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2nd International Conference on Human Machine Interaction, ICHMI 2022

作者： Yang, Fan Yang, Manyuan Yu, Zhiwen Northwestern Polytechnical University China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Normal University China

ISBN: (纸本)9781450396615

For the sake of determining the reliability of an event, this paper proposes a method of identifying the authenticity of a microblog event based on human-machine collaboration. Using the Weibo that was spoken in the incident and the public information of the users participating in the event to identify false incidents. Then separately calculate the user's credibility and the emotional stance of Weibo and comments. The calculation of user credibility takes the complete information of the user as a static description of the user. When performing emotional standpoint detection, we divide it into two steps. For a piece of Weibo, its comments are tested for further computation, for different microblog, the emotions between microblog are tested. Building a graph model for an event. While processing the model, some special microblogs are extracted. Human will deal with these microblogs and give feedback to the graph model. Then the model will be changed accordingly. Finally, GCN is leveraged to process the model to obtain the true and false of the event. Through extensive experiments to verify the proposed model and show a comparative performance, the accuracy is 89.34 and the F-score reaches0.9375. © 2022 ACM.

关键词： Social networking (online)

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Vsgnet: Visual Saliency Guided Network for Skin Lesion Segmentation

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SSRN 2023年

作者： Cai, Zhefei Fan, Yingle Fang, Tao Wu, Wei Laboratory of Pattern Recognition and Image Processing Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Zhejiang310058 China

The accuracy of skin lesion segmentation is of great significance for the subsequent clinical diagnosis. In order to improve the segmentation accuracy, some pioneering works tried to embed multiple complex modules, or used the huge Transformer framework, but due to the limitation of computing resources, these type of large models were not suitable for the actual clinical environment. To address the coexistence challenges of precision and lightweight, we propose a visual saliency guided network (VSGNet) for skin lesion segmentation, which generates saliency images of skin lesions through the efficient attention mechanism of biological vision, and guides the network to quickly locate the target area, so as to solve the localization difficulties in the skin lesion segmentation tasks. VSGNet includes three parts: Color Constancy module, Saliency Detection module and Ultra Lightweight Multi-level Interconnection Network(ULMI-Net). Specially, ULMI-Net uses a U-shaped structure network as the skeleton, including the Adaptive Split Channel Attention (ASCA) module that simulates the parallel mechanism of biological vision dual pathway, and the Channel-Spatial Parallel Attention (CSPA) module inspired by the multi-level interconnection structure of visual cortices. Through these modules, ULMI-Net can balance the efficient extraction and multi-scale fusion of global and local features, and try to achieve the excellent segmentation results at the lowest cost of parameters and computational complexity. To validate the effectiveness and robustness of the proposed VSGNet on three publicly available skin lesion segmentation datasets (ISIC2017, ISIC2018 and PH2 datasets). The experimental results show that compared to other state-of-the-art methods, VSGNet improves the Dice and mIoU metrics by 1.84% and 3.34%, respectively, and with a 196× and 106× reduction in the number of parameters and computational complexity. This paper constructs the VSGNet integrating the biological vision m

关键词： Complex networks

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Long Video Micro-expression Spotting Based On OCC Theory

Long Video Micro-expression Spotting Based On OCC Theory

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, BingTong Zhang, ZheYuan Zhou, Ju Wang, HanPu Chen, Tong Southwest University Institute of Legal Psychology and Intelligent Computing Chongqing400715 China Chongqing Key Laboratory of Non-Linear Circuit and Intelligent Information Processing Chongqing400715 China Southwest University School of Electronic and Information Engineering Chongqing400715 China

ISBN: (纸本)9798350337488

The generation of micro-expression (ME) is unconscious and unaffected by human subjective consciousness. It can reveal hidden emotions in humans, which has important applications in the domains of psychological diagnosis, lie detection, and so on. ME detection, which aims to locate ME apex frames in long videos, is the foundation of ME recognition. In this paper, we propose a ME detection method based on One-Class Classification (OCC) theory for long videos. The method is the first to use neutral expression frames to detect MEs, which addresses the problem of insufficient training samples in ME detection. We design a geometric motion feature based on the prior knowledge from the FACS and utilize it in conjunction with the features extracted by CNN to train separate one-class classifiers for ME detection. Finally, we evaluate the proposed method on publicly available datasets CASME I, CASME II, SAMM, and a mixed database comprising data from the three datasets, to verify the feasibility of the proposed method in both single-database and cross-database ME detection. The experimental results show that our method outperforms three other ME detection methods, demonstrating its ability to more accurately locate ME apex frames in long videos. © 2023 IEEE.

关键词： Micro-expression Detection OCC One-Class Classifier

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Spring pair method of finding saddle points using the minimum energy path as a compass

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Physical Review E 2024年第6期110卷 064123-064123页

作者： Gang Cui Kai Jiang Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Xiangtan Hunan 411105 China

Finding index-1 saddle points is crucial for understanding phase transitions. In this work, we propose a simple yet efficient approach, the spring pair method (SPM), to accurately locate saddle points. Without requiring the Hessian information, the SPM evolves a single pair of spring-coupled particles on an energy surface. By designing complementary drifting and climbing dynamics based on gradient decomposition, the spring pair converges onto the minimum energy path (MEP) and spontaneously aligns its orientation with the MEP tangent, providing a reliable ascent direction for efficient convergence to saddle points. The SPM fundamentally differs from traditional surface walking methods that rely on the eigenvectors of the Hessian, which may deviate from the MEP tangent and potentially lead to convergence failure or undesired saddle points. The efficiency of the SPM for finding saddle points is verified by ample examples, including Lennard-Jones clusters, Morse clusters, water clusters, and the Landau energy functional involving quasicrystal phase transitions.

关键词： Lennard-Jones potential

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Improving the Transferability of Adversarial Examples by Using Generative Adversarial Networks and Data Enhancement

Improving the Transferability of Adversarial Examples by Usi...

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2021 International Conference on Robotics Automation and intelligent Control, ICRAIC 2021

作者： Xie, Pengfei Shi, Shuhao Xie, Wanjing Qin, Ruoxi Hai, Jinjin Wang, Linyuan Chen, Jian Hu, Guoen Yan, Bin Henan Key Laboratory of Imaging and Intelligent Processing PLA Strategy Support Force Information Engineering University Fujian Normal University

Deep neural networks (DNNs) can be attacked by adversarial examples that are undetectable by humans. Generation-based approaches have recently gained popularity because they directly translate the input distribution to the distribution of adversarial instances, making them more effective and efficient. However, existing techniques are susceptible to overfitting on the substitute model, limiting the transferability of adversarial examples. In this paper, we introduce data augmentation into AdvGAN, called AdvGAN-DE, which can dramatically improve the transferability of adversarial examples. Experiments demonstrate that we enhance the success rate by 31.09% for defense models and 10.23% for typically trained models on average when compared to AdvGAN. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Deep neural networks

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A Cross-Domain Ontology Semantic Representation Based on NCBI-BlueBERT Embedding

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Chinese Journal of Electronics 2022年第5期31卷 860-869页

作者： ZHAO Lingling WANG Junjie WANG Chunyu GUO Maozu Faculty of Computing Harbin Institute of Technology Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical University Beijing Key Laboratory of Intelligent Processing for Building Big Data School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture

A common but critical task in biological ontologies data analysis is to compare the difference between ontologies. There have been numerous ontologybased semantic-similarity measures proposed in specific ontology domain, but it still remains a challenge for crossdomain ontologies comparison. An ontology contains the scientific natural language description for the corresponding biological aspect. Therefore, we develop a new method based on natural language processing(NLP) representation model bidirectional encoder representations from transformers(BERT) for cross-domain semantic representation of biological ontologies. This article uses the BERT model to represent the word-level of the ontologies as a set of vectors, facilitating the semantic analysis or comparing the biomedical entities named in an ontology or associated with ontology terms. We evaluated the ability of our method in two experiments: calculating similarities of pair-wise disease ontology and human phenotype ontology terms and predicting the pair-wise of proteins interaction. The experimental results demonstrated the comparative performance. This gives promise to the development of NLP methods in biological data analysis.

关键词： human phenotype ontology cross-domain semantic representation natural language description pair-wise disease ontology data analysis bidirectional encoder representations NLP protein interaction diseases proteins natural language processing ontologies (artificial intelligence) natural language processing representation neural nets bioinformatics semantic-similarity measures cross-domain ontology semantic representation semantic analysis NCBI-BlueBERT embedding biological ontology data analysis

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Novel measuring techniques with applications in pattern classification and diagnostic process under Pythagorean fuzzy environment

Novel measuring techniques with applications in pattern clas...

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2023 International Conference on New Trends in Computational Intelligence, NTCI 2023

作者： Ejegwa, Paul Augustine Zhang, Yanxiong Li, Haiqing Feng, Yuming Institute of Intelligent Information Processing South China Business College Guangdong University of Foreign Studies Guangdong Guangzhou510545 China Joseph Sarwuan Tarka University Department of Mathematics Makurdi Nigeria Chongqing Three Gorges University Key Laboratory of Intelligent Information Processing and Control Chongqing Wanzhou404100 China

ISBN: (纸本)9798350380859

Distance and similarity measures are significant tools for information measure applicable in real-world under Pythagorean fuzzy domain. Some techniques for the computation of distance and similarity have been investigated between Pythagorean fuzzy sets (PFSs), notwithstanding with low performance indexes. To resolve these setbacks, this paper introduces some new measuring techniques with reliable performance in comparison to similar measures. The new techniques are confirmed with a number of theoretic results to illustrate their aptness as unfailing information measuring methods. Certain numerical experiments are carried out to ascertain the advantages of the proposed measures over the existing measures. We demonstrate the applications of the novel techniques in real-life decision-making situations pertaining to pattern recognition and disease diagnostic process where patterns and diseases are encapsulated in Pythagorean fuzzy pairs. © 2023 IEEE.

关键词： Fuzzy sets

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An experimental study of monotone acoustics in Huazang Temple Dialect of Tianzhu 6

An experimental study of monotone acoustics in Huazang Templ...

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6th International Conference on intelligent Computing, Communication, and Devices, ICCD 2023

作者： Ding, Haiying Guo, Lei Zhang, Zhiwen Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China Gansu Provincial Key Laboratory of Intelligent Processing of National Languages Northwest Minzu University Gansu Lanzhou730000 China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

Tianzhu Tibetan Autonomous County is located at the eastern end of the Hexi Corridor. Huazangsi Town is the seat of the current Tianzhu County. According to the atlas of Chinese dialects, Huazangsi dialect belongs to the Hexi section of Lanyin Mandarin. Its tone system has some distinctive tonal characteristics in the three aspects of single tone, continuous tone sandhi and soft tone. This paper analyzes the characteristics of single tone in Tianzhu Huazang Temple dialect through the research method of experimental phonetics, and summarizes the tonal types, values and areas of single tone in Tianzhu Huazang Temple dialect, providing a teaching basis for the acquisition of Mandarin in this region. At the same time, it explores the development and change of the tone of Tianzhu Huazang Temple dialect under the contact with multi-national languages, analyzes the influence of Mandarin tone on the tone of Tianzhu Huazang Temple dialect, and makes a simple prediction of the future development trend of the tone of Tianzhu Huazang Temple dialect. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Linguistics

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Thermal-Torsion Coupling Loading Analysis and Optimization of 3D PoP Assembly Solder Joints at Different Temperatures

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IEEE Transactions on Components, Packaging and Manufacturing Technology 2025年

作者： Gao, Chao Huang, Chunyue Liang, Yin Dian, Chen Lan, Jingyi Wang, Gui Guilin University of Electronic Technology School of Electrical and Mechanical Engineering Guilin541004 China Chengdu University Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu610106 China Chengdu Aeronautic Vocational and Technical College Chengdu610021 China

A simulation analysis was conducted to investigate the stress distribution of Package-on-Package (PoP) assembly array solder joints subjected to thermal-torsional coupling loads, with the validity of the simulation confirmed through coupled loading stress-strain measurement experiments. The volume-weighted average method was employed to calculate the average equivalent stress (Δσ) of the critical solder joint danger element layer within the PoP assembly array, using Δσ as the evaluation benchmark. The impact and sensitivity of structural parameters on the thermal-torsional coupling stress of solder joints were examined. A structural parameter sensitivity model was developed to facilitate the stability and optimization analysis of the structural parameter intervals. The results indicate that solder joints in the lower array of the PoP assembly experience higher thermal-torsional coupling stress, with the peak internal stress occurring at the interface between the solder joint and the copper pad. The variation in thermal-torsional coupling stress of the array solder joints is more pronounced in the low-temperature region compared to the high-temperature region, with maximum stress occurring at -55°C and minimum stress observed at 125°C. Within the structural parameter range, the Δσ value of the critical solder joint shows a negative correlation with solder joint height, solder joint diameter, and substrate thickness, and a positive correlation with PCB thickness. The sensitivity to structural parameters follows the order: solder joint diameter, solder joint height, PCB thickness, and substrate thickness. Finally, the optimal range of structural parameters was determined, and the stability of this range was assessed. © 2011-2012 IEEE.

关键词： Sensitivity analysis

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FUZZY ALIGNMENTS IN DIRECTED ACYCLIC GRAPH FOR NON-AUTOREGRESSIVE MACHINE TRANSLATION 11

FUZZY ALIGNMENTS IN DIRECTED ACYCLIC GRAPH FOR NON-AUTOREGRE...

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11th International Conference on Learning Representations, ICLR 2023

作者： Ma, Zhengrui Shao, Chenze Gui, Shangtong Zhang, Min Feng, Yang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Harbin Institute of Technology Shenzhen China

Non-autoregressive translation (NAT) reduces the decoding latency but suffers from performance degradation due to the multi-modality problem. Recently, the structure of directed acyclic graph has achieved great success in NAT, which tackles the multi-modality problem by introducing dependency between vertices. However, training it with negative log-likelihood loss implicitly requires a strict alignment between reference tokens and vertices, weakening its ability to handle multiple translation modalities. In this paper, we hold the view that all paths in the graph are fuzzily aligned with the reference sentence. We do not require the exact alignment but train the model to maximize a fuzzy alignment score between the graph and reference, which takes captured translations in all modalities into account. Extensive experiments on major WMT benchmarks show that our method substantially improves translation performance and increases prediction confidence, setting a new state of the art for NAT on the raw training data. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Benchmarking

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