蓝牙通讯技术在嵌入式产品中的应用具有极为广阔的前景,微软公司的Windows CE．NET已经成为了主流的嵌入式操作系统之一。论文给出了在Visual Studio 2005中利用托管码并分别采用P／Invoke技术、微软蓝牙嵌入式工具包、OpenNETCF类库和...蓝牙通讯技术在嵌入式产品中的应用具有极为广阔的前景,微软公司的Windows CE．NET已经成为了主流的嵌入式操作系统之一。论文给出了在Visual Studio 2005中利用托管码并分别采用P／Invoke技术、微软蓝牙嵌入式工具包、OpenNETCF类库和利用本机码来开发Windows CE．NET操作系统下蓝牙通讯模块的几种方法,并在其中对P／Invoke技术、托管码开发、本机码开发等几个关键技术进行了阐述。最后给出了利用托管码和本机码开发蓝牙通讯模块这几种方法的优劣比较和分析。其内容对于在Windows mobile平台下开发蓝牙设备间的通讯具有一定实用价值。展开更多
Group distance coding is suitable for secret communication covered by printed documents. However there is no effective method against it. The study found that the hiding method will make group distances of text lines ...Group distance coding is suitable for secret communication covered by printed documents. However there is no effective method against it. The study found that the hiding method will make group distances of text lines coverage on specified values, and make variances of group distances among N-Window text lines become small. Inspired by the discovery, the research brings out a Support Vector Machine （SVM） based steganalysis algorithm. To avoid the disturbance of large difference among words length from same line, the research only reserves samples whose occurrence-frequencies are ± 10dB of the maximum frequency. The results show that the correct rate of the SVM classifier is higher than 90%.展开更多
基金the National Natural Science Foundation of China under Grant No.61170269,No.61170272,No.61202082,No.61003285,and the Fundamental Research Funds for the Central Universities under Grant No.BUPT2013RC0308,No.BUPT2013RC0311
文摘Group distance coding is suitable for secret communication covered by printed documents. However there is no effective method against it. The study found that the hiding method will make group distances of text lines coverage on specified values, and make variances of group distances among N-Window text lines become small. Inspired by the discovery, the research brings out a Support Vector Machine （SVM） based steganalysis algorithm. To avoid the disturbance of large difference among words length from same line, the research only reserves samples whose occurrence-frequencies are ± 10dB of the maximum frequency. The results show that the correct rate of the SVM classifier is higher than 90%.
