A light source of multi-star simulator capable of background adjustment and magnitude control has been designed.Two integrating spheres are employed as the star-point light source and the background light source respe...A light source of multi-star simulator capable of background adjustment and magnitude control has been designed.Two integrating spheres are employed as the star-point light source and the background light source respectively.A beam splitter prism has been designed to serve as the beam combiner for the star-point and the background light sources,and a mathematical model has been constructed respectively to compute the light flux of the two integrating spheres.A magnitude testing system and a background testing system have been created using low-light illuminometer,luminance meter,and testing instruments to measure the star-point magnitude and the background luminance of the multi-star simulator.The test results suggest that the star-point magnitude is adjustable from0 to+5 m_v,with a simulation precision superior to ±0.026 m_v.The maximum background luminance is 3.8×10~5 cd·m^(-2),and the minimum background luminance is6.4×10^(-2)cd·m^(-2).The designed light source system can meet the requirements for simulating the stellar map with a sky background.展开更多
基于本地化差分隐私多关系表示上的Star-JOIN查询已得到研究者广泛关注.现有基于OLH机制与层次树结构的Star-JOIN查询算法存在根节点泄露隐私风险、τ-截断机制没有给出如何选择合适τ值等问题.针对现有算法存在的不足,提出一种有效且...基于本地化差分隐私多关系表示上的Star-JOIN查询已得到研究者广泛关注.现有基于OLH机制与层次树结构的Star-JOIN查询算法存在根节点泄露隐私风险、τ-截断机制没有给出如何选择合适τ值等问题.针对现有算法存在的不足,提出一种有效且满足本地化差分隐私的Star-JOIN查询算法LPRR-JOIN(longitudinal path random response for join).该算法充分利用层次树的纵向路径结构与GRR机制,设计一种纵向本地扰动算法LPRR,该算法以所有属性纵向路径上的节点组合作为扰动值域.每个用户把自身元组映射到相应节点组合中,再利用GRR机制对映射后的元组进行本地扰动.为了避免事实表上存在的频率攻击,LPRR-JOIN算法允许每个用户利用阈值τ本地截断自身元组个数,大于τ条元组删减、小于τ条元组补充.为了寻找合适的τ值,LPRR-JOIN算法利用τ-截断带来的偏差与扰动方差构造总体误差函数,通过优化误差目标函数获得τ值;其次结合用户分组策略获得τ值的总体分布,再利用中位数获得合适的τ值.LPRR-JOIN算法与现有算法在3种多关系数据集上进行比较,实验结果表明其响应查询算法优于同类算法.展开更多
基金Supported by Jilin Province Key Scientific and Technological Projects(20160204008GX)National Key Laboratory Fund Project(61420020210162002)Changchun University of Science and Technology Innovation Fund(XJJLG-2016-15)
文摘A light source of multi-star simulator capable of background adjustment and magnitude control has been designed.Two integrating spheres are employed as the star-point light source and the background light source respectively.A beam splitter prism has been designed to serve as the beam combiner for the star-point and the background light sources,and a mathematical model has been constructed respectively to compute the light flux of the two integrating spheres.A magnitude testing system and a background testing system have been created using low-light illuminometer,luminance meter,and testing instruments to measure the star-point magnitude and the background luminance of the multi-star simulator.The test results suggest that the star-point magnitude is adjustable from0 to+5 m_v,with a simulation precision superior to ±0.026 m_v.The maximum background luminance is 3.8×10~5 cd·m^(-2),and the minimum background luminance is6.4×10^(-2)cd·m^(-2).The designed light source system can meet the requirements for simulating the stellar map with a sky background.
文摘基于本地化差分隐私多关系表示上的Star-JOIN查询已得到研究者广泛关注.现有基于OLH机制与层次树结构的Star-JOIN查询算法存在根节点泄露隐私风险、τ-截断机制没有给出如何选择合适τ值等问题.针对现有算法存在的不足,提出一种有效且满足本地化差分隐私的Star-JOIN查询算法LPRR-JOIN(longitudinal path random response for join).该算法充分利用层次树的纵向路径结构与GRR机制,设计一种纵向本地扰动算法LPRR,该算法以所有属性纵向路径上的节点组合作为扰动值域.每个用户把自身元组映射到相应节点组合中,再利用GRR机制对映射后的元组进行本地扰动.为了避免事实表上存在的频率攻击,LPRR-JOIN算法允许每个用户利用阈值τ本地截断自身元组个数,大于τ条元组删减、小于τ条元组补充.为了寻找合适的τ值,LPRR-JOIN算法利用τ-截断带来的偏差与扰动方差构造总体误差函数,通过优化误差目标函数获得τ值;其次结合用户分组策略获得τ值的总体分布,再利用中位数获得合适的τ值.LPRR-JOIN算法与现有算法在3种多关系数据集上进行比较,实验结果表明其响应查询算法优于同类算法.
