Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solu...Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.展开更多
计算机技术和通信技术的共同发展,使得数据呈现指数大爆炸式的增长。数据中蕴含的巨大价值是有目共睹的。但是对数据集的肆意收集与分析,使用户的隐私数据处在被泄露的风险中。为保护用户的敏感数据的同时实现对基数查询的有效响应,提...计算机技术和通信技术的共同发展,使得数据呈现指数大爆炸式的增长。数据中蕴含的巨大价值是有目共睹的。但是对数据集的肆意收集与分析,使用户的隐私数据处在被泄露的风险中。为保护用户的敏感数据的同时实现对基数查询的有效响应,提出一种基于差分隐私的隐私保护算法BFRRCE(Bloom Filter Random Response for Cardinality Estimation)。首先对用户的数据利用Bloom Filter数据结构进行数据预处理,然后利用本地差分隐私的扰动算法对数据进行扰动,达到保护用户敏感数据的目的。展开更多
可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题,提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法,简称为AVL-Bl...可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题,提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法,简称为AVL-Bloom算法。首先,针对可变长地址灵活可变且无界的特点,利用多个片外哈希表分别存储前缀比特位数相同的路由条目及其下一跳信息,同时应用片上Bloom过滤器加速搜索可能匹配的路由前缀;其次,为了解决基于哈希技术的路由查找算法在查找最长前缀路由时需多次哈希对比的问题,引入AVL树技术,即通过AVL树组织每组路由前缀集合的Bloom过滤器及其哈希表,优化路由前缀长度的查询顺序,并减少哈希计算次数进而降低查询时间;最后,在3种不同的可变长地址数据集上将所提算法与METrie(Multi-Entrance-Trie)和COBF(Controlled prefix and One-hashing Bloom Filter)这两种传统路由查找算法进行对比实验。实验结果表明,AVL-Bloom算法的查询时间明显少于METrie和COBF算法,分别减少了将近83%和64%;同时,AVL-Bloom算法在路由表项数变化较大的情况下也能维持稳定的查找性能,适用于可变长地址的路由查找转发。展开更多
文摘Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.
文摘计算机技术和通信技术的共同发展,使得数据呈现指数大爆炸式的增长。数据中蕴含的巨大价值是有目共睹的。但是对数据集的肆意收集与分析,使用户的隐私数据处在被泄露的风险中。为保护用户的敏感数据的同时实现对基数查询的有效响应,提出一种基于差分隐私的隐私保护算法BFRRCE(Bloom Filter Random Response for Cardinality Estimation)。首先对用户的数据利用Bloom Filter数据结构进行数据预处理,然后利用本地差分隐私的扰动算法对数据进行扰动,达到保护用户敏感数据的目的。
文摘可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题,提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法,简称为AVL-Bloom算法。首先,针对可变长地址灵活可变且无界的特点,利用多个片外哈希表分别存储前缀比特位数相同的路由条目及其下一跳信息,同时应用片上Bloom过滤器加速搜索可能匹配的路由前缀;其次,为了解决基于哈希技术的路由查找算法在查找最长前缀路由时需多次哈希对比的问题,引入AVL树技术,即通过AVL树组织每组路由前缀集合的Bloom过滤器及其哈希表,优化路由前缀长度的查询顺序,并减少哈希计算次数进而降低查询时间;最后,在3种不同的可变长地址数据集上将所提算法与METrie(Multi-Entrance-Trie)和COBF(Controlled prefix and One-hashing Bloom Filter)这两种传统路由查找算法进行对比实验。实验结果表明,AVL-Bloom算法的查询时间明显少于METrie和COBF算法,分别减少了将近83%和64%;同时,AVL-Bloom算法在路由表项数变化较大的情况下也能维持稳定的查找性能,适用于可变长地址的路由查找转发。
