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computer, Vision and intelligent Technology (ICCVIT), International Conference on

作者： Licheng Zhuang Jun Hu Qingqing Wang Yanyan Wang Kaikai Zhang Sheng Liu School of Computer Science and Technology Huaibei Normal University Huaibei China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Huaibei China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

The attack behavior in the network poses a threat to security and privacy issues. In order to improve the effectiveness of IoT network attack detection and compensate for the shortcomings of traditional machine learning methods in detection capabilities, a network intrusion detection method based on lightweight convolutional neural networks (CNN) and bidirectional long short-term memory networks (BiLSTM) is proposed. This method preprocesses data through normalization techniques, extracts data features from both spatial and temporal dimensions using CNN and BiLSTM models, and inputs the extracted spatiotemporal feature vectors into the CNN BiLSTM upper classifier for training, achieving intrusion detection. The proposed model was validated on the dataset UNSW-NB15, and the results showed that the binary and multi classification accuracy of the CNN_BiLSTM model was around 93%. Compared with other methods, the proposed method significantly improves the accuracy of network intrusion detection, and also demonstrates better performance in detection accuracy and false positive rate.

关键词： Training Accuracy Bidirectional long short term memory Network intrusion detection Feature extraction Vectors Spatiotemporal phenomena Convolutional neural networks Data mining Security

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QoS Improvement using Federated Learning-based Position Prediction for mobile IoT 10

QoS Improvement using Federated Learning-based Position Pred...

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Zafar, Saniya Alshehri, Mohammed S. Shah, Syed Aziz Ahmad, Jawad Zafar, Adnan Khattak, Aizaz Ahmad Institute of Space Technology Department of Electrical Engineering Islamabad Pakistan Najran University College of Computer Science and Information Systems Department of Computer Science Saudi Arabia Coventry University Research Centre for Intelligent Healthcare United Kingdom Prince Mohammad Bin Fahd University Cybersecurity Center Alkhobar Saudi Arabia Edinburgh Napier University School of Computing Engineering and the Built Environment United Kingdom

ISBN: (纸本)9798350373011

The rapid advancement in mobile broadband technology has evolved wireless infrastructure influencing internet-of-things (IoTs). This evolution has made mobile IoTs (mIoTs) as centre of attention due to its potential of providing seamless connectivity to enable intelligent transportation systems with huge data demands of vehicular users. To address the ever-escalating data demands of vehicular mobile users, vehicular edge computing (VEC) and moving small cells (mSCs) play a pivotal role. mSCs together with VEC are capable to provide improved service quality for mIoTs. However, incorporating the mSCs in vehicles for mIoTs presents challenges while assigning the resources in mIoT-mSC network. This is due to the existence of time varying interference among mSCs. This work explores the distributed resource assignment mechanism for RSU assisted mIoT-mSC network formed in vehicular environment. In the proposed work, location prediction of city buses deployed with mSCs is done using federated learning (FL) which is subsequently utilized for efficient assignment of resources in mIoT-mSC network. Numerical results are provided to validate the proposed resource assignment mechanism. © 2024 IEEE.

关键词： intelligent systems

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Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys

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science China(Technological sciences) 2023年第6期66卷 1815-1830页

作者： LIU Yue DING Lin YANG ZhengWei GE XianYuan LIU DaHui LIU Wei YU Tao AVDEEV Maxim SHI SiQi School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Shanghai Engineering Research Center of Intelligent Computing System Shanghai 200444China State Key Laboratory of Advanced Special Steel&Shanghai Key Laboratory of Advanced Ferrometallurgy&School of Materials Science and Engineering Shanghai UniversityShanghai 200444China Materials Genome Institute Shanghai UniversityShanghai 200444China Institute of Functional Materials Central Iron&Steel Research InstituteBeijing 100081China Australian Nuclear Science and Technology Organisation Locked Bag 2001Kirrawee DC NSW 2232Australia School of Chemistry The University of SydneySydney 2006Australia Zhejiang Laboratory Hangzhou 311100China

Despite the huge accumulation of scientific literature,it is inefficient and laborious to manually search it for useful information to investigate structure-activity ***,we propose an efficient text-mining framework for the discovery of credible and valuable domain knowledge from abstracts of scientific literature focusing on Nickel-based single crystal ***,the credibility of abstracts is quantified in terms of source timeliness,publication authority and author’s academic ***,eight entity types and domain dictionaries describing Nickel-based single crystal superalloys are predefined to realize the named entity recognition from the abstracts,achieving an accuracy of 85.10%.Thirdly,by formulating 12 naming rules for the alloy brands derived from the recognized entities,we extract the target entities and refine them as domain knowledge through the credibility *** this,we also map out the academic cooperative“Author-Literature-Institute”network,characterize the generations of Nickel-based single crystal superalloys,as well as obtain the fractions of the most important chemical elements in *** extracted rich and diverse knowledge of Nickel-based single crystal superalloys provides important insights toward understanding the structure-activity relationships for Nickel-based single crystal superalloys and is expected to accelerate the design and discovery of novel superalloys.

关键词： Nickel-based single crystal superalloys text mining named entity recognition credibility analysis domain knowledge

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IF-Font: ideographic description sequence-following font generation 24

IF-Font: ideographic description sequence-following font gen...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Xinping Chen Xiao Ke Wenzhong Guo Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou University Fuzhou China and Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China

ISBN: (纸本)9798331314385

Few-shot font generation (FFG) aims to learn the target style from a limited number of reference glyphs and generate the remaining glyphs in the target font. Previous works focus on disentangling the content and style features of glyphs, combining the content features of the source glyph with the style features of the reference glyph to generate new glyphs. However, the disentanglement is challenging due to the complexity of glyphs, often resulting in glyphs that are influenced by the style of the source glyph and prone to artifacts. We propose IF-Font, a novel paradigm which incorporates Ideographic Description Sequence (IDS) instead of the source glyph to control the semantics of generated glyphs. To achieve this, we quantize the reference glyphs into tokens, and model the token distribution of target glyphs using corresponding IDS and reference tokens. The proposed method excels in synthesizing glyphs with neat and correct strokes, and enables the creation of new glyphs based on provided IDS. Extensive experiments demonstrate that our method greatly outperforms state-of-the-art methods in both one-shot and few-shot settings, particularly when the target styles differ significantly from the training font styles. The code is available at https://***/Stareven233/IF-Font.

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Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation

arXiv

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arXiv 2024年

作者： Mou, Xinyi Wei, Zhongyu Huang, Xuanjing School of Data Science Fudan University China Research Institute of Intelligent and Complex Systems Fudan University China School of Computer Science Fudan University China Shanghai Collaborative Innovation Center of Intelligent Visual Computing China

Social media has emerged as a cornerstone of social movements, wielding significant influence in driving societal change. Simulating the response of the public and forecasting the potential impact has become increasingly important. However, existing methods for simulating such phenomena encounter challenges concerning their efficacy and efficiency in capturing the behaviors of social movement participants. In this paper, we introduce a hybrid framework HiSim for social media user simulation, wherein users are categorized into two types. Core users are driven by Large Language Models, while numerous ordinary users are modeled by deductive agent-based models. We further construct a Twitter-like environment to replicate their response dynamics following trigger events. Subsequently, we develop a multi-faceted benchmark SoMoSiMu-Bench for evaluation and conduct comprehensive experiments across real-world datasets. Experimental results demonstrate the effectiveness and flexibility of our method 1 Copyright © 2024, The Authors. All rights reserved.

关键词： Computational methods

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Joint Extraction of Biomedical Entities and Relations based on Decomposition and Recombination Strategy

Joint Extraction of Biomedical Entities and Relations based ...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Zhu, Qiang Hong, Cheng Wang, Bangchao Hu, Xinrong Yang, Jie Liu, Junping Engineering Research Center of Hubei Province for Clothing Information Hubei Provincial Engineering Research Center for Intelligent Textile and Fashion China School of Computer Science and Artificial Intelligence Wuhan Textile University China School of Computing and Information Technology University of Wollongong Australia

ISBN: (纸本)9781665468190

Entities and relations extraction is one of the key task to build medical knowledge graph, which is of great significance to the development of medical artificial intelligence. However, overlapping triples are great challenge for biomedical entities and relations extraction. In order to improve the performance of biomedical entities and relations extraction, we propose a joint extraction of entities and relations method based on decomposition and recombination strategy to mine biomedical text. Our method decomposes entities and relations extraction task into three related sub-modules, which are entity tagging module, relation classification module and recombination matching module. Our main contributions are as follows: first, we introduce a decomposition and recombination end-to-end learning framework for joint entities and relations extraction. Second, we propose a bi-directional prediction method to deal with the overlapping triples problem. Finally, we propose the negative samples generation method to alleviate the error accumulation among these modules. The extensive experiments demonstrate that our method can improve the F1 score by 4.36%, 2.13% and 11.72% in ADE, DDI and BB biomedical corpus. © 2022 IEEE.

关键词： Extraction

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Construction and optimization of a computational holographic lithography system 8

Construction and optimization of a computational holographic...

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8th International Conference on Speckle Metrology, Speckle 2023

作者： Chen, Rui Lin, Angyi You, Jianfeng Lin, Huixiang Zhao, Wenqing Zhang, Fucai School of Control and Computer Engineering North China Electric Power University Baoding071003 China The Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China Engineering Research Center of Intelligent Computing for Complex Energy Systems Ministry of Education North China Electric Power University China

ISBN: (数字)9781510674592

ISBN: (纸本)9781510674585

Traditional lithography techniques are currently facing challenges, including high costs and the susceptibility of mask plates to damage. This research aims to elucidate the feasibility and technical constraints of a novel diffraction lithography approach. This method can reduce the size and cost of lithography machines, break through existing technological barriers, and offer new possibilities for the future development of lithography machines. We have built a basic computational holographic lithography system utilizing a 405nm laser and validated the system using holograms obtained with both classical GS algorithm and a newly proposed method. With the GS holograms, patterns with 700nm features have been successfully exposed on the photoresist. With our new algorithms, multiple holograms for the same target pattern can be generated with different settings in the algorithm. Sequential exposure of those holograms resulted in continuous lines 500 nm wide with reduced speckle artifacts, which was about a 1.4-time improvement over the result from the GS algorithm. Future research will focus on optimizing and enhancing the experimental system and the hologram calculation methods to reduce the line widths further and improve the exposure pattern quality. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Holograms

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A Conflicting Evidence Fusion Method Based on Game Theory Combination Weighting

A Conflicting Evidence Fusion Method Based on Game Theory Co...

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computer, Vision and intelligent Technology (ICCVIT), International Conference on

作者： Ziye Wang Jianyu Xiao School of Computer Science and Technology Huaibei Normal University Huaibei China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior Huaibei China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

This essay introduces a new approach to address the challenges of applying Dempster-Shafer evidence theory to tackling high-conflict evidence. We first employed Jousselme’s distance and compatibility coefficients to measure confidence and support, then converted these values into vectors. Next, we applied game theory to convert the vectors into a system of linear equations,from which we obtained a corresponding combination of weight coefficients that we used to modify the initial evidence. Finally, we applied the Dempster-Shafer combination rule to achieve evidence fusion. A case analysis shows that our proposed method provides more sensible fusion results for high-conflict evidence.

关键词： computer vision Accuracy Evidence theory Data integration Reliability theory Vectors Game theory Convergence

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A Conflicting Evidence Fusion Method Based on a Greedy Strategy

A Conflicting Evidence Fusion Method Based on a Greedy Strat...

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computer, Vision and intelligent Technology (ICCVIT), International Conference on

作者： Haibo Li Jianyu Xiao Qi Tang School of Computer Science and Technology Huaibei Normal University Huaibei China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior Huaibei China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

To address the issue of the conventional D-S combination rule not effectively dealing with highly conflicting evidence fusion, a conflicting evidence fusion algorithm utilizing a greedy strategy is proposed. First, by adopting a greedy strategy, the effective evidence distance is defined based on Jousselme’s evidence distance, followed by the definition of strongly and weakly correlated evidence. The average value of the effective evidence distance is calculated, and based on this the evidence is classified. Finally, weights are calculated individually for the classified evidence. Weights are then reassigned to the two types of evidence, and the corrected evidence is fused to obtain the final fusion result. Numerical examples are provided to demonstrate the effectiveness of the method proposed in this paper in addressing the limitations of the conventional D-S combination rule for fusing highly conflicting evidence.

关键词： computer vision Correlation Evidence theory Classification algorithms

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Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 985-996页

作者： Lei Zou Zidong Wang Bo Shen Hongli Dong Guoping Lu College of Information Science and Technology Donghua UniversityShanghai 201620 Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesex UB83PHUK Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential *** avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption *** purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l_(2)-l_(∞)performance is *** conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state ***,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.

关键词： Artificial-noise-assisted technique eavesdropping encryption-decryption scheme energy-to-peak state estimation finitehorizon state estimation

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