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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Wang, Haolin Liu, Xuefeng Niu, Jianwei Guo, Wenkai Tang, Shaojie State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Center for AI Business Innovation Department of Management Science and Systems University at Buffalo BuffaloNY United States Zhongguancun Laboratory Beijing China

Federated learning is a distributed machine learning paradigm designed to protect user data privacy, which has been successfully implemented across various scenarios. In traditional federated learning, the entire parameter set of local models is updated and averaged in each training round. Although this full network update method maximizes knowledge acquisition and sharing for each model layer, it prevents the layers of the global model from cooperating effectively to complete the tasks of each client, a challenge we refer to as layer mismatch. This mismatch problem recurs after every parameter averaging, consequently slowing down model convergence and degrading overall performance. To address the layer mismatch issue, we introduce the FedPart method, which restricts model updates to either a single layer or a few layers during each communication round. Furthermore, to maintain the efficiency of knowledge acquisition and sharing, we develop several strategies to select trainable layers in each round, including sequential updating and multi-round cycle training. Our theoretical analysis and experimental results show that the FedPart method significantly outperforms traditional full-network update strategies, achieving faster convergence, greater accuracy, and reduced communication and computational overhead. © 2024 Neural information processing systems foundation. All rights reserved.

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A novel deep generative model for mRNA vaccine development: Designing 5′ UTRs with N1-methyl-pseudouridine modification

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1814-1826页

作者： Xiaoshan Tang Miaozhe Huo Yuting Chen Hai Huang Shugang Qin Jiaqi Luo Zeyi Qin Xin Jiang Yongmei Liu Xing Duan Ruohan Wang Lingxi Chen Hao Li Na Fan Zhongshan He Xi He Bairong Shen Shuai Cheng Li Xiangrong Song Institute of Systems Genetics Department of Critical Care MedicineFrontiers Science Center for Disease-related Molecular NetworkState Key Laboratory of Biotherapy and Cancer CenterWest China HospitalSichuan UniversityChengdu 610000China Department of Computer Science City University of Hong KongHong Kong 99907China Department of Biology Brandeis UniversityBostonMA 02453USA

Efficient translation mediated by the 5'untranslated region(5'UTR)is essential for the robust efficacy of mRNA ***,the N1-methyl-pseudouridine(m1)modification of mRNA can impact the translation efficiency of the 5'*** discovered that the optimal 5'UTR for m1y-modified mRNA(m1y-5'UTR)differs significantly from its unmodified counterpart,high-lighting the need for a specialized tool for designing mly-5'UTRs rather than directly utilizing high-expression endogenous gene 5'*** response,we developed a novel machine learning-based tool,Smart5UTR,which employs a deep generative model to identify superior m1y-5'UTRs in *** tailored loss function and network architecture enable Smart5UTR to overcome limitations inherent in existing *** a result,Smart5UTR can successfully design superior 5'UTRs,greatly benefiting mRNA vaccine ***,Smart5UTR-designed superior 5'UTRs significantly enhanced antibody titers induced by COVID-19 mRNA vaccines against the Delta and Omicron variants of SARS-CoV-2,surpassing the performance of vaccines using high-expression endogenous gene 5'UTRs.

关键词： mRNA vaccine Machine learning 5'UTR mRNA design Sequence design N1-Methyl-pseudouridine COVID-19 SARS-CoV-2

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Generic Simulated Evolution and Stochastic Evolution

Generic Simulated Evolution and Stochastic Evolution

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2024 International Conference on computer and Applications, ICCA 2024

作者： Kallab, Chadi Haddad, Samir Shakir, Wafaa M.R. Merhej, Joseph Turkey, Nisrine Sayah, Jinane Lebanese American University Department of Computer Science and Mathematics Jbeil Lebanon University of Balamand Computer Science Department Koura Lebanon Al-Furat Al-Awsat Technical University Department of Computer Systems Babil Iraq Lebanese University LaRRIS Laboratory Computer Science Department Fanar Lebanon Lebanese American University Jbeil Lebanon University of Balamand Telecom and Networks Department Koura Lebanon

ISBN: (纸本)9798350367560

The problem of Multiple Sequence Alignment is regarded as one of the many issues that are categorized as NP-Hard. Firstly, it necessitates, like any other such system, a specific encoding scheme and precise design of the key characteristics of the heuristic algorithm being created and implemented. This paper aims to clarify our suggested universal interpretation of the stochastic evolution (Stoc-E) and Simulated Evolution (SimE) algorithms. Undoubtedly, heuristic search methods such as Sim-E and Stoc-E are more effective than the simplified local search methods observed in Genetic Algorithms (GA), Simulated Annealing (SA), and Tabu Search (TS), which we have already analyzed, for tackling these kinds of problems. Although other works in the literature have examined the use of refined methodology or a restricted set of heuristics, we have steadfastly adhered to our original objective of aligning as many heuristics as feasible, even if these two algorithms are better suited for the placement category of algorithms. Hence, we first developed a thorough encoding scheme that is compatible with all the above techniques. Consistent with our prior study, we are simultaneously presenting several pseudo-code options for these algorithms, together with the capability to trace functions, which will provide further examination for the purpose of adjusting starting parameters. © 2024 IEEE.

关键词： Encoding (symbols)

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Reliable deep learning in anomalous diffusion against out-of-distribution dynamics

NATURE COMPUTATIONAL SCIENCE

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NATURE COMPUTATIONAL science 2024年第11期4卷 877-877页

作者： Feng, Xiaochen Sha, Hao Zhang, Yongbing Su, Yaoquan Liu, Shuai Jiang, Yuan Hou, Shangguo Han, Sanyang Ji, Xiangyang School of Computer Science and Technology Harbin Institute of Technology (Shenzhen) Shenzhen China Shenzhen International Graduate School Tsinghua University Shenzhen China Institute of Systems and Physical Biology Shenzhen Bay Laboratory Shenzhen China Department of Automation Tsinghua University Beijing China

Anomalous diffusion plays a crucial rule in understanding molecular-level dynamics by offering valuable insights into molecular interactions, mobility states and the physical properties of systems across both biological and materials sciences. Deep-learning techniques have recently outperformed conventional statistical methods in anomalous diffusion recognition. However, deep-learning networks are typically trained by data with limited distribution, which inevitably fail to recognize unknown diffusion models and misinterpret dynamics when confronted with out-of-distribution (OOD) scenarios. In this work, we present a general framework for evaluating deep-learning-based OOD dynamics-detection methods. We further develop a baseline approach that achieves robust OOD dynamics detection as well as accurate recognition of in-distribution anomalous diffusion. We demonstrate that this method enables a reliable characterization of complex behaviors across a wide range of experimentally diverse systems, including nicotinic acetylcholine receptors in membranes, fluorescent beads in dextran solutions and silver nanoparticles undergoing active endocytosis.

关键词： Silver nanoparticles

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Efficient and Lightweight Framework for Confidential Medical Image Search using Edge Computing 2

Efficient and Lightweight Framework for Confidential Medical...

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2nd International Conference on Computational Intelligence and Network systems, CINS 2024

作者： Rajan, Arun Amaithi Vetriselvi, V. Aishwarya, R. Rajan, Anitha Amaithi Security Research Laboratory Department of Computer Science and Engineering College of Engineering Guindy Anna University Tamil Nadu Chennai600025 India Department of Computer Science and Business Systems Francis Xavier Engineering College Tamil Nadu Tirunelveli627011 India

ISBN: (纸本)9798331504106

In healthcare, medical images are playing a major role in accurate diagnosis. Cloud storage for medical images creates security risks and latency due to some critical vulnerabilities and their distance from data sources. By bringing computation closer to the source, edge computing improves efficiency, still edge servers cannot be trusted blindly, requiring robust security measures. In this article, an efficient and lightweight framework for secure medical image search and retrieval that leverages edge computing is proposed. Here, Medical images are encrypted and similarity-preserving hashcodes are generated locally at the source, which are sent to a trusted master edge server. Before being stored, searchable hashcodes undergo homomorphic encryption, allowing for secure computations on encrypted data. The master edge server generates n shares of the encrypted images by applying a Learning With Errors (LWE) based image sharing scheme and distributing them across nearby edge devices. During retrieval, to ensure resilience against device compromise, m out of n shares are used to reconstruct the image. The master edge server retrieves and reconstructs the top k relevant images in response to the query image. This framework enhances security and efficiency by reducing reliance on cloud storage and enabling secure processing on edge servers, making it ideal for modern healthcare environments. The efficiency and security of the proposed framework are proved theoretically and experimentally. Hence, it proved that the framework is performing better than existing state-of-the-art models. ©2024 IEEE.

关键词： Electronic health record

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Improving Power Response of Single-Controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

Controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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On tuning of ADRC with competing design indices:a quantitative study

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Control Theory and Technology 2023年第1期21卷 16-33页

作者： Yutao Zhao Yi Huang Zhiqiang Gao Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Department of Electrical Engineering and Computer Science Center for Advanced Control TechnologiesCleveland State UniversityClevelandOH 44115USA

Controller optimization has mostly been done by minimizing a certain single cost *** practice,however,engineers must contend with multiple and conflicting considerations,denoted as design indices(DIs)in this *** to account for such complexity and nuances is detrimental to the applications of any advanced control *** paper addresses this challenge heads on,in the context of active disturbance rejection controller(ADRC)and with four competing DIs:stability margins,tracking,disturbance rejection,and noise *** this end,the lower bound for the bandwidth of the extended state observer is first established for guaranteed closed-loop ***,one by one,the mathematical formula is meticulously derived,connecting each DI to the set of controller *** our best knowledge,this has not been done in the context of *** formulas allow engineers to see quantitatively how the change of each tuning parameter would impact all of the DIs,thus making the guesswork *** example is given to show how such analytical methods can help engineers quickly determine controller parameters in a practical scenario.

关键词： Uncertain systems Active disturbance rejection control(ADRC) Design indices(DIs) Extended state observer(ESO)

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A low-fabrication-temperature, high-gain chip-scale waveguide amplifier

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science China(Information sciences) 2022年第6期65卷 247-255页

作者： Bo WANG Peiqi ZHOU Xingjun WANG Yandong HE State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer Science Peking University Institute of Microelectronics School of Electronics Engineering and Computer Science Peking University Frontier Science Center for Nano-optoelectronics Peking University Peking University Yangtze Delta Institute of Optoelectronics Peng Cheng Laboratory

The increasing prevalence of integrated on-chip optoelectronic devices has identified serious issues regarding inter-device transmission and coupling losses, highlighting an urgent need for on-chip waveguide amplifiers to compensate for these losses. Compared with other Er-based optical materials, erbium silicate is ideally suited to high-efficiency on-chip amplifiers and lasers because of its extremely high Er3+concentration(1022cm-3). Nevertheless, erbium silicate must be annealed above 1000℃ to crystallize and activate the Er3+, which damages other on-chip optoelectronic components and is not conducive to device ***, we report a low-fabrication-temperature, high-luminescence-efficiency gain material by adding Bi2O3to an erbium-ytterbium silicate mixed film. Our experiments demonstrate that the proposed film crystallizes at 600℃ while the activation of Er3+is also achieved, which is the lowest activation temperature of on-chip waveguide amplifier to our knowledge. This material forms the basis for a new chip-scale waveguide amplifier design, with a theoretical multi-energy-level model of Bi-Er-Yb in the mixed thin films used to analyze its signal enhancement properties. We achieve a peak on-chip gain of 23 dB in a 3.3-mm-long waveguide under the pump and signal powers of 300 mW and 1 μW, respectively. These results highlight the potential of the proposed material for realizing on-chip amplifiers and lasers for large-scale nanophotonic integrated circuits.

关键词： photonic circuit integration low fabrication temperature high gain rare earth material waveguide amplifier

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Blockchain-Based Privacy-Aware Voting System

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SN computer science 2024年第8期5卷 1079页

作者： Bendjemaa, Isra Cherifi, Katia Ines Benarous, Leila Boudjit, Saadi Department of Computer Science Faculty of Science University of Amar Telidji Laghouat Algeria LIM Laboratory Faculty of Science University of Amar Telidji Laghouat Algeria LITIS Lab Intelligent Transportation Systems Group University of Rouen Normandy Rouen France

Traditional voting methods, conducted at physical ballot boxes, incur numerous expenses related to campaign logistics, equipping voting centers, and compensating workers. However, these methods may not guarantee the honesty, traceability, and integrity of vote results. In contrast, centralized electronic voting streamlines the process, saving resources and time while automating ballot counting for faster and more accurate outcomes. Despite these advantages, centralized systems are vulnerable to forgery and lack transparency due to their reliance on private servers controlled by the voting authority. To address the issue of single points of failure associated with private servers and to enhance transparency, a distributed, secure, and fully connected technology is required. Therefore, we propose a blockchain-based electronic voting system with a web application as its frontend. The implementation of blockchain technology helps prevent forgery and ensures immutability, as votes are openly monitored by all participants. However, the transparency and traceability provided by blockchain—essential for ensuring that no voter casts multiple votes and that no unauthorized votes are injected—contradict the confidentiality and privacy requirements of the voting process. To reconcile the need for transparency with confidentiality, our proposal incorporates additional security measures, including key images, group addresses, and group signatures. This privacy-aware blockchain-based solution guarantees the uniqueness of each vote and prevents multiple voting attempts without compromising voter confidentiality. We evaluated the security of our designed solution using an attack tree to identify potential threats and estimate their likelihood of occurrence. The results shows that the proposed system is 3.2 time more secure compared to the traditional centralized voting system. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain e-Voting Forgery-resilient Privacy Security Transparency

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Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control 63

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Broens, Yorick Butler, Hans Toth, Roland Asml Veldhoven Netherlands Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Hunren Institute for Computer Science and Control Systems and Control Laboratory Hungary

ISBN: (纸本)9798350316339

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype. © 2024 IEEE.

关键词： Continuous time systems

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