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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第9期8卷 229-238页

作者： Zhan, Tianming Gu, Shenghua Feng, Can Zhan, Yongzhao Wang, Jin School of Computer Science & communications Engineering Jiangsu University Zhenjiang China Jiangsu Key Laboratory of Big Data Analysis Technology Nanjing University of Information Science and Technology Nanjing China Center of software China North Industries Group Corporation Co. Ltd Nanjing China

Automatic brain tumor segmentation from multispectral magnetic resonance imaging (MRI) data is an important but a challenging task because of the high diversity in the appearance of tumor tissues among different patients and in many cases similarity with the normal tissues. In this paper, we propose a fully automatic technique for brain tumor segmentation from multispectral human brain MRIs. We first use the intensities of different patches in multispectral MRIs to represent the features of both normal and abnormal tissues and generate a dictionary for following tissue classification. Then, the sparse representation classification (SRC) is applied to classify the brain tumor and normal brain tissue in the whole image. At last, the Markov random field (MRF) regularization introduces spatial constraints to the SRC to take into account the pair-wise homogeneity in terms of classification labels and multispectral voxel intensities. Our method was evaluated on 20 multi-modality patient datasets with competitive segmentation results. ©, 2015 SERSC.

关键词： Magnetic resonance imaging

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A service evolution registry with alert-based management

A service evolution registry with alert-based management

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2013 5th International Conference on Service Science and Innovation, ICSSI 2013

作者： Feng, Zaiwen Chiu, Dickson K.W. He, Keqing State Key Laboratory of Software Engineering Wuhan University Wuhan China School of Computer Wuhan University Wuhan China Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Technology China Dickson Computer Systems 117 Argyle Street Kowloon Hong Kong

ISBN: (纸本)9780769549859

To enable sustainable service innovation, services are often subject to changes and variations. In particular, service evolution creates problems in invocation if the service users cannot be notified timely. Therefore managing service evolution is a key challenge of the Service-Oriented paradigm. To address this problem, we design a meta-model to facilitate service registration focusing on administrative information and versioning, with an intension to promote reuse. We further develop a sophisticated alert mechanism to send alerts to stakeholders about service evolution information so that they can take timely measures. Currently, part of our work has been proposed to the International Standard Organization (ISO) as the draft of ISO/IEC SC32 19763 Part 7. © 2013 IEEE.

关键词： ISO Standards

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Towards a taxonomy framework of evolution for SOA solution: From a practical point of view

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Combined Workshops on Web Information Systems engineering, WISE 2011 and WISE 2012

作者： Feng, Zaiwen Hung, Patrick C. K. He, Keqing Ma, Yutao Farwick, Matthias Li, Bing Peng, Rong State Key Lab. of Software Engineering Wuhan University China School of Computer Wuhan University China Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Techonology China Faculty of Business and IT University of Ontario Institute of Technology Canada Institute of Computer Science University of Innsbruck Austria

ISBN: (纸本)9783642383328

Presently, the research on evolution of SOA solution is becoming more and more important in industry. It is necessary to extract a taxonomy framework for evolution of SOA solution because by using it, evolution of SOA-based systems can be analyzed and compared comprehensively and objectively. In this paper, a taxonomy framework for evolution of SOA solution is proposed that is illustrated from four perspectives: (a) motivations for evolutionary changes (why), (b) locations where evolutionary changes happen (where), (c) times when evolutionary changes happen (when), and (d) support mechanisms in the process of evolutionary changes (how). Furthermore, the taxonomy framework is applied on analyzing a SOA-based configurable system for urban logistics delivery management, as an application of taxonomy framework. © 2013 Springer-Verlag.

关键词： Taxonomies

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Face hallucination based on sample selection bias correction

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International Journal of Advancements in Computing Technology 2012年第5期4卷 91-98页

作者： Lu, Tao Hu, Ruimin Han, Zhen Jiang, Junjun Chang, Jun National Engineering Research Center on Multimedia Software Wuhan University Wuhan 430072 China Hubei Province Key Laboratory of Intelligent Robot School of Computer Science and Engineering Wuhan Institute of Technology Wuhan 430073 China

In some learning approach problems, the learning algorithm receives training and test samples drawn according to the same distribution. However, this assumption is not available in practice. In face super-resolution, when the training sample available is biased, it may affect quality of the construction face. In this paper, we proposed a novel method to correct the bias of sample selection in training dataset. First, Active Shape Model is used to get the face shape vectors which contain some information about face contour. Then all faces from Chinese face dataset are classified into certain categories based on Hausdor ff Distance by k-means clustering. We correct the sample bias by selecting the most similar faces due to the face shape similarity between samples and test images. Last, the global face reconstruction method based on eigen face is used to achieve satisfied image quality with selected train dataset. Experiments show that the face super-resolution algorithm based on sample selection bias correction can improve the subjective and objective quality of the input low resolution face images compared to traditional eigenface algorithm.

关键词： Learning algorithms

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Surveillance face super-resolution via shape clustering and subspace learning

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2012年第4期5卷 107-116页

作者： Tao, Lu Ruimin, Hu Zhen, Han Yang, Xia Shang, Gao National Engineering Research Center on Multimedia Software Wuhan University Wuhan 430072 China Hubei Province Key Laboratory of Intelligent Robot College of Computer Science and Engineering Wuhan Institute of Technology Wuhan 430073 China School of Computer Wuhan University Wuhan 430072 China

In a learning-based super-resolution algorithm, suitable prior from the training database is a key issue. A novel face hallucination algorithm based on shape clustering and subspace learning for adaptive prior is proposed in this paper. We define face shape metrics with point distribution model by Hausdorff Distance, then a framework of adaptive prior and subspace learning is proposed to enhance the performance of surveillance face super-resolution. Linear regression is used to learn the relationship between low and high image systhesis coefficients. Experiments show that the face super-resolution algorithm based on shape classification can improve the subjective and objective quality of the input low-resolution face images and outperform many state-of-the-art global-based face super-resolution methods.

关键词： Monitoring

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Implementation of behavioral subtyping in aspect-oriented program

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2011年第2期5卷 206-215页

作者： He, Chengwan Li, Zheng Computer School of Science and Engineering Wuhan Institute of Technology Wuhan 430073 China Hubei Province Key Laboratory of Intelligent Robot Wuhan 430073 China State key laboratory of Software Engineering School of Computer Wuhan University China

Semantic conflicts may appear in the process of weaving aspects in the aspect-oriented program. This paper proposes an approach to check such semantic conflicts based on the concept of behavioral subtyping, and presents the conditions of behavioral subtyping. Through extracting the preconditions and postconditions defined in the base program and aspects, then automatically transforming them into the code to check conditions of behavioral subtyping, consequently it achieves checking of semantic conflicts, and guarantees correctness of the program's behavior after weaving aspects. These codes for checking semantic conflicts are implemented by using aspects, and the implementation method is explained through an example.

关键词： Aspect oriented programming

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Face super-resolution based-on non-negative matrix factorization

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2011年第4期5卷 82-87页

作者： Lu, Tao Hu, Ruimin Lan, Chengdong Han, Zhen National Engineering Research Center on Multimedia Software Wuhan University Wuhan 430072 China Hubei Province Key Laboratory of Intelligent Robot College of Computer Science and Engineering Wuhan Institute of Technology Wuhan 430070 China School of Computer Wuhan University Wuhan 430072 China

Principal Component Analysis (PCA) is a classical method which is commonly used for human face images representation in face super-resolution. But the features extracted by PCA are holistic and difficult to have semantic interpretation. In order to synthesize a high-resolution face image with structural details, we propose a face super-resolution algorithm based on non-negative matrix factorization (NMF). This algorithm uses the NMF to obtain structural information representation of face images, and then the target image is regularized by Markov random fields, with maximum a posteriori probability approach. Finally, the steepest descent method is used to optimize NMF coefficient of high-resolution image. Experiment results demonstrate that the NMF-based face super-resolution algorithm performs better than PCA-based algorithms, in the subjective and objective quality.

关键词： Non-negative matrix factorization

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Super-resolution for compressed video based on DCT side information

Super-resolution for compressed video based on DCT side info...

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2009 2nd Asia-Pacific Conference on Computational Intelligence and Industrial Applications, PACIIA 2009

作者： Lu, Tao Hu, Ruimin Lan, Chengdong Han, Zhen Wang, Zhongyuan National Engineering Research Center for Multimedia Software Wuhan University Wuhan 430072 China Hubei Province Key Laboratory of Intelligent Robot College of Computer Science and Engineering Wuhan Institute of Technology Wuhan430073 China School of Computer Wuhan University Wuhan 430072 China

ISBN: (纸本)9781424446070

In previous papers, frequency-domain quantization noise was always treated as uniform distribution in super-resolution construction for compressed video, when at high compressed ratio, this model may introduce error. This paper provides a Laplace model of DCT coefficients whose parameters can extract from the encoder, then transfers them as side information to the decoder, and utilizes the distribution of DCT coefficients as priori information in MAP(Maximum a Posterior) for super-resolution construction. Experimental results demonstrate the effectiveness of this approach. ©2009 IEEE.

关键词： Frequency domain analysis

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Characterizing Smart Contract Evolution

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ACM Transactions on software engineering and Methodology 1000年

作者： Xiangping Chen Ziang Qian Peiyong Liao Yuan Huang Changlin Yang Zibin Zheng Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion School of Journalism and Communication Sun Yat-sen University China School of Software Engineering Sun Yat-sen University China School of Computer Science and Engineering Sun Yat-sen University China

Smart contracts are programs that permanently store and automatically execute on the blockchain system such as Ethereum. Due to the non-tamperable nature of the underlying blockchain, smart contracts are difficult to update once deployed, which requires redeploying the contracts and migrating the data. It means that the observation of smart contract evolution in the real world makes more sense. Hence, in this paper, we conducted the first large-scale empirical study to characterize the evolution of smart contracts in Ethereum. For evolution identification, we presented a contract similarity-based search algorithm, digEvolution, and evaluated its effectiveness with five different search strategies. Then we applied this algorithm to 80,152 on-chain contracts we collected from Ethereum, to dig out the evolution among these contracts. We then explored three research questions. We first studied whether the evolution of smart contracts is common (RQ1), then we studied how do the Gas consumption (RQ2) and the vulnerability (RQ3) of smart contracts vary during the evolution. Our research results show that the evolution of smart contracts is not very common. There are some contract components that have vulnerability but still be called by users. The Gas consumption of most smart contracts doesn’t vary during the evolution, contract is Gas-efficient before and after the evolution. The vulnerability of most smart contracts doesn’t vary during the evolution, both are secure before and after the evolution.

关键词： Smart Contract software Evolution Code Clone

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Interpreting Deep Forest through Feature Contribution and MDI Feature Importance

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ACM Transactions on Knowledge Discovery from data 1000年

作者： Yi-Xiao He Shen-Huan Lyu Yuan Jiang National Key Laboratory for Novel Software Technology and School of Artificial Intelligence Nanjing University China Key Laboratory of Water Big Data Technology of Ministry of Water Resources and College of Computer Science and Software Engineering Hohai University China

Deep forest is a non-differentiable deep model that has achieved impressive empirical success across a wide variety of applications, especially on categorical/symbolic or mixed modeling tasks. Many of the application fields prefer explainable models, such as random forests with feature contributions that can provide a local explanation for each prediction, and Mean Decrease Impurity (MDI) that can provide global feature importance. However, deep forest, as a cascade of random forests, possesses interpretability only at the first layer. From the second layer on, many of the tree splits occur on the new features generated by the previous layer, which makes existing explaining tools for random forests inapplicable. To disclose the impact of the original features in the deep layers, we design a calculation method with an estimation step followed by a calibration step for each layer, and propose our feature contribution and MDI feature importance calculation tools for deep forest. Experimental results on both simulated data and real-world data verify the effectiveness of our methods.

关键词： deep forest feature importance interpretability

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