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作者： Dai, Min Hu, Su-Rui Qi, Jia Tianjin Key Lab of Intelligent Computing and Novel Software Technology School of Computer and Communication Engineering Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

Spike sorting is the essential step in analyzing recording spike signals for studying information processing mechanisms within the nervous system. Overlapping is one of the most serious problems in the spike sorting for multi-channel recordings. In this paper, a modified radial basis function (RBF) network is proposed to decompose the overlapping signals and separate spikes within the same RBF network. A modified radial basis function based on the Gaussian function is employed in the method to improve the accuracy of overlap decomposition. In addition, the improved constructing algorithm reduces the calculation cost by taking advantage of the symmetry of the RBF network. The performance of the presented method is tested at various signal-to-noise ratio levels based on simulated data coming from the University of Leicester and Wave-clus software. Experiment results show that our method successfully solves the fully overlapping problem and has higher accuracy comparing with the Gaussian function. © 2011 Elsevier Ltd. All rights reserved.

关键词： Radial basis function networks

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Study of hybrid strategy for ambulatory ECG waveform clustering

Journal of Software

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Journal of software 2011年第7期6卷 1257-1264页

作者： Zheng, Gang Yu, Tian Laboratory of Biological signal and Intelligent Processing Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China School of Computer and Communication Engineering Tianjin University of Technology Tianjin China Laboratory of Biological signal and Intelligent Processing Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

A hybrid strategy has been proposed to reduce the wrong clustering on Ambulatory ECG (electrocardiogram). Since Ambulatory ECG is usually composed by 24 hours data, the number of individual ECG waveform can reach to 100,000, the request for accurate clustering result is highly required. The proposed strategy adopted some intelligent algorithms to solve the above problem. It clusters ECG waveform sample (selected from Ambulatory ECG) synchronously by Max-Min distance clustering algorithm, K-means algorithm and Simulated annealing algorithm first. And then, it adopted all three outputs from the above three algorithms as input on Back Propagation Artificial Neural Network (BP ANN). In the end, we got more accurate clustering result from the output of ANN. For testing the results, data of MIT/BIH arrhythmia database were used for experiments. After the controlled trial on MIT/BIH data, it can be safely concluded that the clustering result achieved by improved strategy can got more accurate than that by the traditional clustering algorithm. An average accuracy ratio is about 94.6%, 1.6% higher than k-means algorithm averagely and 1.3% higher than Simulated Annealing algorithm averagely. © 2011 ACADEMY PUBLISHER.

关键词： Electrocardiograms

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intelligent financial warning model using Fuzzy Neural Network and case-based reasoning

Intelligent financial warning model using Fuzzy Neural Netwo...

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Proceedings of the IEEE/IAFE Computational Intelligence for Financial engineering (CIFEr)

作者： Vahid Behbood Jie Lu Decision Systems and e-Service Intelligence Laboratory Quantum Computing and Intelligent Systems Software School Faculty of Engineering and Information Technology Sydney University of Technology Broadway NSW Australia

Creating an applicable and precise financial early warning model is highly desirable for decision makers and regulators in the financial industry. Although Business Failure Prediction (BFP) especially banks has been extensively a researched area since late 1960s, the next critical step which is the decision making support scheme has been ignored. This paper presents a novel model for financial warning which combines a fuzzy inference system with the learning ability of neural network as a Fuzzy Neural Network (FNN) to predict organizational financial status and also applies reasoning capability of Fuzzy Case-Based Reasoning (FCBR) to support decision makers measuring appropriate solutions. The proposed financial warning model generates an adaptive fuzzy rule base to predict financial status of target case and then if it is predicted to fail, the FCBR is used to find similar survived cases. Finally according similar cases and a fuzzy rule base, the model provides financial decisions to change particular features as company goals in upcoming year to avoid future financial distress.

关键词： Fuzzy neural networks Predictive models Accuracy Computational modeling Artificial neural networks Cognition Companies

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Scaling-Up Item-Based Collaborative Filtering Recommendation Algorithm Based on Hadoop

Scaling-Up Item-Based Collaborative Filtering Recommendation...

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IEEE World Congress on Services (SERVICES)

作者： Jing Jiang Jie Lu Guangquan Zhang Guodong Long Decision Systems & E-Service Intelligence Research Laboratory Center of Quantum Computing and Intelligent System School of Software Faculty of Engineering and Information Technology Sydney University of Technology Sydney NSW Australia

Collaborative filtering (CF) techniques have achieved widespread success in E-commerce nowadays. The tremendous growth of the number of customers and products in recent years poses some key challenges for recommender systems in which high quality recommendations are required and more recommendations per second for millions of customers and products need to be performed. Thus, the improvement of scalability and efficiency of collaborative filtering (CF) algorithms become increasingly important and difficult. In this paper, we developed and implemented a scaling-up item-based collaborative filtering algorithm on MapReduce, by splitting the three most costly computations in the proposed algorithm into four Map-Reduce phases, each of which can be independently executed on different nodes in parallel. We also proposed efficient partition strategies not only to enable the parallel computation in each Map-Reduce phase but also to maximize data locality to minimize the communication cost. Experimental results effectively showed the good performance in scalability and efficiency of the item-based CF algorithm on a Hadoop cluster.

关键词： Scalability Prediction algorithms Algorithm design and analysis Collaboration Filtering Partitioning algorithms Clustering algorithms

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Long term bank failure prediction using Fuzzy Refinement-based Transductive Transfer learning

Long term bank failure prediction using Fuzzy Refinement-bas...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Vahid Behbood Jie Lu Guangquan Zhang Decision Systems & E-Service Intelligence Research Laboratory Centre of Qua ntum Computing and Intelligent System School of Software Faculty of Engineering and Information Technology University of Technology-Sydney Broadway NSW Australia

Machine learning algorithms, which have been considered as robust methods in different computational fields, assume that the training and test data are drawn from the same distribution. This assumption may be violated in many real world applications like bank failure prediction because training and test data may come from different time periods or domains. An efficient novel algorithm known as Fuzzy Refinement (FR) is proposed in this paper to solve this problem and improve the performance. The algorithm utilizes the fuzzy system and similarity concept to modify the instances' labels in target domain which was initially predicted by shift-unaware Fuzzy Neural Network (FNN) proposed by [1]. The experiments are performed using bank failure financial data of United States to evaluate the algorithm performance. The results address a significant improvement in the predictive accuracy of FNN due to applying the proposed algorithm.

关键词： Prediction algorithms Fuzzy neural networks Pragmatics Training Inference algorithms Accuracy Machine learning algorithms

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A Game Theoretic Model and Tree Analysis Method for Fair Exchange Protocols

A Game Theoretic Model and Tree Analysis Method for Fair Exc...

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Theoretical Aspects of software engineering (TASE)

作者： Guoqiang Li Yonggen Gu Xiuting Tao Jie Tao BASICS School of Software MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai China School of Information and Engineering HUzhou Teacher's College Zhejiang China College of Mathematics Physics and Information Engineering Zhejiang Normal University China

Exchange protocols are an important theoretic basis to make secure electronic commerce and electronic business transactions possible, in which the fairness is a crucial property. To ensure and verify the property, a specific model is proposed, based on the extensive game with imperfect information. Fairness is built in the protocol game and the corresponding game tree. To verify the property, a tree analysis method is offered, and a linear time algorithm is given. As a case study, some flaws of ASW protocol are found.

关键词： Protocols Games Computational modeling Game theory Educational institutions Analytical models Electronic commerce

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Polynomial-time hierarchy of computable reals

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Journal of Computational Information Systems 2011年第4期7卷 1108-1115页

作者： Chen, Qingliang Su, Kaile Wu, Lijun Department of Computer Science Jinan University Guangzhou 510632 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of High Confidence Software Technologies Ministry of Education Peking University Beijing China Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia School of Computer Science and Engineering University of Electronic Science and Technology Chengdu 610054 China

In mathematics, various representations of real numbers have been investigated and all these representations are proved to be mathematically equivalent. Furthermore, it is known that all effective versions of these representations lead to the same class of "computable real numbers". However, when subrecursive (such as primitive recursive) is taken into account, these representations can lead to different notions of "computable real numbers". This paper will look into the polynomial-time version of the problem for computable real numbers under different representations. We will summarize the known results to exhibit the comprehensive hierarchy they form. Our goal is to clarify systematically how the polynomial-time computability depends on the representations of the real numbers. Copyright © 2011 Binary Information Press.

关键词： Polynomial approximation

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No-go theorem for one-way quantum computing on naturally occurring two-level systems

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Physical Review A 2011年第5期83卷 050301(R)-050301(R)页

作者： Jianxin Chen Xie Chen Runyao Duan Zhengfeng Ji Bei Zeng Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts USA Centre for Quantum Computation and Intelligent Systems (QCIS) Faculty of Engineering and Information Technology University of Technology Sydney New South Wales Australia Perimeter Institute for Theoretical Physics Waterloo Ontario Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Institute for Quantum Computing and Department of Combinatorics and Optimization University of Waterloo Waterloo Ontario Canada

The ground states of some many-body quantum systems can serve as resource states for the one-way quantum computing model, achieving the full power of quantum computation. Such resource states are found, for example, in spin-52 and spin-32 systems. It is, of course, desirable to have a natural resource state in a spin-12, that is, qubit system. Here, we give a negative answer to this question for frustration-free systems with two-body interactions. In fact, it is shown to be impossible for any genuinely entangled qubit state to be a nondegenerate ground state of any two-body frustration-free Hamiltonian. What is more, we also prove that every spin-12 frustration-free Hamiltonian with two-body interaction always has a ground state that is a product of single- or two-qubit states. In other words, there cannot be any interesting entanglement features in the ground state of such a qubit Hamiltonian.

关键词： Ground state

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Efficient SLCA computing service for XML filtering in IaaS

Efficient SLCA computing service for XML filtering in IaaS

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12th International Asia Pacific Web Conference, APWeb 2010

作者： Zhang, Chenjing Wang, Xiaoling Zhou, Aoying Shanghai Key Laboratory of Intelligent Information Fudan University China College of Information Technology Shanghai Ocean University China Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University China

ISBN: (纸本)9780769540122

Cloud provides dynamically computing services for large scales of data over the Internet. IaaS(information as a service) is one of utilities to provide information service in Cloud computing. Large scales of XML data are produced continually in Internet. Efficient information filtering services are needed. Previous XML filter approaches aim at XPath queries. However, many users tend to use keywords to describe requirements. SLCA (Smallest Lowest Common Ancestor)-based XML keyword search is one of the most important information retrieval approaches. Former approaches focus on building centralized index for a large scale of XML document collection and can't process continuous XML streams. This paper addresses SLCA computing service for continuous XML document. A novel SLCA computing service is designed, where SLCAs are obtained in one scan of XML stream. We demonstrate the efficiency of our algorithms analytically and experimentally. © 2010 IEEE.

关键词： XML

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Semantic approach for service oriented requirements modeling

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作者： Zhao, Bin Cai, Guang-Jun Jin, Zhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University of the Chinese Academy of Sciences Beijing China Software Engineering Institute Peking University Beijing China

ISBN: (纸本)3642163262

Services computing is an interdisciplinary subject that devotes to bridging the gap between business services and IT services. It is recognized that Requirements engineering is fundamental in implementing the service oriented architecture. It takes traditional RE techniques great efforts to model business requirements and search for the appropriate services. In this paper, we propose an ontological approach to facilitate the service-oriented modeling framework. The general idea is to establishing a common semantic language to describe both the business requirements and services capabilities based on their effects on the environment. After that, we used a case study to illustrate this method and showed that substantial efforts can be spared to construct a service model from business requirements. © 2010 IFIP.

关键词： Ontology

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