15964720
A Network Access Control Architecture Using State-Transfer-Based Dynamic Policy
The access control architecture using state-transfer-based dynamic policy is proposed to make access control more flexible and dynamic. This architecture can dynamically change the policy according to a state-transfer composed of a previous state and a current state. It can indicate the tendency of the system by using both previous and current information in order to decide a more appropriate policy to the current system and future condition. And there are two steps in this dynamic policy method, one is deciding a partial-state and the other one is deciding a state, two dynamic policy decision layers are included into this architecture in order to manage these two steps
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.
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
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.
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.
7606399
A fuzzy image metric with application to fractal coding
Image quality assessment is an important issue addressed in various image processing applications such as image/video compression and image reconstruction. The peak signal-to-noise ratio (PSNR) with the L(2)-metric is commonly used in objective image quality assessment. However, the measure does not agree very well with the human visual perception in many cases. A fuzzy image metric (FIM) is defined based on Sugeno's (1977) fuzzy integral. This new objective image metric, which is to some extent a proper evaluation from the viewpoint of the judgment procedure, is closely approximates the subjective mean opinion score (MOS) with a correlation coefficient of about 0.94, as compared to 0.82 obtained using the PSNR. Compared to the L(2)-metric, we demonstrate that a better performance can be achieved in fractal coding by using the proposed FIM.
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.
15935457
A Design of Data Rebuilding for Decision Support in E-Government System
The E-Government System is composed of three networks and one database. The business network within government offices (the Internal Net), the resource network in central and local administrations and departments (the External Net), the public information network (PIN) relying on the Internet. It is necessary to rebuild data in the three networks of the system in order to construct an effective electronic information database. In data rebuilding, a data exchange platform is set up to enable data sharing between the three networks. The data exchange platform is implemented in a structure that combines the intelligent decision support system (IDSS) and data warehouse (DW).
10184304
A New Rapid and Effective Chemistry Space Filter in Recognizing a Druglike Database
To develop a new chemistry space filter with high efficiency and accuracy, an analysis on distributions of as many as 50 structural and physicochemical properties was carried out on both druglike and nondruglike databases, viz. MACCS-II Drug Data Report (MDDR), Comprehensive Medicinal Chemistry (CMC), and Available Chemicals Directory (ACD). Based on the analysis results, a chemistry space filter was developed that can effectively discriminate a druglike database from a nondruglike database. The filter is composed of two descriptors: one is a molecular saturation related descriptor, and the other is associated with the proportion of heteroatoms in a molecule. Both are molecular size independent. Therefore, the profiles of a druglike database could be characterized as proper molecular saturation and proper percentage of heteroatoms, revealing direct indices for designing and optimizing combinatorial libraries. The application of the new filter on the Chinese Natural Product Database (CNPD) suggested that CNPD is, as expected, a potential druglike database, testifying that the new filter is reliable. Therefore, this newly developed chemistry space filter should be a potent tool for identifying druglike molecules, thus, it would have potential applications in the research of combinatorial library design and virtual high throughput screening using computational approaches for drug discovery.
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.