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2012 International Conference on Systems and Informatics, ICSAI 2012

作者： Yao, Yu Zhang, Nan Gao, Fu-Xiang Yu, Ge Key Laboratory of Medical Image Computing Northeastern University Ministry of Education Shenyang 110819 China School of Information Science and Engineering Northeastern University Shenyang 110819 China

ISBN: (纸本)9781467301992

In this paper, a delayed worm propagation model with birth and death rates is discussed. The number of system reinstallations may be increased when the hosts get unstable (infected or quarantined). In view of such situation, dynamic birth and death rates are introduced. Afterwards, the stability of the positive equilibrium is studied. Through the theoretical analysis, it is proved that the model is locally asymptotically stable without time delay. Moreover, a bifurcation appears when time delay t passes a constant value which means that the worm propagation system is unstable and uncontrollable. Thus, the time delay should be decreased in order to predict or eliminate the worm propagation. Finally, a numeric simulation is presented which fully supports our analysis. © 2012 IEEE.

关键词： Time delay

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Incorporating dynamic attention gating mechanism and pre-trained embedding for Chinese clinical named entity recognition

Incorporating dynamic attention gating mechanism and pre-tra...

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2023 International Conference on Biomimetic Intelligence and Robotics

作者： Qiu, Zhenming Pan, Anyu Qi, Lin College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Engineering Research Center of Medical Imaging and Intelligent Analysis Ministry of Education Shenyang110169 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang110169 China

Clinical Named Entity Recognition (CNER) serves as a cornerstone in clinical research and healthcare informatics, with its primary goal being the discernment and categorization of clinical terminologies present within Electronic medical Records (EMRs). While deep learning has significantly improved CNER’s performance, these models still face challenges in identifying rare or unseen entities. Our study unveils an innovative DAGM-BiLSTM-CRF model that seamlessly integrates data-driven deep learning strategies with human knowledge to surmount this limitation. The distinctive features of this model lie in its integration of a pre-trained character embedding layer, adept at encapsulating nuanced semantic variations at the granularity of individual characters. Furthermore, it incorporates a bidirectional Long Short-Term Memory (BiLSTM) layer, proficient in deriving contextually relevant information by traversing the sequence from both endpoints. The most noteworthy aspect of our model is the inclusion of a Dynamic Attention Gating Mechanism (DAGM) that dynamically recalibrates attention weights based on the traits of the input sequence and a Conditional Random Fields (CRF) layer that considers interdependencies among output labels within a sequence. The evaluation was carried out on the CCKS-2017 CNER benchmark dataset to underscore the superiority of our model over existing cutting-edge methods, thereby validating its proficiency in deciphering the intricacies of Chinese electronic medical records. © 2023 The Authors. Published by Elsevier B.V.

关键词： Embeddings

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Detecting positive opinion leader group from forum

Detecting positive opinion leader group from forum

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13th International Conference on Web-Age Information Management, WAIM 2012

作者： Song, Kaisong Wang, Daling Feng, Shi Wang, Dong Yu, Ge School of Information Science and Engineering Northeastern University Shenyang 110819 China Key Laboratory of Medical Image Computing Northeastern University Ministry of Education Shenyang 110819 China

ISBN: (纸本)9783642322808

Forum has long been the main way of communication, and more and more users publish their opinions by it. The most influential users or opinion leaders will contribute to the formation of information, especially the positive influential users who can guide public opinions and make positive influence. Positive Opinion Leader Group (POLG) represents a group of users, each of who expresses the similar content and same sentiment orientation with their followers to a great extent, who are regarded as the most influential men during the information dissemination process. However, most existing researches pay less attention to the implicit relationship, heterogeneous structure and positive influence. In this paper, we focus on modeling multi-themes user network of forum with explicit and implicit links for this purpose. In detail, we put forward a data structure Longest Sequence Phrase Tree (LSP-Tree) for representing comments on forum, measuring the similarity between comments based on LSP-Tree to obtain implicit links, and further detecting positive opinion leader group. Experiments using dataset from Tianya forum show that our method can detect positive opinion leaders group effectively and efficiently. © 2012 Springer-Verlag.

关键词： Sentiment analysis

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Finite Element Analysis for the Effects of the Descending Aorta Tortuosity on Aortic Hemodynamics

Finite Element Analysis for the Effects of the Descending Ao...

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2022 International Symposium on Biomimetic Intelligence and Robotics, ISBIR 2022

作者： Li, Jiapeng Cao, Xuehao Xu, Lisheng Qi, Lin College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Engineering Research Center of Medical Imaging and Intelligent Analysis Ministry of Education Shenyang110169 China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang110169 China

Large arteries in the human body, such as the aorta, are susceptible to atherosclerosis, and aortic hemodynamic analysis has been widely used to predict cardiovascular disease. In this study, we aim to explore whether the tortuosity of the descending aorta (DA) is associated with the development of atherosclerosis and to investigate how vessel curvature affects blood flow characteristics. To investigate the relationship between tortuosity of DA and atherosclerosis, six models and different degrees of tortuosity were considered and combined for a total of 36 computational models. The models were numerically calculated by finite element analysis based on Fluid-Structure Interaction (FSI), and hemodynamic parameters including blood flow velocity, Wall Shear Stress (WSS), Oscillatory Shear Index (OSI), and Relative Residence Time (RRT), were calculated that are used to identify the locations of thrombosis and atherosclerosis. Our results showed that flow disturbances such as flow recirculation and secondary flow were more severe in the high-tortuosity vessels compared with the less-tortuosity vessels. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Proceedings of International Symposium on Biomimetic Intelligence and Robotics.

关键词： Fluid structure interaction

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Modelling and analysis the worm propagation with variable infection rate

Modelling and analysis the worm propagation with variable in...

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2014 International Conference on Communication Technology and Application, CTA 2014

作者： Yao, Y. Wang, Y. Zhang, Y.Y. Gao, F.X. Key Laboratory of Medical Image Computing of Ministry of Education Northeastern University Shenyang 110004 China College of Information Science and Engineering Northeastern University Shenyang 110819 China

ISBN: (纸本)9781845649302

Previous models regarded infection rate as a constant which failed to catch the dynamical process of the infection rates. In this paper, we proposed a SIQRS model with the variable infection rate for the first time. Then we built the corresponding equation of worm propagation and analyzed the existence and stability of worm-free equilibrium. Moreover, in order to verify the effectiveness of the new model, we showed the numerical analysis. The results of numerical analysis show the SIQRS model with the variable infection rate is consistent with the process of the worm propagation more realistically. Finally, we gave some useful strategies which may be applied to constrain the spread of Internet worms. © 2014 WIT Press.

关键词： Numerical analysis

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An approach of text-based and image-based multi-modal search for online shopping

An approach of text-based and image-based multi-modal search...

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13th International Conference on Web-Age Information Management, WAIM 2012

作者： Li, Renfei Wang, Daling Zhang, Yifei Feng, Shi Yu, Ge School of Information Science and Engineering Northeastern University Shenyang 110819 China Key Laboratory of Medical Image Computing Northeastern University Ministry of Education Shenyang 110819 China

ISBN: (纸本)9783642322808

Nowadays, more and more people prefer online shopping to physical store shopping for its convenience, cheapness and timesaving. Customers visit some commercial shopping websites, and select their favorite commodities by accessing links or retrieving by search box. However, in our real life, most online shopping websites provide a simple and single text retrieval method only, to some extent it's difficult for customers to submit query and retrieve satisfactory results. In this paper, a multi-modal search approach combining text-based and image-based search techniques is presented. Besides text search, a two-stage image search approach is proposed, which utilizes basic features consisting of color and textural features to filter mismatching images in first stage, and further uses SIFT features for accurate search in second stage. Moreover, a prototype system has been developed for multi-modal search on online shopping websites. By submitting some words, phrases, images or their combination, customers can search out what they want. The experiments compared with traditional algorithms based on single visual feature validate that our approach and multi-modal search prototype system are effective, and the retrieval results can satisfy customers' requirements well for online shopping. © 2012 Springer-Verlag.

关键词： Sales

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Multi-information fusion for uncertain semantic representations of videos 10

Multi-information fusion for uncertain semantic representati...

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Proceedings of the 19th ACM international conference on Information and knowledge management

作者： Lu, Bo Wang, Guoren Gong, Xiaofeng Key Laboratory of Medical Image Computing Ministry of Education School of Information Science and Engineering Northeastern University China School of Information Science and Engineering Fudan University China

ISBN: (纸本)9781450300995

Concept-Based Semantic Video Retrieval (CBSVR) usually uses semantic representations of videos to handle user's retrieval requests. It is obvious that the accuracy of semantic video retrieval depends on results of concept detectors, but the detection results are usually imprecise and uncertain. In this paper, we propose a multi-information fusion approach (MIF) which is dedicated to solving the problem of uncertain semantic representations of videos for improving retrieval accuracy. This approach is based on a novel two-phase framework that involves the inferring phase and the fusing phase. In the inferring phase, the most relevant concepts to the user's query are chosen by exploring both contextual correlation among concepts and temporal correlation among shots. In the fusing phase, the inferred probabilities of the related concepts are fused together with the detection results via minimization of potential function to refine the detector prediction. Experiments on the widely used TRECVID datasets demonstrate that our approach can effectively improve the accuracy of semantic concept detection. © 2010 ACM.

关键词： Semantics

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Segmentation of pulmonary vessels based on MSFM method 22

Segmentation of pulmonary vessels based on MSFM method

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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Wang, Xiaowei Cheng, Liying Huang, Danyang Gao, Xuanshuang Liang, Daili He, Liuye Zhang, Zhimei Li, Nan Tan, Wenjun School of Physical Science and Technology Shenyang Normal University Shenyang110034 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110189 China

ISBN: (纸本)9781728162676

Accurate segmentation of pulmonary blood vessels from CT images is of great significance for lung disease detection and segmentation of other lung structures. Manual segmentation is difficult to accurately segment vascular tissue for various reasons. Therefore, in view of the existing problems and shortcomings of the existing lung vessel segmentation method, a more efficient lung vessel segmentation algorithm is proposed, that is, the multi-template fast marching method (MSFM algorithm). Firstly, it used the hole filling and maximum inter-class variance algorithm for preprocess. In the process, the lung parenchyma is extracted from the chest CT, and then the lung blood vessels are extracted in the lung parenchymal area using the MSFM algorithm. In the extraction process, the threshold and gradient are used to limit the progress of the process and the lung blood vessels are more accurately segmented. Through experimental verification, the accuracy of lung blood vessel segmentation based on MSFM algorithm is improved. © 2021 IEEE.

关键词： Blood vessels

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An adaptive clustering algorithm of gaussian curve fitting the histogram based on K-means

An adaptive clustering algorithm of gaussian curve fitting t...

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2019 IEEE International Conferences on Ubiquitous computing and Communications and Data Science and Computational Intelligence and Smart computing, Networking and Services, IUCC/DSCI/SmartCNS 2019

作者： Ma, Guangkun Yang, Jinzhu Song, Xiaoxu Zhao, Hong School of Computer Science and Engineering Northeastern University Shenyang China School of Software Shenyang University of Technology Shenyang China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781728152097

The K-mean algorithm is simple and efficient in vascular segmentation. But in a K-means clustering algorithm, the number of clustering centers must be determined in advance and the random allocation of clustering centers seriously affects the efficiency of the algorithm. In order to solve this problem, an adaptive clustering algorithm based on K-means with the Gaussian curve fitting histogram is proposed, which is used to segment circular-like blood vessels. Firstly, the histogram outline is fitted into the Gaussian curve by the least square method and the maximum value of the curve is obtained. The number of maximal values is counted as the number of clustering centers and the maximum points are used as the central points of clustering. Also, the K-means algorithm is improved by combining the intensity and position information of pixels. The proposed method has been tested by 6 groups of medical images. The algorithm has the advantages of less iterations, fast convergence speed and getting more than 95% Dice Similarity Measure value. The algorithm can effectively solve the determination of multi-seed points and vascular segmentation in medical image segmentation. © 2019 IEEE.

关键词： K-means clustering

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Attribute granulation based on attribute discernibility and AP algorithm

Journal of Software

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Journal of Software 2013年第4期8卷 834-841页

作者： Zhu, Hong Ding, Shifei Zhao, Han Bao, Lina School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China School of Medical Information Xuzhou Medical College Xuzhou 221000 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

For high dimensional data, the redundant attributes of samplers will not only increase the complexity of the calculation, but also affect the accuracy of final result. The existing attribute reduction methods are encountering bottleneck problem of timeliness and spatiality. In order to looking for a relatively coarse attributes granularity of problem solving, this paper proposes an efficient attribute granulation method to remove redundancy attribute. The method calculates the similarity of attributes according attribute discernibility first, and then clusters attributes into several group through affinity propagation clustering algorithm. At last, representative attributes are produced through some algorithms to form a coarser attribute granularity. Experimental results show that the attribute granulation method based on affinity propagation clustering algorithm(AGAP) method is a more efficient algorithm than traditional attribute reduction algorithm(AR). © 2013 ACADEMY PUBLISHER.

关键词： Granulation

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