Using a software reliability model to design a telecommunicationssoftware architecture

The author proposes a software reliability model for a large real-time telecommunications software architecture. Some simple examples of the critical components of the software architecture and their dependencies are described. The component dependencies permit the propagation of faults from the component in which the fault originates to the other components. This propagation can cause failures in the chain (or in the tree) of components. Detection and failures depends on the tests executed or on the number and type of customer requests. An error can occur in any component. This error can be caused by a fault that propagated from another component or it can be a fault that originates in that component. The error can be traced through the component-dependency chain (or tree) to repair all the faults that are associated with that error. The software reliability model guides the design of the software architecture     

A curve evolution approach to object-based tomographic reconstruction

We develop a new approach to tomographic reconstruction problems based on geometric curve evolution techniques. We use a small set of texture coefficients to represent the object and background inhomogeneities and a contour to represent the boundary of multiple connected or unconnected objects. Instead of reconstructing pixel values on a fixed rectangular grid, we then find a reconstruction by jointly estimating these unknown contours and texture coefficients of the object and background. By designing a new "tomographic flow", the resulting problem is recast into a curve evolution problem and an efficient algorithm based on level set techniques is developed. The performance of the curve evolution method is demonstrated using examples with noisy limited-view Radon transformed data and noisy ground-penetrating radar data. The reconstruction results and computational cost are compared with those of conventional, pixel-based regularization methods. The results indicate that the curve evolution methods achieve improved shape reconstruction and have potential computation and memory advantages over conventional regularized inversion methods.     

A statistical approach to subspace based blind identification

Blind identification of single input multiple output systems is considered herein. The low-rank structure of the output signal is exploited to blindly identify the channel using a subspace fitting framework. Two approaches based on a minimal linear parameterization of a subspace are presented and analyzed. The asymptotically best consistent estimate is derived for the class of blind subspace-based techniques. The asymptotic estimation error covariance of the subspace estimates is derived, and the corresponding covariance of the statistically optimal estimates provides a lower bound on the estimation error covariance of subspace methods. A two-step procedure involving only linear systems of equations is presented that asymptotically achieves the bound. Simulations and numerical examples are provided to compare the two approaches     

基于情况评估的度量技术

在组织内部，信息安全管理度量为组织的安全管理状态提供了一个客观、全面的指标。文中提到的度量技术是一种基于情况评估的技术并可以模拟组织的环境。现进一步具体分析了对情况和商业目标的评估。     

A suboptimal approach to channel equalization based on the nearestneighbor rule

Applications of clustering and neural network techniques to channel equalization have revealed the classification nature of this problem. This paper illustrates an implementation of a global system for mobile communications (GSM) receiver in which channel equalization and demodulation are realized by means of the nearest neighbor (NN) classifier algorithm. The most important advantage in using such techniques is the significant reduction in terms of the computational complexity compared with the maximum likelihood sequence estimation (MLSE) equalizer. The proposed approach involves symbol-by-symbol interpretation and the knowledge of the channel is embedded in the mapping process of the received symbols over the symbols of the training sequence. This means that no explicit channel estimation need be carried out, either with correlative blocks or using neural networks thus speeding up the entire process. The performance of the proposed receiver, evaluated through a channel simulator for mobile radio communications, is compared with the results obtained by means of a 16-state Viterbi algorithm and other suboptimal receivers. It is shown that the presented algorithm increases the bit error rate (BER) compared with the MLSE demodulator, but the performance degradation, despite the simplicity of the receiver, is kept within the limits imposed by the GSM specifications     

A new approach to speech segmentation based on the maximum likelihood

Successful speech recognition is highly dependent on appropriate speech segmentation. The poor efficiency of the sequential detection of abrupt changes in the signals with relatively short stationary intervals, as is the case with speech signals, can be improved by the off-line maximum likelihood segmentation algorithm. In this paper the new segmentation algorithm is presented. For the a priori known number of segments, the algorithm determines such signal partitions for which the sum of segment distortion is minimal. The generalized maximum likelihood distortion measure has been introduced, and has proven to be particularly efficient on short signal segments. In the case of an unknown number of segments, its estimate is obtained comparing the reduction of the distortion. The asymptotic properties of the distortion sequence have been analyzed, which led to the definition of the presented segmentation algorithm. The introduced measure can be applied both to the AR and ARMA models. The segmentation algorithm is verified on test signals as well as on the natural speech signal, for which the pitch synchronous framing scheme is applied. The experimental results also include a comparison of the AR and ARMA model-based segmentations. The first results show that ARMA model-based segmentation gives somewhat better results than the AR model algorithm.Research supported in part by the Mathematical Institute of the Serbian Science Academy and Serbian Science Foundation.     

A pyramid approach to subpixel registration based on intensity

We present an automatic subpixel registration algorithm that minimizes the mean square intensity difference between a reference and a test data set, which can be either images (two-dimensional) or volumes (three-dimensional). It uses an explicit spline representation of the images in conjunction with spline processing, and is based on a coarse-to-fine iterative strategy (pyramid approach). The minimization is performed according to a new variation (ML*) of the Marquardt-Levenberg algorithm for nonlinear least-square optimization. The geometric deformation model is a global three-dimensional (3-D) affine transformation that can be optionally restricted to rigid-body motion (rotation and translation), combined with isometric scaling. It also includes an optional adjustment of image contrast differences. We obtain excellent results for the registration of intramodality positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) data. We conclude that the multiresolution refinement strategy is more robust than a comparable single-stage method, being less likely to be trapped into a false local optimum. In addition, our improved version of the Marquardt-Levenberg algorithm is faster.     

A polynomial approach to the generalized Levinson algorithm based on the Toeplitz distance

A polynomial approach to the generalized Levinson algorithm based on the Toeplitz distance concept is given. It turns out that most properties of the standard Levinson algorithm admit natural generalizations, including the three-term recurrence relations, the Christoffel-Darboux formula, and the reflection coefficients (Schur-Szegö parameters) obtainable from the data via an extension of the Schur algorithm. The theory ofsum-lossless transfer functions is shown to play the same illuminating role in the problem as the theory of Szegö orthogonal polynomials in the standard Levinson algorithm.     

基于移动场景下的边缘缓存策略综述

随着移动流量需求的爆炸式增长,传统的流量缓存策略已经满足不了现代通信网络的要求,文章提出一种边缘缓存策略,该策略力图通过在网络边缘进行缓存的方法,来降低核心网络的压力。本策略建立了移动边缘计算网络模型,文章采用协同缓存策略,以最小化中传输开销为目标建立最优化模型,以获得在MEC架构中的内容缓存部署方案。     

Techno-economic evaluation of narrowband and broadband accessnetwork alternatives and evolution scenario assessment

The paper presents the main results obtained within the Research in Advanced Communications in Europe (RACE) project: 2087 TITAN regarding minimum-risk introductory routes for new narrowband and broadband services in the residential and small business market. The project developed a methodology and a tool for techno-economic evaluation of advanced narrowband and broadband telecommunications networks and services. Results from four extensive access network studies are presented. For the narrowband services, optical access and radio in the local loop have been assessed and compared to conventional copper layout in a greenfield environment. Access network upgrade strategies for emerging new broadband services have been evaluated in three studies, with technological options ranging from enhanced copper to hybrid-fiber-coax (HFC) and broadband passive optical networks. An extensive study on different broadband access network upgrade alternatives for public network operators (PNOs) were carried out, taking into account the diversity of conditions met today by European countries. In another study, the effect of competition In the access network was modeled assuming two main operators sharing the market. Broadband upgrade alternatives were evaluated for a new cable operator, competing with the dominant public network operator. In addition, video-on-demand (VoD) and Internet access upgrades have been analyzed. The paper demonstrates the viability of techno-economic studies for the access network, including in-depth analysis of the time-dependence of component cost, tariffs, service penetrations and market shares     

A robust approach to image enhancement based on fuzzy logic

In this paper, we propose a robust approach to image enhancement based on fuzzy logic that addresses the seemingly conflicting goals of image enhancement: (i) removing impulse noise, (ii) smoothing out nonimpulse noise, and (iii) enhancing (or preserving) edges and certain other salient structures. We derive three different filters for each of the above three tasks using the weighted (or fuzzy) least squares (LS) method, and define the criteria for selecting each of the three filters. The criteria are based on the local context, and they constitute the antecedent clauses of the fuzzy rules. The overall result of the fuzzy rule-based system is the combination of the results of the individual filters, where each result contributes to the degree that the corresponding antecedent clause is satisfied. This approach gives us a powerful and flexible image enhancement paradigm. Results of the proposed method on several types of images are compared with those of other standard techniques.     

大城市WCDMA无线覆盖工程设计方案

大城市WCDMA网络规划中的无线覆盖是全网建设的关键之一,技术方案的选取直接关系到网络建成以后的通信质量.在大城市的WCDMA无线网络覆盖设计方面值得探讨和研究的问题很多,本文主要从WCDMA无线网络工程建设的角度出发,比较深入讨论了WCDMA无线覆盖策略、基站覆盖能力、覆盖技术手段、如何解决覆盖问题的工程技术方案等方面的问题.     

A novel approach to motion segmentation based on gamma distribution

We provide a new motion segmentation method in image sequences based on gamma distribution. Motion segmentation is very important because it can be employed for video surveillance, object tracking, and action recognition. The Gaussian mixture model (GMM) has been widely used as a distribution model for motion segmentation. However, we found that the gamma distribution model is more suitable than the GMM for the optical flow based motion segmentation. Experimental results show that the proposed method is very effective in producing accurate motion segmentation results in image sequences.     

A hybrid approach to operating system discovery based on diagnosis

The objective of operating system (OS) discovery is to find which OSs are running on computers in a given network. There are two existing strategies for OS discovery—active and passive—each having fundamental limitations. This paper discusses how the theory of diagnosis can be used to address, in a simple and elegant way, the problems associated with OS discovery. The problems are formalized in a logical framework and solutions are obtained through automated reasoning. The result of using such a knowledge‐oriented approach is a natural unification of the active and passive methods of OS discovery in a hybrid approach. This paper also illustrates the benefits of the hybrid approach by comparing its accuracy with other existing OS discovery tools through a large‐scale experiment.     

A medical digital library to support scenario and user-tailoredinformation retrieval

Current large-scale information sources are designed to support general queries and lack the ability to support scenario-specific information navigation, gathering and presentation. As a result, users are often unable to obtain desired specific information within a well-defined subject area. Today's information systems do not provide efficient content navigation, incremental appropriate matching or content correlation. We are developing the following innovative technologies to remedy these problems: (1) scenario-based proxies, enabling the gathering and filtering of information customized for users within a pre-defined domain; (2) context-sensitive navigation and matching, providing approximate matching and similarity links when an exact match to a user's request is unavailable; (3) content correlation of documents, creating semantic links between documents and information sources; and (4) user models for customizing the retrieved information and the presentation of results. A digital medical library is currently being constructed using these technologies to provide customized information for the user. The technologies are general in nature and can provide custom and scenario-specific information in many other domains (e.g. crisis management)     

大城市WCDMA无线覆盖工程设计方案

大城市WCDMA网络规划中的无线覆盖是全网建设的关键之一,技术方案的选取直接关系到网络建成以后的通信质量。在大城市的WCDMA无线网络覆盖设计方面值得探讨和研究的问题很多,本文主要从WCDMA无线网络工程建设的角度出发,比较深入讨论了WCDMA无线覆盖策略、基站覆盖能力、覆盖技术手段、如何解决覆盖问题的工程技术方案等方面的问题。     

Optimum antenna configuration in MIMO systems: a differential evolution based approach

In this paper, we address the problem of determining the optimum antenna configuration for a multi‐input multi‐output (MIMO) system at any given signal‐to‐noise ratio (SNR). We used two‐level differential evolution (DE) algorithm that finds both an appropriate expression among a set of candidate expressions within the list of the optimization software used, and the parameter values (coefficients) belonging to the selected expression. The results of the proposed expression are compared with the results of high SNR approximation, asymptotic approach and optimum antenna number ratios. It is shown that the numerical outcomes produced by the new expression exhibit very good agreement with the optimum antenna number ratios, and this agreement is almost independent of the specific value of SNR. Copyright © 2010 John Wiley & Sons, Ltd.     

A NEW OPTIMIZATION ALGORITHM BASED ON THE PRINCIPLE OF EVOLUTION

A new genetic algorithm is proposed for the optimization problem of real-valued variable functions. A new robust and adaptive fitness scaling is presented by introducing the median of the population in exponential transformation. For float-point represented chromosomes, crossover and mutation operators are given. Convergence of the algorithm is proved. The performance is tested by two generally used functions. Hybrid algorithm which takes the BP algorithm as a mutation operator is used to train a neural network for image recognition. Experimental results show that the proposed algorithm is an efficient global optimization algorithm.     

A novel approach to diagnose diabetes based on the fractal characteristics of retinal images

A novel diagnostic scheme to develop quantitative indexes of diabetes is introduced in this paper. The fractal dimension of the vascular distribution is estimated because we discovered that the fractal dimension of a severe diabetic patient's retinal vascular distribution appears greater than that of a normal human's. The issue of how to yield an accurate fractal dimension is to use high-quality images. To achieve a better image-processing result, an appropriate image-processing algorithm is adopted in this paper. Another important fractal feature introduced in this paper is the measure of lacunarity, which describes the characteristics of fractals that have the same fractal dimension but different appearances. For those vascular distributions in the same fractal dimension, further classification can be made using the degree of lacunarity. In addition to the image-processing technique, the resolution of original image is also discussed here. In this paper, the influence of the image resolution upon the fractal dimension is explored. We found that a low-resolution image cannot yield an accurate fractal dimension. Therefore, an approach for examining the lower bound of image resolution is also proposed in this paper. As for the classification of diagnosis results, four different approaches are compared to achieve higher accuracy. In this study, the fractal dimension and the measure of lacunarity have shown their significance in the classification of diabetes and are adequate for use as quantitative indexes.     

基于情景分析的科技企业技术管理

情景分析已经在企业的诸多领域得到应用,无论是战略的制定还是产品设计,这些应用的共同点是存在不确定性。对不确定性的管理是公司各层级管理者决策时需要解决的问题,也是情景分析比较其他决策方法得到重视的原因。本文分析了企业技术层面不确定性的特点,从企业技术管理的角度探讨了情景分析在企业技术管理中的应用。