基于混沌特征的运动模式分割和动态纹理分类

采用混沌理论对动态纹理中的像素值序列建模,提取动态纹理中的像素值序列的相关特征量,将视频用特征向量矩阵表示. 通过均值漂移（Mean shift）算法对矩阵中的特征向量聚类,实现对视频中的运动模式分割. 然后,采用地球移动距离（Earth mover’s distance,EMD）度量不同视频的差异,对动态纹理视频分类. 本文对多个数据库测试表明:1）分割算法可以分割出视频中不同的运动模式;2）提出的特征向量可以很好地描述动态纹理系统;3）分类算法可以对动态纹理视频分类,且对视频中噪声干扰具有一定的鲁棒性.     

Stabilization of Rössler chaotic dynamical system using fuzzy logic control algorithm

This paper proposes a fuzzy logic control algorithm (FLCA) to stabilize the Rössler chaotic dynamical system. The fuzzy logic control system is based on a Takagi-Sugeno-Kang inference engine and the stability analysis in the sense of Lyapunov is carried out using Lyapunov’s direct method. The new FLCA is formulated to offer sufficient inequality stability conditions. The asymptotic complexity of our algorithm is analyzed and proved to be lower in comparison with that of linear matrix inequality-based FLCAs. A set of simulation results illustrates the effectiveness of the proposed FLCA.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

中国涂料现状及今后发展热点(一)

综述了目前中国涂料业的发展概况,并介绍了今后发展趋势和研究热点──防腐蚀涂料、卷材涂料、功能涂料、绿色木器涂料和粉末涂料等5种涂料。     

建筑装饰陶瓷饰面砖的应用与发展

分析建筑装饰陶瓷饰面砖的装饰特点，针对陶瓷饰面砖自重大、易脱落、装饰效果受装饰施工技术及质量的影响等问题，提出陶瓷饰面砖的发展应注重适应装饰施工技术及应用而进行产品的技术创新。     

New software developments for quality mesh generation and optimization from biomedical imaging data

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit.     

Automatic classification and prediction models for early Parkinson’s disease diagnosis from SPECT imaging

Early and accurate diagnosis of Parkinson’s disease (PD) is important for early management, proper prognostication and for initiating neuroprotective therapies once they become available. Recent neuroimaging techniques such as dopaminergic imaging using single photon emission computed tomography (SPECT) with ¹²³I-Ioflupane (DaTSCAN) have shown to detect even early stages of the disease. In this paper, we use the striatal binding ratio (SBR) values that are calculated from the ¹²³I-Ioflupane SPECT scans (as obtained from the Parkinson’s progression markers initiative (PPMI) database) for developing automatic classification and prediction/prognostic models for early PD. We used support vector machine (SVM) and logistic regression in the model building process. We observe that the SVM classifier with RBF kernel produced a high accuracy of more than 96% in classifying subjects into early PD and healthy normal; and the logistic model for estimating the risk of PD also produced high degree of fitting with statistical significance indicating its usefulness in PD risk estimation. Hence, we infer that such models have the potential to aid the clinicians in the PD diagnostic process.     

基于先验知识的肝脏轮廓线提取算法研究

准确有效地提取肝脏CT序列的轮廓线是腹部软组织三维模型重建与可视化的关键问题之一。针对肝脏轮廓线提取准确性不高的问题, 提出了一种基于先验知识的肝脏轮廓线提取算法。首先利用拉普拉斯算法进行CT图像增强, 再利用基于边缘先验知识的套索模型对感兴趣区域进行半自动的初始化, 最后通过改进的Snake算法准确地提取肝脏CT图像的边缘。针对序列CT肝脏的边缘提取, 提出根据CT图像序列之间的相关性, 将上一幅图像的轮廓线提取结果作为下一幅CT图像边缘提取的初始化点, 接着批处理地提取CT序列的肝脏边缘。实验结果表明：该算法大大减少了手动初始化结果对目标边缘轮廓准确提取的依赖性, 并有效地解决了肝脏轮廓线的提取问题。     

基于各向异性滤波和空间FCM的MRI图像分割方法

针对具复杂目标和边界模糊的MRI图像中多感兴趣区域的分割中分割MRI图像软组织难的问题, 提出了一种基于各向异性滤波和空间模糊C-均值聚类(SFCM)的MRI图像分割方法; 用新型各向异性滤波对图像进行预处理, 解决去噪平滑的同时弱化图像细节的问题; 用邻域空间信息设计空间函数, 改进传统FCM的目标函数; 用图像的空间信息实现图像各目标准确分类、有效解决孤立区域的正确归类问题, 进而使分割区域完整; 用直方图拟合曲线初始化分类数和初始聚类中心, 加快算法迭代到最优解, 进而减少运行时间。通过实验证实了各向异性滤波和空间FCM的MRI图像分割方法的综合应用显著提高了分割灰度重叠、目标不连续和目标边界模糊的MRI图像的分割效果。     

基于不变矩的高分辨率遥感图像建筑物提取方法

为了有效地对图像进行特征提取, 利用不变矩算法对IKONOS和WorldView两种高分辨率遥感图像的城市建筑物地区进行提取。首先将图像数据经过Canny边缘检测和标记分水岭分割, 然后在此基础上分别利用胡氏不变矩和仿射不变矩对图像进行特征提取; 最后通过实验结果的评价可以证明在建筑物的特征提取上, 仿射不变矩比胡氏不变矩的提取效果更加显著, 进而也证明了利用不变矩算法对高分辨率遥感图像建筑物特征提取这一方法是可行且有效的。