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Learnable antinoise-receiver algorithm based on a quantum feedforward neural network in optical quantum communication

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Physical Review A 2022年第5期105卷 052427-052427页

作者： Zhiguo Qu Xinzhu Liu Le Sun Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer Science Nanjing University of Information Science and Technology Nanjing 210044 China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing 210044 China Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China

The quantum communication process usually consists of three stages: the sender who prepares encoded carriers, the transmission in noisy channels, and the quantum receivers. The transmitted quantum information can be inevitably affected by kinds of quantum noise in the environment. Thus, quantum protocols are extensively studied to improve communication efficiency and accuracy under the influence of quantum noise. The optimization strategies usually occur in these three stages. In this paper, we focus on the optimization strategy of quantum receivers in the third stage. In quantum receiver algorithms, the key to distinguish received non-orthogonal coherent states in free-space optical quantum communication is to construct an optimum displacement operator for transforming the current coherent state into a state that is easier to distinguish than before. To improve the antinoise ability and accuracy of quantum communication, this paper proposes a universal optimization strategy of quantum receivers called learnable antinoise receiver (LAN receiver). In this strategy, a parametrized quantum circuit is constructed as a quantum feedforward neural network as the displacement operator to improve the antinoise ability. The parameters used in the quantum circuit are updated by gradient descent continuously to find the best parameter combination of the quantum circuit that minimizes the error rate and the qubits affected by quantum noise are used as training and testing data. The simulation of the proposed algorithm shows that the LAN receiver can resist different kinds of strong quantum noise. The average error rate of the proposed algorithm LAN receiver under the strong noise channel is 0.18, which has better performance than other type of receivers under the influence of strong quantum noise.

关键词： Machine learning Quantum communication Quantum computation Quantum networks Quantum simulation

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An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

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Signal Transduction and Targeted Therapy 2021年第5期6卷 1585-1600页

作者： Yiyue Ge Tingzhong Tian Suling Huang Fangping Wan Jingxin Li Shuya Li Xiaoting Wang Hui Yang Lixiang Hong Nian Wu Enming Yuan Yunan Luo Lili Cheng Chengliang Hu Yipin Lei Hantao Shu Xiaolong Feng Ziyuan Jiang Yunfu Wu Ying Chi Xiling Guo Lunbiao Cui Liang Xiao Zeng Li Chunhao Yang Zehong Miao Ligong Chen Haitao Li Hainian Zeng Dan Zhao Fengcai Zhu Xiaokun Shen Jianyang Zeng Institute for Interdisciplinary Information Sciences Tsinghua UniversityBeijingChina NHC Key laboratory of Emeric Pathogenic Microbiology Jiangsu Provincial Center for Diseases Control and PreventionNanjingJiangsu ProvinceChina Shanghai Institute of Materia Medica Chinese Academy of SciencesShanghaiChina Silexon Al Technology Co. Ltd.NanjingJiangsu ProvinceChina Department of Computer Science University of Illinois at Urbana-ChampaignIllinoisILUSA School of Pharmaceutical Sciences Tsinghua UniversityBeijingChina School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanHubei ProvinceChina Institute of Pathology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina Department of Automation Tsinghua UniversityBeijingChina Inner Mongolia Alashan League Organization Establishment Committee Office Electronic Support Center AlashanInner MongoliaChina Convalife(Shanghai)Co. Ltd.ShanghaiChina Advanced Innovation Center for Human Brain Protection Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Beijing Advanced Innovation Center for Structural Biology Tsinghua-Peking Joint Center for Life SciencesDepartment of Basic Medical SciencesSchool of MedicineTsinghua UniversityBeijingChina Center for Global Health Nanjing Medical UniversityNanjingJiangsu ProvinceChina

The global spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)requires an urgent need to find effective therapeutics for the treatment of coronavirus disease 2019(COVID-19).In this study,we developed an integrative drug repositioning framework,which fully takes advantage of machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph,literature and transcriptome data to discover the potential drug candidates against *** in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1(PARP1)inhibitor,CVL218,currently in Phase I clinical trial,may be repurposed to treat *** in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic *** addition,we showed that CVL218 can interact with the nucleocapsid(N)protein of SARS-CoV-2 and is able to suppress the LPS-induced production of several inflammatory cytokines that are highly relevant to the prevention of immunopathology induced by SARS-CoV-2 infection.

关键词： prevention respiratory acute

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Shock waves in the magnetic reconnection in the flares on the accretion disk of the SGR~A*

arXiv

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arXiv 2024年

作者： Zhao, Tian-Le Li, Xiao-Feng Tang, Ze-Yuan Rajiv, Kumar Center For Astrophysics Guangzhou University Guangdong Guangzhou510006 China Great Bay Center National Astronomical Data Center Guangdong Guangzhou510006 China Astronomy Science and Technology Research Laboratory Department of Education of Guangdong Province Guangzhou510006 China CAS Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Hefei230026 China School of Computer Science and Information Engineering Changzhou Institute of Technology Jiangsu Changzhou213032 China Harish-Chandra Research Institute Uttar Pradesh Prayagraj211019 India

Sgr A* often shows bright, episodic flares observationally, the mechanism of the flares intermittent brightening is not very clear. Many people believe the flares may formed by the non-thermal particles, which can be a consequence of the magnetic reconnection and shock waves. In this work, we use the larger magnetic loop in the presence of pseudo-Newtonian potential which mimics general relativistic effects. The simulation results show that the reconnection of magnetic field lines passes through a current sheet, which bifurcates into two pairs of slow shocks. We also find the shock waves heat the plasma, especially when the plasma density is low. The shock wave heating effect by the magnetic reconnection is confirmed by the simulation results, and thus the process of instantaneous brightening of the flares on the accretion disk can be explained. © 2024, CC BY.

关键词： Magnetohydrodynamics

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Invulnerability Optimization of Communication Network Based on Analog Attack Strategy

Invulnerability Optimization of Communication Network Based ...

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作者： Lingling Xia Xueli Ni Zhengjun Jing Jiayin Liu Yan Zhang Department of Computer Information and Cyber Security Jiangsu Police Institute Jiangsu Province Electronic Data Forensics and Analysis Engineering Research Center Key Laboratory of Digital Forensics of Jiangsu Provincial Public Security Department College of Computer Engineering Jiangsu University of Technology

Invulnerability of communication networks directly related to security and reliability of networks has received increasing attention in recent years. In order to enhance the destruction resisting capacity of communication network,we propose a new invulnerability optimization method based on analog attack strategy and present an improved invulnerability measure with consideration of network connectivity and construction cost. The experimental simulations are conducted to construct four different optimized communication networks using analog attack strategy with different indicators of node centrality on the initial network respectively. Results demonstrate that the improved metric used to evaluate the economic benefits of network invulnerability is reasonable, and the proposed topology optimization method can improve the invulnerability of communication network.

关键词： Invulnerability optimization Structural optimization Analog attack Communication network

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An Incentive Mechanism Considering Privacy Metric for Personalized Application

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IEEE Transactions on Consumer Electronics 2025年

作者： Xie, Yun Li, Peng Zhang, Jindan Attar, Razaz Waheeb Arya, Varsha Gupta, Brij B. Nanjing Vocational College of Information Technology Jiangsu Province Service Customization Network Application Engineering Research Center Jiangsu Province Service Customization Network Application Engineering Research Center Nanjing210023 China Nanjing University of Posts and Telecommunications School of Computer Science Nanjing210023 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing210023 China Xianyang Polytechnic Institute China Princess Nourah bint Abdulrahman University College of Business Administration Management Department Riyadh11671 Saudi Arabia Hong Kong Metropolitan University Hong Kong Hong Kong Center for Interdisciplinary Research Dehradun India Asia University Department of Computer Science and Information Engineering Taichung413 Taiwan China Medical University Hospital China Medical University Department of Medical Research Taichung Taiwan Pune India Korea University School of Cybersecurity Seoul Korea Republic of Kyung Hee University Kyungheedae-ro Seoul26 Korea Republic of

Edge-based federated learning (EFL) is a solution for personalized applications. It addresses the limitations of cloud-based consumer service systems, such as data privacy and network latency. To further enhance the EFL system’s ability to protect data privacy, differential privacy (DP) is introduced. It is crucial to motivate high-quality collaboration among participants for optimal performance of the DP-EFL system. Researchers primarily focus on efficient learning algorithms, optimized resource scheduling, and user-oriented incentive mechanisms. Existing research exhibits notable limitations in modeling and analyzing the heterogeneity of resource costs (e.g., communication costs), particularly failing to comprehensively account for the additional costs imposed by participants’ privacy protection mechanisms‌. To address this gap, we propose a novel market transaction model based on Stackelberg game theory. This framework integrates incentive-driven reward allocation mechanisms to rigorously investigate the collaborative behaviors and strategic interactions between edge nodes (ENs) and the cloud server (CS)‌. We incorporate privacy costs into the multidimensional costs of participants with privacy metric, and based on this, derived collaboration strategies between ENs and CS, thus solving the Stackelberg game problem by theoretical analysis. Furthermore, numerical experiments validated the rationality of our proposed model, the impact of strategies on the performance of collaborators, and the advantages over other incentive mechanisms. © 2025 IEEE. All rights reserved.

关键词： Federated learning

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3D EAGAN: 3D edge-aware attention generative adversarial network for prostate segmentation in transrectal ultrasound images

arXiv

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arXiv 2023年

作者： Liu, Mengqing Shao, Xiao Jiang, Liping Wu, Kaizhi School of Information Engineering Nanchang Hangkong University Jiangxi Nanchang China School of Computer Science Nanjing University of Information Science and Technology Jiangsu Nanjing China The First Affiliated Hospital of Nanchang University Nanchang University Jiangxi Nanchang China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China

Background: Segment prostates from transrectal ultrasound (TRUS) images plays an essential role in the diagnosis and treatment of prostate cancer. However, traditional segmentation methods are time-consuming and laborious. To address this issue, there is an urgent need to develop computer algorithms that can automatically segment prostates from TRUS images, which makes it become the direction and form of future development. Purpose: Automatic prostate segmentation in TRUS images has always been a challenging problem, since prostates in TRUS images have ambiguous boundaries and inhomogeneous intensity distribution. Although many prostate segmentation methods have been proposed, they still need to be improved due to the lack of sensibility to edge information. Consequently, the objective of this study is to devise a highly effective prostate segmentation method that overcomes these limitations and achieves accurate segmentation of prostates in TRUS images. Methods: A 3D edge-aware attention generative adversarial network (3D EAGAN)-based prostate segmentation method is proposed in this paper, which consists of an edge-aware segmentation network (EASNet) that performs the prostate segmentation and a discriminator network that distinguishes predicted prostates from real prostates. The proposed EASNet is composed of an encoder-decoder-based U-Net backbone network, a detail compensation module, four 3D spatial and channel attention modules, an edge enhance module, and a global feature extractor. The detail compensation module is proposed to compensate for the loss of detailed information caused by the down-sampling process of the encoder. The features of the detail compensation module are selectively enhanced by the 3D spatial and channel attention module. Furthermore, an edge enhance module is proposed to guide shallow layers in the EASNet to focus on contour and edge information in prostates. Finally, features from shallow layers and hierarchical features from the decod

关键词： Generative adversarial networks

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Instagram User Behavior Identification Based on Multidimensional Features

Instagram User Behavior Identification Based on Multidimensi...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Hua Wu Qiuyan Wu Guang Cheng Shuyi Guo Key Laboratory of Computer Network Technology of Jiangsu Province Nanjing China

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186962

The development of smartphones and social networks has brought great convenience to our lives. Due to the increasing requirements of user privacy, user data are protected by encryption protocol. But it also makes it difficult to regulate malicious behavior. The existing user behavior identification adopts the statistical features of encrypted traffic, which fluctuates greatly in different transmission environments. In this paper, we propose a method to obtain the stable features of encrypted traffic. Based on the principle of maximum entropy, we put forward an approach to divide the distribution ranges of these stable features, and map the feature space into SVM vector space. Our research focuses on multiple user behavior in the Instagram application. The evaluation results achieve 99.8% accuracy, 99.3% precision, 99.3% recall, and 0.09% false positive rate(FPR) on average.

关键词： Servers Feature extraction Cryptography Support vector machines Data mining Protocols Transform coding

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Dependent Task Offloading Mechanism for Cloud-Edge-Device Collaboration

SSRN

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SSRN 2022年

作者： Chen, Jiawei Zhang, Junna Bao, Xiang Liu, Chunhong Yuan, Peiyan Zhang, Xinglin Wang, Shangguang School of Computer and Information Engineering Henan Normal University Xinxiang453007 China Engineering Lab of Intelligence Business and Internet of Things Henan Province Xinxiang453007 China South China University of Technology Guangzhou510006 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China

Edge computing provides abundant computing and storage resources at the edge of a network, aiming to meet the growing requirements of delay-sensitive mobile applications. To fully utilize the advantages of edge computing, it is essential to design an appropriate task offloading strategy to efficiently use edge resources. However, the existing studies of task offloading often ignored the dependencies between tasks and the limited service capabilities of edge servers, resulting in long completion times or even infeasible offloading decisions. Therefore, an efficient dependent task offloading mechanism that can optimize the overall task completion time is proposed in this paper. This mechanism is suitable in scenarios where edge servers have limited service caches and computing power. First, a collaborative offloading model that includes one cloud server, edge servers and local devices is designed. This model uses the cloud server as the offloading node to balance the workload among edge servers. Second, the research problem is formulated as a binary optimization function with the goal of minimizing the application completion time, and a dependent task offloading algorithm for a cloud-edge-device collaborative model is proposed. Finally, extensive experiments involving real applications and datasets are performed to verify the effectiveness of the proposed model and algorithm. The experimental results show that compared with other algorithms, the proposed algorithm can reduce the application completion time by approximately 6% to 15%. In addition, the proposed dependent task offloading mechanism displays better adaptability and scalability for large-scale tasks. © 2022, The Authors. All rights reserved.

关键词： Delay-sensitive applications

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Machine Learning-Based Recruitment Strategies for Multicenter Blood Donors: Design and Application

SSRN

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SSRN 2024年

作者： Zhao, Zuoyan Ye, Xiaofan Jiao, Yudong Wang, Mingyuan Cai, Lina Tian, Jinyue Zhang, Zihan Li, Zhenggang Yan, Huimin Zhou, Chun Ma, Yuchi Tang, Yinguang Sun, Tianbao Diao, Renhua Liu, Dexing Fan, Enyong Li, Shaobo Xu, Shouguang Yan, Weibin Xue, Hui Liang, Wenbiao School of Computer Science and Engineering Southeast University Nanjing210096 China Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications [Southeast University Ministry of Education China Jiangsu Province Blood Center Nanjing China Yangzhou Blood Station Yangzhou China Suzhou Red Cross Blood Station Suzhou China College of Software Engineering Southeast University Nanjing210096 China

Background: Short Message Service (SMS) recruitment is crucial for recruiting blood donors, but current methods are inefficient, requiring many messages to improve the success rate. We aimed to enhance SMS recruitment efficiency using machine learning models. Methods: A multicenter study was conducted with blood donation data and SMS recruitment data from the blood stations in Nanjing (Jan 1, 2017, to Nov 30, 2022), Suzhou (Jan 1, 2018, to Apr 30, 2023), and Yangzhou (Oct 1, 1998, to Aug 25, 2024), China. Donor features such as age, gender, job, blood type, and donation history were used. For each city, various machine learning models were trained and the two best models were selected to be applied in subsequent SMS recruitments. Findings: In Nanjing, the best models were multi-layer perceptron (recall: 0·72, 95% CI: 0·65-0·80) and random forest (recall: 0·70, 95% CI: 0·68-0·82). In Suzhou and Yangzhou, multi-layer perceptron (recall: Suzhou: 0·70, 95% CI: 0·62-0·81;Yangzhou: 0·68, 95% CI: 0·61-0·74) and random forest (recall: Suzhou: 0·77, 95% CI: 0·62-0·86;Yangzhou: 0·64, 95% CI: 0·58-0·70) are also the best models. In Nanjing, Suzhou, and Yangzhou, recruitment success increased by 408·28%, 25·19%, and 47·31%, while SMS messages were reduced by 18·71%, 121·52%, and 138·75%, respectively. Recruitment efficiency per SMS improved by 9·54% in Nanjing, 53·61% in Suzhou, and 38·98% in Yangzhou. Interpretation: Our results suggested that recall was the primary evaluation metric, along with accuracy, precision, and F1 score, and that machine learning can improve efficiency and reduce the cost of recruitment, which has a positive influence on ensuring the blood supply. Funding: The Social Development Science and technology Project of jiangsu province (No. BE2022811), the National Natural Science Foundation of China (Nos. 62476056, 62076062, and 62306070), and the Big Data Computing Center of Southeast University. Declaration of Interest: We declare no competing interests.

关键词： Decision trees

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The Generations of Classical Correlations via Quantum Schemes

arXiv

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arXiv 2023年

作者： Chen, Zhenyu Lin, Lijinzhi Lin, Xiaodie Wei, Zhaohui Yao, Penghui Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Yau Mathematical Sciences Center Tsinghua University Beijing100084 China Yanqi Lake Beijing Institute of Mathematical Sciences and Applications 101407 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Province Nanjing210023 China Hefei National Laboratory Hefei230088 China

Suppose two separated parties, Alice and Bob, share a bipartite quantum state or a classical correlation called a seed, and they try to generate a target classical correlation by performing local quantum or classical operations on the seed, i.e., any communications are not allowed. We consider the following fundamental problem about this setting: whether Alice and Bob can use a given seed to generate a target classical correlation. We show that this problem has rich mathematical structures. Firstly, we prove that even if the seed is a pure bipartite state, the above decision problem is already NP-hard and a similar conclusion can also be drawn when the seed is also a classical correlation, implying that this problem is hard to solve generally. Furthermore, we prove that when the seed is a pure quantum state, solving the problem is equivalent to finding out whether the target classical correlation has some diagonal form of positive semi-definite factorizations that matches the seed pure state, revealing an interesting connection between the current problem and optimization theory. Based on this observation and other insights, we give several necessary conditions where the seed pure state has to satisfy to generate the target classical correlation, and it turns out that these conditions can also be generalized to the case that the seed is a mixed quantum state. Lastly, since diagonal forms of positive semi-definite factorizations play a crucial role in solving the problem, we develop an algorithm that can compute them for an arbitrary classical correlation, which has decent performance on the cases we test. © 2023, CC BY.

关键词： Factorization

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