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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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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...

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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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A test data compression scheme based on position information coding

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

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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...

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

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

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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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Psychological stress detection from cross-media microblog data using Deep Sparse Neural Network

Psychological stress detection from cross-media microblog da...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Huijie Lin Jia Jia Quan Guo Yuanyuan Xue Jie Huang Lianhong Cai Ling Feng TNList and Key Laboratory of Pervasive Computing Ministry of Education Department of Computer Science and Technology Tsinghua University Beiiing China Machine Intelligence Laboratory Sichuan University Chengdu China

Long-term stress may lead to many severe physical and mental problems. Traditional psychological stress detection usually relies on the active individual participation, which makes the detection labor-consuming, time-costing and hysteretic. With the rapid development of social networks, people become more and more willing to share moods via microblog platforms. In this paper, we propose an automatic stress detection method from cross-media microblog data. We construct a three-level framework to formulate the problem. We first obtain a set of low-level features from the tweets. Then we define and extract middle-level representations based on psychological and art theories: linguistic attributes from tweets' texts, visual attributes from tweets' images, and social attributes from tweets' comments, retweets and favorites. Finally, a Deep Sparse Neural Network is designed to learn the stress categories incorporating the cross-media attributes. Experiment results show that the proposed method is effective and efficient on detecting psychological stress from microblog data.

关键词： Stress Psychology Feature extraction Image color analysis Pragmatics Brightness Joints

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Effects of non-training movements on the performance of motion classification in electromyography pattern recognition

Effects of non-training movements on the performance of moti...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Xiangxin Li Shixiong Chen Haoshi Zhang Xiufeng Zhang Guanglin Li Key Laboratory of Human-Machine-Intelligence Synergic System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences National Research Center for Rehabilitation Technical Aids

ISBN: (纸本)9781424479276

In electromyography pattern-recognition-based control of a multifunctional prosthesis, it would be inevitable for the users to unintentionally perform some classes of movements that are excluded from the training motion classes of a classifier, which might decay the performance of a trained classifier. It remains unknown how these untrained movements, designated as non-target movements (NTMs) in the study, would affect the performance of a trained classifier in the control of multifunctional prostheses. The goal of the current study was to evaluate the effects of NTMs on the performance of movement classification. Five classes of target movements (TMs) and four classes of NTMs were considered in this pilot study. A classifier based on a linear discriminant analysis (LDA) was trained with the electromyography (EMG) signals from the five TMs and the effects of the four NTMs were examined by feeding the EMG signals of the four NTMs to the trained classifier. Our results showed that these NTMs were classified into one or more classes of the TMs, which would cause the unexpected movements of prostheses. A method to reduce the effects of NTMs has been proposed in the study and our results showed that the averaged classification accuracies of the corrected classifiers were above 99% for the healthy subjects.

关键词： Electromyography Prosthetics Accuracy Training Wrist Muscles Electrodes

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WEWATCH:BI-SCREEN VIDEO WATCHING EXPERIENCE ON SMART DEVICES

WEWATCH:BI-SCREEN VIDEO WATCHING EXPERIENCE ON SMART DEVICES

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

作者： Fuji Ren Mengni Chen Yu Gu Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computing and InformationHefei University of Technology Dept.of Information Science & Intelligent Systems Univ.of TokushimaJapan

The high resolution and widescreen mobile devices have tremendous applications in our daily *** this paper,we demonstrate a specific bi-screen video sharing application called WeWatch that a high resolution video is played across screens of two mobile *** helps users to enhance their watching experience on the Android *** order to efficiently use idle mobile devices,we develop a novel algorithm to share videos with devices with different screen sizes and *** research provides a method which automatically controls videos based on different distances between *** distance is determined by the empirical WiFi RSSI values obtained through the experimental *** have prototyped the system and conducted a real-world energy efficiency and user experience *** show that WeWatch has negligible impact on battery lifetime while over 80%users like our application.

关键词： Video Sharing Screen adaptation Distance detection Energy efficiency.

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Acoustics, content and geo-information based sentiment prediction from large-scale networked voice data

Acoustics, content and geo-information based sentiment predi...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhu Ren Jia Jia Quan Guo Kuo Zhang Lianhong Cai TNList and Key Laboratory of Pervasive Computing Ministry of Education Department of Computer Science and Technology Tsinghua University Beijing China Machine Intelligence Laboratory Sichuan University Chengdu China Sogou Corporation Beijing China

Sentiment analysis from large-scale networked data attracts increasing attention in recent years. Most previous works on sentiment prediction mainly focus on text or image data. However, voice is the most natural and direct way to express people's sentiments in real-time. With the rapid development of smart phone voice dialogue applications (e.g., Siri and Sogou Voice Assistant), the large-scale networked voice data can help us better quantitatively understand the sentimental world we live in. In this paper, we study the problem of sentiment prediction from large-scale networked voice data. In particular, we first investigate the data observations and underlying sentiment patterns in human-mobile voice communication. Then we propose a deep sparse neural network (DSNN) model to incorporate acoustic features, content information and geo-information to automatically predict sentiments. The effectiveness of the proposed model is verified by the experiments on a real dataset from Sogou Voice Assistant application.

关键词： Correlation Cities and towns Feature extraction Acoustics Artificial neural networks Neurons Predictive models

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Using Thin-Film Piezoelectret to Detect Tactile and Slip Signals for Restoring Sensation of Prosthetic Hands

Using Thin-Film Piezoelectret to Detect Tactile and Slip Sig...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Peng Fang Lan Tian Yue Zheng Jianping Huang Guanglin Li Key Laboratory of Human-Machine-Intelligence Synergic System of Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Chinese Academy of Sciences Beijing Beijing CN

Most of the currently available prosthetic hands do not have a proper sensation of touching and slipping. Thus it is not easy for arm amputees to grasp objects properly only with an assistance of visual feedback. In this pilot work, a sensor based on thin-film piezoelectret was used to detect the possible tactile and slip information of a prosthetic hand. The piezoelectret sensor is flexible and is able to be bended, and therefore it could be properly mounted on the surface of prosthetic finger. Our preliminary results demonstrated that both the tactile and slip information could be acquired with the same sensor unit. For a grasp without slippage, the tactile signal was usually a single large peak, whereas the slip signal was a series of vibrations in a small range. Thus these two types of signals could be easily separated based on their different characteristics. This study suggested that by using thin-film piezoelectret sensor, a primary control with involuntary feedback might be achieved for the present prosthetic hands. More studies would be required on the detailed signal processing and control strategy for the restoration of sensation function in prosthetic hands.

关键词： Prosthetic hand Force Thumb Robot sensing systems Piezoelectric transducers Electromyography

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