基于Cortex-A8智能家居系统的设计与实现

本文设计了一套低成本无线智能家居系统的解决方案,具有安全,可靠,稳定的显著特点,以及智能家居系统市场的广大前景.本文还阐明了系统的体系结构,详细介绍了系统软件和硬件部分的设计与实现。并对关键技术(GPRS、24L01)的流程做了详细的阐述。     

浅析电子商务中博客营销的使用技术与特点

随着博客的兴盛,博客营销作为一种新的营销方式出现在人们面前.本文通过总结博客营销的发展现状和特点,对这种新的电子商务模式进行了探讨和展望.     

浅谈计算机技术在交通运输规划与管理中的应用

自从计算机被应用于交通运输业以来,计算机技术在交通运输规划与管理中就得到了越来越广泛的应用.本文分析了计算机技术在交通运输规划与管理中的应用领域,详细讨论了计算机技术在智能运输系统和道路交通系统仿真中的应用.     

软件开发框架模型——现实世界问题的结构化分析

对软件开发框架模型提出了一种新的构化的分析方法,同时介绍了常用的结构化分析的工具及其更实用情况。     

浅谈网络安全风险的评估方法

本文通过分析网络系统风险的概念及评价体系建设原则,针对风险评估的流程进行探讨,并就应注意的几个问题提出几点建议。以期通过本文的阐述为网络管理人员更好地制定安全策略提供有效的技术支持。     

Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.     

Small sample improvements in the threshold cointegration test using residual-based moving block bootstrap

A residual-based moving block bootstrap procedure for testing the null hypothesis of linear cointegration versus cointegration with threshold effects is proposed. When the regressors and errors of the models are serially and contemporaneously correlated, our test compares favourably with the Sup LM test proposed by Gonzalo and Pitarakis. Indeed, shortcomings of the former motivated the development of our test. The small sample performance of the bootstrap test is investigated by Monte Carlo simulations, and the results show that the test performs better than the Sup LM test.     

Cracking the walnut: Using a computer game to impact cognition,emotion, and behavior of highly aggressive fifth grade students

Three fifth grade highly aggressive students participated in a study examining effects of an aggression intervention game. Using single-subject multiple baseline research design, the effect of the game was measured across three domains: attribution of peer intent (cognitive), emotional response (affective) and behavior response (behavioral). The results indicate that, while there were observable individual differences, the game had an immediate impact on attribution of peer behavior across all participants, had a less predictable impact on reported behavioral reactions, and had no discernable impact on reported emotional response. Theoretical and practical implications of the study are discussed.