检索结果-内蒙古大学图书馆

International Conference on Control, Automation, Robotics & Vision

作者： Bin Li Yangmin Li Xinhua Zhao Yuwei Yang Department of Electromechanical Engineering University of Macau Taipa Macao SAR China Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin University of Technology Tianjin 300384 China

ISBN: (纸本)9781479952007

A spatial 2-RPU&SPR parallel manipulator (PM) with three degrees of freedom (DOF) is proposed in this paper. The architecture of the manipulator is comprised of a moving platform attached to a base through two revolute-prismatic-universal jointed serial linkages and one spherical-prismatic-revolute jointed serial linkage. The prismatic motions of the prismatic joints are considered to be actively actuated. The moving platform of the manipulator has one-translational and two rotational (1T2R) DOFs with respect to the fixed base. The kinematics including forward and inverse position analysis is analyzed. At last, the simulations of position and velocity of the manipulator are made to validate the algorithm.

关键词： design Analysis Parallel Manipulator

来源：评论

学校读者我要写书评

暂无评论

Modified damage assessment and repair design for underpass bridge based on fire effect

引用

key Engineering Materials 2014年 574卷 67-76页

作者： Li, Zhonglong Wu, Honglin Zhu, Xiaodi Gu, Hongjiang Liu, ZhenYu Yin, Tao School of Transportation Science and Engineering Harbin Institute of Technology Harbin 150090 China Key Laboratory of Advanced Material and Intelligent Control Technology on Transportation Safety Ministry of Communication 150090 China Postdoctoral Station of Mechanics Harbin Institute of Technology Harbin 150090 China Communications Research Institute of Liaoning Province Shenyang 110015 China School of Civil Engineering Southwest Jiao Tong University Chengdu 614202 China China Railway Fifth Survey and Design Institute Group Co. Ltd. Northeast Branch China

ISBN: (纸本)9783037858172

Due to the fire effect, a frame underpass bridge had suffered a huge damage in Changjiang road in Harbin in the direction to Acheng. One span of the bridge was burned in large area, parts of which were burned badly. Many adjacent beams turned black at bottom of roofs;parts decoration of side wall were damaged to some extent. As a result, both directions of the traffic were disrupted, causing traffic jams. To make sure of repairing and restoring the traffic during the shortest period, Harbin municipal committee established the Changjiang road rescue headquarters. Under the precondition of utmost to save money and ensure that the repaired underpasses technology standards meet the design requirements, the research group were about to use steel plate or carbon fiber sheet as the reinforcing material, after detecting and identifying the bridge damage. Through a comprehensive consideration for the ascension of normal section bearing capacity of two reinforcing materials, pasting carbon fiber sheet was adopted to complete repair reinforcement scheme. © (2014) Trans Tech Publications.

关键词： Roads and streets

来源：评论

学校读者我要写书评

暂无评论

NEW WORD DETECTION AND EMOTIONAL TENDENCY JUDGMENT BASED ON MIXED MODEL

NEW WORD DETECTION AND EMOTIONAL TENDENCY JUDGMENT BASED ON ...

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiao Sun Chongyuan Sun Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

The paper studies a new method for Chinese new word detection and emotional tendency judgment based on mixed model and proposes a new word generation *** we construct conditional random fields(CRFs) to recognize the new words,lead-in features based on character combined with the crowd sourcing network *** then express word as a word vector based on neural network language model(NNLM) to judge the new word emotional *** experimental results show that the method can improve the precision and recall of the new word detection with a good system performance,and it also provides a new way for forecasting the public mood.

关键词： New Word Detection Conditional Random Fields Emotional Tendency Judgment Neural Network Language Model

来源：评论

学校读者我要写书评

暂无评论

Expression image preprocessing based on wavelet transform

Expression image preprocessing based on wavelet transform

引用

IEEE International Conference on Robotics and Biomimetics

作者： Changqin Quan Xiaoming Xu Fuji Ren The Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China P.R Hefei University of Technology Hefei Anhui CN The University of Tokushima Tokushima Japan

ISBN: (纸本)9781479973989

In this paper, we present a new image preprocessing method which is based on Wavelet Transform. Before we extract expression texture information, Wavelet transform will be applied to remove partial high frequency information. And then Gabor Transform will be used to extract expression information. At last we chose the Support Vector Machine to classify facial expressions. Experiments on the Japanese Female Facial Expression (JAFFE) Database illustrate that the Wavelet Transform and Gabor features are effective for facial expression discrimination. Additionally, the experiment results validate the feasibility of this method.

关键词： Decision support systems Conferences Robots Biomimetics XML Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFICATION WITH FUZZY SVM

MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFI...

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiao Sun Chengcheng Li Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

Micro-blog is easily posted and communicated because of its short text ***,its brevity limits the feature *** paper presents a blogger modeling method for Chinese micro-blog sentiment *** paper would adopt a multidimensional strategy to accomplish the feature extraction *** with traditional feature extraction methods and combined with the interactive property of blog,the blog comment will be considered as the performance characteristic of micro-blog emotion *** comes to comments content and the relationship between commentators and micro-bloggers while it extracts the micro blogging text *** last,the paper adopts fuzzy SVM model to reduce the sensation of noise points and outliers on classification *** results demonstrate the effectiveness of the multidimensional feature extraction method on sentiment classification and the classify effect of fuzzy SVM is better than SVM.

关键词： sentiment classification multidimensional fuzzy SVM

来源：评论

学校读者我要写书评

暂无评论

Dynamic facial expression recognition based on K-order emotional intensity model

Dynamic facial expression recognition based on K-order emoti...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Changqin Quan Yao Qian Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China P.R. The Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

ISBN: (纸本)9781479973989

With the development of artificial intelligence and pattern recognition, facial expression recognition plays a more and more important role in intelligent human-computer interaction. In this paper, we present a model named K-order emotional intensity model (K-EIM) which is based on K-Means clustering. Different from other related works, the proposed approach can quantify emotional intensity in an unsupervised way. And then the output from K-EIM is encoded. The coding results are used for the dynamic facial expression recognition. The experiment is conducted on Cohn-Kanade facial expression database and the support vector machine classifier is used for facial expression classification. This method achieved a dynamic facial expression recognition accuracy of 88.32% which suggest that the proposed method shows better performance and proves its validity. Moreover, effect of different segments of emotional intensity is also discussed in the paper.

关键词： Face recognition Encoding Accuracy Emotion recognition Principal component analysis Training Feature extraction

来源：评论

学校读者我要写书评

暂无评论

MINING THE IMPACT OF SOCIAL NEWS ON THE EMOTIONS OF USERS BASED ON DEEP MODEL

MINING THE IMPACT OF SOCIAL NEWS ON THE EMOTIONS OF USERS BA...

引用

2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiao Sun Fei Gao Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

In this paper,Deep Belief Nets(DBN) model and Support Vector Machine(SVM) are used to mine the features hidden in social news,which can influence the emotions of *** feature selection methods for text modeling are used to build the input vectors of DBN,with the purpose of keeping the text information to the greatest *** take advantage of the deep features abstracted by DBN to build social news text *** the same time,three optimal models are used as inputs of SVM to train and classify the social *** get a conclusion that DBN not only reduces the dimension of original features,but also makes the abstracted features with more text information and shows better performance in determining the influence on people' s emotions by social news.

关键词： Deep Belief Network(DBN) Restricted Boltzmann Machine(RBM) Impacts on Emotion Social News

来源：评论

学校读者我要写书评

暂无评论

A Connected Component-Based Distributed method for overlapping community detection

A Connected Component-Based Distributed method for overlappi...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Tian Chen Kai Liu Xin Yi Dandan Shen Wei Wang Fuji Ren Jun Liu Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei AnHui Agricultural University Hefei School of Computer and Information Hefei University of Technology Hefei The University of Tokushima Japan

ISBN: (纸本)9781479926978

In order to find the overlapping community structure more quickly and accurately in complex network, this paper proposes a Connected Component-Based Distributed method (CCBD) for overlapping community detection. CCBD first divides edges set in the network into smaller one. Next, it seeks out connected component using distributed platforms and gives a serials number to them according to certain rules. Then, it classifies these connected components according to the serials number. Task nodes determine whether any two connected components and non-propagating edges can be connected to become a larger community. Finally, CCBD negotiates a new serials name for the new community. Through repeated iterations, we get the community structure in the network. Nodes belong to multiple communities are overlapping nodes. Experiment results show that CCBD has higher time efficiency benefiting from distributed computing. Moreover, the quality of communities detected by CCBD surpasses those found by other algorithms.

关键词： Communities Algorithm design and analysis Educational institutions Complex networks Clustering algorithms Distributed computing Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Chinese Microblog Sentiment Classification Based on Deep Belief Nets with Extended Multi-Modality Features

Chinese Microblog Sentiment Classification Based on Deep Bel...

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Xiao Sun Chengcheng Li Wanyi Xu Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China School of Information Science and Engineering Southeast University Shanghai China Faculty of Engineering University of Tokushima Tokushima Japan

ISBN: (纸本)9781479942732

This paper presents a DBN (deep belief nets) model and a multi-modality feature extraction method to extend features' dimensionalities of short text for Chinese micro blogging sentiment classification. Besides traditional features sets for document classification, comments for certain posts are also extracted as part of the micro blogging features according to the relationship between commenters and posters though constructing micro blogging social network as input information. Then, the integration of the above modality features is combined and represented as input vector for DBN. In this paper, a DBN model, which is stacked with several layers of RBM (Restricted Boltzmann Machine), is implemented to initialize the structure of neural network. The RBM layers can take probability distribution samples of original data to learn hidden structures for better feature representation. A Class RBM (Classification RBM) layer, which is stacked on top of several RBM layers, is adapted to achieve the final sentiment classification. The results demonstrate that, with proper structure and parameter, the performance of the proposed deep learning method on sentiment classification is better than state of the art surface learning models such as SVM or NB, which proves that DBN is suitable for short-length document classification with the proposed feature dimensionality extension method.

关键词： Feature extraction Semantics Visualization Training Social network services Blogs Educational institutions

来源：评论

学校读者我要写书评

暂无评论

Finding Emotional Focus for Emotion Recognition at Sentence Level

引用

电子学报(英文版) 2013年第1期22卷 99-103页

作者： QUAN Changqin REN Fuji Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei 230009 China Faculty of Engineering The University of Tokushima Tokushima Japan

Emotion recognition at sentence level is one of the fundamental problems of textual emotion un- derstanding. Based on the observation that sentence emo- tional focus can be expressed by some clauses in this sen- tence, this paper proposes to find the emotional focus for sentence emotion recognition. For the sake of breaking through the problems brought about by depending on emo- tion lexicons, we first recognize word emotions in a sen- tence based on Maximum entropy model. And then homo- geneous Markov model is built for clause emotion recogni- tion; After that, a strategy based on emotion selection is proposed for a sentence with multiple clauses, and genetic algorithm is used for clause selection by textual feature weighting. The experimental results show that, comparing with the baseline, there are 9.1% and 3.6% improvement respectively for two different evaluations. It is demon- strated that finding emotional focus by clause selection is able to improve the performance of sentence emotion recognition significantly.

关键词：情感识别句子层面聚焦马尔可夫模型最大熵模型特征加权遗传算法

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：