基于混合模式匹配算法的网络入侵检测

为了提升中央处理单元(CPU)和图形处理单元(GPU)协同检测网络入侵的性能,本文提出了一种具有数据包有效载荷长度约束的CPU/GPU混合模式匹配算法(LHPMA)。在分析CPU/GPU混合模式匹配算法(HPMA)的基础上,设计了长度约束分离算法(LBSA)对传入数据包进行提前分类。利用CPU中的预过滤缓冲区对较长数据包进行快速预过滤,结合全匹配缓冲区将较短数据包直接分配给GPU进行全模式匹配,通过减少有效载荷长度的多样性,提升了CPU/GPU协同检测网络入侵的性能。实验结果表明,LHPMA增强了HPMA的处理性能,充分发挥了GPU并行处理较短数据包的优势,并且LHPMA提高了网络入侵检测的吞吐量。     

Hypermatrix scheme for finite element systems on CDC STAR-100 computer

A study is made of the adaptation of the hypermatrix (block matrix) scheme for solving large systems of finite element equations to the CDC STAR-100 computer. Discussion is focused on the organization of the hypermatrix computation using Cholesky decomposition and the mode of storage of the different submatrices to take advantage of the STAR pipeline (streaming) capability. Consideration is also given to the associated data handling problems and the means of balancing the I/O and cpu times in the solution process. Numerical examples are presented showing anticipated gain in cpu speed over the CDC 6600 to be obtained by using the proposed algorithms on the STAR computer.     

Biogeography-based optimisation with chaos

The biogeography-based optimisation (BBO) algorithm is a novel evolutionary algorithm inspired by biogeography. Similarly, to other evolutionary algorithms, entrapment in local optima and slow convergence speed are two probable problems it encounters in solving challenging real problems. Due to the novelty of this algorithm, however, there is little in the literature regarding alleviating these two problems. Chaotic maps are one of the best methods to improve the performance of evolutionary algorithms in terms of both local optima avoidance and convergence speed. In this study, we utilise ten chaotic maps to enhance the performance of the BBO algorithm. The chaotic maps are employed to define selection, emigration, and mutation probabilities. The proposed chaotic BBO algorithms are benchmarked on ten test functions. The results demonstrate that the chaotic maps (especially Gauss/mouse map) are able to significantly boost the performance of BBO. In addition, the results show that the combination of chaotic selection and emigration operators results in the highest performance.     

Using ASCII text files in post-fix notation (reverse Polish) to define mathematical models and systems of differential equations for simulation and non-linear regression

We discuss current methods for supplying equations in ASCII text form to executables for simulation or fitting, then we define a technique using stack notation that has many advantages over traditional approaches to this problem. Simulations are described to compare the cpu time consumed for function evaluation when the models are supplied as object code in dynamic-link libraries, and when they are supplied as ASCII text files in post-fix notation, otherwise known as last-in-first-out or reverse Polish. It is concluded that this new method is extremely convenient; it can be easily extended to include loops for numerical integration, special function evaluation or root finding; it can be optimized by the user for execution speed; and the cpu overhead when the models are involved in regression are minimal.     

Generation and entanglement of multi-dimensional multi-mode coherent fields in cavity QED

We introduce generalized multi-mode superposition of multi-dimensional coherent field states and propose a generation scheme of such states in a cavity QED scenario. An appropriate encoding of information on these states is employed, which maps the states to the Hilbert space of some multi-qudit states. The entanglement of these states is characterized based on such proper encodings. A detailed study of entanglement in general multi-qudit coherent states is presented, and in addition to establishing some explicit expressions for quantifying entanglement of such systems, several important features of entanglement in these system states are exposed. Furthermore, the effects of both cavity decay and channel noise on these system states are studied and their properties are illustrated.     

Measuring 3D crosstalk uniformity and its influence on contrast ratio

An array detector was employed to characterize the crosstalk and contrast ratio uniformity of three‐dimensional (3D) displays. The measurement method is described and demonstrated on a stereoscopic display with passive glasses. The resulting high resolution spatial uniformity maps enable a comprehensive statistical characterization of the display and provide a useful visual assessment tool. The statistical uniformity data are used to evaluate the crosstalk dependence on viewing conditions (such as viewing distance), and show the degradation in display performance that could not be captured with a discrete spot measurement. The measurement method was also employed to examine the influence of crosstalk on contrast ratio. It is shown that for some 3D displays, the crosstalk uniformity can dominate the perceived contrast. A metric is proposed that defines the maximal crosstalk contribution to the perceived contrast for 3D images with small features. The summary parameters extracted from the uniformity maps can be utilized to define the boundary viewing conditions needed to maintain minimum image quality.     

Teaching new tricks to an old map

Geographic Information Systems (GISs) and digital maps are increasingly available to the computer-using humanities scholar. As a result, questions of data availability and validity are the more crucial. Digital maps may be stored in different formats, both as regards coordinate systems in use and the level of sophistication available for storing geographical information related to the maps. The maps themselves are often under copyright by a national survey agency and the situation in Norway is outlined. Historical sources may often contain geographic references to administrative units that are no longer valid. An example is taken from the University Museum of Antiquities in Oslo. Finally, an example is given of a project where maps from 1880 and 1910 are used in an architectural history project.Espen S. Ore holds a degree in the humanities from the University of Oslo. He has also studied computer science at the universities of Oslo and Bergen. Since 1984 he has been employed at the Norwegian Computing Centre for the Humanities. He has worked mostly with non-latin character sets, computer graphics and multimedia. Since 1993 he has been leading a project on a typology of runic writing based on character forms.     

一种基于理性遗传算法(RGA)的协调运动行为合成算法

协调运动行为的合成是实现多机器人系统协调运动的关键.本文针对特定环境下的 多机器人协调运动问题,基于调速避碰的思想,借助CMAC神经网络,来描述各机器人的运动行 为与环境状态之间复杂的、非线性映射关系,利用理性遗传算法来合成与优化各机器人的运 动行为,从而实现多机器人已知环境下,运动行为的相互协调与优化.文章讨论了规划算法的 鲁棒性、完备性及时间复杂度.     

Integration of self-organizing feature map and K-means algorithm for market segmentation

Cluster analysis is a common tool for market segmentation. Conventional research usually employs the multivariate analysis procedures. In recent years, due to their high performance in engineering, artificial neural networks have also been applied in the area of management. Thus, this study aims to compare three clustering methods: (1) the conventional two-stage method, (2) the self-organizing feature maps and (3) our proposed two-stage method, via both simulated and real-world data. The proposed two-stage method is a combination of the self-organizing feature maps and the K-means method. The simulation results indicate that the proposed scheme is slightly better than the conventional two-stage method with respect to the rate of misclassification, and the real-world data on the basis of Wilk's Lambda and discriminant analysis.Scope and purposeThe general idea of segmentation, or clustering, is to group items that are similar. A commonly used method is the multivariate analysis [4]. These methods consist of hierarchical methods, like Ward's minimum variance method, and the non-hierarchical methods, such as the K-means method. Owing to increase in computer power and decrease in computer costs, artificial neural networks (ANNs), which are distributed and parallel information processing systems successfully applied in the area of engineering, have recently been employed to solve the marketing problems. This study aims to discuss the possibility of integrating ANN and multivariate analysis. A two-stage method, which first uses the self-organizing feature maps to determine the number of clusters and the starting point and then employs the K-means method to find the final solution, is proposed. This method provides the marketing analysts a more sophisticated way to analyze the consumer behavior and determine the marking strategy. A case study is also employed to demonstrate the validity of the proposed method.     

Programming models for hybrid FPGA-cpu computational components: a missing link

Emerging hybrid chips containing cpu and FPGA components are an exciting new development promising commercial off-the-shelf economies of scale, while also supporting hardware customization.     

MACH CPU Server的功能和实现的策略

本文介绍Mach核心之上进行处理器管理的cPu serVer(处理器分配服务器,的功能,它所实现的不同处理器分配策略。文中最后给出一个在Mach操作系统核心上实现的一个cPu server的实例,并主要介绍其标准库函数界面以及基于Mach核心的实现考虑。     

Aerial image sequence geolocalization with road traffic as invariant feature

The geolocalization of aerial images is important for extracting geospatial information (e.g. the position of buildings, streets, and cars) and for creating maps. The standard is to use an expensive aerial imaging system equipped with an accurate GPS and IMU and/or do laborious ground control point measurements. In this paper we present a novel method to recognize the geolocation of aerial images automatically without any GPS or IMU. We extract road segments in the image sequence by detecting and tracking cars. We search in a database created from a road network map for the best matches between the road database and the extracted road segments. Geometric hashing is used to retrieve a shortlist of matches. The matches in the shortlist are ranked by a verification process. The highest scoring match gives the location and orientation of the images. We show in the experiments that our method can correctly geolocalize the aerial images in various scenes: e.g. urban, suburban, and rural with motorway. Besides the current images only the road map is needed over the search area. We can search an area of 22,500 km² containing 32,000 km of streets within minutes on a single cpu.     

Detail-preserving exposure fusion using subband architecture

In this paper, we present a novel detail-preserving fusion approach from multiple exposure images using subband architecture. Given a sequence of different exposures, the Quadrature Mirror Filter (QMF) based subband architecture is first employed to decompose the original sequence into different frequency subbands. After that, we compute the importance weight maps according to the image appearance measurements, such as exposure, contrast, and saturation. In order to preserve the details of the subband signals, we compute the gain control maps and improve these subbands. Finally, the coefficients of subbands are blended into a high-quality detail-preserving fusion image. Experimental results demonstrate that the proposed approach successfully creates a visually pleasing exposure fusion image.     

Representing and evaluating ultrasonic maps using active snake contours and Kohonen’s self-organizing feature maps

Active snake contours and Kohonen’s self-organizing feature maps (SOMs) are employed for representing and evaluating discrete point maps of indoor environments efficiently and compactly. A generic error criterion is developed for comparing two different sets of points based on the Euclidean distance measure. The point sets can be chosen as (i) two different sets of map points acquired with different mapping techniques or different sensing modalities, (ii) two sets of fitted curve points to maps extracted by different mapping techniques or sensing modalities, or (iii) a set of extracted map points and a set of fitted curve points. The error criterion makes it possible to compare the accuracy of maps obtained with different techniques among themselves, as well as with an absolute reference. Guidelines for selecting and optimizing the parameters of active snake contours and SOMs are provided using uniform sampling of the parameter space and particle swarm optimization (PSO). A demonstrative example from ultrasonic mapping is given based on experimental data and compared with a very accurate laser map, considered an absolute reference. Both techniques can fill the erroneous gaps in discrete point maps. Snake curve fitting results in more accurate maps than SOMs because it is more robust to outliers. The two methods and the error criterion are sufficiently general that they can also be applied to discrete point maps acquired with other mapping techniques and other sensing modalities.     

Projective texture atlas construction for 3D photography

The use of attribute maps for 3D surfaces is an important issue in geometric modeling, visualization and simulation. Attribute maps describe various properties of a surface that are necessary in applications. In the case of visual properties, such as color, they are also called texture maps. Usually, the attribute representation exploits a parametrization g:U??²→?³ of a surface in order to establish a two-dimensional domain where attributes are defined. However, it is not possible, in general, to find a global parametrization without introducing distortions into the mapping. For this reason, an atlas structure is often employed. The atlas is a set of charts defined by a piecewise parametrization of a surface, which allows local mappings with small distortion. Texture atlas generation can be naturally posed as an optimization problem where the goal is to minimize both the number of charts and the distortion of each mapping. Additionally, specific applications can impose other restrictions, such as the type of mapping. An example is 3D photography, where the texture comes from images of the object captured by a camera [4]. Consequently, the underlying parametrization is a projective mapping. In this work, we investigate the problem of building and manipulating texture atlases for 3D photography applications. We adopt a variational approach to construct an atlas structure with the desired properties. For this purpose, we have extended the method of Cohen–Steiner et al. [6] to handle the texture mapping set-up by minimizing distortion error when creating local charts. We also introduce a new metric tailored to projective maps that is suited to 3D photography.     

Energy-aware scheme for the 3D-HEVC depth maps prediction

This paper presents an energy-aware scheme to reduce the energy consumption on the 3D high-efficiency video coding (3D-HEVC) depth maps prediction. Besides, a qualitative discussion is presented for intra- and inter-frame predictions that conduced to the proposition of a simple energy-aware scheme. Through our analysis, the HEVC intra-prediction is applied over homogeneous regions, whereas bipartition modes are preferred to encode edge regions. Based on this fact, the Simplified Edge Detector (SED) is proposed to employ a fast intra-mode decision. The SED anticipates the blocks that are likely to be better predicted by the HEVC intra-prediction, avoiding evaluations of bipartition modes. On inter-prediction, the TZ Search (TZS) is employed in the 3D-HEVC reference software (HTM) to encode both texture frames and depth maps. However, considering the depth maps properties, lightweight fast algorithms should be considered instead of TZS. Thus, fast algorithms such as Diamond Search, Small Diamond Search (SDSP), and One-at-a-Time Search were evaluated in this paper, aiming to reduce the complexity and energy, whereas sustaining good coding efficiency. By analyzing the depth channel, this scheme (considering intra- and inter-predictions) is able to provide an encoding time reduction of 21.2–23.1 %. As drawback, the combined solution increases the BD-rate in 0.62–0.87 %, in the synthesized views. When considering general-purpose processors, our solution is capable of providing a reduction in the energy consumption ranging between 9.85 and 10.41 %, according to our software analysis using the running average power limit. By using the SDSP combined of SED algorithm instead of HTM-10.2 baseline solution, it is possible to achieve a reduction of about 54 % in the energy consumption, and about 1.8 times in the power dissipation, when running on a dedicated hardware design. Considering that depth maps are only used for view synthesis, a subjective quality assessment was performed using synthesized views, and the results demonstrate that our solution presents minimum quality losses.     

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing ground plots whose coordinates are obtained from Global Positioning System (GPS) receivers that are calibrated to the same geographic coordinate system, and then matching ground plots to image pixels containing the centers of the ground plots. Errors in rectification and GPS coordinates cause observations of ground attributes to be associated with spectral values of incorrect pixels which, in turn, introduces classification errors into the resulting maps. The most important finding of the study is that for common magnitudes of rectification and GPS errors, as many as half the ground plots may be assigned to incorrect pixels. The effects on areal estimates obtained by aggregating class predictions for individual pixels are deviation of the estimates from their true values, erroneous confidence intervals, and incorrect inferences. Results are reported in detail for both probability-based (design-based) and model-based approaches to inference for proportion forest area using maps constructed from Landsat imagery, forest inventory plot observations and a logistic regression model.     

Differentiating between Line and Point Maps Using Spatial Experience: Considering Richard Neutra’s Lovell House

Space Syntax researchers have demonstrated methods for mapping and analysing zones (rooms) and lines (paths) in plans. One Space Syntax technique that is rarely used is focussed on the mapping of points (intersections) in architectural plans, and is an inversion of a more common approach to the mapping of lines (paths) in plans. From a graph theory perspective, the former point map is a dual of the latter, primal line map; meaning the two are numerically comparable. In this paper such a comparison is used to investigate if there is any difference between the capacity of line and point maps to suggest the spatial experience of the individual. The case study chosen to develop such a comparative analysis is Richard Neutra's Lovell House. This design is mapped, using both line and point techniques, and mathematically analysed to determine the socially significant paths and intersections. A selected investigation of the intelligibility implications of these lines and points along with their three-dimensional properties is then developed. The paper concludes that there is some evidence that, for point and line maps with similar mathematical properties, point maps are more successful at suggesting the experiential qualities of space.     

Simple stabilizing matrices for the computation of compressible flows in primitive variables

The key ingredient that balances stability and accuracy in stabilized formulations is the parameter of intrinsic time-scales. For multi-dimensional hyperbolic systems of equations, this parameter is a matrix and the available expressions for its computation involve the solution of an eigenvalue problem, which can be tedious or cpu time consuming. Thus, for formulations based on primitive variables including pressure, a couple of simple stabilizing matrices are presented which are easy to implement and cpu-economic. Numerical evaluations show the performance of the various choices.