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2014 International Conference on Information and Network Security, ICINS 2014

作者： Fu, Liangjia Xia, Chunhe Liu, Xiaochen Gao, Jinghua Software College Beihang University Beijing China Beijing Key Laboratory of Network Technology School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781849199094

In a distributed network, there are multiple routing paths between source node and destination node. In order to meet certain demands of network security, selecting required firewalls in multiple routing paths and deploying appropriate rules on them are indispensable steps. Thus, in this paper, we carry on a further research on it and propose permit and deny algorithms which serve to improve the performance of network security. Then, we give theoretical proof of our algorithms. Finally, we test the effectiveness of algorithms based on a network simulation platform named mininet. The analysis of time efficiency of our algorithms and previous algorithms, as well as the comparison between them prove the high efficiency of our algorithms.

关键词： Network security

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CETA: A Consensus Enhanced Training Approach for Denoising in Distantly Supervised Relation Extraction 29

CETA: A Consensus Enhanced Training Approach for Denoising i...

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29th International Conference on Computational Linguistics, COLING 2022

作者： Liu, Ruri Mo, Shasha Niu, Jianwei Fan, Shengda School of Cyber Science and Technology Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

Distantly supervised relation extraction aims to extract relational facts from texts but suffers from noisy instances. Existing methods usually select reliable sentences that rely on potential noisy labels, resulting in wrongly selecting many noisy training instances or underutilizing a large amount of valuable training data. This paper proposes a sentence-level DSRE method beyond typical instance selection approaches by preventing samples from falling into the wrong classification space on the feature space. Specifically, a theorem for denoising and the corresponding implementation, named Consensus Enhanced Training Approach (CETA), are proposed in this paper. By training the model with CETA, samples of different classes are separated, and samples of the same class are closely clustered in the feature space. Thus the model can easily establish the robust classification boundary to prevent noisy labels from biasing wrongly labeled samples into the wrong classification space. This process is achieved by enhancing the classification consensus between two discrepant classifiers and does not depend on any potential noisy labels, thus avoiding the above two limitations. Extensive experiments on widely-used benchmarks have demonstrated that CETA significantly outperforms the previous methods and achieves new state-of-the-art results. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Classification (of information)

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A Digitally assisted nonlinearity suppression architecture using over-the-air beam cancelation

A Digitally assisted nonlinearity suppression architecture u...

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作者： Mu, Qin Li, Nanxi Chen, Cong Wei, Xiaozheng Wen, Rong Wu, Muqing Li, Xiang Liu, Ying School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China National Key Lab of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu China School of Network and Communication Engineering Chengdu Technological University Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

Using a large number of power amplifiers brings serious nonlinear distortion to 5G communication systems, which becomes a challenging problem for conventional digital predistortion (DPD) to linearize signals. To address this challenge, we propose a digitally assisted nonlinearity suppression architecture for applications in multiple antenna arrays. In this architecture, we use an auxiliary array to generate a nonlinear cancelation signal to cancel with the main beam at the receiving end. We explore a two-step method to model the nonlinear signal and combine neural network to complete the modeling. In addition, we introduce a novel method for estimating and tracking the channel to update the model coefficients. To verify the proposed methods, we design a scene and compare the performance of our architecture with that of conventional DPD. Our experiments demonstrate that our proposed methods can significantly enhance the adjacent channel power leakage ratio performance by 12 dB while also optimizing in-band distortion. Moreover, our architecture outperforms conventional DPD approaches even with enhanced distortion. © 2023 John Wiley & Sons Ltd.

关键词： Power amplifiers

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Multiscale Bilateral Attention Fusion Network for Pansharpening

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5828-5843页

作者： Guo, Zhongyuan Li, Jiawei Lei, Jia Liu, Jinyuan Zhou, Shihua Wang, Bin Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand University of Ulster Intelligent Systems Research Center LondonderryBT48 7JL United Kingdom Bulgarian Academy of Sciences IICT Sofia1000 Bulgaria

High-resolution multispectral (HRMS) images combine spatial and spectral information originating from panchromatic (PAN) and reduced-resolution multispectral (LRMS) images. Pansharpening performs well and is widely used to obtain HRMS images. However, most pansharpening approaches determine the ratio of PAN and LRMS images through direct interpolation, which may introduce artifacts and distort the color of the fused results. To address this issue, an unsupervised progressive pansharpening framework, MSBANet, is proposed, which adopts a multistage fusion strategy. Each stage contains an attention interactive extraction module (AIEM) and a multiscale bilateral fusion module (MBFM). The AIEM extracts spatial and spectral features from input images and captures the correlations between features. The MBFM can efficiently integrate information from the AIEM and improve MSBANet context awareness. We design a hybrid loss function that enhances the ability of the fusion network to store spectral and texture details. In qualitative and quantitative experimental studies on four datasets, MSBANet outperformed state-of-the-art pansharpening techniques. The code will be released. © 2024 IEEE.

关键词： Data mining

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RIS-UAV Assisted Marine communication Based on Deep Neural Network Training 4

RIS-UAV Assisted Marine Communication Based on Deep Neural N...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Zhang, Tianrui Han, Shuangshuang Yang, Ziyuan Li, Qi University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Key Laboratory of Ocean Observation Technology Mnr Tianjin China Key Laboratory of Ocean Observation Technology Mnr The National Ocean Technology Center Tianjin China

ISBN: (纸本)9798350349252

With the reconfigurable intelligent surface (RIS) and unmanned aerial vehicle (UAV) becoming increasingly prevalent in everyday human activities, RIS-UAV assisted wireless communication system helps to extend transmission distance and improve communication quality. However, most of the scenarios about RIS-UAV applications are on land. At the same time, how to jointly optimize the communication link between the UAV equipped with RIS and the communication link between the base station (BS) and the vessel is challenging. In order to solve the above problems, this paper proposes a RIS-UAV assisted marine communication system, and training the beamforming matrix, transmitter and receiver weights implemented by deep neural networks (DNN) to maximize the performance of the system. The simulation results show that the marine wireless communication system based on RIS-UAV achieves lower bit error rate (BER) than the conventional UAV relay communication system. Furthermore, based on parallel intelligence theory, more reasonable intelligent decision-making and prediction are expected be obtained for marine communications in the future. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Conv-based Temporal Sets Prediction for Next-basket Recommendation

Conv-based Temporal Sets Prediction for Next-basket Recommen...

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2023 International Conference on Frontiers of Robotics and Software engineering, FRSE 2023

作者： Zhang, Fan Wang, Shuai Qin, Yongjie Qu, Hong University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China School of Computer Science and Engineering State Grid Information Communication Company of Hunan Electric Power Corporation P.R. China

ISBN: (纸本)9798350301113

Next-basket recommendation (NBR) aims to recommend a set of items to a consumer according to past shopping carts. NBR essientially a more general and complex form than sequential recommendation which recommends the next item according to the historical records. However, the majority of recent literature fails to simultaneously consider the two aspects: 1) complex order-invariant relation of multiple elements within a set;2) intangible order-variant user appetite in users' historical interactions. To overcome the barrier, we propose a novel Conv-based Temporal Sets Prediction model (dubbed ConvTSP). We contrive a Conv-based Relationship Learning module to capturing the cross-relation between items in each basket. Besides, we integrate sequential-level dynamic user appetite and individual-level static user appetite into a fused user appetite representation. Extensive experiments and ablation studies are done to show how effective ConvTSP is. © 2023 IEEE.

关键词： component Next-basket Recommendation

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Improving the performance of hypervisor-based fault tolerance

Improving the performance of hypervisor-based fault toleranc...

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24th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2010

作者： Zhu, Jun Dong, Wei Jiang, Zhefu Shi, Xiaogang Xiao, Zhen Li, Xiaoming School of Electronics Engineering and Computer Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China

ISBN: (纸本)9781424464432

Hypervisor-based fault tolerance (HBFT), a checkpoint-recovery mechanism, is an emerging approach to sustaining mission-critical applications. Based on virtualization technology, HBFT provides an economic and transparent solution. However, the advantages currently come at the cost of substantial overhead during failure-free, especially for memory intensive applications. This paper presents an in-depth examination of HBFT and options to improve its performance. Based on the behavior of memory accesses among checkpointing epochs, we introduce two optimizations, read fault reduction and write fault prediction, for the memory tracking mechanism. These two optimizations improve the mechanism by 31.1% and 21.4% respectively for some application. Then, we present software-superpage which efficiently maps large memory regions between virtual machines (VM). By the above optimizations, HBFT is improved by a factor of 1.4 to 2.2 and it achieves a performance which is about 60% of that of the native VM. © 2010 IEEE.

关键词： Fault tolerance

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Modulated advancements in semiconductor-based nanomaterials for environmental solutions

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Nanotechnology for Environmental engineering 2024年第4期9卷 525-537页

作者： Tirmare, Aarti Hemant Gowda V, Dankan Dhabarde, Rupali J Tirmare, Hemant Appa Kale, Satish Bapuso Suryawanshi, Varsha Amol Kumar N, Anil Department of Electronics and Telecommunications Engineering Bharati Vidyapeeth’s college of Engineering Maharashtra Kolhapur416013 India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka560064 India Department of Computer Science and Technology Department of Technology Shivaji University Kolhapur Maharashtra Kolhapur416008 India Department of Computer Science and Technology Department of Technology Shivaji University Kolhapur Maharashtra Kolhapur416004 India Department of Mechanical Engineering Department of Technology Shivaji University Kolhapur Maharashtra Kolhapur416004 India Maharashtra Kolhapur India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Andhra Pradesh Tirupati India

This research explores significant advancements in semiconductor-based nanomaterials and their crucial applications in addressing environmental challenges. Highlighted for their expansive surface area, chemical stability, and adaptable electrical and optical properties, these nanomaterials present innovative solutions for pressing environmental issues. The paper details novel synthesis methods enhancing these materials’ effectiveness in environmental applications, including pollution remediation, sustainable energy production, and the development of environmental monitoring tools. Key findings include the discovery of advanced techniques for fabricating nanoscale semiconductor components, improving the efficiency of photocatalytic degradation of pollutants, energy conversion, and sensor sensitivity. Additionally, this study investigates the integration of semiconductor nanomaterials with biocompatible polymers and metals, aiming to enhance their operational stability and longevity in environmental applications. The outcomes contribute to the advancement of nanotechnology in environmental conservation, offering insights into the development of eco-friendly materials and innovative strategies for environmental protection. This work underscores the potential of semiconductor-based nanomaterials to revolutionize the field of environmental solutions, presenting a promising avenue for future research and application in sustainable technologies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Nanostructured materials

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An improved outlier detection method in high-dimension based on weighted hypergraph

An improved outlier detection method in high-dimension based...

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2nd International Symposium on Electronic Commerce and Security, ISECS 2009

作者： Li, YinZhao Wu, Di Ren, JiaDong Hu, ChangZhen Lab. of Computer Network Defense Technology Beijing Institute of Technology Beijing 100081 China Department of Information and Electronic Engineering Hebei University of Engineering Handan 056038 China College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9780769536439

Outlier detection in high-dimensional space is a hot topic in data mining, the main goal is to find out a small quantity of data objects with abnormal behavior in data set. In this paper, the concepts of the feature vector and the attribute similarity are defined, an improved algorithm SWHOT based on weighed hypergraph model for outlier detection in high dimensional space is presented. The objects in high dimensional space are translated into binary data type, by looking for the hyperedge of binary set, the data set hypergarph model is established, meanwhile, the weight of the hyperedge is equal to the value of the attribute similarity. In addition, the objects of the hypergraph are clustered by CURE algorithm, arbitrary shaped clusters can be identified. Furthermore, the outliers are found according to the point-to-window weighted support, the point-to-class belongingness and the point-to-window weighted deviation of size, the meaningful outliers in high-dimension can be mined by means of appropriate user-defined threshold. Experimental results show that SWHOT can improve scaling and precision. © 2009 IEEE.

关键词： Data mining

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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