基于嵌入式Web技术的监控系统设计与实现

提出一种基于嵌入式和Web技术的室内设备监控系统方案,使管理者可以不受时空的限制,通过Internet利用Web浏览器完成对远程设备的访问、监控和维护等操作,无需安装特定软件,具有跨平台性,有效解决利用有限资源实现设备的网络接入问题。实际运行效果表明该系统具有良好的稳定性与实时性,具有实际应用和推广价值。     

基于区域一致性和NSCT的SAR图像分割

提出反映合成孔径雷达（sAR）图像区域一致性的G值图,在此基础上运用区域生长方法对图像进行粗分割。在对粗分图像进行区域合并的过程中,对于含有丰富方向和纹理信息的SAR图像,使用非下采样Contourlet变换（NSCT）进行区域特征提取,并采用一种新方法进行区域合并。仿真结果证明了SAR图像分割算法的有效性。     

基于DSDV的无线Mesh网络跨层路由设计

在DSDV协议的基础上,提出一种跨层路由设计的方法,选择一条具有合理长度和最小重传概率的路由进行测试。该链路质量机制可应用到基于IEEE802.11x的无线Mesh网络中,无须对现有的MAC层进行修改,即可作为一个单独模块加入到现有协议。在多跳网络中使用该跨层方案进行路由选择,能节省系统开销,优化系统的整体性能。     

压力电测系统的静态及准静态校准适用性探讨

火药燃气压力最常用的测试方法为压力电测法.用于火药燃气压力测试的常用电测系统包括应变式、压阻式和压电式3种压力电测系统.为保证压力测试精度,需对压力电测系统进行校准.针对以上3种压力电测系统,对于可获取系统灵敏度的两种校准方法——静态校准和准静态校准,分别阐述了两种校准方法的目的、实现、量值传递,根据3种压力电测系统的不同特点,比较了两种校准方法的适用性,并给出了各种校准方法目前所能达到的不确定度.     

平滑度欧式聚类算法分割点云数据

提出一种平滑度欧式聚类点云分割算法,用于实现对Kinect点云的快速、准确分割.首先介绍了Kinect点云的采集和滤波方法,然后在传统欧式聚类算法基础上提出了一种平滑度欧式聚类分割算法,通过加入平滑阈值的约束来防止过度分割或分割不足的问题,并保持了较快的分割速度.通过对工业机器人获取的阀门点云数据进行实验,证明了算法的有效性.     

异构网载波聚合系统基于干扰对齐的联合算法研究*

为了满足异构网络热点区域覆盖,同时解决由于低功率基站在高功率基站覆盖区域随意分布而带来的小区间干扰及系统容量速率受限问题,提出了一种载波聚合系统的联合小区选择、载波选择和干扰对齐算法。该方法是在载波公平比例准则下,动态的选择成员载波。为了进一步降低小区间干扰,设计了新的基于干扰对齐的用户小区选择算法。理论分析表明,联合优化算法问题可以分解成三个子问题进行优化求解处理。仿真结果表明,与调度复用因子为1的参考算法相比,设计的方案由于联合了小区选择和载波选择使得用户选择低功率节点作为服务小区的机会增多,提高了低功率节点小区容量,使系统的吞吐量得到提高。     

The application of a binary division procedure to the classification of forest subcategories using MODIS time-series data during 2000–2010 in China

Forests account for more than 23% of China’s total area. As the most important terrestrial ecosystem, forests have tremendous ecological value. However, it remains difficult to classify forest subcategories at the national scale. In this study, a newly developed binary division procedure was used to categorize forest areas, including their spatiotemporal dynamics, during the period 2000–2010. Time-series images acquired using the Moderate Resolution Imaging Spectroradiometer (MODIS), together with auxiliary data on land use, climate zoning, and topography, were utilized. Hierarchical classification and zoning were combined with remote-sensing auto-classification. Based on the forest extent mask, the state-level forest system was divided into four classes and 18 subcategories. The method achieved an acceptable overall accuracy of 73.1%, based on a comparison to the sample points of China’s fourth forest general survey data set. In 2010, the total forest area was 1.755 × 10⁶ km², and the total area of and shrubs was 4.885 × 10⁵ km². The total area of woodland increased by 2536.25 km² during the decade 2000–2010. The shrub subcategories exhibited almost no change during this time period; however, significant changes in forest area occurred in the mountainous region of Northeast China as well as in the hilly regions of Southern China. The main transformations took place in cold-temperate and temperate mountainous deciduous coniferous forest, subtropical deciduous coniferous forest, subtropical evergreen coniferous forest, and temperate and subtropical deciduous broadleaved mixed forests. The binary division procedure proposed herein can be used not only to rapidly classify more forest subcategories and monitor their dynamic changes, but also to improve the classification accuracy compared with global and national land-cover maps.     

Applying eco-visualisations of different interface formats to evoke sustainable behaviours towards household water saving

The shortage of water resources is a global issue. This study attempts to utilise eco-visualisation interface design to affect users’ water-usage behaviour. Three interface proposals were designed in this study: numeric, water droplet (abstract symbol), and swimming fish (animated image). These three different interface formats range from abstract to figurative and from neutral to affective. A total of 93 subjects were divided into three groups and randomly performed designated dishwashing tasks twice. One of the tasks was completed without the assistance of any interface, whereas the other involved applying one of the three interface formats with eco-visualisations. In this study, the Self-Assessment Manikin scales, the System Usability Scale, and the Questionnaires for User Interaction Satisfaction were used to measure the emotional dimensions and perceived usability and to record the differences in water usage volume. The results indicated that the emotional valence evoked by the animated image interface was significantly higher than that by the numeric interface. The effect of the numeric interface formats on the subjects focused on emotional arousal, whereas other interfaces emphasised emotional valence. With the aid of the eco-visualisations of interface design, the evoked emotional response and enhanced usability could help improve sustainable behaviours towards water saving.     

Users' psychological perception and perceived readability of wearable devices for elderly people

As the population of elderly people in society rises, the importance of technology to assist health management is growing with the demographic shift. Wearable personal computing has been the common solution proposed by related projects to fulfil the needs of elderly people. These add-on devices are attached to the users, and result in uneasiness or discomfort while wearing them in public areas. In this study, three common wearing positions – wrist, upper arm, and neck – were investigated in terms of psychological perception and perceived readability. Twenty-four Taiwanese participants in Miaoli area were asked to wear the designed prototypes for a certain time. The participants completed questionnaires and participated in an open-ended interview. Data of psychological perceptions, visibility, and readability about wearable devices were collected. The results evidenced that the personal attributes of gender, smart device user, and requirement for medical care affect the psychological perception and user attitudes. The statistical results indicated significant differences in elderly people's attitudes towards wearable devices attached to different parts of the body. The wrist was the most favourable location to attach a wearable device.     

基于K均值聚类和粒子群优化的多核SVM图像分割

图像分割是图像理解和计算机视觉的重要内容.针对单核SVM在进行图像分割过程中不能兼顾分割精度高和泛化性能好的问题,提出一种基于K均值聚类和优化多核SVM的图像分割算法.该算法首先运用K均值聚类算法自动选取训练样本,然后提取其颜色特征和纹理特征作为训练样本的特征属性,并使用其对构造的多核SVM分割模型进行训练,最后用粒子群优化算法对多核核参数、惩罚因子以及核权重系数联合寻优,使生成的多核SVM具有更好的分割性能.实验结果表明,本文方法在有效提取图像目标细节的同时,获得了更高的分割精度,与基于单核的SVM分割模型相比,具有更强的泛化能力.