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UK/ China Emerging Technologies (UCET)

作者： Shahid Latif Zeba Idrees Zhuo Zou Jawad Ahmad State Key Laboratory of ASIC and System Fudan University Shanghai China School of Computing Edinburgh Napier University Edinburgh EH11 4DY United Kingdom

ISBN: (数字)9781728194882

ISBN: (纸本)9781728194899

Industrial Internet of Things (IIoT) has arisen as an emerging trend in the industrial sector. Millions of sensors present in IIoT networks generate a massive amount of data that can open the doors for several cyber-attacks. An intrusion detection system (IDS) monitors real-time internet traffic and identify the behavior and type of network attacks. In this paper, we presented a deep random neural (DRaNN) based scheme for intrusion detection in IIoT. The proposed scheme is evaluated by using a new generation IIoT security dataset UNSW-NB15. Experimental results prove that the proposed model successfully classified nine different types of attacks with a low false-positive rate and great accuracy of 99.54%. To validate the feasibility of the proposed scheme, experimental results are also compared with state-of-the-art deep learning-based intrusion detection schemes. The proposed model achieved a higher attack detection rate of 99.41%.

关键词： Intrusion detection Neurons Machine learning Neural networks Internet of Things Feature extraction Training

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An Improved Mask R-CNN with Global Context Modeling for Instance Segmentation

An Improved Mask R-CNN with Global Context Modeling for Inst...

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Chinese Automation Congress (CAC)

作者： Yongbin Song Guanghua Chen Jingjing Liu School of Mechatronic Engineering and Automation Shanghai University Shanghai China State Key Laboratory of ASIC and System School of Microelectronics Fudan University

Mask R-CNN is a recently proposed state-of-the-art algorithm for object instance segmentation. However, it is still a challenge to improve the accuracy of Mask R-CNN. In this paper, a novel Mask R-CNN approach is proposed. Firstly, we combine global context modeling with Mask R-CNN by capturing long-range dependencies. Secondly, we extend the Mask R-CNN approach by fusing a new simplified non-local neural network and Squeeze-and-Excitation block, which helps to achieve long-range dependencies and adaptively recalibrate the channel feature response by modeling the interdependence between channels. Numerical comparisons between our improved method and original Mask R-CNN solvers, on COCO 2017 dataset, are presented to demonstrate that our algorithm improves bounding box AP by 1.3% and mask AP by 1.6%.

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Atomic-scale understanding of enhanced polarization of highly strained nanoscale columnar PbTiO3

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Physical Review B 2021年第18期104卷 184111-184111页

作者： Y. Z. Dai L. Lu F. Zhang L. Jin Y. Jiang D. W. Wang Z. P. Li C.-L. Jia State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 China School of Microelectronics & Key Lab of Micro-Nano Electronics and System Integration of Xi'an City Xi'an Jiaotong University Xi'an 710049 China Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons (ER-C) Forschungszentrum Jülich GmbH 52425 Jülich Germany School of Materials Science and Engineering Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing 100083 China

Spontaneous polarization in displacive ferroelectric oxides originates from the separation of positive charge centers from negative charge centers, which is induced by the off-center displacements of cations and anions in unit cells. For hugely strained ferroelectric oxides, understanding the correlation between the off-center displacements and the strain level is a prerequisite for understanding the polarization behavior. In the present work, the off-center displacements of atoms in nanometer columnar PbTiO3 under a strong tensile strain of 13% along the c -axis direction are quantified by quantitative high-resolution transmission electron microscopy. The measured off-center displacement ΔTi−O (0.052 nm) is about 60% larger than the value of unstrained bulk PbTiO3. The experimental results are confirmed by first-principle calculations, leading to a polarization of 122μC/cm2, providing the basis for understanding the enhanced spontaneous polarization of highly strained displacive ferroelectric oxides.

关键词： Electric polarization Ferroelectricity First-principles calculations Microstructure Phase separation Ferroelectrics Thin films Density functional calculations Scanning transmission electron microscopy Strain engineering

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Fabrication of MEMS-based TiO2/SnO2 core-shell nanowires sensor for enhanced H2S sensing

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Ceramics International 2025年

作者： Zheng, Zhi-Wei He, Shi-Ying Huang, Zhan-Yuan Wang, Yi-Wei Zhang, Xiao-Fei Ou, Lang-Xi Zhang, David Wei Yu, Hong-Xiu Lu, Hong-Liang State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics &Systems School of Microelectronics Fudan University Shanghai 200433 China Institutes of Biomedical Science & Shanghai Stomatological Hospital Fudan University Shanghai 200433 China Zhangjiang Fudan International Innovation Center Shanghai 201203 China National Integrated Circuit Innovation Center Shanghai 201203 China Yiwu Research Institute of Fudan University Chengbei Road Zhejiang Yiwu City322000 China

The TiO2/SnO2 core-shell nanowires (NWs) with precisely controlled SnO2 shell thickness were successfully synthesized via facile hydrothermal method and atomic layer deposition (ALD) process. The innovative approach of integrating ALD with hydrothermal synthesis allowed for the precise tuning of the SnO2 shell thickness, which is critical for optimizing gas sensing performance. The sensing performance of the prepared sensor was found to be highly dependent on the SnO2 shell thickness. Notably, the sensor with a 20 nm SnO2 shell exhibited the highest response (Ra/Rg) of 5.9 towards 5 ppm H2S at 300 °C, which was approximately three times higher than that of the pristine TiO2 NWs sensor (∼1.8). This significant enhancement in H2S sensing performance can be attributed to the formation of the TiO2/SnO2 heterojunction and the optimal SnO2 shell thickness, which were further elucidated through chemisorbed oxygen model, heterojunction depletion theory, and bandgap alignment. Additionally, the sensor demonstrated low power consumption (∼100 mW), great selectivity towards H2S, fast response/recovery times (25 s and 173 s, respectively), the ability to detect H2S at low concentrations (200 ppb), high sensitivity, excellent repeatability and remarkable stability (over 10 months). Therefore, the proposed MEMS-based TiO2/SnO2 core-shell NWs gas sensor provides a promising approach for industrial and environmental monitoring applications. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： pH sensors

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From Anomalous to Normal: Temperature Dependence of the Band Gap in Two-Dimensional Black Phosphorus

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Physical Review Letters 2020年第15期125卷 156802-156802页

作者： Shenyang Huang Fanjie Wang Guowei Zhang Chaoyu Song Yuchen Lei Qiaoxia Xing Chong Wang Yujun Zhang Jiasheng Zhang Yuangang Xie Lei Mu Chunxiao Cong Mingyuan Huang Hugen Yan State Key Laboratory of Surface Physics Key Laboratory of Micro- and Nano-Photonic Structures (Ministry of Education) and Department of Physics Fudan University Shanghai 200433 China Institute of Flexible Electronics Northwestern Polytechnical University Xi’an 710072 China Department of Physics Southern University of Science and Technology Shenzhen 518055 China State Key Laboratory of ASIC and System School of Information Science and Technology Fudan University Shanghai 200433 China

The temperature dependence of the band gap is crucial to a semiconductor. Bulk black phosphorus is known to exhibit an anomalous behavior. Through optical spectroscopy, here we show that the temperature effect on black phosphorus band gap gradually evolves with decreasing layer number, eventually turns into a normal one in the monolayer limit, rendering a crossover from the anomalous to the normal. Meanwhile, the temperature-induced shift in optical resonance also differs with different transition indices for the same thickness sample. A comprehensive analysis reveals that the temperature-tunable interlayer coupling is responsible for the observed diverse scenario. Our study provides a key to the apprehension of the anomalous temperature behavior in certain layered semiconductors.

关键词： Band gap Electronic structure 2-dimensional systems Infrared spectroscopy Tight-binding model

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A Flexible DNN Accelerator Design with Layer Pipeline for FPGAs

A Flexible DNN Accelerator Design with Layer Pipeline for FP...

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International Conference on Information Science and Control Engineering (ICISCE)

作者： Weijie You Deming Chen Chang Wu State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China University of Illinois at Urbana-Champaign Urbana USA

ISBN: (数字)9781728157122

ISBN: (纸本)9781728157139

Deep Neural Networks (DNNs) are very effective for image recognition, object detection and tracking. To meet the need of deployment of DNNs, accelerator designs have been proposed, especially for implementation on FPGAs. Layer pipeline is a new technology to improve computation efficiency by reducing latency between layers. In this paper, we propose a group-based DNN pipeline accelerator design for FPGAs. An entire DNN is partitioned into layer groups with pipeline computation within every group. A configurable logic is used to switch between groups instantaneously. Thus, our design can handle any size DNNs on a single FPGA chip. We evaluate our accelerator for Alexnet and VGG16 on a Xilinx ZC706 board. Our experimental results show that we can increase the throughput by 19% and 42% when compared with layer-based accelerators in [1] and [16].

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High Conductance Margin for Efficient Neuromorphic Computing Enabled by Stacking Nonvolatile van der Waals Transistors

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Physical Review Applied 2021年第4期16卷 044049-044049页

作者： Liping Xu (徐丽萍) Hao Xiong (熊浩) Zhichao Fu (付志超) Menghan Deng (邓梦晗) Shuiyuan Wang (王水源) Jinzhong Zhang (张金中) Liyan Shang (商丽燕) Kai Jiang (姜凯) Yawei Li (李亚巍) Liangqing Zhu (朱亮清) Liang He Zhigao Hu (胡志高) Junhao Chu (褚君浩) Technical Center for Multifunctional Magneto-Optical Spectroscopy (Shanghai) Engineering Research Center of Nanophotonics & Advanced Instrument (Ministry of Education) Department of Materials School of Physics and Electronic Science East China Normal University Shanghai 200241 China Center for Advanced Electronic Materials and Devices School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Computer Science and Technology East China Normal University Shanghai 200062 China ASIC & System State Key Laboratory School of Microelectronics Fudan University Shanghai 200433 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan Shanxi 030006 China Shanghai Institute of Intelligent Electronics & Systems Fudan University Shanghai 200433 China

High-performance artificial synaptic devices are key building blocks for developing efficient neuromorphic computing systems. However, the nonlinear and asymmetric weight update of existing devices has restricted their practical applications. Herein, floating gate nonvolatile memory (FG NVM) devices based on two-dimensional (2D) HfS2/h-BN/FG-graphene heterostructures have been designed and investigated as multifunctional NVM and artificial optoelectronic synapses. Benefiting from the FG architecture, the HfS2-based NVM device exhibits competitive performances, such as a high on:off ratio (>105), large memory window (approximately 100 V), excellent charge retention ability (>104s), and robust durability (>103 cycles). Notably, the artificial optoelectronic synapses based on HfS2 FG NVM show an impressive large conductance margin and good linearity, owing to the ultrahigh photoresponsivity and photogain of HfS2. The energy consumption of per spike in our artificial synapse is as low as 0.2 pJ. Therefore, a high recognition accuracy up to 91.5% of the artificial neural network on the basis of our HfS2-based optoelectronic synapse at the system level has been achieved, which is superior to other reported 2D artificial optoelectronic synapses. This work paves the way forward for all 2D material-based memory for developing efficient optogenetics-inspired neuromorphic computing in brain-inspired intelligent systems.

关键词： Electrical conductivity Optoelectronics Synapses 2-dimensional systems Artificial neural networks Transistors Transition metal dichalcogenides Lithography

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Wearable Heterosynapses: Ultralow Power Wearable Heterosynapse with Photoelectric Synergistic Modulation (Adv. Sci. 8/2020)

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Advanced Science 2020年第8期7卷 2070041-2070041页

作者： Tian-Yu Wang Jia-Lin Meng Zhen-Yu He Lin Chen Hao Zhu Qing-Qing Sun Shi-Jin Ding Peng Zhou David Wei Zhang State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai 200433 China

In article number https://***/10.1002/advs.201903480 , Lin Chen, Qing‐Qing Sun, and co‐workers present a wearable 2D artificial heterosynapse for simulating multi‐terminal correlations in biology with two modulation modes–an electronic mode and a photoexcited mode. The artificial heterosynapse exhibits ultrafast speed and ultralow power consumption, providing a path for a neuromorphic computing system owning more excellent processing ability than the human brain to deal with the increasing data samples.

关键词： artificial heterosynapses neuromorphic computing architectures photoelectric synergistic modulation synaptic devices wearable electronics

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Graphene Top-gated Mos2 Phototransistors

Graphene Top-gated Mos2 Phototransistors

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International Conference on asic

作者： Yaochen Sheng Xinyu Chen Fuyou Liao Jianan Deng Jing Wan Wenzhong Bao State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China School of Information Science and Engineering Fudan University Shanghai China

MoS 2 phototransistor has been widely investigated for its high sensitivity to light ranging from visible to near-infrared owing to the layer-dependent bandgap of MoS 2 . However, most of the devices in the previous studies employed a back-gate device structure, which limits its future practical application. Here, we take advantage of the high transparency of atomically thin graphene membrane to propose a top-gate phototransistor structure, in which the graphene acts as the top-gate electrode. Such MoS 2 photodetector exhibits ultrahigh responsivity reaching 1.4×10 5 AW -1 under the 550 nm incident light. The spectral response is also studied under the illumination of wavelength from 300 nm to 1000 nm. Other factors correlated with the lifetime of photogenerated carriers, including source-drain bias, gate bias, incident light intensity, are also systematically investigated.

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An Optimal Actuator Placement Method for Direct-drive Stages to Maximize Control Bandwidth

An Optimal Actuator Placement Method for Direct-drive Stages...

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Annual Conference of Industrial Electronics Society

作者： Runze Ding Chenyang Ding Yunlang Xu Weike Liu Xiaofeng Yang Academy for Engineering and Technology Fudan University Shanghai China School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China State Key Laboratory of ASIC and System Fudan University Shanghai China

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

This paper develops an optimal actuator placement method for direct-drive stages. Control bandwidth of rigid body motion, which is limited by flexible modes, is maximized. According to a reduced-order state-space model of stage dynamics, a dual-loop optimization method is proposed to optimize actuator locations. In the inner loop, a specific control scheme is employed to obtain the maximum control bandwidth, which is used to formulate a cost function. This control scheme is only for optimization, which does not limit the choices of control methods for an optimized stage. In the outer loop, Genetic Algorithm (GA) is employed to minimize the cost function such that the actuator locations are optimized. Compared with existing over-actuation methods, this method has low cost and complexity. Numerical simulations verify the effectiveness of the proposed method.

关键词： Actuators Bandwidth Mathematical model Dynamics Cost function Computational modeling Acceleration

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