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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhu, Hengde Kong, Xiangyu Xie, Weicheng Huang, Xin He, Xilin Liu, Lu Shen, Linlin Zhang, Wei Gunes, Hatice Song, Siyang School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Department of Computer Science University of Exeter Exeter United Kingdom Affect AI Anhui China Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University Shenzhen China South China Normal University Foshan China School of Software Technology Zhejiang University Hangzhou China Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom

ISBN: (纸本)157735897X

In dyadic human-human interactions, individuals may express multiple different facial reactions in response to the same/similar behaviours expressed by their conversational partners depending on their personalised behaviour patterns. As a result, frequently-employed reconstruction loss-based strategies lead the training of previous automatic facial reaction generation (FRG) models to not only suffer from the 'one-to-many mapping' problem, but also fail to comprehensively consider the quality of the generated facial reactions. Besides, none of them considered such personalised behaviour patterns in generating facial reactions. In this paper, we propose the first adversarial FRG model training strategy which jointly learns appropriateness and realism discriminators to provide comprehensive task-specific supervision for training the target facial reaction generators, and reformulates the 'one-to-many (facial reactions) mapping' training problem as a 'one-to-one (distribution) mapping' training task, i.e., the FRG model is trained to output a distribution representing multiple appropriate/plausible facial reaction from each input human behaviour. In addition, our approach also serves as the first offline FRG approach that considers personalised behaviour patterns in generating of target individuals' facial reactions. Experiments show that our PerReactor not only largely outperformed all existing offline solutions for generating appropriate, diverse and realistic facial reactions, but also is the first offline approach that can effectively generate personalised appropriate facial reactions. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Diagnosable-by-design model-driven development for IEC 61499 industrial cyber-physical systems

arXiv

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arXiv 2021年

作者： Dowdeswell, Barry Sinha, Roopak MacDonell, Stephen G. Department of IT & Software Engineering School of Engineering Computing and Mathematical Sciences Auckland University of Technology Auckland New Zealand

Integrating the design and creation of fault identification and diagnostic capabilities into Model-Driven Development methodologies is one approach to enhancing the resilience of Industrial Cyber-Physical Systems. We present a Fault Diagnostic Engine designed to recognise and diagnose faults in IEC 61499 Function Block Applications. Using diagnostic agents that interact directly with the target application, we demonstrate fault monitoring and analysis techniques and as well as failure scenario intervention. By designing and building fault diagnostic resources during early phases of Model-Driven Development, both iterative testing and long-term fault management capabilities can be created. While applying and refining appropriate model artifacts, we demonstrate that the concurrent development of function blocks alongside fault management capabilities is both feasible and worthwhile. Copyright © 2021, The Authors. All rights reserved.

关键词： Embedded systems

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Making the Stitching Process of Montaged SEM Images Automatic Using Fourier Transform Properties

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Microscopy and Microanalysis 2021年第S1期27卷 478-480页

作者： Nasim Khoonkari Christopher Anand Nabil Bassim Computing and Software Department McMaster University Hamilton Ontario Canada Hamilton Ontario Canada Computing and Software Department McMaster University Hamilton Ontario Canada Canada Department of Materials Science and Engineering McMaster University Hamilton Ontario Canada Hamilton Ontario Canada

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Entirety of Quantum Uncertainty and Its Experimental Verification

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Chinese Physics Letters 2021年第7期38卷 11-16页

作者： Jie Xie Li Zhou Aonan Zhang Huichao Xu Man-Hong Yung Ping Xu Nengkun Yu Lijian Zhang National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences and School of PhysicsNanjing UniversityNanjing 210093China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Centre for Quantum Software and Information School of SoftwareFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNSWAustralia

As a foundation of quantum physics,uncertainty relations describe ultimate limit for the measurement uncertainty of incompatible ***,uncertainty relations are formulated by mathematical bounds for a specific *** we present a method for geometrically characterizing uncertainty relations as an entire area of variances of the observables,ranging over all possible input *** find that for the pair of position and momentum operators,Heisenberg's uncertainty principle points exactly to the attainable area of the variances of position and ***,for finite-dimensional systems,we prove that the corresponding area is necessarily semialgebraic;in other words,this set can be represented via finite polynomial equations and inequalities,or any finite union of such *** particular,we give the analytical characterization of the areas of variances of(a)a pair of one-qubit observables and(b)a pair of projective observables for arbitrary dimension,and give the first experimental observation of such areas in a photonic system.

关键词： observable union operators

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SmartEdge: Smart Healthcare End-to-End Integrated Edge and Cloud computing System for Diabetes Prediction Enabled by Ensemble Machine Learning

SmartEdge: Smart Healthcare End-to-End Integrated Edge and C...

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IEEE International Conference on Cloud computing Technology and Science (CloudCom)

作者： Alain Hennebelle Qifan Dieng Leila Ismail Rajkumar Buyya Independent Researcher in Information Technology Systems and Artificial Intelligence Applications Abu Dhabi United Arab Emirates Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems University of Melbourne Melbourne Australia Department of Computer Science and Software Engineering Intelligent Distributed Computing and Systems (INDUCE) Lab College of Information Technology Emirates Center for Mobility Research National Water and Energy Center UAE University Al-Ain Abu Dhabi United Arab Emirates

ISBN: (数字)9798331507589

ISBN: (纸本)9798331507596

The Internet of Things (IoT) revolutionizes smart city domains such as healthcare, transportation, industry, and education. The Internet of Medical Things (IoMT) is gaining prominence, particularly in smart hospitals and Remote Patient Monitoring (RPM). The vast volume of data generated by IoMT devices should be analyzed in real-time for health surveillance, prognosis, and prediction of diseases. Current approaches relying on Cloud computing to provide the necessary computing and storage capabilities do not scale for these latency-sensitive applications. Edge computing emerges as a solution by bringing cloud services closer to IoMT devices. This paper introduces SmartEdge, an AI-powered smart healthcare end-to-end integrated edge and cloud computing system for diabetes prediction. This work addresses latency concerns and demonstrates the efficacy of edge resources in healthcare applications within an end-to-end system. The system leverages various risk factors for diabetes prediction. We propose an Edge and Cloud-enabled framework to deploy the proposed diabetes prediction models on various configurations using edge nodes and main cloud servers. Performance metrics are evaluated using, latency, accuracy, and response time. By using ensemble machine learning voting algorithms we can improve the prediction accuracy by 5% versus a single model prediction.

关键词： Cloud computing Accuracy Smart cities Computational modeling Transportation industry Surveillance Machine learning Predictive models Diabetes Time factors

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Text Recognition for Station Equipment Troubleshooting Based on BERT-BiLSTM-CRF Models

Text Recognition for Station Equipment Troubleshooting Based...

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Chinese Automation Congress (CAC)

作者： Wei Bai Xiaosu Wang Bo Liang Guoyuan Yang Hanyu Zhi Yinwei Qiao Institute of Computing Technology China Academy of Railway Sciences co. Ltd. Beijing China Postgraduate Department China Academy of Railway Sciences Beijing China School of Automation and Software Engineering Shanxi University Taiyuan China

The excessive length and high semantic complexity of station equipment fault handling report texts are addressed to the extent that effective text recognition is difficult to achieve. A station equipment fault handling dataset is formulated and a text recognition system for station fault reports based on the BERT-BiLSTM-CRF model is designed. The method first preprocesses the data using the BERT pre-trained language model to generate word vectors, which are then fed into BiLSTM to obtain the embedded contextual information, which is passed through the CRF model to obtain the global optimal solution, and finally outputs the textual results of the station equipment fault handling. The experimental results show that the model outperforms the other five comparative models by more than 2% in terms of precision, recall, and $F$ 1 value (checking accuracy) for intelligent recognition over the five entities predicted by the other five comparative models. This brings a new direction of thinking for the analysis of equipment troubleshooting texts in railway stations.

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An Exploration Study on Developing Blockchain Systems – the Practitioners’ Perspective

arXiv

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arXiv 2024年

作者： Aljedaani, Bakheet Ahmad, Aakash Fahmideh, Mahdi Khan, Arif Ali Shen, Jun Computer Science Department Aljumum University College Umm Alqura University Makkah Saudi Arabia School of Computing and Communications Lancaster University Leipzig Germany School of Business University of Southern Queensland QLD Australia M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland School of Computing and Information Technology University of Wollongong Wollongong Australia

Context: Blockchain-based software (BBS) exploits the concepts and technologies popularized by cryptocurrencies like Bitcoin, offering decentralized transaction ledgers with immutable content for security-critical and transaction-critical systems. Recent research has explored the strategic benefits and technical limitations of BBS in various fields, including cybersecurity, healthcare, education, and financial technologies. Despite growing interest from academia and industry, there is a lack of empirical evidence, leading to an incomplete understanding of the processes, methods, and techniques necessary for systematic BBS development. Objectives: Existing research lacks a consolidated view, particularly empirically-driven guidelines based on published evidence and development practices. This study aims to address the gap by consolidating empirical evidence and development practices to derive or leverage existing processes, patterns, and models for designing, implementing, and validating BBS systems. Method: Tied to this knowledge gap, we conducted a two-phase research project. First, a systematic literature review of 58 studies was performed to identify a development process comprising 23 tasks for BBS systems. Second, a survey of 102 blockchain practitioners from 35 countries across six continents was conducted to validate the BBS system development process. Results: Our results revealed a statistically significant difference (p-value © 2024, CC BY-NC-SA.

关键词： Decentralized finance

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Block Hunter: Federated Learning for Cyber Threat Hunting in Blockchain-based IIoT Networks

arXiv

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arXiv 2022年

作者： Yazdinejad, Abbas Dehghantanha, Ali Parizi, Reza M. Hammoudeh, Mohammad Karimipour, Hadis Srivastava, Gautam The Cyber Science Lab University of Guelph Canada The College of Computing and Software Engineering Kennesaw State University GA United States Information & Computer Science Department King Fahd University of Petroleum & Minerals Saudi Arabia The School of Engineering Department of Electrical and Software Engineering The University of Calgary Alberta Canada The Department of Math and Computer Science Brandon University Manitoba Canada The Research Centre for Interneural Computing China Medical University Taichung Taiwan

Nowadays, blockchain-based technologies are being developed in various industries to improve data security. In the context of the Industrial Internet of Things (IIoT), a chain-based network is one of the most notable applications of blockchain technology. IIoT devices have become increasingly prevalent in our digital world, especially in support of developing smart factories. Although blockchain is a powerful tool, it is vulnerable to cyber attacks. Detecting anomalies in blockchain-based IIoT networks in smart factories is crucial in protecting networks and systems from unexpected attacks. In this paper, we use Federated Learning (FL) to build a threat hunting framework called Block Hunter to automatically hunt for attacks in blockchain-based IIoT networks. Block Hunter utilizes a cluster-based architecture for anomaly detection combined with several machine learning models in a federated environment. To the best of our knowledge, Block Hunter is the first federated threat hunting model in IIoT networks that identifies anomalous behavior while preserving privacy. Our results prove the efficiency of the Block Hunter in detecting anomalous activities with high accuracy and minimum required bandwidth. © 2022, CC BY.

关键词： Blockchain

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Development of the InBan-CIDO Ontology by Reusing the Concepts along with Detecting Overlapping Information

arXiv

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arXiv 2021年

作者： Patel, Archana Debnath, Narayan C. Department of Software Engineering School of Computing and Information Technology Eastern International University Viet Nam

The covid-19 pandemic is a global emergency that badly impacted the economies of various countries. Covid-19 hit India when the growth rate of the country was at the lowest in the last 10 years. To semantically analyze the impact of this pandemic on the economy, it is curial to have an ontology. CIDO ontology is a well-standardized ontology that is specially designed to assess the impact of coronavirus disease and utilize its results for future decision forecasting for the government, industry experts, and professionals in the field of various domains like research, medical advancement, technical innovative adoptions, and so on. However, this ontology does not analyze the impact of the Covid-19 pandemic on the Indian banking sector. On the other side, Covid19-IBO ontology has been developed to analyze the impact of the Covid-19 pandemic on the Indian banking sector but this ontology doesn't reflect complete information of Covid-19 data. Resultantly, users cannot get all the relevant information about the Covid-19 and its impact on the Indian economy. This article aims to extend the CIDO ontology to show the impact of Covid-19 on the Indian economy sector by reusing the concepts from other data sources. We also provide a simplified schema matching approach that detects the overlapping information among the ontologies. The experimental analysis proves that the proposed approach has reasonable *** Codes research © 2021, CC BY.

关键词： Ontology

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Precise Single-stage Detector

arXiv

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arXiv 2022年

作者： Chandio, Aisha Gui, Gong Kumar, Teerath Ullah, Irfan Ranjbarzadeh, Ramin Roy, Arunabha M. Hussain, Akhtar Shen, Yao Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Software Engineering School of Computing National University of Computer and Emerging Sciences Islamabad44000 Pakistan Islamabad44000 Pakistan School of Computing Faculty of Engineering and Computing Dublin City University Dublin Ireland Aerospace Engineering Department University of Michigan Ann ArborMI48109 United States Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology Nawabshah Pakistan

There are still two problems in SDD causing some inaccurate results: (1) In the process of feature extraction, with the layer-by-layer acquisition of semantic information, local information is gradually lost, resulting into less representative feature maps;(2) During the Non-Maximum Suppression (NMS) algorithm due to inconsistency in classification and regression tasks, the classification confidence and predicted detection position cannot accurately indicate the position of the prediction boxes. Methods: In order to address these aforementioned issues, we propose a new architecture, a modified version of Single Shot Multibox Detector (SSD), named Precise Single Stage Detector (PSSD). Firstly, we improve the features by adding extra layers to SSD. Secondly, we construct a simple and effective feature enhancement module to expand the receptive field step by step for each layer and enhance its local and semantic information. Finally, we design a more efficient loss function to predict the IOU between the prediction boxes and ground truth boxes, and the threshold IOU guides classification training and attenuates the scores, which are used by the NMS algorithm. Main Results: Benefiting from the above optimization, the proposed model PSSD achieves exciting performance in real-time. Specifically, with the hardware of Titan Xp and the input size of 320 pix, PSSD achieves 33.8 mAP at 45 FPS speed on MS COCO benchmark and 81.28 mAP at 66 FPS speed on Pascal VOC 2007 outperforming state-of-the-art object detection models. Besides, the proposed model performs significantly well with larger input size. Under 512 pix, PSSD can obtain 37.2 mAP with 27 FPS on MS COCO and 82.82 mAP with 40 FPS on Pascal VOC 2007. The experiment results prove that the proposed model has a better trade-off between speed and accuracy. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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