检索结果-内蒙古大学图书馆

SSRN 2024年

作者： Liu, Ruochen Xu, Jiawei Hu, Tianxiang Li, Xiang Wang, Kongxiang Huang, Qi Duan, Zhongtao Liu, Hong Qian, Weifan Zhou, Haiting Cong, Chunxiao Yue, Xiaofei Zhang, Hong Xie, Fengxian Institute for Electric Light Sources School of Information Science and Technology Fudan University Shanghai200438 China Department of Materials Science National Engineering Lab for TFT-LCD Materials and Technologies Fudan University Shanghai200433 China Center for Micro Nano Systems School of Information Science and Technology Fudan University Shanghai200438 China State Key Laboratory of ASIC & System School of Information Science and Technology Fudan University Shanghai200438 China State Key Laboratory of Photovoltaic Science and Technology Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai200438 China

Utilizing textured fluorine-doped tin oxides (FTO) as transparent conductive oxide (TCO) substrates is advantageous for capturing incident light, thereby enhancing the power photoelectric conversion efficiency (PCE) of inverted perovskite solar cells (PSCs). However, the roughness of these substrates and uncontrolled nucleation often results in voids at the perovskite-buried surface, leading to insufficient charge extraction and serving as degradation initiation points. This study introduces (S)-3-amino-4-(4-chlorophenyl)butyric acid hydrochloride (AbaCl), which binds to FTO through its anchor group (–COOH) at the deficient regions of MeO-4PACz. Moreover, the chlorine end molecules offer active sites for nucleation by forming halogen bonds with undercoordinated iodide ions (I–). AbaCl also interacts with formamidinium (FA+) in perovskite precursor solution via hydrogen bonding, promoting crystallization at the buried interface. Consequently, nucleation at this buried interface becomes preferential, ensuring bottom-up growth and preventing voids formation due to incomplete solvent evaporation, allowing the perovskite layer to conformally adhere to the substrate without gaps. As a result, the AbaCl-treated inverted PSCs achieved a champion PCE of 24.5% and exhibited enhanced operational stability. This work presents a method for conformally growing perovskite films on textured substrates to produce efficient and stable PSCs. © 2024, The Authors. All rights reserved.

关键词： Hydrogen bonds

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A Matching Based Escape Routing Algorithm with Variable Design Rules and Constraints 23

A Matching Based Escape Routing Algorithm with Variable Desi...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Qinghai Liu Disi Lin Chuandong Chen Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China and Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou Fujian China Department of Microelectronics Fuzhou University Fuzhou China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

Escape routing is a critical problem in PCB routing, and its quality greatly affects the PCB design cost. Unlike the traditional escape routing that works mainly for the BGA package with unique line width and space, this paper presents a high-performance escape routing algorithm to handle problems with variable design rules and manual constraints, including variable line widths/spaces, the neck mode of wires, and the pad entry for differential pairs. We first propose a novel obstacle-avoiding method to project pins to the boundary and construct a channel projection graph. We then construct a bi-projection graph and propose a matching-based hierarchical sequencing algorithm to consider manual constraints. We perform global routing for each pin/differential pair by congestion-avoiding path initialization and rip-up and reroute path optimization. Finally, we complete detailed routing in every face, ensuring the wire angle and pad entry constraints. Experimental results show that our algorithm can achieve 100% routability without any design rule violation for all given industrial PCB instances, while two state-of-the-art routers cannot complete routing.

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Downstream-agnostic Adversarial Examples

arXiv

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arXiv 2023年

作者： Zhou, Ziqi Hu, Shengshan Zhao, Ruizhi Wang, Qian Zhang, Leo Yu Hou, Junhui Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Wuhan University China School of Information and Communication Technology Griffith University Australia Department of Computer Science City University of Hong Kong Hong Kong National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab

Self-supervised learning usually uses a large amount of unlabeled data to pre-train an encoder which can be used as a general-purpose feature extractor, such that downstream users only need to perform fine-tuning operations to enjoy the benefit of "large model". Despite this promising prospect, the security of pre-trained encoder has not been thoroughly investigated yet, especially when the pre-trained encoder is publicly available for commercial use. In this paper, we propose AdvEncoder, the first framework for generating downstream-agnostic universal adversarial examples based on the pre-trained encoder. AdvEncoder aims to construct a universal adversarial perturbation or patch for a set of natural images that can fool all the downstream tasks inheriting the victim pre-trained encoder. Unlike traditional adversarial example works, the pre-trained encoder only outputs feature vectors rather than classification labels. Therefore, we first exploit the high frequency component information of the image to guide the generation of adversarial examples. Then we design a generative attack framework to construct adversarial perturbations/patches by learning the distribution of the attack surrogate dataset to improve their attack success rates and transferability. Our results show that an attacker can successfully attack downstream tasks without knowing either the pre-training dataset or the downstream dataset. We also tailor four defenses for pre-trained encoders, the results of which further prove the attack ability of AdvEncoder. Our codes are available at: https://github. com/CGCL-codes/AdvEncoder. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Cryogenic quasi-static embedded DRAM for energy-efficient compute-in-memory applications

arXiv

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arXiv 2023年

作者： Shu, Yuhao Zhang, Hongtu Sun, Hao Zhang, Mengru Zhao, Wenfeng Deng, Qi Tang, Zhidong Yuan, Yumeng Hu, Yongqi Gu, Yu Kou, Xufeng Ha, Yajun School of Information Science and Technology ShanghaiTech University Shanghai China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China State Key Laboratory of Integrated Chip and System Frontier Institute of Chip and System Fudan University Shanghai China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Department of Electrical and Computer Engineering Binghamton University SUNY BinghamtonNY United States Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China Shanghai Engineering Research Center of Energy Efficient and Custom AI IC Shanghai China

Compute-in-memory (CIM) presents an attractive approach for energy-efficient computing in data-intensive applications. However, the development of suitable memory designs to achieve high-performance CIM remains a challenging task. Here, we propose a cryogenic quasi-static embedded DRAM to address the logic-memory mismatch of CIM. Guided by the re-calibrated cryogenic device model, the designed four-transistor bit-cell achieves full-swing data storage, low power consumption, and extended retention time at cryogenic temperatures. Combined with the adoption of cryogenic write bitline biasing technique and readout circuitry optimization, our 4Kb cryogenic eDRAM chip demonstrates a 1.37×106 times improvement in retention time, while achieving a 75 times improvement in retention variability, compared to room-temperature operation. Moreover, it also achieves outstanding power performance with a retention power of 112 fW and a dynamic power of 108 µW at 4.2 K, which can be further decreased by 7.1% and 13.6% using the dynamic voltage scaling technique. This work reveals the great potential of cryogenic CMOS for high-density data storage and lays a solid foundation for energy-efficient CIM implementations. Copyright © 2023, The Authors. All rights reserved.

关键词： Computation theory

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Learning interpretable deep state space model for probabilistic time series forecasting

arXiv

引用

arXiv 2021年

作者： Li, Longyuan Yan, Junchi Yang, Xiaokang Jin, Yaohui State Key Lab of Advanced Optical Communication System and Network MoE Key Lab of Artificial Intelligence AI Institute Department of Computer Science and Engineering Shanghai Jiao Tong University China

Probabilistic time series forecasting involves estimating the distribution of future based on its history, which is essential for risk management in downstream decision-making. We propose a deep state space model for probabilistic time series forecasting whereby the non-linear emission model and transition model are parameterized by networks and the dependency is modeled by recurrent neural nets. We take the automatic relevance determination (ARD) view and devise a network to exploit the exogenous variables in addition to time series. In particular, our ARD network can incorporate the uncertainty of the exogenous variables and eventually helps identify useful exogenous variables and suppress those irrelevant for forecasting. The distribution of multi-step ahead forecasts are approximated by Monte Carlo simulation. We show in experiments that our model produces accurate and sharp probabilistic forecasts. The estimated uncertainty of our forecasting also realistically increases over time, in a spontaneous manner. © 2021, CC BY.

关键词： state space methods

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A Matching Based Escape Routing Algorithm with Variable Design Rules and Constraints

A Matching Based Escape Routing Algorithm with Variable Desi...

引用

Design Automation Conference

作者： Qinghai Liu Disi Lin Chuandong Chen Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

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Disjoint-Path and Golden-Pin Based Irregular PCB Routing with Complex Constraints 23

Disjoint-Path and Golden-Pin Based Irregular PCB Routing wit...

引用

Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Qinghai Liu Qinfei Tang Jiarui Chen Chuandong Chen Ziran Zhu Huan He Jianli Chen Yao-Wen Chang Center for Discrete Mathematics Fuzhou University Fuzhou China and Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China Center for Discrete Mathematics Fuzhou University Fuzhou China College of Computer and Date Science Fuzhou University Fuzhou China Department of Microelectronics Fuzhou University Fuzhou China Department of Microelectronics Southeast University Nanjing China Hangzhou Huawei Enterprises Telecommunication Technologies Co. Ltd Hangzhou China State Key Lab of ASIC & System Fudan University Shanghai China Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan and Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350323481

PCB routing becomes time-consuming as the complexity of PCB design increases. Unlike traditional schemes that treat the two essential PCB routing processes separately, namely, escape and bus routing, we consider the continuity between them and present a golden-pin-based routing scheme to find the desired solution with angle and topology constraints. Further, conventional rip-up and reroute methods are often ineffective and inefficient for congestion alleviation and routability optimization. We construct a component graph by modeling components as vertices and applying the minimum weight vertex covering method to improve the routability. A self-adaptable ordering method is presented for escape routing to arrange the pin order on the component boundary, guaranteeing successful bus routing. In addition, escape routing is performed based on a disjoint path method. We construct a dynamic Hanan grid in bus routing and utilize a novel congestion adjustment technique to improve solution quality. Compared with FreeRouting and Allegro, the experiment results show that our algorithm achieves high routability and a significant 90% runtime reduction.

关键词： escape routing

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Bayesian Optimization Approach for Analog Circuit Design Using Multi-Task Gaussian Process

Bayesian Optimization Approach for Analog Circuit Design Usi...

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IEEE International Symposium on Circuits and systems

作者： Jiangli Huang Shuhan Zhang Cong Tao Fan Yang Changhao Yan Dian Zhou Xuan Zeng State Key Lab of ASIC & System School of Microelectronics Fudan University China Department of Electrical Engineering University of Texas at Dallas Richardson TX U.S.A

ISBN: (纸本)9781728192017;9781728192024

In this paper, we propose an efficient Bayesian optimization approach for analog circuit synthesis based on the multi-task Gaussian process model. Instead of building the Gaussian process models separately for each circuit specification as the traditional Bayesian optimization methods do, we extend the Gaussian process to a vector-valued function with a shared covariance function to learn the dependencies between different specifications of circuits. The weighted expected improvement function is selected as the acquisition function to cope with the constraints. The experimental results show that the proposed method can reduce the number of simulations while achieving better optimization results.

关键词： Correlation Circuits and systems Optimization methods Gaussian processes Analog circuits Bayes methods Circuit synthesis

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MetaFollower: Adaptable Personalized Autonomous Car Following

arXiv

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arXiv 2024年

作者： Chen, Xianda Chen, Kehua Zhu, Meixin Yang, Hao Shen, Shaojie Wang, Xuesong Wang, Yinhai Guangzhou511400 China Interdisciplinary Programs Office The Hong Kong University of Science and Technology Hong Kong Guangdong Provincial Key Lab of Integrated Communication Sensing and Computation for Ubiquitous Internet of Things Guangzhou511400 China Department of Civil and System Engineering Whiting School of Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong School of Transportation Engineering Tongji University Shanghai201804 China Department of Civil and Environmental Engineering University of Washington SeattleWA98195 United States

Car-following (CF) modeling, a fundamental component in microscopic traffic simulation, has attracted increasing interest of researchers in the past decades. In this study, we propose an adaptable personalized car-following framework - MetaFollower, by leveraging the power of meta-learning. Specifically, we first utilize Model-Agnostic Meta-Learning (MAML) to extract common driving knowledge from various CF events. Afterward, the pre-trained model can be fine-tuned on new drivers with only a few CF trajectories to achieve personalized CF adaptation. We additionally combine Long Short-Term Memory (LSTM) and Intelligent Driver Model (IDM) to reflect temporal heterogeneity with high interpretability. Unlike conventional adaptive cruise control (ACC) systems that rely on predefined settings and constant parameters without considering heterogeneous driving characteristics, MetaFollower can accurately capture and simulate the intricate dynamics of car-following behavior while considering the unique driving styles of individual drivers. We demonstrate the versatility and adaptability of MetaFollower by showcasing its ability to adapt to new drivers with limited training data quickly. To evaluate the performance of MetaFollower, we conduct rigorous experiments comparing it with both data-driven and physics-based models. The results reveal that our proposed framework outperforms baseline models in predicting car-following behavior with higher accuracy and safety. To the best of our knowledge, this is the first car-following model aiming to achieve fast adaptation by considering both driver and temporal heterogeneity based on meta-learning. Copyright © 2024, The Authors. All rights reserved.

关键词： Adaptive cruise control

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Radiation enhanced sensitivity of temperature and curvature sensor based on Bi/Er Co-doped fibre with ultra-broadband emission

引用

Measurement: Journal of the International Measurement Confederation 2025年 254卷

作者： Huang, Zhexu Luo, Yanhua Wen, Jianxiang Wang, Tingyun Mou, Chengbo Chen, Wei Wei, Shuen Zou, Weiwen Sun, Xiaohong Azmi, Asrul Izam Peng, Gang-Ding Institute of Fiber Optics Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai200444 China Institute for Photonics and Advanced Sensing and School of Physical Sciences The University of Adelaide AdelaideSA5005 Australia State Key Laboratory of Advanced Optical Communications System and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Henan Key Laboratory of Laser and Opto-electric Information Technology School of Information Engineering Zhengzhou University Henan450052 China Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru Johor81310 Malaysia Photonics & Optical Communications School of Electrical Engineering UNSW Sydney NSW2052 Australia

To accommodate the growing scale and diverse applications of fibre optic sensing networks, a temperature and curvature sensing system suitable for radiation environment is proposed based on Bi/Er co-doped fibre (BEDF) with offset-core and ultra-broadband emission. First, two sections of BEDFs were employed to construct an ultra-broadband light source and a Mach-Zehnder Interferometer (MZI) for the sensing system, respectively. Then, the sensing performance of the MZI was evaluated through simulations and experiment. Especially, the impact of gamma radiation on sensing characteristics was evaluated by comparing MZI sensors based on irradiated and non-irradiated BEDFs. Both simulations and experiment results confirmed that the sensitivity improved due to an increase of the refractive index for the fibre core of BEDF, attributed to radiation-induced refractive index change. The sensing results indicate that for the irradiated BEDF based sensor, the maximum temperature sensitivity at 1592 nm was up to 90 pm/℃ with an increase of 50 %, while the maximum curvature sensitivity at 1550 nm was 5.66 nm/m−1 with an increase of 226 %, respectively. Such sensitivity enhancement further demonstrates that 50 kGy gamma ray irradiated BEDF had an increase of effective refractive index of 10-3 order. Moreover, the proposed MZI sensing system, featuring a broadband near-infrared emission exceeding 500 nm, exhibits great potential for temperature and curvature detection in the Internet of Things (IoT) and ultra-large-scale sensor networks. © 2025 Elsevier Ltd

关键词： Gamma radiography

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