of Mechanical and Manufacturing Engineering Nicosia Cyprus

ISBN: (纸本)9798350375923

This paper develops a methodology based on Principal Component Analysis (PCA) to disaggregate distinct baseline electricity, heating and cooling components from the daily total electricity consumption data of 68 houses in Cyprus over the course of one year. The results show that the electricity data involves several principal components, with the two main ones accounting for 52.27% and 14.83% of the total variance, representing cooling and heating, respectively. The findings highlight the potential of using PCA for effective energy disaggregation, which could be extended to various building types and communities. By analyzing energy consumption patterns, targeted energy-saving and improved energy efficiency measures can be identified. Future research will compare PCA results with physics-driven building models, explore alternative disaggregation methods, and apply the methodology to broader datasets. © 2024 IEEE.

关键词： cooling disaggregation Energy demand heating principal component analysis

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Formation of quasi-bound states in the continuum in a single deformed microcavity

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Photonics Research 2024年第11期12卷 2651-2659页

作者： SHUAI LIU BO-HAN WU JEFFREY HUANG ZHESHEN ZHANG Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMichigan 48109USA Research Laboratory of Electronics Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA

Bound states in the continuum(BICs)hold significant promise in manipulating electromagnetic fields and reducing losses in optical structures,leading to advancements in fundamental research and practical *** their observation in various optical systems,the behavior of BIC in whispering-gallery-modes(WGMs)optical microcavities,essential components of photonic integrated chips,has yet to be thoroughly *** this study,we propose and experimentally identify a robust mechanism for generating quasi-BIC in a single deformed *** introducing boundary deformations,we construct stable unidirectional radiation channels as leaking continuum shared by different resonant modes and experimentally verify their external strong mode *** results in drastically suppressed leaking loss of one originally long-lived resonance,manifested as more than a threefold enhancement of its quality(Q)factor,while the other short-lived resonance becomes more lossy,demonstrating the formation of Friedrich–Wintgen quasi-BICs as corroborated by the theoretical model and experimental *** research will provide a practical approach to enhance the Q-factor of optical microcavities,opening up potential applications in the area of deformed microcavities,nonlinear optics,quantum optics,and integrated photonics.

关键词： deformed quasi continuum

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