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Generalized Critical Observability of Labeled Petri Nets Under Nondeterministic Observations

IEEE Transactions on Automation science and engineering 2025年 22卷 14633-14645页

作者： Zhang, Yuling Hadjicostis, Christoforos N. Li, Zhiwu Xidian University School of Electro-Mechanical Engineering Xi’an710071 China University of Cyprus Department of Electrical and Computer Engineering Nicosia1678 Cyprus Macau University of Science and Technology Institute of Systems Engineering China

This paper addresses the property of critical observability in labeled Petri nets. A system is deemed critically observable if its state estimate (formed by observing the system output) can be determined to belong to a set of either critical markings or non-critical markings. More generally, for a critically observable system, there may be multiple types of critical markings and the operator may desire to know the type to which the current state estimate belongs. We propose a generalized version of critical observability, namely generalized critical observability, and provide two necessary and sufficient conditions to check it based on basis markings and integer linear programs, effectively circumventing the need for an exhaustive enumeration of all reachable markings of the net. In addition, we investigate (generalized) critical observability of Petri nets under nondeterministic observations, which may arise due to the loss of transmission signals or due to interference with sensor measurement outputs. To handle this, an augmented system is constructed from the original Petri net by adding new transitions that capture the effect of transitions associated with nondeterministic labels. Thus, we transform the verification of (generalized) critical observability of a Petri net under nondeterministic observations to that of the augmented model. Two real-world examples illustrate the applicability of the presented notion and methodology. © 2004-2012 IEEE.

关键词： Petri nets

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Fuzzy Decision-Based Clustering for Efficient Data Aggregation in Mobile UWSNs

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computers, Materials & Continua 2025年第4期83卷 259-279页

作者： Aadil Mushtaq Pandith Manni Kumar Naveen Kumar Nitin Goyal Sachin Ahuja Yonis Gulzar Rashi Rastogi Rupesh Gupta Department of Computer Science and Engineering Lovely Professional UniversityJalandhar144402PunjabIndia Department of Computer Science and Engineering Chandigarh UniversityMohali140413PunjabIndia Salesforce Inc. DallasTX 75201USA Department of Computer Science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendragarh123031HaryanaIndia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Application Sir Chhotu Ram Institute of Engineering and TechnologyCh.Charan Singh UniversityMeerut250001Uttar PradeshIndia Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpura140401PunjabIndia

Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the ***,many existing data aggregation techniques are designed exclusively for static networks and fail to reflect the dynamic nature of underwater ***,conventional multi-hop data gathering techniques often lead to energy depletion problems near the sink,commonly known as the energy hole ***,cluster-based aggregation methods face significant challenges such as cluster head(CH)failures and collisions within clusters that degrade overall network *** address these limitations,this paper introduces an innovative framework,the Cluster-based Data Aggregation using Fuzzy Decision Model(CDAFDM),tailored for mobile *** proposed method has four main phases:clustering,CH selection,data aggregation,and *** CH selection,a fuzzy decision model is utilized to ensure efficient cluster head selection based on parameters such as residual energy,distance to the sink,and data delivery likelihood,enhancing network stability and energy *** the aggregation phase,CHs transmit a single,consolidated set of non-redundant data to the base station(BS),thereby reducing data duplication and saving *** adapt to the changing network topology,the re-clustering phase periodically updates cluster formations and reselects *** results show that CDAFDM outperforms current protocols such as CAPTAIN(Collection Algorithm for underwater oPTical-AcoustIc sensor Networks),EDDG(Event-Driven Data Gathering),and DCBMEC(Data Collection Based on Mobile Edge Computing)with a packet delivery ratio increase of up to 4%,an energy consumption reduction of 18%,and a data collection latency reduction of 52%.These findings highlight the framework’s potential for reliable and energy-efficient data aggregation mobile UWSNs.

关键词： Clustering data aggregation data collection fuzzy model monitoring UWSN

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MedFILIP: Medical Fine-grained Language-Image Pre-training

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IEEE Journal of Biomedical and Health Informatics 2025年第5期29卷 3587-3597页

作者： Liang, Xinjie Li, Xiangyu Li, Fanding Jiang, Jie Dong, Qing Wang, Wei Wang, Kuanquan Dong, Suyu Luo, Gongning Li, Shuo The School of Computer Science and Technology Harbin Institute of Technology Harbin China The Department of Thoracic Surgery at No. 4 Affiliated Hospital Harbin Medical University Harbin China The School of Computer Science and Technology Harbin Institute of Technology Shenzhen China The College of computer and control engineering Northeast Forestry University Harbin China The Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia The Department of Biomedical Engineering Department of Computer Data Science Case Western Reserve University ClevelandOH United States

Medical vision-language pretraining (VLP) that leverages naturally-paired medical image-report data is crucial for medical image analysis. However, existing methods struggle to accurately characterize associations between images and diseases, leading to inaccurate or incomplete diagnostic results. In this work, we propose MedFILIP, a fine-grained VLP model, introduces medical image-specific knowledge through contrastive learning, specifically: 1) An information extractor based on a large language model is proposed to decouple comprehensive disease details from reports, which excels in extracting disease deals through flexible prompt engineering, thereby effectively reducing text complexity while retaining rich information at a tiny cost. 2) A knowledge injector is proposed to construct relationships between categories and visual attributes, which help the model to make judgments based on image features, and fosters knowledge extrapolation to unfamiliar disease categories. 3) A semantic similarity matrix based on fine-grained annotations is proposed, providing smoother, information-richer labels, thus allowing fine-grained image-text alignment. 4) We validate MedFILIP on numerous datasets, e.g., RSNA-Pneumonia, NIH ChestXray14, VinBigData, and COVID-19. For single-label, multi-label, and fine-grained classification, our model achieves state-of-the-art performance, the classification accuracy has increased by a maximum of 6.69%. © 2013 IEEE.

关键词： Semantics

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A New Model of Trapped Charge Sources in Switching Transient Studies in the Presence of Shunt Reactors

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IEEE Access 2025年 13卷 37118-37127页

作者： Akafi-Mobarakeh, Mohsen Shariatinasab, Reza Siano, Pierluigi Vahidi, Behrooz Reza Najafi, Hamid University of Birjand Department of Electrical and Computer Engineering Birjand*** Iran University of Salerno Department of Management and Innovation Systems Fisciano84084 Italy National University of Science and Technology POLITEHNICA Bucharest Department of Power Systems Bucharest060042 Romania Tehran*** Iran

Insulation coordination studies are of great importance in power grid reliability. In this paper, a new method is proposed for modeling trapped charge sources (TCS) in switching transient studies. The TCS is used to take into account the voltage stored in line capacitors during reclosing operation after fault occurrence. The proposed model is designed based on the active filter concept, thus overcoming the limitations of conventional TCS for simulating transient states in EMTP/ATPDraw. Given the natural frequencies of a transmission line to which the proposed TCS (PTCS) is connected, it injects the appropriate frequencies and eliminates voltage oscillations which limit the use of TCS. To verify the efficiency of the PTCS, it is implemented in a real system with a shunt reactor, and the results are then compared with field measurements. A comparison of the results shows that the PTCS eliminates the voltage oscillations in the simulation before closing and provides a smooth voltage with the desired amplitude. Using the proposed model, the maximum line switching overvoltage is correctly calculated;this, in turn, results in a more accurate transmission line insulation design, which is technically and economically beneficial. © 2025 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://***/licenses/by/4.0/

关键词： Electromagnetic transients

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A Global Approach to Artificial Intelligence

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IEEE Access 2025年 13卷 76946-76962页

作者： De Miguel, Ana M. Gonzalez Sarasa-Cabezuelo, Antonio Complutense University of Madrid Computer Science Faculty Department of Software Engineering and Artificial Intelligence Madrid Spain Complutense University of Madrid Computer Science Faculty Department of Information Systems and Computing Madrid Spain

This paper presents the initial foundations of a new Global approach to Artificial Intelligence based on the modeling of global intelligence and the development of artificial cooperative systems to support this. The research work brings numerous investigations and some of our most recent creations to develop intelligent systems in urgent global, cooperative domains. The investigations present an overall view of current issues like true natural i.e. global intelligence. The creations include several results in global solutions explorations as well as new models, services, architectures and processes which could be of special interest for global organizations that urgently need to achieve intelligent cooperation. The major aim of the approach is to help these organizations, and other related institutions, to succeed in their complex daily duties where true thinking, more natural intelligence and new global artificial systems are required. Further, the paper provides some guidelines for the next evolutions of the work in the form of a brief, open research agenda and, some general actions for deploying Global Artificial Intelligence into our organizations, suggesting how to build new global artificial intelligent systems in real and virtual ecosystems. © 2013 IEEE.

关键词： cooperation deployment development globalization intelligence

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Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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Computationally efficient reductions between some statistical models 36

Computationally efficient reductions between some statistica...

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36th International Conference on Algorithmic Learning Theory, ALT 2025

作者： Lou, Mengqi Bresler, Guy Pananjady, Ashwin School of Industrial and Systems Engineering Georgia Tech United States Department of Electrical Engineering and Computer Science MIT United States Schools of Industrial and Systems Engineering and Electrical and Computer Engineering Georgia Tech United States

We study the problem of approximately transforming a sample from a source statistical model to a sample from a target statistical model without knowing the parameters of the source model, and construct several computationally efficient such reductions between canonical statistical experiments. In particular, we provide computationally efficient procedures that approximately reduce uniform, Erlang, and Laplace location models to general target families. We illustrate our methodology by establishing nonasymptotic reductions between some canonical high-dimensional problems, spanning mixtures of experts, phase retrieval, and signal denoising. Notably, the reductions are structure-preserving and can accommodate missing data. We also point to a possible application in transforming one differentially private mechanism to another. © 2025 M. Lou, G. Bresler & A. Pananjady.

关键词： Differential privacy

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The TMAP Framework: Describing the Design Space of Technology-Mediated Audience Participation in Live Music

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IEEE Access 2025年 13卷 38593-38608页

作者： Hödl, Oliver Turchet, Luca University of Vienna Faculty of Computer Science Cooperative Systems Research Group Vienna1090 Austria University of Applied Sciences Upper Austria Department for Smart and Interconnected Living Hagenberg4232 Austria University of Trento Department of Information Engineering and Computer Science Trento38123 Italy

Technology-mediated audience participation (TMAP) offers a wide variety of ways to enhance the involvement of spectators during a music performance. Technological change has created rich new opportunities for such interactive performance experiences. Effective design of TMAP requires balancing knowledge from diverse human and technological perspectives and taking into account very different characteristics and requirements in live music performance. However, research in this distinctive area of interaction design is limited, and the provision of practical guidance for designers has been scarcely addressed thus far. To bridge this gap, we propose the TMAP Framework, which describes the design space of audience participation in a practice-oriented way to support design-related processes. This descriptive framework is grounded on existing literature from the last 25 years, and has been iteratively improved and peer reviewed with different experts. It was validated using actual TMAP performances not included in the framework development. The TMAP Framework contains 180 entities in a tree-like sorted structure on four levels. Alongside the contribution to knowledge of extensively describing the design space of TMAP in live music, with the validation of the framework, we demonstrate its completeness, stability and generalisability. In this regard, the framework may also serve as a common language between different perspectives and practitioners, thus addressing the highly interdisciplinary nature of the TMAP field. © 2013 IEEE.

关键词： Economic and social effects

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Topology, Size, and Shape Optimization in Civil engineering Structures: A Review

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computer Modeling in engineering & sciences 2025年第2期142卷 933-971页

作者： Ahmed Manguri Hogr Hassan Najmadeen Saeed Robert Jankowski Faculty of Civil and Environmental Engineering Gdansk University of TechnologyGdansk80-223Poland Department of Computer Science ModelingElectronics and Systems EngineeringUniversity of CalabriaCosenza87036Italy Civil Engineering Department University of RaparinRania46012Iraq Civil Engineering Department Tishk International UniversityErbil44001Iraq

The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering *** optimization approaches seek to determine the optimal design,by considering material performance,cost,and structural *** design approaches aim to reduce the built environment’s energy use and carbon *** comprehensive review examines optimization techniques,including size,shape,topology,and multi-objective approaches,by integrating these *** trends and advancements that contribute to developing more efficient,cost-effective,and reliable structural designs were *** review also discusses emerging technologies,such as machine learning applications with different optimization *** of truss,frame,tensegrity,reinforced concrete,origami,pantographic,and adaptive structures are covered and *** techniques are explained,including metaheuristics,genetic algorithm,particle swarm,ant-colony,harmony search algorithm,and their applications with mentioned structure *** and non-linear structures,including geometric and material nonlinearity,are *** role of optimization in active structures,structural design,seismic design,form-finding,and structural control is taken into account,and the most recent techniques and advancements are mentioned.

关键词： Structural optimization topology optimization size optimization shape optimization multi-objective optimization

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Human Pose Estimation and Event Recognition via Feature Extraction and Neuro-Fuzzy Classifier

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IEEE Access 2025年 13卷 37328-37343页

作者： Hanzla, Muhammad Alshammari, Naif S. Alharbi, Shuaa S. Wahid, Wasim Almujally, Nouf Abdullah Jalal, Ahmad Liu, Hui Air University Department of Computer Science Islamabad44000 Pakistan Majmaah University College of Computer and Information Sciences Department of Computer Science Al Majma’ah11952 Saudi Arabia Qassim University College of Computer Department of Information Technology Buraydah52571 Saudi Arabia Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Systems P.O. Box 84428 Riyadh11671 Saudi Arabia Korea University College of Informatics Department of Computer Science and Engineering Seoul02841 Korea Republic of University of Bremen Cognitive Systems Lab Bremen28359 Germany

This paper introduces an advanced framework for Human Pose Estimation (HPE) and Semantic Event Classification (SEC), addressing the growing demand for sophisticated human skeleton modeling, context-aware feature extraction, and machine learning techniques for accurate event recognition in real-world scenarios. HPE, a fundamental task in applications such as sports analytics and surveillance systems, involves predicting human joint locations from visual data. Despite substantial progress driven by deep learning advancements, particularly in handling occlusions and crowded environments, a comprehensive integration of these innovations remains limited in current literature. To bridge this gap, we propose a novel HPE and SEC system featuring a robust six-stage pipeline. The workflow begins with preprocessing steps, including video-to-image sequence conversion, floor removal to reduce noise, grayscale transformation, and human silhouette extraction via binary masks. Human detection is performed using the GrabCut algorithm. Full-body feature extraction incorporates 1-D Fourier Transform, 2-D energy-based motion analysis, 0–180° intensity mapping via the Radon Transform algorithm, and movable body part detection using Fourier-Based Correlation. Key point features are characterized through the degree of freedom, human landmark detection via the HSV algorithm, and angular point analysis using the media pipe algorithm. Features are then optimized using the Ray Optimizer and classified through a Neuro-Fuzzy classifier. The proposed system achieves classification accuracies of 94.82%, 92.33%, and 93.63% on the UCF Sports Actions, Human Action Recognition (HAR), and MPII Human Pose datasets, respectively, outperforming state-of-the-art methods and demonstrating its effectiveness in tackling real-world challenges. © 2025 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://***/licenses/by/4.0/

关键词： Sports

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