17284590
Performance Analysis of the HLLACF
With the popular using of anonymous communication systems, security and overhead traffic attract more attention. HLLCAF was presented to improve the performance of anonymous communication systems. This paper analyzes HLLACF's security and an evaluation algorithm for security is presented. In the end, a simulation experiment and result analysis is given. The theoretic analysis and simulation experiment indicate that the HLLACF can prevent AS-Level passive attack and other similar attacks well while decreasing communication delay and HLLACF also scales well.
8185718
ASG Automated Signature Generation for Worm-Like P2P Traffic Patterns
Many P2P software have the similar communication patterns with computer worms, thus they will bring in false positives for behaviour based worm detection. Up to now, little work is done on the research of the similarities between communication patterns of worm and P2P software as well as how to eliminate the worm-like P2P traffic. Based on the analysis of popular P2P software used nowadays and the host process information, this paper presents ASG, which is a novel host based algorithm to generate signatures for worm-like P2P communication patterns. The contribution of our work lies in three aspects: a) Analyzing communication pattern similarities between P2P traffic and worm traffic through examples. b) Designing one practical and simple signature format for worm-like P2P traffic based on the host process information, c) Presenting automated signature generation (ASG) method to extract the signature of worm-like P2P traffic. Experiments with the popular used P2P software show that ASG can effectively extract the signature and reduce the false positives.
14521064
ALHACF: An Anonymity-Level Selected Hierarchical Anonymous Communication Framework
With the more emphasis paid on network security and privacy, the research on anonymous communication system has developed quickly. In the past, researchers mainly focused on how to improve the anonymity, but few focused on the usability. This paper presents an anonymity-level selected hierarchical anonymous communication framework (ALHACF). In this framework, firstly the anonymity-level is selected by users according to his requirement, and then the path length and set of relay routers will be determined by the anonymity-level. The anonymity and communication performance of ALHACF are analyzed. The analysis indicates that ALHACF inherits the merit of HLLACF, and it can prevent some kinds of attack, keep good anonymity and increase the communication performance markedly.
18169252
Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis of ultrasound images
Region of interest (ROI) is a region used to extract features. In breast ultrasound (BUS) image, the ROI is a breast tumor region. Because of poor image quality (low SNR (signal/noise ratio), low contrast, blurry boundaries, etc.), it is difficult to segment the BUS image accurately and produce a ROI which precisely covers the tumor region. Due to the requirement of accurate ROI for feature extraction, fully automatic classification of BUS images becomes a difficult task. In this paper, a novel fully automatic classification method for BUS images is proposed which can be divided into two steps: ''ROI generation step'' and ''ROI classification step''. The ROI generation step focuses on finding a credible ROI instead of finding the precise tumor location. The ROI classification step employs a novel feature extraction and classification strategy. First, some points in the ROI are selected as the ''classification checkpoints'' which are evenly distributed in the ROI, and the local texture features around each classification checkpoint are extracted. For each ROI, all the classification checkpoints are classified. Finally, the class of the BUS image is determined by analyzing every classification checkpoint in the corresponding ROI. Both steps were implemented by utilizing a supervised texture classification approach. The experiments demonstrate that the proposed method is very robust to the segmentation of BUS images, and very effective and useful for classifying breast tumors.
39145518
Boundary Constrained Manifold Unfolding
14537451
Research on Architecture and Key Technology for Service-Oriented Workflow Performance Analysis
With the advent of SOA and Grid technology, the service has become the most important element of information systems. Because of the characteristic of service, the operation and performance management of workflow meet some new difficulties. Firstly a three-dimensional model of service is proposed. Then the characteristics of workflow in service-oriented environments are presented, based on which the workflow performance analysis architecture is described. As key technologies, workflow performance evaluation and analysis are discussed, including a multi-layer performance evaluation model and three kinds of performance analysis methods.
17455976
Support Vector Machines for Text Categorization in Chinese Question Classification
Question classification plays a crucial important role in the question answering system because categorizing a given question is beneficial to identify an answer in the documents. The goal of question classification is to accurately assign labels to question based on expected answer type. Recently, many machine learning algorithms are used for question classification. However many research results show that SVM perform best in this task, because it is well known to work well for nonlinear, sparse, high dimensional problems. In this experiment, we perform the One-against-One SVM algorithm and a feature extraction method of Chinese questions to get high classification accuracy
9720625
Discovery of functional miRNA-mRNA regulatory modules with computational methods
The identification of miRNAs and their target mRNAs and the construction of their regulatory networks may give new insights into biological procedures. This study proposes a computational method to discover the functional miRNA-mRNA regulatory modules (FMRMs), that is, groups of miRNAs and their target mRNAs that are believed to participate cooperatively in post-transcriptional gene regulation under specific conditions. The proposed method identifies negatively regulated patterns of miRNAs and mRNAs which associate with cancer and normal conditions, respectively, in a prostate cancer data set. GO and the literature also suggest that they may relate with prostate cancer. It can potentially identify the biologically relevant chains of 'miRNA-->target gene --> condition'.
7657998
MAC Performance and Improvement in Mobile Wireless Sensor Networks
Former Media Access Control (MAC) protocols for Wireless Sensor Networks (WSNs) are mainly for static networks. In the networks where mobile nodes exist, the performance will degrade greatly. In this paper the performance of MAC in mobile WSNs (mWSNs) is analyzed and improved algorithms are presented. Simulations validate the effects. A new MAC protocol also is presented for the scenario with more mobile nodes.