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SPAHN novel approach for PL-AG gateway discovery for internet connectivity

Peer-to-Peer Networking and applications 2020年第4期14卷 2275-2284页

作者： Kannan, K. Sivaranjani, P. Sathish Kumar, S. Nalini, M. Balaji, V. R. Sanjeevi, P. Department of ECE R.M.K. College of Engineering and Technology Chennai India Department of Electronics and communication Engineering Kongu Engineering College Erode India Dept of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Thalavapalayam India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of ECE Sri Krishna College of Engineering and Technology Coimbatore India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

Internet Gateway(IGW) main role is detecting availability nodes and providing internet to Mobile Ad Hoc Network(MANET) have whenever connected to internet. Discovery time of gateway is changed based on the throughput and packet delay. Many of the situations the mobile nodes are have fixed host connection to the internet using minimum hop path, it is not good for waiting packets because of that packets are have longer path interface queue. This research paper object is avoided above the problem mentioning using a novel approach of SPAHN (Solving Problem of Ad-Hoc Network). This paper mainly focus is classify the routing protocols of load-aware in MANET and from this classify discover the proactive load-aware gateway (PL-AG) from a device into interface queue size and min-hop-metric. This novel approach has been allowing and gives better handoff between two internet gateways for fixed host seamless connectivity. We justify the performance of the SPAHN approach using two metrics like average end-to-end delay and throughput based on this examination the SPAHN system yield good simulation results comparably existing systems.

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Observer Design for Boundary Coupled Fractional Order Distributed Parameter Systems

Observer Design for Boundary Coupled Fractional Order Distri...

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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Yanjiu ZHOU Juan CHEN Baotong CUI Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of IoT Engineering Jiangnan University Wuxi China Department of Computer Systems Tallinn University of Technology Tallinn Estonia

This paper studies the observer design for the fractional order boundary coupled distributed parameter systems. Firstly, we obtain the decoupled observer error systems from the state system and observer system. Secondly, the advection terms are eliminated through the invertible transformation and we can obtain the general reaction-diffusion partial differential equations, which are more convenient for discussions. Thirdly, Backstepping method and target systems are employed to give kernel partial differential equations and then the related observer gains can be derived from the corresponding kernels. Finally, Mittag-Leffler stability of the designed fractional order observers is analyzed and the main results are illustrated by the simulation graphically.

关键词： control nonlinearities distributed parameter systems observers partial differential equations reaction-diffusion systems stability

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Design of Experiments for Battery Aging Estimation

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IFAC-PapersOnLine 2018年第28期51卷 386-391页

作者： Pózna, Anna I. Hangos, Katalin M. Magyar, Attila Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Egyetem str. 10. VeszprémH-8200 Hungary Process Control Research Group HAS Research Institute for Computer Science and Control Kende str. 13-17. BudapestH-1111 Hungary

Li-ion batteries are widely used in EV applications and are imposed to several aging effects during their lifetime. Since battery health cannot be measured directly, information about its health can be obtained by iteratively re-estimating the parameters of the model describing its dynamical behavior. The optimal design of experiments is investigated in this paper. The proposed method applies families of input signals (PRBS current and constant current-constant voltage (CC-CV) signals) to the batteries to estimate the key aging factors. Simulation experiments have been used to analyze the statistical properties of the estimators as a function of the design parameters of the input signal families. The results show that the CC-CV charging-discharging cycle has the possibility to gain the most information out of the battery model parameter estimation. © 2018

关键词： Parameter estimation Battery management systems Design of experiments Electric excitation Iterative methods Lithium ion batteries Planning Electric Experiment design Input Model formulation Storage operations

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Machine learning for modelling unstructured grid data in computational physics: a review

arXiv

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arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation

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Profiling Adaptive Immunity: A Quantitative Framework for Immune Repertoire Dynamics and Clinical Diagnostics

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Fundamental Research 2025年

作者： Yexing Chen Haiwen Ni Yongjie Li Jin Ma Chen Huang Sixian Yang Xiangfei Xie Haitao Lv Min Li Peng Cao State Key Laboratory of Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Nanjing University of Chinese Medicine Nanjing 210000 China Jiangsu Provincial Medical Innovation Center Affiliated Hospital of Integrated Traditional Chinese and Western Medicine Nanjing University of Chinese Medicine Nanjing 210000 China Department of Hematology Affiliated Hospital of Nanjing University of Chinese Medicine The First Clinical College of Nanjing University of Chinese Medicine Nanjing 210000 China Children’s Hospital of Soochow University Suzhou 215000 China Key Laboratory of Quantum Information University of Science and Technology of China Hefei 230000 China Department of Computer Science College of Engineering and Applied Science University of Cincinnati Cincinnati 45221 USA Department of Oncology Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine Nanjing 210000 China

While immune repertoire(IR) dynamics encode critical disease signatures, existing models fail to capture the non-equilibrium processes that governing clonal selection and somatic hypermutation (SHM). We develop a biophysical framework that mathematically reconstructs IR evolution through energy landscape optimization, where 1) clonal emergence probabilities map to metastable states, 2) repertoire transitions obey non-equilibrium dynamics, and 3) inter-IR distances quantify the distribution transformation costs via optimal transport theory. This model enables macroscopic immune state detection from 10k cells by resolving critical fluctuations in sparse sampling regimes. Experimental validation across murine/human cohorts demonstrates precise unsupervised stratification of immune stages and disease states without prior clinical annotations. By bridging stochastic SHM kinetics with deterministic repertoire shifts, our approach establishes quantitative metrics for tracking immunological trajectories and pathological progression. This paradigm shift from static pattern recognition to dynamic process decoding empowers sensitive immunomonitoring and personalized therapeutic design through ultra-low-input clinical sampling.

关键词： Deductive reasoning Immune repertoire analysis Repertoire shift quantification Early disease screening Systemic immunity inference Kawasaki disease Colorectal cancer

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Applicability of magnetic hysteresis models for predicting the behaviour of MR dampers 9

Applicability of magnetic hysteresis models for predicting t...

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9th ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019

作者： Goldasz, J. Sapinski, B. Jastrzebski, L. Kubik, M. Faculty of Electrical Engineering and Computer Science Cracow University of Technology ul. Warszawska 24 Krakow31-155 Poland BWI Technical Center BWI Group ul. Podgorki Tynieckie 2 Krakow30-399 Poland Department of Process Control AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland Faculty of Mechanical Engineering Brno University of Technology Technicka 2869/2 Brno616 69 Czech Republic

ISBN: (纸本)9788494919466

This study concerns modeling the magnetic hysteretic behaviour of magnetorheological (MR) dampers. Magnetic hysteresis is one of factors influencing the output of such actuators. The origin of magnetic hysteresis in the actuator’s output is obvious - it is the inherent property of ferromagnetic materials which form the electromagnet’s assembly of the actuator. Prior work on solenoid actuators indicates that hysteresis plays a major role in the flux generation mechanism, and it should be accounted for in the controls development process. So far less attention has been paid to studying the contribution of magnetic hysteresis on the output of MR dampers. Majority of studies on the hysteretic behaviour of MR dampers have virtually neglected that specific contributor. Instead, the hysteretic behaviour of MR actuators was studied by observing the relationships between the output (force/torque) and the inputs (current, velocity, position). Instead, in the present study we separate the magnetic hysteresis from the mechanical/hydraulic one by investigating the magnetic flux vs exciting current relationship of an exemplary MR damper subjected to sinusoidal current (voltage) loading. The resulting behaviour of the electromagnets is then examined using the nonlinear inductor approach with hysteresis. The performance of several hysteretic operators is then evaluated based on their ability to reproduce the magnetic flux output of the MR actuator. © 2019 9th ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019. All rights reserved.

关键词： Damping

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Metaproteomics in the One Health framework for unraveling microbial effectors in microbiomes

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Microbiome 2025年第1期13卷 134页

作者： Robert Heyer Maximilian Wolf Dirk Benndorf Sergio Uzzau Jana Seifert Lucia Grenga Martin Pabst Heike Schmitt Bart Mesuere Tim Van Den Bossche Sven-Bastiaan Haange Nico Jehmlich Mariagrazia Di Luca Manuel Ferrer Sergio Serrano-Villar Jean Armengaud Helge B Bode Patrick Hellwig Catherine Robbe Masselot Renaud Léonard Paul Wilmes Multidimensional Omics Analyses Group Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. Bunsen-Kirchhoff-Straße 11 44139 Dortmund Germany. robert.heyer@ISAS.de. Multidimensional Omics Analyses Group Faculty of Technology Bielefeld University Universitätsstraße 25 33615 Bielefeld Germany. robert.heyer@ISAS.de. Multidimensional Omics Analyses Group Faculty of Technology Bielefeld University Universitätsstraße 25 33615 Bielefeld Germany. Bioprocess Engineering Otto-Von-Guericke University Magdeburg Universitätsplatz 2 39106 Magdeburg Germany. Bioprocess Engineering Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Sandtorstraße 1 39106 Magdeburg Germany. Applied Biosciences and Process Engineering Anhalt University of Applied Sciences Köthen Germany. Department of Biomedical Sciences University of Sassari 07100 Sassari Italy. Institute of Animal Science University of Hohenheim Emil-Wolff-Str Stuttgart Germany. HoLMiR - Hohenheim Center for Livestock Microbiome Research University of Hohenheim Leonore-Blosser-Reisen Weg Stuttgart Germany. Département Médicaments Et Technologies Pour La Santé (DMTS) Université Paris-Saclay CEA INRAE SPI Bagnols-Sur-Cèze France. Department of Biotechnology Delft University of Technology Delft The Netherlands. Institute for Infectious Disease Control National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands. Department of Applied Mathematics Computer Science and Statistics Ghent University 9000 Ghent Belgium. VIB - UGent Center for Medical Biotechnology VIB 9052 Ghent Belgium. Department of Biomolecular Medicine Faculty of Medicine and Health Sciences Ghent University 9052 Ghent Belgium. Department of Molecular Toxicology Helmholtz-Centre for Environmental Research - UFZ GmbH Permoserstrasse 15 04318 Leipzig Germany. Department of Biology University of Pisa 56127 Pisa Italy. Instituto de Catalisis y Petroleoquimica (ICP) CSIC 28049 Madrid Sp

One Health seeks to integrate and balance the health of humans, animals, and environmental systems, which are intricately linked through microbiomes. These microbial communities exchange microbes and genes, influencing not only human and animal health but also key environmental, agricultural, and biotechnological processes. Preventing the emergence of pathogens as well as monitoring and controlling the composition of microbiomes through microbial effectors including virulence factors, toxins, antibiotics, non-ribosomal peptides, and viruses holds transformative potential. However, the mechanisms by which these microbial effectors shape microbiomes and their broader functional consequences for host and ecosystem health remain poorly understood. Metaproteomics offers a novel methodological framework as it provides insights into microbial dynamics by quantifying microbial biomass composition, metabolic functions, and detecting effectors like viruses, antimicrobial resistance proteins, and non-ribosomal peptides. Here, we highlight the potential of metaproteomics in elucidating microbial effectors and their impact on microbiomes and discuss their potential for modulating microbiomes to foster desired functions.

关键词： Metaproteomics Microbial community Bacteriophages Microbiome Microbial effectors

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Electric power supply of steel producing companies: Schematic design solutions to improve reliability of power grids

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AIP Conference Proceedings 2022年第1期2686卷

作者： Gennady P. Kornilov Ildar R. Abdulveleev Oxana S. Logunova Palvan I. Kalandarov Obid Tursunov Dilshod Kodirov Doniyor Abdurakhimov 1Department of Power Supply of Industrial Enterprises Nosov Mangnitogorsk State Technical University Magnitogorsk Russia 2Department of Computer Engineering and Programming Nosov Mangnitogorsk State Technical University Magnitogorsk Russia 3Department of Automation and Control of Technological Process and Production Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 100000 Tashkent Uzbekistan 4Department of Power Supply and Renewable Energy Sources Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 100000 Tashkent Uzbekistan 5Research Institute of Forestry 111104 Tashkent Uzbekistan 6Gulistan State University 120100 Gulistan Uzbekistan

This research is aimed at improving electric power supply reliability at major industrial plants by applying schematic design solutions. The authors analyzed the features of branch electric power distribution systems at a metallurgical plant; considered options of their revamping to improve reliability of electric power supply; carried out experimental research on splitting 110 kV meshed system at the integrated iron and steel works. When performing the research, mathematical simulation methods and full-scale experiment methods were used. Following the research, we proposed three options to revamp the power grid at the industrial plant applying schematic design solutions: Scheme A - separating substations, causing problems, in an individual block; Scheme B - separating independent 110 kV closed electric power grids; Scheme C – splitting the meshed system into two independent circuits. It is proved that the most efficient solution is Scheme C, which is characterized by a lower number of unscheduled downtimes of the facilities by mitigating the effects of faults in one of meshed systems on a continuous operation of shops powered from the neighboring grid; eliminated risks of simultaneous stops of all or the majority of metallurgical shops of the works during short circuits in 110 kV grids; and a considerable reduction in short circuit currents and active losses in 110 kV industrial grids. An aggregate benefit from the proposed measures aimed at revamping of the electrical grid of metallurgical units by applying schematic design solutions is over USD750,000/year.

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Perspectives for self-driving labs in synthetic biology

arXiv

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arXiv 2022年

作者： Martin, Hector Garcia Radivojevic, Tijana Zucker, Jeremy Bouchard, Kristofer Sustarich, Jess Peisert, Sean Arnold, Dan Hillson, Nathan Babnigg, Gyorgy Marti, Jose Manuel Mungall, Christopher J. Beckham, Gregg T. Waldburger, Lucas Carothers, James Sundaram, ShivShankar Agarwal, Deb Simmons, Blake A. Backman, Tyler Banerjee, Deepanwita Tanjore, Deepti Ramakrishnan, Lavanya Singh, Anup Lawrence Berkeley National Laboratory Biological Systems and Engineering Division BerkeleyCA United States Department of Energy Agile BioFoundry EmeryvilleCA United States Joint BioEnergy Institute EmeryvilleCA United States BCAM Basque Center for Applied Mathematics Bilbao Spain Lawrence Berkeley National Laboratory Scientific Data Division BerkeleyCA United States Helen Wills Neuroscience Institute Redwood Center for Theoretical Neuroscience BerkeleyCA United States Lawrence Berkeley National Laboratory Energy Storage and Distributed Resources Division BerkeleyCA United States University of California Davis Department of Computer Science DavisCA United States Global Security Computing Applications Division Lawrence Livermore National Laboratory LivermoreCA United States Engineering Directorate Lawrence Livermore National Laboratory LivermoreCA United States Center for Bioengineering Lawrence Livermore National Laboratory LivermoreCA United States Department of Chemical Engineering Molecular Engineering & Sciences Institute Center for Synthetic Biology University of Washington SeattleWA United States Biosciences Division Argonne National Laboratory ArgonneIL United States Advanced Biofuels and Bioproducts Process Development Unit Lawrence Berkeley National Laboratory BerkeleyCA United States Biomaterials and Biomanufacturing Division Sandia National Laboratories LivermoreCA United States Earth and Biological Sciences Division Pacific Northwest National Laboratories RichlandWA United States Resources and Enabling Sciences Center National Renewable Energy Laboratory GoldenCO80401 United States Department of Bioengineering University of California BerkeleyCA United States

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior. However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology. © 2022, CC BY.

关键词： Synthetic biology

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Exponential convergence for distributed smooth optimization under the restricted secant inequality condition

arXiv

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arXiv 2019年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Chai, Tianyou Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers the distributed smooth optimization problem in which the objective is to minimize a global cost function formed by a sum of local smooth cost functions, by using local information exchange. The standard assumption for proving exponential/linear convergence of first-order methods is the strong convexity of the cost functions, which does not hold for many practical applications. In this paper, we first show that the continuous-time distributed primal-dual gradient algorithm converges to one global minimizer exponentially under the assumption that the global cost function satisfies the restricted secant inequality condition. This condition is weaker than the strong convexity condition since it does not require convexity and the global minimizers are not necessary to be unique. We then show that the discrete-time distributed primal-dual algorithm constructed by using the Euler's approximation method converges to one global minimizer linearly under the same condition. The theoretical results are illustrated by numerical simulations. Copyright © 2019, The Authors. All rights reserved.

关键词： Continuous time systems

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