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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Han, Mengqi Yang, Bo Liu, Yuxiang Liu, Sicheng Liu, Qi Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798331527471

With the rapid development of smart manufacturing, existing microservice deployment strategies based on the TCP protocol tend to encounter problems such as network latency, excessive header length, and port exhaustion in high concurrency scenarios. MQTT Broker can relay data between microservices, effectively alleviating these issues. However, the communication overhead of the Broker is significantly related to its deployment and the dependency of microservices. An appropriate deployment solution can significantly improve service quality. To address this issue, this paper models the deployment of MQTT Broker and microservices as a graph with cycles. By introducing auxiliary variables, the NP-hard problem is transformed into a mixed-integer quadratic programming problem, improving problem-solving efficiency and optimizing the microservices deployment strategy to reduce communication overhead. Meanwhile, a real-world heterogeneous cluster was constructed to experiment on fault detection applications, elaborating on the superiority of the microservice deployment strategy designed in this paper. Experimental results demonstrate that our approach reduces communication overhead by 20% in comparison to both the greedy strategy and the K8s strategy. This suggests that achieving an optimal balance between the number of Brokers and microservices is vital for ensuring efficient resource utilization and maintaining low communication latency, particularly as the scale of services expands. © 2024 IEEE.

关键词： Smart manufacturing

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Beyond the network-based multi-omics data integration in COPD: A pathway-centric analysis

Beyond the network-based multi-omics data integration in COP...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Sibilio, Pasquale Conte, Federica Paci, Paola Sapienza University of Rome Department of Computer Control and Management Engineering Rome Italy National Research Council Institute for Systems Analysis and Computer Science 'Antonio Ruberti' Rome Italy Karolinska Institutet Stockholm17177 Sweden

ISBN: (纸本)9798350386226

Chronic obstructive pulmonary disease (COPD) is a lung disease causing hundred thousand of death each year worldwide and defined as a respiratory and airflow impairment majorly due to large and small airways dysfunctions. COPD could be considered as a syndrome that includes disease axes of variable pathological and clinical conditions. Despite recent advances, the comprehension of the molecular mechanisms responsible for COPD disease spectrum is far to be reached. Moreover, we should also consider continuous smoking exposure, which could lead to variability in the disease mechanisms and progression. Network-based multi-omics data integration can help to study the association between molecular determinants on diverse biomolecular layers in a disease context. In a previous study, we leveraged lung RNA-seq and DNA-methylation data of a COPD-control cohort to build a correlation-based integrated network (called coupled network), that helped to unveil genes involved in immune and inflammatory modulation of COPD. Therefore, in our previous study we highlighted the most important genes of the coupled network and inspected their single contribution to disease-related pathways. In this study we aim to overcome this limitation by performing a pathway activity analysis by considering the expression and DNA methylation profiles of coupled network genes. Moreover, we exploit this analysis to study the possible contribution of coupled network genes to the differential disease progression between current and former smokers patients. © 2024 IEEE.

关键词： Lung cancer

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Reinforcement learning-based unknown reference tracking control of HMASs with nonidentical communication delays

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Science China(Information Sciences) 2023年第7期66卷 46-57页

作者： Yong XU Zheng-Guang WU Wei-Wei CHE Deyuan MENG School of Automation Beijing Institute of Technology Institute of Cyber-Systems and Control Zhejiang University College of Mathematics and Computer Science Zhejiang Normal University Department of Automation Qingdao University School of Automation Science and Electrical Engineering Beihang University(BUAA)

This paper focuses on the optimal output synchronization control problem of heterogeneous multiagent systems(HMASs) subject to nonidentical communication delays by a reinforcement learning *** with existing studies assuming that the precise model of the leader is globally or distributively accessible to all or some of the followers, the leader's precise dynamical model is entirely inaccessible to all the followers in this paper. A data-based learning algorithm is first proposed to reconstruct the leader's unknown system matrix online. A distributed predictor subject to communication delays is further devised to estimate the leader's state, where interaction delays are allowed to be nonidentical. Then, a learning-based local controller, together with a discounted performance function, is projected to reach the optimal output synchronization. Bellman equations and game algebraic Riccati equations are constructed to learn the optimal solution by developing a model-based reinforcement learning(RL) algorithm online without solving regulator equations, which is followed by a model-free off-policy RL algorithm to relax the requirement of all agents' dynamics faced by the model-based RL algorithm. The optimal tracking control of HMASs subject to unknown leader dynamics and communication delays is shown to be solvable under the proposed RL algorithms. Finally, the effectiveness of theoretical analysis is verified by numerical simulations.

关键词： heterogeneous multiagent systems HMAS reinforcement learning RL optimal output synchronization communication delays

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Distributed robust matrix-scaled consensus control of perturbed multi-agent systems

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control Theory and Technology 2024年第4期22卷 623-637页

作者： Bin Cheng Gang Li Kun An Chunhui Yu Department of Control Science and Engineering Tongji UniversityShanghai201804China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji UniversityShanghai201804China Shanghai Sunshine Rehabilitation Center Shanghai201613China

Distributed matrix-scaled consensus is a kind of generalized cooperative control problem and has broad applications in the field of social network and *** paper addresses the robust distributed matrix-scaled consensus of perturbed multi-agent systems suffering from unknown *** discontinuous protocols are first proposed to drive agents to achieve cluster consensus and suppress the effect of *** protocols with time-varying gains obeying differential equations are also designed,which are completely distributed and rely on no global *** the boundary layer technique,smooth protocols are proposed to avoid the unexpected chattering effect due to discontinuous *** a cost,under the designed smooth protocols,the defined matrix-scaled consensus error tends to a residual set rather than zero,in which the residual bound is arbitrary small by choosing proper ***,distributed dynamic event-based matrix-scalar consensus controllers are also proposed to avoid continuous *** examples are provided to further verify the designed algorithms.

关键词： Matrix-scaled consensus Perturbed multi-agent systems Adaptive control Distributed control Event-triggered control

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Collision Avoidance in GEO: The Challenges of Orbit Determination for Electric Propulsion Satellites via Optical Ground Based Observations 74

Collision Avoidance in GEO: The Challenges of Orbit Determin...

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74th International Astronautical Congress, IAC 2023

作者： Montalbò, Antonio Vito Abruzzese, Fabrizio Rizzo, Luca Errico, Roberto Mannacio, Fabio Department of Space Systems Control SICRAL Joint Management and Control Centre Space Operations Command Italian Ministry of Defence Via Raffaele Giacomelli 2 Vigna di Valle Rome00062 Italy

The SICRAL Joint management & control Centre (SJMCC) is an Italian military institution in charge of the mission control of the Italian military spacecraft and the first European full-military institute capable of independently performing spacecraft housekeeping and station keeping operations. In this context, one of the most important activities is the management of collision risks. The task is accomplished by determining the orbits of secondary objects (such as neighbouring geostationary satellites) and evaluating the orbital parameters, in order to assess the necessity of a collision avoidance maneuver. In recent years, a new generation of satellites equipped with innovative propulsion systems based on electric thrusters has introduced new challenges to the aforementioned operation. Electric propulsion systems provide very high thrust efficiency and low fuel consumption compared to chemical propulsion, while generically settling for lower thrust levels and longer maneuvering times. This implies that the free dynamics behaviour of the spacecraft is only confined to a short fraction of the orbital period. Consequently, the typical flight dynamics approach, based on the propagation of the obtained state vector, loses its inner value since the electric propulsion spacecraft will persist in a free dynamics regime only for a limited fraction of its orbital period. From the perspective of a mission control centre, such as SJMCC, these new satellites make it necessary to drastically adapt its orbit determination capabilities. Consequently, the main goal of the research has been to model a strategy and a tool to manage the orbit determination of electric propulsion geostationary satellites. The paper thoroughly describes an innovative concept named "Continuous Obit Determination" (COD), also presenting a possible software implementation based on open-source libraries. Evaluating the challenges that electric propulsion satellites bring to satellite control centres, COD is

关键词： determination electric geostationary orbit propulsion thrusters

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A network-based bioinformatic analysis for identifying potential repurposable drugs for obesity avoiding hepatic steatosis side-effect

A network-based bioinformatic analysis for identifying poten...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Brunetti, Martina Fiscon, Giulia Costanzo, Alessia Di Arca, Marcello Paci, Paola Sapienza University of Rome Department of Experimental Medicine Rome Italy Sapienza University of Rome Institute for Systems Analysis and Computer Science "a. Ruberti" National Research Council of Rome Department of Computer Control and Management Engineering "a. Ruberti" Rome Italy Sapienza University of Rome Policlinico Umberto I Department of Translational and Precision Medicine Rome Italy Sapienza University of Rome Department of Computer Control and Management Engineering "a. Ruberti" Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (纸本)9798350386226

Obesity is a complex multifactorial disorder characterized by the excess accumulation of body fat that impairs human health due to the risk of developing other diseases, including cardiovascular and hepatic diseases, hypertension, diabetes, hyperlipidemia. Its spread has been progressively accelerating, resulting in an unprecedented epidemic with no significant signs of slowing down any time soon. Drug therapy via the proposal repurposing solutions can represent an actionable treatment strategy, even if the emergence of drug-induced adverse effects can affect the treatment of this pathology. In this study, we propose a network-based analysis to identify a list of drug candidates predicted to be repurposable for obesity that are unlikely to produce specific adverse side-effect, such as hepatic steatosis. © 2024 IEEE.

关键词： Nutrition

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Differential gene correlation analysis to investigate evolutionary divergence between Cardamine hirsuta and Arabidopsis thaliana

Differential gene correlation analysis to investigate evolut...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： D'Annunzio, Federica Fiscon, Giulia Bertolotti, Gaia Dello Ioio, Raffaele Paci, Paola Sapienza University of Rome Department of Translational and Precision Medicine Rome Italy Sapienza University of Rome Institute for Systems Analysis and Computer Science 'A. Ruberti' National Research Council of Rome Department of Computer Control and Management Engineering 'A. Ruberti' Rome Italy Sapienza University of Rome Department of Biology and Biotechnology 'Charles Darwin' Rome Italy Department of Computer Control and Management Engineering 'A. Ruberti' Sapienza University of Rome Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (纸本)9798350386226

Dissecting the intricate regulatory dynamics between genes stands as a critical step towards the development of precise predictive models within biological systems. A highly effective strategy in this pursuit involves an examination of variations in correlation among gene pairs across different conditions trough differential gene correlation analysis. We anticipated that the application of this method to phylogenetically close plant species could reveal powerful insights on how genes' relationships have a fundamental role in evolutionary dynamics. Building upon this principle, our investigation focused primarily on conducting a comprehensive differential correlation analysis of the roots' orthologous genes of two closely related plant species: Cardamine hirsuta and Arabidopsis thaliana. By leveraging their shared phylogenetic proximity, we were able to draw comparisons that shed light on how evolutionary pressures might have shaped their gene regulatory networks. By integrating differential expression analysis, differential correlation analysis and functional enrichment analysis, we offer a robust framework for future studies aiming to unravel the complexities of adaptation and evolution across a wide range of biological systems. © 2024 IEEE.

关键词： Plant diseases

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Improving Sharpness-Aware Minimization Using Label Smoothing and Adaptive Adversarial Cross-Entropy Loss

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IEEE Access 2025年 13卷 100326-100337页

作者： Tanapat Ratchatorn Masayuki Tanaka Department of Systems and Control Engineering School of Engineering Institute of Science Tokyo Meguro City Tokyo Japan

Recent advances in learning algorithms have identified loss surface sharpness as an effective metric for reducing the generalization gap. Building on this principle, Sharpness-Aware Minimization (SAM) was introduced to improve model generalization and has achieved state-of-the-art performance through its weight perturbation and updating steps. However, SAM’s perturbation is based solely on the gradient of the standard cross-entropy loss. As the model approaches convergence, this gradient diminishes and oscillates, leading to inconsistent perturbation directions. To address these limitations, we introduce SAM-CE-AACE and SAM-SCE-AACE. SAM-CE-AACE replaces the conventional cross-entropy loss with the Adaptive Adversarial Cross-Entropy (AACE) loss in the perturbation step. Unlike the standard loss, AACE increases in both value and gradient magnitude as the model converges, ensuring stable perturbation directions. Additionally, SAM-CE-AACE’s perturbation utilizes AACE loss without normalization, enhancing the model’s exploratory capabilities in near-optimum stages. Moreover, SAM-SCE-AACE further improves SAM-CE-AACE by integrating label smoothing into the weight-updating step, reducing overconfidence in predictions. Together, this combination of the AACE loss function and label smoothing technique leads to further improvement in model performance. Intensive empirical experiments have been conducted to confirm the effectiveness of our methods, with experiments demonstrating improved performance in image classification tasks using different network architectures across various datasets. The reproduction code is available online at https://***/proj/AACE

关键词： Perturbation methods Training Standards Adaptation models Smoothing methods Minimization Vectors Probability distribution Feature extraction Market research

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Verification of Railway control systems Using Model Checking and CTL, Explained Through a Case Study

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Periodica Polytechnica Transportation engineering 2024年第4期52卷 402-411页

作者： Lukács, Gábor Bartha, Tamás Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Kende street 13-17. BudapestH-1111 Hungary

Systematic faults can often occur during the development of a system. The later such faults are discovered, the more expensive it can be to correct them. In systems engineering practice, there are many methods and tools to reduce the likelihood of systematic faults. In this paper, we present the application of a formal model–based verification technique – called model checking – to assist railway engineers in designing and verifying the safety-related functionality of railway control systems. The proposed process is part of a specification-verification environment that facilitates the construction of correct, complete, consistent, and verifiable functional specifications during development. The results and experience in model checking are illustrated by a case study of a vehicle detection point, a common component in this domain. The model checking of the case study has been performed in the widely used UPPAAL modeling and simulation framework, which can also verify formal properties and generate a counterexample in case of a property violation. By analyzing the counterexample, the designer can gain insights into the system's behavior and identify potential design flaws or failures. Model checking can be used to achieve a higher quality functional specification that is typically more complete and/ or contains fewer faults compared to the traditional development approach. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Railroads

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Holistic Self-Distillation with the Squeeze and Excitation Network for Fine-grained Plant Pathology Classification 26

Holistic Self-Distillation with the Squeeze and Excitation N...

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26th International Conference on Information Fusion, FUSION 2023

作者： Su, Jingxuan Anderson, Sean Mihaylova, Lyudmila University of Sheffield Department of Automatic Control & Systems Engineering S1 3JD United Kingdom

ISBN: (纸本)9798890344854

Fine-grained plant pathology classification is an important task for precision agriculture, but at the same time, it is challenging due to the subtle difference in plant categories. Variances in the lighting conditions, position, and stages of disease symptoms usually lead to degradation of classification accuracy. Knowledge distillation is a popular method to improve the model performance to deal with the indistinguishable image classification problem. It aims to have a well-optimised small student network guided by a large teacher network. Existing knowledge distillation methods mainly consider training a teacher network that needs a high storage space and considerable computing resources. Self-knowledge distillation methods have been proposed to distil knowledge from the same network. Although self-knowledge distillation saves time and space compared with knowledge distillation, it only learns label knowledge. In this paper, we propose a novel self-distillation method to recognize the fine-grained plant category, which considers holistic knowledge based on the Squeeze and Excitation Network. We label this new method as holistic self-distillation because it captures knowledge through spatial features and labels. The performance validation of the proposed approach is performed on two public fine-grained plant datasets: Plant Pathology 2021 and Plant Pathology 2020 with the accuracy of 98.22% and 90.72% respectively. We also present experiments on the state-of-the-art algorithm (ResNet-50). The classification results demonstrate the effectiveness of the proposed approach with respect to accuracy. © 2023 International Society of Information Fusion.

关键词： Distillation

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