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Reconfigurable logic circuits and rectifier based on two-terminal ionic homojunctions

Device 2025年第5期3卷

作者： Zhong, Zhipeng Cheng, Xin Song, Wenqing Yang, Qianyi Li, Xiang Wang, Yuyang Wang, Wan Zhuang, Yezhao Chen, Yan Shi, Wu Lin, Tie Meng, Xiangjian Huang, Hai Wang, Jianlu Chu, Junhao State Key Laboratory of Photovoltaic Science and Technology Shanghai Frontiers Science Research Base of Intelligent Optoelectronic and Perception Institute of Optoelectronics and Department of Material Science Fudan University Shanghai 200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai 201210 China State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai 200083 China Frontier Institute of Chip and System Fudan University Shanghai 200433 China

Reconfigurable logic devices that can perform multiple functions with fewer components offer a solution for increasing data processing demands. Achieving reconfigurability without complex designs, however, remains challenging. In this study, we present a two-terminal reconfigurable homojunction device based on ionic-conducting CuInP₂S₆ (CIPS). The device achieves tunable and reversible rectification by controlling Cu migration under an electric field. The homojunction is formed by modulating the contact potential of the CIPS channel, resulting in an asymmetric contact barrier. The resulting device has a rectification ratio of up to 4 × 10⁴, an ultra-low leakage current (∼100 fA), and a high breakdown voltage of 170 V, maintaining read stability over 3,000 cycles. It operates at frequencies up to 10 kHz and can be reconfigured as OR and AND logic states depending on the Cu migration direction of the CIPS homojunction. © 2025 The Author(s)

关键词： copper indium thiophosphate DTI-2: Explore ionic conductor photovoltaic reconfigurable homojunction

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Contrasting lake changes in Tibet revealed by recent multi-modal satellite observations

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Science of the Total Environment 2024年 908卷 168342页

作者： Ran, Jiangjun Liu, Lin Zhang, Guoqing Shum, C.K. Qiu, Jiahui Hu, Ruigang Li, Jianping Peng, Junhuan Hwang, Cheinway Luan, Yi Sun, Yue Xu, Min Chen, Dingmei Ding, Jun Zhong, Yulong Department of Earth and Space Sciences Southern University of Science and Technology Shenzhen China Earth System Science Programme Faculty of Science The Chinese University of Hong Kong Hong Kong Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing China Division of Geodetic Science School of Earth Sciences Ohio State University ColumbusOH United States State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan China Key Laboratory of Physical Oceanography Academy of the Future Ocean College of Oceanic and Atmospheric Science Ocean University of China Qingdao China Laboratory for Ocean Dynamics and Climate Pilot Qingdao National Laboratory for Marine Science and Technology Qingdao China School of Land Science and Technology China University of Geosciences Beijing China Department of Civil Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan State Key Laboratory of Cryospheric Science Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences Lanzhou China Shannan Meteorological Service of Tibet Shannan China Wuhan China

The limited anthropogenic activities on the Tibetan Plateau make this an ideal natural laboratory to elucidate how climate change impacts lake changes. Previous studies have mainly focused on decadal lake changes, yet their rapid evolutions at short temporal intervals and the associated atmospheric origins remain elusive. Here, we produce a new lake area change dataset at monthly sampling over 2015–2020 from 16,801 satellite images. Our estimates achieve an accuracy of © 2023

关键词： Lakes

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MCDS: An Effective Multi-UAV Collaborative Decision-Making system in Mobile Edge computing Networks

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IEEE Internet of Things Journal 2025年

作者： Xiong, Naixue Zhong, Weiyu Chen, Yuxiang He, Dacheng Li, Yuhui Chen, Linshu Liang, Wei Sanya Research Institute of Hunan University of Science and Technology School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology China Sanya Research Institute of Hunan University of Science and Technology Hunan University School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Information Science and Engineering China The Hong Kong Polytechnic University Department of Computing Hong Kong

Mobile Edge computing (MEC) pushes computing resources from the network center to the network edge to provide efficient and reliable computing services. However, due to the mobility and diversity of mobile users (MUs), edge servers (ESs) are likely to be overloaded, which leads to a rapid decline in the quality of service provided by the MEC system. This paper introduces unmanned aerial vehicles (UAVs) to solve the problem of ES overload. This paper presents an effective Multi-UAV Collaborative Decision-Making system (MCDS) tailored to optimize task offloading and resource allocation in MEC networks. The proposed system seeks to reduce task computing delays and energy consumption while guaranteeing timely task completion and compliance with resource constraints. We design a distributed two-stage optimization algorithm to jointly optimize the task offloading decision and resource allocation of the collaborative computing system (UAVs, ESs, and MUs). To address the flight cooperation problem of multi-UAVs, we also proposed a task-aware scheduling algorithm for multi-UAVs. In addition, we conducted a large number of simulation experiments. Experimental results show that our two-stage optimization scheme is lower than other benchmark algorithms in terms of task completion delay, energy consumption and total cost of objective function. Specifically, compared with seven baseline algorithms under three different system setting scenarios, our algorithm reduces the total cost by an average of 38.79%, the energy consumption by an average of 40.70%, and the delay by an average of 15.67%. © 2014 IEEE.

关键词： Drones

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Bridge the vision gap from field to command: A deep learning network enhancing illumination and details

arXiv

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arXiv 2021年

作者： Jiang, Zhuqing Liu, Chang Wang, Ya'nan Li, Kai Men, Aidong Wang, Haiying Luo, Haiyong Beijing University of Posts and Telecommunications China Beijing Key Laboratory of Network System and Network Culture China Institute of Computing Technology Chinese Academy of Sciences China

With the goal of tuning up the brightness, low-light image enhancement enjoys numerous applications, such as surveillance, remote sensing and computational photography. Images captured under low-light conditions often suffer from poor visibility and blur. Solely brightening the dark regions will inevitably amplify the blur, thus may lead to detail loss. In this paper, we propose a simple yet effective two-stream framework named NEID to tune up the brightness and enhance the details simultaneously without introducing many computational costs. Precisely, the proposed method consists of three parts: Light Enhancement (LE), Detail Refinement (DR) and Feature Fusing (FF) module, which can aggregate composite features oriented to multiple tasks based on channel attention mechanism. Extensive experiments conducted on several benchmark datasets demonstrate the efficacy of our method and its superiority over state-of-the-art methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Luminance

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DSP Assembler Auto-Generation Technique and ToolChain Integration

DSP Assembler Auto-Generation Technique and ToolChain Integr...

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International Conference on Communication technology (ICCT)

作者： Wanli Wang Jun Wu Haoqi Ren Zhifeng Zhang Electronics and Information Engineering College Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9781665432078

To promote the application of DSP, a fast and accurate toolchain generation method must be realized. Unlike the traditional manual method, in this paper, we propose a toolchain generation algorithm based on the architecture description language, and migrate the toolchain to adapt to the specified processor architecture. The algorithm uses the DSP architecture description as input to generate intermediate expressions, then uses lexical analysis and syntax analysis tools to migrate the assembly toolchain. In addition, an integrated development environment is developed based on Eclipse, which creates a friendly human-computer interface. Experiments show that this toolchain generation algorithm runs fast and accurately, which solves problems of the development and application of the DSP toolchain, and creates favorable conditions for the promotion of DSP.

关键词： Human computer interaction Microprocessors Conferences Manuals Syntactics Libraries Communications technology

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Size-Invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection

arXiv

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arXiv 2024年

作者： Li, Feiran Xu, Qianqian Bao, Shilong Yang, Zhiyong Cong, Runmin Cao, Xiaochun Huang, Qingming Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Sun Yat-Sen University Shenzhen Campus China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Human motion recognition by three-view kinect sensors in virtual basketball training

Human motion recognition by three-view kinect sensors in vir...

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2020 IEEE Region 10 Conference, TENCON 2020

作者： Yao, Baoqi Gao, Hui Su, Xin Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing China

ISBN: (纸本)9781728184555

In recent years, human action recognition has received a considerable amount of research attention because of it's potential in a variety of applications, such as video surveillance, human-computer interaction, and virtual reality (VR). However, many researches on human action recognition performed in single-camera or double-camera system, which achieve reduced performance due to vulnerability to partial occlusion and miss-recognition of back. Some works on human action recognition use multiple cameras but are too complex for practical application. In this paper, we propose a new human action recognition system using triple Kinect sensors for VR application. Particularly, we design a mark detection method to determine the front of user and fusion skeleton data in real time. Features are extracted from three-dimensional (3D) skeleton data sequences, and divided into five parts according to body parts. A classification model based on the part-aware long short-term memory networks is proposed to recognize human motion. Finally, we demonstrate the system with a virtual reality basketball application and the results of experiment validate the feasibility of the proposed system. © 2020 IEEE.

关键词： Virtual reality

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Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction

arXiv

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arXiv 2023年

作者： Li, Qi Shen, Ziyi Li, Qian Barratt, Dean C. Dowrick, Thomas Clarkson, Matthew J. Vercauteren, Tom Hu, Yipeng Centre for Medical Image Computing Wellcome/EPSRC Centre for Interventional and Surgical Sciences Department of Medical Physics and Biomedical Engineering University College London London United Kingdom State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China School of Biomedical Engineering & Imaging Sciences King’s College London London United Kingdom

Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In this paper, we first investigated two identified contributing factors of the learned inter-frame correlation that enable the DNN-based reconstruction: anatomy and protocol. We propose to incorporate the ability to represent these two factors - readily available during training - as the privileged information to improve existing DNN-based methods. This is implemented in a new multitask method, where the anatomical and protocol discrimination are used as auxiliary tasks. We further develop a differentiable network architecture to optimise the branching location of these auxiliary tasks, which controls the ratio between shared and task-specific network parameters, for maximising the benefits from the two auxiliary tasks. Experimental results, on a dataset with 38 forearms of 19 volunteers acquired with 6 different scanning protocols, show that 1) both anatomical and protocol variances are enabling factors for DNN-based US reconstruction;2) learning how to discriminate different subjects (anatomical variance) and predefined types of scanning paths (protocol variance) both significantly improve frame prediction accuracy, volume reconstruction overlap, accumulated tracking error and final drift, using the proposed algorithm. © 2023, CC BY.

关键词： Deep neural networks

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Poisoning as a Post-Protection: Mitigating Membership Privacy Leakage From Gradient and Prediction of Federated Models

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IEEE Transactions on Dependable and Secure computing 2025年

作者： Liu, Gaoyang Xu, Tianlong Yang, Yang Abdelmoniem, Ahmed M. Wang, Chen J., Liu Huazhong University of Science and Technology Hubei Key Laboratory of Internet of Intelligence School of Electronic Information and Communications Wuhan430074 China Simon Fraser University School of Computing Science BurnabyBCV5A 1S6 Canada Ministry of Education Key Laboratory of Intelligent Sensing System and Security China Hubei University School of Artificial Intelligence Wuhan430062 China Queen Mary University of London School of Electronic Engineering and Computer Science United Kingdom

Federated learning (FL) is a distributed learning paradigm that enables multiple clients to train a unified model without sharing their private data. However, recent works demonstrate that FL models are vulnerable to membership inference attacks (MIAs), which can infer whether a data sample was used to train a given FL model. Existing countermeasures either require far-reaching modifications of FL training process or enforce extra processing in prediction phase, yielding them unlikely to be applied well in practice. In this paper, we design a post-protection mechanism, dubbed P2-Protection, which degrades the inference performance of MIAs by simultaneously poisoning the prediction and gradient of the target FL model to reduce the privacy leakage of training data while keeping the model prediction accuracy. P2-Protection only involves one additional training round to embed the poisoned prediction and gradient into the target FL model, without requiring model retraining or training process modification. We evaluate P2-Protection and compare it with two state-of-the-art defenses against three MIAs on five realistic datasets. Experimental results show that P2-Protection outperforms the existing defenses by offering limited implement overhead and improved utility-privacy trade-off. © 2004-2012 IEEE.

关键词： Federated learning

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Construction and Application of Protein-Protein Interaction Knowledge Graph 9th

Construction and Application of Protein-Protein Interaction ...

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9th International Symposium on Artificial Intelligence and Robotics, ISAIR 2024

作者： Xiong, Jing Wang, Xiaohong Dou, Fangkun Cao, Haowei Hong, Tenglong Li, Zhiwei Jing, Xiaoli School of Computer Science Qufu Normal University Rizhao276827 China Shandong Foreign Trade Vocational College Qingdao266100 China Rizhao-Qufu Normal University Joint Technology Transfer Center Rizhao276827 China Institute of Oceanology Chinese Academy of Sciences Qingdao266071 China Jinan250101 China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan250101 China China Everbright Bank Qingdao R&D Center Qingdao266071 China Rizhao Medical Insurance Service Center Rizhao276826 China Department of Information Research Qingdao Marine Science and Technology Center Qingdao266237 China

ISBN: (纸本)9789819629107

With the rapid advancement of emerging technologies such as high-throughput sequencing, cryo-electron microscopy, mass spectrometry, and artificial intelligence, our understanding of protein interactions has deepened significantly, leading to an increasing demand for effective data integration. This study tackles the complexity of protein interaction networks and the challenges associated with data integration by employing a top-down approach. It utilizes a protein ontology as the semantic framework, integrates resources from the BioGRID and UniProt databases, and constructs a comprehensive protein-protein interaction knowledge graph (PPIKG). This knowledge graph not only provides an intuitive, graphical interface for visualizing intricate protein interactions but also serves as a centralized platform for downloading protein interaction data. It acts as a one-stop solution for scientists aiming to explore and comprehend the complex landscape of protein interactions. With its user-friendly visualization and efficient download tools, the knowledge graph simplifies the data acquisition process, thereby fostering a deeper, holistic understanding of protein interaction networks among researchers. This innovative approach to data integration is set to accelerate scientific discovery and enhance our comprehension of biological systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Knowledge graph

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