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检索条件"任意字段=19th International Conference on Control Systems and Computer Science"

共 42804 条记录，以下是31-40 订阅

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A Novel Study on Modelling and Adaptive Optimal control of a Tubular Reactor Based on Gaussian Processes 19th

A Novel Study on Modelling and Adaptive Optimal Control of a...

引用

19th international conference on Artificial Intelligence: Methodology, systems, and Applications, AIMSA 2024

作者： Grancharova, Alexandra Xie, Junhong Kocijan, Juš Department of Industrial Automation University of Chemical Technology and Metallurgy Sofia Sofia Bulgaria Department of Systems and Control Jozef Stefan Institute Ljubljana Slovenia University of Nova Gorica Rožna Dolina Slovenia

ISBN: (纸本)9783031815416

Number of engineering systems can be characterized as complex since they have a dynamic and nonlinear behaviour incorporating a stochastic uncertainty. On the other hand, as a machine learning method, Gaussian processes (GP) provide a practical, probabilistic approach to learning in kernel machines. this makes them very suitable for obtaining probabilistic, nonparametric black-box models of stochastic nonlinear dynamic systems. In this paper, a novel study on the modeling and adaptive optimal control of a tubular reactor is made by using Gaussian processes. Such reactor is a typical example of a nonlinear distributed parameters system, whose first-principles dynamic models consists of partial differential equations. the purpose is to obtain a nonlinear autoregressive models with exogenous input (NARX) of the output concentration and temperature of the reactor by applying a GP modeling approach. the identified surrogate models are then used to design an adaptive model predictive controller to achieve optimal performance of the reactor despite of the stochastic changes in the feed temperature. the performance of the adaptive MPC based on GP models is studied by simulation experiments. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive control systems

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ResNet-50 for Flower Image Classification: A Comparative Study of Segmentation and Non-Segmentation Approaches 19

ResNet-50 for Flower Image Classification: A Comparative Stu...

引用

19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Manga, Abdul Rachman Nirmala Azis, Huzain Fattah, Farniwati Salim, Yulita Darwis, Herdianti Departement of Computer Science Universitas Muslim Indonesia Makassar Indonesia

ISBN: (纸本)9798331507817

Flower image classification poses a challenge in digital image processing, requiring effective methods for feature extraction and classification. the aim of this research is to improve the accuracy of flower image classification by employing ResNet-50 for feature extraction, with and without segmentation, and evaluating the effectiveness of various classification algorithms. the dataset consists of images of Calendula and Coreopsis flowers, totaling 2,025 samples. Four segmentation techniques—Canny, thresholding, Otsu, and Mean Shift—along with a non-segmentation approach are applied. the features extracted using ResNet-50 are classified with Naive Bayes, Support Vector Machine (SVM), Decision Tree, and K-Neighbors Classifier (KNN). Performance evaluation is conducted using accuracy, precision, recall, and F1-score with 5-fold cross-validation. the results show that SVM delivers the best performance in most scenarios. the highest accuracy in segmentation scenarios was achieved with the Mean Shift technique at 0.91, while the non-segmentation approach yielded the highest accuracy of 0.95. the non-segmentation approach proves more effective, indicating segmentation is not always required for high classification accuracy with ResNet-50. this study shows that ResNet-50, especially without segmentation, can significantly improve flower image classification compared to traditional methods, opening opportunities for more efficient systems. © 2025 IEEE.

关键词： Support vector machines

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Homomorphic Encryption Based ECDSA Generation Over Five Party Protocol 19th

Homomorphic Encryption Based ECDSA Generation Over Five Part...

引用

19th international Workshop on Data Privacy Management, DPM 2024, 8th international Workshop on Cryptocurrencies and Blockchain Technology, CBT 2024 and 10th Workshop on the Security of Industrial control systems and of Cyber-Physical systems, CyberICPS 2024 which were held in conjunction with the 29th European Symposium on Research in computer Security, ESORICS 2024

作者： Aggarwal, Akshit Swain, Srinibas Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati India School of Computer and Mathematical Sciences University of Adelaide Adelaide Australia

ISBN: (纸本)9783031823480

Secure computation of multiparty protocol (MPP) is being widely used to address privacy issues in various technologies, such as cryptocurrencies, blockchain, and many more. the security of MPP is computed in various steps, mainly via secret sharing of keys, encryption/decryption of messages, and signature generation. However, literature suggests the secure computation of multiparty is arduous in the presence of adversarial nature of parties. In this paper, we propose a notion for achieving ECDSA in a multiparty protocol using an Authentication server At. We demonstrate this using four steps: 1. proposal of multiparty (five) protocol (5PP) in which there are parties with adversarial natures. 2. setup of 5PP with At that ensures the mutual identification of parties. 3. Encryption of messages in the proposed 5PP. 4. ECDSA signature generation between the parties in the aforementioned setup. We ensure security in all the steps mainly by using modified Paillier cryptosystem and homomorphic encryption. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Authentication Protocol

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Usage of Cybersecurity Standards in Operational Technology systems 19th

Usage of Cybersecurity Standards in Operational Technology...

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作者： Kannelønning, Kristian Katsikas, Sokratis Department of Information Security and Communication Technology NTNU - Norwegian University of Science and Technology Postboks 191 Gjøvik2802 Norway

ISBN: (纸本)9783031823480

the escalating frequency of cyber attacks against industrial installations over the past decade underscores the growing imperative to fortify cybersecurity in organizations. the advent of Industry 4.0 has interconnected factories with the external world, intensifying cybersecurity risks. While international standards are advocated as a source of knowledge to enhance cybersecurity efforts, scant information exists regarding their applicability and usage in Industry 4.0. Diverse cybersecurity standards are available, either specialized for Information Technology (IT) or Operational Technology (OT) or formulated as universal umbrella standards to guide organizations’ efforts. In this paper, two data sources are deployed - a Semi-Systematic Literature Review (SSLR) and interviews- to unveil the extent of utilization of cybersecurity standards for OT systems in the Industry and to identify potential barriers to cybersecurity standard usage. the results indicate a low applicability of cybersecurity standards within OT systems. Additionally, the size and lack of practical guidelines in OT cybersecurity standards act as entry barriers, especially for Small and Medium Enterprises (SMEs) with limited resources. the interviews reveal that the organizations mitigate the identified barriers by creating bespoke internal OT standards appropriate for the organization’s size and goals. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cybersecurity standards IEC62443 Industry 4.0 Operational Technology

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AI-Assisted Assurance Profile Creation for System Security Assurance 19th

AI-Assisted Assurance Profile Creation for System Security ...

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作者： Yamin, Muhammad Mudassar Wen, Shao-Fang Katt, Basel Norwegian University of Science and Technology Gjøvik Norway

ISBN: (纸本)9783031823619

Security systems Assurance (SSA) is crucial as digital threats evolve and cybersecurity becomes more complex. Recent advancements in large language models (LLMs) have opened new avenues for enhancing SSA strategies. these models offer sophisticated data analysis and argumentation capabilities that were previously unattainable. Leveraging these capabilities, our paper introduces an innovative tool powered by LLMs that automates the generation of security assurance profiles by interpreting standards and security requirements specific to systems. We conducted a case study to compare the effectiveness of this LLM-powered tool against traditional methods managed by human experts. the results show that our automated tool’s performance closely matches that of human experts, highlighting the potential of LLMs to transform SSA processes and significantly improve the efficiency and reliability of cybersecurity defenses. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Assurance Profile Large Language Model Retrieval-Augmented Generation Security Assurance

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Machine Learning Based Parameter Estimation of Energy Models in Digital Production Environments 19thth

Machine Learning Based Parameter Estimation of Energy Model...

引用

19th international conference on computer Aided systems theory, EUROCAST 2024

作者： Fichtl, Fabian Ullrich, Marco Heieck, Frieder Lüdemann-Ravit, Bernd Sonthofen Mittagstrasse 28A Sonthofen87527 Germany

ISBN: (纸本)9783031829598

the growing relevance of data science in engineering highlights the challenges of modelling complex systems using conventional methods, which are often time-consuming. this paper explores the application of various machine learning techniques to create energy models, aiming to minimize model deviation errors against real measurements. By comparing different approaches, this study seeks to optimize energy models, enhancing both accuracy and efficiency. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Learning systems

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POP-HIT: Partially Order-Preserving Hash-Induced Transformation for Privacy Protection in Face Recognition Access control 19th

POP-HIT: Partially Order-Preserving Hash-Induced Transformat...

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19th international conference on Security and Privacy in Communication Networks

作者： Dubasi, Yatish Li, Qinghua Luu, Khoa Univ Arkansas Fayetteville AR 72701 USA

ISBN: (纸本)9783031649530;9783031649547

Server-based face recognition access control (SFRAC) is a widely used biometric authentication method where a camera captures a user's face image and sends the face information to a backend server to determine an authentication result. In existing systems, user face images or raw facial features are sent to the backend server, which induces privacy concerns. this paper proposes a method to protect user face privacy in SFRAC systems, such that user face images or raw facial features are never sent to the server, but the system can still do face-based access control. the method uses a novel partially order-preserving hash-induced transformation (POP-HIT) to perform feature transformation on facial embeddings. POP-HIT maps a user's facial features to a transformed space in order to preserve privacy. Authentication is performed by checking the transformed facial embedding of the user's face image captured at the time of authentication against the user's pre-stored transformed facial embeddings at the server, based on similarity metrics or machine learning methods. Since the server only sees transformed facial embeddings, which cannot be used to recover the facial image, facial privacy is protected. Analysis and experimental evaluations show that our method has a high authentication accuracy, and it achieves privacy protection without being vulnerable to impersonation attacks.

关键词： Facial recognition Access control Privacy

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Monitoring Real-Time systems Under Parametric Delay 19th

Monitoring Real-Time Systems Under Parametric Delay

引用

19th international conference on Integrated Formal Methods

作者： Fraenzle, Martin Grosen, thomas M. Larsen, Kim G. Zimmermann, Martin Carl von Ossietzky Univ Oldenburg Oldenburg Germany Aalborg Univ Aalborg Denmark

ISBN: (纸本)9783031765537;9783031765544

Timed Buchi automata provide a very expressive formalism for expressing requirements of real-time systems. Online monitoring of embedded real-time systems can then be achieved by symbolic execution of such automata on the trace observed from the system. this direct construction however only is faithful if observation of the trace is immediate in the sense that the monitor can assign exact time stamps to the actions it observes, which is rarely true in practice due to the substantial and fluctuating parametric delays introduced by the circuitry connecting the observed system to its monitoring device. We present a purely zone-based online monitoring algorithm, which handles such parametric delays exactly without recurrence to costly verification procedures for parametric timed automata. We have implemented our monitoring algorithm on top of the real-time model checking tool UPPAAL, and report on encouraging initial results.

关键词： Monitoring Timing uncertainty Timed Buchi Automata

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Recognition of Remakes and Fake Facial Images 19th

Recognition of Remakes and Fake Facial Images

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作者： Bobulski, Janusz Kubanek, Mariusz Department of Computer Sciences Czestochowa University of Technology Czestochowa42-201 Poland

ISBN: (纸本)9783031823619

computer Vision techniques are extensively utilised in entertainment, enhancing realism in games and movies. Within video games, these techniques enable the recognition of objects, characters, and player movements, thereby enabling more intelligent game responses to player actions, resulting in more prosperous and more immersive experiences. Moreover, integrating deep learning methodologies with computer vision facilitates the automatic generalisation of special effects and enhances live broadcasts with interactive elements. However, such approaches also present challenges, as they can be exploited to manipulate and fabricate information, such as swapping faces in images or videos. this phenomenon is particularly evident in social media, where various forms of counterfeit or manipulated content proliferate, commonly called fake news. Our article proposes a novel convolutional neural network-based method for detecting alterations in real facial images and distinguishing them from artificially generated ones. Our technique, with its potential to revolutionise the field, enables the classification of facial photos into three categories: authentic faces, authentic faces with applied modifications (e.g., through photo editing software), and artificially generated facial images. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Proceedings - 2023 24th international conference on control systems and computer science, CSCS 2023

Proceedings - 2023 24th International Conference on Control ...

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24th international conference on control systems and computer science, CSCS 2023

ISBN: (纸本)9798350313390

the proceedings contain 103 papers. the topics discussed include: evolutionary hyper-heuristics for improving global optimization algorithms;multi-objective decision making system based on spatial -temporal logics;analysis of trajectory optimization for solving tower of Hanoi problem using industrial manipulator;achievements regarding the optimal control of refinery processes;experimental study of pressure variation in a constant volume enclosure;velocity computation for vehicle trajectory tracking: a comparative analysis of performance and efficiency;smart digital-twin hub concept for rice yield prediction and monitoring from multivariate time series data;enhanced cyber-physical system with semantic technologies and machine learning to support smart farming;qualified remote signature through a hybrid cloud architecture;and an industry 4.0 oriented predictive maintenance solution deployed in real-world automotive manufacturing facilities.

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