19886214
Robust and Adaptive Backstepping Control for Nonlinear Systems Using Fuzzy Logic Systems
In this note, a robust adaptive tracking control problem is discussed for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. A unified and systematic procedure is developed to derive a novel robust adaptive fuzzy controller. Compared with most results reported in the literature, the proposed control algorithm has several advantages: 1) the controller singularity problem is avoided perfectly; 2) the online computation burden is kept to minimum; 3) exponential tracking to the reference trajectory up to an ultimately bounded error is achieved; 4) the controllers are particularly suitable for parallel processing and hardware implementation.
5747087
Efficient Processing of Warping Time Series Join of Motion Capture Data
Discovering non-trivial matching subsequences from two time series is very useful in synthesizing novel time series. This can be applied to applications such as motion synthesis where smooth and natural motion sequences are often required to be generated from existing motion sequences. We first address this problem by defining it as a problem of l-e-join over two time series. Given two time series, the goal of l-e-join is to find those non-trivial matching subsequences by detecting maximal l-connections from the e-matching matrix of the two time series. Given a querying motion sequence, the l-e-join can be applied to retrieve all connectable motion sequences from a database of motion sequences. To support efficient l-e-join of time series, we propose a two-step filter-and-refine algorithm, called Warping Time Series Join (WTSJ) algorithm. The filtering step serves to prune those sparse regions of the e-matching matrix where there are no maximal l-connections without incurring costly computation. The refinement step serves to detect closed l-connections within regions that cannot be pruned by the filtering step. To speed up the computation of e-matching matrix, we propose a block-based time series summarization method, based on which the block-wise e-matching matrix is first computed. Lots of pairwise distance computation of elements can then be avoided by applying the filtering algorithm on the block-wise e-matching matrix.Extensive experiments on l-e-join of motion capture sequences are conducted. The results confirm the efficiency and effectiveness of our proposed algorithm in processing l-e-join of motion capture time series.
1107258
Improving image clustering: An unsupervised feature weight learning framework
We address the problem of feature weight learning for image clustering. In practice, before clustering data, we generally normalize all data features between 0 and 1, because we cannot determine which features are more important. In this paper, we provide a feature weight learning framework for clustering which can obtain the feature weights and cluster labels simultaneously. An alternative optimization algorithm is adopted to solve this problem. Empirical studies on the toy data and real image data demonstrate our algorithm's effectiveness in improving the clustering performance.
8340253
UGE4B: An Universal Grid Environment for Bioinformatics Research
Recent years, grid technology has been used widely in the fields of scientific research. In this paper, we present a universal grid environment for bioinformatics research (UGE4B). Although there have been several similar projects successfully constructed in the world, we need to meet some unique requirements from bioinformatics research in China. UGE4B consists of 6 components, including portal, task management, data management, information server, security and computing node. As a national-wide bioinformatics research platform, UGE4B is built through interconnecting multiple sub grids provided by each bioinformatics institutes. Besides provides a universal portal to end users for bioinformatics computing and data accessing, UGE4B also supported some special bioinformatics applications
26669443
Bottom-up discovery of frequent rooted unordered subtrees
In the past decade, XML has emerged as the standard language for information exchanging over the Internet. Due to its tree-structure paradigm, XML is superior for its capability of storing, querying, and manipulating complex data. Therefore, discovering frequent tree patterns over tree-structured data has become an interesting topic for XML data management. In this paper, we propose a tree mining algorithm, named BUXMiner, for finding a special class of frequent trees, called rooted unordered trees, from a tree-structured database. BUXMiner employs an efficient bottom-up approach to enumerate all candidate trees over a compact global tree guide and computes the frequent trees based on the tree guide. In addition to BUXMiner, we also propose a mining approach called BUMXMiner to discover the maximal frequent rooted unordered trees. We compare BUXMiner with previous tree-structure mining algorithms, namely XQPMinerTID and FastXMiner, which were also proposed to discover rooted unordered trees. The experimental results show that our algorithm outperforms XQPMinerTID and FastXMiner in terms of efficiency. The performance results from real-world applications also indicate the usefulness of our proposed tree mining algorithms in a variety of web applications, such as analysis of web page access patterns and mining frequent XML query patterns for caching.
116588251
On-line evolutionary exponential family mixture
This paper deals with evolutionary clustering, which refers to the problem of clustering data with distribution drifting along time. Starting from a density estimation view to clustering problems, we propose two general on-line frameworks. In the first framework, i.e., historical data dependent (HDD), current model distribution is designed to approximate both current and historical data distributions. In the second framework, i.e., historical model dependent (HMD), current model distribution is designed to approximate both current data distribution and historical model distribution. Both frameworks are based on the general exponential family mixture (EFM) model. As a result, all conventional clustering algorithms based on EFMs can be extended to evolutionary setting under the two frameworks. Empirical results validate the two frameworks.
13922126
Scene Simulation Platform Based on Data Fusion of Multiple Format 3D Models
Scene simulation technology has been the basal component for building 3D simulation application now. Constructing a general scene simulation platform based on multiple format 3D models can greatly speed developing process of simulation application and promote developing efficiency. According to the idea above, a method of building scene simulation platform based on models data fusion is put forward. With this method, multiple 3D model data format such as FLT, 3DS, X, WRL and GLS are fused and driven by OpenGL API. The layered structure and framework based on HLA are also presented to design the platform. Key technologies involving model data fusion and simulation driving are detailed. Finally, challenges associating with realization of the platform named plug-in framework and simulation examples based on the platform are brought forward. It shows greatest traits on building similar large-scale simulation application system.
25276326
Web-Based Service Management of Distributed Learning
This paper tries to design structure of Web-Based Service Management of Distributed Learning (WSMDL). The structure integrating IT service and Educational Auxiliary System service flow. Help desk becomes only interface for all levels of users according to their individual demands. Though analysis of service events and user’s feedback in service flow, it also provides the decision-making to improve the quality of Web-based Service Management of Distributed Learning Service Management. The paper also depicts the functions of WSMDL.
14149219
Multi-agent coordination: a fuzzy logic based approach
In the past decade, the multiagent systems have appeared as a new promising software paradigm. However, its succesful application is subject to the adoption of effective agent coordination techniques. In this paper, we consider a fuzzy logic based approach to agent coordination. Specifically, a bidding based coordination strategy has been proposed to manage the inter-relations among agents. The strategy is developed under the fuzzy logic based task structure model (FSTS) we proposed. Through using the strategy, agents can effectively coordinate their behaviors without consuming so much communication and computation resources.
14934044
ANSYS-Based Dynamic Analysis of High-Speed Motorized Spindle
In the paper, the characteristics of mode and harmonic response of the axis of the high-speed motorized spindle are presented with the FEM (Finite Element Method). A dual-dimension model with the FEM is developed and simulated using ANSYS commercial software. The result shows that the rated rotating speed of the high-speed motorized spindle is far smaller than the first-order natural resonance speed, and the dynamic displacement and stiffness do not change significantly compared with the static performance of working of the motorized spindle. The dynamic characteristics of the motorized spindle are accord with the requirements of design.
38698913
A unified fault model and test generation procedure for interconnect opens and bridges
A unified gate-level fault model for interconnect opens and bridges is proposed. Defects are modeled as constrained multiple line stuck-at faults. A novel feature of the proposed fault model is its flexibility to accommodate increasing levels of accuracy. Additionally the model does not require accurate device level circuit models to achieve desired accuracy. Efficient methods for fault simulation and test generation are discussed and experimental results on benchmark circuits and industrial designs are presented. The experimental results presented show that the tests generated using simpler versions of the proposed fault model achieve higher defect coverage than the tests using two currently popular methods to derive high defect coverage tests.