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Intelligent mobile messaging

Intelligent mobile messaging

引用

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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Performance evaluation of Latent Dirichlet Allocation in text mining

Performance evaluation of Latent Dirichlet Allocation in tex...

引用

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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A distributed SVM for scalable image annotation

A distributed SVM for scalable image annotation

引用

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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Load balancing in MapReduce environments for data intensive applications

Load balancing in MapReduce environments for data intensive ...

引用

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, Yang Li, Maozhen Alham, Nasullah Khalid 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

The distributed computations are widely used in the modern world for processing large scale jobs. Hadoop framework which is based on Google MapReduce model becomes popular due to its great processing power and ease to use. However, due to lack of load management, especially in a heterogeneous computing environment, the performance of Hadoop framework may be deteriorated. Therefore this paper presents a load balancing algorithm which aims to balance the load among heterogeneous nodes. And also, the Hadoop simulator HSim is involved to evaluate the performance of the load balancing algorithm. The results indicate that the performance of the cluster has been significantly enhanced. © 2011 IEEE.

关键词： MapReduce

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Ontology based file retrieval framework for resource limited mobile devices

Ontology based file retrieval framework for resource limited...

引用

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

Recent advances in mobile technologies have emerged new challenges for researchers. File management and retrieval on resource-limited devices has become a challenging problem as these devices are now equipped with larger storage capacities. This paper presents an overview about the possibilities of implementing Semantic Web Technologies in order to facilitate the file retrieval on resource-limited devices. We have proposed a semantic based file retrieval framework which utilizes a generic ontology in file search process. The search module is implemented in Java ME platforms as a case study. Performance of the proposed search module is evaluated through experimental tests along with probabilistic evaluations. The implemented module not only automates file retrieval process but also shows significant improvement in file retrieval efficiency by utilizing the knowledge of employed ontology in the search module. © 2011 IEEE.

关键词： Ontology

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Multi-label Learning for Protein Subcellular Location Prediction

Multi-label Learning for Protein Subcellular Location Predic...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiao Wang Guo-Zheng Li Jia-Ming Liu Rui-Wei Zhao The Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Control Science and Engineering Tongji University Shanghai China

Protein subcellular localization aims at predicting the location of a protein within a cell using computational methods. Knowledge of subcellular localization of proteins indicates protein functions and helps in identifying drug targets. Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. To better reflect the characteristics of multiplex proteins, we formulate prediction of subcellular localization of multiplex proteins as a multi-label learning problem. We present and compare two multi-label learning approaches, which exploit correlations between labels and leverage label-specific features, respectively, to induce a high quality prediction model. Experimental results on six protein data sets under various organisms show that our described methods achieve significantly higher performance than any of the existing methods. Among the different multi-label learning methods, we find that methods exploiting label correlations performs better than those leveraging label-specific features.

关键词： Proteins Correlation Protein engineering Multiplexing Machine learning Humans Learning systems

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A New MPI Parallel computing Environment Based on Fibre-channel Token-Routing Network for Materials Simulation Research

A New MPI Parallel Computing Environment Based on Fibre-chan...

引用

2011 International Conference on Advanced Materials in Microwaves and Optics（AMMO 2011）

作者： Xiaohui ZENG Dongsheng LIU Wenlang LUO Lixin FU school of Electronics and Information Engineering Jinggangshan University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

In order to apply our high efficiency fibre-channel token-routing network(shortened as FC-TR network) to the field of materials simulation research, a new MPI parallel computing environment is proposed and designed, and independently developed a parallel programming environment FC-TR-MPI based on FC-TR network. In FC-TR-MPI, a new method was applied to point-to-point communication that the network communications between processes in the same computing node were changed into memory operations;moreover, according to the underlying software and hardware features of FC-TR network, new algorithms were proposed to optimize the communication performance of some collective communications. Experimental results show that, compared with Sca MPI parallel programming environment, FC-TR-MPI has a higher parallel efficiency and speedup.

关键词： MPI,parallel computing environment,fibre-channel,materials simulation

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Designing and Analysis of a New Book-Lending system Based on Logic Petri Nets

Designing and Analysis of a New Book-Lending System Based on...

引用

International Conference on Electric Information and Control Engineering

作者： Xia Jiang WenJing Luan Department of Computer Laiwu Vocational and Technical College The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University

A new book-lending system is designed and analyzed based on logic Petri nets in this paper. The batch processing function and indeterminacy of readers are included in the system. Its logic Petri net model is establish... 详细信息

ISBN: (纸本)9781424480364

关键词： Book-lending system Batch processing Designing Verification Logic Petri net

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Research on a Remote Network Monitoring Model for Large-scale Materials Manufacturing

Research on a Remote Network Monitoring Model for Large-scal...

引用

2011 International Conference on Advanced Materials and Computer Science(ICAMCS 2011)

作者： Xiaohui ZENG Manhua LI Wenlang LUO Department of Computer Science and Technology Jinggangshan University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

A remote network monitoring model for large-scale materials manufacturing is proposed, including five modules: center control module, data collection and fault alarm module, graph drawing module and data storage module. The center control module not only interacts with users, but also controls the other four modules to work together in harmony. According to this monitoring model, a remote network monitoring platform is designed and realized. The user can interact with the control center module through an Internet browser, and the information about the monitored manufacturing machines and devices can be displayed by means of text, chart, graphic and sound, etc. Moreover, the details about the problems or faults from the monitored objects can be obtained in time. The experimental results indicate that the network monitoring platform can accurately get the information of the monitored objects, and users can conveniently get the online running state of those monitored objects.

关键词： remote network monitoring data storage fault alarm materials manufacturing

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SelectCast: Scalable data aggregation scheme in wireless sensor networks

SelectCast: Scalable data aggregation scheme in wireless sen...

引用

IEEE INFOCOM 2011

作者： Wang, Cheng Tang, Shaojie Li, Xiang-Yang Jiang, Changjun Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States TNLIST School of Software Tsinghua University China

ISBN: (纸本)9781424499212

In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density λ ∈ [1, n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called single-hop-length (SLH) scheme and multiple-hop-length (MLH) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MLH scheme, for a practically important set of symmetric functions called perfectly compressible functions, including the mean, max, or various kinds of indicator functions, etc., the data from Θ(n) sensors can be aggregated to the sink at the throughput of a constant order Θ(1), implying that our MLH scheme is indeed scalable. © 2011 IEEE.

关键词： Efficiency

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