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arXiv 2023年

作者： Subotić, Irina Groß, Dominic The Automatic Control Laboratory ETH Zürich Switzerland The Department of Electrical and Computer Engineering the University of Wisconsin-Madison United States

We analyze a dual-port grid-forming (GFM) control for power systems containing ac and dc transmission, converter-interfaced generation and energy storage, and legacy generation. To operate such a system and provide standard services, state-of-the-art control architectures i) require assigning grid-following (GFL) and GFM controls to different converters, and ii) result in highly complex system dynamics. In contrast, dual-port GFM control (i) subsumes common functions of GFM and GFL controls in a simple controller, ii) can be applied to a wide range of emerging technologies independently of the network configuration, and iii) significantly reduces system complexity. In this work, we provide i) an end-to-end modeling framework that allows to model complex topologies through composition of reduced-order device models, ii) an in-depth discussion of universal dual-port GFM control for emerging power systems, and iii) end-to-end stability conditions that cover a wide range of network topologies, emerging technologies, and legacy technologies. Finally, we validate our findings in detailed case studies. © 2023, CC BY-NC-ND.

关键词： Complex networks

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Decentralized lateral and longitudinal control of vehicle platoons with constant headway spacing

Decentralized lateral and longitudinal control of vehicle pl...

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IEEE Conference on Decision and control

作者： Paul Wijnbergen Mark Jeeninga Redmer de Haan Erjen Lefeber School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automatic Control Lund University Lund Sweden Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands

The formation of platoons, where groups of vehicles follow each other at close distances, has the potential to increase road capacity. In this paper, a decentralized control approach is presented that extends the well-known constant headway vehicle following approach to the two-dimensional case, i.e., lateral control is included in addition to the longitudinal control. The presented control scheme employs a direct vehicle following approach where each vehicle in the platoon is responsible for following the directly preceding vehicle according to a nonlinear spacing policy. The proposed constant headway spacing policy is motivated by an approximation of a delay-based spacing policy and results in a generalization of the constant headway spacing policy to the two-dimensional case. By input-output linearization, necessary and sufficient conditions for the tracking of the nonlinear spacing policy are obtained, which motivate the synthesis of the lateral and longitudinal controllers of each vehicle in the platoon. By deriving an internal state representation of the follower vehicle and showing input-to-state stability, the internal dynamics for each leader-follower subsystem are shown to be well-behaved in case the leader drives in steady state conditions (i.e., the leader vehicle's trajectory is unexcited). The results are illustrated by a simulation.

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Truthful Matching with Online Items and Offline Agents 50

Truthful Matching with Online Items and Offline Agents

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50th International Colloquium on Automata, Languages, and Programming, ICALP 2023

作者： Feldman, Michal Fusco, Federico Mauras, Simon Reiffenhäuser, Rebecca Blavatnik School of Computer Science Tel Aviv University Israel Microsoft Research Herzliya Israel Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Italy Institute for Logic Language and Computation University of Amsterdam Netherlands

ISBN: (纸本)9783959772785

We study truthful mechanisms for welfare maximization in online bipartite matching. In our (multiparameter) setting, every buyer is associated with a (possibly private) desired set of items, and has a private value for being assigned an item in her desired set. Unlike most online matching settings, where agents arrive online, in our setting the items arrive online in an adversarial order while the buyers are present for the entire duration of the process. This poses a significant challenge to the design of truthful mechanisms, due to the ability of buyers to strategize over future rounds. We provide an almost full picture of the competitive ratios in different scenarios, including myopic vs. non-myopic agents, tardy vs. prompt payments, and private vs. public desired sets. Among other results, we identify the frontier up to which the celebrated e/(e − 1) competitive ratio for the vertex-weighted online matching of Karp, Vazirani and Vazirani extends to truthful agents and online items. © Michal Feldman, Federico Fusco, Simon Mauras, and Rebecca Reiffenhäuser.

关键词： Sales

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Delayed Transitions in GPenSIM 1st

Delayed Transitions in GPenSIM

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Feng, Yuming Samolej, Slawomir Davidrajuh, Reggie School of Computer Science and Engineering Chongqing Three Gorges University Wenzhou China Department Computer and Control Engineering Rzeszow University of Technology Rzeszow Poland Department Electrical Engineering and Computer Science University of Stavanger Stavanger Norway

ISBN: (纸本)9789819646128

The General-purpose Petri Net Simulator (GPenSIM) is a tool for modeling, simulation, and performance analysis of discrete event systems. GPenSIM is specially designed to model real-life industrial systems. Hence, the transitions in GPenSIM represent real-life events, such as machines. However, this induces a problem, namely that an enabled transition consumes tokens from its input places immediately. This act of an enabled transition immediately consuming tokens gives only monetarily visibility to the tokens, which can be a problem for certain cases where we need to see the tokens in their input places for a while. This paper proposes a method to delay an enabled transition ("delayed transitions") so that the tokens it is supposed to consume from its input places will be visible for a while. This paper, after presenting the theory and the method, also presents an application (the cat and mouse problem) of the delayed transitions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Discrete event simulation

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Enhancing Efficiency and Safety Through Autonomous Navigation in the Intensive Care Unit 8

Enhancing Efficiency and Safety Through Autonomous Navigatio...

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8th International Conference of Yearly Reports on Informatics, Mathematics, and engineering, ICYRIME 2023

作者： Ponzi, Valerio Puglisi, Adriano Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

The use of autonomous systems in Intensive Care Units (ICUs) has become incredibly important, especially during the COVID-19 pandemic. This period has overwhelmed both ICUs and hospitals, halting many other medical activities and causing significant challenges. This project aims to develop a navigation system tailored specifically for the ICU environment, adapting it to the unique procedures and regulations of that setting. Due to the critical conditions of ICU patients, strict rules dictate precise requirements for navigation, necessitating a context-specific approach. This work will propose a comprehensive navigation system capable of safely guiding from point A to point B within an ICU while addressing the critical issues present in such environments. Unlike traditional Nav2 systems, it will feature specialized collision avoidance components designed specifically for ICU settings, taking into account both contextual demands and the chosen approach. This will involve implementing a multilayered protection technique and employing active movements to prevent collisions with dynamic obstacles. © 2023 Copyright for this paper by its authors.

关键词： Reinforcement learning

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Fauno: The Italian Large Language Model that will leave you senza parole!

arXiv

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arXiv 2023年

作者： Bacciu, Andrea Trappolini, Giovanni Santilli, Andrea Rodolà, Emanuele Silvestri, Fabrizio Sapienza University Department of Computer Control and Management Engineering Italy Sapienza University Computer Science Department Italy

This paper presents Fauno, the first and largest open-source Italian conversational Large Language Model (LLM). Our goal with Fauno is to democratize the study of LLMs in Italian, demonstrating that obtaining a fine-tuned conversational bot with a single GPU is possible. In addition, we release a collection of datasets for conversational AI in Italian. The datasets on which we fine-tuned Fauno include various topics such as general question answering, computer science, and medical questions. We release our code and datasets on https://***/RSTLess-research/Fauno-Italian-LLM © 2023, CC BY.

关键词： Computational linguistics

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Application Interface for GPenSIM 1st

Application Interface for GPenSIM

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Feng, Yuming Samolej, Slawomir Davidrajuh, Reggie School of Computer Science and Engineering Chongqing Three Gorges University Wenzhou China Department of Computer and Control Engineering Rzeszow University of Technology Rzeszow Poland Department of Electrical Engineering and Computer Science University of Stavanger Stavanger Norway

ISBN: (纸本)9789819646128

The General-purpose Petri Net Simulator (GPenSIM) is a tool used by researchers to model, simulate, and analyze the performance of discrete event systems. Its popularity stems from its simple interface, extensibility, and compatibility with the MATLAB platform. This paper focuses on the crucial role of GPenSIM in Petri Net model-based software-to-software and software-to-hardware access and control, highlighting unique features and capabilities in its application interface. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： MATLAB

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Exploring Brain Tumor Segmentation and Patient Survival: An Interpretable Model Approach 8

Exploring Brain Tumor Segmentation and Patient Survival: An ...

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8th International Conference of Yearly Reports on Informatics, Mathematics, and engineering, ICYRIME 2023

作者： Ponzi, Valerio De Magistris, Giorgio Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

Detecting and delineating brain tumors from MRI images using artificial intelligence presents a complex challenge in medical AI. Recent progress has seen a variety of techniques employed to assist medical professionals in this task. Despite the effectiveness of machine learning algorithms in segmenting tumors, their lack of transparency in decision-making hinders trust and validation. In our project, we constructed an interpretable U-Net Model specifically tailored for brain tumor segmentation, leveraging both the Gradient-weighted Class Activation Mapping (Grad-CAM) Algorithm and the SHapley Additive exPlanations (SHAP) library. We relied on the BraTS2020 benchmark dataset for training and evaluation purposes. The U-Net model we employed yielded promising results. We then utilized Grad-CAM to visualize the crucial features attended to by the model within an image. Additionally, we enhanced interpretability by utilizing the SHAP library to elucidate the predictions made by various models (including Random Forest, KNN, SVC, and MLP) utilized for predicting patient survival days. © 2023 Copyright for this paper by its authors.

关键词： Decision making

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GRU-Net: Gaussian Attention Aided Dense Skip Connection Based MultiResUNet for Breast Histopathology Image Segmentation 28th

GRU-Net: Gaussian Attention Aided Dense Skip Connection Base...

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28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024

作者： Roy, Ayush Pramanik, Payel Ghosal, Sohom Valenkova, Daria Kaplun, Dmitrii Sarkar, Ram Department of Electrical Engineering Jadavpur University Kolkata700032 India Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Department of Electronics and Communication Engineering International Institute of Information Technology Chhattisgarh India Department of Automation and Control Processes Saint Petersburg Electrotechnical University LETI Saint Petersburg Russia Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China

ISBN: (纸本)9783031669545

Breast cancer is a major global health concern. Pathologists face challenges in analyzing complex features from pathological images, which is a time-consuming and labor-intensive task. Therefore, efficient computer-based diagnostic tools are needed for early detection and treatment planning. This paper presents a modified version of MultiResU-Net for histopathology image segmentation, which is selected as the backbone for its ability to analyze and segment complex features at multiple scales and ensure effective feature flow via skip connections. The modified version also utilizes the Gaussian distribution-based Attention Module (GdAM) to incorporate histopathology-relevant text information in a Gaussian distribution. The sampled features from the Gaussian text feature-guided distribution highlight specific spatial regions based on prior knowledge. Finally, using the controlled Dense Residual Block (CDRB) on skip connections of MultiResU-Net, the information is transferred from the encoder layers to the decoder layers in a controlled manner using a scaling parameter derived from the extracted spatial features. We validate our approach on two diverse breast cancer histopathology image datasets: TNBC and MonuSeg, demonstrating superior segmentation performance compared to state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Gaussian distribution

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Efficient Centralised and Decentralised Gaussian Process Approaches for Online Tracking within Stone Soup

Efficient Centralised and Decentralised Gaussian Process App...

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International Conference on Information Fusion

作者： Chenyi Lyu Xingchi Liu James Wright Jordi Barr Alasdair Hunter Lyudmila Mihaylova Department of Automatic Control & Systems Engineering University of Sheffield UK Scientific Computing Department Rutherford Appleton Laboratory Science and Technology Facilities Council UK Defence Science and Technology Laboratory UK

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper explores the application of centralised and distributed Gaussian process algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is on the innovative implementation of Gaussian process methods with learning hyperparameters and implementation with a factorised variance of the Gaussian kernel. The performance of the methods with different kernels was evaluated, not only with the Gaussian kernel. Extensive experiments with various kernel configurations demonstrate their importance in enhancing prediction accuracy and efficiency, especially in real-time tracking. The case studies with manoeuvring targets show significant advancements in tracking capabilities, particularly in wireless sensor networks, using optimised Gaussian process methods. This work advances Stone Soup’s capabilities and lays the groundwork for future investigations into adaptive Gaussian Process applications in tracking and sensor data analysis.

关键词： Wireless sensor networks Technological innovation Analytical models Target tracking Data analysis Gaussian processes Benchmark testing Real-time systems Data models Kernel

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