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ACM Transactions on Algorithms 2025年第2期21卷

作者： Kavitha, Telikepalli Makino, Kazuhisa Schlotter, Ildikó Yokoi, Yu School of Technology and Computer Science Tata Institute of Fundamental Research Mumbai India Research Institute for Mathematical Sciences (RIMS) Kyoto University Kyoto Japan HUN-REN Centre for Economic and Regional Studies Budapest Hungary School of Computing Institute of Science Tokyo Meguro-ku Japan

Consider a directed, rooted graph G = (V ∪ {r}, E) where each vertex in V has a partial order preference over its incoming edges. The preferences of a vertex naturally extend to preferences over arborescences rooted at r. We present a polynomial-time algorithm that decides whether a given input instance admits a popular arborescence, i.e., one for which there is no "more popular"arborescence. In fact, our algorithm solves the more general popular common base problem in the intersection of two matroids: we are given an arbitrary matroid and a partition matroid Mpart over E, where partition classes correspond to a set V of agents with |V| = rank(M) and each agent has a partial order preference over its associated partition class;the problem asks for a common base of M and Mpart such that there is no "more popular"common base. Our algorithm is combinatorial and can be regarded as a primal-dual algorithm. It searches for a solution along with its dual certificate, a chain of subsets of E, witnessing its popularity. Our generalized results, expressed in terms of matroids, demonstrate that the identification of agents with vertices of the graph in the popular arborescence problem is not essential. We also study the related popular common independent set problem. For the case with weak rankings, we formulate the popular common independent set polytope and thus show that a minimum-cost popular common independent set can be computed efficiently. By contrast, we prove that it is NP-hard to compute a minimum-cost popular arborescence, even when rankings are strict. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： duality in linear programming matching under preferences matroids

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Eigenvalue-Based Randomness Test for Residual Diagnostics in Panel Data Models

arXiv

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arXiv 2025年

作者： Kurbucz, Marcell T. Garrido, Betsabé Pérez Jakovác, Antal Institute for Global Prosperity The Bartlett University College London 149 Tottenham Court Road LondonW1T 7NF United Kingdom Department of Computer Science Institute of Data Analytics and Information Systems Corvinus University of Budapest 8 Fővám Square Budapest1093 Hungary Department of Computational Sciences Institute for Particle and Nuclear Physics HUN-REN Wigner Research Centre for Physics 29-33 Konkoly-Thege Miklós Street Budapest1121 Hungary Department of Statistics Institute of Data Analytics and Information Systems Corvinus University of Budapest 8 Fővám Square Budapest1093 Hungary

This paper introduces the Eigenvalue-Based Randomness (EBR) test—a novel approach rooted in the Tracy-Widom law from random matrix theory—and applies it to the context of residual analysis in panel data models. Unlike traditional methods, which target specific issues like cross-sectional dependence or autocorrelation, the EBR test simultaneously examines multiple assumptions by analyzing the largest eigenvalue of a symmetrized residual matrix. Monte Carlo simulations demonstrate that the EBR test is particularly robust in detecting not only standard violations such as autocorrelation and linear cross-sectional dependence (CSD) but also more intricate non-linear and non-monotonic dependencies, making it a comprehensive and highly flexible tool for enhancing the reliability of panel data *** Codes 62H25, 15B52, 62M10 © 2025, CC BY.

关键词： Eigenvalues and eigenfunctions

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A lonely weak tile

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Expositiones Mathematicae 2025年

作者： Kiss, Gergely Londner, Itay Matolcsi, Máté Somlai, Gábor HUN-REN Alfréd Rényi Institute of Mathematics Reáltanoda utca 13-15 Budapest H-1053 Hungary Corvinus University of Budapest Department of Mathematics Fövám tér 13-15 Budapest 1093 Hungary Department of Mathematics Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot 7610001 Israel Department of Analysis and Operations Research Institute of Mathematics Budapest University of Technology and Economics Müegyetem rkp. 3. Budapest H-1111 Hungary ELTE-TTK Institute of Mathematics Pázmány Péter sétány 1/C Budapest H-1117 Hungary

The notion of weak tiling was a key ingredient in the proof of Fuglede's spectral set conjecture for convex bodies, due to the fact that every spectral set tiles its complement weakly with a suitable Borel measure. In this paper we review the concept of weak tiling, and answer a question raised by Kolountzakis, Lev and Matolcsi, by giving an example of a set T which tiles its complement weakly, but T is neither spectral, nor a proper tile. © 2024 Elsevier GmbH

关键词： Spectral set Tiling Weak tiling

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Mono camera-based GPS spoofing detection for aerial vehicles

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IFAC-PapersOnLine 2024年第4期58卷 126-131页

作者： Peter Petro Peter Bauer Budapest University of Technology and Economics Budapest Hungary Systems and Control Laboratory Institute for Computer Science and Control (HUN-REN SZTAKI) HUN-REN Budapest Hungary

This paper presents mono camera-based GPS spoofing detection for aerial vehicles utilizing only image information besides the initial orientation of the vehicle. Orientation information is propagated and motion direction is estimated solely from the mono camera images through the estimation of the essential matrix. Histograms of Oriented Displacements and their correlation are considered to detect spoofing considering GPS and image-based data. Straight and turning simulated fight trajectories of a fixed wing research drone with different turbulence levels are compared to evaluate the method. The results are promising with timely detection of every spoofing scenario and without false alarm. The exploration of real fight data is the topic of future development.

关键词： GPS spoofing detection mono camera relative motion UAV

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Detection and Classification of Small-sized UAVs and Birds in Sparse LiDAR Point Cloud *

Detection and Classification of Small-sized UAVs and Birds i...

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Krisztián Balla Anita Keszler Sándor Gazdag Tamás Szirányi András L. Majdik HUN-REN Institute for Computer Science and Control Hungary

ISBN: (数字)9798331510954

ISBN: (纸本)9798331510961

Consumer drones have become significant safety hazards for critical infrastructure, disrupting airports and airplanes, while also raising privacy concerns, such as unauthorized recording. Hence, in this paper, we explore the problem of detecting UAVs based on sparse point cloud data coming from a rosette scanning LiDAR sensor. Besides distinguishing between background and foreground elements, a major problem is filtering out false-positive detections due to birds and other flying objects. To address this issue, we integrate a classification network into our solution along with a semantic segmentation network, which is responsible for highlighting the foreground objects for the classifier. Our algorithm utilizes the attention mechanism throughout the object detection phase to efficiently capture the global features of the scene, while it benefits from the convolutional layer's local feature maps during classification. Experimental results show that our solution is capable of real-time object detection and recognition while maintaining its robustness.

关键词： Point cloud compression Laser radar Semantic segmentation Object detection Feature extraction Birds Robot sensing systems Robustness Recording Security

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Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control 63

Decoupling parameter variation from noise: Biquadratic Lyapu...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Verhoek, Chris Eising, Jaap Dorfler, Florian Toth, Roland Eth Zürich Institut für Automatik Switzerland Eindhoven University of Technology Control Systems Group Netherlands HUN-REN Institute for Computer Science and Control Systems and Control Laboratory Hungary

ISBN: (纸本)9798350316339

A promising step from linear towards nonlinear data-driven control is via the design of controllers for linear parameter-varying (LPV) systems, which are linear systems whose parameters are varying along a measurable scheduling signal. However, the interplay between uncertainty arising from corrupted data and the parameter-varying nature of these systems impacts the stability analysis and limits the generalization of well-understood data-driven methods available for linear time-invariant systems. In this work, we decouple this interplay using a recently developed variant of the Fundamental Lemma for LPV systems and the concept of data-informativity, in combination with biquadratic Lyapunov forms. Together, these allow us to develop novel linear matrix inequality conditions for the existence of scheduling-dependent Lyapunov functions, incorporating the intrinsic nonlinearity. Appealingly, these results are stated purely in terms of the collected data and bounds on the noise, and they are computationally favorable to check. © 2024 IEEE.

关键词： Data-driven control Linear parameter-varying systems Parameter-dependent Lyapunov functions

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A production scheduling and control system for CAR T cell manufacturing 6

A production scheduling and control system for CAR T cell ma...

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6th CIRP Conference on BioManufacturing, BioM 2024

作者： Kis, Tamás Hort, Simon Györgyi, Péter Szögi, Evelin Schmitt, Robert H. HUN-REN Institute for Computer Science and Control Kende str 13-17 Budapest1111 Hungary Aachen Germany RWTH Aachen University Aachen Germany

This paper addresses some of the new challenges posed by scheduling and controlling the production of chimeric antigen receptor (CAR) T cells for personalized therapies. In this therapy, the patient's T cells are genetically modified by adding a gene for a receptor to help T cells attach to the cancer cell antigens. Then, the modified cells are grown and multiplied (called cell expansion) and finally returned to the patient. The production takes place in a manufacturing system that comprises several devices, which are capable of processing cells from multiple patients at the same time. The efficient operation of such a complex system requires a sophisticated control system accompanied by a scheduler to optimize the production of CAR T cells for several patients simultaneously. We propose a scheduling algorithm, which can handle the uncertain duration of cell expansion, and the maximum time lags between consecutive processes simultaneously, a combination hardly studied in the literature. We also describe the main features of an adaptive control system including service-oriented device connections as well as centralized control and monitoring. Finally, we describe how the overall system works, including a JSON based communication between scheduler and control system. © 2024 The Authors.

关键词： T-cells

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A Non-Parametric Identification Scheme of SISO-LTI Systems Using Blaschke-Products∗ 32

A Non-Parametric Identification Scheme of SISO-LTI Systems U...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Ungvari, Gergo Soumelidis, Alexandros Dozsa, Tamas Eötvös Loránd University Faculty of Informatics Department of Numerical Analysis Budapest Hungary HUN-REN Institute for Computer Science and Control Systems and Control Laboratory Budapest Hungary

ISBN: (纸本)9798350395440

In this manuscript, a novel algorithm is presented for the identification of single input single output linear time invariant (SISO-LTI) systems. The proposed method is able to find poles of the transfer function describing the system without any assumptions on the system order. The results presented in this paper generalize earlier identification schemes based on expansions of the transfer function using generalized rational orthogonal basis functions (GOBFs). These previous methods depended on a convergent sequence constructed from the coefficients of the orthogonal GOBF expansion. The first contribution of this study is showing that a wider family of functions may be used to construct similar pole finding algorithms. The aforementioned previous approaches can be interpreted as special cases of the results presented here. In addition, using this generalization a new pole identification scheme is proposed using finite Blaschke-products. Through experiments, the practical utility of this scheme is verified when compared to earlier variations of the pole finding scheme. © 2024 IEEE.

关键词： Poles

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An Improved Lateral Vehicle control Design Using Ultra-Local Model-Based Slip Estimation

An Improved Lateral Vehicle Control Design Using Ultra-Local...

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Mediterranean Conference on control and Automation (MED)

作者： Dániel Fényes Balázs Németh Péter Gáspár HUN-REN Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

In the paper, a complex estimation and control algorithm is presented for autonomous vehicles. The algorithm has an observer layer that aims to estimate the slip of the vehicle on both the front and rear axles. The observer design is based on the combination of the Linear Parameter Varying (LPV) approach and the ultra-local model technique. The goal of the ultra-local model is to update the cornering stiffness in order for the lateral dynamics of the vehicle model to be updated. A Model Predictive control (MPC) is developed based on the updated model and the estimated slips, that can maintain the lateral stability of the vehicle even under extreme circumstances, e.g., moving on a surface with a low adhesion coefficient. This stabilization is achieved by limiting the slips of the vehicle. The proposed algorithm is tested through a complex test scenario using a high-fidelity simulation software, CarMaker.

关键词： Limiting Software algorithms Estimation Observers Predictive models Prediction algorithms Stability analysis

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Identification of Tire Characteristics Using Physics-Informed Neural Network for Road Vehicles

Identification of Tire Characteristics Using Physics-Informe...

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Mediterranean Conference on control and Automation (MED)

作者： Tamás Hegedűs Balázs Németh Péter Gáspár HUN-REN Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

In this paper, a technique is presented for estimating tire characteristics using a Physics-Informed Neural Network (PINN). By integrating physics-based information during the training process the accuracy of the network is enhanced. Utilizing a probabilistic approach, not only individual parameters are identified but also a confidence interval is determined. Additionally, the paper outlines an iterative algorithm for the case when one of the input signals is not measurable or cannot be estimated accurately. Finally, the approach is validated through simulated and real-world test scenarios.

关键词： Training Automation Accuracy Neural networks Road vehicles Probabilistic logic Tires

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