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Application of a digital intelligent assistant to support industrial processes: the case of adaptive allocation in the face of cyber attacks

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Procedia computer Science 2025年 253卷 1555-1564页

作者： Silvia Colabianchi Department of Computer control and management engineering “Antonio Ruberti” Via Ariosto 25 Rome 00185 Italy

The research proposes the application of Digital Intelligent Assistants (DIAs) as proactive agents that can support employees in dealing with cybersecurity issues in sustainable industrial processes underlying the importance of a fruitful Human-Artificial Intelligence collaboration. Cyber-attacks around the world are constantly increasing. DIAs are becoming more effective, also thanks to the use of Large Language Models. Users are required to recall security procedures and rules. Moreover, attacks are constantly evolving and following different patterns. The study presents how a DIA can be a backup agent during and after an attack. The application of digital intelligent assistance technology helps to reduce the cognitive load and pressure that users feel during downtime. In addition, the solution enhances attack reporting by decreasing the shame experienced by the victims. The research proposes a methodological design defining the agent’s technical and functional characteristics and its adaptive relationship with human characteristics. The solution is developed using the RASA framework and evaluated through a case study based on a phishing attack scenario.

关键词： chatbot adaptive automation industry 4.0 cybersecurity

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Advancing Spoken Dialog Systems for Manufacturing: From Conceptual Architecture and Taxonomy to Real Case Applications and Future Directions 19

Advancing Spoken Dialog Systems for Manufacturing: From Conc...

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19th Annual Meeting of the Young Researchers' Roundtable on Spoken Dialogue Systems, YRRSDS 2023

作者： Colabianchi, Silvia University of Rome la Sapienza Department of Computer Control and Management Engineering "Antonio Ruberti" Via Ariosto 25 Rome00185 Italy

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Enhancement of Scribal Hands Identification Via Self-Supervised Learning (Extended Abstract) 18

Enhancement of Scribal Hands Identification Via Self-Supervi...

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18th Italian Research Conference on Digital Libraries, IRCDL 2022

作者： Lastilla, Lorenzo Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Italy

In this paper, the first successful application of the recent framework of self-supervised learning to the problem of handwriting identification for medieval and modern manuscripts is presented. To this end, a novel dataset consisting of both labeled and unlabeled manuscripts extracted from the Vatican Apostolic Library was produced. Moreover, this contribution shows that pretraining a convolutional neural network by leveraging large amounts of unlabeled manuscripts and fine-tuning this model to the task of interest significantly outperforms other baselines, including the common setup of initializing the network from general-domain features, or training the model from scratch, also in terms of generalization power. Overall, these results reveal the strong potential of self-supervised techniques in the field of digital paleography, where unlabeled data is nowadays available, while labeled data is scarcer. © 2022 Copyright for this paper by its authors.

关键词： Convolutional neural networks

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Z-SASLM: Zero-Shot Style-Aligned SLI Blending Latent Manipulation

arXiv

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arXiv 2025年

作者： Borgi, Alessio Maiano, Luca Amerini, Irene Sapienza University of Rome Department of Computer Control and Management Engineering Italy

We introduce Z-SASLM, a Zero-Shot Style-Aligned SLI (Spherical Linear Interpolation) Blending Latent Manipulation pipeline that overcomes the limitations of current multi-style blending methods. Conventional approaches rely on linear blending, assuming a flat latent space leading to suboptimal results when integrating multiple reference styles. In contrast, our framework leverages the nonlinear geometry of the latent space by using SLI Blending to combine weighted style representations. By interpolating along the geodesic on the hypersphere, Z-SASLM preserves the intrinsic structure of the latent space, ensuring high-fidelity and coherent blending of diverse styles—all without the need for fine-tuning. We further propose a new metric, Weighted Multi-Style DINO VIT-B/8, designed to quantitatively evaluate the consistency of the blended styles. While our primary focus is on the theoretical and practical advantages of SLI Blending for style manipulation, we also demonstrate its effectiveness in a multi-modal content fusion setting through comprehensive experimental studies. Experimental results show that Z-SASLM achieves enhanced and robust style alignment. The implementation code can be found at: https://***/alessioborgi/ZSASLM. © 2025, CC BY.

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The forgotten pillar of sustainability: development of the S-assessment tool to evaluate Organizational Social Sustainability

arXiv

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arXiv 2024年

作者： Annarelli, Alessandro Catarci, Tiziana Palagi, Laura DIAG Department of Computer Control and Management Engineering Antonio Ruberti

Pursuing sustainable development has become a global imperative, underscored adopting of the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDG). At the heart of this agenda lies the recognition of social sustainability as a pivotal component, emphasizing the need for inclusive societies where every individual can thrive. Despite its significance, social sustainability remains a "forgotten pillar," often overshadowed by environmental concerns. In response, this paper presents the development and validation of the S-Assessment Tool for Social Sustainability, a comprehensive questionnaire designed to evaluate organizations' performance across critical dimensions such as health and wellness, gender equality, decent work, and economic growth, reducing inequalities, and responsible production and consumption. The questionnaire was constructed on the critical dimensions identified through a systematic and narrative hybrid approach to the analysis of peer-reviewed literature. The framework has been structured around the values of the SDGs. It aims to empower organizations to better understand and address their social impact, fostering positive change and contributing to the collective effort towards a more equitable and sustainable future. Through collaborative partnerships and rigorous methodology, this research underscores the importance of integrating social sustainability into organizational practices and decision-making processes, ultimately advancing the broader agenda of sustainable development. Copyright © 2024, The Authors. All rights reserved.

关键词： Sustainable development

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Fractional Order Sliding Mode control with Fuzzy Parameter Tuning Applied to a SCARA Robot

Fractional Order Sliding Mode Control with Fuzzy Parameter T...

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2024 IEEE International Multi-Conference on Smart Systems and Green Process, IMC-SSGP 2024

作者： Znidi, Aicha Abdelhedi, Fatma Nouri, Ahmed Said Derbel, Nabil National Engineering School of Gabes University of Gabes Lab: Numerical Control of Industrial Processes Tunisia College of Engineering King Abdulaziz University Department of Electrical and Computer Engineering Jeddah22254 Saudi Arabia University of Sfax National Engineering School of Sfax Control & Energy Management Laboratory Tunisia

ISBN: (纸本)9798350378382

This paper presents the application of Fractional Order Sliding Mode control (FO-SMC) in order to achieve a robust motion trajectory regulation in dynamic robot systems. The proposed control strategy benefits of both advantages of fractional calculus and sliding mode control to upgrade the robustness and the performances of the controller. Moreover, the paper proposes to use a fuzzy tuning of sliding mode controller in order to satisfy the capabilities of the actuators. The stability of the closed loop system has been demonstrated using the Lyapunov theory. Simulation results demonstrate the efficiency of the proposed method achieving precise trajectory tracking and robust performances, it has been shown that fuzzy tuning of the sliding function parameters significantly reduces control variable peaks, making the control more suitable for actuator application. © 2024 IEEE.

关键词： Sliding mode control

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Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and Autonomous Systems Institute(TASI)and the Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

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Pager Explosion:Cybersecurity Insights and Afterthoughts

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2359-2362页

作者： Chuan Sheng Wanlun Ma Qing-Long Han Wei Zhou Xiaogang Zhu Sheng Wen Yang Xiang Fei-Yue Wang Swinburne University of Technology Hawthorn VIC 3122Australia IEEE the School of Computer and Mathematical Sciences the University of AdelaideAdelaideSouth Australia 5005Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

PAGER EXPLOSION:THE *** 2024 Lebanon pager explosions represent one of the most unexpected and devastating technological incidents in recent *** September 17 and 18,2024,thousands of pagers and walkie-talkies exploded simultaneously across Lebanon and parts of Syria,resulting in 42 deaths and more than 3500 *** handheld communication devices,previously regarded as secure and low-profile,were rigged with concealed explosives and remotely triggered by attackers.

关键词： injuries thoughts explosion

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Spectral graph theory to investigate topological and dynamic properties of EEG-based brain networks: An application to post-stroke patients 46

Spectral graph theory to investigate topological and dynamic...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Ranieri, Andrea Pichiorri, Floriana Mongiardini, Elena Colamarino, Emma Cincotti, Febo Mattia, Donatella Toppi, Jlenia Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy Fondazione Santa Lucia Hospital Neuroelectrical Imaging and Bci Laboratory Rome00179 Italy

ISBN: (纸本)9798350371499

Brain networks represent one of the most fascinating biophysics contributions to modern medicine. Nowadays clinical practice largely benefits from network theory to characterize both physiological and pathological brain networks. However, to date the analysis of such systems still relies on classic approaches, thus limiting the amount of information extracted from those networks. As to overcome such a limitation, this work investigates the behavior of brain networks combinig combining both spectral graph theory and random walk analysis. Specifically, the algebraic connectivity and the relaxation time have been extracted from functional resting state brain networks estimated from a population of subacute post-stroke subjects. Results have been correlated with the Upper Extremity Fugl-Mayer Assessment (UEFMA) score of each subject as to assess whether a dependence exists between network's organization and motor impairment in the upper limb. © 2024 IEEE.

关键词： Network theory (graphs)

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Influence of the load variations on the PSS performance during steady state and transient state 20

Influence of the load variations on the PSS performance duri...

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20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Hashim, Wassan Adnan Hamad Hameed, Jawad Derbel, Nabil Al-Qalam University College Department of Technical Computer Engineering Kirkuk Iraq University of Sfax National Engineering School of Sfax Control & Energy Management Lab. Tunisia College of Petroleum Processes Engineering Tikrit University Department of Petroleum Systems Control Engineering Iraq University of Sfax National Engineering School of Sfax Control & Energy Management Lab. Sfax Tunisia

ISBN: (纸本)9798350332568

The load on a power station varies from time to time due to uncertain demands of the consumers and is known as variable load on the station. Also it is known to have an effect on the performance of a power system stabilizer while damping inter-area oscillation. In this paper conventional lead lag PSS and PSS2B are assessed on real case studies;Peerdawod Gas power station in north of Iraq- Erbil. The PSS utilizes the local rotor speed and power as its input. To investigate the effects of dynamic loads on power systems stability, the effectiveness of PSS is tested and compared with the variation of loads during and after sadden faults. The simulation software that used MatlabTM/Simulink;and results of this paper contribute to the understanding of how load variations influence the system damping based on PSS. © 2023 IEEE.

关键词： Voltage regulators

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