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International Joint Conference on Neural Networks

作者： Weijiang Feng Naiyang Guan Yuan Li Xiang Zhang Zhigang Luo Institute of Software College of Computer National University of Defense Technology Changsha Hunan P.R. China 410073 Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha Hunan P.R. China 410073

ISBN: (纸本)9781509061839

Studies on nowadays human-machine interface have demonstrated that visual information can enhance speech recognition accuracy especially in noisy environments. Deep learning has been widely used to tackle such audio visual speech recognition (AVSR) problem due to its astonishing achievements in both speech recognition and image recognition. Although existing deep learning models succeed to incorporate visual information into speech recognition, none of them simultaneously considers sequential characteristics of both audio and visual modalities. To overcome this deficiency, we proposed a multimodal recurrent neural network (multimodal RNN) model to take into account the sequential characteristics of both audio and visual modalities for AVSR. In particular, multimodal RNN includes three components, i.e., audio part, visual part, and fusion part, where the audio part and visual part capture the sequential characteristics of audio and visual modalities, respectively, and the fusion part combines the outputs of both modalities. Here we modelled the audio modality by using a LSTM RNN, and modelled the visual modality by using a convolutional neural network (CNN) plus a LSTM RNN, and combined both models by a multimodal layer in the fusion part. We validated the effectiveness of the proposed multimodal RNN model on a multi-speaker AVSR benchmark dataset termed AVletters. The experimental results show the performance improvements comparing to the known highest audio visual recognition accuracies on AVletters, and confirm the robustness of our multimodal RNN model.

关键词： Visualization Hidden Markov models Speech recognition Recurrent neural networks Feature extraction Logic gates Data models

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High-performance Audio Matching with Features Learned by Convolutional Deep Belief Network

High-performance Audio Matching with Features Learned by Con...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Weijiang Feng Naiyang Guan Zhigang Luo Institute of Software College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

Audio matching automatically retrieves all excerpts that have the same content as the query audio clip from given audio recordings. The extracted feature is critical for audio matching and the Chroma Energy Normalized Statistics(CENS) feature is the state-of-the-arts. However, CENS might behave unsatisfactorily on some audio because it is a handcraft feature. In this paper, we propose to utilize the features learned by Convolutional Deep Belief Network(CDBN) to enhance the performance of audio matching. Benefit from the strong generalization ability of CDBN, our method works better than CENS based methods on most audio datasets. Since the features learned by CDBN are binary-valued, we can develop a more efficient audio matching algorithm by taking the advantage of this property. Experimental results on both TIMIT dataset and a simulated music dataset confirm effectiveness of the proposed CDBN based method comparing with the traditional CENS feature based algorithm.

关键词： audio matching convolutional deep belief network content-based audio retrieval

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Towards Robust Ego-Centric Hand Gesture Analysis for Robot Control

Towards Robust Ego-Centric Hand Gesture Analysis for Robot C...

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2016 IEEE International Conference on Signal and Image Processing

作者： Hongyong Song Weijiang Feng Naiyang Guan Xuhui Huang Zhigang Luo Institute of Software College of Computer National University of Defense Technology Department of Computer Science and Technology College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology

Wearable device with an ego-centric camera would be the next generation device for human-computer interaction such as robot *** gesture is a natural way of egocentric human-computer *** this paper, we present an ego-centric multi-stage hand gesture analysis pipeline for robot control which works robustly in the unconstrained environment with varying *** particular, we first propose an adaptive color and contour based hand segmentation method to segment hand region from the egocentric *** then propose a convex U-shaped curve detection algorithm to precisely detect positions of *** parallelly, we utilize the convolutional neural networks to recognize hand *** on these techniques, we combine most information of hand to control the robot and develop a hand gesture analysis system on an i Phone and a robot arm platform to validate its *** result demonstrates that our method works perfectly on controlling the robot arm by hand gesture in real time.

关键词： ego-centric vision hand detection and segmentation fingertips detection hand gesture recognition robot control human-computer interaction

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Symmetric Non-negative Matrix Factorization Based Link Partition Method for Overlapping Community Detection

Symmetric Non-negative Matrix Factorization Based Link Parti...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Xiang Zhang Naiyang Guan Wenju Zhang Xuhui Huang Shuyi Wu Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Hunan P.R. China Institute of Software College of Computer National University of Defense Technology Hunan P.R. China Department of Computer Science and Technology College of Computer National University of Defense Technology Hunan P.R. China

ISBN: (纸本)9781479986989

Partitioning links rather than nodes is effective in overlapping community detection (OCD) on complex networks. However, it consumes high CPU and memory overheads because the volume of links is huge especially when the network is rather complex. In this paper, we proposes a symmetric non-negative matrix factorization (SNMF) based link partition method called SNMF-Link to overcome this deficiency. In particular, SNMF-Link represents data in a lower-dimensional space spanned by the node-link incidence matrix. By solving a lighter SNMF problem, SNMF-Link learns the clustering indicators of each links. Since traditional multiplicative update rule (MUR) based optimization algorithm for SNMF suffers from slow convergence, we applied the augmented Lagrangian method (ALM) to efficiently optimize SNMF. Experimental results show that SNMF-Link is much more efficient than the representative clustering algorithms without reducing the OCD performance.

关键词： Symmetric matrices Convergence Optimization Partitioning algorithms Chlorine Complex networks Image edge detection

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PreCrime to the rescue: Defeating mobile malware one-step ahead 14

PreCrime to the rescue: Defeating mobile malware one-step ah...

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5th ACM Asia-Pacific Workshop on Systems, APSYS 2014

作者： Tan, Cheng Li, Haibo Xia, Yubin Zang, Binyu Chu, Cheng-Kang Li, Tieyan Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Software School Fudan University China State Key Laboratory of Computer Architecture ICT Chinese Academy of Sciences China Huawei Technologies Pte Ltd. Singapore Singapore

ISBN: (纸本)9781450330244

Prior mobile malware defensive means is usually retroactive, which may either lead to high false negatives or can hardly recover systems states from malware activities. PreCrime is a proactive malware detection scheme that detects and stops malware activities from happening. PreCrime creates mirrors of a mobile device in a resource-rich and trusted cloud, which speculatively executes multiple likely user operations concurrently to detect potential tampering and information leakage. Our preliminary evaluation shows that PreCrime introduces small performance overhead on smartphones and feasible delay during speculative execution on the cloud. © 2014 ACM.

关键词： Malware

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Data Avenue: Remote Storage Resource Management in WS-PGRADE/gUSE

Data Avenue: Remote Storage Resource Management in WS-PGRADE...

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International Workshop on Science Gateways (IWSG)

作者： Ákos Hajnal Zoltán Farkas Péter Kacsuk Laboratory of Parallel and Distributed Systems Hungarian Academy of Sciences Budapest Hungary Computer Science and Software Engineering Department University of Westminster London United Kingdom

State-of-the-art gateways are connected to several distributed computing infrastructures (DCIs) and are able to run jobs and workflows simultaneously in all those different DCIs. However, the flexibility of accessing data storages belonging to different DCIs is a missing feature of current gateways. SZTAKI (Institute for Computer Science and Control) has developed a Data Avenue Blacktop service and aLiferay-based Data Avenue port let that open the door for integrating such features into science gateways. The paper explains the design considerations of the Data Avenue Blacktop service and its usage scenarios in science gateways through the Data Avenue port let.

关键词： Conferences Logic gates

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distributed Relation Discovery in Internet of Things

Distributed Relation Discovery in Internet of Things

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International Conference on Cloud Computing and Big Data (CCBD)

作者： Weiping Zhu Hongliang Lu Xiaohui Cui International School of Software Wuhan University China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology China Department of Computing Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9781479966226

Internet of things is an emerging technology that aims to connect various smart objects in our daily life. It facilitates the information exchange and control among objects. In the Internet of things, it is important to discover various relations among objects for analyzing and mining useful knowledge. Existing works on relation discovery mainly focus on centralized processing. It is not suitable for Internet of things due to unavailable of server, one-point failure, computation bottleneck, and security and business concerns. In this paper, we propose a distributed approach to discover the relations among objects in Internet of things. We first build the distritbuted system model which may include multiple relation discovery tasks. Based on that, we design an approach utilizing distributed spanning tree to extract the relations. Rather than sending all the information to the server, the objects only need to send the information to a local leader object in our algorithm. We also discuss more about how to improve the performance of the proposed approach and how to relax the system constraints. Extensive simulation have been done and the results show that the proposed approach outperforms existing approaches in terms of the data amount of transmission.

关键词： Internet of things Synchronization Buildings Servers Algorithm design and analysis Delays

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Failure-divergence refinement of compensating communicating processes

Failure-divergence refinement of compensating communicating ...

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Lecture Notes in Computer Science

作者： Chen, Zhenbang Liu, Zhiming Wang, Ji National Laboratory for Parallel and Distributed Processing Changsha China International Institute for Software Technology United Nations University China

ISBN: (纸本)9783642214363

Compensating CSP (cCSP) extends CSP for specification and verification of long running transactions. The original cCSP is a modest extension to a subset of CSP that does not consider non-deterministic choice, synchronized composition, and recursion. There are a few further extensions. However, it remains a challenge to develop a fixed-point theory of process refinement in cCSP. This paper provides a complete solution to this problem and develops a theory of cCSP, corresponding to the theory of CSP, so that the verification techniques and their tools, such as FDR, can be extended for compensating processes. © 2011 Springer-Verlag.

关键词： Fixed point arithmetic

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Ruan Jian Xue Bao/Journal of software 2011年第1期22卷 132-148页

作者： Li, Hui-Ba Tian, Tian Peng, Yu-Xing Li, Dong-Sheng Lu, Xi-Cheng National Laboratory for Parallel and Distributed Computing Computer School National University of Defense Technology Changsha 410073 China Institute of Software Computer School National University of Defense Technology Changsha 410073 China

The Internet has become a vital information infrastructure for modern society. However, the concurrent nature of network introduces a wide-range of difficulties in traditional programming methodology in developing high-quality network programs that significantly reduce productivity. The influence of concurrency on the complexity of software development is comparable to the "concurrency crisis" of software brought by multi-core processors, but it receives much less attention here than what it deserves. There is no universal approach to cope with this issue, and there are even disagreements between different approaches. In this paper, the basic concurrency models and their implementations are introduced, and then the paper surveys the inherent complexities of these approaches, comparing their advantages and disadvantages. Finally, this paper offers an opinion on the possibilities for future research on this topic. © Copyright 2011, Institute of software, the Chinese Academy of Sciences. All rights reserved.

关键词： Complex networks

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Modelling with relational calculus of object and component systems - RCOS

Modelling with relational calculus of object and component s...

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作者： Chen, Zhenbang Hannousse, Abdel Hakim Van Hung, Dang Knoll, Istvan Li, Xiaoshan Liu, Zhiming Liu, Yang Nan, Qu Okika, Joseph C. Ravn, Anders P. Stolz, Volker Yang, Lu Zhan, Naijun International Institute for Software Technology United Nations University China Faculty of Science and Technology University of Macau Department of Computer Science Aalborg University Denmark Lab. of Computer Science Institute of Software CAS China National Laboratory for Parallel and Distributed Processing China

ISBN: (纸本)3540852883

This chapter presents a formalization of functional and behavioural requirements, and a refinement of requirements to a design for CoCoME using the Relational Calculus of Object and Component Systems (rCOS). We give a model of requirements based on an abstraction of the use cases described in Chapter 3.2. Then the refinement calculus of rCOS is used to derive design models corresponding to the top level designs of Chapter 3.4. We demonstrate how rCOS supports modelling different views and their relationships of the system and the separation of concerns in the development. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Calculations

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