数字图像水印嵌入强度的矩估计方法

在水印图像是均值为零的随机二值序列、原始图像是服从Weibull分布(具有参数a和β)的独立同分布随机序列的条件下，对于原始灰度图像，水印嵌入强度的估计问题可归结为对隐秘图像和原始图像灰度平均值的简单计算的问题．提出矩估计方法，实验结果证实了该方法的有效性．对加法、乘法和融合三种嵌入规则的性能进行了比较和分析，所获得的结论对今后的研究有意义。     

基于XML技术的分布式现场总线远程监控系统设计

针对传统的基于OPC技术的现场总线监控系统存在的若干问题和现场总线远程监控的要求，在微软的Windows分布式Internet结构开发模型基础上，结合XML和SOAP分布式组件模式技术，提出了一种新的分布式现场总线远程监控系统框架体系结构．这个体系结构解决了传统监控系统所存在的问题，使现场总线远程监控成为可能，并使系统具有良好的扩展性．     

数字视频水印技术

为防止越来越多的电子信息产品的盗版、恶意攻击和非法篡改问题,数字视频水印技术应运而生。它能够很好地解决电子信息产品的知识产权保护问题。文中综述了基于水印的数字视频版权保护技术。在简要介绍数字视频水印技术的应用背景和基本特点的基础上,分析了目前常用的水印嵌入算法和检测手段,并指出了实际应用中应注意的一些关键技术,如扩频、纠错编码、假设相关检测、视频水印的嵌入等技术,指出数字视频水印技术必将有一个广阔的发展前景。     

An Isometric Surface Method For Integer Linear Programming * *Supported by the R&D base on advanced manufacturing technology,Academia Sinica

Based on the isometric plane method for linear programming, an algorithm for integer linear programming is proposed in this paper. The algorithm can quickly obtain the optimal integer point simultaneously using isometric planes and cutting planes derived from polyhedral-cones, rounded-minimal-balls and second-rounded-balls at the highest vertex and its neighboring vertices.     

Reproducibility of subjectively graded voluntary isometric muscle strength in unilateral and simultaneous bilateral exertion

Reproduction error of voluntary isometric muscle strength that was graded subjectively by the subject was investigated under unilateral and bilateral conditions. Six kinds of tasks, i.e. elbow flexion, elbow extension, hand grip, second digit abduction, knee extension and leg extension were employed. It was clear that absolute error (AE) increased with increase of exerted muscle strength in both unilateral and bilateral conditions. Mean of AE in each task was 4-5% of maximal muscle strength in the task in unilateral conditions. Algebraic or constant error (CE) decreased with increase of exerted strength. Demands for smaller strength tended to overshoot and larger ones tended to undershoot. In bilateral conditions when the different levels of strength for each limb were required to be exerted, AE on the weaker side tended to be larger than that in unilateral conditions. Thus a possibility that magnitude of AE might be affected by amount of attention was suggested. The subjectively graded criterion strength for a specific required level, when the strength was expressed as relative to the maximal strength, was almost the same in every task within a subject although it was different between subjects. It is suggested that each subject might have an awareness of relative magnitude of exerted strength.     

Variability of grip strength during isometric contraction

The use of measures of strength variability as a means of determining sincerity of effort is becoming a more common practice, particularly in medico-legal and rehabilitation settings. The stability of such variability measures, however, has not been documented. This research investigated, in two studies, the trial-to-trial variability of grip strength under maximal and submaximal effort conditions. In the first study, 63 subjects were asked to give 100% grip effort, and in the second study 40 subjects from the original group were asked to give 50% grip effort. The Jamar hand dynamometer was used to measure grip strength in both experiments, and a coefficient of variation (CV) was calculated for every three repeat measures at each handle position. Testing was conducted on two separate occasions for both experiments. Although the interoccasion reliability of grip strength was very high, in comparison, the CV was not stable over test occasions, with interoccasion reliability indices close to zero. Factors significantly influencing CV were effort level, with submaximal effort producing larger CVs, and gender, with females having greater strength variability. If the rule is applied that one or more CVs above the 7·5% cut-off value could indicate submaximal effort, then for this sample of subjects giving maximal effort, 97% of females and 64% of males would be misclassified. Applying a single CV classification cut-off value to a mixed sample of subjects appears to unfairly discriminate against the females. Further research into the factors associated with high CV values is essential before the CV can be used with any confidence in a clinical setting as a method for determining sincerity of effort.     

Fault diagnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine

Fault diagnosis for wind turbine transmission systems is an important task for reducing their maintenance cost. However, the non-stationary dynamic operating conditions of wind turbines pose a challenge to fault diagnosis for wind turbine transmission systems. In this paper, a novel fault diagnosis method based on manifold learning and Shannon wavelet support vector machine is proposed for wind turbine transmission systems. Firstly, mixed-domain features are extracted to construct a high-dimensional feature set characterizing the properties of non-stationary vibration signals from wind turbine transmission systems. Moreover, an effective manifold learning algorithm with non-linear dimensionality reduction capability, orthogonal neighborhood preserving embedding (ONPE), is applied to compress the high-dimensional feature set into low-dimensional eigenvectors. Finally, the low-dimensional eigenvectors are inputted into a Shannon wavelet support vector machine (SWSVM) to recognize faults. The performance of the proposed method was proved by successful fault diagnosis application in a wind turbine's gearbox. The application results indicated that the proposed method improved the accuracy of fault diagnosis.     

A novel function-structure concept network construction and analysis method for a smart product design system

The rapid growth of data and the requirement of designers to track massive data to obtain design stimuli have posed challenges to conceptual design, thereby promoting the development of data-driven design. Concept networks precisely capture design information from a large volume of unstructured and heterogeneous textual data and saliently decrease time and labor cost for designers to read texts, which creates new opportunities for developing a smart product design system. To advance data-driven design, this study proposes the novel function-structure concept network (FSCN) construction method, which combines sentence parsing and word/phrase extraction to integrate functional and structural information. Furthermore, a network analysis method is proposed to explore design information associations that contain both explicit and implicit associations together and thereby recommend them simultaneously to designers as inspirational stimuli to support design ideation. This approach can enhance designers' capabilities to build associations between design information, conceive new design ideas during conceptual design, and increase creativity for solving design problems. The proposed FSCN construction and analysis method can be used as an auxiliary tool to visualize associations among design information so as to inspire idea generation in the early stage of conceptual design. An illustrative example was used to validate the practicability of the proposed methodology. The code of the proposed method is available at https://github.com/KWflyer/FSCN.