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arXiv 2025年

作者： Xie, Peng Betz, Johannes Raimondo, Davide M. Alanwar, Amr TUM School of Computation Information and Technology Department of Computer Engineering Technical University of Munich Heilbronn74076 Germany TUM School of Engineering and Design Department of Autonomous Vehicles Systems Technical University of Munich Garching85748 Germany School of Automatic Control Department of Engineering and Architecture University of Trieste Via Valerio 10 Trieste34127 Italy

Hybrid systems play a crucial role in modeling real-world applications where discrete and continuous dynamics interact, including autonomous vehicles, power systems, and traffic networks. Safety verification for these systems requires determining whether system states can enter unsafe regions under given initial conditions and uncertainties—a question directly addressed by reachability analysis. However, hybrid systems present unique difficulties because their state space is divided into multiple regions with distinct dynamic models, causing traditional data-driven methods to produce inadequate over-approximations of reachable sets at region boundaries where dynamics change abruptly. This paper introduces a novel approach using hybrid zonotopes for data-driven reachability analysis of piecewise affine systems. Our method addresses the boundary transition problem by developing computational algorithms that calculate the family of set models guaranteed to contain the true system trajectories. Additionally, we extend and evaluate three methods for set-based estimation that account for input-output data with measurement noise. © 2025, CC BY.

关键词： Convergence of numerical methods

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Does Gender Influence the Learning Process of Computational Thinking in Secondary Education?

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computer Applications in Engineering Education 2025年第3期33卷

作者： Lía García-Pérez David Roldán-Álvarez José M. Cañas Department of Computer Architecture and Automatic Complutense University Madrid Spain Fuenlabrada School of Engineering Rey Juan Carlos University Fuenlabrada Spain

The gender gap in STEM disciplines both in the workplace and in university education is still a reality. Computational thinking (CT) is deeply related to these disciplines. CT is fundamental to problem-solving and critical thinking, skills that are core to STEM disciplines. CT involves skills like algorithmic thinking, pattern recognition, and abstraction, all of which are necessary for tasks in fields such as engineering, computer science, mathematics, and science. It is important to understand gender differences, if any, in the acquisition of CT skills, so that we can develop more effective teaching strategies for all. This study analyses the gender differences in the development of CT skills (measured with a standard test) in 149 students of a Spanish secondary school, in three courses between 12 and 14 years old, before and after classroom work sessions with a 3D robotics simulator. In the empirical evidence a relevant a priori gender difference was detected in the first course, likely related with prior experiences on computer programming, but boys and girls finish the first year with similar CT levels. Disparate results appear for second year (male students improve more) and third year (female students improve more) which demands further study.

关键词： computational thinking gender differences robotics STEAM STEM

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Modelling and control of a Flexible Floating Boom: First Approach

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IFAC-PapersOnLine 2017年第1期50卷 13108-13113页

作者： Gapingsi, G.E. Korbas, R. Santos, M. Computer Architecture and Automatic Control Department Computer Science Faculty Complutense University of Madrid C/ Profesor García Santesmases 9 Madrid28040 Spain

Floating booms are useful tools in the marine world, especially for marine demarcation where some kind of contamination of sea, ocean or coastal water is present. In this work we have developed a mathematical model for a flexible floating boom which is hooked on two boats (unmanned surface vehicles). It is meant to be used for oil spill containment in marine areas. In order to simplify the model and to make possible its computer simulation, we have adopted a quasi-static approximation where we assume that the inertial forces are small compared to the drag forces applied to the boom. The simulation of this mathematical model has allowed the analysis of the behavior of the floating boom. Based on this knowledge, we have designed a control system which allows us to maintain the flexible floating boom in a specific configuration by controlling its shape. For that purpose, the control approach deals with the speed of the two ends of the floating boom. The results obtained with the implemented control system are encouraging, considering the model is a simplified discrete one and the control effort is reasonable. © 2017

关键词： Marine pollution control systems Drag Knowledge based systems Models Oil spills Unmanned surface vehicles control approach Floating boom Inertial forces Knowledge based control Modelling and controls Quasistatic approximations Simulation Spill containment

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automatic detection of vehicles in outdoor parking lots from zenith perspective using neural networks

Automatic detection of vehicles in outdoor parking lots from...

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2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： García, Juan Manuel Carrera Piorno, Joaquín Recas Mata-Garcia, María Guijarro Department of Computer Architecture and Automatic Control Faculty of Computer Science Universidad Complutense de Madrid Spain

ISBN: (纸本)9781713819462

Nowadays there are a variety of methods to assist parking users in finding free sites in parking lots. However, there is no automatic system that takes into account the size of the car looking for a space or whether the cars adjacent to the free spaces are correctly parked. This paper presents a new method for detecting and calculating the area of vehicles in images taken from a zenith plane using computer vision and machine learning techniques that will help to create a vehicle-oriented search algorithm dedicated to finding the optimal spaces for vehicles entering an outdoor parking lot based on its characteristics. Results with scaled-down and real vehicles show that this new method can detect the area of the vehicles in an image with an average accuracy of 97.98%. ©2020 Society for Modeling & Simulation International (SCS)

关键词： Vehicles

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Hybrid heuristic and mathematical programming in oil pipelines networks: Use of immigrants

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2005年第1期6卷 9-19页

作者： DE LA CRUZ J.M HERRáN-GONZáLEZ A RISCO-MARTíN J.L ANDRéS-TORO B Department of Computer Architecture and Automatic Control Complutense University of Madrid 28040 Madrid SpainDepartment of Computer Architecture and Automatic Control Complutense University of Madrid 28040 Madrid SpainDepartment of Computer Science Engineering C.E.S. Felipe II (U.C.M.) 28300 Aranjuez SpainDepartment of Computer Architecture and Automatic Control Complutense University of Madrid 28040 Madrid Spain

We solve the problem of petroleum products distribution through oil pipelines networks. This problem is modelled and solved using two techniques: A heuristic method like a multiobjective evolutionary algorithm and Mathematical Programming. In the multiobjective evolutionary algorithm, several objective functions are defined to express the goals of the solutions as well as the preferences among them. Some constraints are included as hard objective functions and some are evaluated through a repairing function to avoid infeasible solutions. In the Mathematical Programming approach the multiobjective optimization is solved using the Constraint Method in Mixed Integer Linear Programming. Some constraints of the mathematical model are nonlinear, so they are linearized. The results obtained with both methods for one concrete network are presented. They are compared with a hybrid solution, where we use the results obtained by Mathematical Programming as the seed of the evolutionary algorithm.

关键词： MOEA MILP Hybrid algorithm Constraints

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Reaching a consensus on access detection by a decision system 2

Reaching a consensus on access detection by a decision syste...

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2014 2nd IEEE International Conference on Progress in Informatics and Computing, PIC 2014

作者： Guevara, Cesar Santos, Matilde Martin, Jose Antonio Lopez, Victoria Dep. Computer Architecture and Automatic Control Complutense University of Madrid Madrid Spain

ISBN: (纸本)9781479920334

Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results. They are able to solve problems related to information security in an efficient way. The intrusion detection implies the use of huge amount of information. For this reason heuristic methodologies have been proposed. In this paper, decision trees, Naive Bayes, and supervised classifying systems UCS, are combined to improve the performance of a classifier. In order to validate the system, a scenario based on real data of the NSL-KDD99 dataset is used. © 2014 IEEE.

关键词： Decision trees

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Multiobjective optimization of the transport in oil pipelines networks

Multiobjective optimization of the transport in oil pipeline...

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2003 IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2003

作者： De La Cruz, J.M. De Andres-Toro, B. Herran, A. Porta, E.B. Blanco, P.F. Dpt. Computer Architecture and Automatic Control Universidad Complutense de Madrid Madrid28040 Spain

ISBN: (纸本)0780379373

Heuristic methods are specially well suited to solve combinatorial problems. One of these problems is the distribution of petroleum products through oil pipelines networks. In this paper the problem is stated and solved using a multiobjective and constraint evolutionary optimization algorithm. Several objective functions has been defined to express the goals of the solutions as well as the preferences among them. Some constraints are included as hard objective functions and some has been evaluated through a repairing function to avoid infeasible solutions. An example of working is given. © 2003 IEEE.

关键词： Heuristic methods

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Knowledge-Based Decision System for Sizing Grid-Connected Photovoltaic Arrays

Knowledge-Based Decision System for Sizing Grid-Connected Ph...

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7th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2012

作者： Mikati, Monir Santos, Matilde ÅF Technology Lindholmspiren 9 41756 Gothenburg Sweden Department of Computer Architecture and Automatic Control Universidad Complutense de Madrid 28040 Madrid Spain

In this paper we have developed a methodology and a numerical model for sizing photovoltaic (PV) arrays for grid-connected power consumers. The decision variables proposed are the PV contribution to the power demand and a transfer factor. The latter is a new index that we have defined, and it constitutes key knowledge for decision making when aiming to reduce power transfers between a local power system and the electric grid. The developed model generates days of solar irradiance and calculates PV power output for commercial PV modules. Sizing diagrams are presented that illustrate how the PV capacity, for a specific location and a local power demand, affects the PV contribution to the demand and the power trades with grid. For the particular simulation conditions studied, the sizing diagrams show PV contribution saturation levels and global transfer factor minimums. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Solar energy

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Towards an improvement of the forecast of wind resources in europe: application of unsupervised machine learning on future projections of polar vortex

Towards an improvement of the forecast of wind resources in ...

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2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： Montes, María Rodríguez Ayarzagüena, Blanca Mata-García, María Guijarro Complutense University of Madrid Spain Dept. Earth Physics and Astrophysics Complutense University of Madrid Spain Dept. Computer Architecture and Automatic Control Complutense University of Madrid Spain

ISBN: (纸本)9781713819462

Studying the impact of climate change on wintertime polar stratosphere is of particular relevance not only for climate knowledge but also for tropospheric projections. Machine learning provides a way to extract information from different climate models and combine the data in a such way that patterns are clearer, so predictions can be inducted. The methods used in this study have been region growing algorithm, K-means and combination of predictions. The final results show three clusters of response trends for the intensity and location of the stratospheric polar night jet. The prediction shows an increase in zonal wind intensity over the 2xCO2 and 4xCO2 concentration points and a decrease in the related latitude. Our methods can be extended for more climate models and simulation periods, and will allow not only to map the behavior of the polar night jet, but other stratospheric and tropospheric features and interactions between them. ©2020 Society for Modeling & Simulation International (SCS)

关键词： Climate models

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A novel threshold to identify plant textures in agricultural images by Otsu and Principal Component Analysis

A novel threshold to identify plant textures in agricultural...

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作者： Montalvo, Martín Guijarro, María Ribeiro, Ángela Department of Software Engineering and Artificial Intelligence School of Computer Science University Complutense of Madrid Spain Department of Computer Architecture and Automatic School of Computer Science University Complutense of Madrid Spain Arganda Del Rey Madrid Spain

In this article, a new strategy to detect green plants in a maize crop has been developed. This strategy is based on five main stages: segmentation, reduction of dimensionality based on PCA, Otsu thresholding, threshold combination and final thresholding. Images are taken in RGB color model and transformed to grayscale image using basic vegetation index and PCA method to reduce the dimensionality of data. After this step, a combination of Otsu thresholds by PCA is designed in order to generate a new threshold and binarize the previous grayscale image. The performance of the proposed strategy is validated with an image set and compared with other strategies, being the best of all the methods analyzed in a quantitative mode. © 2018 - IOS Press and the authors. All rights reserved.

关键词： Principal component analysis

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