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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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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

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

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International Conference on computing and Networking Technology (ICCNT)

作者： Jun Liu Qingqing Qian Xi Wu Fuji Ren Wei Wang Tian Chen AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei Department of Information Science & Intelligent Systems The University of Tokushima Tokushima Japan

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.

关键词： Biological cells Three-dimensional displays Hardware IP networks System-on-chip Genetic algorithms Sociology

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WeWatch: Bi-screen video watching experience on smart devices

WeWatch: Bi-screen video watching experience on smart device...

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

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

ISBN: (纸本)9781467369541

The high resolution and widescreen mobile devices have tremendous applications in our daily lives. In 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 devices. It helps users to enhance their watching experience on the Android system. In order to efficiently use idle mobile devices, we develop a novel algorithm to share videos with devices with different screen sizes and resolutions. Our research provides a method which automatically controls videos based on different distances between devices. The distance is determined by the empirical WiFi RSSI values obtained through the experimental studies. We have prototyped the system and conducted a real-world energy efficiency and user experience evaluations. Results show that WeWatch has negligible impact on battery lifetime while over 80% users like our application.

关键词： Aggregates Smart phones Servers Information services Electronic publishing Internet

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Fruit recognition based on multi-feature and multi-decision

Fruit recognition based on multi-feature and multi-decision

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

作者： Xiaohua Wang Wei Huang Chao Jin Min Hu Fuji Ren School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory The University of Tokushima Japan

ISBN: (纸本)9781467369541

In order to overcome the existing fruit recognition method only for single feature recognition which leads the problem of lower recognition rate, this paper proposes a recognition method based on multi-feature and multi-decision. Firstly, we preprocess the fruit image which is to be classified, separating foreground and background, and then we divide the target area. Secondly, in order to take full advantage of multi-independence and complementarity between features, we extract the color, shape and texture of fruits image and put these features into the BP neural network to classify. Finally, the results of different features are put into the decision-making mechanisms to obtain a final recognition result. The experiment results on object library and self-built library that is built by ourselves show that the method has good identification ability to fruit recognition and achieve the goal to identify different fruit.

关键词： Machine vision Image recognition Image segmentation Image color analysis Shape Image resolution

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ADAPTIVE FACIAL EXPRESSION RECOGNITION METHOD BASED ON MBP AND HMOG FEATURE

ADAPTIVE FACIAL EXPRESSION RECOGNITION METHOD BASED ON MBP A...

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

作者： Min Hu Xiaoyin Huang Xiaohua Wang Kun Li Fuji Ren Liangfeng Xu Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology The University of Tokushima 770-8506Japan

Because of the limitation of Monogenic waves’ extraction from expression texture,this thesis proposes an adaptive facial expression feature fusion method based on MBP（monogenic binary pattern） and Histogram of HMOG（monogenic orientated gradients）.To begin with our method,we get information of orientation,phase and magnitude component from filtered image by monogenic waves,besides,extract and fuse texture information from orientation and magnitude component to recognize facial *** single texture feature have some inadequacies for facial expression *** of all,this paper describes a new kind of HMOG feature inspired by thoughts of HOG（histogram of oriented gradients） to indicate shape information of facial ***,acquiring best adaptive weights of expression block through information ***,we classify the expression image using Nearest Neighbor to get the final result of effect of proposed *** order to verify the efficiency of the methods above,we do a large number of experiments and it turns out our methods have great ability to explain expression feature.

关键词： Monogenic signal Histogram of Monogenic Oriented Gradients Adaptive weights by information entropy Nearest Neighbor

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Adaptive facial expression recognition method based on MBP and HMOG feature

Adaptive facial expression recognition method based on MBP a...

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

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

ISBN: (纸本)9781467369541

Because of the limitation of Monogenic waves' extraction from expression texture, this thesis proposes an adaptive facial expression feature fusion method based on MBP (monogenic binary pattern) and Histogram of HMOG (monogenic orientated gradients). To begin with our method, we get information of orientation, phase and magnitude component from filtered image by monogenic waves, besides, extract and fuse texture information from orientation and magnitude component to recognize facial expression. However single texture feature have some inadequacies for facial expression recognition. First of all, this paper describes a new kind of HMOG feature inspired by thoughts of HOG (histogram of oriented gradients) to indicate shape information of facial image. Secondly, acquiring best adaptive weights of expression block through information entropy. Finally, we classify the expression image using Nearest Neighbor to get the final result of effect of proposed method. In order to verify the efficiency of the methods above, we do a large number of experiments and it turns out our methods have great ability to explain expression feature.

关键词： Feature extraction Face Entropy Information filters Databases Computers

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Age estimation and gender classification of facial images based on Local Directional Pattern

Age estimation and gender classification of facial images ba...

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

作者： Min Hu Yaona Zheng Fuji Ren He Jiang School of Computer and Information Hefei University of Technology Anhui China Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory The University of Tokushima Japan

ISBN: (纸本)9781467369541

In order to improve shortage of Local Binary Pattern (LBP) algorithm in the field of facial feature extraction, this paper uses Local Directional Pattern (LDP) algorithm to extract the facial features about age estimation and gender classification. Because gradient information is more stable than gray information, LDP algorithm is not affected easily by noise. After preprocessing images, we use block strategy to represent facial features more fully. And then, we extract features of each block with LDP algorithm, storing the LDP histogram. Finally, we obtain age and gender identification results by Support Vector Machine (SVM). Experimental results on FG-NET face database show that this method has a good effect on age estimation and gender classification.

关键词： Face Feature extraction Estimation Interference Principal component analysis

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Plant growth simulation algorithm for solving bilevel symbiosis optimization between manufacturing enterprise and logistics enterprise

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ICIC Express Letters 2014年第2期8卷 629-636页

作者： Li, Tong Jiang, Yufei Chen, Chouyong Ji, Tongcai Management College Hangzhou Dianzi University No. 2 St Hangzhou 310018 China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University No. 10 Xuefu St. Jinzhou New District Dalian 116622 China

An intelligence optimization algorithm for solving nonlinear bilevel programming is proposed herein. In this algorithm, the upper solution space and lower reaction set of bilevel programming are looked as two growth environments of plants. Then the plant system evolution style based on growth regulation and the probability growth model based on plant phototropism theory are established. The optimization model combined with above two has realized the evolution of artificial plant from initial status to whole final status (that means no new branch growing), thus the optimal solutions of bilevel programming can be found. The algorithm herein shows its high accuracy and strong astringency. This article solves the problem of bilevel symbiosis optimization between manufacturing enterprise and logistics enterprise by using this algorithm, and the result shows that Plant Growth Simulation Algorithm (PGSA) has good effectiveness and feasibility. © 2014 ISSN 1881-803X.

关键词： Optimization

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FACE RECOGNITION BASED ON ADAPTIVE WEIGHTING AND FUZZY FUSION WITH SINGLE TRAINING SAMPLE

FACE RECOGNITION BASED ON ADAPTIVE WEIGHTING AND FUZZY FUSIO...

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

作者： Xiaohua Wang Chao Jin Wei Liu Min Hu Fuji Ren Affective Computing and Advanced Intelligent Machines Anhui Key Laboratory School of Computer and Information Hefei University of Technology The University of Tokushima 770-8506Japan

In order to solve the robustness issues for single training sample face recognition under occlusion conditions,this paper presents a recognition method based on adaptive weighting and fuzzy *** our method,the information entropy expansion mode is introduced in sub-mode method and via adaptively assigning the weights corresponding to each sub-model can reduce the impact of occluded *** addition,through summing the similar blocks in face images can make up for the defect of the sub-model which ignores the integrity of ***,the method based on fuzzy comprehensive evaluation is utilized for decision-level fusion to the outputs by these two ways of *** results on AR face database show that this method has state-of-the-art classification accuracy and also robustness to occlusion.

关键词： Face recognition Single training sample Adaptive weighting Fuzzy comprehensive evaluation Sub-model

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