Network security situational awareness (NSSA) technology as a new research area in network security plays an important role in changing network security defense model from passive type to active. In order to enhance t...
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Network security situational awareness (NSSA) technology as a new research area in network security plays an important role in changing network security defense model from passive type to active. In order to enhance the capability of perceiving status the network stays in and emergency responding capability, it is especially important to design an index system for large scale NSSA and a situation assessment algorithm. This paper extends the existing hierarchical evaluation method and introduces a new network security assessment algorithm with a high adaptability based on other researchers' work.
Numerical simulations running on very large High Performance Computer clusters still suffer from the I/O bottleneck. The cost of communication can overwhelm the cost of computation, and scales inversely with the numbe...
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Numerical simulations running on very large High Performance Computer clusters still suffer from the I/O bottleneck. The cost of communication can overwhelm the cost of computation, and scales inversely with the number of processors used in the cluster. In previous work we have developed a multiresolution data model to help improve performance for visualizations of very large multi dimensional scientific data sets. In our approach, the data is represented as a multi level hierarchy. Reconstructive error analysis is used to identify regions in the data where the data loss is greatest. We have incorporated this data model into the OpenGGCM solar wind simulation environment. In this paper, we demonstrate that this approach can reduce the I/O and improve the overall performance of a large numerical simulation environment.
In this paper we present two novel multivariate time series representations to classify physiological data of different lengths. The representations may be applied to any group of multivariate time series data that ex...
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In this paper we present two novel multivariate time series representations to classify physiological data of different lengths. The representations may be applied to any group of multivariate time series data that examine the state or health of an entity. Multivariate Bag-of-Patterns and Stacked Bags of-Patterns improve on their univariate counterpart, inspired by the bag-of-words model, by using multiple time series and analyzing the data in a multivariate fashion. We also borrow techniques from the natural language processing domain such as term frequency and inverse document frequency to improve classification accuracy. We introduce a technique named inverse frequency and present experimental results on classifying patients who have experienced acute episodes of hypotension.
The cyber situational awareness of an organization determines its effectiveness in responding to attacks. Mission success is highly dependent on the availability and correct operation of complex computer networks, whi...
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The cyber situational awareness of an organization determines its effectiveness in responding to attacks. Mission success is highly dependent on the availability and correct operation of complex computer networks, which are vulnerable to various types of attacks. Today, situational awareness capabilities are limited in many ways, such as inaccurate and incomplete vulnerability analysis, failure to adapt to evolving networks and attacks, inability to transform raw data into cyber intelligence, and inability for handling uncertainty. We describe advanced capabilities for mission-centric cyber situational awareness, based on defense in depth, provided by the Cauldron tool. Cauldron automatically maps all paths of vulnerability through networks, by correlating, aggregating, normalizing, and fusing data from a variety of sources. It provides sophisticated visualization of attack paths, with automatically generated mitigation recommendations. Flexible modeling supports multi-step analysis of firewall rules as well as host-to-host vulnerability, with attack vectors inside the network as well as from the outside. We describe alert correlation based on Caldron attack graphs, along with analysis of mission impact from attacks.
In the context of the MAgAdI environment, this paper presents SIgMa, a teacher oriented tool, and SIgBLE, its general framework basis. SIgMa's general aims are to automatically detect visible signs of failure or s...
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In the context of the MAgAdI environment, this paper presents SIgMa, a teacher oriented tool, and SIgBLE, its general framework basis. SIgMa's general aims are to automatically detect visible signs of failure or success among data coming from interactions happened on blended learning environments, and to provide relevant feedback adapted to teachers. First, we introduce SIgBLE and the interface of the SIgMa prototype. A usability test of the current prototype is also presented.
In this paper, we have studied the feature analysis of different kinds of in High-resolution SAR satellite images based on SURF theory. This method has been applied on Cosmo-SkyMed images of 3-m resolution. The perfor...
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In this paper, we have studied the feature analysis of different kinds of in High-resolution SAR satellite images based on SURF theory. This method has been applied on Cosmo-SkyMed images of 3-m resolution. The performances of the algorithm have been validated by AIS data and in-situ data. The whole classification accuracy is above 80%.
As the traditional image segmentation methods can not show the location targets of object clearly and accurately. The paper base on statistical analysis and 3D region growing segmentation method of the liver. First of...
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ISBN:
(纸本)9781424488094
As the traditional image segmentation methods can not show the location targets of object clearly and accurately. The paper base on statistical analysis and 3D region growing segmentation method of the liver. First of all, the original abdominal volume data base on thresholding segmentation algorithm which is based on statistical analysis to achieve pretreatmcnt;Secondly, the volume data after pretreatment base on volume rendering which base on RC algorithm to achieve three-dimensional visualization of abdominal CT images;Then, based on 3D region growing algorithm for three-dimensional abdominal images of liver segmentation. Through the design of the liver segmentation experiment from abdominal CT images to validate the effectiveness of the method of paper.
This paper completes the design and realization of software for a visibility measurement system based on WSN. The software of the lower machine is designed on CC2430 development platform with development environment I...
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ISBN:
(纸本)9781424494361
This paper completes the design and realization of software for a visibility measurement system based on WSN. The software of the lower machine is designed on CC2430 development platform with development environment IAR as support. And the computer intelligent monitor software is developed by programming tool Visual C++ 6.0, and based on Windows 98 operating system. Software testing shows that this system has higher precision in visibility detection, which can realize the visibility of data transmission, display and analysis.
Execution traces generated from running high performance computing applications (HPC) may reach tens or hundreds of gigabytes. The trace data can be used for visualization, analysis of profiling information about the ...
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Execution traces generated from running high performance computing applications (HPC) may reach tens or hundreds of gigabytes. The trace data can be used for visualization, analysis of profiling information about the target system. However, in order to make the utilization of this data efficient, the trace needs to be represented in a structure that facilitates the access to its data. One important factor that should be considered when representing trace data is scalability; the trace met model should be able to represent the trace in a compact form that enables scalability of the analysis tools. Additionally, a trace file needs to be available in a format that is well-known in the software engineering area by making it open. In this paper, we propose a metamodel for representing dynamic information generated from HPC that use the MPI standard as the inter-process communication model. MPI Trace Format (MTF) is meant to meet the aforementioned requirements and is intended to facilitate the interoperability among different trace analysis tools.
In CSCL research, the collaborative process is of central importance. Thus, this paper aims to unveil learners' interaction patterns through analyzing context of questions in discussion transcript. Based on assump...
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In CSCL research, the collaborative process is of central importance. Thus, this paper aims to unveil learners' interaction patterns through analyzing context of questions in discussion transcript. Based on assumptions on data source and users' operating process of analyzing questions' context, several design principles have been identified. Guided by these principles, a technical solution is presented to implement a tool for analyzing context of questions. By incorporating text classification and information visualization technologies, the tool supports content and structure analysis of discussion transcripts to generate visual patterns in a form of 5W1H context of questioning. In this way, the tool enables users to understand interaction patterns in an intuitive and friendly manner. A case study is also conducted to validate the effectiveness of the tool.
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