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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Song, ZiAn Deng, ZhengJie Hainan Normal University Haikou571158 China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin541004 China

ISBN: (纸本)9783030786205

Convolutional neural networks have been applied in image recognition widely, and acquired well-known results. However, the discovery of adversarial examples in recent years has attracted many researcher’s attention on the safety and reliability of convolutional neural networks. Adversarial examples are small perturbations added only to the clean image data, which could cause the trained model makes wrong identifications, while people could still recognize. In this paper, we propose a new convolutional neural network to defense the adversarial examples. It breaks into two branches after inputting an image. One branch likes a normal image recognition model, while another branch distills the low-frequency information of the image firstly, and then uses the low-frequency image to train. The two branches combine to make the output of the model. The presented model uses the image’s low-frequency information, through which people often recognizes an object. The experiments show that the presented model suppresses the success rate of the attack in the face of the adversarial examples, and improves the model’s recognition success rate, comparing to some other methods. © 2021, Springer Nature Switzerland AG.

关键词： image recognition

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Polystyrene nanoplastics aggravate house dust mite induced allergic airway inflammation through EGFR/ERK-dependent lung epithelial barrier dysfunction

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Ecotoxicology and Environmental Safety 2025年 298卷 118329页

作者： Wang, Qing He, Wen Zhou, Yufeng Feng, Rui Wang, Yingwen Liu, Lijuan Yuan, Yuan Dai, Jiajia Liu, Yun Zhang, Xiaobo Department of Respiratory Medicine Children's Hospital of Fudan University National Children's Medical Center Shanghai 201102 China Institute of Pediatrics Children's Hospital of Fudan University National Children's Medical Center and the Shanghai Key Laboratory of Medical Epigenetics International Co-laboratory of Medical Epigenetics and Metabolism Ministry of Science and Technology Institutes of Biomedical Sciences Fudan University Shanghai 200032 China National Health Commission (NHC) Key Laboratory of Neonatal Diseases Fudan University Shanghai 201102 China Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai 200433 China Department of Nursing Children's Hospital of Fudan University Shanghai 201102 China MOE Key Laboratory of Metabolism and Molecular Medicine Department of Biochemistry and Molecular Biology School of Basic Medical Sciences and Shanghai Xuhui Central Hospital Fudan University Shanghai 200032 China Center for Pediatric Clinical Quality Control of Shanghai Shanghai 201102 China

Concerns that airborne micro- and nanoplastics (MNPs) may impair human respiratory health are rising. However, the specific effects of MNPs on allergic asthma remain insufficiently explored. This study developed an allergic asthma model using house dust mite (HDM), and mice were exposed to 50 μg polystyrene nanoparticles (PS-NPs) at three-days interval. Additionally, the effects and potential mechanisms of PS-NPs exposure (25, 50 and 100 μg/mL) on lung epithelial barrier dysfunction were explored using mouse lung epithelial type II (MLE-12) and A549 cells. The pathological changes of airway tissue and the increase of inflammatory response confirmed that exposure to PS-NPs significantly aggravated allergic asthma in mice. Importantly, in the presence of HDM sensitization, the accumulation of PS-NPs in the alveolar region was increased, leading to lung epithelial barrier dysfunction and more Th2-mediated eosinophilic inflammation, characterized by elevated IL-4, IL-13, immunoglobulin E (Ig E) and eosinophils. The activation of the epidermal growth factor receptor (EGFR) pathway and its downstream extracellular regulating kinase (ERK) was investigated using transcriptomic sequencing to elucidate the effects of PS-NPs exposure on lung epithelial barrier dysfunction. Furthermore, an EGFR-specific inhibitor AG1478 was employed to confirm the role of the EGFR/ERK pathway in lung epithelial barrier dysfunction and asthma exacerbation in vitro and in vivo experiments. In conclusion, the molecular mechanism by which PS-NPs aggravates asthma in mice was elucidated, which helps to improve the understanding of the health effects of PS-NPs and lays a theoretical foundation for addressing the health risks posed by PS-NPs. © 2025 The Authors

关键词： Asthma EGFR/ERK Epithelial cell Polystyrene nanoplastics Tight junction

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Abstractive Text Summarization Model Based on BERT Vectorization and Bidirectional Decoding

Abstractive Text Summarization Model Based on BERT Vectoriza...

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2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Teng, Keliang Qiang, Baohua Wang, Yufeng Yang, Xianyi Wang, Yuemeng Wang, Chen Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China Hebei Key Laboratory of Intelligent Information Perception and Processing The 54th Research Institute of CETC Shijiazhuang050081 China

ISBN: (纸本)9781510666597

Facing the pressure of the extremely inflated network information and data overload surplus, it is extremely important to locate "valuable information" efficiently and accurately. Text summarization technology in the field of Natural Language processing (NLP) is an effective means to analyze and process network information. In this paper, we propose an abstractive text summarization model based on bidirectional encoder representations from transformers (BERT) vectorization and bidirectional decoding. The BERT is adopted to obtain a more global vector representation, which helps the subsequent encoder and decoder to fuse the full-text information to generate a summary with high generality. The decoding phase adopts a bidirectional decoding structure and combines the attention mechanism to maintain the bilateral decoding result to generate summaries. The bidirectional decoding structure can be fine-tuned according to the bidirectional results, which can overcome the tilt problem of the unidirectional structure, and the generated summaries are more consistent. The experimental results on the NLPCC2017 text summarization dataset show that the summaries generated by our model have the higher coherence at the word and sentence level, and the stronger generalization of the full text. © 2023 SPIE.

关键词： Decoding

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An Online Ascent Phase Trajectory Reconstruction Algorithm Using Gauss Pseudospectral Method

An Online Ascent Phase Trajectory Reconstruction Algorithm U...

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Da Zhang Xuefang Lu YongJi Wang Lei Liu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of C Key Laboratory of Ministry of Education for Image Processing and Intelligent ControlDepartment of Co

ISBN: (纸本)9781467315241

In this paper, we present an online ascent phase trajectory reconstruction algorithm using Gauss Pseudospectral *** Pseudospectral Method (GPM) was used to transform the ascent phase trajectory optimization problem into Nonlinear Program Problem (NLP), we solve the problem using a optimization software named GPOPS in *** this method we can calculate the optimal trajectory control volume and feedback to update the guidance commands *** analysis of the optimized results has been done to prove its *** last, we compare the trajectory recon- struction algorithm to a law without reconstruction algorithm via simulation with aerodynamic and thrust *** simulation results indicate that the method proposed above offers improved performance and has ability for real-time calculating.

关键词： Ascent Phase Trajectory Online Trajectory Reconstruction Gauss Pseudospectral Method Nonlinear Pro- gramming

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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND imageS

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

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Tsinghua Science and Technology 2024年第4期29卷 1069-1081页

作者： Shanwen Guan Xinhua Lu Ji Li Rushi Lan Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic TechnologyGuilin 541004China Guilin Huigu Institute of AI Industrial Technology Guilin 541004China School of Information Engineering Nanyang Institute of TechnologyNanyang 473000China

When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

关键词： wideband direction of arrival(DOA)estimation sparse Bayesian learning(SBL) unitary approximate message passing(UAMP)algorithm Dirichlet process(DP)

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Instance Reweighting Adversarial Training Based on Confused Label

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intelligent Automation & Soft Computing 2023年第8期37卷 1243-1256页

作者： Zhicong Qiu Xianmin Wang Huawei Ma Songcao Hou Jing Li Zuoyong Li Institute of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou511442China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou350121China

Reweighting adversarial examples during training plays an essential role in improving the robustness of neural networks,which lies in the fact that examples closer to the decision boundaries are much more vulnerable to being attacked and should be given larger *** probability margin(PM)method is a promising approach to continuously and path-independently mea-suring such closeness between the example and decision ***,the performance of PM is limited due to the fact that PM fails to effectively distinguish the examples having only one misclassified category and the ones with multiple misclassified categories,where the latter is closer to multi-classification decision boundaries and is supported to be more critical in our *** tackle this problem,this paper proposed an improved PM criterion,called confused-label-based PM(CL-PM),to measure the closeness mentioned above and reweight adversarial examples during ***-cally,a confused label(CL)is defined as the label whose prediction probability is greater than that of the ground truth label given a specific adversarial *** of considering the discrepancy between the probability of the true label and the probability of the most misclassified label as the PM method does,we evaluate the closeness by accumulating the probability differences of all the CLs and ground truth ***-PM shares a negative correlation with data vulnerability:data with larger/smaller CL-PM is safer/riskier and should have a smaller/larger *** demonstrated that CL-PM is more reliable in indicating the closeness regarding multiple misclassified categories,and reweighting adversarial training based on CL-PM outperformed state-of-the-art counterparts.

关键词： Reweighting adversarial training adversarial example boundary closeness confused label

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intelligent multi-user detection using an artificial immune system

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Science in China(Series F) 2009年第12期52卷 2342-2353页

作者： GONG MaoGuo, JIAO LiCheng, MA WenPing & MA JingJing key laboratory of intelligent Perception and image Understanding of Ministry of Education of China Institute of intelligent Information processing, Xidian University, Xi’an 710071, China 1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University Xi’an 710071 China 2. Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.

关键词： artificial immune systems clonal selection multi-user detection code-division multiple-access genetic algorithm

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P systems with shuffle operation

P systems with shuffle operation

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Niu, Yunyun Xu, Jinbang Subramaniant, K.G. Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology 430074 Wuhan China School of Mathematical Sciences Universiti Sains Malaysia 11800 Penang Malaysia

ISBN: (纸本)9781424464388

Shuffle operation on trajectories is useful in modeling parallel composition of words and languages. In this work, a new class of P systems with shuffle operation is presented. Such a system has language-objects and shuffle-operation rules in its regions. It can be used as a language generator;specifically it is used to generate languages from sets of languages. Some comparison results are obtained, which show that the power of shuffle operation is enlarged in the framework of P systems. © 2010 IEEE.

关键词： Modeling languages

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Global asymptotic stability of fuzzy cellular neural networks with unbounded time-varying delays

Global asymptotic stability of fuzzy cellular neural network...

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2011 International Conference on Information Science and Technology, ICIST 2011

作者： Zhu, Chongjun Bao, Gang College of Mathematics and Statistics Hubei Normal University Huangshi 435002 China Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Hubei 430074 China

The global asymptotic stability of fuzzy cellular neural networks with unbounded time-varying delays and Lipschitz continuous activation functions is investigated in this brief. Based on the concept of comparison, som... 详细信息

ISBN: (纸本)9781424494408

关键词： Time varying networks

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