Accelerator based synthesis of hydroxyapatite by MeV ion implantation

Accelerator based MeV ion implantation of Ca²⁺ and P²⁺ into the titanium substrate to form hydroxyapatite (HA) has been carried out. Calcium hydroxide was formed after heating the calcium implanted titanium in air at 80 °C for 3 h. Upon subsequent annealing for 5 min at 600 °C HA was formed on the surface. Penetration depth of the HA layer in this method is much higher as compared to keV ion implantation. By elemental analysis, Ca/P ratio of the HA was found to be 1.76 which is higher than the ideal 1.67. This higher Ca/P ratio is attributed to the higher penetration depth of the MeV technique used.     

Effects of electron irradiation on SiGe devices

The degradation and the recovery behavior of the device performance for SiGe diodes and p-MOSFETs irradiated by 2-MeV electrons are reported. For diodes, it is noted that both the reverse and forward current increase by irradiation. An interesting observation is that the forward current decreases after irradiation for a forward voltage larger than ~ 0.7 V. This reduction can be explained by an increased resistivity of the Si substrate. The degradation recovers by thermal annealing after irradiation. For a fluence of 1 × 10¹⁵ e/cm², the diode performance almost recovers to the initial condition after 250 °C annealing. For the transistors, after irradiation, a slight negative shift of the threshold voltage and a decrease of the drain current for input and output characteristics have been observed together with a decrease of hole mobility. This is mainly due to the increase of the threshold voltage induced by positive charge trapping in the gate oxide.     

Optical, electrical and structural characteristics of Al:ZnO thin films with various thicknesses deposited by DC sputtering at room temperature and annealed in air or vacuum

Transparent and conductive Al-doped ZnO (AZO) films have been grown with various thicknesses between 0.3 and 1.1 μm by magnetron sputtering at room temperature onto soda lime glass substrates. After deposition, the samples have been annealed at temperatures ranging from 150 to 450 °C in air or vacuum. The optical, electrical, and structural characteristics of the AZO coatings have been analyzed as a function of the film thickness and the annealing parameters by spectrophotometry, Hall effect measurements, and X-ray diffraction. As-grown layers are found polycrystalline, with hexagonal structure that shows some elongation of the unit cells along the c-axis, having visible transmittance ∼85-90% and resistivity ∼1.6-2.0 mΩ cm, both parameters slightly decreasing when the film thickness increases. Heating in air or vacuum produces further elongation of the crystalline lattice together with some increase of the visible transmittance and a decrease of the electrical resistance that depends on the heating temperature and atmosphere. The best characteristics have been obtained after treatment in vacuum at 350 °C, where the highest carrier concentrations are achieved, giving visible transmittance ∼90-95% and resistivity ∼0.8-0.9 mΩ cm for the AZO layers with various thicknesses. Some relationships between the analyzed properties have been established, showing the dependence of the lattice distortion, the band gap energy and the mobility on the carrier concentration.     

求解24数码问题的改进遗传退火算法

针对具有巨大搜索解空间的24数码问题,提出了一种基于改进遗传模拟退火算法的求解方法。依据问题特征,设计了个体编码方法、高效的适应度评价函数和遗传操作算子,通过在遗传算法中引入模拟退火的Boltzmann更新机制,克服了传统遗传算法易于过早收敛和易于“卡住”陷入局部极小的问题。仿真实验结果表明,提出的算法能够快速搜索到问题的解,算法对其他组合优化问题也具有应用价值。     

基于RSSI加权质心和GASA优化的WSN定位算法

针对无线传感器网络节点在自身定位中广泛存在较大的定位误差的问题,提出一种基于RSSI加权质心和GASA优化的无线传感器网络定位算法。该算法假设无线传感器网络中存在一定比例的位置已知的锚节点,利用RSSI加权质心算法计算未知节点与锚节点间的距离,建立以未知节点位置为参数的数学模型,用GASA优化算法计算最优解从而获得未知节点的位置,实现未知节点自身的定位。仿真实验的结果表明,当锚节点个数为30,算法的平均定位误差在10%以内,比RSSI加权质心算法降低了10%~15.5%左右,并且随着节点个数的增加平均定位误差降低。     

夜间不定车速环境下的优化调度模型分析

在车辆调度的过程中,夜间环境下对车辆行驶状况的影响因素较多,车速不定,车辆调度的非线性将大大增加,传统的车辆调度模型应用到夜间环境下时,存在调度误差大,耗时严重的问题。提出基于模拟退火-遗传算法的夜间不定车速环境下的调度方法。利用模拟退火算法处理非线性问题的优势,结合遗传算法的优化求解功能,建立基于模拟退火-遗传算法的车辆优化调度模型,针对该模型求解,获取车辆调度的最优值,实现夜间不定车速环境下的优化调度。实验结果表明,利用GA-SA进行夜间不定车速环境下的优化调度,能够缩短调度时间,缓解车辆运行过程中的拥堵,极大提高了车辆运行速度,满足车辆调度的实际需求。     

维修时点预测的动态车间调度问题

针对制造业中生产计划的不确定问题,提出一种维修时点预测与自适应的遗传模拟退火算法相结合的优化调度方法。该方法首先利用差分自回归移动平均模型预测设备未来的故障率,然后借助电气设备的威布尔（Weibull）分布模型逆向求出设备未来故障发生时刻,最后将此作为约束条件,利用自适应的遗传模拟退火算法解决传统的生产调度问题。结合工厂实际情况,主要分析了设备有无维修的随机调度问题,以最小化最大完工时间为目标,获取每一个任务的调度计划以及每一台设备的维修时点,确定出最佳调度方案。实验表明自适应的遗传模拟退火算法的性能较好。在河北某工厂的生产车间中,设备在运行调度方法后三个月的平均故障率比运行前相对降低了3.46%。     

Mass production of magnetocaloric LaFeMnSiB alloys with hydrogenation

LaFe_(11.39)Mn_(0.35)Si_(1.26)B_(0.1)Hxalloys were prepared by hydrogenation.Samples were annealed at 1343Kfor30-90 hto form the NaZn13 phase.La-rich andα-Fe secondary phases were also detected.Saturated hydrogenation at 553 Kand 0.15 MPa of H_2 pressure for 5hwas employed to improve the Curie temperature of the alloys to 279 K.The maximum magnetic entropy change,relative cooling power,and adiabatic temperature change of LaFe_(11.39)Mn_(0.35)Si_(1.26)B_(0.1)H_x annealed at 1343 Kfor 90hafter hydrogen absorption are 6.38J/(kg·K)(magnetic changesμ0ΔH =1.65T),100.1J/kg(μ0ΔH =1.65T),and 2.2 K(μ0ΔH =1.48T),respectively.Although the maximum magnetic entropy change of the LaFe_(11.39)Mn_(0.35)Si_(1.26)B_(0.1)H_x alloys is lower than those of similar alloys with high purity raw materials,the relative cooling power is nearly the same.The effect of impurities of the raw materials used was also discussed.It is assumed that the impurity of 0.2wt.% Al is responsible for the reduced entropy change of the resulted alloys.The LaFe_(11.39)Mn_(0.35)Si_(1.26)B_(0.1)H_x alloys prepared by this method could be a low cost alternative material for room temperature magnetic cooling applications.     

相关向量机超参数优化的网络安全态势预测

针对当前网络安全态势预测方法存在的过学习与欠学习、自由参数多、预测精度不高等问题,提出使用一种改进模拟退火法优化的相关向量机模型(PSA-RVM)来解决网络安全态势预测问题。在预测过程中,首先对网络安全态势样本数据进行相空间重构形成训练样本集;然后,利用Powell算法改进模拟退火(PSA)法,并将相关向量机(RVM)嵌入到PSA算法的目标函数计算过程中,优化RVM超参数,以得到学习能力、预测精度提升的网络安全态势预测模型。仿真实例表明,所提方法具有较高的预测精度,平均相对误差(MAPE)和均方根误差(RMSE)分别为0.39256和0.01261,均优于Elman和PSO-SVR模型;所提方法能够较好地刻画网络安全态势的变化趋势,有助于网络管理人员把握未来网络安全态势发展趋势,从而提前主动采取相应的网络防御措施。     

基于支持向量数据描述的报警融合方法

报警融合是入侵检测系统中很重要的一个环节,然而不同的攻击类型具有不同的数据特点,统一的无差别的处理方法势必会存在缺陷。提出了采用基于支持向量数据描述的报警融合算法,并且结合模拟退火的思想,根据不同的攻击类型,选择适合它的属性和核参数,剔除冗余特征,避免样本不均衡产生的影响,通过局部检测、数据融合以及最终的决策分析,提高了报警的检测率,降低了漏报率。通过KDD99数据集对提出的方法进行了验证。