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2010 International Conference on Biomedical Engineering and Computer Science, ICBECS 2010

作者： Jun, Niu Zeng, Guosun Department of Computer Science and Technology Tongji University Shanghai China College of Information Engineering Zhejiang Business Technology Institute Ningbo China Embedded System and Service Computing Key Lab. Ministry of Education Shanghai China

ISBN: (纸本)9781424453153

This paper proposes a generalized model by extending Markov chain with spatial resources labels, which can describe the functional and performance properties and some basic characteristics such as nondeterminacy and randomicity. The syntax and semantics of the new model are shown based on the existing temporal logics such as CSRL and pathCSRL. The model checking procedure is discussed and thus the practicability of the new model is intuitive. Based on the existing models, the proposed model includes spatial resources labels only by adding the spatial information to the existing labels of states, so the treatment of the state explosion problem is similar to that in the existing models. ©2010 IEEE.

关键词： Model checking

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Neurological rehabilitation of stroke patients via motor imaginary-based brain-computer interface technology

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Neural Regeneration Research 2011年第28期6卷 2198-2202页

作者： Hongyu Sun Yang Xiang Mingdao Yang Department of Computer Science and Technology Tongji University Shanghai 201804 China College of Information and Electrical Engineering Shandong University of Science and Technology China Key Laboratory of Embedded System and Service Computing Ministry of Education of the People＇s Republic of China Tongji University Shanghai 201804 China Qingdao Economic ＆ Technical Development Area First People＇s Hospital Qingdao 266555 Shangdong Province China

The present study utilized motor imaginary-based brain-computer interface technology combined with rehabilitation training in 20 stroke patients. Results from the Berg Balance Scale and the Holden Walking Classification were significantly greater at 4 weeks after treatment （P 〈 0.01）, which suggested that motor imaginary-based brain-computer interface technology improved balance and walking in stroke patients.

关键词： brain-computer interface motor cortex neuronal plasticity rehabilitation stroke neural regeneration

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An improved test case generation method of pair-wise testing

An improved test case generation method of pair-wise testing

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16th Asian Test Symposium, ATS 2007

作者： Qian, Feng-An Jiang, Jian-Hui Key Laboratory of Embedded Systems and Service Computing Ministry of Education of the People's Republic of China Tongji University Shanghai 201804 China Department of Computer Science and Technology Tongji University Shanghai 201804 China

ISBN: (纸本)0769528902

Pair-wise testing is a testing criterion based on specification, which requires that for each pair of parameters, every combination of their valid value should be covered by at least one test case in the test set. This paper presents an improved method based on AETG. Experimental results show that the size of test set produced by our method is relatively small. In addition, the method can be easily implemented. © 2007 IEEE.

关键词： Software testing

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Parallelizing multiclass Support Vector Machines for scalable image annotation

Parallelizing multiclass Support Vector Machines for scalabl...

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Alham, Nasullah Khalid Li, Maozhen Liu, Yang Hammoud, Suhel School of Engineering and Design Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Ministry of Education Tongji University China

ISBN: (纸本)9781612841816

Machine learning techniques have facilitated image retrieval by automatically classifying and annotating images with keywords. Among them Support Vector Machines (SVMs) are used extensively due to their generalization properties. SVM was initially designed for binary classifications. However, most classification problems arising in domains such as image annotation usually involve more than two classes. Notably SVM training is a computationally intensive process especially when the training dataset is large. This paper presents MRMSVM, a distributed multiclass SVM algorithm for large scale image annotation which partitions the training dataset into smaller binary chunks and train SVM in parallel using a cluster of computers. MRMSVM is evaluated in an experimental environment showing that the distributed Multiclass SVM algorithm reduces the training time significantly while maintaining a high level of accuracy in classifications. © 2011 IEEE.

关键词： MapReduce

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Reduction criteria for probabilistic models with spatial restrictions on states

Reduction criteria for probabilistic models with spatial res...

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2nd International Conference on Networks Security, Wireless Communications and Trusted computing, NSWCTC 2010

ISBN: (纸本)9780769540115

Partial order reduction techniques have been used to combat the state explosion problem in model checking procedures for concurrent systems with probabilistic behaviors. There are some results that give criteria on applying partial order reduction for verifying quantitative time properties and reward-based properties on actions. However, there are many situations that reward-based properties are expressed on states rather than on actions because actions are triggered in no time and the quantities can not be obtained easily. This paper presents reduction criteria for a probabilistic temporal logic that allows specification of restrictions on quantitative measures given by spatial resources function for the states of the considered system and provides the proof of the correctness. © 2010 IEEE.

关键词： Markov processes

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A distributed SVM for scalable image annotation

A distributed SVM for scalable image annotation

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Alham, Nasullah Khalid Li, Maozhen Liu, Yang Hammoud, Suhel Ponraj, Mahesh School of Engineering and Design Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Ministry of Education Tongji University China

ISBN: (纸本)9781612841816

Machine learning techniques have facilitated image retrieval by automatically classifying and annotating images with keywords. Among them Support Vector Machines (SVMs) are used extensively due to their generalization properties. However, SVM training is notably a computationally intensive process especially when the training dataset is large. This paper presents MRSVM, a distributed SVM algorithm for large scale image annotation which partitions the training data set into smaller subsets and train SVM in parallel using a cluster of computing nodes. MRSVM is evaluated in an experimental environment showing that the distributed SVM algorithm reduces the training time significantly while maintaining a high level of accuracy in classifications. © 2011 IEEE.

关键词： MapReduce

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Semantic based file retrieval on resource limited devices with ontology alignment support

Semantic based file retrieval on resource limited devices wi...

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Jan, Sadaqat Li, Maozhen Al-Sultany, Ghaidaa Al-Raweshidy, Hamed School of Engineering and Design Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Ministry of Education Tongji University China

ISBN: (纸本)9781612841816

In this paper, we present a file search mechanism that can utilize the ontology alignments to facilitate file retrieval on resource-limited devices by exploiting the knowledge of more than one ontologies. This enables the device users to take advantage of all ontologies, which might have been developed in the same domain. A semantic-based file retrieval framework was previously presented for resource-limited devices, which annotates files with its basic attributes and provides file retrieval capabilities. A generic ontology was developed to define the most commonly used keywords which can be used as metadata of the stored files. The ontology was employed to exploit the semantic based file retrieval capability. The search mechanism was evaluated by formulating two test cases. In first test case the framework make use of single ontology while in the second test case, the ontology alignments were utilized by aligning two ontologies. The implications of ontology alignment support were analyzed through probabilistic evaluation, which shows the progress in file retrieval efficiency. © 2011 IEEE.

关键词： Ontology

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Ontology alignment using Rough Sets

Ontology alignment using Rough Sets

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

ISBN: (纸本)9781612841816

Ontology alignment has been one of the most significant research issues to bridge the semantic gap between heterogeneous systems toward Semantic Web. Many proposed systems in recent years, use multiple similarity measures and variety of aggregating algorithms to map entities from two different ontologies. However, the real issue arises when alignment systems turn out to be uncertain about entities which are neither completely similar nor dissimilar. This paper presents an ontology alignment system which uses a combination of various similarity measures in order to map entities from two different ontologies. Rough Sets have been used to deal with uncertainties during the mapping process by defining the similarity measures as the attributes of entities. The proposed alignment system employs the combination of string based, linguistic based and structural matchers. The structural matcher compares the super-classes, sub-classes and properties of two class entities. We use WordNet to compare the linguistic similarity between entities in the mapping process. The performance of proposed system is evaluated in terms of precision and recall and compared with existing state of the art alignment systems. For this purpose, the Ontology Alignment Evaluation Initiative (OAEI) benchmark group-3 test ontologies have been used. Experimental tests show that the performance our proposed alignment system is comparable with existing alignment systems. © 2011 IEEE.

关键词： Ontology

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Performance evaluation of Latent Dirichlet Allocation in text mining

Performance evaluation of Latent Dirichlet Allocation in tex...

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Liu, Zelong Li, Maozhen Liu, Yang Ponraj, Mahesh School of Engineering and Design Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Ministry of Education Tongji University China

ISBN: (纸本)9781612841816

This paper introduces three classic models of statistical topic models: Latent Semantic Indexing (LSI), Probabilistic Latent Semantic Indexing (PLSI) and Latent Dirichlet Allocation (LDA). Then a method of text classification based on LDA model is briefly described, which uses LDA model as a text representation method. Each document means a probability distribution of fixed latent topic sets. Next, Support Vector Machine (SVM) is chose as classification algorithm. Finally, the evaluation parameters in classification system of LDA with SVM are higher than other two methods which are LSI with SVM and VSM with SVM, showing a better classification performance. © 2011 IEEE.

关键词： Support vector machines

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Intelligent mobile messaging

Intelligent mobile messaging

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2011 8th International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Al-Sultany, Ghaidaa Li, Maozhen Jan, Sadaqat Al-Raweshidy, Hamed School of Engineering and Design Brunel University Uxbridge Middlesex UB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Ministry of Education Tongji University China

ISBN: (纸本)9781612841816

Pervasive computing paradigm's goal is to visualize an ambient smart world via integration of devices into the users in their environment intelligently. Specifically, context aware computing is emerging as one of trails to achieve this paradigm in which services are seamlessly available at right time, right place and with right situation. This paper presents SOIM framework, which facilitates users to publish, annotate and retrieve service queries that are published to cloud. SOIM framework is built on semantic web technologies in support of query action retrieval automatically on low-end mobile devices. A generic ontology is developed which defines a number of keywords, and properties based on semantic reasoning. © 2011 IEEE.

关键词： Ontology

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