Loss-cone instabilities are studied for linear fusion devices. The gyro-kinetic equation for such a configuration is rigorously constructed in terms of action-angle variables by making use of canonical transformation....Loss-cone instabilities are studied for linear fusion devices. The gyro-kinetic equation for such a configuration is rigorously constructed in terms of action-angle variables by making use of canonical transformation. The dispersion relation, including for the first time, finite bounce frequency is obtained and numerically solved. The loss-cone modes are found near ion-cyclotron frequency. The growth rates are greatly reduced and approaching zero with increasing beta value. The results suggest that loss-cone instabilities are unlikely to be threatening to linear fusion devices since a new longitudinal invariant is found and gives a constraint which helps confinement.展开更多
The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism o...The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.展开更多
针对现有恶意域名检测方法对域名生成算法(domain generation algorithm, DGA)随机产生的恶意域名检测性能不高,且对由随机单词组成的恶意域名检测效果较差的问题,提出一种基于字符和词特征融合的恶意域名检测算法(cha-racter and word ...针对现有恶意域名检测方法对域名生成算法(domain generation algorithm, DGA)随机产生的恶意域名检测性能不高,且对由随机单词组成的恶意域名检测效果较差的问题,提出一种基于字符和词特征融合的恶意域名检测算法(cha-racter and word network, CWNet)。利用并行卷积神经网络分别提取域名中字符和词的特征;将两种特征进行拼接,构造成融合特征;利用Softmax函数实现合法域名与恶意域名的检测。实验结果表明,该算法可以提升对恶意域名的检测能力,对更具挑战性的恶意域名家族的检测准确率提升效果更为明显。展开更多
基金supported by the Natural Science Foundation for Young Scientists of China (No. 11605143)National Natural Science Foundation of China (Nos. 11575055,11261140327,11005035,11205053)+3 种基金the project,Plasma Confinement in the Advanced Magnetic Mirror (WX-2015-01-01)the Open Research Subject of the Key Laboratory of Advanced Computation in Xihua University (Nos. szjj2017-011 and szjj2017-012)the Young Scholarship Plan of Xihua University (No. 0220170201)the National Key Research and Development Program of China (No. 2017YFE0300405)
文摘Loss-cone instabilities are studied for linear fusion devices. The gyro-kinetic equation for such a configuration is rigorously constructed in terms of action-angle variables by making use of canonical transformation. The dispersion relation, including for the first time, finite bounce frequency is obtained and numerically solved. The loss-cone modes are found near ion-cyclotron frequency. The growth rates are greatly reduced and approaching zero with increasing beta value. The results suggest that loss-cone instabilities are unlikely to be threatening to linear fusion devices since a new longitudinal invariant is found and gives a constraint which helps confinement.
文摘The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.
文摘针对现有恶意域名检测方法对域名生成算法(domain generation algorithm, DGA)随机产生的恶意域名检测性能不高,且对由随机单词组成的恶意域名检测效果较差的问题,提出一种基于字符和词特征融合的恶意域名检测算法(cha-racter and word network, CWNet)。利用并行卷积神经网络分别提取域名中字符和词的特征;将两种特征进行拼接,构造成融合特征;利用Softmax函数实现合法域名与恶意域名的检测。实验结果表明,该算法可以提升对恶意域名的检测能力,对更具挑战性的恶意域名家族的检测准确率提升效果更为明显。
