Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every s...Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.展开更多
超声和漏磁无损检测方法是目前输油管道常用的安全检测方法,然而其检测数据庞大,必须对数据进行压缩。介绍了一种基于CTW(context tree weight)的无损压缩算法,该算法采用了新的更低冗余度的概率估算法,具有速度快和抗差错能力强等特点...超声和漏磁无损检测方法是目前输油管道常用的安全检测方法,然而其检测数据庞大,必须对数据进行压缩。介绍了一种基于CTW(context tree weight)的无损压缩算法,该算法采用了新的更低冗余度的概率估算法,具有速度快和抗差错能力强等特点,将该算法应用于输油管道超声和漏磁方法无损检测实验数据的无损压缩,得到了较高的压缩率,与LZW(lempel ziv welch)无损压缩算法相比获得了更高的压缩率。展开更多
随着Web 所拥有的信息量和信息种类的急剧增长,Web 站点挖掘对于自动实现特定主题的 Web 资源发现和分类具有重要的意义.然而现有的 Web 站点分类或挖掘算法在利用上下文语义信息、去除噪声信息以进一步提高分类准确率等方面还缺乏深入...随着Web 所拥有的信息量和信息种类的急剧增长,Web 站点挖掘对于自动实现特定主题的 Web 资源发现和分类具有重要的意义.然而现有的 Web 站点分类或挖掘算法在利用上下文语义信息、去除噪声信息以进一步提高分类准确率等方面还缺乏深入研究.从站点的采样尺寸、分析粒度和描述结构 3 个方面分析了设计高效的 Web 站点挖掘算法所需要解决的问题.在此基础上,提出了一种新的 Web 站点多粒度树描述模型,并描述了包括基于隐 Markov 树的两阶段分类算法、粒度间上下文融合算法、两阶段去噪程序以及基于熵的动态剪枝策略在内的多粒度 Web 站点挖掘算法.站点的多粒度描述方法及挖掘算法为多站点查询优化、Web 效用挖掘等的深入研究奠定了基础.实验表明,该算法相对于基线系统平均可以提高 16%的分类准确率,并减少了 34.5%的处理时间.展开更多
针对多级树集合分裂算法(Set Partitioning In H ierarchical Tree,SPIHT)复杂的特点,采用整数实现的提升格式代替了原来的小波变换,简化了计算过程。对小波系数采用基于块的结构划分,在频域重新建立空间方向树。根据块中相邻系数相关...针对多级树集合分裂算法(Set Partitioning In H ierarchical Tree,SPIHT)复杂的特点,采用整数实现的提升格式代替了原来的小波变换,简化了计算过程。对小波系数采用基于块的结构划分,在频域重新建立空间方向树。根据块中相邻系数相关性建立上下文模型,对输出信息进行自适应算术编码,提高了编码效率。实验表明,在相同的比特率条件下。展开更多
文摘Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.
文摘超声和漏磁无损检测方法是目前输油管道常用的安全检测方法,然而其检测数据庞大,必须对数据进行压缩。介绍了一种基于CTW(context tree weight)的无损压缩算法,该算法采用了新的更低冗余度的概率估算法,具有速度快和抗差错能力强等特点,将该算法应用于输油管道超声和漏磁方法无损检测实验数据的无损压缩,得到了较高的压缩率,与LZW(lempel ziv welch)无损压缩算法相比获得了更高的压缩率。
文摘随着Web 所拥有的信息量和信息种类的急剧增长,Web 站点挖掘对于自动实现特定主题的 Web 资源发现和分类具有重要的意义.然而现有的 Web 站点分类或挖掘算法在利用上下文语义信息、去除噪声信息以进一步提高分类准确率等方面还缺乏深入研究.从站点的采样尺寸、分析粒度和描述结构 3 个方面分析了设计高效的 Web 站点挖掘算法所需要解决的问题.在此基础上,提出了一种新的 Web 站点多粒度树描述模型,并描述了包括基于隐 Markov 树的两阶段分类算法、粒度间上下文融合算法、两阶段去噪程序以及基于熵的动态剪枝策略在内的多粒度 Web 站点挖掘算法.站点的多粒度描述方法及挖掘算法为多站点查询优化、Web 效用挖掘等的深入研究奠定了基础.实验表明,该算法相对于基线系统平均可以提高 16%的分类准确率,并减少了 34.5%的处理时间.
文摘针对多级树集合分裂算法(Set Partitioning In H ierarchical Tree,SPIHT)复杂的特点,采用整数实现的提升格式代替了原来的小波变换,简化了计算过程。对小波系数采用基于块的结构划分,在频域重新建立空间方向树。根据块中相邻系数相关性建立上下文模型,对输出信息进行自适应算术编码,提高了编码效率。实验表明,在相同的比特率条件下。
