34310397
Predictive Queries Algorithm Based on Probability Model over Data Streams
Mining the evolving trends of an online data stream and forecasting the data values in the future can provide important support for the decision-making in many time-sensitive applications. This paper models an online data stream as a continuous state transitions process by mapping the possibly infinite stream data into finite states, and uses state transition disGraph (STG) to maintain the track of the state transactions. By studying the statistic information of the history state transitions, the future values can be predicted based on the theory of Markov chain. Extensive simulation experiments are conducted and show that the predictive performance of our method is preferable to that of the existing analogous algorithms.
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.
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
8051159
A Web-based Framework For On-line Collaborative Learning
This paper presents a framework for design of online courses and collaborative learning based on Web technologies. It provides the following features: construction of structured learning materials in a distributed environment; personalization of course contents in the run-time that adapts to the progress of individual students; it can supply relevant Web resources to the students by analyzing the learning history dynamically; students in a group could exchange their learning experiences and discover relevant knowledge via the communication channels provided by the framework. The proposed techniques could be deployed to a variety of online computer-assisted modules to improve the effectiveness of Web-based e-learning
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.
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.
14562695
An Architecture for Automated Driving in Urban Environments
This paper presents a novel navigation architecture for automated car-like vehicles in urban environments. Motion safety is a critical issue in such environments given that they are partially known and highly dynamic with moving objects (other vehicles, pedestrians...). The main feature of the navigation architecture proposed is its ability to make safe motion decisions in real-time, thus taking into account the harsh constraints imposed by the type of environments considered. The architecture is based upon an efficient publish/subscribe middleware system that allows modularity in design and the easy integration of the key functional components required for autonomous navigation, namely perception, localisation, mapping, real-time motion planning and motion tracking. After an overall presentation of the architecture and its main modules, the paper focuses on the “motion” components of the architecture. Experimental results carried out on a simulated Cycab vehicle are presented.
3708864
A New Systolic Architecture for Modular Division
A new systolic architecture for modular division is proposed in this paper. The architecture is based on a new hardware algorithm for modular division that is extended from the plus-minus algorithm for the greatest common divisor computation. Both the area complexity and the time complexity of the new architecture are linear with respect to the operand bit length. Compared to the architecture using a redundant number representation proposed by Kaihara and Takagi, the new architecture allows a doubled throughput due primarily to the greatly reduced critical path delay, while the area is only about 20 percent larger. Moreover, it is shown that, with a small addition to the control logic, the architecture can also be used to perform Montgomery modular multiplication, thereby efficiently realizing a unified modular multiplier/divider
120992950
A mathematical model for bifurcations in a Belousov-Zhabotinsky reaction
Abstract In our investigation we find that there are three stages during the whole lifespan of a Belousov–Zhabotinsky (BZ) system with 1,4-cyclohexanedione (CHD) and ferroin: transitional period (TP), induction period (IP), and main period (MP). When the system goes from the TP to the IP, there is a bifurcation from monostability (orange steady-state) to bistability (both orange and blue steady-states). When the system shifts from the IP to the MP, a different bifurcation occurs from the bistability back to the monostability (orange steady-state). A reduction step before the second bifurcation propagates slower than oxidation steps and pulses during the whole lifespan of the medium. This sharp difference of propagation speed has not been observed in other BZ systems, and cannot be interpreted by the prototype Oregonator model. We construct here an Oregonator-type model that simulates the two bifurcations and the propagation speed difference of the two kinds of step before the second bifurcation. Furthermore, our model demonstrates other bifurcations that are not observable in experiment. Our discovery not only unfolds a new aspect of the well-studied BZ reaction, but also leads to a new demand for further understanding of a reaction–diffusion equation system as the corresponding ordinary differential equation system bifurcates.
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.
26667538
Research on Service Management Data Modeling Based on SID
In order to resolve problems related to information integration in service management system (SMS), this paper introduces Meta Object Facility (MOF) into SMS to propose the concept of universal metamodel in service management domain. And then, Service Management Data Model (SMDM) is established to complete instantiation of metamodel by studying Share Information /Data (SID) Model. In this methodology, firstly, universal metamodel is established to ensure data sharing and reuse in SMS. Secondly, based on analysis of all kinds of information and process in SMS, core classes are defined to instantiate metadata classes and guarantee extendibility of SMDM. Each operational process can establish corresponding data model by definition of sub-class inheriting core class. Finally, data model of service quality monitoring is established to validate modeling methodology's validity. Therefore, consistency between SMDM and functional requirements is achieved and extension of business entities in SID is realized.