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Optimal Strategies to Contain Arboviruses Spread

SN computer Science 2025年第5期6卷 1-13页

作者： Di Giamberardino, Paolo Iacoviello, Daniela Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Globalization, the increase of human travelling and climate changes contribute to the emergency due to arboviruses diffusion. Generally, the infected patients show only mild symptoms, but in some cases, with fragile subjects, this kind of disease can be fatal. In this paper Dengue virus is considered and described by means of a new compartmental model in which the human and the mosquitos populations interact and can infect each other;containment measures, based both on human habits and on the reduction of mosquitoes in different phase of their lives, are determined in the framework of optimal control theory, aiming at decreasing the number of infected patients and limiting the actions to be applied. This latter aspect is particularly important, both for practical and economical aspects, and for ecological reasons, since a too strong actions against mosquitos can be dangerous for the equilibrium of the ecosystem. © The Author(s) 2025.

关键词： Containment strategies Dengue virus Epidemic control Optimal control

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BFuse-Net: Bonferroni Mean Operator-Aided Fusion of Neural Networks for Medical Image Classification 5th

BFuse-Net: Bonferroni Mean Operator-Aided Fusion of Neural ...

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5th International Conference on Medical Imaging and computer Aided Diagnosis, MICAD 2024

作者： Ghosh, Triyas Chakraborty, Soham Kaplun, Dmitrii Gulvanskii, Vyacheslav Sarkar, Ram Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (纸本)9789819638628

In this paper, we have proposed a novel model, called Bonferroni Mean Operator-aided Fusion of Neural Networks (BFuse-Net). Here, we have taken advantage of the capabilities of four deep learning models as the base learners and then applied a customized attention method to prioritize different fine-grained features by passing their outputs via four parallel pipelines. Next, we have employed a novel aggregation method, a modified Bonferroni Mean operator, to merge the decision scores acquired from every pipeline, prioritizing their individual contributions above their interactions with others in the decision scores. Three medical image datasets— LC25000 (colon cancer), Oral Squamous Cell Carcinoma, and Malaria Cell Images have been used for experimentation. The model yields state-of-the-art outcomes for the three datasets. The source codes and additional results can be found at GitHub repository. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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STGNN: a new self-trained generalized neural networks task space control for robot manipulators

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Neural Computing and Applications 2025年 1-26页

作者： Elmogy, Ahmed Elawady, Wael El-Ghaish, Hany Computer Engineering Department Prince Sattam Ibn Abdelaziz University Alkharj16273 Saudi Arabia Computers and Automatic Control Department Faculty of Engineering Tanta University Tanta31527 Egypt

The inherent uncertainties in the dynamic and kinematic parameters of robot manipulators pose significant challenges for their control in task space. This paper introduces an innovative adaptive sliding mode control strategy, leveraging self-trained generalized neural networks to enhance the precision and robustness of robot manipulator control. The proposed framework called STGNN integrates deep neural networks for the real-time estimation and adjustment of dynamics’ and kinematics’ parameters. Key contributions of this work include the development of semi-supervised learning models for adaptive dynamics and kinematics estimation. By training the generalized neural network on different trajectories, the same models can be utilized to operate on a variety of tasks, significantly improving the robustness, scalability, and adaptability of the control system. The STGNN approach allows the models to leverage both labeled and unlabeled data, incorporating a self-training mechanism that enhances their ability to generalize and adapt to diverse operational scenarios. This capability is particularly beneficial for real-time applications, where the ability to learn and adapt on the fly is crucial. Simulation results demonstrate the superior performance of the STGNN framework in controlling robot manipulators in operational space, showcasing its potential for real-world applications. The proposed method significantly advances the adaptability, accuracy, and efficiency of robot control systems, offering notable improvements over conventional approaches. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Self adjusting control systems

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Description and comparison of fault detection algorithms based on a selected building automation device

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Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第3期73卷

作者： Wlostowska, Sandra Kawa, Bartlomiej Borkowski, Piotr Department of Electrical Apparatus Faculty of Electrical Electronics Computer and Control Engineering Lodz University of Technology Lódź Poland

The article compares selected classification algorithms and those dedicated to anomaly detection. The models used temperature measurements in four rooms simulated in the MATLAB Simscape environment as test signals. The empirical part of the work consists of two parts. In the first one, an example data from the simulated building heating model object, models were built using unsupervised and supervised machine learning algorithms. Then, data from the facility was collected again with changed parameters (failures occurred at times other than the test ones, and the temperature patterns differed from those recorded and used to train the models). The algorithm effects and test signals (temperature changes) were saved in the database. The results were presented graphically in the Grafana program. The second part of the work presents a solution in which the analysis of the operating status of the heating system takes place in real time. Using an OPC server, data was exchanged between the MATLAB environment and the database installed on a virtual machine in the Ubuntu system. The conclusions present the results and collect the authors’ suggestions regarding the practical applications of the discussed classification models. © 2025 The Author(s).

关键词： Support vector machines

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Community Membership Hiding via Gradient-based Optimization

arXiv

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arXiv 2025年

作者： Silvestri, Matteo Gabrielli, Edoardo Silvestri, Fabrizio Tolomei, Gabriele Department of Computer Science Sapienza University of Rome Rome Italy Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

We tackle the problem of community membership hiding, which involves strategically altering a network’s structure to obscure a target node’s membership in a specific community identified by a detection algorithm. We reformulate the original discrete counterfactual graph objective as a differentiable constrained optimization task. To solve this, we propose ∇- CMH, a gradient-based method that modifies the network’s structure within the feasible bounds for an individual target node, effectively concealing its membership. Experimental results across multiple datasets and community detection algorithms show that our approach surpasses existing baselines, offering a better balance between accuracy and computational efficiency. © 2025, CC BY.

关键词： Optimization algorithms

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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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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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Architecture of AC-DC Energy Nodes in Supergrids: A Technical Foundation for Future Renewable Integration

Architecture of AC-DC Energy Nodes in Supergrids: A Technica...

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Applied Research in Electrical engineering (AREE), National and International Conference on

作者： Mohammad Hossein Mousavi Hassan Moradi Kumars Rouzbehi Department of Computer and Electrical Engineering Razi University Kermanshah Iran Department of System Engineering and Automatic Control University of Seville Seville Spain

ISBN: (数字)9798350377170

ISBN: (纸本)9798350377187

The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment.

关键词： Renewable energy sources Supply and demand Protocols HVDC transmission Wind farms Power system stability Stability analysis computer security Protection Resilience

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Real-time Embedded System Fault Injector Framework for Micro-architectural State Based Reliability Assessment

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Journal of Electronic Testing: Theory and Applications (JETTA) 2025年 1-16页

作者： Magliano, Enrico Savino, Alessandro Di Carlo, Stefano Department of Control and Computer Engineering(DAUIN) Politecnico di Torino Corso Duca degli Abruzzi 24 Piedmont Turin 10129 Italy

The increasing complexity of Safety-Critical Real-Time Embedded Systems (SACRES) presents significant challenges regarding reliability, security, and trustworthiness. Key concerns include the system’s vulnerability to instantaneous voltage spikes, electromagnetic interference, neutron strikes, and temperatures out of range, which can induce bit-flipping and consequentially temporary corruption of stored memory data and soft errors. These errors may result in system faults that could push the system into dangerous states. In high-stakes fields like automotive, aerospace, and avionics, such failures can have serious, real-world consequences, potentially endangering lives. This paper introduces an innovative, fully configurable fault injection tool designed to monitor and analyze the micro-architectural state of the system. This tool allows a tailored injection campaign, including both CPU registers and RAM, with a flexible fault model able to inject single and multi-bit-flipping in the application and Operating System (OS) space. Tracking the architectural events using the microprocessor’s Performance Monitoring Unit (PMU) and debugging interface. A key feature is its ability to ensure the repeatability of fault injections, which focus on bit-flipping in memory systems. The results of these fault injections allow for a detailed analysis of how soft errors affect system performance, output integrity, and timing predictability, all of which are critical in SACRES. © The Author(s) 2025.

关键词： Architectural Event Embedded System Fault Injector Reliability Soft Error

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A Novel Mutual Information-based Approach for Neurophysiological Characterization of Sense of Presence in Virtual Reality

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IEEE Transactions on Biomedical engineering 2025年 PP卷 PP页

作者： Ronca, Vincenzo Babiloni, Fabio Aricò, Pietro Sapienza University of Rome Department of Computer Control and Management Engineering Italy Sapienza University of Rome Department of Physiology and Pharmacology "vittorio Erspamer" Italy

Objective: The presented work aimed to investigate neurophysiological markers of sense of presence in virtual reality. The study was based on developing and preliminary validating a neurophysiological -based approach for sense of presence evaluation. Methods: A VR environment was designed to modulate multisensory conditions, including visual, auditory, vibrotactile stimuli. EEG, ECG, EDA signals were recorded. The Mutual Information-based sense of presence index (SoPMI) was developed as a synthetic metric for sense of presence, integrating multiple physiological signals. Signal preprocessing and analysis were conducted using EEG-based Global Field Power and Skin Conductance Level to explore their relationship with sense of presence under different VR conditions. Results: SoPMI index demonstrated sensitivity to varying levels of multisensory integration and immersion (all p © 1964-2012 IEEE.

关键词： Virtual reality

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