A two-level strategy for segmenting center of interest from pictures

Segmenting center of interests (COIs) from pictures is an important but highly challenging problem for researchers in computer vision and image processing. The capability of understanding the meanings of pictures by computers can lead to breakthroughs in a wide range of applications including Web image search and online picture-sharing communities. In this paper, a two-level strategy is presented, which consists of a rough segmentation stage and a fine segmentation stage. In the first level, a picture is partitioned into four regions by using a block clustering method based on color and texture features, and the COI within the picture is distinguished from the background according to the principles of photographic composition. This stage aims to determine the approximate region of the target. In the second level, a novel active contour model is established based on shape information and vector method, where the image energy is defined by a hue gradient and the external energy is generated from either a triangular inner force or a supplementary force. This stage tries to extract the boundary of the target accurately. Experimental results on photos downloaded from the Internet show the feasibility and effectiveness of the proposed method.     

一种基于组策略的过滤式特征选择算法

MRMR算法具有快速、高效等优势,在处理高维数据方面较为流行。基于此,提出一种基于组策略的MRMR改进算法（MRMRE）,该算法不仅考虑单个特征属性的相关性与冗余性,同时针对特征组间的相互关系进行研究。算法以MRMR算法为框架,以CCA作为度量基准,选择SVMs作为基分类器,使其特征选择效果提升。在UCI机器学习数据库中图像与基因序列数据集上的大量实验表明：与MRMR算法相比,所提出的算法其特征选择结果具有更高的结果稳定性与分类精度。     

Wireless channel extraction analyzing based on graph theory

Wireless channels comprise various signal characteristics that correspond to different features. This research applies digital signal processing to first excavate and categorize various features found in the channel data. Then, borrowing from graph theory, fast clustering analysis and decision tree modeling are introduced to identify unique “fingerprint” characteristics. Finally, two scenarios were tested using artificial neural networks to identify and verify their applicability in different geographical locations.     

Repetitive control design for variable instantaneous frequencies signals

International Journal of Control, Automation and Systems - Vibration disturbances with variable instantaneous frequencies can be found in many industrial applications. Therefore, rejecting...     

五年制高职动漫专业毕业设计考核评价探究

提升职业教育教学质量是高职院校的核心任务。毕业设计是专业教学的重要环节,它不仅关系到毕业生的质量,也关系到专业的未来发展。从考核评价的角度,对五年制高职动漫专业学生的毕业设计进行可操作性的探讨。     

无线传感器网络中一种高效IBE方案

无线传感器网络的应用日益广泛但安全性问题越发突出,由于其计算能力、存储能力和通信能力有限,一直被认为不适合使用公钥密码学方案。然而近年来不需要认证中心的IBE算法的研究成果表明,IBE方案非常适合无线传感器网络。本文提出一种高效的IBE方案,并做了算法介绍,同时在无线传感器网络中提出相应的密钥分配、认证、管理以及更新的应用方案。与现有其他算法相比,新方案具有系统参数短、安全性高等特点。     

A method for stochastic multiple criteria decision making based on dominance degrees

This paper proposes a method for solving the stochastic multiple criteria decision making (SMCDM) problem, where consequences of alternatives with respect to criteria are represented by random variables with probability distributions. Firstly, definitions and related analysis of dominance degree of one probability distribution over another are given. Then, by calculating the dominance degrees, the dominance degree matrix of alternative pairwise comparisons with respect to each criterion is built. Further, using PROMETHEE II method, an overall dominance degree matrix of alternative pairwise comparisons is constructed, and a net flow of each alternative is calculated. Based on the obtained net flows, a ranking of alternatives is determined. Finally, numerical examples for the three cases are given to illustrate the use of the proposed method.     

服务器容错与磁盘阵列技术的集成

介绍了 2种常用的服务器容错技术 ,详细阐述了RAID技术的基本原理 ,最后给出了一个工程集成实例     

一种应用于图像表达的轮廓层次结构树

提出一种应用于图像表达中的轮廓层次结构树.与Fub提出的区域包含关系树相比,本方法增加了对相邻轮廓所构成的整体轮廓的表示,对图像轮廓关系的描述更为准确完整,可以用在多层次图像重构和图像匹配等图像表达的应用中.实验表明,该方法在图像表达应用中有较好的效果.     

BP神经网络在剩余油分布预测中的应用研究

我国多数油田经过一次、二次采油后,仅能采出地下总储量的30%左右,这意味着有60%～70%的剩余石油仍然残留在地下成为剩余油。加强剩余油分布规律研究、提高石油采收率不仅有着可观的经济效应,而且关系到国家石油战略的安全。本研究应用神经网络的原理,基于BP网络使用MATLAB语言建立一个剩余油分布的预测系统。该系统通过学习在地理坐标和孔隙度之间建立一个非线性函数关系,以此来预测任何区域的孔隙度,再通过孔隙度与剩余油饱和度之间的关系达到剩余油分布预测的目的。