基于干涉原理测量溶液浓度变化分布的实时系统仿真实现

实验利用数字全息干涉技术对电极反应过程中溶液浓度变化分布进行测量。运用基于直方图的自适应滤波方法和基于形态学滤波的固液界面提取方法,解决了每更换一次实验数据都要人工识别和更换滤波参数以及手动去除固侧干扰信息的难题,为实现从摄像机实时读取数据、实时处理、测量和观察提供了仿真依据。     

Efficient embedded wavelet codec based on list structure

A new efficient image codec called embedded wavelet coding based on list structure (EWCBL) is proposed in this paper. By combining the techniques of morphological representation and quadtree partitioning, EWCBL effectively exploits both within-subband clustering and cross-subband similarity of wavelet coefficients. Based on the list structure, a fine fractional bit-plane coding is employed to achieve excellent rate-distortion performance. The patterned morphological dilation is introduced to greatly reduce the redundant test operations. Experimental results show that the proposed EWCBL outperforms state-of-the-art embedded codecs for both lossy and lossless compression. Moreover, the good performance and features of embeddedness and scalability are achieved with relatively low complexity.     

基于SIP家庭网关和Web Service的智能家居系统

提出了一种将 SIP 家庭网关技术和 Web Service 技术相结合的智能家居系统的设计和实现方案,详细介绍了系统各功能模块,给出了在 PDA 上调用基于 SIP 家庭网关的 Web 服务来监控家中各电器状态的实现结果。该技术可以向用户提供智能家居管理、远程监控等具体服务。     

A multiperiod set covering location model for dynamic redeployment of ambulances

Emergency medical service (EMS) providers continually seek ways to improve system performance particularly the response time to incidents. The demand for ambulances fluctuate throughout the week, depending on the day of week, and even the time of day, therefore EMS operators can improve system performance by dynamic relocation/redeployment of ambulances in response to fluctuating demand patters. The objective of the model is to determine the minimum number of ambulances and their locations for each time cluster in which significant changes in demand pattern occur while meeting coverage requirement with a predetermined reliability. The model is further enhanced by calculating ambulance specific busy probabilities and validated by a comprehensive simulation model. Computational results on experimental data sets and data from an EMS agency are provided.     

Estimation of parameters of the Makeham distribution using the least squares method

The Makeham distribution has been used to describe human mortality and establish actuarial tables. The hazard function is defined by μ(t)=A+BC^t$\mu (t)=A+B{C}^t$, we use the least squares type estimation to estimate the parameters of Makeham distribution in this paper. Seven cases are considered, when A, B, C are known or unknown, respectively. Also, we evaluated the mean square errors of these estimators.     

Limits of Learning-Based Superresolution Algorithms

Learning-based superresolution (SR) is a popular SR technique that uses application dependent priors to infer the missing details in low resolution images (LRIs). However, their performance still deteriorates quickly when the magnification factor is only moderately large. This leads us to an important problem: “Do limits of learning-based SR algorithms exist?” This paper is the first attempt to shed some light on this problem when the SR algorithms are designed for general natural images. We first define an expected risk for the SR algorithms that is based on the root mean squared error between the superresolved images and the ground truth images. Then utilizing the statistics of general natural images, we derive a closed form estimate of the lower bound of the expected risk. The lower bound only involves the covariance matrix and the mean vector of the high resolution images (HRIs) and hence can be computed by sampling real images. We also investigate the sufficient number of samples to guarantee an accurate estimate of the lower bound. By computing the curve of the lower bound w.r.t. the magnification factor, we could estimate the limits of learning-based SR algorithms, at which the lower bound of the expected risk exceeds a relatively large threshold. We perform experiments to validate our theory. And based on our observations we conjecture that the limits may be independent of the size of either the LRIs or the HRIs.     

基于社会网络的聊天数据噪声过滤

聊天室中的聊天数据充斥着大量噪声,极大地降低了话题检测的监控效率。但聊天数据只有对话发出时间这一线索可供直接利用,因此噪声过滤是聊天室监控的一个难题。该文提出一种基于社会网络的聊天数据噪声过滤方法,通过分析聊天数据的时序关系,推断出聊天用户间的社会网络关系,根据社会网络蕴含的用户交流特点判断并过滤出噪声。实验证实了该方法能较准确地过滤出噪声,提高话题识别的准确率。     

基于PKI/PMI的安全Web数据交换

基于XML的数据交换是一种典型的Web应用,通过分析基于服务的数据交换数据,说明在该Web应用中,存在的安全问题和需求,架构一个基于PKI/PMI的安全Web数据交换平台,实现应用层的授权和安全访问控制,并应用在实际中.     

一种小型嵌入式Linux Boot Loader的设计与实现

提出了一种小型嵌入式Linux Boot Loader的设计方案,并详细介绍该方案在Arm-Linux平台上的实现过程.方案大大简化了特定应用平台下Linux Boot Loader的设计,并且大大减小了生成的可执行文件的大小,针对特定应用平台自行设计小型的Boot Loader具有一定的参考价值.     

Network traffic classification based on ensemble learning and co-training

Classification of network traffic is the essential step for many network researches. However,with the rapid evolution of Internet applications the effectiveness of the port-based or payload-based identifi-cation approaches has been greatly diminished in recent years. And many researchers begin to turn their attentions to an alternative machine learning based method. This paper presents a novel machine learning-based classification model,which combines ensemble learning paradigm with co-training tech-niques. Compared to previous approaches,most of which only employed single classifier,multiple clas-sifiers and semi-supervised learning are applied in our method and it mainly helps to overcome three shortcomings:limited flow accuracy rate,weak adaptability and huge demand of labeled training set. In this paper,statistical characteristics of IP flows are extracted from the packet level traces to establish the feature set,then the classification model is created and tested and the empirical results prove its feasibility and effectiveness.