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Machine Learning Approach for Detecting Potential Anomalous Cosmic Rays Particles Tracks in Earth-Scale Cosmic Ray Extremely Distributed Observatory 15th

Machine Learning Approach for Detecting Potential Anomalous...

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15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Tyc, Jan Zub, Marcin Hachaj, Tomasz Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Krakow Al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031857027

In this paper, we present a novel contribution to the problem of the detection of potential anomalous cosmic rays particle tracks acquired by Earth-scale complex distributed observatory infrastructure. Detection of such signals provides an opportunity to analyze the performance of the entire research infrastructure of a complex system (for example, potential failures) and a chance to record unknown physical phenomena that can be recorded simultaneously with space radiation observations. The observatory comprises a worldwide network of CMOS detectors cooperating in the citizen science paradigm. We propose, evaluate, and compare several data processing, feature extractions, and potential anomaly discovery pipelines based on machine learning approaches. Although, to date, there have already been published works performing detection and analysis of anomalies in the Cosmic Ray Extremely Distributed Observatory Project (CREDO) dataset, they applied single methods without comparing the results with other possible approaches to analyze potential anomalies. In this work, for the first time, we have used and discussed many anomalous discovery approaches not previously applied to this issue to perform analysis of this extensive dataset (nearly 600,000 images). For this reason, the results published here are of significant cognitive importance to the problem under consideration. We have published both our research’s source codes and dataset so our results can be reproduced. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cosmic rays

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A Comparison of Selected Agent-Based Modelling Frameworks 15th

A Comparison of Selected Agent-Based Modelling Frameworks

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15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Gacek, Paulina Bocheńczyk, Dominika Krajewski, Maciej Kruczek, Bartosz Lazarz, Krzysztof Magnuszewski, Pawel Zięciak, Antoni Kamiński, Filip Wąs, Jaroslaw Department of Applied Computer Science Faculty of Electrical Engineering Automatics IT and Biomedical Engineering AGH University of Krakow Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031857027

In recent years, a variety of new frameworks streamlining the process of agent-based modeling has emerged. These frameworks serve different purposes and each offers a unique set of features. In this practical comparative study, we evaluate the performance of various ABM frameworks through a series of benchmark simulations. By comparing the distinct functionalities offered by these tools, we aim to assist in the selection of an appropriate ABM toolkit for developing system models. This review presents a concise overview of seven popular agent-based modeling tools aiming to inspire further exploration and investigation into this subject. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Digital elevation model

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Architecture for Virtual Machine Resource Optimisation Using Explainable AI Algorithms 21st

Architecture for Virtual Machine Resource Optimisation Usin...

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21st International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2024

作者： Villareal, Wilson Andrés Zabala González-Briones, Alfonso Carchi State Polytechnic University Tulcán040101 Ecuador BISITE Research Group Department of Computer Science and Automatics Faculty of Sciences University of Salamanca Salamanca Spain

ISBN: (纸本)9783031809453

The growing demand for online services and resource-intensive applications has led to the need to optimise the allocation of resources on virtual machines. Traditional methods based on manual allocation are insufficient in the face of the complexity and scale of modern virtualised environments. In this context, it is proposed to develop an architecture based on explainable artificial intelligence algorithms to dynamically optimise resource allocation in virtual machines. The objective is to improve the efficiency and performance of virtualised servers. It is expected to obtain a modular architecture that integrates different techniques of explainable artificial intelligence, contributing to the advancement of knowledge in the management of virtualised systems. The research will provide a solution for the optimisation of resources in virtual machines, improving efficiency and transparency in decision-making. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Toward Using Fuzzy Grey Cognitive Maps in Manned and Autonomous Collision Avoidance at Sea

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IEEE Journal of Oceanic Engineering 2025年第2期50卷 1210-1230页

作者： Gil, Mateusz Poczęta, Katarzyna Wróbel, Krzysztof Yang, Zaili Chen, Pengfei Gdynia Maritime University Research Group on Maritime Transportation Risk and Safety Faculty of Navigation Gdynia81-345 Poland Faculty of Electrical Engineering Automatics Control and Computer Science Kielce University of Technology Kielce25-314 Poland Research Institute LiverpoolL3 3AF United Kingdom Wuhan University of Technology School of Navigation Wuhan430063 China Hubei Key Laboratory of Inland Shipping Technology Wuhan430063 China

With Maritime Autonomous Surface Ships (MASS) slowly but steadily nearing full-scale implementation, the question of their safety persists. Regardless of being a disruptive technology, they will likely be subject to the same factors shaping their safety performance as manned ships nowadays are. Yet, the impact of these factors may be different in each case. The current study presents an application of Fuzzy Grey Cognitive Maps (FGCMs) to the comparative evaluation of factors affecting collision avoidance at sea. To this end, subject matter experts have been elicited, and the data obtained from them have been analyzed, concerning how changes in the intensity of given factors would affect safety performance. The obtained results showed that with the use of FGCM, it was possible to model the relative impact of selected factors both on a specific phase of the maritime collision avoidance process as well as on its entirety. The conducted analysis shows noticeable variability of the influence of some factors, depending on the timing of their activation during the process (time dependence), and using FGCM, it was possible to assess its quantification. Furthermore, the results indicate that greater differences can be found between the factors’ impact on phases of an encounter than between manned and autonomous ships. The outcome of this study may be found interesting for all parties involved in maritime safety modeling as well as working on the forthcoming introduction of autonomous ships. © 1976-2012 IEEE.

关键词： Fuzzy Cognitive Maps

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Optimizing early-stage efficiency in complex system development via model-based systems engineering (MBSE) and concurrent engineering (CE) integration

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Research in Engineering Design 2025年第3期36卷 1-36页

作者： Vizitiu, Cristian Dinculescu, Adrian Cătălin Marin, Mihaela Gabriela Nistorescu, Alexandru Ion Dominey, Kevin Alexander Kristály, Dominic Mircea The Space Applications and Technologies Laboratory Institute of Space Science – INFLPR Subsidiary Magurele Romania Department of Automatics and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

The study conducted a systematic review with a bibliometric analysis to examine the extent of utilization and effectiveness of model-based systems engineering (MBSE) and concurrent engineering (CE) in managing and optimizing system design factors in complex systems across various domains, including space, healthcare, as well as active and assisted living and smart environments. The study aims to explore how MBSE and CE can address the inherent challenges in complex system definition and development, particularly focusing on their impact on system design factors such as mission analysis, system architecture, cost, schedule, and risk contingencies, which are commonly considered critical across the entire system lifecycle. By utilizing the PICO framework, the review formulates research questions and systematically searches multiple databases to identify relevant studies. The systematic review highlights that MBSE is prominently used in approximately 88% of the analyzed articles. These integrations enhance the methodologies’ ability to manage complexity and improve efficiency across various stages of the system lifecycle. Specialized tools such as MagicDraw, Cameo Systems Modeler, and OPCAT play a crucial role in the technical implementation of MBSE and CE, providing detailed diagrams and models that represent system components with their interactions and behavior. The principal findings highlight how MBSE and CE support product systems engineering (PSE) in the early lifecycle stages of complex systems of interest. This support is particularly evident in optimizing system design, reducing time, costs, and technological risks, and enhancing the efficiency of business systems engineering through lifecycle management and quality management.

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Cerebral ischemia detection using deep learning techniques

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Health Information science and Systems 2025年第1期13卷 1-19页

作者： Pastor-Vargas, Rafael Antón-Munárriz, Cristina Haut, Juan M. Robles-Gómez, Antonio Paoletti, Mercedes E. Benítez-Andrades, José Alberto Communications and Control Systems Computer Engineering Science Faculty UNED Madrid Spain Radiology area Hospital Universitario de Navarra Navarra Spain School of Technology University of Extremadura Cáceres Spain ALBA Research Group Department of Electric Systems and Automatics Engineering University of Leon León Spain

Cerebrovascular accident (CVA), commonly known as stroke, stands as a significant contributor to contemporary mortality and morbidity rates, often leading to lasting disabilities. Early identification is crucial in mitigating its impact and reducing mortality. Non-contrast computed tomography (NCCT) remains the primary diagnostic tool in stroke emergencies due to its speed, accessibility, and cost-effectiveness. NCCT enables the exclusion of hemorrhage and directs attention to ischemic causes resulting from arterial flow obstruction. Quantification of NCCT findings employs the Alberta Stroke Program Early Computed Tomography Score (ASPECTS), which evaluates affected brain structures. This study seeks to identify early alterations in NCCT density in patients with stroke symptoms using a binary classifier distinguishing NCCT scans with and without stroke. To achieve this, various well-known deep learning architectures, namely VGG3D, ResNet3D, and DenseNet3D, validated in the ImageNet challenges, are implemented with 3D images covering the entire brain volume. The training results of these networks are presented, wherein diverse parameters are examined for optimal performance. The DenseNet3D network emerges as the most effective model, attaining a training set accuracy of 98% and a test set accuracy of 95%. The aim is to alert medical professionals to potential stroke cases in their early stages based on NCCT findings displaying altered density patterns.

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A simulation model for fault tolerance evaluation

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UPB Scientific Bulletin, Series C: Electrical Engineering 2011年第1期73卷 13-26页

作者： Boteanu, Adrian Dobre, Ciprian Faculty of Automatics and Computer Science University POLITEHNICA of Bucharest Romania

In this paper we present a simulation model designed to evaluate fault tolerance solutions in large scale distributed systems. This model extends the MONARC simulation model with new capabilities for fault tolerance simulation. The model includes failure behavior and capabilities to detect and react to faults. We also present an implementation of this model in MONARC, together with specific evaluation results. The model's implementation considers permanent and transient failures occurring within processing units, network components, as well as databases. The model is easily extendable, allowing the additions of new failure models as required by user experiments. The model can be used in conjunction with key performance metrics, being able to easily pinpoint the likely points or areas of failures in the simulated environments.

关键词： Fault tolerance

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Technology readiness impact on high-tech R&D projects

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2013年第2期75卷 241-250页

作者： Ilas, Constantin Faculty of Automatics and Computer Science University POLITEHNICA of Bucharest Romania

In this paper the impact of technology readiness on the activities in an R&D project is discussed. For this, NASA's technology readiness level (TRL) model, initially developed for aerospace is applied to R&D projects. Two case studies from electronics and robotics are presented. Based on this, it is determined that projects can be grouped in four distinct categories, depending on the TRLs of the technologies used in the project. These categories can be used in the future for selecting the best project management approaches, depending on technologies readiness. In this way, the paper aim is to contribute to the current efforts of finding suitable management approaches, depending on project main characteristics.

关键词： Project management

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Optimization of schedulig process in grid environments

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UPB Scientific Bulletin, Series C: Electrical Engineering 2009年第4期71卷 35-48页

作者： Pop, Florin Cristea, Valentin Faculty of Automatics and Computer Science University POLITEHNICA of Bucharest Bucharest Romania

This article presents of the optimization of Grid scheduling problem. The scheduling models of Grid scheduling algorithms are presented. The paper also proposes a taxonomy of scheduling algorithms, based on functional levels, which offers a reference for designing a complete solution for Grid scheduling. The analyses of possibilities for multi-criteria optimization are presented. A critical analysis of scheduling algorithms describes the open issues in this field and represents the support of optimization methods design. The comparison of existing Grid scheduling tools highlights the state of the art for scheduling in Grids. We present the evaluation of some scheduling mechanism. The experimental results demonstrate a very good improvement in load-balancing and execution time for scheduling algorithm used for optimization.

关键词： Scheduling algorithms

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Parametric optimization of a neutral system with two delays and PD-controller

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Archives of Control sciences 2013年第2期23卷 131-143页

作者： Duda, Józef AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Electronics Department of Automatics al. Mickiewicza 30 30-159 Krakow Poland

In this paper a parametric optimization problem for a linear neutral system with two delays with an integral quadratic performance index is formulated and solved. The method of computing of a performance index value bases on determining of a Lyapunov functional defined on a state space such that its value for an initial state is equal to a performance index value. In the paper a form of a Lyapunov functional is assumed and a method of computing its coefficients is given. An example illustrating the application of discussed theory is presented. It concerns the system with a PD-controller designed to control a plant with two delays both retarded and neutral type. For such system a value of considered performance index is determined.

关键词： Time delay

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