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

共 42756 条记录，以下是1-10 订阅

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Proceedings - 19th international conference on control systems and computer science, CSCS 2013

Proceedings - 19th International Conference on Control Syste...

引用

19th international conference on control systems and computer science, CSCS 2013

the proceedings contain 97 papers. the topics discussed include: engineered devices to support stroke rehabilitation;a new challenge in ecological process control based on PLCs with Profinet communication protocol;Richardson's method of segment counting versus boxcounting;box-count analysis of two dimensional images: methodology, analysis and classification;a device to measure the geophysical and hydrophysical parameters;an effective tool for the tropical cyclones monitoring;preliminary results for automatic detection of arteriovenous malformations from medical images;group greedy RLS sparsity estimation via information theoretic criteria;Bayesian networks applications in the reliability of software systems for monitoring electrical substations;characterization of tumor angiogenesis using fractal measures;fractal like kinetics and preconditioning;quaternary crack-edge representation for lossless contour compression;and a modified stochastic simulation algorithm for time-dependent intensity rates.

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Research on Intelligent Voice Broadcast System for Smart Water Conservancy 19

Research on Intelligent Voice Broadcast System for Smart Wat...

引用

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

作者： Huang, Zhenqian Chen, Lanxin College of Computer Science and Software Engineering Hohai University Nanjing China University of Birmingham Birmingham United Kingdom

ISBN: (纸本)9798331507817

Smart water management imposes higher demands on the real-time capabilities and intelligence of watershed information monitoring systems. therefore, we propose an intelligent voice broadcast system for monitoring water information, aimed at achieving efficient and accurate dissemination of warning information. this system can be deployed and integrated into existing water information monitoring systems to enable real-time voice broadcasting of water-related information. To ensure the system’s timeliness and effectiveness, we propose a Performance Optimization Mechanism for Data Processing, Priority control for voice broadcasting, a Content Optimization Mechanism, and a Timeliness control Mechanism. Comparative experiments demonstrate that the proposed intelligent voice broadcast system significantly enhance the efficiency and accuracy of water information dissemination, providing an innovative solution for real-time monitoring and early warning in water management. © 2025 IEEE.

关键词： Information management

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Advancing Blackboard Framework: Responsive Trigger Mechanisms and Dynamic Feasibility Conditions for Optimal Knowledge Source Selection 19

Advancing Blackboard Framework: Responsive Trigger Mechanism...

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

作者： Muhd Mukhtar, Hana Munira Husin, Husna Sarirah Ismail, Suriana Rahmat, Azizah Ismail, Roslan Software Engineering Section Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia School of Computer Science Taylor’s University Kuala Lumpur Malaysia Centre of Innovative Digital Education & Emerging Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

Expert systems (ES) rely heavily on effective control mechanisms to navigate complex problem-solving tasks. these mechanisms govern how ES utilizes knowledge and data to make decisions and execute actions. Optimizing these mechanisms, or addressing the "control problem," remains a central challenge. Blackboard architectures, with their separation of knowledge and control processes, offer a promising approach. this study introduces an improved control mechanism for blackboard architectures. It focuses on a critical aspect—trigger mechanisms and feasible conditions—for optimal knowledge source selection to participate in the problem-solving process. By leveraging these features, this study aims to enhance decision-making and problem-solving capabilities within complex domains. this paper focuses on the technical details of exploring how it manages the flow of rule activation and execution throughout the problem-solving process. © 2025 IEEE.

关键词： Expert systems

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Application of Ensemble Machine Learning for DDoS Detection in Complex Network Environments 19

Application of Ensemble Machine Learning for DDoS Detection ...

引用

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

作者： Purnawansyah Supriadi, Naufal Abiyyu Manga, Abdul Rachman Adawiyah, Rabiatul Harlinda Hasanuddin, Tasrif Faculty of Computer Science Universitas Muslim Indonesia Makassar Indonesia

ISBN: (纸本)9798331507817

the volume of network traffic is ever-increasing, hence making DDoS attacks serious threats to the integrity of network security. this research paper focuses on improving the accuracy of detecting DDoS attacks using the ensemble machine learning methods of stacking, bagging, voting, and gradient boosting. In this work, is dataset big enough to correctly reflect real network traffic is used for training and testing purposes. the results indicate that gradient boosting has an accuracy rate of 0.99, followed by stacking and bagging, at 0.98. In this regard, both approaches tend to be efficient in the identification of the attack with limited errors in the prediction. Accordingly, the ensemble technique thus provides a robust approach toward the detection of DDoS attacks, while the study provides important information on the implementation of such strategies in real-time network security systems. Additional investigation is advised to examine supplementary datasets and optimize hyperparameters in order to enhance detection efficacy. © 2025 IEEE.

关键词： Machine learning

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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

19th International Workshop on Data Privacy Management, DPM ...

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

ISBN: (纸本)9783031823480

the proceedings contain 33 papers. the special focus in this conference is on Data Privacy Management. the topics include: reteLLMe: Design Rules for Using Large Language Models to Protect the Privacy of Individuals in their Textual Contributions;plausible Deniability of Redacted Text;exploring Distribution Learning of Synthetic Data Generators for Manifolds;HEDAS: Secure and Efficient Distributed OLAP Using Fully Homomorphic Encryption;card-Based Cryptographic Protocols for three-Input Functions with a Standard Deck of Cards Using Private Operations;grid-Based Decompositions for Spatial Data Under Local Differential Privacy;balancing Privacy and Utility in Multivariate Time-Series Classification;dynamic k-Anonymity for Electronic Health Records: A Topological Framework;Using Static Code Analysis for GDPR Compliance Checks;privacy-Preserving Tabular Data Generation: Systematic Literature Review;A DPIA Repository for Interdisciplinary Data Protection Research;secrecy and Sensitivity: Privacy-Performance Trade-Offs in Encrypted Traffic Classification;route Discovery in Private Payment Channel Networks;A Comparative Study of Rust Smart Contract SDKs for Application-Specific Blockchains;offchain Runtime Verification (for the Tezos Blockchain);quantifying Liveness and Safety of Avalanche’s Snowball;We Will DAG You;assessing the Impact of Sanctions in the Crypto Ecosystem: Effective Measures or Ineffective Deterrents?;Practical Implementation of Pairing-Based zkSNARK in Bitcoin Script;Homomorphic Encryption Based ECDSA Generation Over Five Party Protocol;benchmarking Post-quantum Cryptography in Ethereum-Based Blockchains;exploring Anomaly Detection for Marine Radar systems;hunting Vulnerabilities in the Maritime Domain: A Domain Wide Cybersecurity Vulnerability Analysis;threat Modeling in Satellite Communications for Maritime Operations;cybersecurity Challenges in Industrial control systems: An Interview Study with Asset Owners in Norway;usage of Cybersecurity Standards

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19th International Workshop on Data Privacy Management, DPM ...

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ISBN: (纸本)9783031823619

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

19th International Conference on Artificial Intelligence: Me...

引用

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

ISBN: (纸本)9783031815416

the proceedings contain 18 papers. the special focus in this conference is on Artificial Intelligence: Methodology, systems, and Applications. the topics include: Cross-Lingual Style Transfer TTS for High-Quality Machine Dubbing;an Approach to Discovering, Tracking Over Time, and Summarizing Publicly Available Information on a Given Topic;reinforcement Learning control of Cart Pole System with Spike Timing Neural Network Actor-Critic Architecture;Predictive and Explainable Modelling in Economics on the Case Study of Remittance Prediction Using the NeuDen AI Computational Architecture;deep Learning for Multi-class Diagnosis of thyroid Disorders Using Selective Features;Advanced CNN-SVM Machine Learning Techniques for Facial Skin Ultrasound Image Analysis;Testing the NEAT Algorithm on a PSPACE-Complete Problem;investigating the Regularization of Deep Neural Networks for Affect Recognition with Relevance-Guided Local Explanations;Layered Data-Centric AI to Streamline Data Quality Practices for Enhanced Automation;Combining Graph NN and LLM for Improved Text-Based Emotion Recognition;a Novel Study on Modelling and Adaptive Optimal control of a Tubular Reactor Based on Gaussian Processes;converging Dimensions: Information Extraction and Summarization through Multisource, Multimodal, and Multilingual Fusion;enhancing Question Answering in Lecture Videos with a Multimodal Retrieval-Augmented Generation Framework;agent-Based Simulation Leveraging Declarative Modeling for Efficient Resource Allocation in Emergency Scenarios;enhancing Security in Federated Learning: Detection of Synchronized Data Poisoning Attacks;Clinical and Acquisition Data for Optimizing MGMT Methylation Status Prediction: A Comprehensive Ensemble Strategy Emphasizing Non-invasive Approaches.

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Sound Zone control Based on a Kronecker Second-Order Tensor Decomposition 19th

Sound Zone Control Based on a Kronecker Second-Order Tensor ...

引用

19th National conference on Man-Machine Speech Communication

作者： Mao, Zhien Zhang, Wen Northwestern Polytech Univ Shaanxi Prov Key Lab Artificial Intelligence Xian 710072 Shaanxi Peoples R China Northwestern Polytech Univ Ctr Intelligent Acoust & Immers Commun Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9789819610440;9789819610457

In this work, we address the computational challenges in personal audio systems implemented within a room environment, which typically operate under a multi-input multi-output (MIMO) framework. Traditional control algorithms require long control filters to prevent performance degradation, substantially increasing the computational load due to matrix inversion and overall system complexity. We introduce a novel approach utilizing second-order Kronecker product decomposition, where the loudspeaker control filter is expressed as the Kronecker product of two shorter sub-filters. this method effectively reduces the matrix dimensions required for a single filter, significantly lowering computational complexity compared to traditional time-domain techniques. An iterative filter design is then employed to closely approximate the globally optimal solution. Simulation results demonstrate that our method achieves performance comparable to that of the conventional algorithm while significantly reducing computational demands.

关键词： Personal sound zone Pressure matching Nearest Kronecker product Tensor Decomposition

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Cybersecurity Challenges in Industrial control systems: An Interview Study with Asset Owners in Norway 19th

Cybersecurity Challenges in Industrial Control Systems: An I...

引用

作者： Flå, Lars Halvdan thieme, Christoph Alexander Jaatun, Martin Gilje Hanssen, Geir Kjetil SINTEF Digital Trondheim Norway

ISBN: (纸本)9783031823480

this paper presents cybersecurity challenges related to industrial control systems (ICSs), identified through interviews with ICS asset owners. We interviewed participants from 10 companies within the oil and gas, food and beverage, and electricity generation and distribution industries in Norway. the interviews focused on cybersecurity challenges related to the three topics of supply chain, handling of vulnerabilities, and testbeds and digital twins. thematic analysis of the interviews resulted in identification of 7 challenges, which can serve as inspiration and motivation for future research efforts in the field of ICS and Operational Technology (OT) cybersecurity. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Supply chains

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A Deep Learning Approach for Improving Waste Classification Accuracy with ResNet50 Feature Extraction 19

A Deep Learning Approach for Improving Waste Classification ...

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

作者： Darwis, Herdianti Puspitasari, Rahma Purnawansyah Astuti, Wistiani Atmajaya, Dedy Hasnawi, Mardiyyah Faculty of Computer Science Universitas Muslim Indonesia Makassar Indonesia

ISBN: (纸本)9798331507817

this research investigates the use of deep learning for automatic waste classification, specifically using ResNet50 for feature extraction and combining it with various classification algorithms. the dataset comprises 1889 images categorized into four classes: plastic, metal, cardboard, and paper. Two approaches were evaluated: direct classification and feature extraction with ResNet50. the direct classification models, including SVM, KNN, and Random Forest, resulted in low performance, with an average accuracy of 60%. However, using ResNet50 for feature extraction significantly improved the classification accuracy across all models, with the combination of ResNet50 and SVM achieving an accuracy of 91%, and precision, recall, and F1-Score exceeding 92%. this demonstrates the effectiveness of ResNet50's feature extraction capability in enhancing the classification of images. the findings suggest that combining feature extraction and classification models provides a more accurate and efficient solution for automatic waste management systems, supporting the recycling process and waste management efficiency. © 2025 IEEE.

关键词： Data accuracy

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