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Tumor gene expressive data classification based on locally linear representation Fisher criterion

Tumor gene expressive data classification based on locally l...

引用

9th International Conference on Intelligent Computing, ICIC 2013

作者： Li, Bo Tian, Bei-Bei Liu, Jin School of Computer Science and Technology Wuhan University of Science and Technology 430081 Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China State Key Lab. of Software Engineering Wuhan China

ISBN: (纸本)9783642394812

In this paper, a discriminant manifold learning method based on Locally Linear Embedding (LLE), which is named Locally Linear Representation Fisher Criterion (LLRFC), is proposed for the classification of tumor gene expressive data. In the proposed LLRFC, an inter-class graph and intra-class graph is constructed based on the class information of tumor gene expressive data, where the weights between nodes in both graph are optimized using locally linear representation trick. Moreover, a Fisher criterion is modeled to maximize the inter-class scatter and minimize the intra-class scatter simultaneously. Experiments on some benchmark tumor gene expressive data validate its efficiency. © 2013 Springer-Verlag.

关键词： Genes

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Sub-sentence division for tree-based machine translation

Sub-sentence division for tree-based machine translation

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Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language processing of the AFNLP, ACL-IJCNLP 2009

作者： Xiong, Hao Xu, Wenwen Mi, Haitao Liu, Yang Liu, Qun Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China Key Lab. of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

ISBN: (纸本)9781617382581

Tree-based statistical machine translation models have made significant progress in recent years, especially when replacing 1-best trees with packed forests. However, as the parsing accuracy usually goes down dramatically with the increase of sentence length, translating long sentences often takes long time and only produces degenerate translations. We propose a new method named subsentence division that reduces the decoding time and improves the translation quality for tree-based translation. Our approach divides long sentences into several sub-sentences by exploiting tree structures. Large-scale experiments on the NIST 2008 Chinese-to-English test set show that our approach achieves an absolute improvement of 1.1 BLEU points over the baseline system in 50% less time. © 2009 ACL and AFNLP.

关键词： Machine translation

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GEMI: A high performance and high flexibility memory interface architecture for complex embedded SOC

GEMI: A high performance and high flexibility memory interfa...

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International Conference on computer Science and Software Engineering, CSSE 2008

作者： Hualong, Zhao Hongshi, Sang Tianxu, Zhang Yebin, Fan State Key Lab. for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769533360

Two of the most significant factors in the success of today's system-on-chip (SoC) designs are the ability to deliver efficient access to off-chip high speed memory and the ability to be compatible with several different interface-timings of several different sorts of memories. And the scheduling scheme of data streams for multi-master and multi-outstanding requests situation in complex SoC should be considered carefully, too. This paper introduces a novel general external memory interface (GEMI) architecture for the high performance and high flexibility memory interface. Several techniques and methods, i.e. data and command buffers based on asynchronous FIFO, optimized bank management, multi-port access scheduler, request reorder unit, are proposed in this paper for fulfilling the requirements mentioned above. Some techniques are specially proposed for data streams scheduling in complex SoC. At the end of the paper, the simulation and tape-out results are provided. The whole implementation of architecture is proven to be not only functional and efficient, but also flexible and reusable by simulation and silicon verification. © 2008 IEEE.

关键词： Scheduling

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Predicting helix boundaries of α-helix transmembrane protein with feedback conditional random fields 11th

Predicting helix boundaries of α-helix transmembrane protei...

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11th International Conference on Intelligent Computing, ICIC 2015

作者： Wang, Kun Wu, Hongjie Lu, Weizhong Fu, Baochuan Lü, Qiang Huang, Xu School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China School of Computer Science and Technology Soochow University Suzhou215006 China Jiangsu Provincial Key Lab for Information Processing Technologies Suzhou215006 China School of Information Engineering Huzhou University Huzhou313000 China

ISBN: (纸本)9783319221793

Transmembrane proteins play an important role in cellular energy production, signal transmission, metabolism. Existing machine learning methods are difficult to model the global correlation of the membrane protein sequence, and they also can not improve the quality of the model from sophisticated sequence features. To address these problems, in this paper we proposed a novel method by a feedback conditional random fields (FCRF) to predict helix boundaries of α-helix transmembrane protein. A feedback mechanism was introduced into multi-level conditional random fields. The results of lower level model were used to calculate new feedback features to enhance the ability of basic conditional random fields. One wide-used dataset DB1 was used to validate the performance of the method. The method achieved 95% on helix location accuracy. Compared with the other predictors, FCRF ranks first on the accuracy of helix location. © Springer International Publishing Switzerland 2015.

关键词： Learning systems

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Steam turbine fault diagnosis based on single-valued neutrosophic multigranulation rough sets over two universes

Steam turbine fault diagnosis based on single-valued neutros...

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作者： Zhang, Chao Zhai, Yanhui Li, Deyu Mu, Yimin School of Computer and Information Technology Shanxi University Taiyuan China Key Lab. of Computational Intelligence and Chinese Information Processing of Ministry of Education Taiyuan China College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

Steam turbine fault diagnosis is a significant issue in fault diagnosis technology, which has made remarkable progress in the area of electromechanical engineering. Although many studies based on fuzzy approaches are developed on this topic, they can only cope with incomplete and uncertain information, but have limitations in processing indeterminate and inconsistent information in practical decision-making procedures. In addition, it is beneficial to solve problems under group decision-making background that aims to aggregate each expert's preference to reach a final conclusion by consensus and unanimity. To deal with these difficulties in steam turbine fault diagnosis, by combining multigranulation rough sets over two universes with single-valued neutrosophic sets theories, a single-valued neutrosophic multigranulation rough set over two universes is investigated in this paper. Then, we construct a general decision-making rule through using single-valued neutrosophic multigranulation rough sets over two universes within the background of steam turbine fault diagnosis. Finally, the validity of the decision-making method is verified by an illustrative case. © 2016 - IOS Press and the authors. All rights reserved.

关键词： Steam turbines

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A novel feature extraction approach based on neighborhood rough set and PCA for migraine rs-fMRI

A novel feature extraction approach based on neighborhood ro...

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作者： Li, Zhanhui Fan, Jiancong Ren, Yande Tang, Leiyu College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Affiliated Hospital of Qingdao University Qingdao China Provincial Key Lab. for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Qingdao China

As a common disease, migraine has a high incidence but the pathogenesis is still not clear. Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) is an important research topic in the field of brain medicine, which can classify rs-fMRI data to automatically diagnose brain diseases. However, the original features of the rs-fMRI data are difficult to be extracted and the high-dimensional characteristics, which make the data analysis an extremely complicated task. Those have also plagued many researchers and bring great challenges to the existing pattern classification methods. Aiming at the high dimensionality of rs-fMRI data, in this paper, we propose a feature extraction approach based on the combination of neighborhood rough set and PCA, thereby improving the accuracy of migraine identification. Firstly, Resting-State fMRI Data Analysis Toolkit plus was applied for preprocessing, calculating three characteristic indices: Amplitude of Low Frequency Fluctuation (ALFF), Regional Homogeneity (ReHo) and Functional Connectivity (FC. The inter-group difference analysis was performed by two-sample T test and GRF correction. Then, correlation coefficient matrix original features extraction was performed by means of automatic anatomical lab.l template (AAL). Finally, the original features were trained by the traditional classification algorithm in machine learning. The experimental results show that the propose approach can obtain good performance in predicting migraine. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Principal component analysis

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Radio LFM Fuze Interference Identification Based on Convolutional Neural Network and Attention Mechanism 23

Radio LFM Fuze Interference Identification Based on Convolut...

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23rd IEEE International Conference on Communication technology, ICCT 2023

作者： Xian, Zhaoxia Bai, Zhiquan Yang, Jikai Zhao, Jinqiu Wang, Caifeng Hao, Xinhong Shandong Provincial Key Lab. of Wireless Communication Technologies School of Information Science and Engineering Shandong University Shandong Qingdao China School of Computer and Information Engineering Qilu Institute of Technology Shandong Jinan China School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350325959

In modern battlefields, the fuze is exposed to a complex electromagnetic environment, and suffers severe interference. To identify the typical interferences and improve the reliability of fuze, this paper designs a radio linear frequency modulation (LFM) fuze interference identification network based on convolutional neural network (CNN) and attention mechanism (AM). Firstly, the received signal at the fuze is transformed from the time domain to the time-frequency domain by the short-time Fourier transform (STFT) to obtain the time-frequency images as the network input. Considering the powerful feature extraction capability of CNN, we take it to obtain the semantic features of the time-frequency images and perform the interference recognition, where AM is further employed to focus on more important channel information and improve the recognition accuracy. Simulations show that the recognition accuracy of the network can be over 98% at a jamming-to-signal ratio (JSR) of -16.0dB with better robustness and low complexity. © 2023 IEEE.

关键词： attention mechanism convolutional neural network fuze interference signal identification time-frequency analysis

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Pick-up tree based route recommendation from taxi trajectories

Pick-up tree based route recommendation from taxi trajectori...

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

作者： Hu, Haoran Wu, Zhiang Mao, Bo Zhuang, Yi Cao, Jie Pan, Jingui State Key Lab. for Novel Software Technology Nanjing University Nanjing China Jiangsu Provincial Key Laboratory of E-Business Nanjing University of Finance and Economics Nanjing China College of Computer and Information Engineering Zhejiang Gongshang University Hangzhou China

ISBN: (纸本)9783642322808

Recommending suitable routes to taxi drivers for picking up passengers is helpful to raise their incomes and reduce the gasoline consumption. In this paper, a pick-up tree based route recommender system is proposed to minimize the traveling distance without carrying passengers for a given taxis set. Firstly, we apply clustering approach to the GPS trajectory data of a large number of taxis that indicates state variance from "free" to "occupied", and take the centroids as potential pick-up points. Secondly, we propose a heuristic based on skyline computation to construct a pick-up tree in which current position is its root node that connects all centroids. Then, we present a probability model to estimate gasoline consumption of every route. By adopting the estimated gasoline consumption as the weight of every route, the weighted Round-Robin recommendation method for the set of taxis is proposed. Our experimental results on real-world taxi trajectories data set have shown that the proposed recommendation method effectively reduce the driving distance before carrying passengers, especially when the number of cabs becomes large. Meanwhile, the time-cost of our method is also lower than the existing methods. © 2012 Springer-Verlag.

关键词： Taxicabs

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A process distance metric based on alignment of process structure trees

A process distance metric based on alignment of process stru...

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SenDe, IDP, IEKB, MBC, International Workshops, APWeb 2012

作者： Fu, Xiaodong Yue, Kun Zou, Ping Wang, Feng Ji, Kaifan Yunnan Provincial Key Lab. of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming 650500 China School of Information Science and Engineering Yunnan University Kunming 650091 China Faculty of Management and Economics Kunming University of Science and Technology Kunming 650093 China

ISBN: (纸本)9783642294259

For various applications in today's service-oriented enterprise computing systems, such as process-oriented service discovering or clustering, it is necessary to measure the distance between two process models. In this paper, we propose a quantitative measure to calculate the distance or similarity between different block-structured processes. We first transform each process into a process structure tree, and then calculate the process distance based on the alignment of two process structure trees. The proposed distance metric satisfies four distance measure properties, i.e., non-negativity, identity of indiscernible, symmetry and triangle inequality. These properties make the distance metric can be used as a quantitative tool in effective process model management activities. We illustrate the methodology with examples, by which its features are shown. Moreover, experiment study shows that the proposed method is feasible. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Trees (mathematics)

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Exploring Various Features in Semantic Role lab.ling

Exploring Various Features in Semantic Role Labeling

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International Conference on Advanced Language processing and Web information technology (ALPIT)

作者： Hongling Wang Guodong Zhou Qiaoming Zhu Peide Qian Jiangsu Provincial Key Lab for Computer Information Processing TechnologySchool of Computer Science and Technology Soochow University Suzhou China 215006

This paper explores the contributions of various features in semantic role lab.ling. Moreover, an optimal set of features is selected using a greedy strategy. Finally, an effective headword-driven pruning algorithm is proposed to filter out irrelavant instances. Evaluation on the CoNLL'2005 SRL benchmark corpus shows that our method achieved comparable performance with the best-reported ones on a single automatic parse tree.

关键词： Training Classification algorithms Accuracy Pediatrics Support vector machines lab.ling System performance

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