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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Zheng, Yi Jing, Heming Xie, Qiujie Zhang, Yuejie Feng, Rui Zhang, Tao Gao, Shang Fudan University School of Computer Science Shanghai Key Lab of Intelligent Information Processing China Shanghai University of Finance and Economics School of Information Management and Engineering China Deakin University School of Information Technology Australia

ISBN: (纸本)9781728163277

Recent neural models for video captioning usually employed an encoder-decoder framework. However, most approaches either neglected the spatial and temporal interactions between objects in a video or implicitly modelled the interactions, resulting in less desired performance. In this paper, we propose a novel relation-aware graph learning framework. It explicitly models both spatial and temporal relations for objects. In particular, a relation-aware graph is designed to depict the spatial relations between different objects in a scene. Parallelly, a temporal graph network is designed to perform relational reasoning for the same objects in adjacent frames. Features of both types of relations are learned and fused for the follow-up language decoder. Experiments on two bench-mark datasets show the effectiveness of our framework. It achieves state-of-the-art performance with CIDEr scores on MSVD and MSR-VTT. © 2023 IEEE.

关键词： Relation-Aware Graph Scene Graph Temporal Graph Video captioning

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IMEWAS--A Integrated Multi-platform EAPoW-Based WLAN AAA Solution

IMEWAS--A Integrated Multi-platform EAPoW-Based WLAN AAA Sol...

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International Conference on Wireless and Mobile Communications (ICWMC)

作者： Ling Chen Jian-de Lu Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou Jiangsu China

ISBN: (纸本)9781424431397;9780769527963

As security is becoming a significant obstacle to wider deployment of wireless LANs, IEEE 802.1x and EAPoW has been put forward to enhance authentication in WLAN. At present, some existing client solution such as Xsupplicant or WIRE1x has only applies to one platform, Linux or Windows, and is ill-considered of EAPoW. This paper discusses an integrated multi- platform EAPOW-based WLAN AAA Solution - IMEWAS, its architecture and module design and implementation. The integrated flexible and secure solution has been proved feasible.

关键词： Wireless LAN Authentication Access protocols Network servers Linux Wireless application protocol Access control Encapsulation File servers Authorization

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A Real-time Cutting Model Based on Finite Element and Order Reduction

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computer Systems Science & Engineering 2022年第10期43卷 1-15页

作者： Xiaorui Zhang Wenzheng Zhang Wei Sun Hailun Wu Aiguo Song Sunil Kumar Jha Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in ***,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time *** proposed model uses the finite element model to construct a deformation model of the virtual ***,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation *** addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual ***,the Bezier curve is adopted to draw the incision outline after the virtual lung has been ***,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual *** results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

关键词： Virtual surgery cutting model finite element model model order reduction Bezier curve

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Data distribution algorithm of high-speed intrusion detection system based on network processor

Data distribution algorithm of high-speed intrusion detectio...

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2nd International Conference on Semantics, Knowledge, and Grid, SKG 2006

作者： Xu, Cheng Yu, Fei Dai, Zhenghui Yue, Guangxue Li, Renfa School of Computer and Communication Hunan University Changsha 410082 China Provincial Key Laboratory of Computer Information Processing Technology Jiangsu Province Suzhou Jiangsu 2150063 China State Key Laboratory of Information Security Graduate School Chinese Academy of Sciences Beijing 100049 China College of Informationg Engineering JiaXing University JiaXing 314000 China

ISBN: (纸本)076952673X

Because the processing speed of intrusion detection system can hardly keep pace with the high-speed development of network, improving the speed of intrusion detection has been the problem starved for solve. By adopting the network processor, a distribution algorithm based on protocol analysis has been realized. By delivering the captured data package to each detect node according to protocol types and then accomplishing the detection for data package through the collaboration of the detect nodes, the processing efficiency of the intrusion detection system has been improved as a whole. © 2006 IEEE.

关键词： Intrusion detection

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Dynamic thresholding networks for schizophrenia diagnosis

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Artificial Intelligence in Medicine 2019年 96卷 25-32页

作者： Zou, Hongliang Yang, Jian PCA Lab Key Lab of Intelligent Perception and systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China

Background and objective: Functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI) is an effective approach to describe the neural interaction between distributed brain regions. Recent progress in neuroimaging study reported that the connection between regions is time-varying, which may enhance understanding of normal cognition and alterations that result from brain disorders. However, conventional sliding window based dynamic FC (DFC) analysis has several drawbacks, including arbitrary choice of window length, inaccurate descriptor of FC, and the fact that many spurious connections were included in the fully-connected networks due to noise. This study aims to develop an effective dynamic thresholding brain networks method to diagnose schizophrenia. Methods: In this study, we proposed a time-varying window length DFC method based on dynamic time warping to construct brain functional networks. To further eliminate the influence of spurious connections caused by noise, orthogonal minimum spanning tree was applied in these networks to generate time-varying window length dynamic thresholding FC (TVWDTFC) networks. To validate the effectiveness of our proposed method, experiments were conducted on a dataset, which including 56 individuals with schizophrenia and 74 healthy controls. Results: We achieved a classification accuracy of 0.8077 (p < 0.001, permutation test) using support vector machine. Experimental results demonstrated that the proposed method outperforms several state-of-the-art approaches, which verified the effectiveness of our proposed TVWDTFC method in schizophrenia diagnosis. Additionally, we also found that the selected discriminative features were mostly distributed in frontal, parietal, and limbic area. Conclusions: The results suggest that our approach may be a promising tool for computer-aided diagnosis of schizophrenia. © 2019 Elsevier B.V.

关键词： Dynamic time warping Orthogonal minimum spanning tree rs-fMRI Schizophrenia Time-varying window length DFC

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Image Hiding Algorithm in Discrete Cosine Transform Domain Based on Grey Prediction and Grey Relational Analysis

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China Communications 2013年第7期10卷 57-70页

作者：黄海平黄世超陈九天王汝传 College of Computer Nanjing University of Posts and Telecommunications Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Laboratory of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University

Traditional information hiding algorithms cannot maintain a good balance of capacity,invisibility and *** this paper,a novel blind colour image information hiding algorithm based on grey prediction and grey relational analysis in the Discrete Cosine Transform(DCT) domain is ***,this algorithm compresses the secret image losslessly based on the improved grey prediction GM(1,1)(IGM) *** then chooses the blocks of rich texture in the cover image as the embedding regions using Double-dimension Grey Relational Analysis(DGRA).Finally,it adaptively embeds the compressed secret bits stream into the DCT domain mid-frequency coefficients,which are decided by those blocks' Double-Dimension Grey Correlation Degree(DGCD) and Human Visual System(HVS).This method can ensure an adequate balance between invisibility,capacity and *** results show that the proposed algorithm is robust against JPEG compression(46.724 6 dB when the compression quality factor is 90%),Gaussian noise(45.531 3 dB when the parameter is(0,0.000 5)) etc.,and it is a blind information hiding algorithm that can be extracted without an original carrier.

关键词： image information hiding IGM DGRA blind information hiding DCT

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NerfCap: Human Performance Capture with Dynamic Neural Radiance Fields

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IEEE Transactions on Visualization and computer Graphics 2023年第12期29卷 5097-5110页

作者： Wang, Kangkan Peng, Sida Zhou, Xiaowei Yang, Jian Zhang, Guofeng Nanjing University of Science and Technology Key Lab of Intelligent Percept. and Syst. for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Jiangsu Nanjing210094 China Zhejiang University State Key Lab of CAD&CG Zijingang Campus Zhejiang Hangzhou310058 China

This paper addresses the challenge of human performance capture from sparse multi-view or monocular videos. Given a template mesh of the performer, previous methods capture the human motion by non-rigidly registering the template mesh to images with 2D silhouettes or dense photometric alignment. However, the detailed surface deformation cannot be recovered from the silhouettes, while the photometric alignment suffers from instability caused by appearance variation in the videos. To solve these problems, we propose NerfCap, a novel performance capture method based on the dynamic neural radiance field (NeRF) representation of the performer. Specifically, a canonical NeRF is initialized from the template geometry and registered to the video frames by optimizing the deformation field and the appearance model of the canonical NeRF. To capture both large body motion and detailed surface deformation, NerfCap combines linear blend skinning with embedded graph deformation. In contrast to the mesh-based methods that suffer from fixed topology and texture, NerfCap is able to flexibly capture complex geometry and appearance variation across the videos, and synthesize more photo-realistic images. In addition, NerfCap can be pre-trained end to end in a self-supervised manner by matching the synthesized videos with the input videos. Experimental results on various datasets show that NerfCap outperforms prior works in terms of both surface reconstruction accuracy and novel-view synthesis quality. © 1995-2012 IEEE.

关键词： Image reconstruction

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SDWS: Semantic Search for Deep Web Data

SDWS: Semantic Search for Deep Web Data

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International Symposiums on information processing (ISIP)

作者： Wei Fang Zhiming Cui Pengyu Hu Li Huang Pengpeng Zhao Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou Jiangsu China Institute of Intelligence Information Processing and Application China

ISBN: (纸本)9781424430536;9780769531519

A lot of high quality and wealthy data are hidden in backend database and search engines can not index this page, which is called Deep Web. It is mostly accessible through query interfaces. SDWS, a semantic search engine for Deep Web is presented. We are studying and implementing semantic Web technology to the each process of Deep Web information integrated, and expertise in Deep Web discovering, annotating query results and integrating information. The novel approach promise better access to Deep Web.

关键词： Ontologies Search engines Semantic Web information processing Portals Deductive databases Application software laboratories Indexes Context-aware services

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A domain-specific question answering system based on ontology and question templates

A domain-specific question answering system based on ontolog...

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11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD2010

作者： Wang, D.S. Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Graduate University of the Chinese Academy of Sciences Beijing China Department of Computer Science Jiangsu University of Science and Technology Zhenjiang China

ISBN: (纸本)9780769540887

The rapid growth in the development of Internet-based information systems increases the demand for natural language interfaces that are easy to set up and maintain. Unfortunately, the problem of deep understanding natural language queries is far from being solved. In this paper, an automated question answering system based on domain ontology and question template is proposed, which does not need deep understanding of user's questions. Ontology was employed to model the interesting domain, and properties of concepts are described by a collection of question templates. The system captures a user's intention by matching his questions to predefined templates, and return answers corresponding to template's query focus. The system has been applied to mobile service consulting area, and experimental results show that the system has high practicability as well as maintainability. © 2010 IEEE.

关键词： Ontology

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RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine

RoKEPG: RoBERTa and Knowledge Enhancement for Prescription G...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Pu, Hua Mi, Jiacong Lu, Shan He, Jieyue Southeast University School of Computer Science and Engineering Key Lab of Computer Network and Information Integration Moe Jiangsu Nanjing210018 China Nanjing Fenghuo Tiandi Communication Technology Co. Ltd Jiangsu Nanjing China

ISBN: (纸本)9798350337488

Traditional Chinese medicine (TCM) prescription is the most critical form of TCM treatment, and uncovering the complex nonlinear relationship between symptoms and TCM is of great significance for clinical practice and assisting physicians in diagnosis and treatment. Although there have been some studies on TCM prescription generation, these studies consider a single factor and directly model the symptom-prescription generation problem mainly based on symptom descriptions, lacking guidance from TCM knowledge. To this end, we propose a RoBERTa and Knowledge Enhancement model for Prescription Generation of Traditional Chinese Medicine (RoKEPG). RoKEPG is firstly pre-trained by our constructed TCM corpus, followed by fine-tuning the pre-trained model, and the model is guided to generate TCM prescriptions by introducing four classes of knowledge of TCM through the attention mask matrix. Experimental results on the publicly available TCM prescription dataset show that RoKEPG improves the F1 metric by about 2% over the baseline model with the best results. © 2023 IEEE.

关键词： Deep learning Pre-trained language models Traditional Chinese medicine prescription generation

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