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检索条件"机构=Affective Computing and Advanced Intelligent Machines Key Laboratory"

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A test data compression scheme based on position information coding 5

A test data compression scheme based on position information...

引用

5th International Conference on computing Communication and Networking Technologies, ICCCNT 2014

作者： Chen, Tian Yang, Bingdong Wang, Wei Hao, Birong Ren, Fuji Liu, Jun Wang, Yixin School of Computer and Information Hefei University of Technology Hefei230009 China AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei230009 China University of Tokushima 770-8506 Japan

ISBN: (纸本)9781479926961

Under the condition of Built-off Self-test (BOST), a novel test data compression scheme based on position information coding is presented, which is targeting test data and test power consumption. The proposed scheme gets the next test stimuli by reversing some bits of the responses corresponding to the previous test vectors. During the process of bit flip, test power problem should be taken into account;both the shift power and capture power during the test should be limited in the scope of security. For shift power, need to modify the scan chain by adding blocking logic;and the capture power reduction through the test cube filling based on the response. Experimental results justify the efficacy of the proposed method in attaining test-data compression;the average compression ratio is 73.63% on the premise of capture power consumption reduced by 20%. © 2014 IEEE.

关键词： Electric power utilization

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A low power BIST scheme based on block encoding 5

A low power BIST scheme based on block encoding

引用

5th International Conference on computing Communication and Networking Technologies, ICCCNT 2014

作者： Chen, Tian Zheng, Liuyang Wang, Wei Ren, Fuji Zhang, Xishan Chang, Hao School of Computer and Information Hefei University of Technology Hefei230009 China AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei230009 China University of Tokushima 770-8506 Japan

ISBN: (纸本)9781479926961

With the development of integrated circuit manufacturing technology, low power test has become a focus of concern during testing fields. This paper proposes a new low power BIST (built-in self test) scheme based on block encoding which first exploit a block re-encoding method to optimize the test cube, and then a low power test based on LFSR (linear feedback shift register) reseeding is applied. According to the compatibility of flag, the scheme proposes a grouping algorithm based on flag to divide and reorder the test cubes in the test cube set. Experimental results show that the scheme not only obtain better test compression ratio and test data storage, but also reduce the test power consumption effectively. © 2014 IEEE.

关键词： Shift registers

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Hybrid model based sentiment classification of Chinese micro-blog

Hybrid model based sentiment classification of Chinese micro...

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International Conference on Audio, Language and Image Processing, ICALIP

作者： Xiao Sun Chengcheng Li Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China

ISBN: (纸本)9781479939046

Through analysis and study of emotional characteristics in Chinese micro-blog, such as Sina Weibo, this paper proposed a multidimensional sentiment classification method based on micro-blog emoticon by dividing micro-blog into 7 types of emotions categories: happiness, fondness, sorrow, anger, fear, detestation and surprise. We used predefined micro-blog emoticon sets to initial screen large-scale unmarked data, and automatically labeled them, then used this emotional corpus as training set to train the emotion classifier, which divided micro-blog data into multiple emotion categories. The experimental results show that accuracy rate of using unigram model for each class can reach 63.7%. And the adoption of different feature selection methods for Support Vector machines and Naive Bias classifier experiment, by which the obtained accuracy rate and recall rate has reached higher than 71%.

关键词： Accuracy Blogs Support vector machines Twitter Niobium Educational institutions Training

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Chinese microblogging emotion classification based on support vector machine

Chinese microblogging emotion classification based on suppor...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Xiao Sun Chengcheng Li Jiaqi Ye Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China

ISBN: (纸本)9781479926978

Through the analysis and study of the emotional characteristics in Chinese micro-blog, this paper proposed a multidimensional sentiment classification method based micro-blog emotion classification, emoticon in micro-blog is adopted to train the support vector machine and divide micro-blog into seven types of emotions: happiness, fondness, sorrow, anger, fear, detestation and surprise. We used micro-blog emoticon to initial screen large-scale unmarked data, and automatically labeled them into seven types, then used this emotional corpus as training set to train the emotion classifier to classify micro-blog data into multiple emotion categories. The experimental results show that precision of unigram model for each type can reach 63.7%. Meanwhile, different feature selection methods for support vector machines and Naive Bayes classifier experiment have been adopted in the experiment, the precision and recall has reached more than 71%.

关键词： Accuracy Support vector machines Twitter Niobium Training Blogs Sentiment analysis

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FACE RECOGNITION BASED ON DOUBLE COMPLEMENTARY SPACE AND MULTI-DECISION CLASSIFICATION

FACE RECOGNITION BASED ON DOUBLE COMPLEMENTARY SPACE AND MUL...

引用

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

作者： Fuji Ren Yanqiu Li Liangfeng Xu Min Hu Xiaohua Wang Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology Faculty of Engineering The University of Tokushima770-8506TokushimaJapan

In order to overcome the one-sidedness and limitations of a single subspace in feature extraction and classification,we propose a face recognition method that extracts features in double complementary space and utilize multi-decision for *** the feature extraction stage,we use ICA and LPE algorithm as the first layer in complementary space to extract global and local features of the face ***,for the purpose of solving the problem that features extracted by ICA are lack of classification information,we further extract classification information from the independent features extracted by ICA on the condition that the FLDA and DCV algorithm are used as the second layer in the complementary *** the classification stage,the test samples are firstly projected to the independent *** that,projected the samples which are difficult to identify to the LPE space and reclassified ***,the results are been determined *** results on ORL database show that the proposed method can effectively improve the recognition rate.

关键词： algorithms complementary space multi-decision classification face recognition

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Test wrapper optimization technique using BDF and GA for 3D IP cores 5

Test wrapper optimization technique using BDF and GA for 3D ...

引用

5th International Conference on computing Communication and Networking Technologies, ICCCNT 2014

作者： Liu, Jun Qian, Qingqing Wu, Xi Ren, Fuji Wang, Wei Chen, Tian School of Computer and Information Hefei University of Technology Hefei230009 China AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei230009 China Department of Information Science and Intelligent Systems Faculty of Engineering University of Tokushima Tokushima7708502 Japan

ISBN: (纸本)9781479926961

To reduce pre-bond and post-bond test cost for 3D IP (Three Dimensional Intellectual Property) cores, this paper proposed a test wrapper optimization technique using BFD(Best Fit Decreasing) and GA (Genetic Algorithm) algorithm under the constraints of TSVs(Through Silicon Vias) number, the proposed technique firstly used BFD to balance the length of pre-bond wrapper chains to reduce pre-bond test time. Then, on the basis of optimization results of pre-bond wrapper chains, the GA was used to stitch pre-bond wrapper chains to form balanced post-bond wrapper chains under the constrained TSVs number to reduce hardware overhead and post-bond test time. Experimental results demonstrated the presented methodology can effectively reduce hardware overhead at the cost of little increased test time. © 2014 IEEE.

关键词： Chains

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Design and realization of 3D NOC multicast router base on multicast rotational routing arithmetic

Design and realization of 3D NOC multicast router base on mu...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Wei Wang Runfeng Li Fang Fang Tian Chen Fuji Ren Jun Liu Xi Wu Hefei University of Technology Hefei China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine China

ISBN: (纸本)9781479926978

Traditional 3D NoC router may encounter the situations of congestion and hot spot. And it also doesn't have the function of multicast. In this paper, we present a new routing arithmetic called Multicast Rotational Routing Arithmetic (MRRA). It can handle several destination addresses at the same time, recombine packets, sent the same data to the different destination nodes, and avoid the congestion. The proposed algorithm is implemented by the new multicast 3D NoC router which is also proposed in this paper. The 3D NoC router is designed in Verilog HDL, simulated by Modelsim, synthesized and prototyped by Synplify and FPGA respectively. The experiment results show that the multicast router of MRRA can achieve a very good performance in terms of throughput and delay. The increased area utilization also can be tolerated.

关键词： Routing Three-dimensional displays Throughput Algorithm design and analysis Ports (Computers) Hardware design languages Integrated circuits

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Face recognition based on double complementary space and multi-decision classification

Face recognition based on double complementary space and mul...

引用

IEEE International Conference on Cloud computing and Intelligence Systems (CCIS)

作者： Fuji Ren Yanqiu Li Liangfeng Xu Min Hu Xiaohua Wang School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory Faculty of Engineering The University of Tokushima Tokushima Japan

ISBN: (纸本)9781467369541

In order to overcome the one-sidedness and limitations of a single subspace in feature extraction and classification, we propose a face recognition method that extracts features in double complementary space and utilize multi-decision for classification. In the feature extraction stage, we use ICA and LPE algorithm as the first layer in complementary space to extract global and local features of the face images. Then, for the purpose of solving the problem that features extracted by ICA are lack of classification information, we further extract classification information from the independent features extracted by ICA on the condition that the FLDA and DCV algorithm are used as the second layer in the complementary space. In the classification stage, the test samples are firstly projected to the independent subspace. After that, projected the samples which are difficult to identify to the LPE space and reclassified them. Finally, the results are been determined comprehensively. Experimental results on ORL database show that the proposed method can effectively improve the recognition rate.

关键词： Feature extraction Classification algorithms Face recognition Face Data mining Entropy Databases

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A test data compression scheme based on position information coding

A test data compression scheme based on position information...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Tian Chen Bingdong Yang Wei Wang Birong Hao Fuji Ren Jun Liu YiXin Wang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei The University of Tokushima Japan

ISBN: (纸本)9781479926978

Under the condition of Built-off Self-test (BOST), a novel test data compression scheme based on position information coding is presented, which is targeting test data and test power consumption. The proposed scheme gets the next test stimuli by reversing some bits of the responses corresponding to the previous test vectors. During the process of bit flip, test power problem should be taken into account; both the shift power and capture power during the test should be limited in the scope of security. For shift power, need to modify the scan chain by adding blocking logic; and the capture power reduction through the test cube filling based on the response. Experimental results justify the efficacy of the proposed method in attaining test-data compression; the average compression ratio is 73.63% on the premise of capture power consumption reduced by 20%.

关键词： Encoding Hamming distance Test data compression Radiation detectors Hardware Sorting Built-in self-test

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A Connected Component-Based Distributed method for overlapping community detection 5

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

引用

5th International Conference on computing Communication and Networking Technologies, ICCCNT 2014

作者： Chen, Tian Liu, Kai Yi, Xin Shen, Dandan Wang, Wei Ren, Fuji Liu, Jun School of Computer and Information Hefei University of Technology Hefei230009 China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei230009 China AnHui Agricultural University Hefei230036 China University of Tokushima 770-8506 Japan

ISBN: (纸本)9781479926961

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. © 2014 IEEE.

关键词： Complex networks

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