Resilient overlay network for real-time interactive multimedia sessions in corporate networks

Real-time interactive multimedia communications are becoming increasingly useful for education, business, e-commerce and e-government, providing an enriched user experience in teleconferencing, e-meetings, distance training and product demonstrations. Large corporations are usually located at several sites, so real-time multipoint sessions within corporations are especially difficult. IP multicast is available or feasible within each site of an organization. Thus, corporate networks can be considered as various multicast-capable networks interconnected through a wide area network without multicast connectivity. This paper proposes a resilient self-managed overlay network to support real-time multipoint interactive sessions within corporate networks. The proposed overlay takes advantage of the configuration of corporate networks to self-organize and provide an efficient media delivery service, making use of multicast communications wherever available. Various self-healing techniques are implemented allowing for the continuity of ongoing sessions in spite of network disruptions and entity failures. Extensive simulations and tests have been carried out to assess the performance and resilience of the overlay facing several types of disruptions.     

A PC-based architecture for parameter analysis of vector-controlled induction motor drive

In this article a methodology for constructing a user interface for system control and data acquisition of a drive which is suitable for three-phase induction motors (3?IM) is presented. The entire hardware implementation is shown, including power and digital stages. Communication between the computer and the controller is engaged in order to enhance an analysis of power quality, adjust the controller parameters for tuning the flux and speed loops, and performance of the embedded algorithm. USB and Ethernet protocols have been put into operation in the user front-end because a high speed sample frequency is required in order to guarantee the real-time operation of the whole system. A software interface is developed using LabVIEW environment enabling features not only as filtering signals of phase voltage and current but also power spectrum measurements. Vector-controlled drive is programmed on a digital signal processor (DSP) in order to ensure efficient use of energy in the power stage and proper tracking of the reference at low and high speeds.     

支持非第一范式的DBMS中DD的设计和实现

NFMDB数据库管理系统是在 RDBMS的基础上扩充而成的 ,它支持非第一范式 NF2 (Nonfirst normal form)及多媒体数据类型。首先 ,分析了集中式和分离式字典系统的特点 ,并阐述了主动 DD和被动 DD的区别 ;其次 ,讨论了 NFMDB系统为处理 NF2问题而引入的关系字典、属性字典等字典的构造 ,并给出了部分结构描述 ;然后 ,用 create语句描述了一个关于 NF2 存储模式实例 ,同时以 select语句为例讨论了用关系字典和属性字典为基础转换多维 NF2 问题为平滑关系的算法 ,所有这些操作均在关系字典和属性字典中给出了相应的存储描述 ;最后 ,探讨了以关系方式存储 DD的优点以及 DD与 DBMS的关系。由此得出以扩充 DD系统为基础处理 NF2 问题是可行的。     

The role of a “make” or internal human resource management system in Spanish manufacturing companies: Empirical evidence

The combined study of the literature about human resource management and the resource‐based view of the firm and organizational learning provides an analysis framework useful for understanding how strategic human resource management systems contribute to the creation and development of a sustained competitive advantage for the firm. This article has two major aims. First, it provides a conceptual framework linking simultaneously three theoretical blocks: (a) human resource management, (b) organizational learning and knowledge management, and (c) sustained competitive advantage. Second, the article builds a causal model and tests it with a sample of Spanish firms from the manufacturing industry using structural equation modeling (SEM). After the performance of a cluster analysis, a group of 72 learning firms is identified and used to test the model. Finally, major conclusions and implications for management are drawn and further avenues for research are suggested. © 2008 Wiley Periodicals, Inc.     

Building language resources for a Multi-Engine English-Filipino machine translation system

In this paper, we present the building of various language resources for a multi-engine bi-directional English-Filipino Machine Translation (MT) system. Since linguistics information on Philippine languages are available, but as of yet, the focus has been on theoretical linguistics and little is done on the computational aspects of these languages, attempts are reported here on the manual construction of these language resources such as the grammar, lexicon, morphological information, and the corpora which were literally built from almost non-existent digital forms. Due to the inherent difficulties of manual construction, we also discuss our experiments on various technologies for automatic extraction of these resources to handle the intricacies of the Filipino language, designed with the intention of using them for the MT system. To implement the different MT engines and to ensure the improvement of translation quality, other language tools (such as the morphological analyzer and generator, and the part of speech tagger) were developed.     

Induction charge detector with multiple sensing stages

An induction charge detector yields the net charge and the time of flight of a particle. The unique ability to independently measure these two parameters sets apart this rather simple detection technique. The main shortcoming of this instrument is its high charge detection limit, resulting from the intrinsic noise of the detector electronics and the low signal associated with the charge to measure. The goal of the present work is to lower the detection limit of this detector. This article describes an induction charge detector whose main novelty is a sequence of aligned cylindrical electrodes for measuring the charge of a particle n times. In a time domain analysis, this feature reduces both the detection limit and the standard error of the charge measurement by factors of square root of 2 and square root of n. More importantly, sensing stages could be added to arbitrarily lower the detection limit in a frequency domain analysis.     

Gaussian mean-shift is an EM algorithm

The mean-shift algorithm, based on ideas proposed by Fukunaga and Hosteller, is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density estimate. Mean-shift can be used as a nonparametric clustering method and has attracted recent attention in computer vision applications such as image segmentation or tracking. We show that, when the kernel is Gaussian, mean-shift is an expectation-maximization (EM) algorithm and, when the kernel is non-Gaussian, mean-shift is a generalized EM algorithm. This implies that mean-shift converges from almost any starting point and that, in general, its convergence is of linear order. For Gaussian mean-shift, we show: 1) the rate of linear convergence approaches 0 (superlinear convergence) for very narrow or very wide kernels, but is often close to 1 (thus, extremely slow) for intermediate widths and exactly 1 (sublinear convergence) for widths at which modes merge, 2) the iterates approach the mode along the local principal component of the data points from the inside of the convex hull of the data points, and 3) the convergence domains are nonconvex and can be disconnected and show fractal behavior. We suggest ways of accelerating mean-shift based on the EM interpretation     

Analysis of the HLA class I associated peptide repertoire in a hepatocellular carcinoma cell line reveals tumor-specific peptides as putative targets for immunotherapy

HLA class I molecules present peptides on the cell surface to CD8(+) T cells. The repertoire of peptides that associate to class I molecules represents the cellular proteome. Therefore, cells expressing different proteomes could generate different class I-associated peptide repertoires. A large number of peptides have been sequenced from HLA class I alleles, mostly from lymphoid cells. On the other hand, T cell immunotherapy is a goal in the fight against cancer, but the identification of T cell epitopes is a laborious task. Proteomic techniques allow the definition of putative T cell epitopes by the identification of HLA natural ligands in tumor cells. In this study, we have compared the HLA class I-associated peptide repertoire from the hepatocellular carcinoma (HCC) cell line SK-Hep-1 with that previously described from lymphoid cells. The analysis of the peptide pool confirmed that, as expected, the peptides from SK-Hep-1 derive from proteins localized in the same compartments as in lymphoid cells. Within this pool, we have identified 12 HLA class I peptides derived from HCC-related proteins. This confirms that tumor cell lines could be a good source of tumor associated antigens to be used, together with MS, to define putative epitopes for cytotoxic T cells from cancer patients.     

基于神经网络的时间序列鲁棒预测

为了实现神经网络预测模型的便棒预测,提出一种基于非线性偏自相关的一般化预测模型辨识方法。该方法通过考察待预测时间序列的当前序列值对各阶历史序列的不可约自依赖,确定神经网络这类非线性自回归模型的自回归阶数。实现表明,该方法可有效地提高神经网络预测模型的鲁棒预测能力。     

模糊聚类神经网络的非对称学习算法

通过仿真和分析表明模糊聚类神经网络原有学习算法FCNN的局限性,如初值敏感性、吸引域不灵活和稳定点不合理等;指出造成上述局限的原因主要在于算法的对称性和权值向量的修正缺乏协同。为此,通过在网络模型中引入层内反馈、在算法中引入加速项,消除了算法的对称性并使权值向量的修正具有一定的协同性;通过改进算法结构,消除了小尺度振荡现象并使算法的稳定点趋于合理。计算机仿真结果表明改进后的非对称学习算法AFC可以有效克服原有算法的不足并具有较高的收敛速度。